python /home/admin/mtr/script_for_cron.py -j default -m 20 -a 'python3 ~/workarea/git/Velours/python/prod/datou.py -j batch_current -C 2524174' -s traitement_4234 -M 0 -S 0 -U 100,80,95 import MySQLdb succeeded Import error (python version) ['/Users/moilerat/Documents/Fotonower/install/caffe/distribute/python', '/home/admin/workarea/git/Velours/python/prod', '/home/admin/workarea/install/darknet', '/home/admin/workarea/git/Velours/python', '/home/admin/workarea/install/caffe_frcnn_python3/py-faster-rcnn/caffe-fast-rcnn/python', '/home/admin/mtr/.credentials', '/home/admin/workarea/install/caffe/python', '/home/admin/workarea/install/caffe_frcnn/py-faster-rcnn/tools', '/home/admin/workarea/git/fotonowerpip', '/home/admin/workarea/install/segment-anything', '/home/admin/workarea/git/pyfvs', '/home/admin/workarea/git/apy', '/usr/lib/python38.zip', '/usr/lib/python3.8', '/usr/lib/python3.8/lib-dynload', '/home/admin/.local/lib/python3.8/site-packages', '/usr/local/lib/python3.8/dist-packages', '/usr/lib/python3/dist-packages'] process id : 2473413 load datou : 0 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : step 0 init_dummy_multi_datou is not linked in the step_by_step architecture ! WARNING : step 1294 init_dummy_multi_datou is not linked in the step_by_step architecture ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! DataTypes for each output/input checked ! Unexpected type for variable list_input_json ERROR or WARNING : can't parse json string Expecting value: line 1 column 1 (char 0) Tried to parse : (photo_id, hashtag_id, score_max) was removed should we ? (x0, y0, x1, y1) was removed should we ? chemin de la photo was removed should we ? (photo_id, hashtag_id, score_max) was removed should we ? (x0, y0, x1, y1) was removed should we ? chemin de la photo was removed should we ? load thcls load pdts Running datou job : batch_current TODO datou_current to load to do maybe to take outside batchDatouExec updating current state to 1 list_input_json: [] Current got : datou_id : 4234, datou_cur_ids : ['2524174'] with mtr_portfolio_ids : ['20029321'] and first list_photo_ids : [] new path : /proc/2473413/ Inside batchDatouExec : verbose : 0 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! List Step Type Loaded in datou : mask_detect, brightness, blur_detection, rle_unique_nms_with_priority, crop_condition, thcl, ventilate_hashtags_in_portfolio, final, velours_tree, send_mail_cod, split_time_score over limit max, limiting to limit_max 21 list_input_json : [] origin We have 1 , WARNING: data may be incomplete, need to offset and complete ! BFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 21 ; length of list_pids : 21 ; length of list_args : 21 time to download the photos : 3.664161443710327 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : 0 number of steps : 11 step1:mask_detect Wed Feb 12 08:47:48 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Beginning of datou step mask_detect ! save_polygon : True begin detect begin to check gpu status inside check gpu memory l 3637 free memory gpu now : 10998 max_wait_temp : 1 max_wait : 0 gpu_flag : 0 2025-02-12 08:47:51.095779: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2025-02-12 08:47:51.127032: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493065000 Hz 2025-02-12 08:47:51.129210: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f3578000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-02-12 08:47:51.129271: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-02-12 08:47:51.133241: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-02-12 08:47:51.449900: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x25905f80 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-02-12 08:47:51.449962: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-02-12 08:47:51.451020: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-02-12 08:47:51.451394: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-12 08:47:51.453565: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-02-12 08:47:51.455672: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-02-12 08:47:51.456020: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-02-12 08:47:51.458290: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-02-12 08:47:51.459372: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-02-12 08:47:51.464122: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-02-12 08:47:51.465669: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-02-12 08:47:51.465741: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-12 08:47:51.466496: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-02-12 08:47:51.466512: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-02-12 08:47:51.466521: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-02-12 08:47:51.467909: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 10193 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:41:00.0, compute capability: 7.5) WARNING:tensorflow:From /home/admin/workarea/git/Velours/python/mtr/mask_rcnn/mask_detection.py:69: The name tf.keras.backend.set_session is deprecated. Please use tf.compat.v1.keras.backend.set_session instead. 2025-02-12 08:47:51.723041: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-02-12 08:47:51.723129: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-12 08:47:51.723150: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-02-12 08:47:51.723182: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-02-12 08:47:51.723201: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-02-12 08:47:51.723220: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-02-12 08:47:51.723237: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-02-12 08:47:51.723255: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-02-12 08:47:51.724831: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-02-12 08:47:51.726163: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-02-12 08:47:51.726240: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-12 08:47:51.726264: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-02-12 08:47:51.726285: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-02-12 08:47:51.726305: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-02-12 08:47:51.726325: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-02-12 08:47:51.726345: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-02-12 08:47:51.726365: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-02-12 08:47:51.728040: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-02-12 08:47:51.728073: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-02-12 08:47:51.728083: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-02-12 08:47:51.728091: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-02-12 08:47:51.729587: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 10193 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:41:00.0, compute capability: 7.5) Using TensorFlow backend. WARNING:tensorflow:From /home/admin/workarea/install/Mask_RCNN/model.py:396: calling crop_and_resize_v1 (from tensorflow.python.ops.image_ops_impl) with box_ind is deprecated and will be removed in a future version. Instructions for updating: box_ind is deprecated, use box_indices instead WARNING:tensorflow:From /home/admin/workarea/install/Mask_RCNN/model.py:703: to_int32 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.cast` instead. WARNING:tensorflow:From /home/admin/workarea/install/Mask_RCNN/model.py:729: to_float (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.cast` instead. Inside mask_sub_process Inside mask_detect About to load cache.load_thcl_param To do loadFromThcl(), then load ParamDescType : thcl2847 thcls : [{'id': 2847, 'mtr_user_id': 31, 'name': 'learn_RUBBIA_REFUS_AMIENS_23', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'photo_desc_type': 5275, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'}] thcl {'id': 2847, 'mtr_user_id': 31, 'name': 'learn_RUBBIA_REFUS_AMIENS_23', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'photo_desc_type': 5275, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'} Update svm_hashtag_type_desc : 5275 FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (5275, 'learn_RUBBIA_REFUS_AMIENS_23', 16384, 25088, 'learn_RUBBIA_REFUS_AMIENS_23', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 1, datetime.datetime(2021, 4, 23, 14, 19, 39), datetime.datetime(2021, 4, 23, 14, 19, 39)) {'thcl': {'id': 2847, 'mtr_user_id': 31, 'name': 'learn_RUBBIA_REFUS_AMIENS_23', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'photo_desc_type': 5275, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'}, 'list_hashtags': ['background', 'papier', 'carton', 'metal', 'pet_clair', 'autre', 'pehd', 'pet_fonce', 'environnement'], 'list_hashtags_csv': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'svm_hashtag_type_desc': 5275, 'photo_desc_type': 5275, 'pb_hashtag_id_or_classifier': 0} list_class_names : ['background', 'papier', 'carton', 'metal', 'pet_clair', 'autre', 'pehd', 'pet_fonce', 'environnement'] Configurations: BACKBONE resnet101 BACKBONE_SHAPES [[160 160] [ 80 80] [ 40 40] [ 20 20] [ 10 10]] BACKBONE_STRIDES [4, 8, 16, 32, 64] BATCH_SIZE 1 BBOX_STD_DEV [0.1 0.1 0.2 0.2] DETECTION_MAX_INSTANCES 100 DETECTION_MIN_CONFIDENCE 0.3 DETECTION_NMS_THRESHOLD 0.3 GPU_COUNT 1 IMAGES_PER_GPU 1 IMAGE_MAX_DIM 640 IMAGE_MIN_DIM 640 IMAGE_PADDING True IMAGE_SHAPE [640 640 3] LEARNING_MOMENTUM 0.9 LEARNING_RATE 0.001 LOSS_WEIGHTS {'rpn_class_loss': 1.0, 'rpn_bbox_loss': 1.0, 'mrcnn_class_loss': 1.0, 'mrcnn_bbox_loss': 1.0, 'mrcnn_mask_loss': 1.0} MASK_POOL_SIZE 14 MASK_SHAPE [28, 28] MAX_GT_INSTANCES 100 MEAN_PIXEL [123.7 116.8 103.9] MINI_MASK_SHAPE (56, 56) NAME learn_RUBBIA_REFUS_AMIENS_23 NUM_CLASSES 9 POOL_SIZE 7 POST_NMS_ROIS_INFERENCE 1000 POST_NMS_ROIS_TRAINING 2000 ROI_POSITIVE_RATIO 0.33 RPN_ANCHOR_RATIOS [0.5, 1, 2] RPN_ANCHOR_SCALES (16, 32, 64, 128, 256) RPN_ANCHOR_STRIDE 1 RPN_BBOX_STD_DEV [0.1 0.1 0.2 0.2] RPN_NMS_THRESHOLD 0.7 RPN_TRAIN_ANCHORS_PER_IMAGE 256 STEPS_PER_EPOCH 1000 TRAIN_ROIS_PER_IMAGE 200 USE_MINI_MASK True USE_RPN_ROIS True VALIDATION_STEPS 50 WEIGHT_DECAY 0.0001 model_param file didn't exist model_name : learn_RUBBIA_REFUS_AMIENS_23 model_type : mask_rcnn list file need : ['mask_model.h5'] file exist in s3 : ['mask_model.h5'] file manque in s3 : [] 2025-02-12 08:47:58.477021: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-02-12 08:47:58.626381: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 local folder : /data/models_weight/learn_RUBBIA_REFUS_AMIENS_23 /data/models_weight/learn_RUBBIA_REFUS_AMIENS_23/mask_model.h5 size_local : 256009536 size in s3 : 256009536 create time local : 2021-08-09 09:43:22 create time in s3 : 2021-08-06 18:54:04 mask_model.h5 already exist and didn't need to update list_images length : 21 NEW PHOTO pour l'instant on ne peut pas sauvegarder la photo dans les tile Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -117.86016 max: 145.43203 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 5 time for calcul the mask position with numpy : 7.033348083496094e-05 nb_pixel_total : 317 time to create 1 rle with old method : 0.0006279945373535156 length of segment : 37 time for calcul the mask position with numpy : 6.008148193359375e-05 nb_pixel_total : 1042 time to create 1 rle with old method : 0.001825094223022461 length of segment : 35 time for calcul the mask position with numpy : 3.910064697265625e-05 nb_pixel_total : 17 time to create 1 rle with old method : 6.341934204101562e-05 length of segment : 9 time for calcul the mask position with numpy : 5.793571472167969e-05 nb_pixel_total : 991 time to create 1 rle with old method : 0.0017786026000976562 length of segment : 31 time for calcul the mask position with numpy : 7.128715515136719e-05 nb_pixel_total : 1488 time to create 1 rle with old method : 0.008478879928588867 length of segment : 67 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -118.68828 max: 150.70547 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 6 time for calcul the mask position with numpy : 5.6743621826171875e-05 nb_pixel_total : 975 time to create 1 rle with old method : 0.0012218952178955078 length of segment : 48 time for calcul the mask position with numpy : 4.38690185546875e-05 nb_pixel_total : 647 time to create 1 rle with old method : 0.0009634494781494141 length of segment : 33 time for calcul the mask position with numpy : 0.0002605915069580078 nb_pixel_total : 11084 time to create 1 rle with old method : 0.012769699096679688 length of segment : 426 time for calcul the mask position with numpy : 4.4345855712890625e-05 nb_pixel_total : 575 time to create 1 rle with old method : 0.0007355213165283203 length of segment : 33 time for calcul the mask position with numpy : 3.457069396972656e-05 nb_pixel_total : 523 time to create 1 rle with old method : 0.0006513595581054688 length of segment : 39 time for calcul the mask position with numpy : 3.528594970703125e-05 nb_pixel_total : 243 time to create 1 rle with old method : 0.00032591819763183594 length of segment : 41 Processing 1 images image shape: (400, 400, 3) min: 26.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -81.29766 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 1 time for calcul the mask position with numpy : 0.00010156631469726562 nb_pixel_total : 6245 time to create 1 rle with old method : 0.007488727569580078 length of segment : 102 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -111.57500 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 4 time for calcul the mask position with numpy : 0.00011754035949707031 nb_pixel_total : 6366 time to create 1 rle with old method : 0.007310152053833008 length of segment : 119 time for calcul the mask position with numpy : 0.0001068115234375 nb_pixel_total : 4328 time to create 1 rle with old method : 0.004954338073730469 length of segment : 187 time for calcul the mask position with numpy : 3.5762786865234375e-05 nb_pixel_total : 231 time to create 1 rle with old method : 0.0003247261047363281 length of segment : 23 time for calcul the mask position with numpy : 2.9802322387695312e-05 nb_pixel_total : 114 time to create 1 rle with old method : 0.0001773834228515625 length of segment : 16 Processing 1 images image shape: (400, 320, 3) min: 0.00000 max: 243.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 98.28359 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 4 time for calcul the mask position with numpy : 9.465217590332031e-05 nb_pixel_total : 532 time to create 1 rle with old method : 0.0012035369873046875 length of segment : 21 time for calcul the mask position with numpy : 7.081031799316406e-05 nb_pixel_total : 246 time to create 1 rle with old method : 0.0005633831024169922 length of segment : 19 time for calcul the mask position with numpy : 6.961822509765625e-05 nb_pixel_total : 374 time to create 1 rle with old method : 0.000820159912109375 length of segment : 25 time for calcul the mask position with numpy : 0.0007319450378417969 nb_pixel_total : 41059 time to create 1 rle with old method : 0.07149815559387207 length of segment : 236 Processing 1 images image shape: (400, 400, 3) min: 24.00000 max: 197.00000 molded_images shape: (1, 640, 640, 3) min: -79.82500 max: 80.52969 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 1 time for calcul the mask position with numpy : 0.0011627674102783203 nb_pixel_total : 148847 time to create 1 rle with old method : 0.15642786026000977 length of segment : 393 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -119.38359 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 11 time for calcul the mask position with numpy : 3.886222839355469e-05 nb_pixel_total : 196 time to create 1 rle with old method : 0.0003190040588378906 length of segment : 10 time for calcul the mask position with numpy : 4.5299530029296875e-05 nb_pixel_total : 1394 time to create 1 rle with old method : 0.0017595291137695312 length of segment : 53 time for calcul the mask position with numpy : 3.314018249511719e-05 nb_pixel_total : 252 time to create 1 rle with old method : 0.0003662109375 length of segment : 19 time for calcul the mask position with numpy : 4.124641418457031e-05 nb_pixel_total : 714 time to create 1 rle with old method : 0.0010204315185546875 length of segment : 27 time for calcul the mask position with numpy : 2.8848648071289062e-05 nb_pixel_total : 180 time to create 1 rle with old method : 0.00024247169494628906 length of segment : 17 time for calcul the mask position with numpy : 3.361701965332031e-05 nb_pixel_total : 526 time to create 1 rle with old method : 0.0006732940673828125 length of segment : 31 time for calcul the mask position with numpy : 2.8133392333984375e-05 nb_pixel_total : 101 time to create 1 rle with old method : 0.00016760826110839844 length of segment : 9 time for calcul the mask position with numpy : 3.0517578125e-05 nb_pixel_total : 275 time to create 1 rle with old method : 0.0004279613494873047 length of segment : 13 time for calcul the mask position with numpy : 3.147125244140625e-05 nb_pixel_total : 480 time to create 1 rle with old method : 0.0005848407745361328 length of segment : 22 time for calcul the mask position with numpy : 6.508827209472656e-05 nb_pixel_total : 2156 time to create 1 rle with old method : 0.0027518272399902344 length of segment : 47 time for calcul the mask position with numpy : 7.343292236328125e-05 nb_pixel_total : 3256 time to create 1 rle with old method : 0.003798246383666992 length of segment : 70 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -119.47734 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 8 time for calcul the mask position with numpy : 6.127357482910156e-05 nb_pixel_total : 1914 time to create 1 rle with old method : 0.002358675003051758 length of segment : 32 time for calcul the mask position with numpy : 3.170967102050781e-05 nb_pixel_total : 82 time to create 1 rle with old method : 0.00015473365783691406 length of segment : 8 time for calcul the mask position with numpy : 0.00023674964904785156 nb_pixel_total : 13617 time to create 1 rle with old method : 0.015408992767333984 length of segment : 135 time for calcul the mask position with numpy : 5.316734313964844e-05 nb_pixel_total : 1595 time to create 1 rle with old method : 0.0019605159759521484 length of segment : 46 time for calcul the mask position with numpy : 2.8848648071289062e-05 nb_pixel_total : 144 time to create 1 rle with old method : 0.0002028942108154297 length of segment : 13 time for calcul the mask position with numpy : 4.100799560546875e-05 nb_pixel_total : 1078 time to create 1 rle with old method : 0.0013263225555419922 length of segment : 32 time for calcul the mask position with numpy : 3.981590270996094e-05 nb_pixel_total : 413 time to create 1 rle with old method : 0.0005500316619873047 length of segment : 53 time for calcul the mask position with numpy : 8.344650268554688e-05 nb_pixel_total : 2928 time to create 1 rle with old method : 0.003392457962036133 length of segment : 44 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -117.01641 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 10 time for calcul the mask position with numpy : 6.604194641113281e-05 nb_pixel_total : 1287 time to create 1 rle with old method : 0.0017704963684082031 length of segment : 42 time for calcul the mask position with numpy : 3.457069396972656e-05 nb_pixel_total : 204 time to create 1 rle with old method : 0.0003077983856201172 length of segment : 16 time for calcul the mask position with numpy : 2.6941299438476562e-05 nb_pixel_total : 31 time to create 1 rle with old method : 6.222724914550781e-05 length of segment : 8 time for calcul the mask position with numpy : 7.271766662597656e-05 nb_pixel_total : 1369 time to create 1 rle with old method : 0.0017824172973632812 length of segment : 113 time for calcul the mask position with numpy : 0.00019097328186035156 nb_pixel_total : 1984 time to create 1 rle with old method : 0.0024847984313964844 length of segment : 64 time for calcul the mask position with numpy : 5.14984130859375e-05 nb_pixel_total : 821 time to create 1 rle with old method : 0.0010941028594970703 length of segment : 38 time for calcul the mask position with numpy : 6.794929504394531e-05 nb_pixel_total : 1226 time to create 1 rle with old method : 0.0016798973083496094 length of segment : 103 time for calcul the mask position with numpy : 5.030632019042969e-05 nb_pixel_total : 971 time to create 1 rle with old method : 0.0012590885162353516 length of segment : 39 time for calcul the mask position with numpy : 5.14984130859375e-05 nb_pixel_total : 1206 time to create 1 rle with old method : 0.0021905899047851562 length of segment : 42 time for calcul the mask position with numpy : 6.151199340820312e-05 nb_pixel_total : 768 time to create 1 rle with old method : 0.0010764598846435547 length of segment : 38 Processing 1 images image shape: (400, 320, 3) min: 0.00000 max: 254.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 114.73672 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 10 time for calcul the mask position with numpy : 0.0001068115234375 nb_pixel_total : 1412 time to create 1 rle with old method : 0.0027565956115722656 length of segment : 67 time for calcul the mask position with numpy : 0.00015306472778320312 nb_pixel_total : 3203 time to create 1 rle with old method : 0.004060029983520508 length of segment : 189 time for calcul the mask position with numpy : 3.9577484130859375e-05 nb_pixel_total : 205 time to create 1 rle with old method : 0.0003032684326171875 length of segment : 31 time for calcul the mask position with numpy : 3.1948089599609375e-05 nb_pixel_total : 132 time to create 1 rle with old method : 0.00020647048950195312 length of segment : 20 time for calcul the mask position with numpy : 3.647804260253906e-05 nb_pixel_total : 273 time to create 1 rle with old method : 0.0003898143768310547 length of segment : 37 time for calcul the mask position with numpy : 4.982948303222656e-05 nb_pixel_total : 726 time to create 1 rle with old method : 0.0009806156158447266 length of segment : 34 time for calcul the mask position with numpy : 7.486343383789062e-05 nb_pixel_total : 1389 time to create 1 rle with old method : 0.0017445087432861328 length of segment : 70 time for calcul the mask position with numpy : 4.38690185546875e-05 nb_pixel_total : 390 time to create 1 rle with old method : 0.0005185604095458984 length of segment : 51 time for calcul the mask position with numpy : 3.170967102050781e-05 nb_pixel_total : 260 time to create 1 rle with old method : 0.0003311634063720703 length of segment : 32 time for calcul the mask position with numpy : 4.506111145019531e-05 nb_pixel_total : 747 time to create 1 rle with old method : 0.0009567737579345703 length of segment : 43 Processing 1 images image shape: (280, 400, 3) min: 25.00000 max: 201.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 81.70781 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 1 time for calcul the mask position with numpy : 0.0011091232299804688 nb_pixel_total : 105596 time to create 1 rle with old method : 0.11414361000061035 length of segment : 281 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 143.54141 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 11 time for calcul the mask position with numpy : 5.6743621826171875e-05 nb_pixel_total : 1548 time to create 1 rle with old method : 0.0019974708557128906 length of segment : 41 time for calcul the mask position with numpy : 3.4332275390625e-05 nb_pixel_total : 264 time to create 1 rle with old method : 0.00040984153747558594 length of segment : 14 time for calcul the mask position with numpy : 6.461143493652344e-05 nb_pixel_total : 2593 time to create 1 rle with old method : 0.003017902374267578 length of segment : 75 time for calcul the mask position with numpy : 6.151199340820312e-05 nb_pixel_total : 1632 time to create 1 rle with old method : 0.001990795135498047 length of segment : 61 time for calcul the mask position with numpy : 3.4809112548828125e-05 nb_pixel_total : 433 time to create 1 rle with old method : 0.0005304813385009766 length of segment : 46 time for calcul the mask position with numpy : 3.4332275390625e-05 nb_pixel_total : 302 time to create 1 rle with old method : 0.00043201446533203125 length of segment : 25 time for calcul the mask position with numpy : 0.00012373924255371094 nb_pixel_total : 7754 time to create 1 rle with old method : 0.009092569351196289 length of segment : 77 time for calcul the mask position with numpy : 6.771087646484375e-05 nb_pixel_total : 2871 time to create 1 rle with old method : 0.0032062530517578125 length of segment : 62 time for calcul the mask position with numpy : 3.337860107421875e-05 nb_pixel_total : 174 time to create 1 rle with old method : 0.0002970695495605469 length of segment : 15 time for calcul the mask position with numpy : 4.029273986816406e-05 nb_pixel_total : 854 time to create 1 rle with old method : 0.0010900497436523438 length of segment : 35 time for calcul the mask position with numpy : 3.361701965332031e-05 nb_pixel_total : 130 time to create 1 rle with old method : 0.0001933574676513672 length of segment : 32 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 235.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 118.18594 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 4 time for calcul the mask position with numpy : 4.1961669921875e-05 nb_pixel_total : 467 time to create 1 rle with old method : 0.0006349086761474609 length of segment : 18 time for calcul the mask position with numpy : 3.266334533691406e-05 nb_pixel_total : 271 time to create 1 rle with old method : 0.00038886070251464844 length of segment : 17 time for calcul the mask position with numpy : 2.9087066650390625e-05 nb_pixel_total : 176 time to create 1 rle with old method : 0.00024437904357910156 length of segment : 21 time for calcul the mask position with numpy : 2.9802322387695312e-05 nb_pixel_total : 123 time to create 1 rle with old method : 0.00020551681518554688 length of segment : 13 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 150.06484 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 6 time for calcul the mask position with numpy : 4.506111145019531e-05 nb_pixel_total : 377 time to create 1 rle with old method : 0.0005137920379638672 length of segment : 29 time for calcul the mask position with numpy : 4.935264587402344e-05 nb_pixel_total : 846 time to create 1 rle with old method : 0.0011353492736816406 length of segment : 66 time for calcul the mask position with numpy : 3.4332275390625e-05 nb_pixel_total : 169 time to create 1 rle with old method : 0.0002510547637939453 length of segment : 23 time for calcul the mask position with numpy : 7.367134094238281e-05 nb_pixel_total : 3208 time to create 1 rle with old method : 0.003796100616455078 length of segment : 87 time for calcul the mask position with numpy : 3.4332275390625e-05 nb_pixel_total : 107 time to create 1 rle with old method : 0.00015425682067871094 length of segment : 27 time for calcul the mask position with numpy : 8.58306884765625e-05 nb_pixel_total : 3487 time to create 1 rle with old method : 0.004346609115600586 length of segment : 91 Processing 1 images image shape: (280, 320, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 131.88750 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 2 time for calcul the mask position with numpy : 4.100799560546875e-05 nb_pixel_total : 332 time to create 1 rle with old method : 0.0004684925079345703 length of segment : 17 time for calcul the mask position with numpy : 3.5762786865234375e-05 nb_pixel_total : 388 time to create 1 rle with old method : 0.0005691051483154297 length of segment : 25 NEW PHOTO pour l'instant on ne peut pas sauvegarder la photo dans les tile Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -116.78984 max: 145.73672 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 7 time for calcul the mask position with numpy : 4.863739013671875e-05 nb_pixel_total : 1010 time to create 1 rle with old method : 0.0013034343719482422 length of segment : 36 time for calcul the mask position with numpy : 4.482269287109375e-05 nb_pixel_total : 1029 time to create 1 rle with old method : 0.001455068588256836 length of segment : 31 time for calcul the mask position with numpy : 2.9087066650390625e-05 nb_pixel_total : 53 time to create 1 rle with old method : 9.846687316894531e-05 length of segment : 14 time for calcul the mask position with numpy : 3.409385681152344e-05 nb_pixel_total : 337 time to create 1 rle with old method : 0.0004553794860839844 length of segment : 33 time for calcul the mask position with numpy : 3.337860107421875e-05 nb_pixel_total : 266 time to create 1 rle with old method : 0.00039649009704589844 length of segment : 31 time for calcul the mask position with numpy : 3.147125244140625e-05 nb_pixel_total : 57 time to create 1 rle with old method : 0.00010251998901367188 length of segment : 20 time for calcul the mask position with numpy : 5.078315734863281e-05 nb_pixel_total : 1709 time to create 1 rle with old method : 0.002397298812866211 length of segment : 50 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -117.63750 max: 150.92422 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 7 time for calcul the mask position with numpy : 6.389617919921875e-05 nb_pixel_total : 938 time to create 1 rle with old method : 0.001493215560913086 length of segment : 46 time for calcul the mask position with numpy : 3.9577484130859375e-05 nb_pixel_total : 571 time to create 1 rle with old method : 0.0007712841033935547 length of segment : 22 time for calcul the mask position with numpy : 4.506111145019531e-05 nb_pixel_total : 868 time to create 1 rle with old method : 0.0012180805206298828 length of segment : 38 time for calcul the mask position with numpy : 3.0279159545898438e-05 nb_pixel_total : 146 time to create 1 rle with old method : 0.00022745132446289062 length of segment : 23 time for calcul the mask position with numpy : 0.00019025802612304688 nb_pixel_total : 2195 time to create 1 rle with old method : 0.0025377273559570312 length of segment : 145 time for calcul the mask position with numpy : 3.790855407714844e-05 nb_pixel_total : 222 time to create 1 rle with old method : 0.0003008842468261719 length of segment : 39 time for calcul the mask position with numpy : 3.123283386230469e-05 nb_pixel_total : 114 time to create 1 rle with old method : 0.00018739700317382812 length of segment : 19 Processing 1 images image shape: (400, 400, 3) min: 26.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -91.86016 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 1 time for calcul the mask position with numpy : 6.079673767089844e-05 nb_pixel_total : 422 time to create 1 rle with old method : 0.0009925365447998047 length of segment : 15 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -112.62969 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 6 time for calcul the mask position with numpy : 0.00015115737915039062 nb_pixel_total : 7652 time to create 1 rle with old method : 0.010784626007080078 length of segment : 143 time for calcul the mask position with numpy : 0.0001571178436279297 nb_pixel_total : 3718 time to create 1 rle with old method : 0.00456547737121582 length of segment : 184 time for calcul the mask position with numpy : 4.673004150390625e-05 nb_pixel_total : 263 time to create 1 rle with old method : 0.00048804283142089844 length of segment : 17 time for calcul the mask position with numpy : 3.218650817871094e-05 nb_pixel_total : 99 time to create 1 rle with old method : 0.0001659393310546875 length of segment : 14 time for calcul the mask position with numpy : 3.4809112548828125e-05 nb_pixel_total : 278 time to create 1 rle with old method : 0.0003948211669921875 length of segment : 25 time for calcul the mask position with numpy : 3.0279159545898438e-05 nb_pixel_total : 90 time to create 1 rle with old method : 0.0002052783966064453 length of segment : 13 Processing 1 images image shape: (400, 320, 3) min: 0.00000 max: 249.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 121.33437 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 1 time for calcul the mask position with numpy : 6.29425048828125e-05 nb_pixel_total : 524 time to create 1 rle with old method : 0.0012657642364501953 length of segment : 21 Processing 1 images image shape: (400, 400, 3) min: 20.00000 max: 202.00000 molded_images shape: (1, 640, 640, 3) min: -83.27422 max: 83.13906 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 1 time for calcul the mask position with numpy : 0.001871347427368164 nb_pixel_total : 150031 time to create 1 rle with new method : 0.0028040409088134766 length of segment : 391 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -118.92656 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 11 time for calcul the mask position with numpy : 6.103515625e-05 nb_pixel_total : 1337 time to create 1 rle with old method : 0.0016326904296875 length of segment : 52 time for calcul the mask position with numpy : 3.695487976074219e-05 nb_pixel_total : 178 time to create 1 rle with old method : 0.0002930164337158203 length of segment : 9 time for calcul the mask position with numpy : 3.409385681152344e-05 nb_pixel_total : 243 time to create 1 rle with old method : 0.0003657341003417969 length of segment : 19 time for calcul the mask position with numpy : 3.886222839355469e-05 nb_pixel_total : 522 time to create 1 rle with old method : 0.0006999969482421875 length of segment : 30 time for calcul the mask position with numpy : 3.1948089599609375e-05 nb_pixel_total : 215 time to create 1 rle with old method : 0.0002894401550292969 length of segment : 25 time for calcul the mask position with numpy : 4.00543212890625e-05 nb_pixel_total : 366 time to create 1 rle with old method : 0.0005753040313720703 length of segment : 18 time for calcul the mask position with numpy : 4.220008850097656e-05 nb_pixel_total : 550 time to create 1 rle with old method : 0.0007691383361816406 length of segment : 24 time for calcul the mask position with numpy : 0.00013065338134765625 nb_pixel_total : 5951 time to create 1 rle with old method : 0.007296323776245117 length of segment : 71 time for calcul the mask position with numpy : 5.125999450683594e-05 nb_pixel_total : 346 time to create 1 rle with old method : 0.0005156993865966797 length of segment : 20 time for calcul the mask position with numpy : 4.5299530029296875e-05 nb_pixel_total : 1013 time to create 1 rle with old method : 0.0012807846069335938 length of segment : 28 time for calcul the mask position with numpy : 7.343292236328125e-05 nb_pixel_total : 1118 time to create 1 rle with old method : 0.0018928050994873047 length of segment : 29 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -116.98125 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 6 time for calcul the mask position with numpy : 4.9114227294921875e-05 nb_pixel_total : 75 time to create 1 rle with old method : 0.00019073486328125 length of segment : 7 time for calcul the mask position with numpy : 6.222724914550781e-05 nb_pixel_total : 1550 time to create 1 rle with old method : 0.002633810043334961 length of segment : 44 time for calcul the mask position with numpy : 4.220008850097656e-05 nb_pixel_total : 154 time to create 1 rle with old method : 0.0003323554992675781 length of segment : 13 time for calcul the mask position with numpy : 6.961822509765625e-05 nb_pixel_total : 1809 time to create 1 rle with old method : 0.0033533573150634766 length of segment : 29 time for calcul the mask position with numpy : 0.0003266334533691406 nb_pixel_total : 13451 time to create 1 rle with old method : 0.022305965423583984 length of segment : 127 time for calcul the mask position with numpy : 5.2928924560546875e-05 nb_pixel_total : 635 time to create 1 rle with old method : 0.0008594989776611328 length of segment : 29 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -116.52422 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 8 time for calcul the mask position with numpy : 4.57763671875e-05 nb_pixel_total : 180 time to create 1 rle with old method : 0.0002837181091308594 length of segment : 17 time for calcul the mask position with numpy : 3.218650817871094e-05 nb_pixel_total : 150 time to create 1 rle with old method : 0.0002338886260986328 length of segment : 14 time for calcul the mask position with numpy : 2.956390380859375e-05 nb_pixel_total : 35 time to create 1 rle with old method : 7.987022399902344e-05 length of segment : 8 time for calcul the mask position with numpy : 5.6743621826171875e-05 nb_pixel_total : 1165 time to create 1 rle with old method : 0.0016491413116455078 length of segment : 41 time for calcul the mask position with numpy : 4.3392181396484375e-05 nb_pixel_total : 799 time to create 1 rle with old method : 0.0010459423065185547 length of segment : 37 time for calcul the mask position with numpy : 7.462501525878906e-05 nb_pixel_total : 1327 time to create 1 rle with old method : 0.0017197132110595703 length of segment : 113 time for calcul the mask position with numpy : 3.981590270996094e-05 nb_pixel_total : 763 time to create 1 rle with old method : 0.000988006591796875 length of segment : 37 time for calcul the mask position with numpy : 6.842613220214844e-05 nb_pixel_total : 1290 time to create 1 rle with old method : 0.0016698837280273438 length of segment : 102 Processing 1 images image shape: (400, 320, 3) min: 0.00000 max: 251.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 118.11562 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 7 time for calcul the mask position with numpy : 7.891654968261719e-05 nb_pixel_total : 1723 time to create 1 rle with old method : 0.002174854278564453 length of segment : 84 time for calcul the mask position with numpy : 0.00016045570373535156 nb_pixel_total : 3142 time to create 1 rle with old method : 0.0038025379180908203 length of segment : 190 time for calcul the mask position with numpy : 5.0067901611328125e-05 nb_pixel_total : 774 time to create 1 rle with old method : 0.0010199546813964844 length of segment : 30 time for calcul the mask position with numpy : 7.605552673339844e-05 nb_pixel_total : 1653 time to create 1 rle with old method : 0.0022733211517333984 length of segment : 89 time for calcul the mask position with numpy : 3.409385681152344e-05 nb_pixel_total : 116 time to create 1 rle with old method : 0.00018787384033203125 length of segment : 18 time for calcul the mask position with numpy : 3.0040740966796875e-05 nb_pixel_total : 95 time to create 1 rle with old method : 0.0001518726348876953 length of segment : 15 time for calcul the mask position with numpy : 4.1961669921875e-05 nb_pixel_total : 738 time to create 1 rle with old method : 0.0009706020355224609 length of segment : 41 Processing 1 images image shape: (280, 400, 3) min: 25.00000 max: 216.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 97.52187 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 1 time for calcul the mask position with numpy : 0.0012106895446777344 nb_pixel_total : 106311 time to create 1 rle with old method : 0.12927889823913574 length of segment : 279 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 142.33828 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 8 time for calcul the mask position with numpy : 4.601478576660156e-05 nb_pixel_total : 350 time to create 1 rle with old method : 0.0005471706390380859 length of segment : 28 time for calcul the mask position with numpy : 6.318092346191406e-05 nb_pixel_total : 1666 time to create 1 rle with old method : 0.0021402835845947266 length of segment : 43 time for calcul the mask position with numpy : 3.3855438232421875e-05 nb_pixel_total : 165 time to create 1 rle with old method : 0.0002868175506591797 length of segment : 11 time for calcul the mask position with numpy : 4.839897155761719e-05 nb_pixel_total : 999 time to create 1 rle with old method : 0.0013887882232666016 length of segment : 37 time for calcul the mask position with numpy : 4.696846008300781e-05 nb_pixel_total : 295 time to create 1 rle with old method : 0.0004787445068359375 length of segment : 17 time for calcul the mask position with numpy : 4.696846008300781e-05 nb_pixel_total : 456 time to create 1 rle with old method : 0.0005803108215332031 length of segment : 43 time for calcul the mask position with numpy : 0.00018596649169921875 nb_pixel_total : 7309 time to create 1 rle with old method : 0.009404659271240234 length of segment : 152 time for calcul the mask position with numpy : 0.0001671314239501953 nb_pixel_total : 7414 time to create 1 rle with old method : 0.00947713851928711 length of segment : 77 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 223.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 106.07656 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 4 time for calcul the mask position with numpy : 4.220008850097656e-05 nb_pixel_total : 181 time to create 1 rle with old method : 0.0002770423889160156 length of segment : 21 time for calcul the mask position with numpy : 3.743171691894531e-05 nb_pixel_total : 413 time to create 1 rle with old method : 0.0005788803100585938 length of segment : 26 time for calcul the mask position with numpy : 3.5762786865234375e-05 nb_pixel_total : 348 time to create 1 rle with old method : 0.0006320476531982422 length of segment : 19 time for calcul the mask position with numpy : 3.1948089599609375e-05 nb_pixel_total : 128 time to create 1 rle with old method : 0.00020241737365722656 length of segment : 18 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 150.12344 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 7 time for calcul the mask position with numpy : 4.4345855712890625e-05 nb_pixel_total : 358 time to create 1 rle with old method : 0.0004954338073730469 length of segment : 28 time for calcul the mask position with numpy : 3.457069396972656e-05 nb_pixel_total : 197 time to create 1 rle with old method : 0.00028705596923828125 length of segment : 26 time for calcul the mask position with numpy : 5.078315734863281e-05 nb_pixel_total : 369 time to create 1 rle with old method : 0.0006215572357177734 length of segment : 77 time for calcul the mask position with numpy : 3.361701965332031e-05 nb_pixel_total : 125 time to create 1 rle with old method : 0.0001804828643798828 length of segment : 29 length of segment : 0 time for calcul the mask position with numpy : 6.29425048828125e-05 nb_pixel_total : 2361 time to create 1 rle with old method : 0.0030367374420166016 length of segment : 73 time for calcul the mask position with numpy : 7.62939453125e-05 nb_pixel_total : 2657 time to create 1 rle with old method : 0.0035305023193359375 length of segment : 98 Processing 1 images image shape: (280, 320, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 132.01250 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 3 time for calcul the mask position with numpy : 5.125999450683594e-05 nb_pixel_total : 326 time to create 1 rle with old method : 0.0004780292510986328 length of segment : 17 time for calcul the mask position with numpy : 3.8623809814453125e-05 nb_pixel_total : 393 time to create 1 rle with old method : 0.0006010532379150391 length of segment : 24 time for calcul the mask position with numpy : 4.649162292480469e-05 nb_pixel_total : 286 time to create 1 rle with old method : 0.0004353523254394531 length of segment : 54 NEW PHOTO pour l'instant on ne peut pas sauvegarder la photo dans les tile Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -116.45000 max: 145.73672 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 4 time for calcul the mask position with numpy : 5.5789947509765625e-05 nb_pixel_total : 924 time to create 1 rle with old method : 0.0012295246124267578 length of segment : 40 time for calcul the mask position with numpy : 3.647804260253906e-05 nb_pixel_total : 305 time to create 1 rle with old method : 0.00045013427734375 length of segment : 37 time for calcul the mask position with numpy : 4.38690185546875e-05 nb_pixel_total : 1031 time to create 1 rle with old method : 0.0014102458953857422 length of segment : 39 time for calcul the mask position with numpy : 3.123283386230469e-05 nb_pixel_total : 27 time to create 1 rle with old method : 6.29425048828125e-05 length of segment : 9 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -118.24297 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 6 time for calcul the mask position with numpy : 5.435943603515625e-05 nb_pixel_total : 773 time to create 1 rle with old method : 0.0011134147644042969 length of segment : 32 time for calcul the mask position with numpy : 4.839897155761719e-05 nb_pixel_total : 968 time to create 1 rle with old method : 0.0012595653533935547 length of segment : 48 time for calcul the mask position with numpy : 4.363059997558594e-05 nb_pixel_total : 550 time to create 1 rle with old method : 0.0008170604705810547 length of segment : 51 time for calcul the mask position with numpy : 3.170967102050781e-05 nb_pixel_total : 60 time to create 1 rle with old method : 0.00013399124145507812 length of segment : 6 time for calcul the mask position with numpy : 0.00026226043701171875 nb_pixel_total : 1487 time to create 1 rle with old method : 0.001934051513671875 length of segment : 127 time for calcul the mask position with numpy : 4.220008850097656e-05 nb_pixel_total : 688 time to create 1 rle with old method : 0.0009071826934814453 length of segment : 36 Processing 1 images image shape: (400, 400, 3) min: 32.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -91.55547 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 1 time for calcul the mask position with numpy : 6.198883056640625e-05 nb_pixel_total : 498 time to create 1 rle with old method : 0.0008373260498046875 length of segment : 15 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -116.78203 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 4 time for calcul the mask position with numpy : 0.00012445449829101562 nb_pixel_total : 5473 time to create 1 rle with old method : 0.006600856781005859 length of segment : 141 time for calcul the mask position with numpy : 0.00010132789611816406 nb_pixel_total : 3444 time to create 1 rle with old method : 0.004139900207519531 length of segment : 165 time for calcul the mask position with numpy : 3.3855438232421875e-05 nb_pixel_total : 66 time to create 1 rle with old method : 0.00013065338134765625 length of segment : 8 time for calcul the mask position with numpy : 3.314018249511719e-05 nb_pixel_total : 123 time to create 1 rle with old method : 0.0002110004425048828 length of segment : 18 Processing 1 images image shape: (400, 320, 3) min: 0.00000 max: 252.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 123.22891 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 1 time for calcul the mask position with numpy : 4.982948303222656e-05 nb_pixel_total : 625 time to create 1 rle with old method : 0.0008647441864013672 length of segment : 22 Processing 1 images image shape: (400, 400, 3) min: 19.00000 max: 197.00000 molded_images shape: (1, 640, 640, 3) min: -85.82109 max: 81.35781 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 0 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -120.45000 max: 149.48672 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 9 time for calcul the mask position with numpy : 4.76837158203125e-05 nb_pixel_total : 1035 time to create 1 rle with old method : 0.0012712478637695312 length of segment : 57 time for calcul the mask position with numpy : 3.266334533691406e-05 nb_pixel_total : 292 time to create 1 rle with old method : 0.0005025863647460938 length of segment : 20 time for calcul the mask position with numpy : 2.9325485229492188e-05 nb_pixel_total : 193 time to create 1 rle with old method : 0.0003008842468261719 length of segment : 10 time for calcul the mask position with numpy : 0.00010824203491210938 nb_pixel_total : 4819 time to create 1 rle with old method : 0.005495548248291016 length of segment : 91 time for calcul the mask position with numpy : 3.62396240234375e-05 nb_pixel_total : 504 time to create 1 rle with old method : 0.0006206035614013672 length of segment : 31 time for calcul the mask position with numpy : 7.510185241699219e-05 nb_pixel_total : 40 time to create 1 rle with old method : 0.00010967254638671875 length of segment : 18 time for calcul the mask position with numpy : 4.38690185546875e-05 nb_pixel_total : 1011 time to create 1 rle with old method : 0.0014328956604003906 length of segment : 34 time for calcul the mask position with numpy : 4.1484832763671875e-05 nb_pixel_total : 1057 time to create 1 rle with old method : 0.0013332366943359375 length of segment : 30 time for calcul the mask position with numpy : 3.457069396972656e-05 nb_pixel_total : 155 time to create 1 rle with old method : 0.00029397010803222656 length of segment : 20 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -117.70781 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 8 time for calcul the mask position with numpy : 3.5762786865234375e-05 nb_pixel_total : 97 time to create 1 rle with old method : 0.00017189979553222656 length of segment : 7 time for calcul the mask position with numpy : 5.555152893066406e-05 nb_pixel_total : 1666 time to create 1 rle with old method : 0.0022270679473876953 length of segment : 24 time for calcul the mask position with numpy : 0.00021266937255859375 nb_pixel_total : 13669 time to create 1 rle with old method : 0.01579880714416504 length of segment : 122 time for calcul the mask position with numpy : 4.315376281738281e-05 nb_pixel_total : 223 time to create 1 rle with old method : 0.00032019615173339844 length of segment : 37 time for calcul the mask position with numpy : 5.459785461425781e-05 nb_pixel_total : 1098 time to create 1 rle with old method : 0.0013458728790283203 length of segment : 53 time for calcul the mask position with numpy : 4.696846008300781e-05 nb_pixel_total : 135 time to create 1 rle with old method : 0.0002913475036621094 length of segment : 13 time for calcul the mask position with numpy : 4.029273986816406e-05 nb_pixel_total : 692 time to create 1 rle with old method : 0.0007946491241455078 length of segment : 31 time for calcul the mask position with numpy : 4.38690185546875e-05 nb_pixel_total : 553 time to create 1 rle with old method : 0.0008745193481445312 length of segment : 23 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -112.55156 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 9 time for calcul the mask position with numpy : 3.552436828613281e-05 nb_pixel_total : 205 time to create 1 rle with old method : 0.0002818107604980469 length of segment : 16 time for calcul the mask position with numpy : 4.1484832763671875e-05 nb_pixel_total : 829 time to create 1 rle with old method : 0.0010335445404052734 length of segment : 37 time for calcul the mask position with numpy : 5.602836608886719e-05 nb_pixel_total : 1493 time to create 1 rle with old method : 0.0018870830535888672 length of segment : 43 time for calcul the mask position with numpy : 3.314018249511719e-05 nb_pixel_total : 34 time to create 1 rle with old method : 7.891654968261719e-05 length of segment : 8 time for calcul the mask position with numpy : 4.1961669921875e-05 nb_pixel_total : 1028 time to create 1 rle with old method : 0.0012657642364501953 length of segment : 39 time for calcul the mask position with numpy : 4.4345855712890625e-05 nb_pixel_total : 1204 time to create 1 rle with old method : 0.0014150142669677734 length of segment : 42 time for calcul the mask position with numpy : 3.123283386230469e-05 nb_pixel_total : 125 time to create 1 rle with old method : 0.00021123886108398438 length of segment : 16 time for calcul the mask position with numpy : 5.6743621826171875e-05 nb_pixel_total : 1193 time to create 1 rle with old method : 0.0014224052429199219 length of segment : 108 time for calcul the mask position with numpy : 6.0558319091796875e-05 nb_pixel_total : 1167 time to create 1 rle with old method : 0.0015435218811035156 length of segment : 104 Processing 1 images image shape: (400, 320, 3) min: 0.00000 max: 242.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 115.91250 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 9 time for calcul the mask position with numpy : 6.818771362304688e-05 nb_pixel_total : 1255 time to create 1 rle with old method : 0.0015757083892822266 length of segment : 117 time for calcul the mask position with numpy : 5.340576171875e-05 nb_pixel_total : 182 time to create 1 rle with old method : 0.00037789344787597656 length of segment : 30 time for calcul the mask position with numpy : 0.0002429485321044922 nb_pixel_total : 4011 time to create 1 rle with old method : 0.005496501922607422 length of segment : 210 time for calcul the mask position with numpy : 4.124641418457031e-05 nb_pixel_total : 66 time to create 1 rle with old method : 0.00011849403381347656 length of segment : 11 time for calcul the mask position with numpy : 3.5762786865234375e-05 nb_pixel_total : 337 time to create 1 rle with old method : 0.0004515647888183594 length of segment : 38 time for calcul the mask position with numpy : 3.790855407714844e-05 nb_pixel_total : 395 time to create 1 rle with old method : 0.0005538463592529297 length of segment : 43 time for calcul the mask position with numpy : 5.793571472167969e-05 nb_pixel_total : 758 time to create 1 rle with old method : 0.0010504722595214844 length of segment : 33 time for calcul the mask position with numpy : 7.009506225585938e-05 nb_pixel_total : 1589 time to create 1 rle with old method : 0.0020678043365478516 length of segment : 114 time for calcul the mask position with numpy : 4.696846008300781e-05 nb_pixel_total : 655 time to create 1 rle with old method : 0.0008878707885742188 length of segment : 41 Processing 1 images image shape: (280, 400, 3) min: 28.00000 max: 204.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 78.40078 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 1 time for calcul the mask position with numpy : 0.00098419189453125 nb_pixel_total : 106502 time to create 1 rle with old method : 0.14131617546081543 length of segment : 281 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 138.50625 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 9 time for calcul the mask position with numpy : 4.1961669921875e-05 nb_pixel_total : 239 time to create 1 rle with old method : 0.00037288665771484375 length of segment : 12 time for calcul the mask position with numpy : 4.100799560546875e-05 nb_pixel_total : 499 time to create 1 rle with old method : 0.0006325244903564453 length of segment : 49 time for calcul the mask position with numpy : 3.266334533691406e-05 nb_pixel_total : 205 time to create 1 rle with old method : 0.00029969215393066406 length of segment : 18 time for calcul the mask position with numpy : 7.033348083496094e-05 nb_pixel_total : 1643 time to create 1 rle with old method : 0.0020868778228759766 length of segment : 42 time for calcul the mask position with numpy : 4.1484832763671875e-05 nb_pixel_total : 859 time to create 1 rle with old method : 0.001157999038696289 length of segment : 34 time for calcul the mask position with numpy : 6.580352783203125e-05 nb_pixel_total : 2400 time to create 1 rle with old method : 0.0028984546661376953 length of segment : 70 time for calcul the mask position with numpy : 7.224082946777344e-05 nb_pixel_total : 2587 time to create 1 rle with old method : 0.005202770233154297 length of segment : 57 time for calcul the mask position with numpy : 0.00018548965454101562 nb_pixel_total : 7578 time to create 1 rle with old method : 0.009164810180664062 length of segment : 77 time for calcul the mask position with numpy : 8.821487426757812e-05 nb_pixel_total : 3847 time to create 1 rle with old method : 0.004559755325317383 length of segment : 135 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 222.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 100.87734 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 3 time for calcul the mask position with numpy : 3.814697265625e-05 nb_pixel_total : 115 time to create 1 rle with old method : 0.00018215179443359375 length of segment : 18 time for calcul the mask position with numpy : 4.6253204345703125e-05 nb_pixel_total : 453 time to create 1 rle with old method : 0.0006976127624511719 length of segment : 25 time for calcul the mask position with numpy : 4.6253204345703125e-05 nb_pixel_total : 381 time to create 1 rle with old method : 0.0006306171417236328 length of segment : 16 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 150.24062 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 8 time for calcul the mask position with numpy : 0.00013303756713867188 nb_pixel_total : 612 time to create 1 rle with old method : 0.00106048583984375 length of segment : 54 time for calcul the mask position with numpy : 3.814697265625e-05 nb_pixel_total : 124 time to create 1 rle with old method : 0.00018525123596191406 length of segment : 27 time for calcul the mask position with numpy : 3.24249267578125e-05 nb_pixel_total : 195 time to create 1 rle with old method : 0.0002720355987548828 length of segment : 22 time for calcul the mask position with numpy : 8.487701416015625e-05 nb_pixel_total : 3517 time to create 1 rle with old method : 0.004098415374755859 length of segment : 94 time for calcul the mask position with numpy : 4.553794860839844e-05 nb_pixel_total : 125 time to create 1 rle with old method : 0.00023555755615234375 length of segment : 15 time for calcul the mask position with numpy : 4.0531158447265625e-05 nb_pixel_total : 170 time to create 1 rle with old method : 0.0002872943878173828 length of segment : 13 time for calcul the mask position with numpy : 5.173683166503906e-05 nb_pixel_total : 532 time to create 1 rle with old method : 0.0008161067962646484 length of segment : 36 time for calcul the mask position with numpy : 4.172325134277344e-05 nb_pixel_total : 2 time to create 1 rle with old method : 2.5510787963867188e-05 length of segment : 2 Processing 1 images image shape: (280, 320, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 131.76250 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 2 time for calcul the mask position with numpy : 3.695487976074219e-05 nb_pixel_total : 402 time to create 1 rle with old method : 0.0005342960357666016 length of segment : 25 time for calcul the mask position with numpy : 3.552436828613281e-05 nb_pixel_total : 327 time to create 1 rle with old method : 0.00046753883361816406 length of segment : 17 NEW PHOTO pour l'instant on ne peut pas sauvegarder la photo dans les tile Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -116.56719 max: 144.96328 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 5 time for calcul the mask position with numpy : 3.337860107421875e-05 nb_pixel_total : 8 time to create 1 rle with old method : 3.790855407714844e-05 length of segment : 4 time for calcul the mask position with numpy : 3.337860107421875e-05 nb_pixel_total : 262 time to create 1 rle with old method : 0.0003612041473388672 length of segment : 32 time for calcul the mask position with numpy : 4.172325134277344e-05 nb_pixel_total : 974 time to create 1 rle with old method : 0.0013241767883300781 length of segment : 41 time for calcul the mask position with numpy : 4.5299530029296875e-05 nb_pixel_total : 958 time to create 1 rle with old method : 0.0012509822845458984 length of segment : 43 length of segment : 0 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -118.62578 max: 151.04141 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 2 time for calcul the mask position with numpy : 0.00027823448181152344 nb_pixel_total : 13391 time to create 1 rle with old method : 0.015094518661499023 length of segment : 515 time for calcul the mask position with numpy : 7.343292236328125e-05 nb_pixel_total : 219 time to create 1 rle with old method : 0.0003204345703125 length of segment : 34 Processing 1 images image shape: (400, 400, 3) min: 31.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -89.27031 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 2 time for calcul the mask position with numpy : 0.0001399517059326172 nb_pixel_total : 2600 time to create 1 rle with old method : 0.004052162170410156 length of segment : 125 time for calcul the mask position with numpy : 5.793571472167969e-05 nb_pixel_total : 398 time to create 1 rle with old method : 0.0008027553558349609 length of segment : 13 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -112.64531 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 6 time for calcul the mask position with numpy : 0.0001876354217529297 nb_pixel_total : 7921 time to create 1 rle with old method : 0.00959467887878418 length of segment : 151 time for calcul the mask position with numpy : 0.0001246929168701172 nb_pixel_total : 4126 time to create 1 rle with old method : 0.004934787750244141 length of segment : 186 time for calcul the mask position with numpy : 3.838539123535156e-05 nb_pixel_total : 201 time to create 1 rle with old method : 0.00028395652770996094 length of segment : 23 time for calcul the mask position with numpy : 3.0994415283203125e-05 nb_pixel_total : 99 time to create 1 rle with old method : 0.00016617774963378906 length of segment : 15 time for calcul the mask position with numpy : 3.981590270996094e-05 nb_pixel_total : 338 time to create 1 rle with old method : 0.0005939006805419922 length of segment : 20 time for calcul the mask position with numpy : 5.030632019042969e-05 nb_pixel_total : 1203 time to create 1 rle with old method : 0.0015604496002197266 length of segment : 71 Processing 1 images image shape: (400, 320, 3) min: 0.00000 max: 239.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 110.34609 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 3 time for calcul the mask position with numpy : 5.14984130859375e-05 nb_pixel_total : 618 time to create 1 rle with old method : 0.00112152099609375 length of segment : 24 time for calcul the mask position with numpy : 4.673004150390625e-05 nb_pixel_total : 1213 time to create 1 rle with old method : 0.0016431808471679688 length of segment : 36 time for calcul the mask position with numpy : 5.3882598876953125e-05 nb_pixel_total : 219 time to create 1 rle with old method : 0.0005590915679931641 length of segment : 17 Processing 1 images image shape: (400, 400, 3) min: 24.00000 max: 200.00000 molded_images shape: (1, 640, 640, 3) min: -82.18047 max: 82.09219 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 0 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -120.29766 max: 149.96328 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 11 time for calcul the mask position with numpy : 5.626678466796875e-05 nb_pixel_total : 1278 time to create 1 rle with old method : 0.0016584396362304688 length of segment : 50 time for calcul the mask position with numpy : 3.24249267578125e-05 nb_pixel_total : 190 time to create 1 rle with old method : 0.0003154277801513672 length of segment : 9 time for calcul the mask position with numpy : 3.1948089599609375e-05 nb_pixel_total : 228 time to create 1 rle with old method : 0.0003581047058105469 length of segment : 18 time for calcul the mask position with numpy : 3.719329833984375e-05 nb_pixel_total : 964 time to create 1 rle with old method : 0.001237630844116211 length of segment : 27 time for calcul the mask position with numpy : 0.000102996826171875 nb_pixel_total : 3892 time to create 1 rle with old method : 0.00474238395690918 length of segment : 103 time for calcul the mask position with numpy : 3.24249267578125e-05 nb_pixel_total : 250 time to create 1 rle with old method : 0.00036597251892089844 length of segment : 12 time for calcul the mask position with numpy : 3.3855438232421875e-05 nb_pixel_total : 528 time to create 1 rle with old method : 0.0006504058837890625 length of segment : 32 time for calcul the mask position with numpy : 4.57763671875e-05 nb_pixel_total : 1111 time to create 1 rle with old method : 0.001600027084350586 length of segment : 50 time for calcul the mask position with numpy : 3.3855438232421875e-05 nb_pixel_total : 282 time to create 1 rle with old method : 0.0004153251647949219 length of segment : 19 time for calcul the mask position with numpy : 3.266334533691406e-05 nb_pixel_total : 288 time to create 1 rle with old method : 0.0004506111145019531 length of segment : 34 time for calcul the mask position with numpy : 3.719329833984375e-05 nb_pixel_total : 471 time to create 1 rle with old method : 0.0006387233734130859 length of segment : 19 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -118.53594 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 9 time for calcul the mask position with numpy : 5.435943603515625e-05 nb_pixel_total : 1762 time to create 1 rle with old method : 0.002107858657836914 length of segment : 28 time for calcul the mask position with numpy : 3.552436828613281e-05 nb_pixel_total : 623 time to create 1 rle with old method : 0.0007419586181640625 length of segment : 28 time for calcul the mask position with numpy : 0.0002472400665283203 nb_pixel_total : 14494 time to create 1 rle with old method : 0.020310163497924805 length of segment : 143 time for calcul the mask position with numpy : 5.626678466796875e-05 nb_pixel_total : 1616 time to create 1 rle with old method : 0.0020706653594970703 length of segment : 45 time for calcul the mask position with numpy : 3.910064697265625e-05 nb_pixel_total : 508 time to create 1 rle with old method : 0.0006330013275146484 length of segment : 58 time for calcul the mask position with numpy : 3.0040740966796875e-05 nb_pixel_total : 98 time to create 1 rle with old method : 0.0001690387725830078 length of segment : 9 time for calcul the mask position with numpy : 7.05718994140625e-05 nb_pixel_total : 876 time to create 1 rle with old method : 0.0012598037719726562 length of segment : 44 time for calcul the mask position with numpy : 4.410743713378906e-05 nb_pixel_total : 683 time to create 1 rle with old method : 0.0009729862213134766 length of segment : 25 time for calcul the mask position with numpy : 4.076957702636719e-05 nb_pixel_total : 1166 time to create 1 rle with old method : 0.001308441162109375 length of segment : 48 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -109.65703 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 8 time for calcul the mask position with numpy : 6.4849853515625e-05 nb_pixel_total : 1450 time to create 1 rle with old method : 0.0018551349639892578 length of segment : 43 time for calcul the mask position with numpy : 3.3855438232421875e-05 nb_pixel_total : 209 time to create 1 rle with old method : 0.00030040740966796875 length of segment : 16 time for calcul the mask position with numpy : 6.842613220214844e-05 nb_pixel_total : 1320 time to create 1 rle with old method : 0.0016641616821289062 length of segment : 113 time for calcul the mask position with numpy : 3.743171691894531e-05 nb_pixel_total : 792 time to create 1 rle with old method : 0.0009374618530273438 length of segment : 35 time for calcul the mask position with numpy : 8.630752563476562e-05 nb_pixel_total : 614 time to create 1 rle with old method : 0.0008687973022460938 length of segment : 94 time for calcul the mask position with numpy : 2.6941299438476562e-05 nb_pixel_total : 32 time to create 1 rle with old method : 6.508827209472656e-05 length of segment : 8 time for calcul the mask position with numpy : 3.8623809814453125e-05 nb_pixel_total : 1025 time to create 1 rle with old method : 0.0011630058288574219 length of segment : 39 time for calcul the mask position with numpy : 3.409385681152344e-05 nb_pixel_total : 773 time to create 1 rle with old method : 0.0008678436279296875 length of segment : 36 Processing 1 images image shape: (400, 320, 3) min: 0.00000 max: 231.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 114.28750 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 6 time for calcul the mask position with numpy : 3.886222839355469e-05 nb_pixel_total : 363 time to create 1 rle with old method : 0.0004978179931640625 length of segment : 46 time for calcul the mask position with numpy : 7.033348083496094e-05 nb_pixel_total : 1319 time to create 1 rle with old method : 0.0017218589782714844 length of segment : 72 time for calcul the mask position with numpy : 0.00015091896057128906 nb_pixel_total : 4412 time to create 1 rle with old method : 0.005007028579711914 length of segment : 224 time for calcul the mask position with numpy : 2.9802322387695312e-05 nb_pixel_total : 48 time to create 1 rle with old method : 8.559226989746094e-05 length of segment : 10 time for calcul the mask position with numpy : 4.553794860839844e-05 nb_pixel_total : 721 time to create 1 rle with old method : 0.0010116100311279297 length of segment : 34 time for calcul the mask position with numpy : 3.5762786865234375e-05 nb_pixel_total : 257 time to create 1 rle with old method : 0.00033926963806152344 length of segment : 36 Processing 1 images image shape: (280, 400, 3) min: 20.00000 max: 209.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 89.24062 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 1 time for calcul the mask position with numpy : 0.0009417533874511719 nb_pixel_total : 106000 time to create 1 rle with old method : 0.10989642143249512 length of segment : 282 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 144.72891 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 10 time for calcul the mask position with numpy : 3.7670135498046875e-05 nb_pixel_total : 223 time to create 1 rle with old method : 0.0003414154052734375 length of segment : 14 time for calcul the mask position with numpy : 3.457069396972656e-05 nb_pixel_total : 205 time to create 1 rle with old method : 0.00033164024353027344 length of segment : 17 time for calcul the mask position with numpy : 6.771087646484375e-05 nb_pixel_total : 2608 time to create 1 rle with old method : 0.003384828567504883 length of segment : 71 time for calcul the mask position with numpy : 5.1975250244140625e-05 nb_pixel_total : 1558 time to create 1 rle with old method : 0.0020208358764648438 length of segment : 41 time for calcul the mask position with numpy : 4.2438507080078125e-05 nb_pixel_total : 419 time to create 1 rle with old method : 0.0005834102630615234 length of segment : 38 time for calcul the mask position with numpy : 0.00013065338134765625 nb_pixel_total : 7590 time to create 1 rle with old method : 0.009392499923706055 length of segment : 79 time for calcul the mask position with numpy : 4.3392181396484375e-05 nb_pixel_total : 350 time to create 1 rle with old method : 0.0004703998565673828 length of segment : 32 time for calcul the mask position with numpy : 5.6743621826171875e-05 nb_pixel_total : 1342 time to create 1 rle with old method : 0.0017595291137695312 length of segment : 70 time for calcul the mask position with numpy : 6.961822509765625e-05 nb_pixel_total : 2380 time to create 1 rle with old method : 0.0029191970825195312 length of segment : 66 time for calcul the mask position with numpy : 3.4809112548828125e-05 nb_pixel_total : 171 time to create 1 rle with old method : 0.0002582073211669922 length of segment : 21 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 216.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 96.35000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 3 time for calcul the mask position with numpy : 4.982948303222656e-05 nb_pixel_total : 397 time to create 1 rle with old method : 0.0006005764007568359 length of segment : 17 time for calcul the mask position with numpy : 4.100799560546875e-05 nb_pixel_total : 434 time to create 1 rle with old method : 0.0006380081176757812 length of segment : 27 time for calcul the mask position with numpy : 3.457069396972656e-05 nb_pixel_total : 288 time to create 1 rle with old method : 0.00041365623474121094 length of segment : 20 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 150.04531 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 6 time for calcul the mask position with numpy : 5.316734313964844e-05 nb_pixel_total : 1026 time to create 1 rle with old method : 0.0012438297271728516 length of segment : 76 time for calcul the mask position with numpy : 3.123283386230469e-05 nb_pixel_total : 238 time to create 1 rle with old method : 0.00030159950256347656 length of segment : 27 time for calcul the mask position with numpy : 3.147125244140625e-05 nb_pixel_total : 132 time to create 1 rle with old method : 0.00019669532775878906 length of segment : 28 length of segment : 0 time for calcul the mask position with numpy : 6.532669067382812e-05 nb_pixel_total : 245 time to create 1 rle with old method : 0.0004971027374267578 length of segment : 33 time for calcul the mask position with numpy : 3.0994415283203125e-05 nb_pixel_total : 198 time to create 1 rle with old method : 0.00028324127197265625 length of segment : 16 Processing 1 images image shape: (280, 320, 3) min: 0.00000 max: 254.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 133.82500 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 2 time for calcul the mask position with numpy : 4.172325134277344e-05 nb_pixel_total : 414 time to create 1 rle with old method : 0.0006024837493896484 length of segment : 26 time for calcul the mask position with numpy : 3.409385681152344e-05 nb_pixel_total : 336 time to create 1 rle with old method : 0.0004944801330566406 length of segment : 17 NEW PHOTO pour l'instant on ne peut pas sauvegarder la photo dans les tile Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -117.43828 max: 145.03359 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 5 time for calcul the mask position with numpy : 4.124641418457031e-05 nb_pixel_total : 360 time to create 1 rle with old method : 0.0004780292510986328 length of segment : 31 time for calcul the mask position with numpy : 4.172325134277344e-05 nb_pixel_total : 980 time to create 1 rle with old method : 0.001188039779663086 length of segment : 38 time for calcul the mask position with numpy : 3.147125244140625e-05 nb_pixel_total : 40 time to create 1 rle with old method : 0.00010418891906738281 length of segment : 13 length of segment : 0 time for calcul the mask position with numpy : 4.267692565917969e-05 nb_pixel_total : 1083 time to create 1 rle with old method : 0.0014276504516601562 length of segment : 43 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -117.51641 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 9 time for calcul the mask position with numpy : 5.173683166503906e-05 nb_pixel_total : 1069 time to create 1 rle with old method : 0.001272439956665039 length of segment : 51 time for calcul the mask position with numpy : 3.7670135498046875e-05 nb_pixel_total : 507 time to create 1 rle with old method : 0.0007495880126953125 length of segment : 19 time for calcul the mask position with numpy : 2.7418136596679688e-05 nb_pixel_total : 61 time to create 1 rle with old method : 9.822845458984375e-05 length of segment : 14 time for calcul the mask position with numpy : 2.7418136596679688e-05 nb_pixel_total : 103 time to create 1 rle with old method : 0.0001556873321533203 length of segment : 14 time for calcul the mask position with numpy : 2.5510787963867188e-05 nb_pixel_total : 33 time to create 1 rle with old method : 6.842613220214844e-05 length of segment : 5 time for calcul the mask position with numpy : 8.96453857421875e-05 nb_pixel_total : 139 time to create 1 rle with old method : 0.0002465248107910156 length of segment : 13 time for calcul the mask position with numpy : 4.1961669921875e-05 nb_pixel_total : 373 time to create 1 rle with old method : 0.0007092952728271484 length of segment : 36 time for calcul the mask position with numpy : 3.5762786865234375e-05 nb_pixel_total : 292 time to create 1 rle with old method : 0.00040459632873535156 length of segment : 38 time for calcul the mask position with numpy : 2.9087066650390625e-05 nb_pixel_total : 321 time to create 1 rle with old method : 0.0004277229309082031 length of segment : 33 Processing 1 images image shape: (400, 400, 3) min: 19.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -91.86016 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 3 time for calcul the mask position with numpy : 0.0001246929168701172 nb_pixel_total : 6532 time to create 1 rle with old method : 0.007966041564941406 length of segment : 103 time for calcul the mask position with numpy : 8.368492126464844e-05 nb_pixel_total : 4837 time to create 1 rle with old method : 0.006081104278564453 length of segment : 77 time for calcul the mask position with numpy : 8.130073547363281e-05 nb_pixel_total : 3162 time to create 1 rle with old method : 0.0038344860076904297 length of segment : 130 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -112.52031 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 7 time for calcul the mask position with numpy : 4.7206878662109375e-05 nb_pixel_total : 132 time to create 1 rle with old method : 0.00029206275939941406 length of segment : 16 time for calcul the mask position with numpy : 0.00014829635620117188 nb_pixel_total : 7192 time to create 1 rle with old method : 0.01191091537475586 length of segment : 155 time for calcul the mask position with numpy : 0.00013327598571777344 nb_pixel_total : 4496 time to create 1 rle with old method : 0.007338285446166992 length of segment : 178 time for calcul the mask position with numpy : 3.314018249511719e-05 nb_pixel_total : 215 time to create 1 rle with old method : 0.00027060508728027344 length of segment : 22 time for calcul the mask position with numpy : 2.7418136596679688e-05 nb_pixel_total : 95 time to create 1 rle with old method : 0.0001468658447265625 length of segment : 14 time for calcul the mask position with numpy : 3.9577484130859375e-05 nb_pixel_total : 329 time to create 1 rle with old method : 0.0005755424499511719 length of segment : 20 time for calcul the mask position with numpy : 3.3855438232421875e-05 nb_pixel_total : 415 time to create 1 rle with old method : 0.0004897117614746094 length of segment : 23 Processing 1 images image shape: (400, 320, 3) min: 0.00000 max: 243.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 99.49453 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 2 time for calcul the mask position with numpy : 5.1021575927734375e-05 nb_pixel_total : 548 time to create 1 rle with old method : 0.0009362697601318359 length of segment : 24 time for calcul the mask position with numpy : 6.866455078125e-05 nb_pixel_total : 1875 time to create 1 rle with old method : 0.0025777816772460938 length of segment : 70 Processing 1 images image shape: (400, 400, 3) min: 25.00000 max: 201.00000 molded_images shape: (1, 640, 640, 3) min: -80.84063 max: 78.01797 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 0 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -120.29766 max: 148.41641 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 14 time for calcul the mask position with numpy : 6.890296936035156e-05 nb_pixel_total : 1254 time to create 1 rle with old method : 0.0016186237335205078 length of segment : 45 time for calcul the mask position with numpy : 3.743171691894531e-05 nb_pixel_total : 255 time to create 1 rle with old method : 0.0003998279571533203 length of segment : 21 time for calcul the mask position with numpy : 3.409385681152344e-05 nb_pixel_total : 156 time to create 1 rle with old method : 0.0002582073211669922 length of segment : 9 time for calcul the mask position with numpy : 3.933906555175781e-05 nb_pixel_total : 887 time to create 1 rle with old method : 0.0011780261993408203 length of segment : 28 time for calcul the mask position with numpy : 3.528594970703125e-05 nb_pixel_total : 458 time to create 1 rle with old method : 0.0006673336029052734 length of segment : 24 time for calcul the mask position with numpy : 3.9577484130859375e-05 nb_pixel_total : 542 time to create 1 rle with old method : 0.0007293224334716797 length of segment : 32 time for calcul the mask position with numpy : 3.4809112548828125e-05 nb_pixel_total : 246 time to create 1 rle with old method : 0.00042629241943359375 length of segment : 14 time for calcul the mask position with numpy : 6.628036499023438e-05 nb_pixel_total : 2121 time to create 1 rle with old method : 0.002660512924194336 length of segment : 53 time for calcul the mask position with numpy : 3.24249267578125e-05 nb_pixel_total : 72 time to create 1 rle with old method : 0.00014352798461914062 length of segment : 7 time for calcul the mask position with numpy : 3.695487976074219e-05 nb_pixel_total : 429 time to create 1 rle with old method : 0.0006279945373535156 length of segment : 22 time for calcul the mask position with numpy : 8.511543273925781e-05 nb_pixel_total : 4427 time to create 1 rle with old method : 0.005600929260253906 length of segment : 87 time for calcul the mask position with numpy : 3.457069396972656e-05 nb_pixel_total : 215 time to create 1 rle with old method : 0.00034427642822265625 length of segment : 22 time for calcul the mask position with numpy : 3.1948089599609375e-05 nb_pixel_total : 175 time to create 1 rle with old method : 0.0002465248107910156 length of segment : 21 time for calcul the mask position with numpy : 3.337860107421875e-05 nb_pixel_total : 390 time to create 1 rle with old method : 0.0005848407745361328 length of segment : 20 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -120.22734 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 8 time for calcul the mask position with numpy : 4.982948303222656e-05 nb_pixel_total : 1044 time to create 1 rle with old method : 0.001310586929321289 length of segment : 46 time for calcul the mask position with numpy : 5.14984130859375e-05 nb_pixel_total : 1736 time to create 1 rle with old method : 0.002106189727783203 length of segment : 28 time for calcul the mask position with numpy : 3.62396240234375e-05 nb_pixel_total : 364 time to create 1 rle with old method : 0.0004527568817138672 length of segment : 56 time for calcul the mask position with numpy : 2.7894973754882812e-05 nb_pixel_total : 98 time to create 1 rle with old method : 0.00016832351684570312 length of segment : 9 time for calcul the mask position with numpy : 3.528594970703125e-05 nb_pixel_total : 670 time to create 1 rle with old method : 0.0008897781372070312 length of segment : 31 time for calcul the mask position with numpy : 3.695487976074219e-05 nb_pixel_total : 769 time to create 1 rle with old method : 0.000946044921875 length of segment : 47 time for calcul the mask position with numpy : 8.440017700195312e-05 nb_pixel_total : 2320 time to create 1 rle with old method : 0.0029501914978027344 length of segment : 118 time for calcul the mask position with numpy : 7.343292236328125e-05 nb_pixel_total : 2246 time to create 1 rle with old method : 0.0026998519897460938 length of segment : 98 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -114.83281 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 9 time for calcul the mask position with numpy : 4.7206878662109375e-05 nb_pixel_total : 815 time to create 1 rle with old method : 0.001047372817993164 length of segment : 37 time for calcul the mask position with numpy : 5.936622619628906e-05 nb_pixel_total : 1312 time to create 1 rle with old method : 0.0019092559814453125 length of segment : 41 time for calcul the mask position with numpy : 3.170967102050781e-05 nb_pixel_total : 147 time to create 1 rle with old method : 0.00022721290588378906 length of segment : 15 time for calcul the mask position with numpy : 3.0279159545898438e-05 nb_pixel_total : 34 time to create 1 rle with old method : 7.367134094238281e-05 length of segment : 8 time for calcul the mask position with numpy : 6.031990051269531e-05 nb_pixel_total : 1133 time to create 1 rle with old method : 0.0014531612396240234 length of segment : 96 time for calcul the mask position with numpy : 0.00010323524475097656 nb_pixel_total : 1312 time to create 1 rle with old method : 0.0016410350799560547 length of segment : 110 time for calcul the mask position with numpy : 0.0001289844512939453 nb_pixel_total : 1340 time to create 1 rle with old method : 0.0020477771759033203 length of segment : 104 time for calcul the mask position with numpy : 8.58306884765625e-05 nb_pixel_total : 993 time to create 1 rle with old method : 0.0018012523651123047 length of segment : 39 time for calcul the mask position with numpy : 7.581710815429688e-05 nb_pixel_total : 1226 time to create 1 rle with old method : 0.0018274784088134766 length of segment : 44 Processing 1 images image shape: (400, 320, 3) min: 0.00000 max: 250.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 114.71719 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 8 time for calcul the mask position with numpy : 0.0001461505889892578 nb_pixel_total : 3176 time to create 1 rle with old method : 0.0036056041717529297 length of segment : 188 time for calcul the mask position with numpy : 3.838539123535156e-05 nb_pixel_total : 80 time to create 1 rle with old method : 0.00013637542724609375 length of segment : 14 time for calcul the mask position with numpy : 3.695487976074219e-05 nb_pixel_total : 418 time to create 1 rle with old method : 0.0005862712860107422 length of segment : 47 time for calcul the mask position with numpy : 5.030632019042969e-05 nb_pixel_total : 769 time to create 1 rle with old method : 0.0010883808135986328 length of segment : 31 time for calcul the mask position with numpy : 6.961822509765625e-05 nb_pixel_total : 1038 time to create 1 rle with old method : 0.0017285346984863281 length of segment : 78 time for calcul the mask position with numpy : 3.2901763916015625e-05 nb_pixel_total : 126 time to create 1 rle with old method : 0.0001876354217529297 length of segment : 20 time for calcul the mask position with numpy : 3.6716461181640625e-05 nb_pixel_total : 337 time to create 1 rle with old method : 0.0004711151123046875 length of segment : 38 time for calcul the mask position with numpy : 3.24249267578125e-05 nb_pixel_total : 332 time to create 1 rle with old method : 0.00043272972106933594 length of segment : 41 Processing 1 images image shape: (280, 400, 3) min: 26.00000 max: 208.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 88.40313 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 1 time for calcul the mask position with numpy : 0.0010273456573486328 nb_pixel_total : 106589 time to create 1 rle with old method : 0.12394118309020996 length of segment : 280 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 143.00234 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 12 time for calcul the mask position with numpy : 5.6743621826171875e-05 nb_pixel_total : 1552 time to create 1 rle with old method : 0.002029895782470703 length of segment : 39 time for calcul the mask position with numpy : 3.743171691894531e-05 nb_pixel_total : 415 time to create 1 rle with old method : 0.0005962848663330078 length of segment : 31 time for calcul the mask position with numpy : 3.170967102050781e-05 nb_pixel_total : 190 time to create 1 rle with old method : 0.0003058910369873047 length of segment : 16 time for calcul the mask position with numpy : 3.6716461181640625e-05 nb_pixel_total : 229 time to create 1 rle with old method : 0.0003643035888671875 length of segment : 13 time for calcul the mask position with numpy : 6.532669067382812e-05 nb_pixel_total : 2523 time to create 1 rle with old method : 0.0030694007873535156 length of segment : 71 time for calcul the mask position with numpy : 7.510185241699219e-05 nb_pixel_total : 3006 time to create 1 rle with old method : 0.003623485565185547 length of segment : 73 time for calcul the mask position with numpy : 3.552436828613281e-05 nb_pixel_total : 185 time to create 1 rle with old method : 0.00028133392333984375 length of segment : 35 time for calcul the mask position with numpy : 8.320808410644531e-05 nb_pixel_total : 928 time to create 1 rle with old method : 0.002077341079711914 length of segment : 38 time for calcul the mask position with numpy : 0.0001990795135498047 nb_pixel_total : 7429 time to create 1 rle with old method : 0.01099395751953125 length of segment : 78 time for calcul the mask position with numpy : 6.365776062011719e-05 nb_pixel_total : 2212 time to create 1 rle with old method : 0.00267791748046875 length of segment : 64 time for calcul the mask position with numpy : 3.457069396972656e-05 nb_pixel_total : 440 time to create 1 rle with old method : 0.0005488395690917969 length of segment : 45 time for calcul the mask position with numpy : 3.552436828613281e-05 nb_pixel_total : 202 time to create 1 rle with old method : 0.0003459453582763672 length of segment : 49 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 229.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 112.61562 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 2 time for calcul the mask position with numpy : 3.981590270996094e-05 nb_pixel_total : 241 time to create 1 rle with old method : 0.00036215782165527344 length of segment : 25 time for calcul the mask position with numpy : 3.5762786865234375e-05 nb_pixel_total : 368 time to create 1 rle with old method : 0.0005769729614257812 length of segment : 15 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 150.45937 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 5 time for calcul the mask position with numpy : 4.0531158447265625e-05 nb_pixel_total : 382 time to create 1 rle with old method : 0.0005307197570800781 length of segment : 34 time for calcul the mask position with numpy : 3.361701965332031e-05 nb_pixel_total : 244 time to create 1 rle with old method : 0.00035071372985839844 length of segment : 25 time for calcul the mask position with numpy : 4.6253204345703125e-05 nb_pixel_total : 767 time to create 1 rle with old method : 0.0010619163513183594 length of segment : 59 time for calcul the mask position with numpy : 3.123283386230469e-05 nb_pixel_total : 127 time to create 1 rle with old method : 0.0001857280731201172 length of segment : 28 time for calcul the mask position with numpy : 5.078315734863281e-05 nb_pixel_total : 89 time to create 1 rle with old method : 0.0002491474151611328 length of segment : 28 Processing 1 images image shape: (280, 320, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 134.32500 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 3 time for calcul the mask position with numpy : 4.1484832763671875e-05 nb_pixel_total : 318 time to create 1 rle with old method : 0.0004780292510986328 length of segment : 17 time for calcul the mask position with numpy : 3.62396240234375e-05 nb_pixel_total : 373 time to create 1 rle with old method : 0.0005586147308349609 length of segment : 24 time for calcul the mask position with numpy : 0.0004949569702148438 nb_pixel_total : 41444 time to create 1 rle with old method : 0.04688262939453125 length of segment : 289 NEW PHOTO pour l'instant on ne peut pas sauvegarder la photo dans les tile Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -117.39531 max: 145.13125 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 6 time for calcul the mask position with numpy : 4.029273986816406e-05 nb_pixel_total : 355 time to create 1 rle with old method : 0.0004875659942626953 length of segment : 33 time for calcul the mask position with numpy : 4.291534423828125e-05 nb_pixel_total : 1029 time to create 1 rle with old method : 0.0013909339904785156 length of segment : 34 length of segment : 0 time for calcul the mask position with numpy : 7.510185241699219e-05 nb_pixel_total : 2723 time to create 1 rle with old method : 0.003470182418823242 length of segment : 75 time for calcul the mask position with numpy : 4.506111145019531e-05 nb_pixel_total : 1111 time to create 1 rle with old method : 0.0014820098876953125 length of segment : 40 time for calcul the mask position with numpy : 0.00021386146545410156 nb_pixel_total : 4103 time to create 1 rle with old method : 0.00512385368347168 length of segment : 124 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -117.45781 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 8 time for calcul the mask position with numpy : 6.246566772460938e-05 nb_pixel_total : 1151 time to create 1 rle with old method : 0.0014090538024902344 length of segment : 47 time for calcul the mask position with numpy : 4.1961669921875e-05 nb_pixel_total : 688 time to create 1 rle with old method : 0.0010256767272949219 length of segment : 21 time for calcul the mask position with numpy : 3.457069396972656e-05 nb_pixel_total : 98 time to create 1 rle with old method : 0.00022745132446289062 length of segment : 14 time for calcul the mask position with numpy : 3.910064697265625e-05 nb_pixel_total : 684 time to create 1 rle with old method : 0.0009520053863525391 length of segment : 40 time for calcul the mask position with numpy : 3.123283386230469e-05 nb_pixel_total : 56 time to create 1 rle with old method : 0.00010991096496582031 length of segment : 10 time for calcul the mask position with numpy : 3.361701965332031e-05 nb_pixel_total : 312 time to create 1 rle with old method : 0.00043845176696777344 length of segment : 45 time for calcul the mask position with numpy : 0.00019097328186035156 nb_pixel_total : 1262 time to create 1 rle with old method : 0.0017590522766113281 length of segment : 113 time for calcul the mask position with numpy : 4.506111145019531e-05 nb_pixel_total : 953 time to create 1 rle with old method : 0.0012590885162353516 length of segment : 54 Processing 1 images image shape: (400, 400, 3) min: 24.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -83.21953 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 2 time for calcul the mask position with numpy : 0.00012683868408203125 nb_pixel_total : 6157 time to create 1 rle with old method : 0.007638454437255859 length of segment : 119 time for calcul the mask position with numpy : 9.870529174804688e-05 nb_pixel_total : 1905 time to create 1 rle with old method : 0.002240419387817383 length of segment : 121 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -117.59844 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 6 time for calcul the mask position with numpy : 0.0001304149627685547 nb_pixel_total : 7666 time to create 1 rle with old method : 0.008944988250732422 length of segment : 144 time for calcul the mask position with numpy : 3.552436828613281e-05 nb_pixel_total : 101 time to create 1 rle with old method : 0.0001709461212158203 length of segment : 16 time for calcul the mask position with numpy : 0.00010395050048828125 nb_pixel_total : 3584 time to create 1 rle with old method : 0.0044689178466796875 length of segment : 165 time for calcul the mask position with numpy : 3.2901763916015625e-05 nb_pixel_total : 98 time to create 1 rle with old method : 0.00015878677368164062 length of segment : 13 time for calcul the mask position with numpy : 3.409385681152344e-05 nb_pixel_total : 306 time to create 1 rle with old method : 0.0004248619079589844 length of segment : 25 time for calcul the mask position with numpy : 6.246566772460938e-05 nb_pixel_total : 1501 time to create 1 rle with old method : 0.0019500255584716797 length of segment : 81 Processing 1 images image shape: (400, 320, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 129.38516 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 2 time for calcul the mask position with numpy : 5.2928924560546875e-05 nb_pixel_total : 544 time to create 1 rle with old method : 0.000982522964477539 length of segment : 23 time for calcul the mask position with numpy : 5.602836608886719e-05 nb_pixel_total : 1826 time to create 1 rle with old method : 0.002225637435913086 length of segment : 59 Processing 1 images image shape: (400, 400, 3) min: 26.00000 max: 194.00000 molded_images shape: (1, 640, 640, 3) min: -81.70391 max: 75.83047 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 0 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -120.23906 max: 136.28359 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 13 time for calcul the mask position with numpy : 4.38690185546875e-05 nb_pixel_total : 233 time to create 1 rle with old method : 0.0003428459167480469 length of segment : 20 time for calcul the mask position with numpy : 4.9114227294921875e-05 nb_pixel_total : 1396 time to create 1 rle with old method : 0.0017852783203125 length of segment : 53 time for calcul the mask position with numpy : 3.1948089599609375e-05 nb_pixel_total : 162 time to create 1 rle with old method : 0.00027871131896972656 length of segment : 9 time for calcul the mask position with numpy : 4.315376281738281e-05 nb_pixel_total : 1027 time to create 1 rle with old method : 0.001356363296508789 length of segment : 26 time for calcul the mask position with numpy : 3.0040740966796875e-05 nb_pixel_total : 96 time to create 1 rle with old method : 0.0001728534698486328 length of segment : 9 time for calcul the mask position with numpy : 3.4809112548828125e-05 nb_pixel_total : 343 time to create 1 rle with old method : 0.0005519390106201172 length of segment : 17 time for calcul the mask position with numpy : 9.250640869140625e-05 nb_pixel_total : 3418 time to create 1 rle with old method : 0.004361629486083984 length of segment : 111 time for calcul the mask position with numpy : 3.981590270996094e-05 nb_pixel_total : 517 time to create 1 rle with old method : 0.0007350444793701172 length of segment : 17 time for calcul the mask position with numpy : 3.552436828613281e-05 nb_pixel_total : 414 time to create 1 rle with old method : 0.0006210803985595703 length of segment : 18 time for calcul the mask position with numpy : 3.886222839355469e-05 nb_pixel_total : 557 time to create 1 rle with old method : 0.0008187294006347656 length of segment : 25 time for calcul the mask position with numpy : 3.409385681152344e-05 nb_pixel_total : 188 time to create 1 rle with old method : 0.00034308433532714844 length of segment : 21 time for calcul the mask position with numpy : 3.790855407714844e-05 nb_pixel_total : 527 time to create 1 rle with old method : 0.000728607177734375 length of segment : 31 time for calcul the mask position with numpy : 3.62396240234375e-05 nb_pixel_total : 537 time to create 1 rle with old method : 0.0007441043853759766 length of segment : 32 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -112.41484 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 10 time for calcul the mask position with numpy : 6.532669067382812e-05 nb_pixel_total : 2223 time to create 1 rle with old method : 0.0028078556060791016 length of segment : 37 time for calcul the mask position with numpy : 0.00022840499877929688 nb_pixel_total : 14176 time to create 1 rle with old method : 0.016671419143676758 length of segment : 131 time for calcul the mask position with numpy : 3.2901763916015625e-05 nb_pixel_total : 101 time to create 1 rle with old method : 0.00018286705017089844 length of segment : 9 time for calcul the mask position with numpy : 3.9577484130859375e-05 nb_pixel_total : 622 time to create 1 rle with old method : 0.0008034706115722656 length of segment : 30 time for calcul the mask position with numpy : 7.486343383789062e-05 nb_pixel_total : 2341 time to create 1 rle with old method : 0.003132343292236328 length of segment : 113 time for calcul the mask position with numpy : 3.910064697265625e-05 nb_pixel_total : 564 time to create 1 rle with old method : 0.0007562637329101562 length of segment : 24 time for calcul the mask position with numpy : 3.218650817871094e-05 nb_pixel_total : 234 time to create 1 rle with old method : 0.00035452842712402344 length of segment : 17 time for calcul the mask position with numpy : 5.459785461425781e-05 nb_pixel_total : 1612 time to create 1 rle with old method : 0.0021674633026123047 length of segment : 45 time for calcul the mask position with numpy : 3.743171691894531e-05 nb_pixel_total : 432 time to create 1 rle with old method : 0.000545501708984375 length of segment : 47 time for calcul the mask position with numpy : 3.4332275390625e-05 nb_pixel_total : 604 time to create 1 rle with old method : 0.0006854534149169922 length of segment : 27 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -116.69219 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 7 time for calcul the mask position with numpy : 4.6253204345703125e-05 nb_pixel_total : 136 time to create 1 rle with old method : 0.00026798248291015625 length of segment : 14 time for calcul the mask position with numpy : 5.078315734863281e-05 nb_pixel_total : 836 time to create 1 rle with old method : 0.0013654232025146484 length of segment : 38 time for calcul the mask position with numpy : 6.556510925292969e-05 nb_pixel_total : 1213 time to create 1 rle with old method : 0.0017600059509277344 length of segment : 101 time for calcul the mask position with numpy : 7.200241088867188e-05 nb_pixel_total : 1252 time to create 1 rle with old method : 0.001734018325805664 length of segment : 42 time for calcul the mask position with numpy : 4.100799560546875e-05 nb_pixel_total : 882 time to create 1 rle with old method : 0.0010728836059570312 length of segment : 38 time for calcul the mask position with numpy : 6.556510925292969e-05 nb_pixel_total : 1231 time to create 1 rle with old method : 0.001613616943359375 length of segment : 107 time for calcul the mask position with numpy : 5.1021575927734375e-05 nb_pixel_total : 1170 time to create 1 rle with old method : 0.001432180404663086 length of segment : 43 Processing 1 images image shape: (400, 320, 3) min: 0.00000 max: 239.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 116.73672 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 7 time for calcul the mask position with numpy : 9.131431579589844e-05 nb_pixel_total : 1086 time to create 1 rle with old method : 0.0021026134490966797 length of segment : 98 time for calcul the mask position with numpy : 0.00015807151794433594 nb_pixel_total : 3393 time to create 1 rle with old method : 0.004017829895019531 length of segment : 181 time for calcul the mask position with numpy : 3.504753112792969e-05 nb_pixel_total : 151 time to create 1 rle with old method : 0.0002288818359375 length of segment : 27 time for calcul the mask position with numpy : 3.528594970703125e-05 nb_pixel_total : 312 time to create 1 rle with old method : 0.0004379749298095703 length of segment : 37 time for calcul the mask position with numpy : 2.9325485229492188e-05 nb_pixel_total : 80 time to create 1 rle with old method : 0.0001239776611328125 length of segment : 15 time for calcul the mask position with numpy : 3.218650817871094e-05 nb_pixel_total : 187 time to create 1 rle with old method : 0.0002772808074951172 length of segment : 28 time for calcul the mask position with numpy : 5.7220458984375e-05 nb_pixel_total : 1134 time to create 1 rle with old method : 0.0016064643859863281 length of segment : 116 Processing 1 images image shape: (280, 400, 3) min: 28.00000 max: 205.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 86.52969 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 1 time for calcul the mask position with numpy : 0.0009031295776367188 nb_pixel_total : 106625 time to create 1 rle with old method : 0.11370229721069336 length of segment : 283 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 142.81484 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 9 time for calcul the mask position with numpy : 5.7220458984375e-05 nb_pixel_total : 1544 time to create 1 rle with old method : 0.0019216537475585938 length of segment : 40 time for calcul the mask position with numpy : 3.170967102050781e-05 nb_pixel_total : 179 time to create 1 rle with old method : 0.00031375885009765625 length of segment : 10 time for calcul the mask position with numpy : 7.033348083496094e-05 nb_pixel_total : 2986 time to create 1 rle with old method : 0.003777742385864258 length of segment : 65 time for calcul the mask position with numpy : 3.5762786865234375e-05 nb_pixel_total : 427 time to create 1 rle with old method : 0.0006089210510253906 length of segment : 33 time for calcul the mask position with numpy : 4.0531158447265625e-05 nb_pixel_total : 843 time to create 1 rle with old method : 0.0010960102081298828 length of segment : 34 time for calcul the mask position with numpy : 8.893013000488281e-05 nb_pixel_total : 2479 time to create 1 rle with old method : 0.003065824508666992 length of segment : 73 time for calcul the mask position with numpy : 3.62396240234375e-05 nb_pixel_total : 410 time to create 1 rle with old method : 0.0005481243133544922 length of segment : 47 time for calcul the mask position with numpy : 0.00011467933654785156 nb_pixel_total : 7473 time to create 1 rle with old method : 0.009157180786132812 length of segment : 77 time for calcul the mask position with numpy : 0.00011467933654785156 nb_pixel_total : 7504 time to create 1 rle with old method : 0.009015560150146484 length of segment : 79 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 242.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 121.71328 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 4 time for calcul the mask position with numpy : 5.030632019042969e-05 nb_pixel_total : 394 time to create 1 rle with old method : 0.0007004737854003906 length of segment : 19 time for calcul the mask position with numpy : 3.2901763916015625e-05 nb_pixel_total : 270 time to create 1 rle with old method : 0.0003917217254638672 length of segment : 17 time for calcul the mask position with numpy : 3.123283386230469e-05 nb_pixel_total : 129 time to create 1 rle with old method : 0.0001876354217529297 length of segment : 18 time for calcul the mask position with numpy : 2.9325485229492188e-05 nb_pixel_total : 68 time to create 1 rle with old method : 0.00011086463928222656 length of segment : 12 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 150.12734 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 5 time for calcul the mask position with numpy : 4.935264587402344e-05 nb_pixel_total : 349 time to create 1 rle with old method : 0.0005884170532226562 length of segment : 27 time for calcul the mask position with numpy : 3.314018249511719e-05 nb_pixel_total : 206 time to create 1 rle with old method : 0.0002765655517578125 length of segment : 24 time for calcul the mask position with numpy : 3.170967102050781e-05 nb_pixel_total : 157 time to create 1 rle with old method : 0.00022149085998535156 length of segment : 28 time for calcul the mask position with numpy : 4.38690185546875e-05 nb_pixel_total : 452 time to create 1 rle with old method : 0.0007493495941162109 length of segment : 22 time for calcul the mask position with numpy : 5.1021575927734375e-05 nb_pixel_total : 188 time to create 1 rle with old method : 0.0003790855407714844 length of segment : 41 Processing 1 images image shape: (280, 320, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 129.63750 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 2 time for calcul the mask position with numpy : 4.601478576660156e-05 nb_pixel_total : 304 time to create 1 rle with old method : 0.0005664825439453125 length of segment : 17 time for calcul the mask position with numpy : 4.363059997558594e-05 nb_pixel_total : 398 time to create 1 rle with old method : 0.0006914138793945312 length of segment : 24 NEW PHOTO pour l'instant on ne peut pas sauvegarder la photo dans les tile Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -117.39531 max: 145.06875 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 5 time for calcul the mask position with numpy : 4.7206878662109375e-05 nb_pixel_total : 949 time to create 1 rle with old method : 0.0012383460998535156 length of segment : 52 time for calcul the mask position with numpy : 3.504753112792969e-05 nb_pixel_total : 331 time to create 1 rle with old method : 0.0005006790161132812 length of segment : 32 time for calcul the mask position with numpy : 3.0517578125e-05 nb_pixel_total : 6 time to create 1 rle with old method : 3.552436828613281e-05 length of segment : 3 time for calcul the mask position with numpy : 4.1484832763671875e-05 nb_pixel_total : 959 time to create 1 rle with old method : 0.0012278556823730469 length of segment : 51 time for calcul the mask position with numpy : 9.560585021972656e-05 nb_pixel_total : 2943 time to create 1 rle with old method : 0.003648996353149414 length of segment : 87 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -117.64531 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 6 time for calcul the mask position with numpy : 4.482269287109375e-05 nb_pixel_total : 540 time to create 1 rle with old method : 0.0008096694946289062 length of segment : 20 time for calcul the mask position with numpy : 4.00543212890625e-05 nb_pixel_total : 512 time to create 1 rle with old method : 0.0007889270782470703 length of segment : 31 time for calcul the mask position with numpy : 0.00021147727966308594 nb_pixel_total : 3173 time to create 1 rle with old method : 0.00414586067199707 length of segment : 154 time for calcul the mask position with numpy : 4.601478576660156e-05 nb_pixel_total : 847 time to create 1 rle with old method : 0.001093149185180664 length of segment : 38 time for calcul the mask position with numpy : 3.337860107421875e-05 nb_pixel_total : 248 time to create 1 rle with old method : 0.000354766845703125 length of segment : 41 time for calcul the mask position with numpy : 8.7738037109375e-05 nb_pixel_total : 698 time to create 1 rle with old method : 0.0009489059448242188 length of segment : 48 Processing 1 images image shape: (400, 400, 3) min: 25.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -90.18438 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 3 time for calcul the mask position with numpy : 9.751319885253906e-05 nb_pixel_total : 1529 time to create 1 rle with old method : 0.0032432079315185547 length of segment : 29 time for calcul the mask position with numpy : 8.916854858398438e-05 nb_pixel_total : 4129 time to create 1 rle with old method : 0.005302906036376953 length of segment : 122 time for calcul the mask position with numpy : 0.0001366138458251953 nb_pixel_total : 6428 time to create 1 rle with old method : 0.00747227668762207 length of segment : 103 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -115.93047 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 8 time for calcul the mask position with numpy : 0.00014090538024902344 nb_pixel_total : 3632 time to create 1 rle with old method : 0.0044286251068115234 length of segment : 194 time for calcul the mask position with numpy : 0.00018477439880371094 nb_pixel_total : 6913 time to create 1 rle with old method : 0.008559226989746094 length of segment : 134 time for calcul the mask position with numpy : 4.076957702636719e-05 nb_pixel_total : 102 time to create 1 rle with old method : 0.0001773834228515625 length of segment : 15 time for calcul the mask position with numpy : 4.029273986816406e-05 nb_pixel_total : 396 time to create 1 rle with old method : 0.0005955696105957031 length of segment : 20 time for calcul the mask position with numpy : 3.600120544433594e-05 nb_pixel_total : 95 time to create 1 rle with old method : 0.00015664100646972656 length of segment : 16 time for calcul the mask position with numpy : 4.220008850097656e-05 nb_pixel_total : 300 time to create 1 rle with old method : 0.0005087852478027344 length of segment : 18 time for calcul the mask position with numpy : 3.8623809814453125e-05 nb_pixel_total : 263 time to create 1 rle with old method : 0.0003719329833984375 length of segment : 25 time for calcul the mask position with numpy : 4.0531158447265625e-05 nb_pixel_total : 342 time to create 1 rle with old method : 0.0006005764007568359 length of segment : 25 Processing 1 images image shape: (400, 320, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 131.18984 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 2 time for calcul the mask position with numpy : 4.124641418457031e-05 nb_pixel_total : 513 time to create 1 rle with old method : 0.0009427070617675781 length of segment : 23 time for calcul the mask position with numpy : 3.886222839355469e-05 nb_pixel_total : 214 time to create 1 rle with old method : 0.0003247261047363281 length of segment : 22 Processing 1 images image shape: (400, 400, 3) min: 24.00000 max: 195.00000 molded_images shape: (1, 640, 640, 3) min: -81.70391 max: 69.54922 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 0 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -119.12969 max: 132.12187 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 14 time for calcul the mask position with numpy : 6.508827209472656e-05 nb_pixel_total : 1050 time to create 1 rle with old method : 0.0014529228210449219 length of segment : 63 time for calcul the mask position with numpy : 4.3392181396484375e-05 nb_pixel_total : 254 time to create 1 rle with old method : 0.0003643035888671875 length of segment : 19 time for calcul the mask position with numpy : 6.0558319091796875e-05 nb_pixel_total : 524 time to create 1 rle with old method : 0.0009202957153320312 length of segment : 23 time for calcul the mask position with numpy : 3.361701965332031e-05 nb_pixel_total : 164 time to create 1 rle with old method : 0.0002982616424560547 length of segment : 9 time for calcul the mask position with numpy : 4.076957702636719e-05 nb_pixel_total : 558 time to create 1 rle with old method : 0.0007965564727783203 length of segment : 21 time for calcul the mask position with numpy : 4.839897155761719e-05 nb_pixel_total : 1075 time to create 1 rle with old method : 0.0014352798461914062 length of segment : 27 time for calcul the mask position with numpy : 3.218650817871094e-05 nb_pixel_total : 117 time to create 1 rle with old method : 0.00020599365234375 length of segment : 11 time for calcul the mask position with numpy : 3.8623809814453125e-05 nb_pixel_total : 274 time to create 1 rle with old method : 0.00043320655822753906 length of segment : 29 time for calcul the mask position with numpy : 3.600120544433594e-05 nb_pixel_total : 306 time to create 1 rle with old method : 0.0005066394805908203 length of segment : 16 time for calcul the mask position with numpy : 7.677078247070312e-05 nb_pixel_total : 1730 time to create 1 rle with old method : 0.002373933792114258 length of segment : 44 time for calcul the mask position with numpy : 4.0531158447265625e-05 nb_pixel_total : 527 time to create 1 rle with old method : 0.0006949901580810547 length of segment : 31 time for calcul the mask position with numpy : 3.62396240234375e-05 nb_pixel_total : 384 time to create 1 rle with old method : 0.0005557537078857422 length of segment : 18 time for calcul the mask position with numpy : 4.029273986816406e-05 nb_pixel_total : 546 time to create 1 rle with old method : 0.0007281303405761719 length of segment : 22 time for calcul the mask position with numpy : 4.3392181396484375e-05 nb_pixel_total : 586 time to create 1 rle with old method : 0.0008628368377685547 length of segment : 25 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -112.41484 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 9 time for calcul the mask position with numpy : 6.127357482910156e-05 nb_pixel_total : 2074 time to create 1 rle with old method : 0.0026280879974365234 length of segment : 31 time for calcul the mask position with numpy : 3.695487976074219e-05 nb_pixel_total : 113 time to create 1 rle with old method : 0.0002110004425048828 length of segment : 9 time for calcul the mask position with numpy : 0.00026798248291015625 nb_pixel_total : 14371 time to create 1 rle with old method : 0.01800847053527832 length of segment : 129 time for calcul the mask position with numpy : 5.459785461425781e-05 nb_pixel_total : 651 time to create 1 rle with old method : 0.0008897781372070312 length of segment : 32 time for calcul the mask position with numpy : 3.4332275390625e-05 nb_pixel_total : 189 time to create 1 rle with old method : 0.0002987384796142578 length of segment : 12 time for calcul the mask position with numpy : 7.176399230957031e-05 nb_pixel_total : 2182 time to create 1 rle with old method : 0.0027403831481933594 length of segment : 79 time for calcul the mask position with numpy : 8.487701416015625e-05 nb_pixel_total : 1296 time to create 1 rle with old method : 0.0020208358764648438 length of segment : 50 time for calcul the mask position with numpy : 4.220008850097656e-05 nb_pixel_total : 373 time to create 1 rle with old method : 0.0005247592926025391 length of segment : 52 time for calcul the mask position with numpy : 4.315376281738281e-05 nb_pixel_total : 641 time to create 1 rle with old method : 0.0008449554443359375 length of segment : 28 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -115.45781 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 6 time for calcul the mask position with numpy : 3.719329833984375e-05 nb_pixel_total : 206 time to create 1 rle with old method : 0.0003058910369873047 length of segment : 17 time for calcul the mask position with numpy : 7.486343383789062e-05 nb_pixel_total : 1236 time to create 1 rle with old method : 0.0016219615936279297 length of segment : 119 time for calcul the mask position with numpy : 4.3392181396484375e-05 nb_pixel_total : 733 time to create 1 rle with old method : 0.0009129047393798828 length of segment : 35 time for calcul the mask position with numpy : 6.246566772460938e-05 nb_pixel_total : 1178 time to create 1 rle with old method : 0.0016694068908691406 length of segment : 42 time for calcul the mask position with numpy : 4.553794860839844e-05 nb_pixel_total : 999 time to create 1 rle with old method : 0.001222372055053711 length of segment : 39 time for calcul the mask position with numpy : 4.9114227294921875e-05 nb_pixel_total : 1190 time to create 1 rle with old method : 0.0015442371368408203 length of segment : 42 Processing 1 images image shape: (400, 320, 3) min: 0.00000 max: 238.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 113.31875 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 8 time for calcul the mask position with numpy : 9.34600830078125e-05 nb_pixel_total : 1406 time to create 1 rle with old method : 0.0018925666809082031 length of segment : 109 time for calcul the mask position with numpy : 3.266334533691406e-05 nb_pixel_total : 50 time to create 1 rle with old method : 9.083747863769531e-05 length of segment : 11 time for calcul the mask position with numpy : 0.00014352798461914062 nb_pixel_total : 3330 time to create 1 rle with old method : 0.004588603973388672 length of segment : 197 time for calcul the mask position with numpy : 3.457069396972656e-05 nb_pixel_total : 138 time to create 1 rle with old method : 0.00020170211791992188 length of segment : 23 time for calcul the mask position with numpy : 3.337860107421875e-05 nb_pixel_total : 188 time to create 1 rle with old method : 0.0002815723419189453 length of segment : 30 time for calcul the mask position with numpy : 3.695487976074219e-05 nb_pixel_total : 371 time to create 1 rle with old method : 0.000530242919921875 length of segment : 46 time for calcul the mask position with numpy : 4.267692565917969e-05 nb_pixel_total : 649 time to create 1 rle with old method : 0.0008244514465332031 length of segment : 39 time for calcul the mask position with numpy : 0.00021576881408691406 nb_pixel_total : 4377 time to create 1 rle with old method : 0.005202054977416992 length of segment : 239 Processing 1 images image shape: (280, 400, 3) min: 28.00000 max: 206.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 90.54922 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 0 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 144.59219 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 6 time for calcul the mask position with numpy : 8.273124694824219e-05 nb_pixel_total : 1566 time to create 1 rle with old method : 0.0020225048065185547 length of segment : 41 time for calcul the mask position with numpy : 3.981590270996094e-05 nb_pixel_total : 176 time to create 1 rle with old method : 0.00034737586975097656 length of segment : 17 time for calcul the mask position with numpy : 9.846687316894531e-05 nb_pixel_total : 3119 time to create 1 rle with old method : 0.0039408206939697266 length of segment : 65 time for calcul the mask position with numpy : 5.1975250244140625e-05 nb_pixel_total : 214 time to create 1 rle with old method : 0.0003750324249267578 length of segment : 18 time for calcul the mask position with numpy : 4.410743713378906e-05 nb_pixel_total : 829 time to create 1 rle with old method : 0.001130819320678711 length of segment : 34 time for calcul the mask position with numpy : 0.00013828277587890625 nb_pixel_total : 7597 time to create 1 rle with old method : 0.009291887283325195 length of segment : 78 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 233.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 113.49062 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 3 time for calcul the mask position with numpy : 4.1484832763671875e-05 nb_pixel_total : 307 time to create 1 rle with old method : 0.0004630088806152344 length of segment : 15 time for calcul the mask position with numpy : 3.790855407714844e-05 nb_pixel_total : 48 time to create 1 rle with old method : 0.00010418891906738281 length of segment : 7 time for calcul the mask position with numpy : 3.170967102050781e-05 nb_pixel_total : 73 time to create 1 rle with old method : 0.00013065338134765625 length of segment : 12 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 150.01016 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 8 time for calcul the mask position with numpy : 4.506111145019531e-05 nb_pixel_total : 363 time to create 1 rle with old method : 0.00048160552978515625 length of segment : 32 time for calcul the mask position with numpy : 4.7206878662109375e-05 nb_pixel_total : 433 time to create 1 rle with old method : 0.0007658004760742188 length of segment : 23 time for calcul the mask position with numpy : 3.337860107421875e-05 nb_pixel_total : 163 time to create 1 rle with old method : 0.00047516822814941406 length of segment : 23 time for calcul the mask position with numpy : 3.266334533691406e-05 nb_pixel_total : 118 time to create 1 rle with old method : 0.00017333030700683594 length of segment : 28 time for calcul the mask position with numpy : 6.318092346191406e-05 nb_pixel_total : 264 time to create 1 rle with old method : 0.0004923343658447266 length of segment : 49 time for calcul the mask position with numpy : 0.00017499923706054688 nb_pixel_total : 57 time to create 1 rle with old method : 0.00013494491577148438 length of segment : 12 time for calcul the mask position with numpy : 0.00016546249389648438 nb_pixel_total : 2305 time to create 1 rle with old method : 0.0030291080474853516 length of segment : 228 length of segment : 0 Processing 1 images image shape: (280, 320, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 129.57500 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 2 time for calcul the mask position with numpy : 3.838539123535156e-05 nb_pixel_total : 308 time to create 1 rle with old method : 0.00043845176696777344 length of segment : 17 time for calcul the mask position with numpy : 3.647804260253906e-05 nb_pixel_total : 401 time to create 1 rle with old method : 0.0005881786346435547 length of segment : 26 NEW PHOTO pour l'instant on ne peut pas sauvegarder la photo dans les tile Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -117.25859 max: 145.10391 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 5 time for calcul the mask position with numpy : 4.124641418457031e-05 nb_pixel_total : 341 time to create 1 rle with old method : 0.0004813671112060547 length of segment : 36 time for calcul the mask position with numpy : 3.123283386230469e-05 nb_pixel_total : 5 time to create 1 rle with old method : 0.00010013580322265625 length of segment : 3 time for calcul the mask position with numpy : 4.935264587402344e-05 nb_pixel_total : 994 time to create 1 rle with old method : 0.0013077259063720703 length of segment : 30 time for calcul the mask position with numpy : 4.410743713378906e-05 nb_pixel_total : 1110 time to create 1 rle with old method : 0.001573324203491211 length of segment : 31 time for calcul the mask position with numpy : 6.4849853515625e-05 nb_pixel_total : 1703 time to create 1 rle with old method : 0.002151966094970703 length of segment : 45 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -117.45781 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 9 time for calcul the mask position with numpy : 0.00026679039001464844 nb_pixel_total : 9955 time to create 1 rle with old method : 0.011385917663574219 length of segment : 385 time for calcul the mask position with numpy : 6.29425048828125e-05 nb_pixel_total : 858 time to create 1 rle with old method : 0.00113677978515625 length of segment : 37 time for calcul the mask position with numpy : 4.029273986816406e-05 nb_pixel_total : 555 time to create 1 rle with old method : 0.0008959770202636719 length of segment : 21 time for calcul the mask position with numpy : 3.933906555175781e-05 nb_pixel_total : 647 time to create 1 rle with old method : 0.0009834766387939453 length of segment : 21 time for calcul the mask position with numpy : 4.482269287109375e-05 nb_pixel_total : 848 time to create 1 rle with old method : 0.0010952949523925781 length of segment : 51 time for calcul the mask position with numpy : 2.9325485229492188e-05 nb_pixel_total : 63 time to create 1 rle with old method : 0.00010895729064941406 length of segment : 13 time for calcul the mask position with numpy : 3.409385681152344e-05 nb_pixel_total : 258 time to create 1 rle with old method : 0.0003769397735595703 length of segment : 40 time for calcul the mask position with numpy : 4.267692565917969e-05 nb_pixel_total : 735 time to create 1 rle with old method : 0.0009891986846923828 length of segment : 58 time for calcul the mask position with numpy : 4.1484832763671875e-05 nb_pixel_total : 686 time to create 1 rle with old method : 0.0010352134704589844 length of segment : 21 Processing 1 images image shape: (400, 400, 3) min: 16.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -88.29766 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 2 time for calcul the mask position with numpy : 8.487701416015625e-05 nb_pixel_total : 4116 time to create 1 rle with old method : 0.005210399627685547 length of segment : 136 time for calcul the mask position with numpy : 3.814697265625e-05 nb_pixel_total : 420 time to create 1 rle with old method : 0.0006456375122070312 length of segment : 14 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -118.08672 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 7 time for calcul the mask position with numpy : 0.0001227855682373047 nb_pixel_total : 6573 time to create 1 rle with old method : 0.007742166519165039 length of segment : 165 time for calcul the mask position with numpy : 0.0001239776611328125 nb_pixel_total : 4263 time to create 1 rle with old method : 0.005332231521606445 length of segment : 193 time for calcul the mask position with numpy : 4.792213439941406e-05 nb_pixel_total : 352 time to create 1 rle with old method : 0.0006191730499267578 length of segment : 21 time for calcul the mask position with numpy : 3.1948089599609375e-05 nb_pixel_total : 84 time to create 1 rle with old method : 0.00013947486877441406 length of segment : 12 time for calcul the mask position with numpy : 3.647804260253906e-05 nb_pixel_total : 284 time to create 1 rle with old method : 0.00041604042053222656 length of segment : 37 time for calcul the mask position with numpy : 3.1948089599609375e-05 nb_pixel_total : 255 time to create 1 rle with old method : 0.0003733634948730469 length of segment : 23 time for calcul the mask position with numpy : 3.743171691894531e-05 nb_pixel_total : 449 time to create 1 rle with old method : 0.0006139278411865234 length of segment : 25 Processing 1 images image shape: (400, 320, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 134.86953 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 4 time for calcul the mask position with numpy : 4.1484832763671875e-05 nb_pixel_total : 495 time to create 1 rle with old method : 0.0007259845733642578 length of segment : 22 time for calcul the mask position with numpy : 8.440017700195312e-05 nb_pixel_total : 3626 time to create 1 rle with old method : 0.005279541015625 length of segment : 59 time for calcul the mask position with numpy : 5.698204040527344e-05 nb_pixel_total : 1370 time to create 1 rle with old method : 0.0017008781433105469 length of segment : 50 time for calcul the mask position with numpy : 0.0006127357482910156 nb_pixel_total : 51796 time to create 1 rle with old method : 0.06075453758239746 length of segment : 316 Processing 1 images image shape: (400, 400, 3) min: 26.00000 max: 203.00000 molded_images shape: (1, 640, 640, 3) min: -82.96563 max: 83.81875 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 1 time for calcul the mask position with numpy : 0.001338958740234375 nb_pixel_total : 152406 time to create 1 rle with new method : 0.0018270015716552734 length of segment : 401 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -119.02813 max: 140.85391 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 12 time for calcul the mask position with numpy : 5.793571472167969e-05 nb_pixel_total : 1289 time to create 1 rle with old method : 0.0019183158874511719 length of segment : 51 time for calcul the mask position with numpy : 5.221366882324219e-05 nb_pixel_total : 161 time to create 1 rle with old method : 0.00040078163146972656 length of segment : 10 time for calcul the mask position with numpy : 3.814697265625e-05 nb_pixel_total : 247 time to create 1 rle with old method : 0.0003898143768310547 length of segment : 19 time for calcul the mask position with numpy : 3.933906555175781e-05 nb_pixel_total : 501 time to create 1 rle with old method : 0.0006763935089111328 length of segment : 31 time for calcul the mask position with numpy : 3.981590270996094e-05 nb_pixel_total : 547 time to create 1 rle with old method : 0.0007801055908203125 length of segment : 21 time for calcul the mask position with numpy : 8.20159912109375e-05 nb_pixel_total : 2582 time to create 1 rle with old method : 0.0033130645751953125 length of segment : 77 time for calcul the mask position with numpy : 3.337860107421875e-05 nb_pixel_total : 181 time to create 1 rle with old method : 0.0003173351287841797 length of segment : 19 time for calcul the mask position with numpy : 4.029273986816406e-05 nb_pixel_total : 598 time to create 1 rle with old method : 0.0008208751678466797 length of segment : 24 time for calcul the mask position with numpy : 3.981590270996094e-05 nb_pixel_total : 800 time to create 1 rle with old method : 0.0011026859283447266 length of segment : 27 time for calcul the mask position with numpy : 3.24249267578125e-05 nb_pixel_total : 203 time to create 1 rle with old method : 0.00035119056701660156 length of segment : 21 time for calcul the mask position with numpy : 3.62396240234375e-05 nb_pixel_total : 447 time to create 1 rle with old method : 0.0006196498870849609 length of segment : 20 time for calcul the mask position with numpy : 3.361701965332031e-05 nb_pixel_total : 291 time to create 1 rle with old method : 0.0005116462707519531 length of segment : 13 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -117.25078 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 7 time for calcul the mask position with numpy : 6.0558319091796875e-05 nb_pixel_total : 1695 time to create 1 rle with old method : 0.0021445751190185547 length of segment : 43 time for calcul the mask position with numpy : 6.127357482910156e-05 nb_pixel_total : 2372 time to create 1 rle with old method : 0.0032455921173095703 length of segment : 37 time for calcul the mask position with numpy : 2.9802322387695312e-05 nb_pixel_total : 84 time to create 1 rle with old method : 0.00016546249389648438 length of segment : 7 time for calcul the mask position with numpy : 6.532669067382812e-05 nb_pixel_total : 2507 time to create 1 rle with old method : 0.0031697750091552734 length of segment : 64 time for calcul the mask position with numpy : 3.170967102050781e-05 nb_pixel_total : 200 time to create 1 rle with old method : 0.0003285408020019531 length of segment : 14 time for calcul the mask position with numpy : 3.5762786865234375e-05 nb_pixel_total : 626 time to create 1 rle with old method : 0.0008127689361572266 length of segment : 28 time for calcul the mask position with numpy : 4.792213439941406e-05 nb_pixel_total : 920 time to create 1 rle with old method : 0.0013384819030761719 length of segment : 48 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -110.22734 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 7 time for calcul the mask position with numpy : 5.91278076171875e-05 nb_pixel_total : 1239 time to create 1 rle with old method : 0.0017292499542236328 length of segment : 41 time for calcul the mask position with numpy : 3.361701965332031e-05 nb_pixel_total : 169 time to create 1 rle with old method : 0.00026297569274902344 length of segment : 17 time for calcul the mask position with numpy : 3.170967102050781e-05 nb_pixel_total : 202 time to create 1 rle with old method : 0.0003216266632080078 length of segment : 14 time for calcul the mask position with numpy : 4.315376281738281e-05 nb_pixel_total : 818 time to create 1 rle with old method : 0.0010638236999511719 length of segment : 37 time for calcul the mask position with numpy : 7.390975952148438e-05 nb_pixel_total : 1376 time to create 1 rle with old method : 0.0017657279968261719 length of segment : 112 time for calcul the mask position with numpy : 9.799003601074219e-05 nb_pixel_total : 1159 time to create 1 rle with old method : 0.0014727115631103516 length of segment : 118 time for calcul the mask position with numpy : 6.079673767089844e-05 nb_pixel_total : 1260 time to create 1 rle with old method : 0.0015687942504882812 length of segment : 115 Processing 1 images image shape: (400, 320, 3) min: 0.00000 max: 236.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 109.96719 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 7 time for calcul the mask position with numpy : 0.00014543533325195312 nb_pixel_total : 3367 time to create 1 rle with old method : 0.004314899444580078 length of segment : 186 time for calcul the mask position with numpy : 3.457069396972656e-05 nb_pixel_total : 57 time to create 1 rle with old method : 9.965896606445312e-05 length of segment : 14 time for calcul the mask position with numpy : 4.220008850097656e-05 nb_pixel_total : 788 time to create 1 rle with old method : 0.001096487045288086 length of segment : 30 time for calcul the mask position with numpy : 5.9604644775390625e-05 nb_pixel_total : 1205 time to create 1 rle with old method : 0.0015692710876464844 length of segment : 79 time for calcul the mask position with numpy : 3.6716461181640625e-05 nb_pixel_total : 298 time to create 1 rle with old method : 0.0004324913024902344 length of segment : 44 time for calcul the mask position with numpy : 3.4332275390625e-05 nb_pixel_total : 265 time to create 1 rle with old method : 0.0003707408905029297 length of segment : 39 time for calcul the mask position with numpy : 6.246566772460938e-05 nb_pixel_total : 1437 time to create 1 rle with old method : 0.0019404888153076172 length of segment : 81 Processing 1 images image shape: (280, 400, 3) min: 32.00000 max: 207.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 89.13125 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 1 time for calcul the mask position with numpy : 0.0008997917175292969 nb_pixel_total : 106267 time to create 1 rle with old method : 0.1143333911895752 length of segment : 280 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 144.94375 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 8 time for calcul the mask position with numpy : 4.1961669921875e-05 nb_pixel_total : 282 time to create 1 rle with old method : 0.0004265308380126953 length of segment : 24 time for calcul the mask position with numpy : 7.128715515136719e-05 nb_pixel_total : 2552 time to create 1 rle with old method : 0.003182649612426758 length of segment : 74 time for calcul the mask position with numpy : 6.103515625e-05 nb_pixel_total : 1621 time to create 1 rle with old method : 0.0021326541900634766 length of segment : 42 time for calcul the mask position with numpy : 3.743171691894531e-05 nb_pixel_total : 245 time to create 1 rle with old method : 0.0003871917724609375 length of segment : 13 time for calcul the mask position with numpy : 4.76837158203125e-05 nb_pixel_total : 955 time to create 1 rle with old method : 0.001245260238647461 length of segment : 37 time for calcul the mask position with numpy : 6.103515625e-05 nb_pixel_total : 1545 time to create 1 rle with old method : 0.0019884109497070312 length of segment : 65 time for calcul the mask position with numpy : 3.3855438232421875e-05 nb_pixel_total : 198 time to create 1 rle with old method : 0.0003197193145751953 length of segment : 17 time for calcul the mask position with numpy : 0.00011205673217773438 nb_pixel_total : 7308 time to create 1 rle with old method : 0.008956670761108398 length of segment : 76 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 130.79531 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 4 time for calcul the mask position with numpy : 4.0531158447265625e-05 nb_pixel_total : 397 time to create 1 rle with old method : 0.0005877017974853516 length of segment : 19 time for calcul the mask position with numpy : 2.9087066650390625e-05 nb_pixel_total : 54 time to create 1 rle with old method : 0.0001068115234375 length of segment : 8 time for calcul the mask position with numpy : 3.0040740966796875e-05 nb_pixel_total : 116 time to create 1 rle with old method : 0.00017881393432617188 length of segment : 18 time for calcul the mask position with numpy : 4.00543212890625e-05 nb_pixel_total : 610 time to create 1 rle with old method : 0.0009074211120605469 length of segment : 48 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 150.22891 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 8 time for calcul the mask position with numpy : 4.315376281738281e-05 nb_pixel_total : 370 time to create 1 rle with old method : 0.0005440711975097656 length of segment : 39 time for calcul the mask position with numpy : 3.170967102050781e-05 nb_pixel_total : 141 time to create 1 rle with old method : 0.0002124309539794922 length of segment : 27 time for calcul the mask position with numpy : 3.147125244140625e-05 nb_pixel_total : 194 time to create 1 rle with old method : 0.0002741813659667969 length of segment : 23 time for calcul the mask position with numpy : 3.886222839355469e-05 nb_pixel_total : 421 time to create 1 rle with old method : 0.000751495361328125 length of segment : 23 time for calcul the mask position with numpy : 7.081031799316406e-05 nb_pixel_total : 3322 time to create 1 rle with old method : 0.004252195358276367 length of segment : 91 length of segment : 0 time for calcul the mask position with numpy : 7.200241088867188e-05 nb_pixel_total : 3264 time to create 1 rle with old method : 0.004050493240356445 length of segment : 93 time for calcul the mask position with numpy : 3.4809112548828125e-05 nb_pixel_total : 323 time to create 1 rle with old method : 0.0004680156707763672 length of segment : 23 Processing 1 images image shape: (280, 320, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 130.51250 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 3 time for calcul the mask position with numpy : 3.8623809814453125e-05 nb_pixel_total : 311 time to create 1 rle with old method : 0.0004329681396484375 length of segment : 17 time for calcul the mask position with numpy : 3.504753112792969e-05 nb_pixel_total : 378 time to create 1 rle with old method : 0.0005688667297363281 length of segment : 24 time for calcul the mask position with numpy : 3.266334533691406e-05 nb_pixel_total : 309 time to create 1 rle with old method : 0.00043964385986328125 length of segment : 23 NEW PHOTO pour l'instant on ne peut pas sauvegarder la photo dans les tile Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -117.94219 max: 145.13125 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 7 time for calcul the mask position with numpy : 3.981590270996094e-05 nb_pixel_total : 330 time to create 1 rle with old method : 0.00045490264892578125 length of segment : 29 length of segment : 0 time for calcul the mask position with numpy : 4.291534423828125e-05 nb_pixel_total : 999 time to create 1 rle with old method : 0.0013339519500732422 length of segment : 39 length of segment : 0 time for calcul the mask position with numpy : 4.172325134277344e-05 nb_pixel_total : 1041 time to create 1 rle with old method : 0.0013327598571777344 length of segment : 37 time for calcul the mask position with numpy : 5.14984130859375e-05 nb_pixel_total : 1813 time to create 1 rle with old method : 0.002364635467529297 length of segment : 38 time for calcul the mask position with numpy : 9.632110595703125e-05 nb_pixel_total : 3141 time to create 1 rle with old method : 0.003946542739868164 length of segment : 89 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -117.21563 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 5 time for calcul the mask position with numpy : 4.601478576660156e-05 nb_pixel_total : 836 time to create 1 rle with old method : 0.0010290145874023438 length of segment : 36 time for calcul the mask position with numpy : 4.1961669921875e-05 nb_pixel_total : 763 time to create 1 rle with old method : 0.0011773109436035156 length of segment : 24 time for calcul the mask position with numpy : 0.00018548965454101562 nb_pixel_total : 1985 time to create 1 rle with old method : 0.002544403076171875 length of segment : 131 time for calcul the mask position with numpy : 3.62396240234375e-05 nb_pixel_total : 240 time to create 1 rle with old method : 0.0004191398620605469 length of segment : 32 time for calcul the mask position with numpy : 3.3855438232421875e-05 nb_pixel_total : 303 time to create 1 rle with old method : 0.00040411949157714844 length of segment : 37 Processing 1 images image shape: (400, 400, 3) min: 28.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -84.19219 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 3 time for calcul the mask position with numpy : 0.00010800361633300781 nb_pixel_total : 6366 time to create 1 rle with old method : 0.007237911224365234 length of segment : 117 time for calcul the mask position with numpy : 8.416175842285156e-05 nb_pixel_total : 2024 time to create 1 rle with old method : 0.002552509307861328 length of segment : 121 time for calcul the mask position with numpy : 7.963180541992188e-05 nb_pixel_total : 3737 time to create 1 rle with old method : 0.004559993743896484 length of segment : 108 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -118.36797 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 8 time for calcul the mask position with numpy : 4.6253204345703125e-05 nb_pixel_total : 403 time to create 1 rle with old method : 0.0006785392761230469 length of segment : 21 time for calcul the mask position with numpy : 0.00011563301086425781 nb_pixel_total : 3714 time to create 1 rle with old method : 0.004605770111083984 length of segment : 174 time for calcul the mask position with numpy : 0.00015997886657714844 nb_pixel_total : 7665 time to create 1 rle with old method : 0.00925588607788086 length of segment : 167 time for calcul the mask position with numpy : 4.792213439941406e-05 nb_pixel_total : 466 time to create 1 rle with old method : 0.0005965232849121094 length of segment : 25 time for calcul the mask position with numpy : 3.2901763916015625e-05 nb_pixel_total : 208 time to create 1 rle with old method : 0.0003018379211425781 length of segment : 21 time for calcul the mask position with numpy : 5.269050598144531e-05 nb_pixel_total : 1239 time to create 1 rle with old method : 0.0016148090362548828 length of segment : 70 time for calcul the mask position with numpy : 3.0994415283203125e-05 nb_pixel_total : 90 time to create 1 rle with old method : 0.000152587890625 length of segment : 14 time for calcul the mask position with numpy : 0.00011515617370605469 nb_pixel_total : 6725 time to create 1 rle with old method : 0.008350372314453125 length of segment : 145 Processing 1 images image shape: (400, 320, 3) min: 0.00000 max: 253.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 126.77187 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 3 time for calcul the mask position with numpy : 5.14984130859375e-05 nb_pixel_total : 543 time to create 1 rle with old method : 0.000762939453125 length of segment : 21 time for calcul the mask position with numpy : 4.601478576660156e-05 nb_pixel_total : 527 time to create 1 rle with old method : 0.0008082389831542969 length of segment : 58 time for calcul the mask position with numpy : 0.0005183219909667969 nb_pixel_total : 47852 time to create 1 rle with old method : 0.05664229393005371 length of segment : 322 Processing 1 images image shape: (400, 400, 3) min: 27.00000 max: 196.00000 molded_images shape: (1, 640, 640, 3) min: -78.57109 max: 73.45547 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 1 time for calcul the mask position with numpy : 0.001293182373046875 nb_pixel_total : 151020 time to create 1 rle with new method : 0.0018918514251708984 length of segment : 394 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -120.23906 max: 133.84453 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 13 time for calcul the mask position with numpy : 4.1484832763671875e-05 nb_pixel_total : 169 time to create 1 rle with old method : 0.00029015541076660156 length of segment : 10 time for calcul the mask position with numpy : 5.650520324707031e-05 nb_pixel_total : 1208 time to create 1 rle with old method : 0.0014994144439697266 length of segment : 50 time for calcul the mask position with numpy : 3.337860107421875e-05 nb_pixel_total : 258 time to create 1 rle with old method : 0.0003809928894042969 length of segment : 19 time for calcul the mask position with numpy : 3.7670135498046875e-05 nb_pixel_total : 535 time to create 1 rle with old method : 0.0006995201110839844 length of segment : 32 time for calcul the mask position with numpy : 3.3855438232421875e-05 nb_pixel_total : 207 time to create 1 rle with old method : 0.00035071372985839844 length of segment : 21 time for calcul the mask position with numpy : 0.00011229515075683594 nb_pixel_total : 5435 time to create 1 rle with old method : 0.007004976272583008 length of segment : 92 time for calcul the mask position with numpy : 5.1021575927734375e-05 nb_pixel_total : 1259 time to create 1 rle with old method : 0.0016608238220214844 length of segment : 32 time for calcul the mask position with numpy : 4.124641418457031e-05 nb_pixel_total : 792 time to create 1 rle with old method : 0.001173257827758789 length of segment : 27 time for calcul the mask position with numpy : 3.600120544433594e-05 nb_pixel_total : 329 time to create 1 rle with old method : 0.0004894733428955078 length of segment : 30 time for calcul the mask position with numpy : 3.886222839355469e-05 nb_pixel_total : 549 time to create 1 rle with old method : 0.0008039474487304688 length of segment : 27 time for calcul the mask position with numpy : 3.886222839355469e-05 nb_pixel_total : 477 time to create 1 rle with old method : 0.0007314682006835938 length of segment : 23 time for calcul the mask position with numpy : 3.600120544433594e-05 nb_pixel_total : 435 time to create 1 rle with old method : 0.003942728042602539 length of segment : 20 time for calcul the mask position with numpy : 6.151199340820312e-05 nb_pixel_total : 342 time to create 1 rle with old method : 0.0005741119384765625 length of segment : 16 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -114.81328 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 5 time for calcul the mask position with numpy : 3.62396240234375e-05 nb_pixel_total : 104 time to create 1 rle with old method : 0.0001850128173828125 length of segment : 8 time for calcul the mask position with numpy : 5.1021575927734375e-05 nb_pixel_total : 1483 time to create 1 rle with old method : 0.001987934112548828 length of segment : 42 time for calcul the mask position with numpy : 5.14984130859375e-05 nb_pixel_total : 1689 time to create 1 rle with old method : 0.0023887157440185547 length of segment : 27 time for calcul the mask position with numpy : 0.00013065338134765625 nb_pixel_total : 6982 time to create 1 rle with old method : 0.008755207061767578 length of segment : 109 time for calcul the mask position with numpy : 4.601478576660156e-05 nb_pixel_total : 711 time to create 1 rle with old method : 0.0009353160858154297 length of segment : 66 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -115.95391 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 10 time for calcul the mask position with numpy : 4.076957702636719e-05 nb_pixel_total : 169 time to create 1 rle with old method : 0.00026607513427734375 length of segment : 17 time for calcul the mask position with numpy : 3.0517578125e-05 nb_pixel_total : 113 time to create 1 rle with old method : 0.00021266937255859375 length of segment : 15 time for calcul the mask position with numpy : 8.654594421386719e-05 nb_pixel_total : 1516 time to create 1 rle with old method : 0.0019428730010986328 length of segment : 139 time for calcul the mask position with numpy : 3.170967102050781e-05 nb_pixel_total : 100 time to create 1 rle with old method : 0.00017571449279785156 length of segment : 12 time for calcul the mask position with numpy : 5.6743621826171875e-05 nb_pixel_total : 1265 time to create 1 rle with old method : 0.0018112659454345703 length of segment : 43 time for calcul the mask position with numpy : 2.9087066650390625e-05 nb_pixel_total : 35 time to create 1 rle with old method : 7.486343383789062e-05 length of segment : 8 time for calcul the mask position with numpy : 6.818771362304688e-05 nb_pixel_total : 1339 time to create 1 rle with old method : 0.0016748905181884766 length of segment : 114 time for calcul the mask position with numpy : 4.57763671875e-05 nb_pixel_total : 824 time to create 1 rle with old method : 0.0010492801666259766 length of segment : 38 time for calcul the mask position with numpy : 3.62396240234375e-05 nb_pixel_total : 721 time to create 1 rle with old method : 0.0009298324584960938 length of segment : 36 time for calcul the mask position with numpy : 5.221366882324219e-05 nb_pixel_total : 1183 time to create 1 rle with old method : 0.0015218257904052734 length of segment : 41 Processing 1 images image shape: (400, 320, 3) min: 0.00000 max: 250.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 118.54922 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 9 time for calcul the mask position with numpy : 0.00014638900756835938 nb_pixel_total : 3168 time to create 1 rle with old method : 0.004033565521240234 length of segment : 188 time for calcul the mask position with numpy : 4.124641418457031e-05 nb_pixel_total : 348 time to create 1 rle with old method : 0.0005102157592773438 length of segment : 47 time for calcul the mask position with numpy : 4.410743713378906e-05 nb_pixel_total : 759 time to create 1 rle with old method : 0.0010318756103515625 length of segment : 29 time for calcul the mask position with numpy : 3.4809112548828125e-05 nb_pixel_total : 357 time to create 1 rle with old method : 0.0004901885986328125 length of segment : 37 time for calcul the mask position with numpy : 3.337860107421875e-05 nb_pixel_total : 189 time to create 1 rle with old method : 0.00026535987854003906 length of segment : 38 time for calcul the mask position with numpy : 2.7894973754882812e-05 nb_pixel_total : 53 time to create 1 rle with old method : 9.560585021972656e-05 length of segment : 12 time for calcul the mask position with numpy : 3.075599670410156e-05 nb_pixel_total : 166 time to create 1 rle with old method : 0.00024890899658203125 length of segment : 29 time for calcul the mask position with numpy : 5.3882598876953125e-05 nb_pixel_total : 640 time to create 1 rle with old method : 0.0009772777557373047 length of segment : 74 time for calcul the mask position with numpy : 3.933906555175781e-05 nb_pixel_total : 668 time to create 1 rle with old method : 0.0008175373077392578 length of segment : 40 Processing 1 images image shape: (280, 400, 3) min: 22.00000 max: 207.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 86.01406 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 1 time for calcul the mask position with numpy : 0.0015139579772949219 nb_pixel_total : 105864 time to create 1 rle with old method : 0.11693406105041504 length of segment : 280 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 147.76016 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 9 time for calcul the mask position with numpy : 5.53131103515625e-05 nb_pixel_total : 1514 time to create 1 rle with old method : 0.0020148754119873047 length of segment : 41 time for calcul the mask position with numpy : 3.2901763916015625e-05 nb_pixel_total : 267 time to create 1 rle with old method : 0.0004150867462158203 length of segment : 13 time for calcul the mask position with numpy : 3.266334533691406e-05 nb_pixel_total : 216 time to create 1 rle with old method : 0.0003209114074707031 length of segment : 22 time for calcul the mask position with numpy : 6.318092346191406e-05 nb_pixel_total : 2013 time to create 1 rle with old method : 0.002546072006225586 length of segment : 79 time for calcul the mask position with numpy : 3.24249267578125e-05 nb_pixel_total : 127 time to create 1 rle with old method : 0.00021767616271972656 length of segment : 17 time for calcul the mask position with numpy : 4.0531158447265625e-05 nb_pixel_total : 844 time to create 1 rle with old method : 0.0010945796966552734 length of segment : 35 time for calcul the mask position with numpy : 0.0001690387725830078 nb_pixel_total : 9535 time to create 1 rle with old method : 0.011293411254882812 length of segment : 155 time for calcul the mask position with numpy : 4.267692565917969e-05 nb_pixel_total : 261 time to create 1 rle with old method : 0.00036144256591796875 length of segment : 50 time for calcul the mask position with numpy : 0.00012063980102539062 nb_pixel_total : 7479 time to create 1 rle with old method : 0.009313106536865234 length of segment : 79 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 135.84219 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 3 time for calcul the mask position with numpy : 4.553794860839844e-05 nb_pixel_total : 274 time to create 1 rle with old method : 0.0004742145538330078 length of segment : 16 time for calcul the mask position with numpy : 3.504753112792969e-05 nb_pixel_total : 441 time to create 1 rle with old method : 0.000667572021484375 length of segment : 20 time for calcul the mask position with numpy : 2.7894973754882812e-05 nb_pixel_total : 44 time to create 1 rle with old method : 8.749961853027344e-05 length of segment : 6 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 150.08437 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 11 time for calcul the mask position with numpy : 6.008148193359375e-05 nb_pixel_total : 317 time to create 1 rle with old method : 0.0006160736083984375 length of segment : 31 time for calcul the mask position with numpy : 4.076957702636719e-05 nb_pixel_total : 137 time to create 1 rle with old method : 0.0002665519714355469 length of segment : 29 time for calcul the mask position with numpy : 4.124641418457031e-05 nb_pixel_total : 172 time to create 1 rle with old method : 0.00034499168395996094 length of segment : 23 time for calcul the mask position with numpy : 5.173683166503906e-05 nb_pixel_total : 580 time to create 1 rle with old method : 0.0011374950408935547 length of segment : 55 time for calcul the mask position with numpy : 4.220008850097656e-05 nb_pixel_total : 302 time to create 1 rle with old method : 0.0006170272827148438 length of segment : 33 time for calcul the mask position with numpy : 0.00012922286987304688 nb_pixel_total : 613 time to create 1 rle with old method : 0.0009686946868896484 length of segment : 60 time for calcul the mask position with numpy : 3.4332275390625e-05 nb_pixel_total : 328 time to create 1 rle with old method : 0.0004889965057373047 length of segment : 25 time for calcul the mask position with numpy : 4.673004150390625e-05 nb_pixel_total : 999 time to create 1 rle with old method : 0.0013322830200195312 length of segment : 88 time for calcul the mask position with numpy : 7.009506225585938e-05 nb_pixel_total : 3058 time to create 1 rle with old method : 0.0037190914154052734 length of segment : 84 time for calcul the mask position with numpy : 4.076957702636719e-05 nb_pixel_total : 15 time to create 1 rle with old method : 5.054473876953125e-05 length of segment : 4 time for calcul the mask position with numpy : 0.00015926361083984375 nb_pixel_total : 1497 time to create 1 rle with old method : 0.0018978118896484375 length of segment : 157 Processing 1 images image shape: (280, 320, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 129.26250 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 3 time for calcul the mask position with numpy : 3.981590270996094e-05 nb_pixel_total : 306 time to create 1 rle with old method : 0.0004525184631347656 length of segment : 16 time for calcul the mask position with numpy : 3.600120544433594e-05 nb_pixel_total : 378 time to create 1 rle with old method : 0.0006275177001953125 length of segment : 24 time for calcul the mask position with numpy : 0.0005030632019042969 nb_pixel_total : 44179 time to create 1 rle with old method : 0.050145626068115234 length of segment : 277 NEW PHOTO pour l'instant on ne peut pas sauvegarder la photo dans les tile Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -117.43828 max: 145.20547 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 6 time for calcul the mask position with numpy : 4.458427429199219e-05 nb_pixel_total : 262 time to create 1 rle with old method : 0.0003693103790283203 length of segment : 27 time for calcul the mask position with numpy : 5.054473876953125e-05 nb_pixel_total : 1 time to create 1 rle with old method : 2.0265579223632812e-05 length of segment : 1 time for calcul the mask position with numpy : 5.936622619628906e-05 nb_pixel_total : 890 time to create 1 rle with old method : 0.0014066696166992188 length of segment : 46 time for calcul the mask position with numpy : 5.030632019042969e-05 nb_pixel_total : 985 time to create 1 rle with old method : 0.001575469970703125 length of segment : 42 length of segment : 0 length of segment : 0 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -118.21172 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 5 time for calcul the mask position with numpy : 5.1975250244140625e-05 nb_pixel_total : 748 time to create 1 rle with old method : 0.0011107921600341797 length of segment : 22 time for calcul the mask position with numpy : 5.412101745605469e-05 nb_pixel_total : 981 time to create 1 rle with old method : 0.0013911724090576172 length of segment : 54 time for calcul the mask position with numpy : 4.220008850097656e-05 nb_pixel_total : 580 time to create 1 rle with old method : 0.0008156299591064453 length of segment : 57 time for calcul the mask position with numpy : 0.00021386146545410156 nb_pixel_total : 3712 time to create 1 rle with old method : 0.004781961441040039 length of segment : 157 time for calcul the mask position with numpy : 3.457069396972656e-05 nb_pixel_total : 54 time to create 1 rle with old method : 0.0001838207244873047 length of segment : 11 Processing 1 images image shape: (400, 400, 3) min: 27.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -96.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 4 time for calcul the mask position with numpy : 8.273124694824219e-05 nb_pixel_total : 2819 time to create 1 rle with old method : 0.0034682750701904297 length of segment : 178 time for calcul the mask position with numpy : 3.814697265625e-05 nb_pixel_total : 185 time to create 1 rle with old method : 0.00031948089599609375 length of segment : 19 time for calcul the mask position with numpy : 3.409385681152344e-05 nb_pixel_total : 86 time to create 1 rle with old method : 0.00023055076599121094 length of segment : 13 time for calcul the mask position with numpy : 4.649162292480469e-05 nb_pixel_total : 415 time to create 1 rle with old method : 0.0005860328674316406 length of segment : 23 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -120.51250 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 5 time for calcul the mask position with numpy : 4.673004150390625e-05 nb_pixel_total : 345 time to create 1 rle with old method : 0.0006031990051269531 length of segment : 20 time for calcul the mask position with numpy : 0.00010418891906738281 nb_pixel_total : 3769 time to create 1 rle with old method : 0.004857778549194336 length of segment : 199 time for calcul the mask position with numpy : 0.00012993812561035156 nb_pixel_total : 6762 time to create 1 rle with old method : 0.008411884307861328 length of segment : 152 time for calcul the mask position with numpy : 3.981590270996094e-05 nb_pixel_total : 395 time to create 1 rle with old method : 0.0005624294281005859 length of segment : 23 time for calcul the mask position with numpy : 3.504753112792969e-05 nb_pixel_total : 273 time to create 1 rle with old method : 0.00038170814514160156 length of segment : 24 Processing 1 images image shape: (400, 320, 3) min: 0.00000 max: 245.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 113.80703 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 3 time for calcul the mask position with numpy : 5.650520324707031e-05 nb_pixel_total : 523 time to create 1 rle with old method : 0.001007080078125 length of segment : 23 time for calcul the mask position with numpy : 5.4836273193359375e-05 nb_pixel_total : 561 time to create 1 rle with old method : 0.0011110305786132812 length of segment : 35 time for calcul the mask position with numpy : 0.0006616115570068359 nb_pixel_total : 47826 time to create 1 rle with old method : 0.07786893844604492 length of segment : 305 Processing 1 images image shape: (400, 400, 3) min: 30.00000 max: 193.00000 molded_images shape: (1, 640, 640, 3) min: -83.98906 max: 75.89297 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 1 time for calcul the mask position with numpy : 0.002226591110229492 nb_pixel_total : 149111 time to create 1 rle with old method : 0.20430684089660645 length of segment : 408 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -119.80547 max: 136.28359 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 12 time for calcul the mask position with numpy : 0.0001087188720703125 nb_pixel_total : 1290 time to create 1 rle with old method : 0.0025107860565185547 length of segment : 49 time for calcul the mask position with numpy : 6.127357482910156e-05 nb_pixel_total : 184 time to create 1 rle with old method : 0.00041985511779785156 length of segment : 9 time for calcul the mask position with numpy : 6.508827209472656e-05 nb_pixel_total : 233 time to create 1 rle with old method : 0.0005538463592529297 length of segment : 19 time for calcul the mask position with numpy : 7.43865966796875e-05 nb_pixel_total : 336 time to create 1 rle with old method : 0.0008242130279541016 length of segment : 31 time for calcul the mask position with numpy : 0.00019311904907226562 nb_pixel_total : 4328 time to create 1 rle with old method : 0.00834345817565918 length of segment : 125 time for calcul the mask position with numpy : 0.00010633468627929688 nb_pixel_total : 1006 time to create 1 rle with old method : 0.002051115036010742 length of segment : 28 time for calcul the mask position with numpy : 7.295608520507812e-05 nb_pixel_total : 454 time to create 1 rle with old method : 0.0011394023895263672 length of segment : 19 time for calcul the mask position with numpy : 7.104873657226562e-05 nb_pixel_total : 384 time to create 1 rle with old method : 0.0008499622344970703 length of segment : 18 time for calcul the mask position with numpy : 7.295608520507812e-05 nb_pixel_total : 394 time to create 1 rle with old method : 0.0009570121765136719 length of segment : 16 time for calcul the mask position with numpy : 8.177757263183594e-05 nb_pixel_total : 547 time to create 1 rle with old method : 0.001150369644165039 length of segment : 33 time for calcul the mask position with numpy : 6.079673767089844e-05 nb_pixel_total : 108 time to create 1 rle with old method : 0.0002841949462890625 length of segment : 10 time for calcul the mask position with numpy : 7.534027099609375e-05 nb_pixel_total : 537 time to create 1 rle with old method : 0.00110626220703125 length of segment : 32 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -117.65703 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 8 time for calcul the mask position with numpy : 6.961822509765625e-05 nb_pixel_total : 99 time to create 1 rle with old method : 0.0002865791320800781 length of segment : 10 time for calcul the mask position with numpy : 8.988380432128906e-05 nb_pixel_total : 1656 time to create 1 rle with old method : 0.003460407257080078 length of segment : 42 time for calcul the mask position with numpy : 9.012222290039062e-05 nb_pixel_total : 1690 time to create 1 rle with old method : 0.0035173892974853516 length of segment : 28 time for calcul the mask position with numpy : 6.198883056640625e-05 nb_pixel_total : 176 time to create 1 rle with old method : 0.0004057884216308594 length of segment : 15 time for calcul the mask position with numpy : 0.00038504600524902344 nb_pixel_total : 14642 time to create 1 rle with old method : 0.026706457138061523 length of segment : 136 time for calcul the mask position with numpy : 8.654594421386719e-05 nb_pixel_total : 228 time to create 1 rle with old method : 0.0004966259002685547 length of segment : 18 time for calcul the mask position with numpy : 0.00011849403381347656 nb_pixel_total : 1753 time to create 1 rle with old method : 0.003513813018798828 length of segment : 84 time for calcul the mask position with numpy : 5.698204040527344e-05 nb_pixel_total : 401 time to create 1 rle with old method : 0.0005753040313720703 length of segment : 58 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -115.22344 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 10 time for calcul the mask position with numpy : 8.511543273925781e-05 nb_pixel_total : 995 time to create 1 rle with old method : 0.0015442371368408203 length of segment : 98 time for calcul the mask position with numpy : 4.029273986816406e-05 nb_pixel_total : 179 time to create 1 rle with old method : 0.0002808570861816406 length of segment : 19 time for calcul the mask position with numpy : 3.123283386230469e-05 nb_pixel_total : 34 time to create 1 rle with old method : 7.462501525878906e-05 length of segment : 8 time for calcul the mask position with numpy : 0.00011849403381347656 nb_pixel_total : 3857 time to create 1 rle with old method : 0.005323886871337891 length of segment : 158 time for calcul the mask position with numpy : 8.940696716308594e-05 nb_pixel_total : 1439 time to create 1 rle with old method : 0.001964092254638672 length of segment : 43 time for calcul the mask position with numpy : 0.0004324913024902344 nb_pixel_total : 21832 time to create 1 rle with old method : 0.025951623916625977 length of segment : 314 time for calcul the mask position with numpy : 5.91278076171875e-05 nb_pixel_total : 757 time to create 1 rle with old method : 0.0010035037994384766 length of segment : 36 time for calcul the mask position with numpy : 7.605552673339844e-05 nb_pixel_total : 2565 time to create 1 rle with old method : 0.0033180713653564453 length of segment : 57 time for calcul the mask position with numpy : 4.076957702636719e-05 nb_pixel_total : 771 time to create 1 rle with old method : 0.000997304916381836 length of segment : 35 time for calcul the mask position with numpy : 5.817413330078125e-05 nb_pixel_total : 1363 time to create 1 rle with old method : 0.00189208984375 length of segment : 42 Processing 1 images image shape: (400, 320, 3) min: 0.00000 max: 250.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 124.64687 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 7 time for calcul the mask position with numpy : 4.57763671875e-05 nb_pixel_total : 520 time to create 1 rle with old method : 0.0006895065307617188 length of segment : 37 time for calcul the mask position with numpy : 3.170967102050781e-05 nb_pixel_total : 64 time to create 1 rle with old method : 0.00011157989501953125 length of segment : 15 time for calcul the mask position with numpy : 0.00016021728515625 nb_pixel_total : 3376 time to create 1 rle with old method : 0.004568338394165039 length of segment : 197 time for calcul the mask position with numpy : 4.100799560546875e-05 nb_pixel_total : 202 time to create 1 rle with old method : 0.00028514862060546875 length of segment : 31 time for calcul the mask position with numpy : 4.1484832763671875e-05 nb_pixel_total : 478 time to create 1 rle with old method : 0.0006458759307861328 length of segment : 44 time for calcul the mask position with numpy : 5.078315734863281e-05 nb_pixel_total : 1043 time to create 1 rle with old method : 0.001401662826538086 length of segment : 34 time for calcul the mask position with numpy : 4.482269287109375e-05 nb_pixel_total : 877 time to create 1 rle with old method : 0.001241445541381836 length of segment : 42 Processing 1 images image shape: (280, 400, 3) min: 24.00000 max: 201.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 83.58047 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 1 time for calcul the mask position with numpy : 0.0009214878082275391 nb_pixel_total : 106594 time to create 1 rle with old method : 0.11804699897766113 length of segment : 280 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 147.38906 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 9 time for calcul the mask position with numpy : 3.910064697265625e-05 nb_pixel_total : 161 time to create 1 rle with old method : 0.0002892017364501953 length of segment : 18 time for calcul the mask position with numpy : 3.2901763916015625e-05 nb_pixel_total : 219 time to create 1 rle with old method : 0.0003364086151123047 length of segment : 19 time for calcul the mask position with numpy : 5.316734313964844e-05 nb_pixel_total : 1517 time to create 1 rle with old method : 0.0019981861114501953 length of segment : 40 time for calcul the mask position with numpy : 3.457069396972656e-05 nb_pixel_total : 241 time to create 1 rle with old method : 0.0003905296325683594 length of segment : 18 time for calcul the mask position with numpy : 6.222724914550781e-05 nb_pixel_total : 1680 time to create 1 rle with old method : 0.002160787582397461 length of segment : 64 time for calcul the mask position with numpy : 0.00012254714965820312 nb_pixel_total : 7478 time to create 1 rle with old method : 0.008571147918701172 length of segment : 81 time for calcul the mask position with numpy : 4.458427429199219e-05 nb_pixel_total : 967 time to create 1 rle with old method : 0.0011947154998779297 length of segment : 37 time for calcul the mask position with numpy : 3.695487976074219e-05 nb_pixel_total : 411 time to create 1 rle with old method : 0.0005159378051757812 length of segment : 42 time for calcul the mask position with numpy : 3.409385681152344e-05 nb_pixel_total : 368 time to create 1 rle with old method : 0.00048613548278808594 length of segment : 38 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 130.89297 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 4 time for calcul the mask position with numpy : 4.935264587402344e-05 nb_pixel_total : 421 time to create 1 rle with old method : 0.0006029605865478516 length of segment : 19 time for calcul the mask position with numpy : 3.504753112792969e-05 nb_pixel_total : 263 time to create 1 rle with old method : 0.0003991127014160156 length of segment : 17 time for calcul the mask position with numpy : 3.361701965332031e-05 nb_pixel_total : 196 time to create 1 rle with old method : 0.00029277801513671875 length of segment : 21 time for calcul the mask position with numpy : 3.552436828613281e-05 nb_pixel_total : 406 time to create 1 rle with old method : 0.000598907470703125 length of segment : 21 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 149.70937 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 7 time for calcul the mask position with numpy : 5.2928924560546875e-05 nb_pixel_total : 521 time to create 1 rle with old method : 0.0008566379547119141 length of segment : 26 time for calcul the mask position with numpy : 3.504753112792969e-05 nb_pixel_total : 189 time to create 1 rle with old method : 0.00027179718017578125 length of segment : 23 time for calcul the mask position with numpy : 3.457069396972656e-05 nb_pixel_total : 322 time to create 1 rle with old method : 0.0004627704620361328 length of segment : 25 time for calcul the mask position with numpy : 4.2438507080078125e-05 nb_pixel_total : 598 time to create 1 rle with old method : 0.0009243488311767578 length of segment : 42 time for calcul the mask position with numpy : 3.2901763916015625e-05 nb_pixel_total : 114 time to create 1 rle with old method : 0.0002646446228027344 length of segment : 28 length of segment : 0 time for calcul the mask position with numpy : 3.457069396972656e-05 nb_pixel_total : 317 time to create 1 rle with old method : 0.00044727325439453125 length of segment : 23 Processing 1 images image shape: (280, 320, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 130.51250 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 2 time for calcul the mask position with numpy : 4.887580871582031e-05 nb_pixel_total : 384 time to create 1 rle with old method : 0.0005767345428466797 length of segment : 26 time for calcul the mask position with numpy : 3.457069396972656e-05 nb_pixel_total : 325 time to create 1 rle with old method : 0.00047016143798828125 length of segment : 17 NEW PHOTO pour l'instant on ne peut pas sauvegarder la photo dans les tile Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -117.39531 max: 145.11172 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 7 time for calcul the mask position with numpy : 4.029273986816406e-05 nb_pixel_total : 19 time to create 1 rle with old method : 5.6743621826171875e-05 length of segment : 8 time for calcul the mask position with numpy : 4.506111145019531e-05 nb_pixel_total : 1010 time to create 1 rle with old method : 0.0014142990112304688 length of segment : 43 time for calcul the mask position with numpy : 4.482269287109375e-05 nb_pixel_total : 910 time to create 1 rle with old method : 0.0012137889862060547 length of segment : 49 time for calcul the mask position with numpy : 3.4809112548828125e-05 nb_pixel_total : 291 time to create 1 rle with old method : 0.0004050731658935547 length of segment : 26 length of segment : 0 time for calcul the mask position with numpy : 4.00543212890625e-05 nb_pixel_total : 952 time to create 1 rle with old method : 0.0012636184692382812 length of segment : 37 time for calcul the mask position with numpy : 3.5762786865234375e-05 nb_pixel_total : 411 time to create 1 rle with old method : 0.0005354881286621094 length of segment : 30 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -118.21172 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 8 time for calcul the mask position with numpy : 0.00010466575622558594 nb_pixel_total : 790 time to create 1 rle with old method : 0.0014195442199707031 length of segment : 35 time for calcul the mask position with numpy : 5.698204040527344e-05 nb_pixel_total : 394 time to create 1 rle with old method : 0.0006659030914306641 length of segment : 42 time for calcul the mask position with numpy : 5.4836273193359375e-05 nb_pixel_total : 817 time to create 1 rle with old method : 0.0011303424835205078 length of segment : 46 time for calcul the mask position with numpy : 4.291534423828125e-05 nb_pixel_total : 155 time to create 1 rle with old method : 0.00026607513427734375 length of segment : 24 time for calcul the mask position with numpy : 4.696846008300781e-05 nb_pixel_total : 387 time to create 1 rle with old method : 0.0007014274597167969 length of segment : 17 time for calcul the mask position with numpy : 0.00026988983154296875 nb_pixel_total : 2076 time to create 1 rle with old method : 0.0027265548706054688 length of segment : 137 time for calcul the mask position with numpy : 6.866455078125e-05 nb_pixel_total : 282 time to create 1 rle with old method : 0.0004203319549560547 length of segment : 44 time for calcul the mask position with numpy : 7.390975952148438e-05 nb_pixel_total : 1043 time to create 1 rle with old method : 0.0014815330505371094 length of segment : 66 Processing 1 images image shape: (400, 400, 3) min: 21.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -83.94219 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 3 time for calcul the mask position with numpy : 0.00010538101196289062 nb_pixel_total : 6555 time to create 1 rle with old method : 0.007622718811035156 length of segment : 103 time for calcul the mask position with numpy : 7.867813110351562e-05 nb_pixel_total : 3314 time to create 1 rle with old method : 0.003979206085205078 length of segment : 146 time for calcul the mask position with numpy : 4.9591064453125e-05 nb_pixel_total : 724 time to create 1 rle with old method : 0.0009653568267822266 length of segment : 30 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -117.84453 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 5 time for calcul the mask position with numpy : 0.00012040138244628906 nb_pixel_total : 5627 time to create 1 rle with old method : 0.0067157745361328125 length of segment : 138 time for calcul the mask position with numpy : 4.2438507080078125e-05 nb_pixel_total : 317 time to create 1 rle with old method : 0.0005857944488525391 length of segment : 19 time for calcul the mask position with numpy : 8.392333984375e-05 nb_pixel_total : 2153 time to create 1 rle with old method : 0.0027692317962646484 length of segment : 198 time for calcul the mask position with numpy : 3.361701965332031e-05 nb_pixel_total : 99 time to create 1 rle with old method : 0.00016260147094726562 length of segment : 14 time for calcul the mask position with numpy : 6.890296936035156e-05 nb_pixel_total : 1849 time to create 1 rle with old method : 0.0023272037506103516 length of segment : 81 Processing 1 images image shape: (400, 320, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 136.88516 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 2 time for calcul the mask position with numpy : 5.054473876953125e-05 nb_pixel_total : 465 time to create 1 rle with old method : 0.0008189678192138672 length of segment : 19 time for calcul the mask position with numpy : 8.726119995117188e-05 nb_pixel_total : 2860 time to create 1 rle with old method : 0.004096508026123047 length of segment : 99 Processing 1 images image shape: (400, 400, 3) min: 24.00000 max: 196.00000 molded_images shape: (1, 640, 640, 3) min: -81.70391 max: 72.89297 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 1 time for calcul the mask position with numpy : 0.0012824535369873047 nb_pixel_total : 151991 time to create 1 rle with new method : 0.0018775463104248047 length of segment : 398 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -119.59844 max: 132.91484 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 12 time for calcul the mask position with numpy : 4.1484832763671875e-05 nb_pixel_total : 275 time to create 1 rle with old method : 0.00039958953857421875 length of segment : 19 time for calcul the mask position with numpy : 3.147125244140625e-05 nb_pixel_total : 187 time to create 1 rle with old method : 0.0003046989440917969 length of segment : 10 time for calcul the mask position with numpy : 4.8160552978515625e-05 nb_pixel_total : 1341 time to create 1 rle with old method : 0.0017504692077636719 length of segment : 49 time for calcul the mask position with numpy : 4.315376281738281e-05 nb_pixel_total : 992 time to create 1 rle with old method : 0.0014383792877197266 length of segment : 29 time for calcul the mask position with numpy : 9.822845458984375e-05 nb_pixel_total : 5328 time to create 1 rle with old method : 0.006299018859863281 length of segment : 82 time for calcul the mask position with numpy : 4.744529724121094e-05 nb_pixel_total : 285 time to create 1 rle with old method : 0.0005567073822021484 length of segment : 35 time for calcul the mask position with numpy : 3.62396240234375e-05 nb_pixel_total : 455 time to create 1 rle with old method : 0.0006880760192871094 length of segment : 23 time for calcul the mask position with numpy : 7.891654968261719e-05 nb_pixel_total : 3172 time to create 1 rle with old method : 0.003924846649169922 length of segment : 46 time for calcul the mask position with numpy : 3.4332275390625e-05 nb_pixel_total : 291 time to create 1 rle with old method : 0.0004596710205078125 length of segment : 13 time for calcul the mask position with numpy : 3.695487976074219e-05 nb_pixel_total : 532 time to create 1 rle with old method : 0.0007061958312988281 length of segment : 33 time for calcul the mask position with numpy : 3.695487976074219e-05 nb_pixel_total : 547 time to create 1 rle with old method : 0.0007002353668212891 length of segment : 32 time for calcul the mask position with numpy : 6.556510925292969e-05 nb_pixel_total : 2984 time to create 1 rle with old method : 0.004032611846923828 length of segment : 42 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -114.20000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 8 time for calcul the mask position with numpy : 3.600120544433594e-05 nb_pixel_total : 103 time to create 1 rle with old method : 0.0001914501190185547 length of segment : 9 time for calcul the mask position with numpy : 5.1975250244140625e-05 nb_pixel_total : 1581 time to create 1 rle with old method : 0.0021986961364746094 length of segment : 39 time for calcul the mask position with numpy : 3.147125244140625e-05 nb_pixel_total : 228 time to create 1 rle with old method : 0.0003542900085449219 length of segment : 15 time for calcul the mask position with numpy : 5.507469177246094e-05 nb_pixel_total : 1849 time to create 1 rle with old method : 0.0025358200073242188 length of segment : 31 time for calcul the mask position with numpy : 7.653236389160156e-05 nb_pixel_total : 1544 time to create 1 rle with old method : 0.0024025440216064453 length of segment : 33 time for calcul the mask position with numpy : 3.910064697265625e-05 nb_pixel_total : 437 time to create 1 rle with old method : 0.0005655288696289062 length of segment : 55 time for calcul the mask position with numpy : 0.0002129077911376953 nb_pixel_total : 13471 time to create 1 rle with old method : 0.016266345977783203 length of segment : 123 time for calcul the mask position with numpy : 4.363059997558594e-05 nb_pixel_total : 668 time to create 1 rle with old method : 0.0008742809295654297 length of segment : 29 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -116.44219 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 8 time for calcul the mask position with numpy : 0.00010609626770019531 nb_pixel_total : 4352 time to create 1 rle with old method : 0.005063295364379883 length of segment : 150 time for calcul the mask position with numpy : 6.0558319091796875e-05 nb_pixel_total : 1252 time to create 1 rle with old method : 0.0017523765563964844 length of segment : 43 time for calcul the mask position with numpy : 2.9325485229492188e-05 nb_pixel_total : 35 time to create 1 rle with old method : 7.510185241699219e-05 length of segment : 8 time for calcul the mask position with numpy : 4.029273986816406e-05 nb_pixel_total : 830 time to create 1 rle with old method : 0.0010263919830322266 length of segment : 38 time for calcul the mask position with numpy : 9.34600830078125e-05 nb_pixel_total : 1593 time to create 1 rle with old method : 0.0022058486938476562 length of segment : 143 time for calcul the mask position with numpy : 6.747245788574219e-05 nb_pixel_total : 1260 time to create 1 rle with old method : 0.00157928466796875 length of segment : 118 time for calcul the mask position with numpy : 3.3855438232421875e-05 nb_pixel_total : 141 time to create 1 rle with old method : 0.0002002716064453125 length of segment : 35 time for calcul the mask position with numpy : 3.7670135498046875e-05 nb_pixel_total : 814 time to create 1 rle with old method : 0.0009925365447998047 length of segment : 38 Processing 1 images image shape: (400, 320, 3) min: 0.00000 max: 244.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 121.17422 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 8 time for calcul the mask position with numpy : 0.000110626220703125 nb_pixel_total : 2150 time to create 1 rle with old method : 0.0028076171875 length of segment : 150 time for calcul the mask position with numpy : 0.00024390220642089844 nb_pixel_total : 3064 time to create 1 rle with old method : 0.0038194656372070312 length of segment : 178 time for calcul the mask position with numpy : 0.0001010894775390625 nb_pixel_total : 462 time to create 1 rle with old method : 0.0009202957153320312 length of segment : 37 time for calcul the mask position with numpy : 6.0558319091796875e-05 nb_pixel_total : 124 time to create 1 rle with old method : 0.00032639503479003906 length of segment : 20 time for calcul the mask position with numpy : 8.749961853027344e-05 nb_pixel_total : 879 time to create 1 rle with old method : 0.0019507408142089844 length of segment : 43 time for calcul the mask position with numpy : 5.054473876953125e-05 nb_pixel_total : 76 time to create 1 rle with old method : 0.00017523765563964844 length of segment : 14 time for calcul the mask position with numpy : 5.173683166503906e-05 nb_pixel_total : 321 time to create 1 rle with old method : 0.0005447864532470703 length of segment : 40 time for calcul the mask position with numpy : 5.316734313964844e-05 nb_pixel_total : 454 time to create 1 rle with old method : 0.0007736682891845703 length of segment : 39 Processing 1 images image shape: (280, 400, 3) min: 30.00000 max: 197.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 80.65469 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 1 time for calcul the mask position with numpy : 0.0009601116180419922 nb_pixel_total : 107083 time to create 1 rle with old method : 0.1177833080291748 length of segment : 282 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 143.18984 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 10 time for calcul the mask position with numpy : 6.079673767089844e-05 nb_pixel_total : 248 time to create 1 rle with old method : 0.0004999637603759766 length of segment : 20 time for calcul the mask position with numpy : 4.482269287109375e-05 nb_pixel_total : 198 time to create 1 rle with old method : 0.0004582405090332031 length of segment : 18 time for calcul the mask position with numpy : 8.344650268554688e-05 nb_pixel_total : 1676 time to create 1 rle with old method : 0.0028667449951171875 length of segment : 61 time for calcul the mask position with numpy : 7.700920104980469e-05 nb_pixel_total : 1581 time to create 1 rle with old method : 0.0028870105743408203 length of segment : 41 time for calcul the mask position with numpy : 5.8650970458984375e-05 nb_pixel_total : 448 time to create 1 rle with old method : 0.0007622241973876953 length of segment : 32 time for calcul the mask position with numpy : 3.409385681152344e-05 nb_pixel_total : 155 time to create 1 rle with old method : 0.00026106834411621094 length of segment : 15 time for calcul the mask position with numpy : 3.933906555175781e-05 nb_pixel_total : 387 time to create 1 rle with old method : 0.0005280971527099609 length of segment : 44 time for calcul the mask position with numpy : 4.4345855712890625e-05 nb_pixel_total : 335 time to create 1 rle with old method : 0.0005199909210205078 length of segment : 52 time for calcul the mask position with numpy : 0.000133514404296875 nb_pixel_total : 7503 time to create 1 rle with old method : 0.009089946746826172 length of segment : 80 time for calcul the mask position with numpy : 5.412101745605469e-05 nb_pixel_total : 913 time to create 1 rle with old method : 0.0012030601501464844 length of segment : 36 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 251.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 126.39297 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 2 time for calcul the mask position with numpy : 0.000110626220703125 nb_pixel_total : 213 time to create 1 rle with old method : 0.0009169578552246094 length of segment : 24 time for calcul the mask position with numpy : 6.270408630371094e-05 nb_pixel_total : 98 time to create 1 rle with old method : 0.0002913475036621094 length of segment : 12 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 150.50234 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 7 time for calcul the mask position with numpy : 3.9577484130859375e-05 nb_pixel_total : 152 time to create 1 rle with old method : 0.0002694129943847656 length of segment : 28 time for calcul the mask position with numpy : 3.361701965332031e-05 nb_pixel_total : 166 time to create 1 rle with old method : 0.0002467632293701172 length of segment : 23 time for calcul the mask position with numpy : 0.00011372566223144531 nb_pixel_total : 529 time to create 1 rle with old method : 0.0006771087646484375 length of segment : 49 time for calcul the mask position with numpy : 5.555152893066406e-05 nb_pixel_total : 194 time to create 1 rle with old method : 0.00038242340087890625 length of segment : 47 time for calcul the mask position with numpy : 4.792213439941406e-05 nb_pixel_total : 418 time to create 1 rle with old method : 0.0006966590881347656 length of segment : 25 time for calcul the mask position with numpy : 8.463859558105469e-05 nb_pixel_total : 2249 time to create 1 rle with old method : 0.0031189918518066406 length of segment : 91 time for calcul the mask position with numpy : 0.00022101402282714844 nb_pixel_total : 508 time to create 1 rle with old method : 0.0009913444519042969 length of segment : 43 Processing 1 images image shape: (280, 320, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 130.57500 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 3 time for calcul the mask position with numpy : 4.029273986816406e-05 nb_pixel_total : 334 time to create 1 rle with old method : 0.0004839897155761719 length of segment : 18 time for calcul the mask position with numpy : 3.552436828613281e-05 nb_pixel_total : 389 time to create 1 rle with old method : 0.0005767345428466797 length of segment : 24 time for calcul the mask position with numpy : 3.790855407714844e-05 nb_pixel_total : 565 time to create 1 rle with old method : 0.00078582763671875 length of segment : 42 NEW PHOTO pour l'instant on ne peut pas sauvegarder la photo dans les tile Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -117.54766 max: 145.60781 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 5 time for calcul the mask position with numpy : 4.458427429199219e-05 nb_pixel_total : 11 time to create 1 rle with old method : 5.14984130859375e-05 length of segment : 8 time for calcul the mask position with numpy : 3.9577484130859375e-05 nb_pixel_total : 240 time to create 1 rle with old method : 0.0004324913024902344 length of segment : 26 time for calcul the mask position with numpy : 4.887580871582031e-05 nb_pixel_total : 617 time to create 1 rle with old method : 0.001129150390625 length of segment : 48 time for calcul the mask position with numpy : 4.220008850097656e-05 nb_pixel_total : 654 time to create 1 rle with old method : 0.0009262561798095703 length of segment : 52 length of segment : 0 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -118.69219 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 5 time for calcul the mask position with numpy : 5.14984130859375e-05 nb_pixel_total : 828 time to create 1 rle with old method : 0.0010597705841064453 length of segment : 37 time for calcul the mask position with numpy : 4.124641418457031e-05 nb_pixel_total : 673 time to create 1 rle with old method : 0.0009889602661132812 length of segment : 61 time for calcul the mask position with numpy : 3.743171691894531e-05 nb_pixel_total : 452 time to create 1 rle with old method : 0.0007500648498535156 length of segment : 17 time for calcul the mask position with numpy : 4.1484832763671875e-05 nb_pixel_total : 827 time to create 1 rle with old method : 0.0010776519775390625 length of segment : 40 time for calcul the mask position with numpy : 8.702278137207031e-05 nb_pixel_total : 783 time to create 1 rle with old method : 0.0010046958923339844 length of segment : 32 Processing 1 images image shape: (400, 400, 3) min: 22.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -82.62969 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 4 time for calcul the mask position with numpy : 0.0001049041748046875 nb_pixel_total : 6064 time to create 1 rle with old method : 0.00722193717956543 length of segment : 119 time for calcul the mask position with numpy : 9.107589721679688e-05 nb_pixel_total : 4105 time to create 1 rle with old method : 0.005008220672607422 length of segment : 128 time for calcul the mask position with numpy : 5.698204040527344e-05 nb_pixel_total : 1003 time to create 1 rle with old method : 0.0013267993927001953 length of segment : 33 time for calcul the mask position with numpy : 8.273124694824219e-05 nb_pixel_total : 4104 time to create 1 rle with old method : 0.004849433898925781 length of segment : 95 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -120.71172 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 3 time for calcul the mask position with numpy : 0.00010919570922851562 nb_pixel_total : 4084 time to create 1 rle with old method : 0.005533933639526367 length of segment : 111 time for calcul the mask position with numpy : 0.0001666545867919922 nb_pixel_total : 4146 time to create 1 rle with old method : 0.0072481632232666016 length of segment : 182 time for calcul the mask position with numpy : 4.410743713378906e-05 nb_pixel_total : 236 time to create 1 rle with old method : 0.0004527568817138672 length of segment : 15 Processing 1 images image shape: (400, 320, 3) min: 0.00000 max: 239.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 106.79922 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 2 time for calcul the mask position with numpy : 4.076957702636719e-05 nb_pixel_total : 494 time to create 1 rle with old method : 0.0006771087646484375 length of segment : 22 time for calcul the mask position with numpy : 3.2901763916015625e-05 nb_pixel_total : 261 time to create 1 rle with old method : 0.00038361549377441406 length of segment : 18 Processing 1 images image shape: (400, 400, 3) min: 25.00000 max: 201.00000 molded_images shape: (1, 640, 640, 3) min: -81.29766 max: 84.74844 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 1 time for calcul the mask position with numpy : 0.0012595653533935547 nb_pixel_total : 150562 time to create 1 rle with new method : 0.001806497573852539 length of segment : 396 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -119.38359 max: 138.91250 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 11 time for calcul the mask position with numpy : 6.079673767089844e-05 nb_pixel_total : 229 time to create 1 rle with old method : 0.0004229545593261719 length of segment : 12 time for calcul the mask position with numpy : 5.340576171875e-05 nb_pixel_total : 1347 time to create 1 rle with old method : 0.0018107891082763672 length of segment : 53 time for calcul the mask position with numpy : 3.2901763916015625e-05 nb_pixel_total : 191 time to create 1 rle with old method : 0.0003235340118408203 length of segment : 10 time for calcul the mask position with numpy : 4.458427429199219e-05 nb_pixel_total : 999 time to create 1 rle with old method : 0.001394033432006836 length of segment : 30 time for calcul the mask position with numpy : 3.3855438232421875e-05 nb_pixel_total : 254 time to create 1 rle with old method : 0.0005781650543212891 length of segment : 19 time for calcul the mask position with numpy : 3.1948089599609375e-05 nb_pixel_total : 102 time to create 1 rle with old method : 0.00017642974853515625 length of segment : 11 time for calcul the mask position with numpy : 3.7670135498046875e-05 nb_pixel_total : 309 time to create 1 rle with old method : 0.0005092620849609375 length of segment : 33 time for calcul the mask position with numpy : 3.5762786865234375e-05 nb_pixel_total : 306 time to create 1 rle with old method : 0.0005061626434326172 length of segment : 14 time for calcul the mask position with numpy : 4.029273986816406e-05 nb_pixel_total : 518 time to create 1 rle with old method : 0.0007004737854003906 length of segment : 32 time for calcul the mask position with numpy : 0.00012302398681640625 nb_pixel_total : 755 time to create 1 rle with old method : 0.0010738372802734375 length of segment : 87 time for calcul the mask position with numpy : 5.0067901611328125e-05 nb_pixel_total : 980 time to create 1 rle with old method : 0.001293182373046875 length of segment : 39 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -111.89141 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 9 time for calcul the mask position with numpy : 0.0001163482666015625 nb_pixel_total : 1452 time to create 1 rle with old method : 0.0028829574584960938 length of segment : 42 time for calcul the mask position with numpy : 6.222724914550781e-05 nb_pixel_total : 227 time to create 1 rle with old method : 0.0004973411560058594 length of segment : 17 time for calcul the mask position with numpy : 0.00010251998901367188 nb_pixel_total : 1779 time to create 1 rle with old method : 0.0036089420318603516 length of segment : 29 time for calcul the mask position with numpy : 5.650520324707031e-05 nb_pixel_total : 192 time to create 1 rle with old method : 0.00044035911560058594 length of segment : 14 time for calcul the mask position with numpy : 6.580352783203125e-05 nb_pixel_total : 612 time to create 1 rle with old method : 0.001245737075805664 length of segment : 31 time for calcul the mask position with numpy : 4.100799560546875e-05 nb_pixel_total : 404 time to create 1 rle with old method : 0.0005292892456054688 length of segment : 51 time for calcul the mask position with numpy : 4.172325134277344e-05 nb_pixel_total : 675 time to create 1 rle with old method : 0.0008785724639892578 length of segment : 30 time for calcul the mask position with numpy : 3.62396240234375e-05 nb_pixel_total : 309 time to create 1 rle with old method : 0.0004305839538574219 length of segment : 19 time for calcul the mask position with numpy : 3.695487976074219e-05 nb_pixel_total : 513 time to create 1 rle with old method : 0.0007340908050537109 length of segment : 29 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -113.23906 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 7 time for calcul the mask position with numpy : 6.723403930664062e-05 nb_pixel_total : 2391 time to create 1 rle with old method : 0.00292205810546875 length of segment : 57 time for calcul the mask position with numpy : 6.628036499023438e-05 nb_pixel_total : 1404 time to create 1 rle with old method : 0.0018644332885742188 length of segment : 42 time for calcul the mask position with numpy : 4.029273986816406e-05 nb_pixel_total : 39 time to create 1 rle with old method : 8.702278137207031e-05 length of segment : 8 time for calcul the mask position with numpy : 3.600120544433594e-05 nb_pixel_total : 245 time to create 1 rle with old method : 0.0004508495330810547 length of segment : 26 time for calcul the mask position with numpy : 4.220008850097656e-05 nb_pixel_total : 718 time to create 1 rle with old method : 0.0008721351623535156 length of segment : 34 time for calcul the mask position with numpy : 4.792213439941406e-05 nb_pixel_total : 1096 time to create 1 rle with old method : 0.0014140605926513672 length of segment : 43 time for calcul the mask position with numpy : 4.887580871582031e-05 nb_pixel_total : 806 time to create 1 rle with old method : 0.0013549327850341797 length of segment : 37 Processing 1 images image shape: (400, 320, 3) min: 0.00000 max: 245.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 122.02187 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 10 time for calcul the mask position with numpy : 5.435943603515625e-05 nb_pixel_total : 1345 time to create 1 rle with old method : 0.001623392105102539 length of segment : 53 time for calcul the mask position with numpy : 4.458427429199219e-05 nb_pixel_total : 374 time to create 1 rle with old method : 0.0005385875701904297 length of segment : 40 time for calcul the mask position with numpy : 2.956390380859375e-05 nb_pixel_total : 81 time to create 1 rle with old method : 0.00012564659118652344 length of segment : 18 time for calcul the mask position with numpy : 0.00016260147094726562 nb_pixel_total : 3134 time to create 1 rle with old method : 0.003926277160644531 length of segment : 189 time for calcul the mask position with numpy : 5.030632019042969e-05 nb_pixel_total : 780 time to create 1 rle with old method : 0.0011017322540283203 length of segment : 30 time for calcul the mask position with numpy : 7.128715515136719e-05 nb_pixel_total : 1736 time to create 1 rle with old method : 0.002397775650024414 length of segment : 91 time for calcul the mask position with numpy : 4.57763671875e-05 nb_pixel_total : 120 time to create 1 rle with old method : 0.0002853870391845703 length of segment : 18 time for calcul the mask position with numpy : 5.0067901611328125e-05 nb_pixel_total : 548 time to create 1 rle with old method : 0.0008492469787597656 length of segment : 37 time for calcul the mask position with numpy : 9.369850158691406e-05 nb_pixel_total : 1578 time to create 1 rle with old method : 0.002454996109008789 length of segment : 113 time for calcul the mask position with numpy : 0.00018715858459472656 nb_pixel_total : 3680 time to create 1 rle with old method : 0.004625797271728516 length of segment : 215 Processing 1 images image shape: (280, 400, 3) min: 20.00000 max: 202.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 85.11562 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 2 time for calcul the mask position with numpy : 0.0012326240539550781 nb_pixel_total : 106825 time to create 1 rle with old method : 0.13700509071350098 length of segment : 280 time for calcul the mask position with numpy : 6.4849853515625e-05 nb_pixel_total : 1376 time to create 1 rle with old method : 0.0017294883728027344 length of segment : 65 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 143.40078 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 8 time for calcul the mask position with numpy : 3.838539123535156e-05 nb_pixel_total : 193 time to create 1 rle with old method : 0.0003428459167480469 length of segment : 12 time for calcul the mask position with numpy : 5.5789947509765625e-05 nb_pixel_total : 1575 time to create 1 rle with old method : 0.001954317092895508 length of segment : 59 time for calcul the mask position with numpy : 3.790855407714844e-05 nb_pixel_total : 442 time to create 1 rle with old method : 0.0006368160247802734 length of segment : 30 time for calcul the mask position with numpy : 7.200241088867188e-05 nb_pixel_total : 2644 time to create 1 rle with old method : 0.003107309341430664 length of segment : 75 time for calcul the mask position with numpy : 5.459785461425781e-05 nb_pixel_total : 1548 time to create 1 rle with old method : 0.0019192695617675781 length of segment : 41 time for calcul the mask position with numpy : 3.266334533691406e-05 nb_pixel_total : 152 time to create 1 rle with old method : 0.0002658367156982422 length of segment : 19 time for calcul the mask position with numpy : 4.2438507080078125e-05 nb_pixel_total : 906 time to create 1 rle with old method : 0.0011191368103027344 length of segment : 35 time for calcul the mask position with numpy : 0.00011444091796875 nb_pixel_total : 7418 time to create 1 rle with old method : 0.00894308090209961 length of segment : 81 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 208.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 76.41875 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 1 time for calcul the mask position with numpy : 4.0531158447265625e-05 nb_pixel_total : 431 time to create 1 rle with old method : 0.0006589889526367188 length of segment : 17 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 150.59609 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 9 time for calcul the mask position with numpy : 4.2438507080078125e-05 nb_pixel_total : 374 time to create 1 rle with old method : 0.0005180835723876953 length of segment : 29 time for calcul the mask position with numpy : 3.24249267578125e-05 nb_pixel_total : 165 time to create 1 rle with old method : 0.0002467632293701172 length of segment : 24 time for calcul the mask position with numpy : 3.075599670410156e-05 nb_pixel_total : 122 time to create 1 rle with old method : 0.0001761913299560547 length of segment : 27 time for calcul the mask position with numpy : 3.337860107421875e-05 nb_pixel_total : 344 time to create 1 rle with old method : 0.0004887580871582031 length of segment : 23 time for calcul the mask position with numpy : 0.00011396408081054688 nb_pixel_total : 235 time to create 1 rle with old method : 0.0004200935363769531 length of segment : 57 time for calcul the mask position with numpy : 7.271766662597656e-05 nb_pixel_total : 3453 time to create 1 rle with old method : 0.0040090084075927734 length of segment : 90 time for calcul the mask position with numpy : 4.57763671875e-05 nb_pixel_total : 493 time to create 1 rle with old method : 0.0007739067077636719 length of segment : 24 time for calcul the mask position with numpy : 4.0531158447265625e-05 nb_pixel_total : 662 time to create 1 rle with old method : 0.0010421276092529297 length of segment : 45 time for calcul the mask position with numpy : 0.0001914501190185547 nb_pixel_total : 2578 time to create 1 rle with old method : 0.0032660961151123047 length of segment : 176 Processing 1 images image shape: (280, 320, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 130.32500 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 3 time for calcul the mask position with numpy : 5.340576171875e-05 nb_pixel_total : 314 time to create 1 rle with old method : 0.0006077289581298828 length of segment : 17 time for calcul the mask position with numpy : 4.982948303222656e-05 nb_pixel_total : 369 time to create 1 rle with old method : 0.0007383823394775391 length of segment : 24 time for calcul the mask position with numpy : 4.57763671875e-05 nb_pixel_total : 519 time to create 1 rle with old method : 0.0009107589721679688 length of segment : 41 NEW PHOTO pour l'instant on ne peut pas sauvegarder la photo dans les tile Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -117.86406 max: 145.13125 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 4 time for calcul the mask position with numpy : 5.698204040527344e-05 nb_pixel_total : 284 time to create 1 rle with old method : 0.0005924701690673828 length of segment : 28 time for calcul the mask position with numpy : 5.14984130859375e-05 nb_pixel_total : 11 time to create 1 rle with old method : 6.771087646484375e-05 length of segment : 7 time for calcul the mask position with numpy : 6.008148193359375e-05 nb_pixel_total : 1067 time to create 1 rle with old method : 0.0021512508392333984 length of segment : 33 time for calcul the mask position with numpy : 6.604194641113281e-05 nb_pixel_total : 1033 time to create 1 rle with old method : 0.0021271705627441406 length of segment : 30 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -117.52031 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 10 time for calcul the mask position with numpy : 6.580352783203125e-05 nb_pixel_total : 1580 time to create 1 rle with old method : 0.002045869827270508 length of segment : 75 time for calcul the mask position with numpy : 4.7206878662109375e-05 nb_pixel_total : 334 time to create 1 rle with old method : 0.0005605220794677734 length of segment : 44 time for calcul the mask position with numpy : 4.482269287109375e-05 nb_pixel_total : 533 time to create 1 rle with old method : 0.0008661746978759766 length of segment : 21 time for calcul the mask position with numpy : 4.76837158203125e-05 nb_pixel_total : 702 time to create 1 rle with old method : 0.0009806156158447266 length of segment : 33 time for calcul the mask position with numpy : 3.361701965332031e-05 nb_pixel_total : 29 time to create 1 rle with old method : 6.985664367675781e-05 length of segment : 5 time for calcul the mask position with numpy : 4.076957702636719e-05 nb_pixel_total : 613 time to create 1 rle with old method : 0.0009343624114990234 length of segment : 46 time for calcul the mask position with numpy : 0.0002334117889404297 nb_pixel_total : 1048 time to create 1 rle with old method : 0.0014126300811767578 length of segment : 113 time for calcul the mask position with numpy : 4.57763671875e-05 nb_pixel_total : 668 time to create 1 rle with old method : 0.0010497570037841797 length of segment : 20 length of segment : 0 time for calcul the mask position with numpy : 6.556510925292969e-05 nb_pixel_total : 820 time to create 1 rle with old method : 0.001528024673461914 length of segment : 39 Processing 1 images image shape: (400, 400, 3) min: 30.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -87.13750 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 2 time for calcul the mask position with numpy : 0.00010156631469726562 nb_pixel_total : 6526 time to create 1 rle with old method : 0.007621288299560547 length of segment : 105 time for calcul the mask position with numpy : 0.00011086463928222656 nb_pixel_total : 2975 time to create 1 rle with old method : 0.00360870361328125 length of segment : 141 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -114.30938 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 5 time for calcul the mask position with numpy : 5.7220458984375e-05 nb_pixel_total : 381 time to create 1 rle with old method : 0.0008764266967773438 length of segment : 20 time for calcul the mask position with numpy : 0.00016355514526367188 nb_pixel_total : 5124 time to create 1 rle with old method : 0.00924372673034668 length of segment : 119 time for calcul the mask position with numpy : 0.000209808349609375 nb_pixel_total : 5340 time to create 1 rle with old method : 0.011201858520507812 length of segment : 211 time for calcul the mask position with numpy : 4.4345855712890625e-05 nb_pixel_total : 398 time to create 1 rle with old method : 0.000568389892578125 length of segment : 22 time for calcul the mask position with numpy : 4.553794860839844e-05 nb_pixel_total : 241 time to create 1 rle with old method : 0.00039958953857421875 length of segment : 37 Processing 1 images image shape: (400, 320, 3) min: 0.00000 max: 249.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 128.53750 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 1 time for calcul the mask position with numpy : 5.364418029785156e-05 nb_pixel_total : 562 time to create 1 rle with old method : 0.001013040542602539 length of segment : 31 Processing 1 images image shape: (400, 400, 3) min: 27.00000 max: 196.00000 molded_images shape: (1, 640, 640, 3) min: -82.21172 max: 78.26797 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 1 time for calcul the mask position with numpy : 0.0012671947479248047 nb_pixel_total : 151000 time to create 1 rle with new method : 0.0018205642700195312 length of segment : 398 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -116.30547 max: 137.37344 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 11 time for calcul the mask position with numpy : 4.1484832763671875e-05 nb_pixel_total : 232 time to create 1 rle with old method : 0.00034332275390625 length of segment : 19 time for calcul the mask position with numpy : 5.0067901611328125e-05 nb_pixel_total : 1077 time to create 1 rle with old method : 0.0013577938079833984 length of segment : 73 time for calcul the mask position with numpy : 9.059906005859375e-05 nb_pixel_total : 3196 time to create 1 rle with old method : 0.0038208961486816406 length of segment : 100 time for calcul the mask position with numpy : 3.814697265625e-05 nb_pixel_total : 480 time to create 1 rle with old method : 0.0006458759307861328 length of segment : 23 time for calcul the mask position with numpy : 3.0517578125e-05 nb_pixel_total : 144 time to create 1 rle with old method : 0.00025725364685058594 length of segment : 9 time for calcul the mask position with numpy : 3.886222839355469e-05 nb_pixel_total : 564 time to create 1 rle with old method : 0.0007941722869873047 length of segment : 33 time for calcul the mask position with numpy : 3.5762786865234375e-05 nb_pixel_total : 354 time to create 1 rle with old method : 0.0004849433898925781 length of segment : 39 time for calcul the mask position with numpy : 3.933906555175781e-05 nb_pixel_total : 680 time to create 1 rle with old method : 0.0009100437164306641 length of segment : 26 time for calcul the mask position with numpy : 3.409385681152344e-05 nb_pixel_total : 254 time to create 1 rle with old method : 0.0004584789276123047 length of segment : 13 time for calcul the mask position with numpy : 3.6716461181640625e-05 nb_pixel_total : 461 time to create 1 rle with old method : 0.0006699562072753906 length of segment : 21 time for calcul the mask position with numpy : 4.267692565917969e-05 nb_pixel_total : 889 time to create 1 rle with old method : 0.0011758804321289062 length of segment : 42 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -111.63359 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 9 time for calcul the mask position with numpy : 4.1961669921875e-05 nb_pixel_total : 207 time to create 1 rle with old method : 0.0003256797790527344 length of segment : 14 time for calcul the mask position with numpy : 3.0994415283203125e-05 nb_pixel_total : 60 time to create 1 rle with old method : 0.00010204315185546875 length of segment : 13 time for calcul the mask position with numpy : 4.696846008300781e-05 nb_pixel_total : 313 time to create 1 rle with old method : 0.00045990943908691406 length of segment : 18 time for calcul the mask position with numpy : 0.00032019615173339844 nb_pixel_total : 22085 time to create 1 rle with old method : 0.02542734146118164 length of segment : 204 time for calcul the mask position with numpy : 7.295608520507812e-05 nb_pixel_total : 1377 time to create 1 rle with old method : 0.0016810894012451172 length of segment : 61 time for calcul the mask position with numpy : 5.245208740234375e-05 nb_pixel_total : 1790 time to create 1 rle with old method : 0.0024356842041015625 length of segment : 26 time for calcul the mask position with numpy : 4.9591064453125e-05 nb_pixel_total : 1227 time to create 1 rle with old method : 0.0016770362854003906 length of segment : 51 time for calcul the mask position with numpy : 3.6716461181640625e-05 nb_pixel_total : 426 time to create 1 rle with old method : 0.0005826950073242188 length of segment : 52 time for calcul the mask position with numpy : 3.814697265625e-05 nb_pixel_total : 648 time to create 1 rle with old method : 0.000843048095703125 length of segment : 30 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -115.66094 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 7 time for calcul the mask position with numpy : 7.557868957519531e-05 nb_pixel_total : 1375 time to create 1 rle with old method : 0.0019176006317138672 length of segment : 43 time for calcul the mask position with numpy : 3.552436828613281e-05 nb_pixel_total : 246 time to create 1 rle with old method : 0.0004508495330810547 length of segment : 20 time for calcul the mask position with numpy : 8.487701416015625e-05 nb_pixel_total : 949 time to create 1 rle with old method : 0.0012812614440917969 length of segment : 105 time for calcul the mask position with numpy : 3.743171691894531e-05 nb_pixel_total : 607 time to create 1 rle with old method : 0.0007848739624023438 length of segment : 32 time for calcul the mask position with numpy : 2.765655517578125e-05 nb_pixel_total : 33 time to create 1 rle with old method : 7.033348083496094e-05 length of segment : 8 time for calcul the mask position with numpy : 9.846687316894531e-05 nb_pixel_total : 3877 time to create 1 rle with old method : 0.004526853561401367 length of segment : 162 time for calcul the mask position with numpy : 6.389617919921875e-05 nb_pixel_total : 1910 time to create 1 rle with old method : 0.00237274169921875 length of segment : 55 Processing 1 images image shape: (400, 320, 3) min: 0.00000 max: 239.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 117.23672 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 8 time for calcul the mask position with numpy : 4.363059997558594e-05 nb_pixel_total : 405 time to create 1 rle with old method : 0.0005986690521240234 length of segment : 47 time for calcul the mask position with numpy : 3.0279159545898438e-05 nb_pixel_total : 97 time to create 1 rle with old method : 0.00015425682067871094 length of segment : 17 time for calcul the mask position with numpy : 7.05718994140625e-05 nb_pixel_total : 1459 time to create 1 rle with old method : 0.0019686222076416016 length of segment : 95 time for calcul the mask position with numpy : 3.3855438232421875e-05 nb_pixel_total : 124 time to create 1 rle with old method : 0.0001819133758544922 length of segment : 18 time for calcul the mask position with numpy : 0.000148773193359375 nb_pixel_total : 3301 time to create 1 rle with old method : 0.004160881042480469 length of segment : 185 time for calcul the mask position with numpy : 3.790855407714844e-05 nb_pixel_total : 378 time to create 1 rle with old method : 0.0005283355712890625 length of segment : 39 time for calcul the mask position with numpy : 3.361701965332031e-05 nb_pixel_total : 269 time to create 1 rle with old method : 0.00037026405334472656 length of segment : 40 time for calcul the mask position with numpy : 4.100799560546875e-05 nb_pixel_total : 656 time to create 1 rle with old method : 0.0008993148803710938 length of segment : 43 Processing 1 images image shape: (280, 400, 3) min: 19.00000 max: 201.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 83.47109 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 1 time for calcul the mask position with numpy : 0.0011532306671142578 nb_pixel_total : 106290 time to create 1 rle with old method : 0.11643838882446289 length of segment : 281 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 147.68984 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 9 time for calcul the mask position with numpy : 4.506111145019531e-05 nb_pixel_total : 244 time to create 1 rle with old method : 0.0003809928894042969 length of segment : 16 time for calcul the mask position with numpy : 5.173683166503906e-05 nb_pixel_total : 1563 time to create 1 rle with old method : 0.002111196517944336 length of segment : 40 time for calcul the mask position with numpy : 6.723403930664062e-05 nb_pixel_total : 2631 time to create 1 rle with old method : 0.0035185813903808594 length of segment : 76 time for calcul the mask position with numpy : 3.5762786865234375e-05 nb_pixel_total : 441 time to create 1 rle with old method : 0.0006077289581298828 length of segment : 27 time for calcul the mask position with numpy : 3.933906555175781e-05 nb_pixel_total : 464 time to create 1 rle with old method : 0.0006723403930664062 length of segment : 50 time for calcul the mask position with numpy : 0.0001289844512939453 nb_pixel_total : 7570 time to create 1 rle with old method : 0.009187698364257812 length of segment : 77 time for calcul the mask position with numpy : 3.24249267578125e-05 nb_pixel_total : 125 time to create 1 rle with old method : 0.00018405914306640625 length of segment : 20 time for calcul the mask position with numpy : 4.172325134277344e-05 nb_pixel_total : 953 time to create 1 rle with old method : 0.0012295246124267578 length of segment : 36 time for calcul the mask position with numpy : 2.9802322387695312e-05 nb_pixel_total : 133 time to create 1 rle with old method : 0.00023746490478515625 length of segment : 15 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 200.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 87.87734 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 1 time for calcul the mask position with numpy : 4.00543212890625e-05 nb_pixel_total : 421 time to create 1 rle with old method : 0.0006043910980224609 length of segment : 20 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 149.66250 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 8 time for calcul the mask position with numpy : 3.981590270996094e-05 nb_pixel_total : 313 time to create 1 rle with old method : 0.00044655799865722656 length of segment : 24 time for calcul the mask position with numpy : 3.552436828613281e-05 nb_pixel_total : 129 time to create 1 rle with old method : 0.0001888275146484375 length of segment : 28 time for calcul the mask position with numpy : 3.266334533691406e-05 nb_pixel_total : 242 time to create 1 rle with old method : 0.00035881996154785156 length of segment : 25 time for calcul the mask position with numpy : 0.00014162063598632812 nb_pixel_total : 475 time to create 1 rle with old method : 0.0009112358093261719 length of segment : 48 time for calcul the mask position with numpy : 5.9604644775390625e-05 nb_pixel_total : 1396 time to create 1 rle with old method : 0.0017979145050048828 length of segment : 69 time for calcul the mask position with numpy : 4.1484832763671875e-05 nb_pixel_total : 629 time to create 1 rle with old method : 0.001008749008178711 length of segment : 43 time for calcul the mask position with numpy : 5.173683166503906e-05 nb_pixel_total : 339 time to create 1 rle with old method : 0.0005609989166259766 length of segment : 23 time for calcul the mask position with numpy : 0.0002701282501220703 nb_pixel_total : 238 time to create 1 rle with old method : 0.0010647773742675781 length of segment : 35 Processing 1 images image shape: (280, 320, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 132.20000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 3 time for calcul the mask position with numpy : 3.814697265625e-05 nb_pixel_total : 291 time to create 1 rle with old method : 0.00042939186096191406 length of segment : 16 time for calcul the mask position with numpy : 3.4809112548828125e-05 nb_pixel_total : 378 time to create 1 rle with old method : 0.0005652904510498047 length of segment : 23 time for calcul the mask position with numpy : 0.0003428459167480469 nb_pixel_total : 24434 time to create 1 rle with old method : 0.0314023494720459 length of segment : 387 NEW PHOTO pour l'instant on ne peut pas sauvegarder la photo dans les tile Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -117.05547 max: 145.43203 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 5 time for calcul the mask position with numpy : 3.647804260253906e-05 nb_pixel_total : 25 time to create 1 rle with old method : 6.723403930664062e-05 length of segment : 10 time for calcul the mask position with numpy : 4.220008850097656e-05 nb_pixel_total : 1061 time to create 1 rle with old method : 0.0014166831970214844 length of segment : 33 time for calcul the mask position with numpy : 3.24249267578125e-05 nb_pixel_total : 200 time to create 1 rle with old method : 0.00029754638671875 length of segment : 32 length of segment : 0 time for calcul the mask position with numpy : 3.266334533691406e-05 nb_pixel_total : 273 time to create 1 rle with old method : 0.00036454200744628906 length of segment : 34 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -118.69219 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 3 time for calcul the mask position with numpy : 4.482269287109375e-05 nb_pixel_total : 687 time to create 1 rle with old method : 0.0009920597076416016 length of segment : 21 time for calcul the mask position with numpy : 5.984306335449219e-05 nb_pixel_total : 775 time to create 1 rle with old method : 0.001064300537109375 length of segment : 36 time for calcul the mask position with numpy : 3.743171691894531e-05 nb_pixel_total : 507 time to create 1 rle with old method : 0.0007486343383789062 length of segment : 55 Processing 1 images image shape: (400, 400, 3) min: 26.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -80.30938 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 3 time for calcul the mask position with numpy : 9.965896606445312e-05 nb_pixel_total : 6145 time to create 1 rle with old method : 0.006999015808105469 length of segment : 122 time for calcul the mask position with numpy : 8.654594421386719e-05 nb_pixel_total : 3728 time to create 1 rle with old method : 0.004550933837890625 length of segment : 165 time for calcul the mask position with numpy : 8.821487426757812e-05 nb_pixel_total : 3485 time to create 1 rle with old method : 0.0050792694091796875 length of segment : 93 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -119.08672 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 8 time for calcul the mask position with numpy : 4.5299530029296875e-05 nb_pixel_total : 377 time to create 1 rle with old method : 0.0006115436553955078 length of segment : 21 time for calcul the mask position with numpy : 0.00011968612670898438 nb_pixel_total : 4735 time to create 1 rle with old method : 0.006314277648925781 length of segment : 137 time for calcul the mask position with numpy : 3.790855407714844e-05 nb_pixel_total : 118 time to create 1 rle with old method : 0.00019073486328125 length of segment : 14 time for calcul the mask position with numpy : 0.00011587142944335938 nb_pixel_total : 3962 time to create 1 rle with old method : 0.004952192306518555 length of segment : 180 time for calcul the mask position with numpy : 5.1975250244140625e-05 nb_pixel_total : 1146 time to create 1 rle with old method : 0.0013985633850097656 length of segment : 64 time for calcul the mask position with numpy : 3.24249267578125e-05 nb_pixel_total : 245 time to create 1 rle with old method : 0.00034046173095703125 length of segment : 22 time for calcul the mask position with numpy : 3.218650817871094e-05 nb_pixel_total : 241 time to create 1 rle with old method : 0.0003762245178222656 length of segment : 30 time for calcul the mask position with numpy : 3.5762786865234375e-05 nb_pixel_total : 389 time to create 1 rle with old method : 0.0005707740783691406 length of segment : 19 Processing 1 images image shape: (400, 320, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 135.95547 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 2 time for calcul the mask position with numpy : 4.291534423828125e-05 nb_pixel_total : 502 time to create 1 rle with old method : 0.0007016658782958984 length of segment : 19 time for calcul the mask position with numpy : 0.0006921291351318359 nb_pixel_total : 62060 time to create 1 rle with old method : 0.06928491592407227 length of segment : 357 Processing 1 images image shape: (400, 400, 3) min: 13.00000 max: 205.00000 molded_images shape: (1, 640, 640, 3) min: -80.38359 max: 79.72891 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 1 time for calcul the mask position with numpy : 0.0012896060943603516 nb_pixel_total : 150002 time to create 1 rle with new method : 0.002028226852416992 length of segment : 393 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -118.41875 max: 146.65078 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 13 time for calcul the mask position with numpy : 4.1961669921875e-05 nb_pixel_total : 230 time to create 1 rle with old method : 0.0003571510314941406 length of segment : 11 time for calcul the mask position with numpy : 3.314018249511719e-05 nb_pixel_total : 250 time to create 1 rle with old method : 0.0003647804260253906 length of segment : 19 time for calcul the mask position with numpy : 4.887580871582031e-05 nb_pixel_total : 1325 time to create 1 rle with old method : 0.0017070770263671875 length of segment : 53 time for calcul the mask position with numpy : 0.000102996826171875 nb_pixel_total : 4374 time to create 1 rle with old method : 0.0054967403411865234 length of segment : 99 time for calcul the mask position with numpy : 3.361701965332031e-05 nb_pixel_total : 165 time to create 1 rle with old method : 0.0002579689025878906 length of segment : 16 time for calcul the mask position with numpy : 2.9802322387695312e-05 nb_pixel_total : 106 time to create 1 rle with old method : 0.00016689300537109375 length of segment : 12 time for calcul the mask position with numpy : 3.6716461181640625e-05 nb_pixel_total : 538 time to create 1 rle with old method : 0.0007517337799072266 length of segment : 32 time for calcul the mask position with numpy : 3.552436828613281e-05 nb_pixel_total : 295 time to create 1 rle with old method : 0.0004832744598388672 length of segment : 23 time for calcul the mask position with numpy : 3.8623809814453125e-05 nb_pixel_total : 518 time to create 1 rle with old method : 0.0007646083831787109 length of segment : 26 time for calcul the mask position with numpy : 6.890296936035156e-05 nb_pixel_total : 2679 time to create 1 rle with old method : 0.0033419132232666016 length of segment : 60 time for calcul the mask position with numpy : 3.647804260253906e-05 nb_pixel_total : 298 time to create 1 rle with old method : 0.0004956722259521484 length of segment : 19 time for calcul the mask position with numpy : 4.291534423828125e-05 nb_pixel_total : 830 time to create 1 rle with old method : 0.0011782646179199219 length of segment : 27 time for calcul the mask position with numpy : 3.6716461181640625e-05 nb_pixel_total : 514 time to create 1 rle with old method : 0.0007688999176025391 length of segment : 21 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -112.16875 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 6 time for calcul the mask position with numpy : 4.458427429199219e-05 nb_pixel_total : 172 time to create 1 rle with old method : 0.0003478527069091797 length of segment : 14 time for calcul the mask position with numpy : 5.7697296142578125e-05 nb_pixel_total : 980 time to create 1 rle with old method : 0.001735687255859375 length of segment : 51 time for calcul the mask position with numpy : 3.266334533691406e-05 nb_pixel_total : 266 time to create 1 rle with old method : 0.0003833770751953125 length of segment : 18 time for calcul the mask position with numpy : 5.340576171875e-05 nb_pixel_total : 1856 time to create 1 rle with old method : 0.002532482147216797 length of segment : 29 time for calcul the mask position with numpy : 0.0002512931823730469 nb_pixel_total : 15136 time to create 1 rle with old method : 0.018181562423706055 length of segment : 155 time for calcul the mask position with numpy : 4.100799560546875e-05 nb_pixel_total : 651 time to create 1 rle with old method : 0.0008509159088134766 length of segment : 29 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -115.30547 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 9 time for calcul the mask position with numpy : 7.62939453125e-05 nb_pixel_total : 932 time to create 1 rle with old method : 0.0016927719116210938 length of segment : 92 time for calcul the mask position with numpy : 4.267692565917969e-05 nb_pixel_total : 32 time to create 1 rle with old method : 9.799003601074219e-05 length of segment : 9 time for calcul the mask position with numpy : 0.00011539459228515625 nb_pixel_total : 4581 time to create 1 rle with old method : 0.0054874420166015625 length of segment : 133 time for calcul the mask position with numpy : 5.650520324707031e-05 nb_pixel_total : 1322 time to create 1 rle with old method : 0.0018537044525146484 length of segment : 41 time for calcul the mask position with numpy : 5.698204040527344e-05 nb_pixel_total : 1389 time to create 1 rle with old method : 0.0018317699432373047 length of segment : 42 time for calcul the mask position with numpy : 4.220008850097656e-05 nb_pixel_total : 823 time to create 1 rle with old method : 0.0010433197021484375 length of segment : 38 time for calcul the mask position with numpy : 3.170967102050781e-05 nb_pixel_total : 192 time to create 1 rle with old method : 0.0003058910369873047 length of segment : 16 time for calcul the mask position with numpy : 6.556510925292969e-05 nb_pixel_total : 1248 time to create 1 rle with old method : 0.0016901493072509766 length of segment : 116 time for calcul the mask position with numpy : 4.029273986816406e-05 nb_pixel_total : 806 time to create 1 rle with old method : 0.000934600830078125 length of segment : 36 Processing 1 images image shape: (400, 320, 3) min: 0.00000 max: 243.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 118.83828 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 10 time for calcul the mask position with numpy : 0.00015425682067871094 nb_pixel_total : 3412 time to create 1 rle with old method : 0.004078865051269531 length of segment : 183 time for calcul the mask position with numpy : 4.291534423828125e-05 nb_pixel_total : 367 time to create 1 rle with old method : 0.00054168701171875 length of segment : 56 time for calcul the mask position with numpy : 3.0279159545898438e-05 nb_pixel_total : 85 time to create 1 rle with old method : 0.00013589859008789062 length of segment : 15 time for calcul the mask position with numpy : 3.719329833984375e-05 nb_pixel_total : 384 time to create 1 rle with old method : 0.0005321502685546875 length of segment : 36 time for calcul the mask position with numpy : 3.147125244140625e-05 nb_pixel_total : 120 time to create 1 rle with old method : 0.0001811981201171875 length of segment : 19 time for calcul the mask position with numpy : 8.034706115722656e-05 nb_pixel_total : 1108 time to create 1 rle with old method : 0.0015859603881835938 length of segment : 96 time for calcul the mask position with numpy : 4.267692565917969e-05 nb_pixel_total : 403 time to create 1 rle with old method : 0.0005481243133544922 length of segment : 39 time for calcul the mask position with numpy : 3.4332275390625e-05 nb_pixel_total : 267 time to create 1 rle with old method : 0.0003616809844970703 length of segment : 39 time for calcul the mask position with numpy : 4.4345855712890625e-05 nb_pixel_total : 486 time to create 1 rle with old method : 0.0007150173187255859 length of segment : 35 time for calcul the mask position with numpy : 5.936622619628906e-05 nb_pixel_total : 1227 time to create 1 rle with old method : 0.0016486644744873047 length of segment : 93 Processing 1 images image shape: (280, 400, 3) min: 17.00000 max: 213.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 93.93203 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 1 time for calcul the mask position with numpy : 0.0009086132049560547 nb_pixel_total : 106638 time to create 1 rle with old method : 0.11577033996582031 length of segment : 282 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 147.44766 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 11 time for calcul the mask position with numpy : 3.790855407714844e-05 nb_pixel_total : 194 time to create 1 rle with old method : 0.0003418922424316406 length of segment : 19 time for calcul the mask position with numpy : 5.1975250244140625e-05 nb_pixel_total : 1658 time to create 1 rle with old method : 0.0021610260009765625 length of segment : 42 time for calcul the mask position with numpy : 3.337860107421875e-05 nb_pixel_total : 281 time to create 1 rle with old method : 0.0004012584686279297 length of segment : 27 time for calcul the mask position with numpy : 4.1961669921875e-05 nb_pixel_total : 900 time to create 1 rle with old method : 0.0012073516845703125 length of segment : 35 time for calcul the mask position with numpy : 0.0001220703125 nb_pixel_total : 7478 time to create 1 rle with old method : 0.009373188018798828 length of segment : 79 time for calcul the mask position with numpy : 6.341934204101562e-05 nb_pixel_total : 1634 time to create 1 rle with old method : 0.0019969940185546875 length of segment : 61 time for calcul the mask position with numpy : 4.839897155761719e-05 nb_pixel_total : 1066 time to create 1 rle with old method : 0.0015099048614501953 length of segment : 36 time for calcul the mask position with numpy : 3.695487976074219e-05 nb_pixel_total : 419 time to create 1 rle with old method : 0.0005297660827636719 length of segment : 47 time for calcul the mask position with numpy : 6.794929504394531e-05 nb_pixel_total : 2510 time to create 1 rle with old method : 0.003175020217895508 length of segment : 72 time for calcul the mask position with numpy : 7.081031799316406e-05 nb_pixel_total : 3056 time to create 1 rle with old method : 0.0037462711334228516 length of segment : 65 time for calcul the mask position with numpy : 3.719329833984375e-05 nb_pixel_total : 451 time to create 1 rle with old method : 0.0006694793701171875 length of segment : 28 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 202.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 88.13516 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 3 time for calcul the mask position with numpy : 4.935264587402344e-05 nb_pixel_total : 348 time to create 1 rle with old method : 0.0007936954498291016 length of segment : 24 time for calcul the mask position with numpy : 3.719329833984375e-05 nb_pixel_total : 380 time to create 1 rle with old method : 0.0006475448608398438 length of segment : 24 time for calcul the mask position with numpy : 3.314018249511719e-05 nb_pixel_total : 203 time to create 1 rle with old method : 0.0002887248992919922 length of segment : 32 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 150.04922 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 6 time for calcul the mask position with numpy : 4.7206878662109375e-05 nb_pixel_total : 289 time to create 1 rle with old method : 0.0005412101745605469 length of segment : 24 time for calcul the mask position with numpy : 3.8623809814453125e-05 nb_pixel_total : 124 time to create 1 rle with old method : 0.0002281665802001953 length of segment : 27 time for calcul the mask position with numpy : 3.409385681152344e-05 nb_pixel_total : 330 time to create 1 rle with old method : 0.00047469139099121094 length of segment : 25 time for calcul the mask position with numpy : 3.337860107421875e-05 nb_pixel_total : 327 time to create 1 rle with old method : 0.00048351287841796875 length of segment : 23 time for calcul the mask position with numpy : 4.172325134277344e-05 nb_pixel_total : 285 time to create 1 rle with old method : 0.0005311965942382812 length of segment : 22 time for calcul the mask position with numpy : 8.296966552734375e-05 nb_pixel_total : 3137 time to create 1 rle with old method : 0.003882884979248047 length of segment : 101 Processing 1 images image shape: (280, 320, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 131.57500 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 2 time for calcul the mask position with numpy : 3.814697265625e-05 nb_pixel_total : 324 time to create 1 rle with old method : 0.0004589557647705078 length of segment : 18 time for calcul the mask position with numpy : 3.528594970703125e-05 nb_pixel_total : 398 time to create 1 rle with old method : 0.0005555152893066406 length of segment : 25 NEW PHOTO pour l'instant on ne peut pas sauvegarder la photo dans les tile Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -117.43828 max: 144.86953 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 5 time for calcul the mask position with numpy : 3.4809112548828125e-05 nb_pixel_total : 14 time to create 1 rle with old method : 5.316734313964844e-05 length of segment : 10 time for calcul the mask position with numpy : 3.24249267578125e-05 nb_pixel_total : 256 time to create 1 rle with old method : 0.0003635883331298828 length of segment : 27 time for calcul the mask position with numpy : 4.1484832763671875e-05 nb_pixel_total : 928 time to create 1 rle with old method : 0.0013327598571777344 length of segment : 47 time for calcul the mask position with numpy : 4.887580871582031e-05 nb_pixel_total : 1050 time to create 1 rle with old method : 0.0014052391052246094 length of segment : 41 time for calcul the mask position with numpy : 4.9591064453125e-05 nb_pixel_total : 1787 time to create 1 rle with old method : 0.002389669418334961 length of segment : 46 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -116.92266 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 4 time for calcul the mask position with numpy : 4.553794860839844e-05 nb_pixel_total : 723 time to create 1 rle with old method : 0.00090789794921875 length of segment : 33 time for calcul the mask position with numpy : 3.4809112548828125e-05 nb_pixel_total : 172 time to create 1 rle with old method : 0.00031447410583496094 length of segment : 40 time for calcul the mask position with numpy : 3.6716461181640625e-05 nb_pixel_total : 495 time to create 1 rle with old method : 0.000736236572265625 length of segment : 17 length of segment : 0 Processing 1 images image shape: (400, 400, 3) min: 21.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -87.23906 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 2 time for calcul the mask position with numpy : 6.890296936035156e-05 nb_pixel_total : 1392 time to create 1 rle with old method : 0.002232074737548828 length of segment : 40 time for calcul the mask position with numpy : 7.939338684082031e-05 nb_pixel_total : 3680 time to create 1 rle with old method : 0.004448890686035156 length of segment : 154 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -120.37969 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 6 time for calcul the mask position with numpy : 0.00015735626220703125 nb_pixel_total : 7288 time to create 1 rle with old method : 0.008504152297973633 length of segment : 145 time for calcul the mask position with numpy : 4.673004150390625e-05 nb_pixel_total : 387 time to create 1 rle with old method : 0.0006456375122070312 length of segment : 21 time for calcul the mask position with numpy : 8.559226989746094e-05 nb_pixel_total : 2096 time to create 1 rle with old method : 0.0027892589569091797 length of segment : 113 time for calcul the mask position with numpy : 3.838539123535156e-05 nb_pixel_total : 242 time to create 1 rle with old method : 0.0003445148468017578 length of segment : 23 time for calcul the mask position with numpy : 3.4809112548828125e-05 nb_pixel_total : 244 time to create 1 rle with old method : 0.00037598609924316406 length of segment : 28 time for calcul the mask position with numpy : 4.9591064453125e-05 nb_pixel_total : 1175 time to create 1 rle with old method : 0.0015287399291992188 length of segment : 76 Processing 1 images image shape: (400, 320, 3) min: 0.00000 max: 250.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 128.09609 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 3 time for calcul the mask position with numpy : 5.14984130859375e-05 nb_pixel_total : 550 time to create 1 rle with old method : 0.0010082721710205078 length of segment : 22 time for calcul the mask position with numpy : 6.532669067382812e-05 nb_pixel_total : 2659 time to create 1 rle with old method : 0.003303050994873047 length of segment : 83 time for calcul the mask position with numpy : 3.457069396972656e-05 nb_pixel_total : 375 time to create 1 rle with old method : 0.0005662441253662109 length of segment : 23 Processing 1 images image shape: (400, 400, 3) min: 25.00000 max: 195.00000 molded_images shape: (1, 640, 640, 3) min: -81.19609 max: 76.95547 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 1 time for calcul the mask position with numpy : 0.0012769699096679688 nb_pixel_total : 151730 time to create 1 rle with new method : 0.0020189285278320312 length of segment : 398 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -121.18828 max: 136.17422 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 13 time for calcul the mask position with numpy : 7.843971252441406e-05 nb_pixel_total : 1316 time to create 1 rle with old method : 0.0019249916076660156 length of segment : 47 time for calcul the mask position with numpy : 4.482269287109375e-05 nb_pixel_total : 244 time to create 1 rle with old method : 0.00044846534729003906 length of segment : 18 time for calcul the mask position with numpy : 5.0067901611328125e-05 nb_pixel_total : 555 time to create 1 rle with old method : 0.0009884834289550781 length of segment : 27 time for calcul the mask position with numpy : 4.0531158447265625e-05 nb_pixel_total : 165 time to create 1 rle with old method : 0.00033402442932128906 length of segment : 9 time for calcul the mask position with numpy : 5.245208740234375e-05 nb_pixel_total : 756 time to create 1 rle with old method : 0.0011289119720458984 length of segment : 27 time for calcul the mask position with numpy : 0.00016045570373535156 nb_pixel_total : 7003 time to create 1 rle with old method : 0.008511781692504883 length of segment : 91 time for calcul the mask position with numpy : 6.389617919921875e-05 nb_pixel_total : 538 time to create 1 rle with old method : 0.0007605552673339844 length of segment : 32 time for calcul the mask position with numpy : 3.933906555175781e-05 nb_pixel_total : 208 time to create 1 rle with old method : 0.00031256675720214844 length of segment : 29 time for calcul the mask position with numpy : 0.00010347366333007812 nb_pixel_total : 3312 time to create 1 rle with old method : 0.00433039665222168 length of segment : 71 time for calcul the mask position with numpy : 5.9604644775390625e-05 nb_pixel_total : 304 time to create 1 rle with old method : 0.00044345855712890625 length of segment : 38 time for calcul the mask position with numpy : 0.00010466575622558594 nb_pixel_total : 1458 time to create 1 rle with old method : 0.001991748809814453 length of segment : 130 time for calcul the mask position with numpy : 6.794929504394531e-05 nb_pixel_total : 393 time to create 1 rle with old method : 0.0006268024444580078 length of segment : 33 time for calcul the mask position with numpy : 4.291534423828125e-05 nb_pixel_total : 91 time to create 1 rle with old method : 0.00019240379333496094 length of segment : 8 Processing 1 images image shape: (400, 400, 3) min: 3.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -112.53203 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 6 time for calcul the mask position with numpy : 5.8650970458984375e-05 nb_pixel_total : 1805 time to create 1 rle with old method : 0.002348661422729492 length of segment : 27 time for calcul the mask position with numpy : 5.745887756347656e-05 nb_pixel_total : 1737 time to create 1 rle with old method : 0.002418994903564453 length of segment : 44 time for calcul the mask position with numpy : 3.7670135498046875e-05 nb_pixel_total : 536 time to create 1 rle with old method : 0.0007555484771728516 length of segment : 32 time for calcul the mask position with numpy : 0.000247955322265625 nb_pixel_total : 14540 time to create 1 rle with old method : 0.01704549789428711 length of segment : 136 time for calcul the mask position with numpy : 3.9577484130859375e-05 nb_pixel_total : 360 time to create 1 rle with old method : 0.0005142688751220703 length of segment : 50 time for calcul the mask position with numpy : 4.863739013671875e-05 nb_pixel_total : 644 time to create 1 rle with old method : 0.0008423328399658203 length of segment : 30 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -115.09453 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 5 time for calcul the mask position with numpy : 3.4809112548828125e-05 nb_pixel_total : 31 time to create 1 rle with old method : 7.43865966796875e-05 length of segment : 7 time for calcul the mask position with numpy : 3.933906555175781e-05 nb_pixel_total : 806 time to create 1 rle with old method : 0.0010728836059570312 length of segment : 37 time for calcul the mask position with numpy : 3.981590270996094e-05 nb_pixel_total : 755 time to create 1 rle with old method : 0.0009472370147705078 length of segment : 36 time for calcul the mask position with numpy : 5.841255187988281e-05 nb_pixel_total : 1229 time to create 1 rle with old method : 0.0017805099487304688 length of segment : 42 time for calcul the mask position with numpy : 0.00011396408081054688 nb_pixel_total : 4539 time to create 1 rle with old method : 0.005208492279052734 length of segment : 142 Processing 1 images image shape: (400, 320, 3) min: 0.00000 max: 240.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 118.48672 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 8 time for calcul the mask position with numpy : 5.91278076171875e-05 nb_pixel_total : 84 time to create 1 rle with old method : 0.00023365020751953125 length of segment : 17 time for calcul the mask position with numpy : 0.00022411346435546875 nb_pixel_total : 3003 time to create 1 rle with old method : 0.0050201416015625 length of segment : 177 time for calcul the mask position with numpy : 3.838539123535156e-05 nb_pixel_total : 137 time to create 1 rle with old method : 0.00021386146545410156 length of segment : 21 time for calcul the mask position with numpy : 6.127357482910156e-05 nb_pixel_total : 977 time to create 1 rle with old method : 0.0014073848724365234 length of segment : 80 time for calcul the mask position with numpy : 3.528594970703125e-05 nb_pixel_total : 299 time to create 1 rle with old method : 0.0004246234893798828 length of segment : 37 time for calcul the mask position with numpy : 3.886222839355469e-05 nb_pixel_total : 456 time to create 1 rle with old method : 0.0006482601165771484 length of segment : 50 time for calcul the mask position with numpy : 3.266334533691406e-05 nb_pixel_total : 166 time to create 1 rle with old method : 0.00024366378784179688 length of segment : 27 time for calcul the mask position with numpy : 3.528594970703125e-05 nb_pixel_total : 312 time to create 1 rle with old method : 0.000461578369140625 length of segment : 34 Processing 1 images image shape: (280, 400, 3) min: 27.00000 max: 201.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 83.26797 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 1 time for calcul the mask position with numpy : 0.0009586811065673828 nb_pixel_total : 106254 time to create 1 rle with old method : 0.11737871170043945 length of segment : 282 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 147.26016 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 7 time for calcul the mask position with numpy : 3.719329833984375e-05 nb_pixel_total : 156 time to create 1 rle with old method : 0.0002727508544921875 length of segment : 11 time for calcul the mask position with numpy : 5.221366882324219e-05 nb_pixel_total : 1613 time to create 1 rle with old method : 0.0029115676879882812 length of segment : 41 time for calcul the mask position with numpy : 5.316734313964844e-05 nb_pixel_total : 941 time to create 1 rle with old method : 0.0012557506561279297 length of segment : 36 time for calcul the mask position with numpy : 3.361701965332031e-05 nb_pixel_total : 189 time to create 1 rle with old method : 0.0003147125244140625 length of segment : 14 time for calcul the mask position with numpy : 7.152557373046875e-05 nb_pixel_total : 2543 time to create 1 rle with old method : 0.003361225128173828 length of segment : 71 time for calcul the mask position with numpy : 9.179115295410156e-05 nb_pixel_total : 1683 time to create 1 rle with old method : 0.002937793731689453 length of segment : 67 time for calcul the mask position with numpy : 0.00012755393981933594 nb_pixel_total : 7400 time to create 1 rle with old method : 0.00863194465637207 length of segment : 80 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 205.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 83.34219 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 2 time for calcul the mask position with numpy : 4.8160552978515625e-05 nb_pixel_total : 396 time to create 1 rle with old method : 0.0007350444793701172 length of segment : 20 time for calcul the mask position with numpy : 5.459785461425781e-05 nb_pixel_total : 151 time to create 1 rle with old method : 0.00042366981506347656 length of segment : 13 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 149.92422 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 7 time for calcul the mask position with numpy : 5.364418029785156e-05 nb_pixel_total : 673 time to create 1 rle with old method : 0.0008752346038818359 length of segment : 52 time for calcul the mask position with numpy : 3.814697265625e-05 nb_pixel_total : 211 time to create 1 rle with old method : 0.0002868175506591797 length of segment : 22 time for calcul the mask position with numpy : 3.4332275390625e-05 nb_pixel_total : 308 time to create 1 rle with old method : 0.0004482269287109375 length of segment : 24 time for calcul the mask position with numpy : 3.814697265625e-05 nb_pixel_total : 447 time to create 1 rle with old method : 0.0006909370422363281 length of segment : 33 time for calcul the mask position with numpy : 3.528594970703125e-05 nb_pixel_total : 118 time to create 1 rle with old method : 0.00017261505126953125 length of segment : 27 time for calcul the mask position with numpy : 4.982948303222656e-05 nb_pixel_total : 521 time to create 1 rle with old method : 0.0008237361907958984 length of segment : 26 time for calcul the mask position with numpy : 3.266334533691406e-05 nb_pixel_total : 268 time to create 1 rle with old method : 0.0004038810729980469 length of segment : 19 Processing 1 images image shape: (280, 320, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 132.45000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 2 time for calcul the mask position with numpy : 5.030632019042969e-05 nb_pixel_total : 380 time to create 1 rle with old method : 0.0006899833679199219 length of segment : 24 time for calcul the mask position with numpy : 5.555152893066406e-05 nb_pixel_total : 309 time to create 1 rle with old method : 0.0005548000335693359 length of segment : 17 NEW PHOTO pour l'instant on ne peut pas sauvegarder la photo dans les tile Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -117.43828 max: 144.97891 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 7 time for calcul the mask position with numpy : 6.604194641113281e-05 nb_pixel_total : 1009 time to create 1 rle with old method : 0.0015835762023925781 length of segment : 42 time for calcul the mask position with numpy : 4.076957702636719e-05 nb_pixel_total : 30 time to create 1 rle with old method : 8.821487426757812e-05 length of segment : 10 time for calcul the mask position with numpy : 4.3392181396484375e-05 nb_pixel_total : 1067 time to create 1 rle with old method : 0.0014328956604003906 length of segment : 37 time for calcul the mask position with numpy : 5.4836273193359375e-05 nb_pixel_total : 2059 time to create 1 rle with old method : 0.0028276443481445312 length of segment : 33 length of segment : 0 time for calcul the mask position with numpy : 3.6716461181640625e-05 nb_pixel_total : 270 time to create 1 rle with old method : 0.00037980079650878906 length of segment : 31 time for calcul the mask position with numpy : 4.100799560546875e-05 nb_pixel_total : 404 time to create 1 rle with old method : 0.0005402565002441406 length of segment : 46 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -119.11406 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 3 time for calcul the mask position with numpy : 5.054473876953125e-05 nb_pixel_total : 825 time to create 1 rle with old method : 0.0011029243469238281 length of segment : 38 time for calcul the mask position with numpy : 4.887580871582031e-05 nb_pixel_total : 1205 time to create 1 rle with old method : 0.0016832351684570312 length of segment : 30 time for calcul the mask position with numpy : 0.0002465248107910156 nb_pixel_total : 4287 time to create 1 rle with old method : 0.005164623260498047 length of segment : 164 Processing 1 images image shape: (400, 400, 3) min: 29.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -88.61016 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 2 time for calcul the mask position with numpy : 0.00012683868408203125 nb_pixel_total : 6316 time to create 1 rle with old method : 0.007712364196777344 length of segment : 126 time for calcul the mask position with numpy : 6.794929504394531e-05 nb_pixel_total : 932 time to create 1 rle with old method : 0.0013523101806640625 length of segment : 31 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -117.45000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 5 time for calcul the mask position with numpy : 0.00011301040649414062 nb_pixel_total : 4491 time to create 1 rle with old method : 0.00543212890625 length of segment : 111 time for calcul the mask position with numpy : 4.6253204345703125e-05 nb_pixel_total : 401 time to create 1 rle with old method : 0.0007054805755615234 length of segment : 22 time for calcul the mask position with numpy : 0.00016164779663085938 nb_pixel_total : 2340 time to create 1 rle with old method : 0.0036773681640625 length of segment : 186 time for calcul the mask position with numpy : 4.38690185546875e-05 nb_pixel_total : 418 time to create 1 rle with old method : 0.0006320476531982422 length of segment : 21 time for calcul the mask position with numpy : 3.2901763916015625e-05 nb_pixel_total : 253 time to create 1 rle with old method : 0.00034332275390625 length of segment : 23 Processing 1 images image shape: (400, 320, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 134.05703 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 2 time for calcul the mask position with numpy : 4.3392181396484375e-05 nb_pixel_total : 542 time to create 1 rle with old method : 0.0007750988006591797 length of segment : 23 time for calcul the mask position with numpy : 5.8650970458984375e-05 nb_pixel_total : 2426 time to create 1 rle with old method : 0.002966642379760742 length of segment : 62 Processing 1 images image shape: (400, 400, 3) min: 23.00000 max: 196.00000 molded_images shape: (1, 640, 640, 3) min: -82.05938 max: 78.26797 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 1 time for calcul the mask position with numpy : 0.0012204647064208984 nb_pixel_total : 149822 time to create 1 rle with old method : 0.15644097328186035 length of segment : 391 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -120.70000 max: 136.29141 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 11 time for calcul the mask position with numpy : 5.9604644775390625e-05 nb_pixel_total : 1288 time to create 1 rle with old method : 0.0016756057739257812 length of segment : 48 time for calcul the mask position with numpy : 3.409385681152344e-05 nb_pixel_total : 252 time to create 1 rle with old method : 0.0003590583801269531 length of segment : 20 time for calcul the mask position with numpy : 3.2901763916015625e-05 nb_pixel_total : 166 time to create 1 rle with old method : 0.00026488304138183594 length of segment : 17 time for calcul the mask position with numpy : 9.131431579589844e-05 nb_pixel_total : 2649 time to create 1 rle with old method : 0.0031075477600097656 length of segment : 110 time for calcul the mask position with numpy : 6.67572021484375e-05 nb_pixel_total : 340 time to create 1 rle with old method : 0.0009109973907470703 length of segment : 18 time for calcul the mask position with numpy : 7.271766662597656e-05 nb_pixel_total : 763 time to create 1 rle with old method : 0.0014967918395996094 length of segment : 32 time for calcul the mask position with numpy : 4.00543212890625e-05 nb_pixel_total : 522 time to create 1 rle with old method : 0.0006830692291259766 length of segment : 34 time for calcul the mask position with numpy : 3.170967102050781e-05 nb_pixel_total : 182 time to create 1 rle with old method : 0.00030231475830078125 length of segment : 12 time for calcul the mask position with numpy : 0.00011587142944335938 nb_pixel_total : 4782 time to create 1 rle with old method : 0.005736827850341797 length of segment : 94 time for calcul the mask position with numpy : 3.7670135498046875e-05 nb_pixel_total : 277 time to create 1 rle with old method : 0.0004341602325439453 length of segment : 12 time for calcul the mask position with numpy : 3.218650817871094e-05 nb_pixel_total : 224 time to create 1 rle with old method : 0.0003447532653808594 length of segment : 16 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -117.56328 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 9 time for calcul the mask position with numpy : 3.933906555175781e-05 nb_pixel_total : 194 time to create 1 rle with old method : 0.00028896331787109375 length of segment : 14 time for calcul the mask position with numpy : 5.555152893066406e-05 nb_pixel_total : 1975 time to create 1 rle with old method : 0.0024650096893310547 length of segment : 29 time for calcul the mask position with numpy : 5.0067901611328125e-05 nb_pixel_total : 1661 time to create 1 rle with old method : 0.002040386199951172 length of segment : 42 time for calcul the mask position with numpy : 3.5762786865234375e-05 nb_pixel_total : 532 time to create 1 rle with old method : 0.0006799697875976562 length of segment : 30 time for calcul the mask position with numpy : 3.147125244140625e-05 nb_pixel_total : 313 time to create 1 rle with old method : 0.0004074573516845703 length of segment : 22 time for calcul the mask position with numpy : 3.218650817871094e-05 nb_pixel_total : 295 time to create 1 rle with old method : 0.00044608116149902344 length of segment : 20 time for calcul the mask position with numpy : 3.4809112548828125e-05 nb_pixel_total : 416 time to create 1 rle with old method : 0.0005061626434326172 length of segment : 53 time for calcul the mask position with numpy : 9.202957153320312e-05 nb_pixel_total : 3293 time to create 1 rle with old method : 0.003891468048095703 length of segment : 73 time for calcul the mask position with numpy : 3.933906555175781e-05 nb_pixel_total : 660 time to create 1 rle with old method : 0.0007340908050537109 length of segment : 30 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -116.73516 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 10 time for calcul the mask position with numpy : 4.124641418457031e-05 nb_pixel_total : 33 time to create 1 rle with old method : 7.915496826171875e-05 length of segment : 8 time for calcul the mask position with numpy : 5.817413330078125e-05 nb_pixel_total : 1071 time to create 1 rle with old method : 0.0014119148254394531 length of segment : 110 time for calcul the mask position with numpy : 5.507469177246094e-05 nb_pixel_total : 1233 time to create 1 rle with old method : 0.0016291141510009766 length of segment : 43 time for calcul the mask position with numpy : 2.9325485229492188e-05 nb_pixel_total : 86 time to create 1 rle with old method : 0.00014734268188476562 length of segment : 10 time for calcul the mask position with numpy : 6.651878356933594e-05 nb_pixel_total : 1256 time to create 1 rle with old method : 0.0014579296112060547 length of segment : 115 time for calcul the mask position with numpy : 4.100799560546875e-05 nb_pixel_total : 778 time to create 1 rle with old method : 0.0009691715240478516 length of segment : 34 time for calcul the mask position with numpy : 6.985664367675781e-05 nb_pixel_total : 1174 time to create 1 rle with old method : 0.0014841556549072266 length of segment : 107 time for calcul the mask position with numpy : 3.600120544433594e-05 nb_pixel_total : 758 time to create 1 rle with old method : 0.0009202957153320312 length of segment : 36 time for calcul the mask position with numpy : 0.00011754035949707031 nb_pixel_total : 3273 time to create 1 rle with old method : 0.004232168197631836 length of segment : 166 time for calcul the mask position with numpy : 6.4849853515625e-05 nb_pixel_total : 1086 time to create 1 rle with old method : 0.0014257431030273438 length of segment : 109 Processing 1 images image shape: (400, 320, 3) min: 0.00000 max: 245.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 122.77187 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 13 time for calcul the mask position with numpy : 4.315376281738281e-05 nb_pixel_total : 132 time to create 1 rle with old method : 0.00019669532775878906 length of segment : 18 time for calcul the mask position with numpy : 0.00014543533325195312 nb_pixel_total : 2790 time to create 1 rle with old method : 0.005286216735839844 length of segment : 182 time for calcul the mask position with numpy : 9.107589721679688e-05 nb_pixel_total : 488 time to create 1 rle with old method : 0.0006792545318603516 length of segment : 53 time for calcul the mask position with numpy : 0.00011157989501953125 nb_pixel_total : 1223 time to create 1 rle with old method : 0.0016324520111083984 length of segment : 81 time for calcul the mask position with numpy : 4.9591064453125e-05 nb_pixel_total : 76 time to create 1 rle with old method : 0.0001423358917236328 length of segment : 16 time for calcul the mask position with numpy : 7.343292236328125e-05 nb_pixel_total : 1263 time to create 1 rle with old method : 0.0015621185302734375 length of segment : 82 time for calcul the mask position with numpy : 5.364418029785156e-05 nb_pixel_total : 364 time to create 1 rle with old method : 0.00048804283142089844 length of segment : 36 time for calcul the mask position with numpy : 9.965896606445312e-05 nb_pixel_total : 257 time to create 1 rle with old method : 0.0009050369262695312 length of segment : 44 time for calcul the mask position with numpy : 3.790855407714844e-05 nb_pixel_total : 175 time to create 1 rle with old method : 0.0002567768096923828 length of segment : 26 time for calcul the mask position with numpy : 6.508827209472656e-05 nb_pixel_total : 365 time to create 1 rle with old method : 0.0007355213165283203 length of segment : 36 time for calcul the mask position with numpy : 4.3392181396484375e-05 nb_pixel_total : 660 time to create 1 rle with old method : 0.0007936954498291016 length of segment : 40 time for calcul the mask position with numpy : 4.4345855712890625e-05 nb_pixel_total : 659 time to create 1 rle with old method : 0.0008037090301513672 length of segment : 50 time for calcul the mask position with numpy : 4.00543212890625e-05 nb_pixel_total : 582 time to create 1 rle with old method : 0.0007264614105224609 length of segment : 39 Processing 1 images image shape: (280, 400, 3) min: 31.00000 max: 198.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 80.19375 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 1 time for calcul the mask position with numpy : 0.0008492469787597656 nb_pixel_total : 106587 time to create 1 rle with old method : 0.10939598083496094 length of segment : 281 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 147.21328 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 9 time for calcul the mask position with numpy : 3.933906555175781e-05 nb_pixel_total : 223 time to create 1 rle with old method : 0.0003285408020019531 length of segment : 19 time for calcul the mask position with numpy : 6.723403930664062e-05 nb_pixel_total : 2607 time to create 1 rle with old method : 0.003075838088989258 length of segment : 74 time for calcul the mask position with numpy : 5.7220458984375e-05 nb_pixel_total : 1673 time to create 1 rle with old method : 0.0019545555114746094 length of segment : 62 time for calcul the mask position with numpy : 4.9114227294921875e-05 nb_pixel_total : 1655 time to create 1 rle with old method : 0.0018947124481201172 length of segment : 42 time for calcul the mask position with numpy : 4.1961669921875e-05 nb_pixel_total : 974 time to create 1 rle with old method : 0.0012056827545166016 length of segment : 38 time for calcul the mask position with numpy : 0.00011324882507324219 nb_pixel_total : 7437 time to create 1 rle with old method : 0.008252620697021484 length of segment : 78 time for calcul the mask position with numpy : 4.696846008300781e-05 nb_pixel_total : 1277 time to create 1 rle with old method : 0.0015964508056640625 length of segment : 46 time for calcul the mask position with numpy : 6.556510925292969e-05 nb_pixel_total : 2888 time to create 1 rle with old method : 0.0034253597259521484 length of segment : 66 time for calcul the mask position with numpy : 4.076957702636719e-05 nb_pixel_total : 366 time to create 1 rle with old method : 0.0004718303680419922 length of segment : 50 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 206.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 88.76797 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 2 time for calcul the mask position with numpy : 3.9577484130859375e-05 nb_pixel_total : 403 time to create 1 rle with old method : 0.0005359649658203125 length of segment : 21 time for calcul the mask position with numpy : 3.0517578125e-05 nb_pixel_total : 136 time to create 1 rle with old method : 0.00021195411682128906 length of segment : 14 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 149.71719 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 7 time for calcul the mask position with numpy : 4.1961669921875e-05 nb_pixel_total : 254 time to create 1 rle with old method : 0.0003426074981689453 length of segment : 34 time for calcul the mask position with numpy : 3.5762786865234375e-05 nb_pixel_total : 273 time to create 1 rle with old method : 0.0003802776336669922 length of segment : 24 time for calcul the mask position with numpy : 3.1948089599609375e-05 nb_pixel_total : 133 time to create 1 rle with old method : 0.00019049644470214844 length of segment : 28 time for calcul the mask position with numpy : 7.772445678710938e-05 nb_pixel_total : 3243 time to create 1 rle with old method : 0.0041348934173583984 length of segment : 83 time for calcul the mask position with numpy : 5.316734313964844e-05 nb_pixel_total : 441 time to create 1 rle with old method : 0.0006701946258544922 length of segment : 24 time for calcul the mask position with numpy : 3.5762786865234375e-05 nb_pixel_total : 239 time to create 1 rle with old method : 0.00039267539978027344 length of segment : 23 time for calcul the mask position with numpy : 7.557868957519531e-05 nb_pixel_total : 3581 time to create 1 rle with old method : 0.004083871841430664 length of segment : 91 Processing 1 images image shape: (280, 320, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 130.82500 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 2 time for calcul the mask position with numpy : 6.008148193359375e-05 nb_pixel_total : 312 time to create 1 rle with old method : 0.0006754398345947266 length of segment : 17 time for calcul the mask position with numpy : 5.9604644775390625e-05 nb_pixel_total : 378 time to create 1 rle with old method : 0.0008423328399658203 length of segment : 24 NEW PHOTO pour l'instant on ne peut pas sauvegarder la photo dans les tile Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -116.63359 max: 145.18203 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 5 time for calcul the mask position with numpy : 5.698204040527344e-05 nb_pixel_total : 1059 time to create 1 rle with old method : 0.001435995101928711 length of segment : 37 time for calcul the mask position with numpy : 3.910064697265625e-05 nb_pixel_total : 19 time to create 1 rle with old method : 5.650520324707031e-05 length of segment : 7 time for calcul the mask position with numpy : 3.528594970703125e-05 nb_pixel_total : 251 time to create 1 rle with old method : 0.00036072731018066406 length of segment : 30 time for calcul the mask position with numpy : 7.200241088867188e-05 nb_pixel_total : 2017 time to create 1 rle with old method : 0.0025594234466552734 length of segment : 53 time for calcul the mask position with numpy : 5.2928924560546875e-05 nb_pixel_total : 951 time to create 1 rle with old method : 0.0012111663818359375 length of segment : 32 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -117.45781 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 5 time for calcul the mask position with numpy : 5.841255187988281e-05 nb_pixel_total : 788 time to create 1 rle with old method : 0.0010159015655517578 length of segment : 36 time for calcul the mask position with numpy : 7.200241088867188e-05 nb_pixel_total : 2124 time to create 1 rle with old method : 0.002795696258544922 length of segment : 51 time for calcul the mask position with numpy : 9.274482727050781e-05 nb_pixel_total : 2195 time to create 1 rle with old method : 0.002906322479248047 length of segment : 50 time for calcul the mask position with numpy : 6.151199340820312e-05 nb_pixel_total : 733 time to create 1 rle with old method : 0.0009684562683105469 length of segment : 42 time for calcul the mask position with numpy : 4.6253204345703125e-05 nb_pixel_total : 140 time to create 1 rle with old method : 0.0002474784851074219 length of segment : 24 Processing 1 images image shape: (400, 400, 3) min: 23.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -82.97734 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 3 time for calcul the mask position with numpy : 4.57763671875e-05 nb_pixel_total : 669 time to create 1 rle with old method : 0.0007686614990234375 length of segment : 39 time for calcul the mask position with numpy : 0.00011730194091796875 nb_pixel_total : 5703 time to create 1 rle with old method : 0.006096363067626953 length of segment : 114 time for calcul the mask position with numpy : 3.981590270996094e-05 nb_pixel_total : 678 time to create 1 rle with old method : 0.000885009765625 length of segment : 28 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -120.60625 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 4 time for calcul the mask position with numpy : 0.00010800361633300781 nb_pixel_total : 4926 time to create 1 rle with old method : 0.0054492950439453125 length of segment : 114 time for calcul the mask position with numpy : 9.942054748535156e-05 nb_pixel_total : 4174 time to create 1 rle with old method : 0.004776477813720703 length of segment : 182 time for calcul the mask position with numpy : 3.9577484130859375e-05 nb_pixel_total : 323 time to create 1 rle with old method : 0.0005795955657958984 length of segment : 19 time for calcul the mask position with numpy : 3.0040740966796875e-05 nb_pixel_total : 262 time to create 1 rle with old method : 0.0003368854522705078 length of segment : 23 Processing 1 images image shape: (400, 320, 3) min: 0.00000 max: 253.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 131.79922 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 1 time for calcul the mask position with numpy : 4.696846008300781e-05 nb_pixel_total : 504 time to create 1 rle with old method : 0.0007181167602539062 length of segment : 19 Processing 1 images image shape: (400, 400, 3) min: 19.00000 max: 203.00000 molded_images shape: (1, 640, 640, 3) min: -81.86406 max: 84.29141 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 0 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -120.87578 max: 147.14687 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 12 time for calcul the mask position with numpy : 5.125999450683594e-05 nb_pixel_total : 250 time to create 1 rle with old method : 0.0003571510314941406 length of segment : 20 time for calcul the mask position with numpy : 3.337860107421875e-05 nb_pixel_total : 118 time to create 1 rle with old method : 0.0002086162567138672 length of segment : 10 time for calcul the mask position with numpy : 8.869171142578125e-05 nb_pixel_total : 1076 time to create 1 rle with old method : 0.0016474723815917969 length of segment : 71 time for calcul the mask position with numpy : 4.482269287109375e-05 nb_pixel_total : 600 time to create 1 rle with old method : 0.0007607936859130859 length of segment : 28 time for calcul the mask position with numpy : 3.5762786865234375e-05 nb_pixel_total : 498 time to create 1 rle with old method : 0.0006210803985595703 length of segment : 30 time for calcul the mask position with numpy : 4.100799560546875e-05 nb_pixel_total : 706 time to create 1 rle with old method : 0.0009055137634277344 length of segment : 27 time for calcul the mask position with numpy : 3.528594970703125e-05 nb_pixel_total : 385 time to create 1 rle with old method : 0.000522613525390625 length of segment : 22 time for calcul the mask position with numpy : 3.218650817871094e-05 nb_pixel_total : 270 time to create 1 rle with old method : 0.0003955364227294922 length of segment : 14 time for calcul the mask position with numpy : 0.0001971721649169922 nb_pixel_total : 6123 time to create 1 rle with old method : 0.0072400569915771484 length of segment : 113 time for calcul the mask position with numpy : 5.054473876953125e-05 nb_pixel_total : 756 time to create 1 rle with old method : 0.0009441375732421875 length of segment : 38 time for calcul the mask position with numpy : 3.1948089599609375e-05 nb_pixel_total : 274 time to create 1 rle with old method : 0.00040411949157714844 length of segment : 17 time for calcul the mask position with numpy : 2.9802322387695312e-05 nb_pixel_total : 227 time to create 1 rle with old method : 0.0003142356872558594 length of segment : 17 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -119.58672 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 6 time for calcul the mask position with numpy : 4.696846008300781e-05 nb_pixel_total : 158 time to create 1 rle with old method : 0.00027489662170410156 length of segment : 11 time for calcul the mask position with numpy : 0.0002498626708984375 nb_pixel_total : 15766 time to create 1 rle with old method : 0.018271684646606445 length of segment : 160 time for calcul the mask position with numpy : 4.792213439941406e-05 nb_pixel_total : 424 time to create 1 rle with old method : 0.0006043910980224609 length of segment : 29 time for calcul the mask position with numpy : 5.793571472167969e-05 nb_pixel_total : 1691 time to create 1 rle with old method : 0.002194643020629883 length of segment : 25 time for calcul the mask position with numpy : 6.270408630371094e-05 nb_pixel_total : 1689 time to create 1 rle with old method : 0.0022580623626708984 length of segment : 46 time for calcul the mask position with numpy : 3.9577484130859375e-05 nb_pixel_total : 663 time to create 1 rle with old method : 0.000820159912109375 length of segment : 29 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -113.59844 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 7 time for calcul the mask position with numpy : 7.557868957519531e-05 nb_pixel_total : 1305 time to create 1 rle with old method : 0.0017011165618896484 length of segment : 43 time for calcul the mask position with numpy : 3.266334533691406e-05 nb_pixel_total : 173 time to create 1 rle with old method : 0.0002713203430175781 length of segment : 14 time for calcul the mask position with numpy : 3.123283386230469e-05 nb_pixel_total : 251 time to create 1 rle with old method : 0.0004088878631591797 length of segment : 25 time for calcul the mask position with numpy : 6.771087646484375e-05 nb_pixel_total : 1444 time to create 1 rle with old method : 0.0017514228820800781 length of segment : 119 time for calcul the mask position with numpy : 3.790855407714844e-05 nb_pixel_total : 708 time to create 1 rle with old method : 0.0008363723754882812 length of segment : 35 time for calcul the mask position with numpy : 2.9087066650390625e-05 nb_pixel_total : 36 time to create 1 rle with old method : 7.557868957519531e-05 length of segment : 9 time for calcul the mask position with numpy : 0.00011277198791503906 nb_pixel_total : 4543 time to create 1 rle with old method : 0.005513906478881836 length of segment : 135 Processing 1 images image shape: (400, 320, 3) min: 0.00000 max: 243.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 122.45937 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 9 time for calcul the mask position with numpy : 4.3392181396484375e-05 nb_pixel_total : 378 time to create 1 rle with old method : 0.00047326087951660156 length of segment : 38 time for calcul the mask position with numpy : 0.00015282630920410156 nb_pixel_total : 3019 time to create 1 rle with old method : 0.0037746429443359375 length of segment : 177 time for calcul the mask position with numpy : 3.266334533691406e-05 nb_pixel_total : 136 time to create 1 rle with old method : 0.00018787384033203125 length of segment : 20 time for calcul the mask position with numpy : 5.4836273193359375e-05 nb_pixel_total : 881 time to create 1 rle with old method : 0.0011761188507080078 length of segment : 70 time for calcul the mask position with numpy : 2.9802322387695312e-05 nb_pixel_total : 105 time to create 1 rle with old method : 0.00015306472778320312 length of segment : 18 time for calcul the mask position with numpy : 3.409385681152344e-05 nb_pixel_total : 373 time to create 1 rle with old method : 0.0005042552947998047 length of segment : 48 time for calcul the mask position with numpy : 4.410743713378906e-05 nb_pixel_total : 188 time to create 1 rle with old method : 0.0003273487091064453 length of segment : 57 time for calcul the mask position with numpy : 4.029273986816406e-05 nb_pixel_total : 647 time to create 1 rle with old method : 0.000812530517578125 length of segment : 41 time for calcul the mask position with numpy : 3.2901763916015625e-05 nb_pixel_total : 178 time to create 1 rle with old method : 0.00026297569274902344 length of segment : 26 Processing 1 images image shape: (280, 400, 3) min: 23.00000 max: 216.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 96.60391 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 1 time for calcul the mask position with numpy : 0.0008556842803955078 nb_pixel_total : 106344 time to create 1 rle with old method : 0.11884713172912598 length of segment : 280 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 142.32266 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 10 time for calcul the mask position with numpy : 3.981590270996094e-05 nb_pixel_total : 169 time to create 1 rle with old method : 0.00027298927307128906 length of segment : 11 time for calcul the mask position with numpy : 3.409385681152344e-05 nb_pixel_total : 333 time to create 1 rle with old method : 0.0004477500915527344 length of segment : 25 time for calcul the mask position with numpy : 4.8160552978515625e-05 nb_pixel_total : 1639 time to create 1 rle with old method : 0.0019502639770507812 length of segment : 41 time for calcul the mask position with numpy : 3.4332275390625e-05 nb_pixel_total : 485 time to create 1 rle with old method : 0.0005793571472167969 length of segment : 47 time for calcul the mask position with numpy : 6.198883056640625e-05 nb_pixel_total : 2451 time to create 1 rle with old method : 0.0028734207153320312 length of segment : 70 time for calcul the mask position with numpy : 2.6941299438476562e-05 nb_pixel_total : 36 time to create 1 rle with old method : 6.580352783203125e-05 length of segment : 8 time for calcul the mask position with numpy : 3.933906555175781e-05 nb_pixel_total : 900 time to create 1 rle with old method : 0.0010619163513183594 length of segment : 36 time for calcul the mask position with numpy : 3.24249267578125e-05 nb_pixel_total : 227 time to create 1 rle with old method : 0.0003025531768798828 length of segment : 24 time for calcul the mask position with numpy : 2.9087066650390625e-05 nb_pixel_total : 167 time to create 1 rle with old method : 0.00025844573974609375 length of segment : 20 time for calcul the mask position with numpy : 0.00011229515075683594 nb_pixel_total : 7523 time to create 1 rle with old method : 0.008564233779907227 length of segment : 79 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 208.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 87.62344 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 2 time for calcul the mask position with numpy : 3.886222839355469e-05 nb_pixel_total : 327 time to create 1 rle with old method : 0.00045180320739746094 length of segment : 19 time for calcul the mask position with numpy : 3.0040740966796875e-05 nb_pixel_total : 299 time to create 1 rle with old method : 0.00040268898010253906 length of segment : 19 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 150.57266 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 5 time for calcul the mask position with numpy : 6.747245788574219e-05 nb_pixel_total : 2239 time to create 1 rle with old method : 0.002488374710083008 length of segment : 91 time for calcul the mask position with numpy : 3.314018249511719e-05 nb_pixel_total : 349 time to create 1 rle with old method : 0.0004398822784423828 length of segment : 27 time for calcul the mask position with numpy : 3.886222839355469e-05 nb_pixel_total : 539 time to create 1 rle with old method : 0.000762939453125 length of segment : 33 time for calcul the mask position with numpy : 0.0001266002655029297 nb_pixel_total : 238 time to create 1 rle with old method : 0.00031828880310058594 length of segment : 36 length of segment : 0 Processing 1 images image shape: (280, 320, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 132.60000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 3 time for calcul the mask position with numpy : 4.172325134277344e-05 nb_pixel_total : 395 time to create 1 rle with old method : 0.0005445480346679688 length of segment : 25 time for calcul the mask position with numpy : 3.123283386230469e-05 nb_pixel_total : 305 time to create 1 rle with old method : 0.00042629241943359375 length of segment : 17 time for calcul the mask position with numpy : 3.147125244140625e-05 nb_pixel_total : 486 time to create 1 rle with old method : 0.0005736351013183594 length of segment : 36 NEW PHOTO pour l'instant on ne peut pas sauvegarder la photo dans les tile Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -117.43828 max: 145.11172 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 6 time for calcul the mask position with numpy : 5.078315734863281e-05 nb_pixel_total : 902 time to create 1 rle with old method : 0.00116729736328125 length of segment : 32 time for calcul the mask position with numpy : 3.147125244140625e-05 nb_pixel_total : 28 time to create 1 rle with old method : 0.00013828277587890625 length of segment : 9 time for calcul the mask position with numpy : 3.337860107421875e-05 nb_pixel_total : 257 time to create 1 rle with old method : 0.00035190582275390625 length of segment : 28 time for calcul the mask position with numpy : 4.57763671875e-05 nb_pixel_total : 1113 time to create 1 rle with old method : 0.001478433609008789 length of segment : 35 time for calcul the mask position with numpy : 4.744529724121094e-05 nb_pixel_total : 1018 time to create 1 rle with old method : 0.0014123916625976562 length of segment : 63 time for calcul the mask position with numpy : 3.814697265625e-05 nb_pixel_total : 333 time to create 1 rle with old method : 0.0004596710205078125 length of segment : 33 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -118.09063 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 6 time for calcul the mask position with numpy : 5.745887756347656e-05 nb_pixel_total : 256 time to create 1 rle with old method : 0.0005400180816650391 length of segment : 29 time for calcul the mask position with numpy : 7.62939453125e-05 nb_pixel_total : 2258 time to create 1 rle with old method : 0.003946065902709961 length of segment : 52 time for calcul the mask position with numpy : 8.487701416015625e-05 nb_pixel_total : 1825 time to create 1 rle with old method : 0.0031256675720214844 length of segment : 103 time for calcul the mask position with numpy : 0.0001232624053955078 nb_pixel_total : 4625 time to create 1 rle with old method : 0.007604360580444336 length of segment : 129 time for calcul the mask position with numpy : 3.743171691894531e-05 nb_pixel_total : 204 time to create 1 rle with old method : 0.0002968311309814453 length of segment : 30 time for calcul the mask position with numpy : 3.0279159545898438e-05 nb_pixel_total : 99 time to create 1 rle with old method : 0.0001761913299560547 length of segment : 8 Processing 1 images image shape: (400, 400, 3) min: 26.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -83.17656 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 1 time for calcul the mask position with numpy : 4.792213439941406e-05 nb_pixel_total : 846 time to create 1 rle with old method : 0.0010302066802978516 length of segment : 49 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -117.20000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 3 time for calcul the mask position with numpy : 4.887580871582031e-05 nb_pixel_total : 372 time to create 1 rle with old method : 0.0006382465362548828 length of segment : 21 time for calcul the mask position with numpy : 0.00010514259338378906 nb_pixel_total : 4455 time to create 1 rle with old method : 0.005229473114013672 length of segment : 188 time for calcul the mask position with numpy : 0.00013208389282226562 nb_pixel_total : 6365 time to create 1 rle with old method : 0.007764339447021484 length of segment : 140 Processing 1 images image shape: (400, 320, 3) min: 0.00000 max: 241.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 111.82656 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 3 time for calcul the mask position with numpy : 4.38690185546875e-05 nb_pixel_total : 509 time to create 1 rle with old method : 0.0006883144378662109 length of segment : 20 time for calcul the mask position with numpy : 4.267692565917969e-05 nb_pixel_total : 744 time to create 1 rle with old method : 0.0009400844573974609 length of segment : 52 time for calcul the mask position with numpy : 0.0004830360412597656 nb_pixel_total : 41890 time to create 1 rle with old method : 0.04277348518371582 length of segment : 280 Processing 1 images image shape: (400, 400, 3) min: 19.00000 max: 202.00000 molded_images shape: (1, 640, 640, 3) min: -83.07500 max: 80.42031 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 1 time for calcul the mask position with numpy : 0.0012307167053222656 nb_pixel_total : 149998 time to create 1 rle with old method : 0.16031193733215332 length of segment : 394 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -119.48516 max: 137.16641 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 11 time for calcul the mask position with numpy : 4.506111145019531e-05 nb_pixel_total : 255 time to create 1 rle with old method : 0.0003502368927001953 length of segment : 19 time for calcul the mask position with numpy : 3.0279159545898438e-05 nb_pixel_total : 118 time to create 1 rle with old method : 0.000209808349609375 length of segment : 10 time for calcul the mask position with numpy : 2.9325485229492188e-05 nb_pixel_total : 209 time to create 1 rle with old method : 0.00031828880310058594 length of segment : 10 time for calcul the mask position with numpy : 4.220008850097656e-05 nb_pixel_total : 1008 time to create 1 rle with old method : 0.0012671947479248047 length of segment : 70 time for calcul the mask position with numpy : 0.00014352798461914062 nb_pixel_total : 8455 time to create 1 rle with old method : 0.009757518768310547 length of segment : 164 time for calcul the mask position with numpy : 5.1021575927734375e-05 nb_pixel_total : 556 time to create 1 rle with old method : 0.0007534027099609375 length of segment : 34 time for calcul the mask position with numpy : 3.7670135498046875e-05 nb_pixel_total : 405 time to create 1 rle with old method : 0.0006308555603027344 length of segment : 22 time for calcul the mask position with numpy : 9.1552734375e-05 nb_pixel_total : 3448 time to create 1 rle with old method : 0.004504203796386719 length of segment : 67 time for calcul the mask position with numpy : 4.220008850097656e-05 nb_pixel_total : 546 time to create 1 rle with old method : 0.0007364749908447266 length of segment : 33 time for calcul the mask position with numpy : 3.147125244140625e-05 nb_pixel_total : 212 time to create 1 rle with old method : 0.0003151893615722656 length of segment : 16 time for calcul the mask position with numpy : 3.933906555175781e-05 nb_pixel_total : 428 time to create 1 rle with old method : 0.0006186962127685547 length of segment : 21 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -119.58672 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 4 time for calcul the mask position with numpy : 4.100799560546875e-05 nb_pixel_total : 170 time to create 1 rle with old method : 0.0002779960632324219 length of segment : 12 time for calcul the mask position with numpy : 5.1975250244140625e-05 nb_pixel_total : 1708 time to create 1 rle with old method : 0.002163410186767578 length of segment : 46 time for calcul the mask position with numpy : 6.198883056640625e-05 nb_pixel_total : 1860 time to create 1 rle with old method : 0.0025246143341064453 length of segment : 28 time for calcul the mask position with numpy : 5.14984130859375e-05 nb_pixel_total : 749 time to create 1 rle with old method : 0.0010709762573242188 length of segment : 31 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -114.84063 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 5 time for calcul the mask position with numpy : 6.413459777832031e-05 nb_pixel_total : 1330 time to create 1 rle with old method : 0.0016622543334960938 length of segment : 44 time for calcul the mask position with numpy : 3.123283386230469e-05 nb_pixel_total : 34 time to create 1 rle with old method : 7.128715515136719e-05 length of segment : 8 time for calcul the mask position with numpy : 8.106231689453125e-05 nb_pixel_total : 921 time to create 1 rle with old method : 0.001132965087890625 length of segment : 89 time for calcul the mask position with numpy : 4.220008850097656e-05 nb_pixel_total : 701 time to create 1 rle with old method : 0.0009157657623291016 length of segment : 33 time for calcul the mask position with numpy : 0.00010561943054199219 nb_pixel_total : 698 time to create 1 rle with old method : 0.0008916854858398438 length of segment : 48 Processing 1 images image shape: (400, 320, 3) min: 0.00000 max: 246.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 115.52969 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 8 time for calcul the mask position with numpy : 4.792213439941406e-05 nb_pixel_total : 217 time to create 1 rle with old method : 0.00034618377685546875 length of segment : 59 time for calcul the mask position with numpy : 0.0001380443572998047 nb_pixel_total : 3049 time to create 1 rle with old method : 0.0036880970001220703 length of segment : 183 time for calcul the mask position with numpy : 4.649162292480469e-05 nb_pixel_total : 347 time to create 1 rle with old method : 0.00043773651123046875 length of segment : 37 time for calcul the mask position with numpy : 4.2438507080078125e-05 nb_pixel_total : 597 time to create 1 rle with old method : 0.0007658004760742188 length of segment : 46 time for calcul the mask position with numpy : 2.956390380859375e-05 nb_pixel_total : 143 time to create 1 rle with old method : 0.00019884109497070312 length of segment : 24 time for calcul the mask position with numpy : 4.887580871582031e-05 nb_pixel_total : 487 time to create 1 rle with old method : 0.0005979537963867188 length of segment : 47 time for calcul the mask position with numpy : 3.457069396972656e-05 nb_pixel_total : 355 time to create 1 rle with old method : 0.0004749298095703125 length of segment : 37 time for calcul the mask position with numpy : 3.981590270996094e-05 nb_pixel_total : 672 time to create 1 rle with old method : 0.0008118152618408203 length of segment : 40 Processing 1 images image shape: (280, 400, 3) min: 32.00000 max: 214.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 94.80312 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 1 time for calcul the mask position with numpy : 0.0009462833404541016 nb_pixel_total : 106032 time to create 1 rle with old method : 0.10761189460754395 length of segment : 280 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 142.85781 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 9 time for calcul the mask position with numpy : 4.0531158447265625e-05 nb_pixel_total : 188 time to create 1 rle with old method : 0.0002865791320800781 length of segment : 12 time for calcul the mask position with numpy : 4.935264587402344e-05 nb_pixel_total : 1643 time to create 1 rle with old method : 0.001961946487426758 length of segment : 42 time for calcul the mask position with numpy : 3.3855438232421875e-05 nb_pixel_total : 440 time to create 1 rle with old method : 0.0005238056182861328 length of segment : 47 time for calcul the mask position with numpy : 6.413459777832031e-05 nb_pixel_total : 2566 time to create 1 rle with old method : 0.0029158592224121094 length of segment : 75 time for calcul the mask position with numpy : 0.00012230873107910156 nb_pixel_total : 7515 time to create 1 rle with old method : 0.007881402969360352 length of segment : 80 time for calcul the mask position with numpy : 3.981590270996094e-05 nb_pixel_total : 885 time to create 1 rle with old method : 0.0010123252868652344 length of segment : 36 time for calcul the mask position with numpy : 5.9604644775390625e-05 nb_pixel_total : 1620 time to create 1 rle with old method : 0.0019381046295166016 length of segment : 60 time for calcul the mask position with numpy : 0.0001926422119140625 nb_pixel_total : 10074 time to create 1 rle with old method : 0.011599302291870117 length of segment : 169 time for calcul the mask position with numpy : 8.106231689453125e-05 nb_pixel_total : 2875 time to create 1 rle with old method : 0.003692626953125 length of segment : 62 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 222.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 79.78750 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 2 time for calcul the mask position with numpy : 4.482269287109375e-05 nb_pixel_total : 350 time to create 1 rle with old method : 0.0005576610565185547 length of segment : 17 time for calcul the mask position with numpy : 3.0040740966796875e-05 nb_pixel_total : 294 time to create 1 rle with old method : 0.00044274330139160156 length of segment : 18 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 150.19766 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 6 time for calcul the mask position with numpy : 4.0531158447265625e-05 nb_pixel_total : 272 time to create 1 rle with old method : 0.00036263465881347656 length of segment : 24 time for calcul the mask position with numpy : 2.956390380859375e-05 nb_pixel_total : 161 time to create 1 rle with old method : 0.00021529197692871094 length of segment : 28 time for calcul the mask position with numpy : 2.8848648071289062e-05 nb_pixel_total : 237 time to create 1 rle with old method : 0.0003170967102050781 length of segment : 24 time for calcul the mask position with numpy : 4.6253204345703125e-05 nb_pixel_total : 476 time to create 1 rle with old method : 0.0007007122039794922 length of segment : 32 time for calcul the mask position with numpy : 7.653236389160156e-05 nb_pixel_total : 3447 time to create 1 rle with old method : 0.003984928131103516 length of segment : 99 time for calcul the mask position with numpy : 0.00014400482177734375 nb_pixel_total : 370 time to create 1 rle with old method : 0.0005519390106201172 length of segment : 67 Processing 1 images image shape: (280, 320, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 132.22500 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 3 time for calcul the mask position with numpy : 3.910064697265625e-05 nb_pixel_total : 309 time to create 1 rle with old method : 0.0003917217254638672 length of segment : 17 time for calcul the mask position with numpy : 3.170967102050781e-05 nb_pixel_total : 374 time to create 1 rle with old method : 0.0005154609680175781 length of segment : 23 time for calcul the mask position with numpy : 0.0004260540008544922 nb_pixel_total : 40277 time to create 1 rle with old method : 0.04419302940368652 length of segment : 275 NEW PHOTO pour l'instant on ne peut pas sauvegarder la photo dans les tile Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -117.82500 max: 145.19766 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 6 time for calcul the mask position with numpy : 3.814697265625e-05 nb_pixel_total : 215 time to create 1 rle with old method : 0.0002720355987548828 length of segment : 25 time for calcul the mask position with numpy : 3.7670135498046875e-05 nb_pixel_total : 1006 time to create 1 rle with old method : 0.0012891292572021484 length of segment : 35 time for calcul the mask position with numpy : 2.765655517578125e-05 nb_pixel_total : 13 time to create 1 rle with old method : 4.482269287109375e-05 length of segment : 5 time for calcul the mask position with numpy : 3.743171691894531e-05 nb_pixel_total : 1077 time to create 1 rle with old method : 0.0013284683227539062 length of segment : 35 time for calcul the mask position with numpy : 2.6941299438476562e-05 nb_pixel_total : 12 time to create 1 rle with old method : 4.172325134277344e-05 length of segment : 9 time for calcul the mask position with numpy : 4.57763671875e-05 nb_pixel_total : 1738 time to create 1 rle with old method : 0.0020444393157958984 length of segment : 44 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -117.76641 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 7 time for calcul the mask position with numpy : 6.532669067382812e-05 nb_pixel_total : 2215 time to create 1 rle with old method : 0.0026273727416992188 length of segment : 49 time for calcul the mask position with numpy : 4.172325134277344e-05 nb_pixel_total : 837 time to create 1 rle with old method : 0.0009999275207519531 length of segment : 41 time for calcul the mask position with numpy : 3.0517578125e-05 nb_pixel_total : 262 time to create 1 rle with old method : 0.0003743171691894531 length of segment : 24 time for calcul the mask position with numpy : 3.504753112792969e-05 nb_pixel_total : 486 time to create 1 rle with old method : 0.0006692409515380859 length of segment : 56 time for calcul the mask position with numpy : 4.506111145019531e-05 nb_pixel_total : 661 time to create 1 rle with old method : 0.0008084774017333984 length of segment : 70 time for calcul the mask position with numpy : 5.53131103515625e-05 nb_pixel_total : 2169 time to create 1 rle with old method : 0.0027284622192382812 length of segment : 47 time for calcul the mask position with numpy : 3.552436828613281e-05 nb_pixel_total : 524 time to create 1 rle with old method : 0.0006642341613769531 length of segment : 32 Processing 1 images image shape: (400, 400, 3) min: 10.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -112.27422 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 1 time for calcul the mask position with numpy : 0.00020885467529296875 nb_pixel_total : 7793 time to create 1 rle with old method : 0.009251117706298828 length of segment : 228 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -120.57500 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 6 time for calcul the mask position with numpy : 9.775161743164062e-05 nb_pixel_total : 3471 time to create 1 rle with old method : 0.003941059112548828 length of segment : 163 time for calcul the mask position with numpy : 4.553794860839844e-05 nb_pixel_total : 1134 time to create 1 rle with old method : 0.0013213157653808594 length of segment : 66 time for calcul the mask position with numpy : 0.00010800361633300781 nb_pixel_total : 5989 time to create 1 rle with old method : 0.006551980972290039 length of segment : 143 time for calcul the mask position with numpy : 3.1948089599609375e-05 nb_pixel_total : 284 time to create 1 rle with old method : 0.0003437995910644531 length of segment : 25 time for calcul the mask position with numpy : 2.956390380859375e-05 nb_pixel_total : 237 time to create 1 rle with old method : 0.0003342628479003906 length of segment : 25 time for calcul the mask position with numpy : 0.00012755393981933594 nb_pixel_total : 9112 time to create 1 rle with old method : 0.009890556335449219 length of segment : 125 Processing 1 images image shape: (400, 320, 3) min: 0.00000 max: 254.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 131.82266 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 3 time for calcul the mask position with numpy : 4.553794860839844e-05 nb_pixel_total : 554 time to create 1 rle with old method : 0.0007345676422119141 length of segment : 21 time for calcul the mask position with numpy : 4.267692565917969e-05 nb_pixel_total : 1099 time to create 1 rle with old method : 0.001359701156616211 length of segment : 36 time for calcul the mask position with numpy : 3.2901763916015625e-05 nb_pixel_total : 362 time to create 1 rle with old method : 0.0004930496215820312 length of segment : 20 Processing 1 images image shape: (400, 400, 3) min: 23.00000 max: 198.00000 molded_images shape: (1, 640, 640, 3) min: -84.70000 max: 82.53750 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 1 time for calcul the mask position with numpy : 0.001219034194946289 nb_pixel_total : 150519 time to create 1 rle with new method : 0.0020360946655273438 length of segment : 396 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -121.23125 max: 137.76797 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 14 time for calcul the mask position with numpy : 7.152557373046875e-05 nb_pixel_total : 251 time to create 1 rle with old method : 0.0003838539123535156 length of segment : 18 time for calcul the mask position with numpy : 5.936622619628906e-05 nb_pixel_total : 1492 time to create 1 rle with old method : 0.0018792152404785156 length of segment : 53 time for calcul the mask position with numpy : 5.340576171875e-05 nb_pixel_total : 200 time to create 1 rle with old method : 0.00033092498779296875 length of segment : 9 time for calcul the mask position with numpy : 4.744529724121094e-05 nb_pixel_total : 570 time to create 1 rle with old method : 0.0007548332214355469 length of segment : 35 time for calcul the mask position with numpy : 9.655952453613281e-05 nb_pixel_total : 3061 time to create 1 rle with old method : 0.003746509552001953 length of segment : 48 time for calcul the mask position with numpy : 4.6253204345703125e-05 nb_pixel_total : 782 time to create 1 rle with old method : 0.0010395050048828125 length of segment : 28 time for calcul the mask position with numpy : 2.9325485229492188e-05 nb_pixel_total : 92 time to create 1 rle with old method : 0.0001621246337890625 length of segment : 9 time for calcul the mask position with numpy : 3.886222839355469e-05 nb_pixel_total : 449 time to create 1 rle with old method : 0.0006494522094726562 length of segment : 38 time for calcul the mask position with numpy : 3.62396240234375e-05 nb_pixel_total : 510 time to create 1 rle with old method : 0.0006670951843261719 length of segment : 23 time for calcul the mask position with numpy : 3.528594970703125e-05 nb_pixel_total : 295 time to create 1 rle with old method : 0.0004951953887939453 length of segment : 16 time for calcul the mask position with numpy : 3.409385681152344e-05 nb_pixel_total : 96 time to create 1 rle with old method : 0.0001647472381591797 length of segment : 23 time for calcul the mask position with numpy : 3.910064697265625e-05 nb_pixel_total : 561 time to create 1 rle with old method : 0.0007526874542236328 length of segment : 34 time for calcul the mask position with numpy : 3.600120544433594e-05 nb_pixel_total : 419 time to create 1 rle with old method : 0.0005691051483154297 length of segment : 20 time for calcul the mask position with numpy : 2.956390380859375e-05 nb_pixel_total : 250 time to create 1 rle with old method : 0.0003402233123779297 length of segment : 19 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -119.81719 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 5 time for calcul the mask position with numpy : 6.222724914550781e-05 nb_pixel_total : 1689 time to create 1 rle with old method : 0.002232074737548828 length of segment : 27 time for calcul the mask position with numpy : 3.600120544433594e-05 nb_pixel_total : 175 time to create 1 rle with old method : 0.00029397010803222656 length of segment : 13 time for calcul the mask position with numpy : 6.127357482910156e-05 nb_pixel_total : 1647 time to create 1 rle with old method : 0.0022420883178710938 length of segment : 43 time for calcul the mask position with numpy : 5.364418029785156e-05 nb_pixel_total : 1301 time to create 1 rle with old method : 0.0016524791717529297 length of segment : 46 time for calcul the mask position with numpy : 4.6253204345703125e-05 nb_pixel_total : 903 time to create 1 rle with old method : 0.0012011528015136719 length of segment : 48 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -119.79766 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 7 time for calcul the mask position with numpy : 6.318092346191406e-05 nb_pixel_total : 1305 time to create 1 rle with old method : 0.0017480850219726562 length of segment : 41 time for calcul the mask position with numpy : 3.2901763916015625e-05 nb_pixel_total : 40 time to create 1 rle with old method : 8.225440979003906e-05 length of segment : 9 time for calcul the mask position with numpy : 2.9325485229492188e-05 nb_pixel_total : 102 time to create 1 rle with old method : 0.000156402587890625 length of segment : 15 time for calcul the mask position with numpy : 3.838539123535156e-05 nb_pixel_total : 756 time to create 1 rle with old method : 0.0009961128234863281 length of segment : 35 time for calcul the mask position with numpy : 0.00032830238342285156 nb_pixel_total : 21400 time to create 1 rle with old method : 0.02410578727722168 length of segment : 294 time for calcul the mask position with numpy : 3.695487976074219e-05 nb_pixel_total : 146 time to create 1 rle with old method : 0.0002105236053466797 length of segment : 20 time for calcul the mask position with numpy : 4.696846008300781e-05 nb_pixel_total : 1213 time to create 1 rle with old method : 0.0015361309051513672 length of segment : 42 Processing 1 images image shape: (400, 320, 3) min: 0.00000 max: 235.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 111.61953 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 7 time for calcul the mask position with numpy : 0.0001373291015625 nb_pixel_total : 3051 time to create 1 rle with old method : 0.003590822219848633 length of segment : 176 time for calcul the mask position with numpy : 7.033348083496094e-05 nb_pixel_total : 1340 time to create 1 rle with old method : 0.001817941665649414 length of segment : 92 time for calcul the mask position with numpy : 4.649162292480469e-05 nb_pixel_total : 589 time to create 1 rle with old method : 0.0008466243743896484 length of segment : 73 time for calcul the mask position with numpy : 3.6716461181640625e-05 nb_pixel_total : 433 time to create 1 rle with old method : 0.00060272216796875 length of segment : 46 time for calcul the mask position with numpy : 2.9802322387695312e-05 nb_pixel_total : 123 time to create 1 rle with old method : 0.000194549560546875 length of segment : 20 time for calcul the mask position with numpy : 3.814697265625e-05 nb_pixel_total : 636 time to create 1 rle with old method : 0.0008027553558349609 length of segment : 39 time for calcul the mask position with numpy : 0.0001983642578125 nb_pixel_total : 4401 time to create 1 rle with old method : 0.0053615570068359375 length of segment : 237 Processing 1 images image shape: (280, 400, 3) min: 24.00000 max: 196.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 78.44766 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 1 time for calcul the mask position with numpy : 0.0011508464813232422 nb_pixel_total : 105720 time to create 1 rle with old method : 0.11180472373962402 length of segment : 280 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 149.26797 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 9 time for calcul the mask position with numpy : 6.29425048828125e-05 nb_pixel_total : 1698 time to create 1 rle with old method : 0.002050638198852539 length of segment : 61 time for calcul the mask position with numpy : 3.24249267578125e-05 nb_pixel_total : 156 time to create 1 rle with old method : 0.0002932548522949219 length of segment : 16 time for calcul the mask position with numpy : 3.0279159545898438e-05 nb_pixel_total : 134 time to create 1 rle with old method : 0.00022149085998535156 length of segment : 12 time for calcul the mask position with numpy : 3.910064697265625e-05 nb_pixel_total : 859 time to create 1 rle with old method : 0.0011343955993652344 length of segment : 35 time for calcul the mask position with numpy : 6.508827209472656e-05 nb_pixel_total : 1750 time to create 1 rle with old method : 0.002327442169189453 length of segment : 42 time for calcul the mask position with numpy : 3.1948089599609375e-05 nb_pixel_total : 178 time to create 1 rle with old method : 0.0002899169921875 length of segment : 21 time for calcul the mask position with numpy : 0.00011157989501953125 nb_pixel_total : 7235 time to create 1 rle with old method : 0.008365631103515625 length of segment : 78 time for calcul the mask position with numpy : 5.793571472167969e-05 nb_pixel_total : 1745 time to create 1 rle with old method : 0.0022661685943603516 length of segment : 61 time for calcul the mask position with numpy : 5.936622619628906e-05 nb_pixel_total : 1807 time to create 1 rle with old method : 0.002298116683959961 length of segment : 71 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 224.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 102.36953 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 1 time for calcul the mask position with numpy : 3.981590270996094e-05 nb_pixel_total : 430 time to create 1 rle with old method : 0.0006327629089355469 length of segment : 18 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 150.13906 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 8 time for calcul the mask position with numpy : 4.982948303222656e-05 nb_pixel_total : 419 time to create 1 rle with old method : 0.0005826950073242188 length of segment : 30 time for calcul the mask position with numpy : 3.170967102050781e-05 nb_pixel_total : 183 time to create 1 rle with old method : 0.0003464221954345703 length of segment : 23 time for calcul the mask position with numpy : 3.0279159545898438e-05 nb_pixel_total : 134 time to create 1 rle with old method : 0.00018906593322753906 length of segment : 27 time for calcul the mask position with numpy : 3.8623809814453125e-05 nb_pixel_total : 339 time to create 1 rle with old method : 0.0006430149078369141 length of segment : 19 time for calcul the mask position with numpy : 4.3392181396484375e-05 nb_pixel_total : 256 time to create 1 rle with old method : 0.0004665851593017578 length of segment : 16 time for calcul the mask position with numpy : 6.961822509765625e-05 nb_pixel_total : 2971 time to create 1 rle with old method : 0.0037300586700439453 length of segment : 103 time for calcul the mask position with numpy : 3.4809112548828125e-05 nb_pixel_total : 394 time to create 1 rle with old method : 0.0005545616149902344 length of segment : 27 time for calcul the mask position with numpy : 7.963180541992188e-05 nb_pixel_total : 3543 time to create 1 rle with old method : 0.004195451736450195 length of segment : 98 Processing 1 images image shape: (280, 320, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 134.13750 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 2 time for calcul the mask position with numpy : 3.814697265625e-05 nb_pixel_total : 306 time to create 1 rle with old method : 0.0004360675811767578 length of segment : 17 time for calcul the mask position with numpy : 3.5762786865234375e-05 nb_pixel_total : 406 time to create 1 rle with old method : 0.0006120204925537109 length of segment : 24 NEW PHOTO pour l'instant on ne peut pas sauvegarder la photo dans les tile Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -117.66875 max: 145.19766 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 5 time for calcul the mask position with numpy : 3.790855407714844e-05 nb_pixel_total : 313 time to create 1 rle with old method : 0.0004200935363769531 length of segment : 27 time for calcul the mask position with numpy : 4.1961669921875e-05 nb_pixel_total : 1004 time to create 1 rle with old method : 0.0014119148254394531 length of segment : 39 time for calcul the mask position with numpy : 3.123283386230469e-05 nb_pixel_total : 38 time to create 1 rle with old method : 7.867813110351562e-05 length of segment : 14 time for calcul the mask position with numpy : 6.198883056640625e-05 nb_pixel_total : 2117 time to create 1 rle with old method : 0.002622842788696289 length of segment : 66 length of segment : 0 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -117.55156 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 6 time for calcul the mask position with numpy : 4.744529724121094e-05 nb_pixel_total : 771 time to create 1 rle with old method : 0.0009617805480957031 length of segment : 37 time for calcul the mask position with numpy : 6.270408630371094e-05 nb_pixel_total : 2422 time to create 1 rle with old method : 0.0031108856201171875 length of segment : 48 time for calcul the mask position with numpy : 5.936622619628906e-05 nb_pixel_total : 1494 time to create 1 rle with old method : 0.0019211769104003906 length of segment : 69 time for calcul the mask position with numpy : 4.029273986816406e-05 nb_pixel_total : 701 time to create 1 rle with old method : 0.0008754730224609375 length of segment : 37 time for calcul the mask position with numpy : 6.318092346191406e-05 nb_pixel_total : 2400 time to create 1 rle with old method : 0.0029494762420654297 length of segment : 51 time for calcul the mask position with numpy : 3.361701965332031e-05 nb_pixel_total : 166 time to create 1 rle with old method : 0.0002913475036621094 length of segment : 37 Processing 1 images image shape: (400, 400, 3) min: 23.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -90.23516 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 2 time for calcul the mask position with numpy : 0.0002772808074951172 nb_pixel_total : 13213 time to create 1 rle with old method : 0.015987396240234375 length of segment : 214 time for calcul the mask position with numpy : 0.00010585784912109375 nb_pixel_total : 6320 time to create 1 rle with old method : 0.007669210433959961 length of segment : 106 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -118.51641 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 5 time for calcul the mask position with numpy : 0.00010180473327636719 nb_pixel_total : 1383 time to create 1 rle with old method : 0.0021615028381347656 length of segment : 91 time for calcul the mask position with numpy : 3.218650817871094e-05 nb_pixel_total : 108 time to create 1 rle with old method : 0.00017976760864257812 length of segment : 14 time for calcul the mask position with numpy : 3.123283386230469e-05 nb_pixel_total : 257 time to create 1 rle with old method : 0.0003600120544433594 length of segment : 23 time for calcul the mask position with numpy : 3.2901763916015625e-05 nb_pixel_total : 177 time to create 1 rle with old method : 0.0003216266632080078 length of segment : 13 time for calcul the mask position with numpy : 0.00010466575622558594 nb_pixel_total : 5555 time to create 1 rle with old method : 0.007041215896606445 length of segment : 106 Processing 1 images image shape: (400, 320, 3) min: 0.00000 max: 246.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 120.01406 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 3 time for calcul the mask position with numpy : 4.315376281738281e-05 nb_pixel_total : 541 time to create 1 rle with old method : 0.0008299350738525391 length of segment : 21 time for calcul the mask position with numpy : 3.2901763916015625e-05 nb_pixel_total : 248 time to create 1 rle with old method : 0.0003478527069091797 length of segment : 23 time for calcul the mask position with numpy : 3.0040740966796875e-05 nb_pixel_total : 114 time to create 1 rle with old method : 0.00020503997802734375 length of segment : 11 Processing 1 images image shape: (400, 400, 3) min: 26.00000 max: 190.00000 molded_images shape: (1, 640, 640, 3) min: -82.46563 max: 71.95547 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 1 time for calcul the mask position with numpy : 0.0013089179992675781 nb_pixel_total : 151281 time to create 1 rle with new method : 0.0019218921661376953 length of segment : 409 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -119.28203 max: 133.47109 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 11 time for calcul the mask position with numpy : 5.6743621826171875e-05 nb_pixel_total : 1239 time to create 1 rle with old method : 0.0016219615936279297 length of segment : 51 time for calcul the mask position with numpy : 3.409385681152344e-05 nb_pixel_total : 260 time to create 1 rle with old method : 0.00039768218994140625 length of segment : 19 time for calcul the mask position with numpy : 3.981590270996094e-05 nb_pixel_total : 772 time to create 1 rle with old method : 0.0011365413665771484 length of segment : 28 time for calcul the mask position with numpy : 3.838539123535156e-05 nb_pixel_total : 523 time to create 1 rle with old method : 0.0007033348083496094 length of segment : 32 time for calcul the mask position with numpy : 3.0279159545898438e-05 nb_pixel_total : 118 time to create 1 rle with old method : 0.00020313262939453125 length of segment : 11 time for calcul the mask position with numpy : 8.630752563476562e-05 nb_pixel_total : 3109 time to create 1 rle with old method : 0.003871440887451172 length of segment : 62 time for calcul the mask position with numpy : 3.910064697265625e-05 nb_pixel_total : 231 time to create 1 rle with old method : 0.0003273487091064453 length of segment : 25 time for calcul the mask position with numpy : 3.886222839355469e-05 nb_pixel_total : 495 time to create 1 rle with old method : 0.0007109642028808594 length of segment : 28 time for calcul the mask position with numpy : 3.695487976074219e-05 nb_pixel_total : 325 time to create 1 rle with old method : 0.0004904270172119141 length of segment : 46 time for calcul the mask position with numpy : 3.0994415283203125e-05 nb_pixel_total : 204 time to create 1 rle with old method : 0.0003237724304199219 length of segment : 10 time for calcul the mask position with numpy : 2.9802322387695312e-05 nb_pixel_total : 108 time to create 1 rle with old method : 0.00019931793212890625 length of segment : 7 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -119.73906 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 4 time for calcul the mask position with numpy : 6.628036499023438e-05 nb_pixel_total : 2197 time to create 1 rle with old method : 0.002766847610473633 length of segment : 42 time for calcul the mask position with numpy : 3.528594970703125e-05 nb_pixel_total : 166 time to create 1 rle with old method : 0.00028061866760253906 length of segment : 12 time for calcul the mask position with numpy : 4.4345855712890625e-05 nb_pixel_total : 719 time to create 1 rle with old method : 0.0010654926300048828 length of segment : 35 time for calcul the mask position with numpy : 4.291534423828125e-05 nb_pixel_total : 630 time to create 1 rle with old method : 0.0007984638214111328 length of segment : 98 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -112.46953 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 5 time for calcul the mask position with numpy : 5.555152893066406e-05 nb_pixel_total : 804 time to create 1 rle with old method : 0.0011219978332519531 length of segment : 40 time for calcul the mask position with numpy : 5.7697296142578125e-05 nb_pixel_total : 1051 time to create 1 rle with old method : 0.0013761520385742188 length of segment : 105 time for calcul the mask position with numpy : 8.249282836914062e-05 nb_pixel_total : 1230 time to create 1 rle with old method : 0.0015587806701660156 length of segment : 123 time for calcul the mask position with numpy : 4.601478576660156e-05 nb_pixel_total : 1246 time to create 1 rle with old method : 0.0015807151794433594 length of segment : 43 time for calcul the mask position with numpy : 4.3392181396484375e-05 nb_pixel_total : 1039 time to create 1 rle with old method : 0.0013844966888427734 length of segment : 37 Processing 1 images image shape: (400, 320, 3) min: 0.00000 max: 232.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 107.31094 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 7 time for calcul the mask position with numpy : 0.00016021728515625 nb_pixel_total : 3127 time to create 1 rle with old method : 0.0038034915924072266 length of segment : 180 time for calcul the mask position with numpy : 4.601478576660156e-05 nb_pixel_total : 690 time to create 1 rle with old method : 0.0008971691131591797 length of segment : 28 time for calcul the mask position with numpy : 3.337860107421875e-05 nb_pixel_total : 269 time to create 1 rle with old method : 0.00040030479431152344 length of segment : 32 time for calcul the mask position with numpy : 3.218650817871094e-05 nb_pixel_total : 230 time to create 1 rle with old method : 0.0003230571746826172 length of segment : 35 time for calcul the mask position with numpy : 3.0040740966796875e-05 nb_pixel_total : 143 time to create 1 rle with old method : 0.0002200603485107422 length of segment : 24 time for calcul the mask position with numpy : 3.8623809814453125e-05 nb_pixel_total : 676 time to create 1 rle with old method : 0.0009157657623291016 length of segment : 38 time for calcul the mask position with numpy : 3.814697265625e-05 nb_pixel_total : 669 time to create 1 rle with old method : 0.0008435249328613281 length of segment : 38 Processing 1 images image shape: (280, 400, 3) min: 25.00000 max: 199.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 81.47500 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 1 time for calcul the mask position with numpy : 0.0009524822235107422 nb_pixel_total : 106568 time to create 1 rle with old method : 0.1163015365600586 length of segment : 282 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 146.89297 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 11 time for calcul the mask position with numpy : 6.127357482910156e-05 nb_pixel_total : 1672 time to create 1 rle with old method : 0.0019996166229248047 length of segment : 60 time for calcul the mask position with numpy : 5.412101745605469e-05 nb_pixel_total : 1710 time to create 1 rle with old method : 0.0022203922271728516 length of segment : 44 time for calcul the mask position with numpy : 3.0994415283203125e-05 nb_pixel_total : 132 time to create 1 rle with old method : 0.0002200603485107422 length of segment : 12 time for calcul the mask position with numpy : 6.628036499023438e-05 nb_pixel_total : 2635 time to create 1 rle with old method : 0.003366231918334961 length of segment : 76 time for calcul the mask position with numpy : 3.0994415283203125e-05 nb_pixel_total : 167 time to create 1 rle with old method : 0.0003268718719482422 length of segment : 11 time for calcul the mask position with numpy : 4.076957702636719e-05 nb_pixel_total : 877 time to create 1 rle with old method : 0.001146078109741211 length of segment : 37 time for calcul the mask position with numpy : 3.5762786865234375e-05 nb_pixel_total : 428 time to create 1 rle with old method : 0.0005621910095214844 length of segment : 43 time for calcul the mask position with numpy : 3.147125244140625e-05 nb_pixel_total : 185 time to create 1 rle with old method : 0.000293731689453125 length of segment : 22 time for calcul the mask position with numpy : 3.719329833984375e-05 nb_pixel_total : 446 time to create 1 rle with old method : 0.0005984306335449219 length of segment : 33 time for calcul the mask position with numpy : 0.00011754035949707031 nb_pixel_total : 7580 time to create 1 rle with old method : 0.008937597274780273 length of segment : 81 time for calcul the mask position with numpy : 0.00011372566223144531 nb_pixel_total : 7436 time to create 1 rle with old method : 0.008794784545898438 length of segment : 80 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 225.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 98.76406 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 6 time for calcul the mask position with numpy : 4.4345855712890625e-05 nb_pixel_total : 69 time to create 1 rle with old method : 0.0001780986785888672 length of segment : 11 time for calcul the mask position with numpy : 7.414817810058594e-05 nb_pixel_total : 2798 time to create 1 rle with old method : 0.003575563430786133 length of segment : 91 time for calcul the mask position with numpy : 3.790855407714844e-05 nb_pixel_total : 378 time to create 1 rle with old method : 0.0005528926849365234 length of segment : 18 time for calcul the mask position with numpy : 3.4332275390625e-05 nb_pixel_total : 315 time to create 1 rle with old method : 0.0004456043243408203 length of segment : 19 time for calcul the mask position with numpy : 6.532669067382812e-05 nb_pixel_total : 2071 time to create 1 rle with old method : 0.002656221389770508 length of segment : 83 time for calcul the mask position with numpy : 3.361701965332031e-05 nb_pixel_total : 176 time to create 1 rle with old method : 0.00026798248291015625 length of segment : 18 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 149.95156 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 7 time for calcul the mask position with numpy : 4.029273986816406e-05 nb_pixel_total : 313 time to create 1 rle with old method : 0.00045943260192871094 length of segment : 24 time for calcul the mask position with numpy : 3.2901763916015625e-05 nb_pixel_total : 127 time to create 1 rle with old method : 0.00020742416381835938 length of segment : 15 time for calcul the mask position with numpy : 3.1948089599609375e-05 nb_pixel_total : 127 time to create 1 rle with old method : 0.0001971721649169922 length of segment : 28 time for calcul the mask position with numpy : 3.218650817871094e-05 nb_pixel_total : 271 time to create 1 rle with old method : 0.0003769397735595703 length of segment : 28 time for calcul the mask position with numpy : 7.677078247070312e-05 nb_pixel_total : 3318 time to create 1 rle with old method : 0.004138469696044922 length of segment : 89 time for calcul the mask position with numpy : 6.222724914550781e-05 nb_pixel_total : 359 time to create 1 rle with old method : 0.0006880760192871094 length of segment : 27 time for calcul the mask position with numpy : 9.34600830078125e-05 nb_pixel_total : 3433 time to create 1 rle with old method : 0.004424571990966797 length of segment : 91 Processing 1 images image shape: (280, 320, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 132.60000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 3 time for calcul the mask position with numpy : 3.933906555175781e-05 nb_pixel_total : 315 time to create 1 rle with old method : 0.00043773651123046875 length of segment : 17 time for calcul the mask position with numpy : 3.647804260253906e-05 nb_pixel_total : 379 time to create 1 rle with old method : 0.0005545616149902344 length of segment : 24 time for calcul the mask position with numpy : 4.696846008300781e-05 nb_pixel_total : 36 time to create 1 rle with old method : 8.487701416015625e-05 length of segment : 17 NEW PHOTO pour l'instant on ne peut pas sauvegarder la photo dans les tile Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -118.93047 max: 145.03359 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 7 time for calcul the mask position with numpy : 3.933906555175781e-05 nb_pixel_total : 31 time to create 1 rle with old method : 8.296966552734375e-05 length of segment : 11 time for calcul the mask position with numpy : 3.361701965332031e-05 nb_pixel_total : 218 time to create 1 rle with old method : 0.00030803680419921875 length of segment : 25 time for calcul the mask position with numpy : 4.00543212890625e-05 nb_pixel_total : 934 time to create 1 rle with old method : 0.0012857913970947266 length of segment : 49 length of segment : 0 time for calcul the mask position with numpy : 4.506111145019531e-05 nb_pixel_total : 1017 time to create 1 rle with old method : 0.0013206005096435547 length of segment : 42 time for calcul the mask position with numpy : 2.9802322387695312e-05 nb_pixel_total : 10 time to create 1 rle with old method : 7.963180541992188e-05 length of segment : 2 time for calcul the mask position with numpy : 5.1021575927734375e-05 nb_pixel_total : 1825 time to create 1 rle with old method : 0.0023474693298339844 length of segment : 43 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -117.43438 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 3 time for calcul the mask position with numpy : 6.437301635742188e-05 nb_pixel_total : 2283 time to create 1 rle with old method : 0.0028176307678222656 length of segment : 48 time for calcul the mask position with numpy : 0.00022864341735839844 nb_pixel_total : 1959 time to create 1 rle with old method : 0.0026171207427978516 length of segment : 159 time for calcul the mask position with numpy : 4.57763671875e-05 nb_pixel_total : 745 time to create 1 rle with old method : 0.0009350776672363281 length of segment : 35 Processing 1 images image shape: (400, 400, 3) min: 26.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -92.01250 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 5 time for calcul the mask position with numpy : 0.00011658668518066406 nb_pixel_total : 4206 time to create 1 rle with old method : 0.005251407623291016 length of segment : 81 time for calcul the mask position with numpy : 5.650520324707031e-05 nb_pixel_total : 723 time to create 1 rle with old method : 0.0010504722595214844 length of segment : 32 time for calcul the mask position with numpy : 0.0001633167266845703 nb_pixel_total : 6157 time to create 1 rle with old method : 0.0071527957916259766 length of segment : 115 time for calcul the mask position with numpy : 5.841255187988281e-05 nb_pixel_total : 292 time to create 1 rle with old method : 0.00044035911560058594 length of segment : 16 time for calcul the mask position with numpy : 0.0004036426544189453 nb_pixel_total : 1477 time to create 1 rle with old method : 0.002122163772583008 length of segment : 107 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -119.58672 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 3 time for calcul the mask position with numpy : 9.989738464355469e-05 nb_pixel_total : 3690 time to create 1 rle with old method : 0.004178047180175781 length of segment : 173 time for calcul the mask position with numpy : 3.790855407714844e-05 nb_pixel_total : 269 time to create 1 rle with old method : 0.0003750324249267578 length of segment : 23 time for calcul the mask position with numpy : 3.266334533691406e-05 nb_pixel_total : 393 time to create 1 rle with old method : 0.0005176067352294922 length of segment : 24 Processing 1 images image shape: (400, 320, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 133.76406 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 4 time for calcul the mask position with numpy : 4.601478576660156e-05 nb_pixel_total : 479 time to create 1 rle with old method : 0.0006725788116455078 length of segment : 18 time for calcul the mask position with numpy : 3.0279159545898438e-05 nb_pixel_total : 221 time to create 1 rle with old method : 0.0003228187561035156 length of segment : 24 time for calcul the mask position with numpy : 5.650520324707031e-05 nb_pixel_total : 1417 time to create 1 rle with old method : 0.0017452239990234375 length of segment : 45 time for calcul the mask position with numpy : 5.14984130859375e-05 nb_pixel_total : 1529 time to create 1 rle with old method : 0.0018961429595947266 length of segment : 38 Processing 1 images image shape: (400, 400, 3) min: 29.00000 max: 195.00000 molded_images shape: (1, 640, 640, 3) min: -89.67656 max: 73.88906 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 0 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -119.44609 max: 139.22891 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 14 time for calcul the mask position with numpy : 6.175041198730469e-05 nb_pixel_total : 320 time to create 1 rle with old method : 0.0004818439483642578 length of segment : 23 time for calcul the mask position with numpy : 3.719329833984375e-05 nb_pixel_total : 182 time to create 1 rle with old method : 0.00031113624572753906 length of segment : 23 time for calcul the mask position with numpy : 5.6743621826171875e-05 nb_pixel_total : 2190 time to create 1 rle with old method : 0.0025742053985595703 length of segment : 59 time for calcul the mask position with numpy : 0.00017118453979492188 nb_pixel_total : 8092 time to create 1 rle with old method : 0.008985519409179688 length of segment : 154 time for calcul the mask position with numpy : 4.410743713378906e-05 nb_pixel_total : 555 time to create 1 rle with old method : 0.0006794929504394531 length of segment : 34 time for calcul the mask position with numpy : 4.0531158447265625e-05 nb_pixel_total : 710 time to create 1 rle with old method : 0.0009031295776367188 length of segment : 25 time for calcul the mask position with numpy : 3.337860107421875e-05 nb_pixel_total : 216 time to create 1 rle with old method : 0.0003287792205810547 length of segment : 12 time for calcul the mask position with numpy : 3.4332275390625e-05 nb_pixel_total : 260 time to create 1 rle with old method : 0.00034689903259277344 length of segment : 36 time for calcul the mask position with numpy : 4.553794860839844e-05 nb_pixel_total : 1179 time to create 1 rle with old method : 0.0014774799346923828 length of segment : 33 time for calcul the mask position with numpy : 7.915496826171875e-05 nb_pixel_total : 2738 time to create 1 rle with old method : 0.003298521041870117 length of segment : 46 time for calcul the mask position with numpy : 2.8371810913085938e-05 nb_pixel_total : 106 time to create 1 rle with old method : 0.0001666545867919922 length of segment : 10 time for calcul the mask position with numpy : 3.170967102050781e-05 nb_pixel_total : 303 time to create 1 rle with old method : 0.0004360675811767578 length of segment : 13 time for calcul the mask position with numpy : 2.7418136596679688e-05 nb_pixel_total : 104 time to create 1 rle with old method : 0.0001842975616455078 length of segment : 7 time for calcul the mask position with numpy : 4.1484832763671875e-05 nb_pixel_total : 893 time to create 1 rle with old method : 0.0011129379272460938 length of segment : 22 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -117.60625 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 4 time for calcul the mask position with numpy : 6.651878356933594e-05 nb_pixel_total : 1597 time to create 1 rle with old method : 0.002079010009765625 length of segment : 51 time for calcul the mask position with numpy : 6.222724914550781e-05 nb_pixel_total : 2075 time to create 1 rle with old method : 0.0025641918182373047 length of segment : 36 time for calcul the mask position with numpy : 3.0040740966796875e-05 nb_pixel_total : 157 time to create 1 rle with old method : 0.0002493858337402344 length of segment : 11 time for calcul the mask position with numpy : 3.147125244140625e-05 nb_pixel_total : 224 time to create 1 rle with old method : 0.000339508056640625 length of segment : 16 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -115.93828 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 5 time for calcul the mask position with numpy : 4.863739013671875e-05 nb_pixel_total : 691 time to create 1 rle with old method : 0.0008697509765625 length of segment : 38 time for calcul the mask position with numpy : 2.6702880859375e-05 nb_pixel_total : 32 time to create 1 rle with old method : 6.413459777832031e-05 length of segment : 8 time for calcul the mask position with numpy : 7.462501525878906e-05 nb_pixel_total : 1656 time to create 1 rle with old method : 0.0019388198852539062 length of segment : 113 time for calcul the mask position with numpy : 6.222724914550781e-05 nb_pixel_total : 1224 time to create 1 rle with old method : 0.0014104843139648438 length of segment : 112 time for calcul the mask position with numpy : 3.886222839355469e-05 nb_pixel_total : 905 time to create 1 rle with old method : 0.001070261001586914 length of segment : 38 Processing 1 images image shape: (400, 320, 3) min: 0.00000 max: 241.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 104.41250 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 8 time for calcul the mask position with numpy : 0.0001354217529296875 nb_pixel_total : 3130 time to create 1 rle with old method : 0.0034575462341308594 length of segment : 177 time for calcul the mask position with numpy : 4.029273986816406e-05 nb_pixel_total : 614 time to create 1 rle with old method : 0.0007836818695068359 length of segment : 43 time for calcul the mask position with numpy : 6.031990051269531e-05 nb_pixel_total : 950 time to create 1 rle with old method : 0.001211404800415039 length of segment : 96 time for calcul the mask position with numpy : 4.172325134277344e-05 nb_pixel_total : 826 time to create 1 rle with old method : 0.001031637191772461 length of segment : 38 time for calcul the mask position with numpy : 2.6226043701171875e-05 nb_pixel_total : 70 time to create 1 rle with old method : 0.0001087188720703125 length of segment : 12 time for calcul the mask position with numpy : 3.1948089599609375e-05 nb_pixel_total : 449 time to create 1 rle with old method : 0.0005536079406738281 length of segment : 38 time for calcul the mask position with numpy : 5.7697296142578125e-05 nb_pixel_total : 1005 time to create 1 rle with old method : 0.0013043880462646484 length of segment : 97 time for calcul the mask position with numpy : 0.0001938343048095703 nb_pixel_total : 4589 time to create 1 rle with old method : 0.005106449127197266 length of segment : 236 Processing 1 images image shape: (280, 400, 3) min: 25.00000 max: 191.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 77.77578 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 1 time for calcul the mask position with numpy : 0.0009336471557617188 nb_pixel_total : 106746 time to create 1 rle with old method : 0.10861492156982422 length of segment : 278 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 146.13906 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 8 time for calcul the mask position with numpy : 3.910064697265625e-05 nb_pixel_total : 235 time to create 1 rle with old method : 0.0003497600555419922 length of segment : 14 time for calcul the mask position with numpy : 6.079673767089844e-05 nb_pixel_total : 2449 time to create 1 rle with old method : 0.002778768539428711 length of segment : 71 time for calcul the mask position with numpy : 2.8133392333984375e-05 nb_pixel_total : 153 time to create 1 rle with old method : 0.00022864341735839844 length of segment : 13 time for calcul the mask position with numpy : 4.863739013671875e-05 nb_pixel_total : 1852 time to create 1 rle with old method : 0.0022134780883789062 length of segment : 45 time for calcul the mask position with numpy : 3.504753112792969e-05 nb_pixel_total : 462 time to create 1 rle with old method : 0.00055694580078125 length of segment : 40 time for calcul the mask position with numpy : 5.340576171875e-05 nb_pixel_total : 1648 time to create 1 rle with old method : 0.0020482540130615234 length of segment : 60 time for calcul the mask position with numpy : 0.00010657310485839844 nb_pixel_total : 7733 time to create 1 rle with old method : 0.008543252944946289 length of segment : 79 time for calcul the mask position with numpy : 3.147125244140625e-05 nb_pixel_total : 369 time to create 1 rle with old method : 0.0004956722259521484 length of segment : 19 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 223.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 101.51406 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 5 time for calcul the mask position with numpy : 4.673004150390625e-05 nb_pixel_total : 571 time to create 1 rle with old method : 0.0008251667022705078 length of segment : 22 time for calcul the mask position with numpy : 3.170967102050781e-05 nb_pixel_total : 151 time to create 1 rle with old method : 0.0002307891845703125 length of segment : 21 time for calcul the mask position with numpy : 5.888938903808594e-05 nb_pixel_total : 1975 time to create 1 rle with old method : 0.0027129650115966797 length of segment : 54 time for calcul the mask position with numpy : 3.24249267578125e-05 nb_pixel_total : 138 time to create 1 rle with old method : 0.00020241737365722656 length of segment : 17 time for calcul the mask position with numpy : 3.2901763916015625e-05 nb_pixel_total : 280 time to create 1 rle with old method : 0.0004162788391113281 length of segment : 20 Processing 1 images image shape: (280, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 150.12344 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 10 time for calcul the mask position with numpy : 5.2928924560546875e-05 nb_pixel_total : 560 time to create 1 rle with old method : 0.0007669925689697266 length of segment : 29 time for calcul the mask position with numpy : 4.9114227294921875e-05 nb_pixel_total : 461 time to create 1 rle with old method : 0.0006420612335205078 length of segment : 71 time for calcul the mask position with numpy : 2.8848648071289062e-05 nb_pixel_total : 129 time to create 1 rle with old method : 0.00017213821411132812 length of segment : 27 time for calcul the mask position with numpy : 6.175041198730469e-05 nb_pixel_total : 2792 time to create 1 rle with old method : 0.003312349319458008 length of segment : 80 time for calcul the mask position with numpy : 2.9802322387695312e-05 nb_pixel_total : 253 time to create 1 rle with old method : 0.0003533363342285156 length of segment : 20 time for calcul the mask position with numpy : 2.7894973754882812e-05 nb_pixel_total : 175 time to create 1 rle with old method : 0.000240325927734375 length of segment : 25 time for calcul the mask position with numpy : 2.7179718017578125e-05 nb_pixel_total : 143 time to create 1 rle with old method : 0.00019693374633789062 length of segment : 16 time for calcul the mask position with numpy : 4.8160552978515625e-05 nb_pixel_total : 693 time to create 1 rle with old method : 0.0009112358093261719 length of segment : 58 time for calcul the mask position with numpy : 6.079673767089844e-05 nb_pixel_total : 2962 time to create 1 rle with old method : 0.0031502246856689453 length of segment : 88 time for calcul the mask position with numpy : 4.172325134277344e-05 nb_pixel_total : 70 time to create 1 rle with old method : 0.00018739700317382812 length of segment : 19 Processing 1 images image shape: (280, 320, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 133.82500 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 2 time for calcul the mask position with numpy : 3.838539123535156e-05 nb_pixel_total : 304 time to create 1 rle with old method : 0.00041556358337402344 length of segment : 17 time for calcul the mask position with numpy : 3.5762786865234375e-05 nb_pixel_total : 411 time to create 1 rle with old method : 0.0005631446838378906 length of segment : 26 Detection mask done ! Trying to reset tf kernel 2473696 begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 5706 tf kernel not reseted sub process len(results) : 1680 len(list_Values) 1680 None max_time_sub_proc : 3600 parent process len(results) : 0 len(list_Values) 1680 process is alive finish correctly or not : True after detect begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 10998 Inside saveOutput : final : False verbose : 0 eke 12-6-18 : saveMask need to be cleaned for new output ! Catched exception ! Connect or reconnect ! Number saved : None batch 1 Loaded 1816 chid ids of type : 4228 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 91753 save missing photos in datou_result : time spend for datou_step_exec : 73.79338955879211 time spend to save output : 19.590962648391724 total time spend for step 1 : 93.38435220718384 step2:brightness Wed Feb 12 08:49:21 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 VR 22-3-18 : For now we do not clean correctly the datou structure inside step calcul brightness treat image : temp/1739346464_2473413_1332404633_38a2bb0a7fe4e90e18bb82f54e343ff9.jpg treat image : temp/1739346464_2473413_1332404630_60cc21c8c3993ab29d9900a81893aafc.jpg treat image : temp/1739346464_2473413_1332404627_bfc458f6e20f6bf48c1d80688b8e14a4.jpg treat image : temp/1739346464_2473413_1332404610_f7b528ea130502475878e8aed497ed88.jpg treat image : temp/1739346464_2473413_1332404608_a4e91d3076bd154d8c3a6cba4c243648.jpg treat image : temp/1739346464_2473413_1332404605_1ce8177d952785cb72560b3d9ea8a1ae.jpg treat image : temp/1739346464_2473413_1332404602_9997e0ee4449950f179ac6e0b8e2db84.jpg treat image : temp/1739346464_2473413_1332404599_b525c1dcd208cd5f8f55b5f26fafb799.jpg treat image : temp/1739346464_2473413_1332404596_a930e080a92cd2469c0cb4cf8b26f080.jpg treat image : temp/1739346464_2473413_1332404585_50169419049934aa0a8194372035c5f3.jpg treat image : temp/1739346464_2473413_1332404583_cf044b807d9bde85b5e3944aa1a1d100.jpg treat image : temp/1739346464_2473413_1332404581_e839e62fc7a3e2837649f4becd9789da.jpg treat image : temp/1739346464_2473413_1332404578_94771e6330bfa7c22cfe9d0079aca712.jpg treat image : temp/1739346464_2473413_1332404575_e68bee22c9be22a860d7ca2eecd92502.jpg treat image : temp/1739346464_2473413_1332404571_fc6ffc76009a99b859cd2fbf82d2d136.jpg treat image : temp/1739346464_2473413_1332404558_e606bd56802e908ffde2620e3a84df3f.jpg treat image : temp/1739346464_2473413_1332404555_17454f6310de98023aca87540d6dade5.jpg treat image : temp/1739346464_2473413_1332404550_a32c7b48411f0dfc9cf29cc5e5328cf2.jpg treat image : temp/1739346464_2473413_1332404545_e9b7af0eeae2798da235d4419176fb1b.jpg treat image : temp/1739346464_2473413_1332404540_70864e1989eef7514dfffe30f6eaf8c1.jpg treat image : temp/1739346464_2473413_1332404535_75e9f74cd25d787fcfc09e885091fa05.jpg Inside saveOutput : final : False verbose : 0 begin to insert list_values into class_photo_scores : length of list_valuse in save_photo_hashtag_id_thcl_score : 21 time used for this insertion : 0.012781858444213867 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 21 time used for this insertion : 0.021924495697021484 save missing photos in datou_result : time spend for datou_step_exec : 4.869779825210571 time spend to save output : 0.039780616760253906 total time spend for step 2 : 4.909560441970825 step3:blur_detection Wed Feb 12 08:49:26 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 VR 22-3-18 : For now we do not clean correctly the datou structure inside step blur_detection methode: ratio et variance treat image : temp/1739346464_2473413_1332404633_38a2bb0a7fe4e90e18bb82f54e343ff9.jpg resize: (1080, 1920) 1332404633 -6.897064333781125 treat image : temp/1739346464_2473413_1332404630_60cc21c8c3993ab29d9900a81893aafc.jpg resize: (1080, 1920) 1332404630 -6.885617531871497 treat image : temp/1739346464_2473413_1332404627_bfc458f6e20f6bf48c1d80688b8e14a4.jpg resize: (1080, 1920) 1332404627 -6.901302299485353 treat image : temp/1739346464_2473413_1332404610_f7b528ea130502475878e8aed497ed88.jpg resize: (1080, 1920) 1332404610 -6.8914866282913705 treat image : temp/1739346464_2473413_1332404608_a4e91d3076bd154d8c3a6cba4c243648.jpg resize: (1080, 1920) 1332404608 -6.90501317202887 treat image : temp/1739346464_2473413_1332404605_1ce8177d952785cb72560b3d9ea8a1ae.jpg resize: (1080, 1920) 1332404605 -6.907404045974517 treat image : temp/1739346464_2473413_1332404602_9997e0ee4449950f179ac6e0b8e2db84.jpg resize: (1080, 1920) 1332404602 -6.908753310459022 treat image : temp/1739346464_2473413_1332404599_b525c1dcd208cd5f8f55b5f26fafb799.jpg resize: (1080, 1920) 1332404599 -6.906811749293834 treat image : temp/1739346464_2473413_1332404596_a930e080a92cd2469c0cb4cf8b26f080.jpg resize: (1080, 1920) 1332404596 -6.895344367047699 treat image : temp/1739346464_2473413_1332404585_50169419049934aa0a8194372035c5f3.jpg resize: (1080, 1920) 1332404585 -6.8839312798471175 treat image : temp/1739346464_2473413_1332404583_cf044b807d9bde85b5e3944aa1a1d100.jpg resize: (1080, 1920) 1332404583 -6.879402909437718 treat image : temp/1739346464_2473413_1332404581_e839e62fc7a3e2837649f4becd9789da.jpg resize: (1080, 1920) 1332404581 -6.878464210763026 treat image : temp/1739346464_2473413_1332404578_94771e6330bfa7c22cfe9d0079aca712.jpg resize: (1080, 1920) 1332404578 -6.86996101979846 treat image : temp/1739346464_2473413_1332404575_e68bee22c9be22a860d7ca2eecd92502.jpg resize: (1080, 1920) 1332404575 -6.881758720590853 treat image : temp/1739346464_2473413_1332404571_fc6ffc76009a99b859cd2fbf82d2d136.jpg resize: (1080, 1920) 1332404571 -6.88349410785495 treat image : temp/1739346464_2473413_1332404558_e606bd56802e908ffde2620e3a84df3f.jpg resize: (1080, 1920) 1332404558 -6.853935340356413 treat image : temp/1739346464_2473413_1332404555_17454f6310de98023aca87540d6dade5.jpg resize: (1080, 1920) 1332404555 -6.892483721105581 treat image : temp/1739346464_2473413_1332404550_a32c7b48411f0dfc9cf29cc5e5328cf2.jpg resize: (1080, 1920) 1332404550 -6.830097098899389 treat image : temp/1739346464_2473413_1332404545_e9b7af0eeae2798da235d4419176fb1b.jpg resize: (1080, 1920) 1332404545 -6.885675706962043 treat image : temp/1739346464_2473413_1332404540_70864e1989eef7514dfffe30f6eaf8c1.jpg resize: (1080, 1920) 1332404540 -6.855293276036565 treat image : temp/1739346464_2473413_1332404535_75e9f74cd25d787fcfc09e885091fa05.jpg resize: (1080, 1920) 1332404535 -6.95432985415064 Inside saveOutput : final : False verbose : 0 begin to insert list_values into class_photo_scores : length of list_valuse in save_photo_hashtag_id_thcl_score : 21 time used for this insertion : 0.013373374938964844 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 21 time used for this insertion : 0.7948601245880127 save missing photos in datou_result : time spend for datou_step_exec : 16.45536732673645 time spend to save output : 0.8137085437774658 total time spend for step 3 : 17.269075870513916 step4:rle_unique_nms_with_priority Wed Feb 12 08:49:44 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 VR 22-3-18 : For now we do not clean correctly the datou structure Begin step rle-unique-nms batch 1 Loaded 1816 chid ids of type : 4228 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++nb_obj : 83 nb_hashtags : 8 time to prepare the origin masks : 1.1146461963653564 time for calcul the mask position with numpy : 0.041136980056762695 nb_pixel_total : 1675326 time to create 1 rle with new method : 0.3165404796600342 time for calcul the mask position with numpy : 0.008135318756103516 nb_pixel_total : 243 time to create 1 rle with old method : 0.000274658203125 time for calcul the mask position with numpy : 0.008065938949584961 nb_pixel_total : 1488 time to create 1 rle with old method : 0.0015976428985595703 time for calcul the mask position with numpy : 0.007983922958374023 nb_pixel_total : 17 time to create 1 rle with old method : 2.8371810913085938e-05 time for calcul the mask position with numpy : 0.008104801177978516 nb_pixel_total : 317 time to create 1 rle with old method : 0.00037169456481933594 time for calcul the mask position with numpy : 0.008240222930908203 nb_pixel_total : 1042 time to create 1 rle with old method : 0.0011916160583496094 time for calcul the mask position with numpy : 0.008298397064208984 nb_pixel_total : 48 time to create 1 rle with old method : 8.487701416015625e-05 time for calcul the mask position with numpy : 0.008199691772460938 nb_pixel_total : 647 time to create 1 rle with old method : 0.0007340908050537109 time for calcul the mask position with numpy : 0.00822305679321289 nb_pixel_total : 79 time to create 1 rle with old method : 0.00012731552124023438 time for calcul the mask position with numpy : 0.008289813995361328 nb_pixel_total : 11084 time to create 1 rle with old method : 0.01520848274230957 time for calcul the mask position with numpy : 0.010440826416015625 nb_pixel_total : 41059 time to create 1 rle with old method : 0.04885458946228027 time for calcul the mask position with numpy : 0.008710622787475586 nb_pixel_total : 231 time to create 1 rle with old method : 0.00028133392333984375 time for calcul the mask position with numpy : 0.008407115936279297 nb_pixel_total : 523 time to create 1 rle with old method : 0.0006220340728759766 time for calcul the mask position with numpy : 0.008345365524291992 nb_pixel_total : 975 time to create 1 rle with old method : 0.0011453628540039062 time for calcul the mask position with numpy : 0.00832223892211914 nb_pixel_total : 4328 time to create 1 rle with old method : 0.005272388458251953 time for calcul the mask position with numpy : 0.008218050003051758 nb_pixel_total : 6245 time to create 1 rle with old method : 0.008197784423828125 time for calcul the mask position with numpy : 0.010471343994140625 nb_pixel_total : 6366 time to create 1 rle with old method : 0.009186267852783203 time for calcul the mask position with numpy : 0.008426904678344727 nb_pixel_total : 374 time to create 1 rle with old method : 0.00043964385986328125 time for calcul the mask position with numpy : 0.008359670639038086 nb_pixel_total : 246 time to create 1 rle with old method : 0.00029468536376953125 time for calcul the mask position with numpy : 0.008356332778930664 nb_pixel_total : 532 time to create 1 rle with old method : 0.0006361007690429688 time for calcul the mask position with numpy : 0.008427143096923828 nb_pixel_total : 114 time to create 1 rle with old method : 0.0001480579376220703 time for calcul the mask position with numpy : 0.00898599624633789 nb_pixel_total : 148847 time to create 1 rle with old method : 0.18464159965515137 time for calcul the mask position with numpy : 0.010754585266113281 nb_pixel_total : 1984 time to create 1 rle with old method : 0.0031266212463378906 time for calcul the mask position with numpy : 0.009054899215698242 nb_pixel_total : 101 time to create 1 rle with old method : 0.0001552104949951172 time for calcul the mask position with numpy : 0.008537769317626953 nb_pixel_total : 17 time to create 1 rle with old method : 6.246566772460938e-05 time for calcul the mask position with numpy : 0.008653640747070312 nb_pixel_total : 821 time to create 1 rle with old method : 0.0011281967163085938 time for calcul the mask position with numpy : 0.009352445602416992 nb_pixel_total : 24 time to create 1 rle with old method : 0.00010514259338378906 time for calcul the mask position with numpy : 0.009018898010253906 nb_pixel_total : 1914 time to create 1 rle with old method : 0.002702951431274414 time for calcul the mask position with numpy : 0.009248733520507812 nb_pixel_total : 1369 time to create 1 rle with old method : 0.0019299983978271484 time for calcul the mask position with numpy : 0.009325265884399414 nb_pixel_total : 205 time to create 1 rle with old method : 0.0003254413604736328 time for calcul the mask position with numpy : 0.009302377700805664 nb_pixel_total : 2850 time to create 1 rle with old method : 0.003686666488647461 time for calcul the mask position with numpy : 0.009104251861572266 nb_pixel_total : 971 time to create 1 rle with old method : 0.001241445541381836 time for calcul the mask position with numpy : 0.009182214736938477 nb_pixel_total : 261 time to create 1 rle with old method : 0.0003483295440673828 time for calcul the mask position with numpy : 0.009074211120605469 nb_pixel_total : 260 time to create 1 rle with old method : 0.0003592967987060547 time for calcul the mask position with numpy : 0.008654356002807617 nb_pixel_total : 180 time to create 1 rle with old method : 0.00024175643920898438 time for calcul the mask position with numpy : 0.008962631225585938 nb_pixel_total : 13617 time to create 1 rle with old method : 0.01752161979675293 time for calcul the mask position with numpy : 0.008840799331665039 nb_pixel_total : 1394 time to create 1 rle with old method : 0.0018062591552734375 time for calcul the mask position with numpy : 0.008687257766723633 nb_pixel_total : 747 time to create 1 rle with old method : 0.0009753704071044922 time for calcul the mask position with numpy : 0.00864553451538086 nb_pixel_total : 726 time to create 1 rle with old method : 0.0009448528289794922 time for calcul the mask position with numpy : 0.009212017059326172 nb_pixel_total : 714 time to create 1 rle with old method : 0.0012288093566894531 time for calcul the mask position with numpy : 0.009879112243652344 nb_pixel_total : 3256 time to create 1 rle with old method : 0.005416154861450195 time for calcul the mask position with numpy : 0.009811878204345703 nb_pixel_total : 3203 time to create 1 rle with old method : 0.005417823791503906 time for calcul the mask position with numpy : 0.009978532791137695 nb_pixel_total : 26 time to create 1 rle with old method : 8.177757263183594e-05 time for calcul the mask position with numpy : 0.009958505630493164 nb_pixel_total : 132 time to create 1 rle with old method : 0.0002532005310058594 time for calcul the mask position with numpy : 0.009874343872070312 nb_pixel_total : 59 time to create 1 rle with old method : 0.00019049644470214844 time for calcul the mask position with numpy : 0.009845972061157227 nb_pixel_total : 1412 time to create 1 rle with old method : 0.002401113510131836 time for calcul the mask position with numpy : 0.009396791458129883 nb_pixel_total : 413 time to create 1 rle with old method : 0.0005092620849609375 time for calcul the mask position with numpy : 0.008457422256469727 nb_pixel_total : 166 time to create 1 rle with old method : 0.0002498626708984375 time for calcul the mask position with numpy : 0.008208990097045898 nb_pixel_total : 196 time to create 1 rle with old method : 0.00021529197692871094 time for calcul the mask position with numpy : 0.008288145065307617 nb_pixel_total : 275 time to create 1 rle with old method : 0.0003414154052734375 time for calcul the mask position with numpy : 0.008311748504638672 nb_pixel_total : 526 time to create 1 rle with old method : 0.0006017684936523438 time for calcul the mask position with numpy : 0.007929325103759766 nb_pixel_total : 31 time to create 1 rle with old method : 4.220008850097656e-05 time for calcul the mask position with numpy : 0.008060216903686523 nb_pixel_total : 2156 time to create 1 rle with old method : 0.0023527145385742188 time for calcul the mask position with numpy : 0.008125066757202148 nb_pixel_total : 1287 time to create 1 rle with old method : 0.0015268325805664062 time for calcul the mask position with numpy : 0.008213281631469727 nb_pixel_total : 273 time to create 1 rle with old method : 0.0003268718719482422 time for calcul the mask position with numpy : 0.008105993270874023 nb_pixel_total : 390 time to create 1 rle with old method : 0.0004754066467285156 time for calcul the mask position with numpy : 0.008087635040283203 nb_pixel_total : 82 time to create 1 rle with old method : 0.00010013580322265625 time for calcul the mask position with numpy : 0.00812983512878418 nb_pixel_total : 144 time to create 1 rle with old method : 0.00017261505126953125 time for calcul the mask position with numpy : 0.00808262825012207 nb_pixel_total : 204 time to create 1 rle with old method : 0.00024056434631347656 time for calcul the mask position with numpy : 0.008127450942993164 nb_pixel_total : 252 time to create 1 rle with old method : 0.0003025531768798828 time for calcul the mask position with numpy : 0.008512258529663086 nb_pixel_total : 105596 time to create 1 rle with old method : 0.11417102813720703 time for calcul the mask position with numpy : 0.008382797241210938 nb_pixel_total : 315 time to create 1 rle with old method : 0.00040221214294433594 time for calcul the mask position with numpy : 0.008356571197509766 nb_pixel_total : 3208 time to create 1 rle with old method : 0.003469705581665039 time for calcul the mask position with numpy : 0.008391380310058594 nb_pixel_total : 302 time to create 1 rle with old method : 0.00036907196044921875 time for calcul the mask position with numpy : 0.00847005844116211 nb_pixel_total : 174 time to create 1 rle with old method : 0.00021266937255859375 time for calcul the mask position with numpy : 0.008378028869628906 nb_pixel_total : 264 time to create 1 rle with old method : 0.00031566619873046875 time for calcul the mask position with numpy : 0.008223772048950195 nb_pixel_total : 1632 time to create 1 rle with old method : 0.0018334388732910156 time for calcul the mask position with numpy : 0.008401632308959961 nb_pixel_total : 123 time to create 1 rle with old method : 0.00015163421630859375 time for calcul the mask position with numpy : 0.008224964141845703 nb_pixel_total : 433 time to create 1 rle with old method : 0.0005035400390625 time for calcul the mask position with numpy : 0.008084774017333984 nb_pixel_total : 388 time to create 1 rle with old method : 0.0004544258117675781 time for calcul the mask position with numpy : 0.008260726928710938 nb_pixel_total : 130 time to create 1 rle with old method : 0.00015091896057128906 time for calcul the mask position with numpy : 0.008339166641235352 nb_pixel_total : 467 time to create 1 rle with old method : 0.0005230903625488281 time for calcul the mask position with numpy : 0.008060455322265625 nb_pixel_total : 1548 time to create 1 rle with old method : 0.0017516613006591797 time for calcul the mask position with numpy : 0.008095502853393555 nb_pixel_total : 2593 time to create 1 rle with old method : 0.002969980239868164 time for calcul the mask position with numpy : 0.008160829544067383 nb_pixel_total : 176 time to create 1 rle with old method : 0.0002186298370361328 time for calcul the mask position with numpy : 0.008120298385620117 nb_pixel_total : 2871 time to create 1 rle with old method : 0.0031194686889648438 time for calcul the mask position with numpy : 0.008280515670776367 nb_pixel_total : 107 time to create 1 rle with old method : 0.00012755393981933594 time for calcul the mask position with numpy : 0.007932424545288086 nb_pixel_total : 169 time to create 1 rle with old method : 0.0001938343048095703 time for calcul the mask position with numpy : 0.00827479362487793 nb_pixel_total : 747 time to create 1 rle with old method : 0.0008795261383056641 time for calcul the mask position with numpy : 0.008371114730834961 nb_pixel_total : 7754 time to create 1 rle with old method : 0.008642911911010742 time for calcul the mask position with numpy : 0.008145809173583984 nb_pixel_total : 854 time to create 1 rle with old method : 0.0009829998016357422 time for calcul the mask position with numpy : 0.008341073989868164 nb_pixel_total : 377 time to create 1 rle with old method : 0.00044536590576171875 time for calcul the mask position with numpy : 0.008026123046875 nb_pixel_total : 271 time to create 1 rle with old method : 0.00031495094299316406 time for calcul the mask position with numpy : 0.008105754852294922 nb_pixel_total : 332 time to create 1 rle with old method : 0.00038242340087890625 create new chi : 1.565317153930664 after preparing all the mask , begin to delete the rle from the crop_hashtag_id => VR 28-11-20 : il faut déplacer cela apres le save_crop_hashtag_ids_obj de la ligne 9514 ! we have 0 chi objets contains the rles time to delete rle : 0.005286455154418945 batch 1 Loaded 84 chid ids of type : 4230 Number RLEs to save : 10103 TO DO : save crop sub photo not yet done ! save time : 0.6534552574157715 nb_obj : 77 nb_hashtags : 7 time to prepare the origin masks : 1.8381776809692383 time for calcul the mask position with numpy : 0.031009435653686523 nb_pixel_total : 1734546 time to create 1 rle with new method : 0.05660820007324219 time for calcul the mask position with numpy : 0.005935192108154297 nb_pixel_total : 222 time to create 1 rle with old method : 0.00027060508728027344 time for calcul the mask position with numpy : 0.005584239959716797 nb_pixel_total : 337 time to create 1 rle with old method : 0.0003669261932373047 time for calcul the mask position with numpy : 0.005674123764038086 nb_pixel_total : 53 time to create 1 rle with old method : 7.843971252441406e-05 time for calcul the mask position with numpy : 0.005554676055908203 nb_pixel_total : 1010 time to create 1 rle with old method : 0.0011286735534667969 time for calcul the mask position with numpy : 0.005808115005493164 nb_pixel_total : 1709 time to create 1 rle with old method : 0.0018792152404785156 time for calcul the mask position with numpy : 0.005617380142211914 nb_pixel_total : 13 time to create 1 rle with old method : 3.6716461181640625e-05 time for calcul the mask position with numpy : 0.0058176517486572266 nb_pixel_total : 64 time to create 1 rle with old method : 0.00012826919555664062 time for calcul the mask position with numpy : 0.0059130191802978516 nb_pixel_total : 10 time to create 1 rle with old method : 4.458427429199219e-05 time for calcul the mask position with numpy : 0.005715608596801758 nb_pixel_total : 10 time to create 1 rle with old method : 3.600120544433594e-05 time for calcul the mask position with numpy : 0.0057866573333740234 nb_pixel_total : 146 time to create 1 rle with old method : 0.000202178955078125 time for calcul the mask position with numpy : 0.005718231201171875 nb_pixel_total : 571 time to create 1 rle with old method : 0.0006487369537353516 time for calcul the mask position with numpy : 0.006029605865478516 nb_pixel_total : 2195 time to create 1 rle with old method : 0.0024302005767822266 time for calcul the mask position with numpy : 0.005862712860107422 nb_pixel_total : 278 time to create 1 rle with old method : 0.0003185272216796875 time for calcul the mask position with numpy : 0.0058438777923583984 nb_pixel_total : 938 time to create 1 rle with old method : 0.0011701583862304688 time for calcul the mask position with numpy : 0.005749940872192383 nb_pixel_total : 263 time to create 1 rle with old method : 0.00036597251892089844 time for calcul the mask position with numpy : 0.005723714828491211 nb_pixel_total : 90 time to create 1 rle with old method : 0.00012564659118652344 time for calcul the mask position with numpy : 0.005825996398925781 nb_pixel_total : 868 time to create 1 rle with old method : 0.00106048583984375 time for calcul the mask position with numpy : 0.005815029144287109 nb_pixel_total : 3718 time to create 1 rle with old method : 0.004266977310180664 time for calcul the mask position with numpy : 0.005892276763916016 nb_pixel_total : 422 time to create 1 rle with old method : 0.0005447864532470703 time for calcul the mask position with numpy : 0.0058329105377197266 nb_pixel_total : 7652 time to create 1 rle with old method : 0.008806467056274414 time for calcul the mask position with numpy : 0.005802631378173828 nb_pixel_total : 524 time to create 1 rle with old method : 0.0005908012390136719 time for calcul the mask position with numpy : 0.005795001983642578 nb_pixel_total : 99 time to create 1 rle with old method : 0.00013589859008789062 time for calcul the mask position with numpy : 0.0072481632232666016 nb_pixel_total : 150031 time to create 1 rle with new method : 0.02685403823852539 time for calcul the mask position with numpy : 0.0059888362884521484 nb_pixel_total : 26 time to create 1 rle with old method : 6.413459777832031e-05 time for calcul the mask position with numpy : 0.0059642791748046875 nb_pixel_total : 799 time to create 1 rle with old method : 0.0008742809295654297 time for calcul the mask position with numpy : 0.005854368209838867 nb_pixel_total : 1207 time to create 1 rle with old method : 0.0013856887817382812 time for calcul the mask position with numpy : 0.00584721565246582 nb_pixel_total : 1809 time to create 1 rle with old method : 0.0020151138305664062 time for calcul the mask position with numpy : 0.005766153335571289 nb_pixel_total : 53 time to create 1 rle with old method : 0.00011229515075683594 time for calcul the mask position with numpy : 0.005735874176025391 nb_pixel_total : 215 time to create 1 rle with old method : 0.00023508071899414062 time for calcul the mask position with numpy : 0.0056993961334228516 nb_pixel_total : 346 time to create 1 rle with old method : 0.0004487037658691406 time for calcul the mask position with numpy : 0.006045341491699219 nb_pixel_total : 12074 time to create 1 rle with old method : 0.013892412185668945 time for calcul the mask position with numpy : 0.0061664581298828125 nb_pixel_total : 180 time to create 1 rle with old method : 0.00024509429931640625 time for calcul the mask position with numpy : 0.0063626766204833984 nb_pixel_total : 1337 time to create 1 rle with old method : 0.001653909683227539 time for calcul the mask position with numpy : 0.00637507438659668 nb_pixel_total : 738 time to create 1 rle with old method : 0.0009274482727050781 time for calcul the mask position with numpy : 0.006384134292602539 nb_pixel_total : 774 time to create 1 rle with old method : 0.0009849071502685547 time for calcul the mask position with numpy : 0.006413698196411133 nb_pixel_total : 107 time to create 1 rle with old method : 0.00020170211791992188 time for calcul the mask position with numpy : 0.006319522857666016 nb_pixel_total : 1013 time to create 1 rle with old method : 0.001203775405883789 time for calcul the mask position with numpy : 0.006386518478393555 nb_pixel_total : 3142 time to create 1 rle with old method : 0.00366973876953125 time for calcul the mask position with numpy : 0.00692296028137207 nb_pixel_total : 5951 time to create 1 rle with old method : 0.010066986083984375 time for calcul the mask position with numpy : 0.007267951965332031 nb_pixel_total : 116 time to create 1 rle with old method : 0.00017070770263671875 time for calcul the mask position with numpy : 0.006446361541748047 nb_pixel_total : 1723 time to create 1 rle with old method : 0.002080202102661133 time for calcul the mask position with numpy : 0.006671428680419922 nb_pixel_total : 101 time to create 1 rle with old method : 0.0002472400665283203 time for calcul the mask position with numpy : 0.006751537322998047 nb_pixel_total : 1550 time to create 1 rle with old method : 0.0021877288818359375 time for calcul the mask position with numpy : 0.0066547393798828125 nb_pixel_total : 178 time to create 1 rle with old method : 0.0002377033233642578 time for calcul the mask position with numpy : 0.006451845169067383 nb_pixel_total : 550 time to create 1 rle with old method : 0.0006701946258544922 time for calcul the mask position with numpy : 0.00640869140625 nb_pixel_total : 522 time to create 1 rle with old method : 0.0006351470947265625 time for calcul the mask position with numpy : 0.006342649459838867 nb_pixel_total : 635 time to create 1 rle with old method : 0.0008897781372070312 time for calcul the mask position with numpy : 0.006102561950683594 nb_pixel_total : 35 time to create 1 rle with old method : 5.936622619628906e-05 time for calcul the mask position with numpy : 0.005887031555175781 nb_pixel_total : 95 time to create 1 rle with old method : 0.00012254714965820312 time for calcul the mask position with numpy : 0.005975246429443359 nb_pixel_total : 1165 time to create 1 rle with old method : 0.0014748573303222656 time for calcul the mask position with numpy : 0.005891323089599609 nb_pixel_total : 366 time to create 1 rle with old method : 0.0004668235778808594 time for calcul the mask position with numpy : 0.006128549575805664 nb_pixel_total : 75 time to create 1 rle with old method : 0.000133514404296875 time for calcul the mask position with numpy : 0.0059773921966552734 nb_pixel_total : 154 time to create 1 rle with old method : 0.00019812583923339844 time for calcul the mask position with numpy : 0.0060918331146240234 nb_pixel_total : 150 time to create 1 rle with old method : 0.00019288063049316406 time for calcul the mask position with numpy : 0.006348609924316406 nb_pixel_total : 243 time to create 1 rle with old method : 0.0002982616424560547 time for calcul the mask position with numpy : 0.006643533706665039 nb_pixel_total : 106311 time to create 1 rle with old method : 0.11443161964416504 time for calcul the mask position with numpy : 0.006298065185546875 nb_pixel_total : 590 time to create 1 rle with old method : 0.0007271766662597656 time for calcul the mask position with numpy : 0.005919933319091797 nb_pixel_total : 286 time to create 1 rle with old method : 0.00036215782165527344 time for calcul the mask position with numpy : 0.006385326385498047 nb_pixel_total : 350 time to create 1 rle with old method : 0.0004372596740722656 time for calcul the mask position with numpy : 0.005875349044799805 nb_pixel_total : 2361 time to create 1 rle with old method : 0.0028810501098632812 time for calcul the mask position with numpy : 0.006101369857788086 nb_pixel_total : 165 time to create 1 rle with old method : 0.00022554397583007812 time for calcul the mask position with numpy : 0.006090402603149414 nb_pixel_total : 128 time to create 1 rle with old method : 0.0001621246337890625 time for calcul the mask position with numpy : 0.0059413909912109375 nb_pixel_total : 456 time to create 1 rle with old method : 0.0005629062652587891 time for calcul the mask position with numpy : 0.006213188171386719 nb_pixel_total : 393 time to create 1 rle with old method : 0.0005307197570800781 time for calcul the mask position with numpy : 0.00596928596496582 nb_pixel_total : 348 time to create 1 rle with old method : 0.0004296302795410156 time for calcul the mask position with numpy : 0.005964517593383789 nb_pixel_total : 1666 time to create 1 rle with old method : 0.0018944740295410156 time for calcul the mask position with numpy : 0.0058863162994384766 nb_pixel_total : 6802 time to create 1 rle with old method : 0.0077397823333740234 time for calcul the mask position with numpy : 0.00627589225769043 nb_pixel_total : 413 time to create 1 rle with old method : 0.0005295276641845703 time for calcul the mask position with numpy : 0.006234169006347656 nb_pixel_total : 181 time to create 1 rle with old method : 0.0003669261932373047 time for calcul the mask position with numpy : 0.006133317947387695 nb_pixel_total : 125 time to create 1 rle with old method : 0.00016880035400390625 time for calcul the mask position with numpy : 0.005929231643676758 nb_pixel_total : 197 time to create 1 rle with old method : 0.00022459030151367188 time for calcul the mask position with numpy : 0.006056308746337891 nb_pixel_total : 7414 time to create 1 rle with old method : 0.008489131927490234 time for calcul the mask position with numpy : 0.006192445755004883 nb_pixel_total : 238 time to create 1 rle with old method : 0.0004706382751464844 time for calcul the mask position with numpy : 0.006026506423950195 nb_pixel_total : 999 time to create 1 rle with old method : 0.0011894702911376953 time for calcul the mask position with numpy : 0.0057294368743896484 nb_pixel_total : 358 time to create 1 rle with old method : 0.0004363059997558594 time for calcul the mask position with numpy : 0.005998373031616211 nb_pixel_total : 326 time to create 1 rle with old method : 0.00040268898010253906 time for calcul the mask position with numpy : 0.0061185359954833984 nb_pixel_total : 295 time to create 1 rle with old method : 0.0003628730773925781 create new chi : 0.801159143447876 after preparing all the mask , begin to delete the rle from the crop_hashtag_id => VR 28-11-20 : il faut déplacer cela apres le save_crop_hashtag_ids_obj de la ligne 9514 ! we have 0 chi objets contains the rles time to delete rle : 0.001264810562133789 batch 1 Loaded 78 chid ids of type : 4230 Number RLEs to save : 8293 TO DO : save crop sub photo not yet done ! save time : 0.4712209701538086 nb_obj : 74 nb_hashtags : 7 time to prepare the origin masks : 1.1184885501861572 time for calcul the mask position with numpy : 0.01830887794494629 nb_pixel_total : 1884841 time to create 1 rle with new method : 0.06594133377075195 time for calcul the mask position with numpy : 0.006049394607543945 nb_pixel_total : 550 time to create 1 rle with old method : 0.0006127357482910156 time for calcul the mask position with numpy : 0.0056819915771484375 nb_pixel_total : 27 time to create 1 rle with old method : 4.9591064453125e-05 time for calcul the mask position with numpy : 0.00583648681640625 nb_pixel_total : 115 time to create 1 rle with old method : 0.00018405914306640625 time for calcul the mask position with numpy : 0.005692481994628906 nb_pixel_total : 924 time to create 1 rle with old method : 0.0011553764343261719 time for calcul the mask position with numpy : 0.005868673324584961 nb_pixel_total : 305 time to create 1 rle with old method : 0.000347137451171875 time for calcul the mask position with numpy : 0.005961418151855469 nb_pixel_total : 773 time to create 1 rle with old method : 0.0009286403656005859 time for calcul the mask position with numpy : 0.005988359451293945 nb_pixel_total : 29 time to create 1 rle with old method : 5.555152893066406e-05 time for calcul the mask position with numpy : 0.005599021911621094 nb_pixel_total : 1487 time to create 1 rle with old method : 0.0016243457794189453 time for calcul the mask position with numpy : 0.006049394607543945 nb_pixel_total : 123 time to create 1 rle with old method : 0.00017142295837402344 time for calcul the mask position with numpy : 0.006042957305908203 nb_pixel_total : 688 time to create 1 rle with old method : 0.0007827281951904297 time for calcul the mask position with numpy : 0.005843639373779297 nb_pixel_total : 66 time to create 1 rle with old method : 9.465217590332031e-05 time for calcul the mask position with numpy : 0.00573277473449707 nb_pixel_total : 968 time to create 1 rle with old method : 0.0011916160583496094 time for calcul the mask position with numpy : 0.005997419357299805 nb_pixel_total : 3444 time to create 1 rle with old method : 0.0038995742797851562 time for calcul the mask position with numpy : 0.0057675838470458984 nb_pixel_total : 498 time to create 1 rle with old method : 0.0006299018859863281 time for calcul the mask position with numpy : 0.005784034729003906 nb_pixel_total : 5473 time to create 1 rle with old method : 0.006401777267456055 time for calcul the mask position with numpy : 0.006138324737548828 nb_pixel_total : 625 time to create 1 rle with old method : 0.0007784366607666016 time for calcul the mask position with numpy : 0.005906105041503906 nb_pixel_total : 553 time to create 1 rle with old method : 0.0006673336029052734 time for calcul the mask position with numpy : 0.00586700439453125 nb_pixel_total : 692 time to create 1 rle with old method : 0.000789642333984375 time for calcul the mask position with numpy : 0.0058841705322265625 nb_pixel_total : 40 time to create 1 rle with old method : 8.153915405273438e-05 time for calcul the mask position with numpy : 0.00632929801940918 nb_pixel_total : 829 time to create 1 rle with old method : 0.0009467601776123047 time for calcul the mask position with numpy : 0.0058248043060302734 nb_pixel_total : 1147 time to create 1 rle with old method : 0.0013232231140136719 time for calcul the mask position with numpy : 0.0058095455169677734 nb_pixel_total : 1666 time to create 1 rle with old method : 0.0018963813781738281 time for calcul the mask position with numpy : 0.00662684440612793 nb_pixel_total : 182 time to create 1 rle with old method : 0.0002396106719970703 time for calcul the mask position with numpy : 0.005968332290649414 nb_pixel_total : 50 time to create 1 rle with old method : 0.00017142295837402344 time for calcul the mask position with numpy : 0.009604930877685547 nb_pixel_total : 1028 time to create 1 rle with old method : 0.0011603832244873047 time for calcul the mask position with numpy : 0.005815029144287109 nb_pixel_total : 188 time to create 1 rle with old method : 0.00031757354736328125 time for calcul the mask position with numpy : 0.005753993988037109 nb_pixel_total : 13669 time to create 1 rle with old method : 0.0157926082611084 time for calcul the mask position with numpy : 0.005866527557373047 nb_pixel_total : 125 time to create 1 rle with old method : 0.00016927719116210938 time for calcul the mask position with numpy : 0.005690813064575195 nb_pixel_total : 1035 time to create 1 rle with old method : 0.001058816909790039 time for calcul the mask position with numpy : 0.005875825881958008 nb_pixel_total : 752 time to create 1 rle with old method : 0.0008137226104736328 time for calcul the mask position with numpy : 0.006308317184448242 nb_pixel_total : 655 time to create 1 rle with old method : 0.0007507801055908203 time for calcul the mask position with numpy : 0.005957603454589844 nb_pixel_total : 1255 time to create 1 rle with old method : 0.001417398452758789 time for calcul the mask position with numpy : 0.0058116912841796875 nb_pixel_total : 538 time to create 1 rle with old method : 0.00069427490234375 time for calcul the mask position with numpy : 0.005733966827392578 nb_pixel_total : 1057 time to create 1 rle with old method : 0.001270294189453125 time for calcul the mask position with numpy : 0.006061077117919922 nb_pixel_total : 4011 time to create 1 rle with old method : 0.0048983097076416016 time for calcul the mask position with numpy : 0.006172895431518555 nb_pixel_total : 4819 time to create 1 rle with old method : 0.005501270294189453 time for calcul the mask position with numpy : 0.006043672561645508 nb_pixel_total : 168 time to create 1 rle with old method : 0.00020003318786621094 time for calcul the mask position with numpy : 0.006087779998779297 nb_pixel_total : 1011 time to create 1 rle with old method : 0.0012280941009521484 time for calcul the mask position with numpy : 0.0059316158294677734 nb_pixel_total : 133 time to create 1 rle with old method : 0.00021076202392578125 time for calcul the mask position with numpy : 0.00575709342956543 nb_pixel_total : 193 time to create 1 rle with old method : 0.0002532005310058594 time for calcul the mask position with numpy : 0.005742311477661133 nb_pixel_total : 155 time to create 1 rle with old method : 0.0002155303955078125 time for calcul the mask position with numpy : 0.005920886993408203 nb_pixel_total : 504 time to create 1 rle with old method : 0.0005595684051513672 time for calcul the mask position with numpy : 0.005732059478759766 nb_pixel_total : 34 time to create 1 rle with old method : 6.365776062011719e-05 time for calcul the mask position with numpy : 0.00616455078125 nb_pixel_total : 66 time to create 1 rle with old method : 9.608268737792969e-05 time for calcul the mask position with numpy : 0.005785942077636719 nb_pixel_total : 1493 time to create 1 rle with old method : 0.0017542839050292969 time for calcul the mask position with numpy : 0.005747556686401367 nb_pixel_total : 395 time to create 1 rle with old method : 0.0004699230194091797 time for calcul the mask position with numpy : 0.005778789520263672 nb_pixel_total : 337 time to create 1 rle with old method : 0.0003666877746582031 time for calcul the mask position with numpy : 0.005945682525634766 nb_pixel_total : 97 time to create 1 rle with old method : 0.00013303756713867188 time for calcul the mask position with numpy : 0.005728006362915039 nb_pixel_total : 135 time to create 1 rle with old method : 0.0001685619354248047 time for calcul the mask position with numpy : 0.0056743621826171875 nb_pixel_total : 205 time to create 1 rle with old method : 0.0002593994140625 time for calcul the mask position with numpy : 0.005984306335449219 nb_pixel_total : 292 time to create 1 rle with old method : 0.0003783702850341797 time for calcul the mask position with numpy : 0.006482362747192383 nb_pixel_total : 106502 time to create 1 rle with old method : 0.12155461311340332 time for calcul the mask position with numpy : 0.006104707717895508 nb_pixel_total : 3517 time to create 1 rle with old method : 0.004022836685180664 time for calcul the mask position with numpy : 0.0058536529541015625 nb_pixel_total : 205 time to create 1 rle with old method : 0.0002446174621582031 time for calcul the mask position with numpy : 0.006087064743041992 nb_pixel_total : 239 time to create 1 rle with old method : 0.00029349327087402344 time for calcul the mask position with numpy : 0.00644373893737793 nb_pixel_total : 115 time to create 1 rle with old method : 0.0001659393310546875 time for calcul the mask position with numpy : 0.006159543991088867 nb_pixel_total : 499 time to create 1 rle with old method : 0.0006000995635986328 time for calcul the mask position with numpy : 0.006022930145263672 nb_pixel_total : 453 time to create 1 rle with old method : 0.0005211830139160156 time for calcul the mask position with numpy : 0.005960941314697266 nb_pixel_total : 402 time to create 1 rle with old method : 0.0005276203155517578 time for calcul the mask position with numpy : 0.005944967269897461 nb_pixel_total : 381 time to create 1 rle with old method : 0.0004601478576660156 time for calcul the mask position with numpy : 0.00591731071472168 nb_pixel_total : 1643 time to create 1 rle with old method : 0.0019259452819824219 time for calcul the mask position with numpy : 0.005778312683105469 nb_pixel_total : 3847 time to create 1 rle with old method : 0.004483222961425781 time for calcul the mask position with numpy : 0.005912303924560547 nb_pixel_total : 2400 time to create 1 rle with old method : 0.0027875900268554688 time for calcul the mask position with numpy : 0.005766630172729492 nb_pixel_total : 2587 time to create 1 rle with old method : 0.003114938735961914 time for calcul the mask position with numpy : 0.005591392517089844 nb_pixel_total : 125 time to create 1 rle with old method : 0.00017976760864257812 time for calcul the mask position with numpy : 0.005683183670043945 nb_pixel_total : 124 time to create 1 rle with old method : 0.00015234947204589844 time for calcul the mask position with numpy : 0.0056874752044677734 nb_pixel_total : 195 time to create 1 rle with old method : 0.00025081634521484375 time for calcul the mask position with numpy : 0.005692720413208008 nb_pixel_total : 532 time to create 1 rle with old method : 0.0005903244018554688 time for calcul the mask position with numpy : 0.005888223648071289 nb_pixel_total : 2 time to create 1 rle with old method : 2.3603439331054688e-05 time for calcul the mask position with numpy : 0.005879878997802734 nb_pixel_total : 7578 time to create 1 rle with old method : 0.007936954498291016 time for calcul the mask position with numpy : 0.005908966064453125 nb_pixel_total : 612 time to create 1 rle with old method : 0.0007319450378417969 time for calcul the mask position with numpy : 0.0056149959564208984 nb_pixel_total : 859 time to create 1 rle with old method : 0.0009076595306396484 time for calcul the mask position with numpy : 0.005741596221923828 nb_pixel_total : 11 time to create 1 rle with old method : 4.363059997558594e-05 time for calcul the mask position with numpy : 0.005675792694091797 nb_pixel_total : 327 time to create 1 rle with old method : 0.0003726482391357422 create new chi : 0.7501778602600098 after preparing all the mask , begin to delete the rle from the crop_hashtag_id => VR 28-11-20 : il faut déplacer cela apres le save_crop_hashtag_ids_obj de la ligne 9514 ! we have 0 chi objets contains the rles time to delete rle : 0.0012307167053222656 batch 1 Loaded 75 chid ids of type : 4230 Number RLEs to save : 7812 TO DO : save crop sub photo not yet done ! save time : 0.45281457901000977 nb_obj : 82 nb_hashtags : 6 time to prepare the origin masks : 1.7255656719207764 time for calcul the mask position with numpy : 0.03982877731323242 nb_pixel_total : 1871872 time to create 1 rle with new method : 0.6189613342285156 time for calcul the mask position with numpy : 0.006393909454345703 nb_pixel_total : 219 time to create 1 rle with old method : 0.0002543926239013672 time for calcul the mask position with numpy : 0.006403923034667969 nb_pixel_total : 8 time to create 1 rle with old method : 3.528594970703125e-05 time for calcul the mask position with numpy : 0.006487607955932617 nb_pixel_total : 974 time to create 1 rle with old method : 0.0011522769927978516 time for calcul the mask position with numpy : 0.006417989730834961 nb_pixel_total : 262 time to create 1 rle with old method : 0.0003457069396972656 time for calcul the mask position with numpy : 0.006299495697021484 nb_pixel_total : 71 time to create 1 rle with old method : 0.0001385211944580078 time for calcul the mask position with numpy : 0.006122589111328125 nb_pixel_total : 13391 time to create 1 rle with old method : 0.014440059661865234 time for calcul the mask position with numpy : 0.006246328353881836 nb_pixel_total : 2600 time to create 1 rle with old method : 0.0030319690704345703 time for calcul the mask position with numpy : 0.005939483642578125 nb_pixel_total : 1203 time to create 1 rle with old method : 0.0014314651489257812 time for calcul the mask position with numpy : 0.006041049957275391 nb_pixel_total : 201 time to create 1 rle with old method : 0.0002334117889404297 time for calcul the mask position with numpy : 0.0061206817626953125 nb_pixel_total : 338 time to create 1 rle with old method : 0.0004379749298095703 time for calcul the mask position with numpy : 0.006131410598754883 nb_pixel_total : 99 time to create 1 rle with old method : 0.00013017654418945312 time for calcul the mask position with numpy : 0.006301164627075195 nb_pixel_total : 62 time to create 1 rle with old method : 0.00014209747314453125 time for calcul the mask position with numpy : 0.0060541629791259766 nb_pixel_total : 4126 time to create 1 rle with old method : 0.004836559295654297 time for calcul the mask position with numpy : 0.0057332515716552734 nb_pixel_total : 398 time to create 1 rle with old method : 0.0004525184631347656 time for calcul the mask position with numpy : 0.006247997283935547 nb_pixel_total : 7921 time to create 1 rle with old method : 0.008825540542602539 time for calcul the mask position with numpy : 0.00637364387512207 nb_pixel_total : 982 time to create 1 rle with old method : 0.0011444091796875 time for calcul the mask position with numpy : 0.006071567535400391 nb_pixel_total : 247 time to create 1 rle with old method : 0.00036406517028808594 time for calcul the mask position with numpy : 0.006066799163818359 nb_pixel_total : 219 time to create 1 rle with old method : 0.00025963783264160156 time for calcul the mask position with numpy : 0.006227970123291016 nb_pixel_total : 618 time to create 1 rle with old method : 0.0007462501525878906 time for calcul the mask position with numpy : 0.006208658218383789 nb_pixel_total : 683 time to create 1 rle with old method : 0.0008237361907958984 time for calcul the mask position with numpy : 0.00599980354309082 nb_pixel_total : 255 time to create 1 rle with old method : 0.0003600120544433594 time for calcul the mask position with numpy : 0.006186246871948242 nb_pixel_total : 1320 time to create 1 rle with old method : 0.0015666484832763672 time for calcul the mask position with numpy : 0.006055355072021484 nb_pixel_total : 792 time to create 1 rle with old method : 0.0009300708770751953 time for calcul the mask position with numpy : 0.005950927734375 nb_pixel_total : 36 time to create 1 rle with old method : 6.341934204101562e-05 time for calcul the mask position with numpy : 0.006060361862182617 nb_pixel_total : 44 time to create 1 rle with old method : 9.322166442871094e-05 time for calcul the mask position with numpy : 0.005889892578125 nb_pixel_total : 1762 time to create 1 rle with old method : 0.0020499229431152344 time for calcul the mask position with numpy : 0.00606226921081543 nb_pixel_total : 609 time to create 1 rle with old method : 0.0007183551788330078 time for calcul the mask position with numpy : 0.00656580924987793 nb_pixel_total : 860 time to create 1 rle with old method : 0.0010297298431396484 time for calcul the mask position with numpy : 0.00603795051574707 nb_pixel_total : 26 time to create 1 rle with old method : 9.059906005859375e-05 time for calcul the mask position with numpy : 0.005910634994506836 nb_pixel_total : 14494 time to create 1 rle with old method : 0.015254735946655273 time for calcul the mask position with numpy : 0.0061876773834228516 nb_pixel_total : 1025 time to create 1 rle with old method : 0.0011320114135742188 time for calcul the mask position with numpy : 0.006299495697021484 nb_pixel_total : 1278 time to create 1 rle with old method : 0.001382589340209961 time for calcul the mask position with numpy : 0.006186246871948242 nb_pixel_total : 721 time to create 1 rle with old method : 0.0008497238159179688 time for calcul the mask position with numpy : 0.005912303924560547 nb_pixel_total : 964 time to create 1 rle with old method : 0.0011429786682128906 time for calcul the mask position with numpy : 0.00586700439453125 nb_pixel_total : 4412 time to create 1 rle with old method : 0.004739046096801758 time for calcul the mask position with numpy : 0.006037473678588867 nb_pixel_total : 3892 time to create 1 rle with old method : 0.004533290863037109 time for calcul the mask position with numpy : 0.006162405014038086 nb_pixel_total : 42 time to create 1 rle with old method : 0.0001087188720703125 time for calcul the mask position with numpy : 0.005993843078613281 nb_pixel_total : 1319 time to create 1 rle with old method : 0.001434326171875 time for calcul the mask position with numpy : 0.0061376094818115234 nb_pixel_total : 17 time to create 1 rle with old method : 7.033348083496094e-05 time for calcul the mask position with numpy : 0.005889892578125 nb_pixel_total : 508 time to create 1 rle with old method : 0.0006437301635742188 time for calcul the mask position with numpy : 0.005927324295043945 nb_pixel_total : 838 time to create 1 rle with old method : 0.0009331703186035156 time for calcul the mask position with numpy : 0.006057262420654297 nb_pixel_total : 188 time to create 1 rle with old method : 0.0002617835998535156 time for calcul the mask position with numpy : 0.005855083465576172 nb_pixel_total : 120 time to create 1 rle with old method : 0.00018167495727539062 time for calcul the mask position with numpy : 0.006012678146362305 nb_pixel_total : 190 time to create 1 rle with old method : 0.0002181529998779297 time for calcul the mask position with numpy : 0.00612330436706543 nb_pixel_total : 164 time to create 1 rle with old method : 0.00022339820861816406 time for calcul the mask position with numpy : 0.005937337875366211 nb_pixel_total : 288 time to create 1 rle with old method : 0.00037026405334472656 time for calcul the mask position with numpy : 0.00636601448059082 nb_pixel_total : 528 time to create 1 rle with old method : 0.0006299018859863281 time for calcul the mask position with numpy : 0.006014108657836914 nb_pixel_total : 282 time to create 1 rle with old method : 0.00038433074951171875 time for calcul the mask position with numpy : 0.006139278411865234 nb_pixel_total : 623 time to create 1 rle with old method : 0.0007207393646240234 time for calcul the mask position with numpy : 0.00609588623046875 nb_pixel_total : 32 time to create 1 rle with old method : 5.984306335449219e-05 time for calcul the mask position with numpy : 0.006052494049072266 nb_pixel_total : 48 time to create 1 rle with old method : 7.462501525878906e-05 time for calcul the mask position with numpy : 0.00588679313659668 nb_pixel_total : 1450 time to create 1 rle with old method : 0.0016667842864990234 time for calcul the mask position with numpy : 0.006241559982299805 nb_pixel_total : 18 time to create 1 rle with old method : 8.249282836914062e-05 time for calcul the mask position with numpy : 0.0058786869049072266 nb_pixel_total : 257 time to create 1 rle with old method : 0.000293731689453125 time for calcul the mask position with numpy : 0.0059661865234375 nb_pixel_total : 471 time to create 1 rle with old method : 0.0005021095275878906 time for calcul the mask position with numpy : 0.005615234375 nb_pixel_total : 363 time to create 1 rle with old method : 0.0004401206970214844 time for calcul the mask position with numpy : 0.005781650543212891 nb_pixel_total : 98 time to create 1 rle with old method : 0.00011849403381347656 time for calcul the mask position with numpy : 0.0058977603912353516 nb_pixel_total : 209 time to create 1 rle with old method : 0.00028228759765625 time for calcul the mask position with numpy : 0.006041049957275391 nb_pixel_total : 228 time to create 1 rle with old method : 0.0002696514129638672 time for calcul the mask position with numpy : 0.007619142532348633 nb_pixel_total : 106000 time to create 1 rle with old method : 0.11075091361999512 time for calcul the mask position with numpy : 0.006287097930908203 nb_pixel_total : 419 time to create 1 rle with old method : 0.000507354736328125 time for calcul the mask position with numpy : 0.01007843017578125 nb_pixel_total : 350 time to create 1 rle with old method : 0.0007855892181396484 time for calcul the mask position with numpy : 0.006539106369018555 nb_pixel_total : 205 time to create 1 rle with old method : 0.00024080276489257812 time for calcul the mask position with numpy : 0.005878925323486328 nb_pixel_total : 10 time to create 1 rle with old method : 3.933906555175781e-05 time for calcul the mask position with numpy : 0.0061762332916259766 nb_pixel_total : 223 time to create 1 rle with old method : 0.0002655982971191406 time for calcul the mask position with numpy : 0.006006717681884766 nb_pixel_total : 1342 time to create 1 rle with old method : 0.0015358924865722656 time for calcul the mask position with numpy : 0.005800962448120117 nb_pixel_total : 434 time to create 1 rle with old method : 0.0004642009735107422 time for calcul the mask position with numpy : 0.005799531936645508 nb_pixel_total : 414 time to create 1 rle with old method : 0.0007445812225341797 time for calcul the mask position with numpy : 0.006134748458862305 nb_pixel_total : 397 time to create 1 rle with old method : 0.0004703998565673828 time for calcul the mask position with numpy : 0.006231546401977539 nb_pixel_total : 1558 time to create 1 rle with old method : 0.0017728805541992188 time for calcul the mask position with numpy : 0.006072521209716797 nb_pixel_total : 171 time to create 1 rle with old method : 0.00019979476928710938 time for calcul the mask position with numpy : 0.006291389465332031 nb_pixel_total : 2608 time to create 1 rle with old method : 0.0028839111328125 time for calcul the mask position with numpy : 0.006204843521118164 nb_pixel_total : 2380 time to create 1 rle with old method : 0.0026705265045166016 time for calcul the mask position with numpy : 0.006087064743041992 nb_pixel_total : 132 time to create 1 rle with old method : 0.00015473365783691406 time for calcul the mask position with numpy : 0.00654911994934082 nb_pixel_total : 238 time to create 1 rle with old method : 0.00026798248291015625 time for calcul the mask position with numpy : 0.0064258575439453125 nb_pixel_total : 7590 time to create 1 rle with old method : 0.008337974548339844 time for calcul the mask position with numpy : 0.006939888000488281 nb_pixel_total : 1026 time to create 1 rle with old method : 0.0011835098266601562 time for calcul the mask position with numpy : 0.00803685188293457 nb_pixel_total : 37 time to create 1 rle with old method : 0.00012540817260742188 time for calcul the mask position with numpy : 0.008228063583374023 nb_pixel_total : 98 time to create 1 rle with old method : 0.00012874603271484375 time for calcul the mask position with numpy : 0.008264780044555664 nb_pixel_total : 79 time to create 1 rle with old method : 0.00010609626770019531 time for calcul the mask position with numpy : 0.011945247650146484 nb_pixel_total : 288 time to create 1 rle with old method : 0.0003304481506347656 time for calcul the mask position with numpy : 0.008195638656616211 nb_pixel_total : 336 time to create 1 rle with old method : 0.0003941059112548828 create new chi : 1.4096200466156006 after preparing all the mask , begin to delete the rle from the crop_hashtag_id => VR 28-11-20 : il faut déplacer cela apres le save_crop_hashtag_ids_obj de la ligne 9514 ! we have 0 chi objets contains the rles time to delete rle : 0.001428365707397461 batch 1 Loaded 94 chid ids of type : 4230 Number RLEs to save : 8933 TO DO : save crop sub photo not yet done ! save time : 0.509284496307373 nb_obj : 94 nb_hashtags : 6 time to prepare the origin masks : 1.8759291172027588 time for calcul the mask position with numpy : 0.04354548454284668 nb_pixel_total : 1836879 time to create 1 rle with new method : 0.3664367198944092 time for calcul the mask position with numpy : 0.009178876876831055 nb_pixel_total : 139 time to create 1 rle with old method : 0.00018405914306640625 time for calcul the mask position with numpy : 0.009281396865844727 nb_pixel_total : 52 time to create 1 rle with old method : 0.00010085105895996094 time for calcul the mask position with numpy : 0.008754968643188477 nb_pixel_total : 10 time to create 1 rle with old method : 3.504753112792969e-05 time for calcul the mask position with numpy : 0.008747100830078125 nb_pixel_total : 980 time to create 1 rle with old method : 0.0010623931884765625 time for calcul the mask position with numpy : 0.008853673934936523 nb_pixel_total : 140 time to create 1 rle with old method : 0.0002090930938720703 time for calcul the mask position with numpy : 0.008858680725097656 nb_pixel_total : 373 time to create 1 rle with old method : 0.0004532337188720703 time for calcul the mask position with numpy : 0.008675098419189453 nb_pixel_total : 292 time to create 1 rle with old method : 0.00033593177795410156 time for calcul the mask position with numpy : 0.008997678756713867 nb_pixel_total : 40 time to create 1 rle with old method : 0.00010418891906738281 time for calcul the mask position with numpy : 0.009075641632080078 nb_pixel_total : 360 time to create 1 rle with old method : 0.0003924369812011719 time for calcul the mask position with numpy : 0.005939483642578125 nb_pixel_total : 33 time to create 1 rle with old method : 5.269050598144531e-05 time for calcul the mask position with numpy : 0.005573749542236328 nb_pixel_total : 103 time to create 1 rle with old method : 0.00013256072998046875 time for calcul the mask position with numpy : 0.005635738372802734 nb_pixel_total : 61 time to create 1 rle with old method : 8.678436279296875e-05 time for calcul the mask position with numpy : 0.005602836608886719 nb_pixel_total : 507 time to create 1 rle with old method : 0.0006015300750732422 time for calcul the mask position with numpy : 0.00559687614440918 nb_pixel_total : 3162 time to create 1 rle with old method : 0.0036869049072265625 time for calcul the mask position with numpy : 0.006057024002075195 nb_pixel_total : 215 time to create 1 rle with old method : 0.0002727508544921875 time for calcul the mask position with numpy : 0.009150981903076172 nb_pixel_total : 415 time to create 1 rle with old method : 0.000461578369140625 time for calcul the mask position with numpy : 0.008970260620117188 nb_pixel_total : 303 time to create 1 rle with old method : 0.0004057884216308594 time for calcul the mask position with numpy : 0.008867025375366211 nb_pixel_total : 26 time to create 1 rle with old method : 8.559226989746094e-05 time for calcul the mask position with numpy : 0.009101629257202148 nb_pixel_total : 1069 time to create 1 rle with old method : 0.001262664794921875 time for calcul the mask position with numpy : 0.009375333786010742 nb_pixel_total : 19 time to create 1 rle with old method : 5.340576171875e-05 time for calcul the mask position with numpy : 0.010301589965820312 nb_pixel_total : 77 time to create 1 rle with old method : 0.0002570152282714844 time for calcul the mask position with numpy : 0.008449077606201172 nb_pixel_total : 1805 time to create 1 rle with old method : 0.0021555423736572266 time for calcul the mask position with numpy : 0.005931854248046875 nb_pixel_total : 132 time to create 1 rle with old method : 0.000186920166015625 time for calcul the mask position with numpy : 0.005892276763916016 nb_pixel_total : 4642 time to create 1 rle with old method : 0.005232334136962891 time for calcul the mask position with numpy : 0.00588536262512207 nb_pixel_total : 284 time to create 1 rle with old method : 0.00038051605224609375 time for calcul the mask position with numpy : 0.006234169006347656 nb_pixel_total : 6532 time to create 1 rle with old method : 0.007076740264892578 time for calcul the mask position with numpy : 0.0058994293212890625 nb_pixel_total : 7192 time to create 1 rle with old method : 0.007906198501586914 time for calcul the mask position with numpy : 0.005795955657958984 nb_pixel_total : 4837 time to create 1 rle with old method : 0.005216836929321289 time for calcul the mask position with numpy : 0.005716562271118164 nb_pixel_total : 548 time to create 1 rle with old method : 0.0006189346313476562 time for calcul the mask position with numpy : 0.0055849552154541016 nb_pixel_total : 95 time to create 1 rle with old method : 0.0001246929168701172 time for calcul the mask position with numpy : 0.008856534957885742 nb_pixel_total : 2246 time to create 1 rle with old method : 0.002462148666381836 time for calcul the mask position with numpy : 0.008779764175415039 nb_pixel_total : 72 time to create 1 rle with old method : 0.00010418891906738281 time for calcul the mask position with numpy : 0.008868694305419922 nb_pixel_total : 815 time to create 1 rle with old method : 0.0009481906890869141 time for calcul the mask position with numpy : 0.008675575256347656 nb_pixel_total : 2320 time to create 1 rle with old method : 0.002518892288208008 time for calcul the mask position with numpy : 0.009558439254760742 nb_pixel_total : 1736 time to create 1 rle with old method : 0.0020198822021484375 time for calcul the mask position with numpy : 0.008719444274902344 nb_pixel_total : 368 time to create 1 rle with old method : 0.0004684925079345703 time for calcul the mask position with numpy : 0.00885009765625 nb_pixel_total : 175 time to create 1 rle with old method : 0.0003559589385986328 time for calcul the mask position with numpy : 0.008433103561401367 nb_pixel_total : 1133 time to create 1 rle with old method : 0.00119781494140625 time for calcul the mask position with numpy : 0.008672237396240234 nb_pixel_total : 1340 time to create 1 rle with old method : 0.0014586448669433594 time for calcul the mask position with numpy : 0.008529186248779297 nb_pixel_total : 237 time to create 1 rle with old method : 0.00029659271240234375 time for calcul the mask position with numpy : 0.008748054504394531 nb_pixel_total : 993 time to create 1 rle with old method : 0.0010628700256347656 time for calcul the mask position with numpy : 0.008446216583251953 nb_pixel_total : 1254 time to create 1 rle with old method : 0.001354217529296875 time for calcul the mask position with numpy : 0.008676290512084961 nb_pixel_total : 769 time to create 1 rle with old method : 0.0008947849273681641 time for calcul the mask position with numpy : 0.009257793426513672 nb_pixel_total : 887 time to create 1 rle with old method : 0.001024007797241211 time for calcul the mask position with numpy : 0.008998394012451172 nb_pixel_total : 4419 time to create 1 rle with old method : 0.004897117614746094 time for calcul the mask position with numpy : 0.008862495422363281 nb_pixel_total : 3176 time to create 1 rle with old method : 0.003590106964111328 time for calcul the mask position with numpy : 0.009023427963256836 nb_pixel_total : 72 time to create 1 rle with old method : 0.00010538101196289062 time for calcul the mask position with numpy : 0.0060160160064697266 nb_pixel_total : 126 time to create 1 rle with old method : 0.0001766681671142578 time for calcul the mask position with numpy : 0.005709171295166016 nb_pixel_total : 1038 time to create 1 rle with old method : 0.0011398792266845703 time for calcul the mask position with numpy : 0.005695343017578125 nb_pixel_total : 364 time to create 1 rle with old method : 0.0004165172576904297 time for calcul the mask position with numpy : 0.005612850189208984 nb_pixel_total : 769 time to create 1 rle with old method : 0.0008130073547363281 time for calcul the mask position with numpy : 0.008714675903320312 nb_pixel_total : 1044 time to create 1 rle with old method : 0.0011708736419677734 time for calcul the mask position with numpy : 0.005900144577026367 nb_pixel_total : 429 time to create 1 rle with old method : 0.0004780292510986328 time for calcul the mask position with numpy : 0.005780458450317383 nb_pixel_total : 156 time to create 1 rle with old method : 0.00019168853759765625 time for calcul the mask position with numpy : 0.005741596221923828 nb_pixel_total : 246 time to create 1 rle with old method : 0.00032901763916015625 time for calcul the mask position with numpy : 0.00563812255859375 nb_pixel_total : 215 time to create 1 rle with old method : 0.00027441978454589844 time for calcul the mask position with numpy : 0.005693912506103516 nb_pixel_total : 6 time to create 1 rle with old method : 3.743171691894531e-05 time for calcul the mask position with numpy : 0.00573277473449707 nb_pixel_total : 542 time to create 1 rle with old method : 0.0006463527679443359 time for calcul the mask position with numpy : 0.005707979202270508 nb_pixel_total : 670 time to create 1 rle with old method : 0.0008502006530761719 time for calcul the mask position with numpy : 0.005920886993408203 nb_pixel_total : 34 time to create 1 rle with old method : 5.698204040527344e-05 time for calcul the mask position with numpy : 0.0059051513671875 nb_pixel_total : 80 time to create 1 rle with old method : 0.00011181831359863281 time for calcul the mask position with numpy : 0.005897998809814453 nb_pixel_total : 2121 time to create 1 rle with old method : 0.0024862289428710938 time for calcul the mask position with numpy : 0.009486913681030273 nb_pixel_total : 1312 time to create 1 rle with old method : 0.0014798641204833984 time for calcul the mask position with numpy : 0.009212017059326172 nb_pixel_total : 337 time to create 1 rle with old method : 0.0003905296325683594 time for calcul the mask position with numpy : 0.009075641632080078 nb_pixel_total : 22 time to create 1 rle with old method : 5.340576171875e-05 time for calcul the mask position with numpy : 0.00949716567993164 nb_pixel_total : 390 time to create 1 rle with old method : 0.00043964385986328125 time for calcul the mask position with numpy : 0.009462118148803711 nb_pixel_total : 418 time to create 1 rle with old method : 0.00048041343688964844 time for calcul the mask position with numpy : 0.009489774703979492 nb_pixel_total : 98 time to create 1 rle with old method : 0.00014209747314453125 time for calcul the mask position with numpy : 0.009423017501831055 nb_pixel_total : 42 time to create 1 rle with old method : 7.677078247070312e-05 time for calcul the mask position with numpy : 0.009459495544433594 nb_pixel_total : 147 time to create 1 rle with old method : 0.0001773834228515625 time for calcul the mask position with numpy : 0.009416580200195312 nb_pixel_total : 255 time to create 1 rle with old method : 0.0002982616424560547 time for calcul the mask position with numpy : 0.010056018829345703 nb_pixel_total : 106589 time to create 1 rle with old method : 0.11064839363098145 time for calcul the mask position with numpy : 0.010131120681762695 nb_pixel_total : 415 time to create 1 rle with old method : 0.0005309581756591797 time for calcul the mask position with numpy : 0.014139175415039062 nb_pixel_total : 190 time to create 1 rle with old method : 0.00037670135498046875 time for calcul the mask position with numpy : 0.010735273361206055 nb_pixel_total : 40935 time to create 1 rle with old method : 0.044057369232177734 time for calcul the mask position with numpy : 0.009438276290893555 nb_pixel_total : 3006 time to create 1 rle with old method : 0.0034570693969726562 time for calcul the mask position with numpy : 0.01015925407409668 nb_pixel_total : 229 time to create 1 rle with old method : 0.0003445148468017578 time for calcul the mask position with numpy : 0.010199308395385742 nb_pixel_total : 440 time to create 1 rle with old method : 0.00051116943359375 time for calcul the mask position with numpy : 0.009370803833007812 nb_pixel_total : 54 time to create 1 rle with old method : 9.679794311523438e-05 time for calcul the mask position with numpy : 0.009271621704101562 nb_pixel_total : 373 time to create 1 rle with old method : 0.00043010711669921875 time for calcul the mask position with numpy : 0.009412527084350586 nb_pixel_total : 185 time to create 1 rle with old method : 0.00022530555725097656 time for calcul the mask position with numpy : 0.009204864501953125 nb_pixel_total : 368 time to create 1 rle with old method : 0.00043082237243652344 time for calcul the mask position with numpy : 0.007647514343261719 nb_pixel_total : 1552 time to create 1 rle with old method : 0.0015974044799804688 time for calcul the mask position with numpy : 0.0076487064361572266 nb_pixel_total : 2212 time to create 1 rle with old method : 0.0023643970489501953 time for calcul the mask position with numpy : 0.008300065994262695 nb_pixel_total : 2523 time to create 1 rle with old method : 0.002711057662963867 time for calcul the mask position with numpy : 0.0079193115234375 nb_pixel_total : 241 time to create 1 rle with old method : 0.0002918243408203125 time for calcul the mask position with numpy : 0.008097648620605469 nb_pixel_total : 127 time to create 1 rle with old method : 0.0001430511474609375 time for calcul the mask position with numpy : 0.007872343063354492 nb_pixel_total : 244 time to create 1 rle with old method : 0.00028967857360839844 time for calcul the mask position with numpy : 0.007822275161743164 nb_pixel_total : 89 time to create 1 rle with old method : 0.00012755393981933594 time for calcul the mask position with numpy : 0.008188486099243164 nb_pixel_total : 7429 time to create 1 rle with old method : 0.007953882217407227 time for calcul the mask position with numpy : 0.008237123489379883 nb_pixel_total : 576 time to create 1 rle with old method : 0.0007128715515136719 time for calcul the mask position with numpy : 0.00815582275390625 nb_pixel_total : 382 time to create 1 rle with old method : 0.0004553794860839844 time for calcul the mask position with numpy : 0.008097171783447266 nb_pixel_total : 928 time to create 1 rle with old method : 0.001071929931640625 time for calcul the mask position with numpy : 0.008177995681762695 nb_pixel_total : 318 time to create 1 rle with old method : 0.0003826618194580078 create new chi : 1.4354357719421387 after preparing all the mask , begin to delete the rle from the crop_hashtag_id => VR 28-11-20 : il faut déplacer cela apres le save_crop_hashtag_ids_obj de la ligne 9514 ! we have 0 chi objets contains the rles time to delete rle : 0.0017125606536865234 batch 1 Loaded 106 chid ids of type : 4230 Number RLEs to save : 9614 TO DO : save crop sub photo not yet done ! save time : 1.459742784500122 nb_obj : 89 nb_hashtags : 6 time to prepare the origin masks : 1.9055452346801758 time for calcul the mask position with numpy : 0.025841712951660156 nb_pixel_total : 1871967 time to create 1 rle with new method : 0.06199002265930176 time for calcul the mask position with numpy : 0.006005764007568359 nb_pixel_total : 1029 time to create 1 rle with old method : 0.001201629638671875 time for calcul the mask position with numpy : 0.005747556686401367 nb_pixel_total : 312 time to create 1 rle with old method : 0.00037550926208496094 time for calcul the mask position with numpy : 0.005816221237182617 nb_pixel_total : 355 time to create 1 rle with old method : 0.00043845176696777344 time for calcul the mask position with numpy : 0.0059490203857421875 nb_pixel_total : 111 time to create 1 rle with old method : 0.0002377033233642578 time for calcul the mask position with numpy : 0.0065457820892333984 nb_pixel_total : 98 time to create 1 rle with old method : 0.00014925003051757812 time for calcul the mask position with numpy : 0.006900787353515625 nb_pixel_total : 1262 time to create 1 rle with old method : 0.0015256404876708984 time for calcul the mask position with numpy : 0.006880521774291992 nb_pixel_total : 688 time to create 1 rle with old method : 0.001055002212524414 time for calcul the mask position with numpy : 0.006329774856567383 nb_pixel_total : 1905 time to create 1 rle with old method : 0.00214385986328125 time for calcul the mask position with numpy : 0.005850553512573242 nb_pixel_total : 2 time to create 1 rle with old method : 2.574920654296875e-05 time for calcul the mask position with numpy : 0.0059430599212646484 nb_pixel_total : 52 time to create 1 rle with old method : 0.00013375282287597656 time for calcul the mask position with numpy : 0.005856513977050781 nb_pixel_total : 2689 time to create 1 rle with old method : 0.002977609634399414 time for calcul the mask position with numpy : 0.005859851837158203 nb_pixel_total : 953 time to create 1 rle with old method : 0.0011320114135742188 time for calcul the mask position with numpy : 0.0056874752044677734 nb_pixel_total : 30 time to create 1 rle with old method : 0.0001823902130126953 time for calcul the mask position with numpy : 0.005881786346435547 nb_pixel_total : 1963 time to create 1 rle with old method : 0.0023920536041259766 time for calcul the mask position with numpy : 0.006049156188964844 nb_pixel_total : 306 time to create 1 rle with old method : 0.00036263465881347656 time for calcul the mask position with numpy : 0.006003856658935547 nb_pixel_total : 684 time to create 1 rle with old method : 0.0007855892181396484 time for calcul the mask position with numpy : 0.005749702453613281 nb_pixel_total : 1151 time to create 1 rle with old method : 0.0014073848724365234 time for calcul the mask position with numpy : 0.005844593048095703 nb_pixel_total : 98 time to create 1 rle with old method : 0.00013065338134765625 time for calcul the mask position with numpy : 0.005832672119140625 nb_pixel_total : 101 time to create 1 rle with old method : 0.0001499652862548828 time for calcul the mask position with numpy : 0.005950212478637695 nb_pixel_total : 3584 time to create 1 rle with old method : 0.0042877197265625 time for calcul the mask position with numpy : 0.006106376647949219 nb_pixel_total : 1096 time to create 1 rle with old method : 0.0012967586517333984 time for calcul the mask position with numpy : 0.006072998046875 nb_pixel_total : 6157 time to create 1 rle with old method : 0.006702899932861328 time for calcul the mask position with numpy : 0.005948543548583984 nb_pixel_total : 1826 time to create 1 rle with old method : 0.0019423961639404297 time for calcul the mask position with numpy : 0.006033897399902344 nb_pixel_total : 7666 time to create 1 rle with old method : 0.008205175399780273 time for calcul the mask position with numpy : 0.005931854248046875 nb_pixel_total : 544 time to create 1 rle with old method : 0.000701904296875 time for calcul the mask position with numpy : 0.005941867828369141 nb_pixel_total : 234 time to create 1 rle with old method : 0.0002636909484863281 time for calcul the mask position with numpy : 0.0059010982513427734 nb_pixel_total : 564 time to create 1 rle with old method : 0.0006933212280273438 time for calcul the mask position with numpy : 0.005940675735473633 nb_pixel_total : 2341 time to create 1 rle with old method : 0.0026717185974121094 time for calcul the mask position with numpy : 0.006083011627197266 nb_pixel_total : 604 time to create 1 rle with old method : 0.0007076263427734375 time for calcul the mask position with numpy : 0.006167888641357422 nb_pixel_total : 96 time to create 1 rle with old method : 0.0001423358917236328 time for calcul the mask position with numpy : 0.0062961578369140625 nb_pixel_total : 1180 time to create 1 rle with old method : 0.0013322830200195312 time for calcul the mask position with numpy : 0.005953073501586914 nb_pixel_total : 836 time to create 1 rle with old method : 0.0009546279907226562 time for calcul the mask position with numpy : 0.005870342254638672 nb_pixel_total : 2223 time to create 1 rle with old method : 0.0032339096069335938 time for calcul the mask position with numpy : 0.006144285202026367 nb_pixel_total : 43 time to create 1 rle with old method : 0.00011181831359863281 time for calcul the mask position with numpy : 0.005887269973754883 nb_pixel_total : 187 time to create 1 rle with old method : 0.0002384185791015625 time for calcul the mask position with numpy : 0.0060579776763916016 nb_pixel_total : 204 time to create 1 rle with old method : 0.0002865791320800781 time for calcul the mask position with numpy : 0.00628209114074707 nb_pixel_total : 882 time to create 1 rle with old method : 0.0010251998901367188 time for calcul the mask position with numpy : 0.00597071647644043 nb_pixel_total : 295 time to create 1 rle with old method : 0.00038695335388183594 time for calcul the mask position with numpy : 0.006096839904785156 nb_pixel_total : 414 time to create 1 rle with old method : 0.0005269050598144531 time for calcul the mask position with numpy : 0.006137371063232422 nb_pixel_total : 14176 time to create 1 rle with old method : 0.015615701675415039 time for calcul the mask position with numpy : 0.006025075912475586 nb_pixel_total : 31 time to create 1 rle with old method : 0.0001773834228515625 time for calcul the mask position with numpy : 0.005758762359619141 nb_pixel_total : 1396 time to create 1 rle with old method : 0.0015561580657958984 time for calcul the mask position with numpy : 0.005665779113769531 nb_pixel_total : 667 time to create 1 rle with old method : 0.0008115768432617188 time for calcul the mask position with numpy : 0.005860090255737305 nb_pixel_total : 1027 time to create 1 rle with old method : 0.0011410713195800781 time for calcul the mask position with numpy : 0.00622248649597168 nb_pixel_total : 3408 time to create 1 rle with old method : 0.0040950775146484375 time for calcul the mask position with numpy : 0.006392478942871094 nb_pixel_total : 151 time to create 1 rle with old method : 0.00021338462829589844 time for calcul the mask position with numpy : 0.005898952484130859 nb_pixel_total : 1086 time to create 1 rle with old method : 0.0016772747039794922 time for calcul the mask position with numpy : 0.006508827209472656 nb_pixel_total : 3393 time to create 1 rle with old method : 0.0055162906646728516 time for calcul the mask position with numpy : 0.006436824798583984 nb_pixel_total : 351 time to create 1 rle with old method : 0.0006771087646484375 time for calcul the mask position with numpy : 0.006398200988769531 nb_pixel_total : 13 time to create 1 rle with old method : 6.4849853515625e-05 time for calcul the mask position with numpy : 0.006416797637939453 nb_pixel_total : 517 time to create 1 rle with old method : 0.0008935928344726562 time for calcul the mask position with numpy : 0.006419181823730469 nb_pixel_total : 343 time to create 1 rle with old method : 0.0005979537963867188 time for calcul the mask position with numpy : 0.006444215774536133 nb_pixel_total : 162 time to create 1 rle with old method : 0.0002872943878173828 time for calcul the mask position with numpy : 0.006427288055419922 nb_pixel_total : 557 time to create 1 rle with old method : 0.0009317398071289062 time for calcul the mask position with numpy : 0.006404876708984375 nb_pixel_total : 188 time to create 1 rle with old method : 0.00035452842712402344 time for calcul the mask position with numpy : 0.00637054443359375 nb_pixel_total : 11 time to create 1 rle with old method : 8.20159912109375e-05 time for calcul the mask position with numpy : 0.006426095962524414 nb_pixel_total : 39 time to create 1 rle with old method : 0.00011444091796875 time for calcul the mask position with numpy : 0.006516456604003906 nb_pixel_total : 527 time to create 1 rle with old method : 0.0008945465087890625 time for calcul the mask position with numpy : 0.006022930145263672 nb_pixel_total : 24 time to create 1 rle with old method : 5.1975250244140625e-05 time for calcul the mask position with numpy : 0.005861520767211914 nb_pixel_total : 622 time to create 1 rle with old method : 0.0007092952728271484 time for calcul the mask position with numpy : 0.005794048309326172 nb_pixel_total : 80 time to create 1 rle with old method : 0.00010776519775390625 time for calcul the mask position with numpy : 0.00561833381652832 nb_pixel_total : 1252 time to create 1 rle with old method : 0.0013506412506103516 time for calcul the mask position with numpy : 0.0056111812591552734 nb_pixel_total : 312 time to create 1 rle with old method : 0.0004017353057861328 time for calcul the mask position with numpy : 0.005578517913818359 nb_pixel_total : 101 time to create 1 rle with old method : 0.00013065338134765625 time for calcul the mask position with numpy : 0.0057065486907958984 nb_pixel_total : 136 time to create 1 rle with old method : 0.00019073486328125 time for calcul the mask position with numpy : 0.005923271179199219 nb_pixel_total : 233 time to create 1 rle with old method : 0.0002987384796142578 time for calcul the mask position with numpy : 0.00677490234375 nb_pixel_total : 106625 time to create 1 rle with old method : 0.11050009727478027 time for calcul the mask position with numpy : 0.006518840789794922 nb_pixel_total : 427 time to create 1 rle with old method : 0.0004684925079345703 time for calcul the mask position with numpy : 0.005776643753051758 nb_pixel_total : 2986 time to create 1 rle with old method : 0.003272533416748047 time for calcul the mask position with numpy : 0.0058383941650390625 nb_pixel_total : 179 time to create 1 rle with old method : 0.00020766258239746094 time for calcul the mask position with numpy : 0.006253957748413086 nb_pixel_total : 115 time to create 1 rle with old method : 0.00016021728515625 time for calcul the mask position with numpy : 0.006091117858886719 nb_pixel_total : 14 time to create 1 rle with old method : 3.933906555175781e-05 time for calcul the mask position with numpy : 0.006494045257568359 nb_pixel_total : 410 time to create 1 rle with old method : 0.0005164146423339844 time for calcul the mask position with numpy : 0.005982160568237305 nb_pixel_total : 398 time to create 1 rle with old method : 0.0004858970642089844 time for calcul the mask position with numpy : 0.006020784378051758 nb_pixel_total : 394 time to create 1 rle with old method : 0.0005004405975341797 time for calcul the mask position with numpy : 0.006096839904785156 nb_pixel_total : 1544 time to create 1 rle with old method : 0.0017490386962890625 time for calcul the mask position with numpy : 0.005949974060058594 nb_pixel_total : 68 time to create 1 rle with old method : 0.00010228157043457031 time for calcul the mask position with numpy : 0.0061190128326416016 nb_pixel_total : 2479 time to create 1 rle with old method : 0.002707242965698242 time for calcul the mask position with numpy : 0.006003856658935547 nb_pixel_total : 157 time to create 1 rle with old method : 0.00019407272338867188 time for calcul the mask position with numpy : 0.005922794342041016 nb_pixel_total : 206 time to create 1 rle with old method : 0.00024318695068359375 time for calcul the mask position with numpy : 0.0061566829681396484 nb_pixel_total : 211 time to create 1 rle with old method : 0.00028705596923828125 time for calcul the mask position with numpy : 0.006024599075317383 nb_pixel_total : 71 time to create 1 rle with old method : 0.0001461505889892578 time for calcul the mask position with numpy : 0.006137847900390625 nb_pixel_total : 90 time to create 1 rle with old method : 0.00022268295288085938 time for calcul the mask position with numpy : 0.0060825347900390625 nb_pixel_total : 7473 time to create 1 rle with old method : 0.008274555206298828 time for calcul the mask position with numpy : 0.005812406539916992 nb_pixel_total : 843 time to create 1 rle with old method : 0.0009877681732177734 time for calcul the mask position with numpy : 0.00596165657043457 nb_pixel_total : 349 time to create 1 rle with old method : 0.0004296302795410156 time for calcul the mask position with numpy : 0.006000041961669922 nb_pixel_total : 452 time to create 1 rle with old method : 0.0005583763122558594 time for calcul the mask position with numpy : 0.006066322326660156 nb_pixel_total : 270 time to create 1 rle with old method : 0.00033664703369140625 time for calcul the mask position with numpy : 0.00597691535949707 nb_pixel_total : 304 time to create 1 rle with old method : 0.000385284423828125 create new chi : 0.8553822040557861 after preparing all the mask , begin to delete the rle from the crop_hashtag_id => VR 28-11-20 : il faut déplacer cela apres le save_crop_hashtag_ids_obj de la ligne 9514 ! we have 0 chi objets contains the rles time to delete rle : 0.0015408992767333984 batch 1 Loaded 99 chid ids of type : 4230 Number RLEs to save : 8911 TO DO : save crop sub photo not yet done ! save time : 2.802963972091675 nb_obj : 88 nb_hashtags : 8 time to prepare the origin masks : 1.7600042819976807 time for calcul the mask position with numpy : 0.10707640647888184 nb_pixel_total : 1873563 time to create 1 rle with new method : 0.09827232360839844 time for calcul the mask position with numpy : 0.005953550338745117 nb_pixel_total : 698 time to create 1 rle with old method : 0.0008192062377929688 time for calcul the mask position with numpy : 0.005749702453613281 nb_pixel_total : 949 time to create 1 rle with old method : 0.0010554790496826172 time for calcul the mask position with numpy : 0.005597352981567383 nb_pixel_total : 248 time to create 1 rle with old method : 0.00031876564025878906 time for calcul the mask position with numpy : 0.005601644515991211 nb_pixel_total : 6 time to create 1 rle with old method : 2.9087066650390625e-05 time for calcul the mask position with numpy : 0.005658149719238281 nb_pixel_total : 331 time to create 1 rle with old method : 0.0003733634948730469 time for calcul the mask position with numpy : 0.0057179927825927734 nb_pixel_total : 95 time to create 1 rle with old method : 0.0001537799835205078 time for calcul the mask position with numpy : 0.0057048797607421875 nb_pixel_total : 512 time to create 1 rle with old method : 0.0005714893341064453 time for calcul the mask position with numpy : 0.00580286979675293 nb_pixel_total : 3173 time to create 1 rle with old method : 0.003470182418823242 time for calcul the mask position with numpy : 0.00570225715637207 nb_pixel_total : 519 time to create 1 rle with old method : 0.0005970001220703125 time for calcul the mask position with numpy : 0.0057032108306884766 nb_pixel_total : 23 time to create 1 rle with old method : 8.082389831542969e-05 time for calcul the mask position with numpy : 0.0056972503662109375 nb_pixel_total : 4129 time to create 1 rle with old method : 0.004806995391845703 time for calcul the mask position with numpy : 0.005781888961791992 nb_pixel_total : 2943 time to create 1 rle with old method : 0.003527402877807617 time for calcul the mask position with numpy : 0.005875587463378906 nb_pixel_total : 263 time to create 1 rle with old method : 0.00030422210693359375 time for calcul the mask position with numpy : 0.00571894645690918 nb_pixel_total : 300 time to create 1 rle with old method : 0.0003669261932373047 time for calcul the mask position with numpy : 0.0057604312896728516 nb_pixel_total : 847 time to create 1 rle with old method : 0.0009760856628417969 time for calcul the mask position with numpy : 0.0057697296142578125 nb_pixel_total : 102 time to create 1 rle with old method : 0.0001277923583984375 time for calcul the mask position with numpy : 0.005895137786865234 nb_pixel_total : 1529 time to create 1 rle with old method : 0.0017256736755371094 time for calcul the mask position with numpy : 0.005821943283081055 nb_pixel_total : 3612 time to create 1 rle with old method : 0.003985881805419922 time for calcul the mask position with numpy : 0.005791902542114258 nb_pixel_total : 96 time to create 1 rle with old method : 0.0001690387725830078 time for calcul the mask position with numpy : 0.005797386169433594 nb_pixel_total : 342 time to create 1 rle with old method : 0.00042057037353515625 time for calcul the mask position with numpy : 0.00582432746887207 nb_pixel_total : 6428 time to create 1 rle with old method : 0.006749629974365234 time for calcul the mask position with numpy : 0.005670070648193359 nb_pixel_total : 396 time to create 1 rle with old method : 0.0004794597625732422 time for calcul the mask position with numpy : 0.005821704864501953 nb_pixel_total : 6913 time to create 1 rle with old method : 0.007284402847290039 time for calcul the mask position with numpy : 0.0056836605072021484 nb_pixel_total : 214 time to create 1 rle with old method : 0.00025725364685058594 time for calcul the mask position with numpy : 0.005663871765136719 nb_pixel_total : 513 time to create 1 rle with old method : 0.0005624294281005859 time for calcul the mask position with numpy : 0.005807638168334961 nb_pixel_total : 95 time to create 1 rle with old method : 0.00012493133544921875 time for calcul the mask position with numpy : 0.005648374557495117 nb_pixel_total : 2182 time to create 1 rle with old method : 0.0025327205657958984 time for calcul the mask position with numpy : 0.00574040412902832 nb_pixel_total : 641 time to create 1 rle with old method : 0.0008070468902587891 time for calcul the mask position with numpy : 0.0059850215911865234 nb_pixel_total : 117 time to create 1 rle with old method : 0.0001468658447265625 time for calcul the mask position with numpy : 0.005947589874267578 nb_pixel_total : 1236 time to create 1 rle with old method : 0.0013859272003173828 time for calcul the mask position with numpy : 0.0059773921966552734 nb_pixel_total : 733 time to create 1 rle with old method : 0.0008499622344970703 time for calcul the mask position with numpy : 0.005744218826293945 nb_pixel_total : 2074 time to create 1 rle with old method : 0.002379894256591797 time for calcul the mask position with numpy : 0.005820035934448242 nb_pixel_total : 367 time to create 1 rle with old method : 0.00048160552978515625 time for calcul the mask position with numpy : 0.005755901336669922 nb_pixel_total : 188 time to create 1 rle with old method : 0.00024390220642089844 time for calcul the mask position with numpy : 0.006012678146362305 nb_pixel_total : 999 time to create 1 rle with old method : 0.0011539459228515625 time for calcul the mask position with numpy : 0.005896091461181641 nb_pixel_total : 384 time to create 1 rle with old method : 0.00042247772216796875 time for calcul the mask position with numpy : 0.006045818328857422 nb_pixel_total : 190 time to create 1 rle with old method : 0.00024771690368652344 time for calcul the mask position with numpy : 0.005930900573730469 nb_pixel_total : 14371 time to create 1 rle with old method : 0.01545572280883789 time for calcul the mask position with numpy : 0.005964040756225586 nb_pixel_total : 20 time to create 1 rle with old method : 0.000171661376953125 time for calcul the mask position with numpy : 0.006517648696899414 nb_pixel_total : 1050 time to create 1 rle with old method : 0.0017693042755126953 time for calcul the mask position with numpy : 0.006451606750488281 nb_pixel_total : 649 time to create 1 rle with old method : 0.0010478496551513672 time for calcul the mask position with numpy : 0.0064585208892822266 nb_pixel_total : 291 time to create 1 rle with old method : 0.0005297660827636719 time for calcul the mask position with numpy : 0.006518840789794922 nb_pixel_total : 270 time to create 1 rle with old method : 0.0005474090576171875 time for calcul the mask position with numpy : 0.007039546966552734 nb_pixel_total : 1272 time to create 1 rle with old method : 0.0026988983154296875 time for calcul the mask position with numpy : 0.006883144378662109 nb_pixel_total : 1406 time to create 1 rle with old method : 0.002338409423828125 time for calcul the mask position with numpy : 0.006638288497924805 nb_pixel_total : 1075 time to create 1 rle with old method : 0.0017554759979248047 time for calcul the mask position with numpy : 0.00650787353515625 nb_pixel_total : 3330 time to create 1 rle with old method : 0.0053899288177490234 time for calcul the mask position with numpy : 0.0066068172454833984 nb_pixel_total : 6 time to create 1 rle with old method : 4.00543212890625e-05 time for calcul the mask position with numpy : 0.006571531295776367 nb_pixel_total : 144 time to create 1 rle with old method : 0.0002646446228027344 time for calcul the mask position with numpy : 0.006015777587890625 nb_pixel_total : 1730 time to create 1 rle with old method : 0.001967906951904297 time for calcul the mask position with numpy : 0.006157398223876953 nb_pixel_total : 354 time to create 1 rle with old method : 0.0003921985626220703 time for calcul the mask position with numpy : 0.006018877029418945 nb_pixel_total : 558 time to create 1 rle with old method : 0.0006766319274902344 time for calcul the mask position with numpy : 0.005891561508178711 nb_pixel_total : 109 time to create 1 rle with old method : 0.00016880035400390625 time for calcul the mask position with numpy : 0.005880594253540039 nb_pixel_total : 306 time to create 1 rle with old method : 0.0003657341003417969 time for calcul the mask position with numpy : 0.005696773529052734 nb_pixel_total : 164 time to create 1 rle with old method : 0.00025010108947753906 time for calcul the mask position with numpy : 0.0057599544525146484 nb_pixel_total : 45 time to create 1 rle with old method : 8.463859558105469e-05 time for calcul the mask position with numpy : 0.00565791130065918 nb_pixel_total : 546 time to create 1 rle with old method : 0.0006659030914306641 time for calcul the mask position with numpy : 0.005608797073364258 nb_pixel_total : 274 time to create 1 rle with old method : 0.0003120899200439453 time for calcul the mask position with numpy : 0.005540132522583008 nb_pixel_total : 527 time to create 1 rle with old method : 0.0005946159362792969 time for calcul the mask position with numpy : 0.0055179595947265625 nb_pixel_total : 651 time to create 1 rle with old method : 0.0007479190826416016 time for calcul the mask position with numpy : 0.0055615901947021484 nb_pixel_total : 2 time to create 1 rle with old method : 2.5510787963867188e-05 time for calcul the mask position with numpy : 0.005604743957519531 nb_pixel_total : 50 time to create 1 rle with old method : 7.510185241699219e-05 time for calcul the mask position with numpy : 0.0057468414306640625 nb_pixel_total : 1178 time to create 1 rle with old method : 0.001432180404663086 time for calcul the mask position with numpy : 0.005881786346435547 nb_pixel_total : 371 time to create 1 rle with old method : 0.00041985511779785156 time for calcul the mask position with numpy : 0.0058901309967041016 nb_pixel_total : 113 time to create 1 rle with old method : 0.00015878677368164062 time for calcul the mask position with numpy : 0.006076812744140625 nb_pixel_total : 189 time to create 1 rle with old method : 0.00022983551025390625 time for calcul the mask position with numpy : 0.005888223648071289 nb_pixel_total : 206 time to create 1 rle with old method : 0.00024390220642089844 time for calcul the mask position with numpy : 0.00797724723815918 nb_pixel_total : 254 time to create 1 rle with old method : 0.00030350685119628906 time for calcul the mask position with numpy : 0.008194684982299805 nb_pixel_total : 105841 time to create 1 rle with old method : 0.11004447937011719 time for calcul the mask position with numpy : 0.00822758674621582 nb_pixel_total : 214 time to create 1 rle with old method : 0.00023746490478515625 time for calcul the mask position with numpy : 0.008003473281860352 nb_pixel_total : 176 time to create 1 rle with old method : 0.000209808349609375 time for calcul the mask position with numpy : 0.008007049560546875 nb_pixel_total : 3119 time to create 1 rle with old method : 0.0034627914428710938 time for calcul the mask position with numpy : 0.007842302322387695 nb_pixel_total : 2248 time to create 1 rle with old method : 0.0027010440826416016 time for calcul the mask position with numpy : 0.00828409194946289 nb_pixel_total : 48 time to create 1 rle with old method : 6.604194641113281e-05 time for calcul the mask position with numpy : 0.008270502090454102 nb_pixel_total : 57 time to create 1 rle with old method : 8.463859558105469e-05 time for calcul the mask position with numpy : 0.008295774459838867 nb_pixel_total : 401 time to create 1 rle with old method : 0.0004940032958984375 time for calcul the mask position with numpy : 0.008075714111328125 nb_pixel_total : 8 time to create 1 rle with old method : 3.743171691894531e-05 time for calcul the mask position with numpy : 0.008174419403076172 nb_pixel_total : 313 time to create 1 rle with old method : 0.0003631114959716797 time for calcul the mask position with numpy : 0.008114337921142578 nb_pixel_total : 1566 time to create 1 rle with old method : 0.0018799304962158203 time for calcul the mask position with numpy : 0.008311271667480469 nb_pixel_total : 118 time to create 1 rle with old method : 0.0001423358917236328 time for calcul the mask position with numpy : 0.008144378662109375 nb_pixel_total : 163 time to create 1 rle with old method : 0.00019359588623046875 time for calcul the mask position with numpy : 0.007999658584594727 nb_pixel_total : 264 time to create 1 rle with old method : 0.00034356117248535156 time for calcul the mask position with numpy : 0.008314371109008789 nb_pixel_total : 7597 time to create 1 rle with old method : 0.00836944580078125 time for calcul the mask position with numpy : 0.008092164993286133 nb_pixel_total : 363 time to create 1 rle with old method : 0.0004277229309082031 time for calcul the mask position with numpy : 0.00816035270690918 nb_pixel_total : 829 time to create 1 rle with old method : 0.0008726119995117188 time for calcul the mask position with numpy : 0.008449077606201172 nb_pixel_total : 433 time to create 1 rle with old method : 0.0005884170532226562 time for calcul the mask position with numpy : 0.008396148681640625 nb_pixel_total : 308 time to create 1 rle with old method : 0.0003631114959716797 time for calcul the mask position with numpy : 0.008411407470703125 nb_pixel_total : 73 time to create 1 rle with old method : 9.632110595703125e-05 create new chi : 1.0069940090179443 after preparing all the mask , begin to delete the rle from the crop_hashtag_id => VR 28-11-20 : il faut déplacer cela apres le save_crop_hashtag_ids_obj de la ligne 9514 ! we have 0 chi objets contains the rles time to delete rle : 0.0014967918395996094 batch 1 Loaded 94 chid ids of type : 4230 Number RLEs to save : 9160 TO DO : save crop sub photo not yet done ! save time : 1.952301025390625 nb_obj : 100 nb_hashtags : 5 time to prepare the origin masks : 2.5177245140075684 time for calcul the mask position with numpy : 0.9914059638977051 nb_pixel_total : 1665931 time to create 1 rle with new method : 0.07746124267578125 time for calcul the mask position with numpy : 0.006463766098022461 nb_pixel_total : 49367 time to create 1 rle with old method : 0.05028247833251953 time for calcul the mask position with numpy : 0.0058438777923583984 nb_pixel_total : 341 time to create 1 rle with old method : 0.0003838539123535156 time for calcul the mask position with numpy : 0.009297370910644531 nb_pixel_total : 127 time to create 1 rle with old method : 0.00019240379333496094 time for calcul the mask position with numpy : 0.00919485092163086 nb_pixel_total : 1703 time to create 1 rle with old method : 0.001953601837158203 time for calcul the mask position with numpy : 0.009610414505004883 nb_pixel_total : 258 time to create 1 rle with old method : 0.00032067298889160156 time for calcul the mask position with numpy : 0.00950765609741211 nb_pixel_total : 5 time to create 1 rle with old method : 2.6464462280273438e-05 time for calcul the mask position with numpy : 0.008784294128417969 nb_pixel_total : 994 time to create 1 rle with old method : 0.0011415481567382812 time for calcul the mask position with numpy : 0.00825190544128418 nb_pixel_total : 63 time to create 1 rle with old method : 9.608268737792969e-05 time for calcul the mask position with numpy : 0.008667945861816406 nb_pixel_total : 341 time to create 1 rle with old method : 0.0006580352783203125 time for calcul the mask position with numpy : 0.008509159088134766 nb_pixel_total : 12 time to create 1 rle with old method : 5.5789947509765625e-05 time for calcul the mask position with numpy : 0.009412288665771484 nb_pixel_total : 9955 time to create 1 rle with old method : 0.010669946670532227 time for calcul the mask position with numpy : 0.008168220520019531 nb_pixel_total : 4116 time to create 1 rle with old method : 0.00471806526184082 time for calcul the mask position with numpy : 0.008578062057495117 nb_pixel_total : 555 time to create 1 rle with old method : 0.0007135868072509766 time for calcul the mask position with numpy : 0.00995326042175293 nb_pixel_total : 101 time to create 1 rle with old method : 0.0001804828643798828 time for calcul the mask position with numpy : 0.009937047958374023 nb_pixel_total : 38 time to create 1 rle with old method : 0.00010633468627929688 time for calcul the mask position with numpy : 0.009470224380493164 nb_pixel_total : 5 time to create 1 rle with old method : 5.459785461425781e-05 time for calcul the mask position with numpy : 0.008002042770385742 nb_pixel_total : 284 time to create 1 rle with old method : 0.0003600120544433594 time for calcul the mask position with numpy : 0.010838031768798828 nb_pixel_total : 848 time to create 1 rle with old method : 0.00121307373046875 time for calcul the mask position with numpy : 0.00996088981628418 nb_pixel_total : 24 time to create 1 rle with old method : 6.341934204101562e-05 time for calcul the mask position with numpy : 0.010207653045654297 nb_pixel_total : 255 time to create 1 rle with old method : 0.0003108978271484375 time for calcul the mask position with numpy : 0.006231784820556641 nb_pixel_total : 449 time to create 1 rle with old method : 0.0005421638488769531 time for calcul the mask position with numpy : 0.006088733673095703 nb_pixel_total : 12 time to create 1 rle with old method : 4.3392181396484375e-05 time for calcul the mask position with numpy : 0.008892536163330078 nb_pixel_total : 352 time to create 1 rle with old method : 0.00048089027404785156 time for calcul the mask position with numpy : 0.00785207748413086 nb_pixel_total : 858 time to create 1 rle with old method : 0.00104522705078125 time for calcul the mask position with numpy : 0.007980823516845703 nb_pixel_total : 84 time to create 1 rle with old method : 0.00011968612670898438 time for calcul the mask position with numpy : 0.009166717529296875 nb_pixel_total : 3626 time to create 1 rle with old method : 0.004266262054443359 time for calcul the mask position with numpy : 0.008091211318969727 nb_pixel_total : 4263 time to create 1 rle with old method : 0.005126237869262695 time for calcul the mask position with numpy : 0.009507894515991211 nb_pixel_total : 130 time to create 1 rle with old method : 0.00023174285888671875 time for calcul the mask position with numpy : 0.007862091064453125 nb_pixel_total : 420 time to create 1 rle with old method : 0.0005249977111816406 time for calcul the mask position with numpy : 0.009832143783569336 nb_pixel_total : 6573 time to create 1 rle with old method : 0.007211446762084961 time for calcul the mask position with numpy : 0.009894847869873047 nb_pixel_total : 1370 time to create 1 rle with old method : 0.0015943050384521484 time for calcul the mask position with numpy : 0.009678840637207031 nb_pixel_total : 495 time to create 1 rle with old method : 0.0005974769592285156 time for calcul the mask position with numpy : 0.010988473892211914 nb_pixel_total : 152406 time to create 1 rle with new method : 0.06423306465148926 time for calcul the mask position with numpy : 0.009743213653564453 nb_pixel_total : 920 time to create 1 rle with old method : 0.0014922618865966797 time for calcul the mask position with numpy : 0.009966611862182617 nb_pixel_total : 626 time to create 1 rle with old method : 0.0007996559143066406 time for calcul the mask position with numpy : 0.010011672973632812 nb_pixel_total : 2507 time to create 1 rle with old method : 0.0029363632202148438 time for calcul the mask position with numpy : 0.007634639739990234 nb_pixel_total : 818 time to create 1 rle with old method : 0.0009710788726806641 time for calcul the mask position with numpy : 0.006518125534057617 nb_pixel_total : 2372 time to create 1 rle with old method : 0.003086090087890625 time for calcul the mask position with numpy : 0.006315946578979492 nb_pixel_total : 35 time to create 1 rle with old method : 0.0001327991485595703 time for calcul the mask position with numpy : 0.006642580032348633 nb_pixel_total : 1246 time to create 1 rle with old method : 0.001470327377319336 time for calcul the mask position with numpy : 0.009805440902709961 nb_pixel_total : 1159 time to create 1 rle with old method : 0.0014035701751708984 time for calcul the mask position with numpy : 0.010087966918945312 nb_pixel_total : 8 time to create 1 rle with old method : 3.695487976074219e-05 time for calcul the mask position with numpy : 0.0070683956146240234 nb_pixel_total : 11557 time to create 1 rle with old method : 0.01396036148071289 time for calcul the mask position with numpy : 0.008165359497070312 nb_pixel_total : 169 time to create 1 rle with old method : 0.00023245811462402344 time for calcul the mask position with numpy : 0.008432388305664062 nb_pixel_total : 1289 time to create 1 rle with old method : 0.0015015602111816406 time for calcul the mask position with numpy : 0.009320974349975586 nb_pixel_total : 788 time to create 1 rle with old method : 0.0009431838989257812 time for calcul the mask position with numpy : 0.007706880569458008 nb_pixel_total : 9 time to create 1 rle with old method : 5.6743621826171875e-05 time for calcul the mask position with numpy : 0.007883787155151367 nb_pixel_total : 517 time to create 1 rle with old method : 0.0006644725799560547 time for calcul the mask position with numpy : 0.008449077606201172 nb_pixel_total : 800 time to create 1 rle with old method : 0.0009148120880126953 time for calcul the mask position with numpy : 0.006665468215942383 nb_pixel_total : 3367 time to create 1 rle with old method : 0.003712892532348633 time for calcul the mask position with numpy : 0.007992029190063477 nb_pixel_total : 53 time to create 1 rle with old method : 0.00016021728515625 time for calcul the mask position with numpy : 0.009241819381713867 nb_pixel_total : 2539 time to create 1 rle with old method : 0.003160238265991211 time for calcul the mask position with numpy : 0.009084701538085938 nb_pixel_total : 1205 time to create 1 rle with old method : 0.0014078617095947266 time for calcul the mask position with numpy : 0.007729053497314453 nb_pixel_total : 80 time to create 1 rle with old method : 0.0001628398895263672 time for calcul the mask position with numpy : 0.00828409194946289 nb_pixel_total : 47 time to create 1 rle with old method : 0.00011992454528808594 time for calcul the mask position with numpy : 0.007857084274291992 nb_pixel_total : 1695 time to create 1 rle with old method : 0.00202178955078125 time for calcul the mask position with numpy : 0.009425163269042969 nb_pixel_total : 9 time to create 1 rle with old method : 6.270408630371094e-05 time for calcul the mask position with numpy : 0.005948781967163086 nb_pixel_total : 547 time to create 1 rle with old method : 0.0006282329559326172 time for calcul the mask position with numpy : 0.006294727325439453 nb_pixel_total : 24 time to create 1 rle with old method : 7.987022399902344e-05 time for calcul the mask position with numpy : 0.007300138473510742 nb_pixel_total : 161 time to create 1 rle with old method : 0.00021386146545410156 time for calcul the mask position with numpy : 0.005933046340942383 nb_pixel_total : 262 time to create 1 rle with old method : 0.00031304359436035156 time for calcul the mask position with numpy : 0.006242513656616211 nb_pixel_total : 598 time to create 1 rle with old method : 0.0007116794586181641 time for calcul the mask position with numpy : 0.0063018798828125 nb_pixel_total : 181 time to create 1 rle with old method : 0.00023698806762695312 time for calcul the mask position with numpy : 0.0061953067779541016 nb_pixel_total : 501 time to create 1 rle with old method : 0.0005433559417724609 time for calcul the mask position with numpy : 0.0062372684478759766 nb_pixel_total : 4 time to create 1 rle with old method : 7.987022399902344e-05 time for calcul the mask position with numpy : 0.0060710906982421875 nb_pixel_total : 55 time to create 1 rle with old method : 8.296966552734375e-05 time for calcul the mask position with numpy : 0.00619816780090332 nb_pixel_total : 1239 time to create 1 rle with old method : 0.0013227462768554688 time for calcul the mask position with numpy : 0.005982637405395508 nb_pixel_total : 265 time to create 1 rle with old method : 0.00033473968505859375 time for calcul the mask position with numpy : 0.005839824676513672 nb_pixel_total : 24 time to create 1 rle with old method : 6.699562072753906e-05 time for calcul the mask position with numpy : 0.0060269832611083984 nb_pixel_total : 447 time to create 1 rle with old method : 0.0006151199340820312 time for calcul the mask position with numpy : 0.0064775943756103516 nb_pixel_total : 298 time to create 1 rle with old method : 0.0003886222839355469 time for calcul the mask position with numpy : 0.006199359893798828 nb_pixel_total : 84 time to create 1 rle with old method : 0.000125885009765625 time for calcul the mask position with numpy : 0.00988912582397461 nb_pixel_total : 203 time to create 1 rle with old method : 0.0002541542053222656 time for calcul the mask position with numpy : 0.009603738784790039 nb_pixel_total : 200 time to create 1 rle with old method : 0.000278472900390625 time for calcul the mask position with numpy : 0.009659528732299805 nb_pixel_total : 202 time to create 1 rle with old method : 0.0002689361572265625 time for calcul the mask position with numpy : 0.010132789611816406 nb_pixel_total : 247 time to create 1 rle with old method : 0.0003294944763183594 time for calcul the mask position with numpy : 0.012658119201660156 nb_pixel_total : 106267 time to create 1 rle with old method : 0.11022019386291504 time for calcul the mask position with numpy : 0.009691953659057617 nb_pixel_total : 3322 time to create 1 rle with old method : 0.0038080215454101562 time for calcul the mask position with numpy : 0.007147789001464844 nb_pixel_total : 226 time to create 1 rle with old method : 0.0003190040588378906 time for calcul the mask position with numpy : 0.006255626678466797 nb_pixel_total : 198 time to create 1 rle with old method : 0.0002346038818359375 time for calcul the mask position with numpy : 0.006482124328613281 nb_pixel_total : 282 time to create 1 rle with old method : 0.0003726482391357422 time for calcul the mask position with numpy : 0.0062100887298583984 nb_pixel_total : 245 time to create 1 rle with old method : 0.0002987384796142578 time for calcul the mask position with numpy : 0.005759000778198242 nb_pixel_total : 116 time to create 1 rle with old method : 0.0001468658447265625 time for calcul the mask position with numpy : 0.005841255187988281 nb_pixel_total : 54 time to create 1 rle with old method : 8.487701416015625e-05 time for calcul the mask position with numpy : 0.006210803985595703 nb_pixel_total : 610 time to create 1 rle with old method : 0.0007183551788330078 time for calcul the mask position with numpy : 0.0064280033111572266 nb_pixel_total : 378 time to create 1 rle with old method : 0.00047516822814941406 time for calcul the mask position with numpy : 0.006295680999755859 nb_pixel_total : 397 time to create 1 rle with old method : 0.0004954338073730469 time for calcul the mask position with numpy : 0.006401538848876953 nb_pixel_total : 1621 time to create 1 rle with old method : 0.0018606185913085938 time for calcul the mask position with numpy : 0.005926847457885742 nb_pixel_total : 2552 time to create 1 rle with old method : 0.0026204586029052734 time for calcul the mask position with numpy : 0.005950927734375 nb_pixel_total : 141 time to create 1 rle with old method : 0.00017571449279785156 time for calcul the mask position with numpy : 0.0058481693267822266 nb_pixel_total : 194 time to create 1 rle with old method : 0.00022721290588378906 time for calcul the mask position with numpy : 0.007740497589111328 nb_pixel_total : 309 time to create 1 rle with old method : 0.0003268718719482422 time for calcul the mask position with numpy : 0.0077266693115234375 nb_pixel_total : 7308 time to create 1 rle with old method : 0.0075054168701171875 time for calcul the mask position with numpy : 0.007684230804443359 nb_pixel_total : 1545 time to create 1 rle with old method : 0.0016412734985351562 time for calcul the mask position with numpy : 0.007892847061157227 nb_pixel_total : 370 time to create 1 rle with old method : 0.00040459632873535156 time for calcul the mask position with numpy : 0.010600805282592773 nb_pixel_total : 945 time to create 1 rle with old method : 0.0010194778442382812 time for calcul the mask position with numpy : 0.00760650634765625 nb_pixel_total : 14 time to create 1 rle with old method : 3.886222839355469e-05 time for calcul the mask position with numpy : 0.007714509963989258 nb_pixel_total : 56 time to create 1 rle with old method : 8.511543273925781e-05 time for calcul the mask position with numpy : 0.0076906681060791016 nb_pixel_total : 421 time to create 1 rle with old method : 0.00047850608825683594 time for calcul the mask position with numpy : 0.007689237594604492 nb_pixel_total : 311 time to create 1 rle with old method : 0.00033164024353027344 create new chi : 2.221059560775757 after preparing all the mask , begin to delete the rle from the crop_hashtag_id => VR 28-11-20 : il faut déplacer cela apres le save_crop_hashtag_ids_obj de la ligne 9514 ! we have 0 chi objets contains the rles time to delete rle : 0.0018093585968017578 batch 1 Loaded 113 chid ids of type : 4230 Number RLEs to save : 10789 TO DO : save crop sub photo not yet done ! save time : 1.1311354637145996 nb_obj : 96 nb_hashtags : 8 time to prepare the origin masks : 2.1544148921966553 time for calcul the mask position with numpy : 0.020186185836791992 nb_pixel_total : 1622661 time to create 1 rle with new method : 0.16212844848632812 time for calcul the mask position with numpy : 0.00644373893737793 nb_pixel_total : 330 time to create 1 rle with old method : 0.0006222724914550781 time for calcul the mask position with numpy : 0.006552934646606445 nb_pixel_total : 999 time to create 1 rle with old method : 0.0012428760528564453 time for calcul the mask position with numpy : 0.006292819976806641 nb_pixel_total : 1813 time to create 1 rle with old method : 0.0022284984588623047 time for calcul the mask position with numpy : 0.006264209747314453 nb_pixel_total : 47852 time to create 1 rle with old method : 0.05091547966003418 time for calcul the mask position with numpy : 0.005908966064453125 nb_pixel_total : 92 time to create 1 rle with old method : 0.00014638900756835938 time for calcul the mask position with numpy : 0.005808591842651367 nb_pixel_total : 303 time to create 1 rle with old method : 0.0006022453308105469 time for calcul the mask position with numpy : 0.005887746810913086 nb_pixel_total : 240 time to create 1 rle with old method : 0.0003192424774169922 time for calcul the mask position with numpy : 0.0059032440185546875 nb_pixel_total : 1985 time to create 1 rle with old method : 0.0024704933166503906 time for calcul the mask position with numpy : 0.006008148193359375 nb_pixel_total : 763 time to create 1 rle with old method : 0.0008814334869384766 time for calcul the mask position with numpy : 0.0060999393463134766 nb_pixel_total : 2024 time to create 1 rle with old method : 0.002252340316772461 time for calcul the mask position with numpy : 0.005925178527832031 nb_pixel_total : 1239 time to create 1 rle with old method : 0.0014586448669433594 time for calcul the mask position with numpy : 0.006034374237060547 nb_pixel_total : 20 time to create 1 rle with old method : 8.296966552734375e-05 time for calcul the mask position with numpy : 0.005961894989013672 nb_pixel_total : 3141 time to create 1 rle with old method : 0.0038754940032958984 time for calcul the mask position with numpy : 0.006334066390991211 nb_pixel_total : 208 time to create 1 rle with old method : 0.0002505779266357422 time for calcul the mask position with numpy : 0.006026268005371094 nb_pixel_total : 466 time to create 1 rle with old method : 0.029161691665649414 time for calcul the mask position with numpy : 0.011252880096435547 nb_pixel_total : 403 time to create 1 rle with old method : 0.0006439685821533203 time for calcul the mask position with numpy : 0.005879878997802734 nb_pixel_total : 90 time to create 1 rle with old method : 0.00011372566223144531 time for calcul the mask position with numpy : 0.005928993225097656 nb_pixel_total : 836 time to create 1 rle with old method : 0.0009999275207519531 time for calcul the mask position with numpy : 0.005741596221923828 nb_pixel_total : 3714 time to create 1 rle with old method : 0.004592180252075195 time for calcul the mask position with numpy : 0.006432771682739258 nb_pixel_total : 6366 time to create 1 rle with old method : 0.00713348388671875 time for calcul the mask position with numpy : 0.007143497467041016 nb_pixel_total : 7665 time to create 1 rle with old method : 0.008637666702270508 time for calcul the mask position with numpy : 0.006430387496948242 nb_pixel_total : 521 time to create 1 rle with old method : 0.0006771087646484375 time for calcul the mask position with numpy : 0.006524562835693359 nb_pixel_total : 3737 time to create 1 rle with old method : 0.0041697025299072266 time for calcul the mask position with numpy : 0.006029605865478516 nb_pixel_total : 491 time to create 1 rle with old method : 0.0005793571472167969 time for calcul the mask position with numpy : 0.0057408809661865234 nb_pixel_total : 36 time to create 1 rle with old method : 0.00010538101196289062 time for calcul the mask position with numpy : 0.006425619125366211 nb_pixel_total : 543 time to create 1 rle with old method : 0.0006084442138671875 time for calcul the mask position with numpy : 0.0066852569580078125 nb_pixel_total : 151020 time to create 1 rle with new method : 0.057419538497924805 time for calcul the mask position with numpy : 0.006060123443603516 nb_pixel_total : 824 time to create 1 rle with old method : 0.0009143352508544922 time for calcul the mask position with numpy : 0.005889892578125 nb_pixel_total : 3 time to create 1 rle with old method : 3.6716461181640625e-05 time for calcul the mask position with numpy : 0.005894184112548828 nb_pixel_total : 1689 time to create 1 rle with old method : 0.0019745826721191406 time for calcul the mask position with numpy : 0.006407499313354492 nb_pixel_total : 1224 time to create 1 rle with old method : 0.0015361309051513672 time for calcul the mask position with numpy : 0.005877256393432617 nb_pixel_total : 189 time to create 1 rle with old method : 0.0002529621124267578 time for calcul the mask position with numpy : 0.0060083866119384766 nb_pixel_total : 1183 time to create 1 rle with old method : 0.0014488697052001953 time for calcul the mask position with numpy : 0.008821249008178711 nb_pixel_total : 6982 time to create 1 rle with old method : 0.008239030838012695 time for calcul the mask position with numpy : 0.010681867599487305 nb_pixel_total : 169 time to create 1 rle with old method : 0.00023794174194335938 time for calcul the mask position with numpy : 0.010309696197509766 nb_pixel_total : 1208 time to create 1 rle with old method : 0.0015096664428710938 time for calcul the mask position with numpy : 0.00994729995727539 nb_pixel_total : 1259 time to create 1 rle with old method : 0.0015916824340820312 time for calcul the mask position with numpy : 0.010209083557128906 nb_pixel_total : 668 time to create 1 rle with old method : 0.0008308887481689453 time for calcul the mask position with numpy : 0.009882926940917969 nb_pixel_total : 759 time to create 1 rle with old method : 0.0009024143218994141 time for calcul the mask position with numpy : 0.010059833526611328 nb_pixel_total : 792 time to create 1 rle with old method : 0.000986337661743164 time for calcul the mask position with numpy : 0.01043248176574707 nb_pixel_total : 5404 time to create 1 rle with old method : 0.006500959396362305 time for calcul the mask position with numpy : 0.009961366653442383 nb_pixel_total : 3168 time to create 1 rle with old method : 0.00347900390625 time for calcul the mask position with numpy : 0.009981632232666016 nb_pixel_total : 166 time to create 1 rle with old method : 0.00020241737365722656 time for calcul the mask position with numpy : 0.009705066680908203 nb_pixel_total : 640 time to create 1 rle with old method : 0.0007672309875488281 time for calcul the mask position with numpy : 0.009700536727905273 nb_pixel_total : 1503 time to create 1 rle with old method : 0.0017185211181640625 time for calcul the mask position with numpy : 0.009786605834960938 nb_pixel_total : 8 time to create 1 rle with old method : 5.6743621826171875e-05 time for calcul the mask position with numpy : 0.009650230407714844 nb_pixel_total : 31 time to create 1 rle with old method : 8.654594421386719e-05 time for calcul the mask position with numpy : 0.009994983673095703 nb_pixel_total : 1483 time to create 1 rle with old method : 0.0016932487487792969 time for calcul the mask position with numpy : 0.006012678146362305 nb_pixel_total : 711 time to create 1 rle with old method : 0.0008556842803955078 time for calcul the mask position with numpy : 0.005905866622924805 nb_pixel_total : 477 time to create 1 rle with old method : 0.0005743503570556641 time for calcul the mask position with numpy : 0.005825042724609375 nb_pixel_total : 268 time to create 1 rle with old method : 0.000324249267578125 time for calcul the mask position with numpy : 0.0058443546295166016 nb_pixel_total : 169 time to create 1 rle with old method : 0.0002155303955078125 time for calcul the mask position with numpy : 0.006175518035888672 nb_pixel_total : 549 time to create 1 rle with old method : 0.0006663799285888672 time for calcul the mask position with numpy : 0.005879640579223633 nb_pixel_total : 207 time to create 1 rle with old method : 0.00027561187744140625 time for calcul the mask position with numpy : 0.005974292755126953 nb_pixel_total : 535 time to create 1 rle with old method : 0.0006110668182373047 time for calcul the mask position with numpy : 0.005728960037231445 nb_pixel_total : 329 time to create 1 rle with old method : 0.00041484832763671875 time for calcul the mask position with numpy : 0.006044864654541016 nb_pixel_total : 35 time to create 1 rle with old method : 6.508827209472656e-05 time for calcul the mask position with numpy : 0.005868196487426758 nb_pixel_total : 53 time to create 1 rle with old method : 8.797645568847656e-05 time for calcul the mask position with numpy : 0.005741119384765625 nb_pixel_total : 1265 time to create 1 rle with old method : 0.0013484954833984375 time for calcul the mask position with numpy : 0.005795478820800781 nb_pixel_total : 357 time to create 1 rle with old method : 0.0004494190216064453 time for calcul the mask position with numpy : 0.005899906158447266 nb_pixel_total : 435 time to create 1 rle with old method : 0.0005133152008056641 time for calcul the mask position with numpy : 0.005835533142089844 nb_pixel_total : 348 time to create 1 rle with old method : 0.0004134178161621094 time for calcul the mask position with numpy : 0.005823612213134766 nb_pixel_total : 48 time to create 1 rle with old method : 0.00014781951904296875 time for calcul the mask position with numpy : 0.005773305892944336 nb_pixel_total : 104 time to create 1 rle with old method : 0.00015425682067871094 time for calcul the mask position with numpy : 0.005765199661254883 nb_pixel_total : 80 time to create 1 rle with old method : 0.00011014938354492188 time for calcul the mask position with numpy : 0.00583195686340332 nb_pixel_total : 113 time to create 1 rle with old method : 0.0001513957977294922 time for calcul the mask position with numpy : 0.005743741989135742 nb_pixel_total : 258 time to create 1 rle with old method : 0.00030541419982910156 time for calcul the mask position with numpy : 0.00626373291015625 nb_pixel_total : 105864 time to create 1 rle with old method : 0.10998940467834473 time for calcul the mask position with numpy : 0.0061070919036865234 nb_pixel_total : 43681 time to create 1 rle with old method : 0.04588198661804199 time for calcul the mask position with numpy : 0.00629878044128418 nb_pixel_total : 796 time to create 1 rle with old method : 0.0009534358978271484 time for calcul the mask position with numpy : 0.006194591522216797 nb_pixel_total : 216 time to create 1 rle with old method : 0.0002803802490234375 time for calcul the mask position with numpy : 0.006251811981201172 nb_pixel_total : 2013 time to create 1 rle with old method : 0.0025000572204589844 time for calcul the mask position with numpy : 0.00632786750793457 nb_pixel_total : 1183 time to create 1 rle with old method : 0.0015063285827636719 time for calcul the mask position with numpy : 0.00634002685546875 nb_pixel_total : 267 time to create 1 rle with old method : 0.00040650367736816406 time for calcul the mask position with numpy : 0.006021022796630859 nb_pixel_total : 44 time to create 1 rle with old method : 8.225440979003906e-05 time for calcul the mask position with numpy : 0.006022453308105469 nb_pixel_total : 648 time to create 1 rle with old method : 0.0008635520935058594 time for calcul the mask position with numpy : 0.012614250183105469 nb_pixel_total : 613 time to create 1 rle with old method : 0.0007867813110351562 time for calcul the mask position with numpy : 0.006964921951293945 nb_pixel_total : 378 time to create 1 rle with old method : 0.00047588348388671875 time for calcul the mask position with numpy : 0.006268739700317383 nb_pixel_total : 261 time to create 1 rle with old method : 0.0004570484161376953 time for calcul the mask position with numpy : 0.00659489631652832 nb_pixel_total : 441 time to create 1 rle with old method : 0.0005273818969726562 time for calcul the mask position with numpy : 0.005989551544189453 nb_pixel_total : 1514 time to create 1 rle with old method : 0.0017251968383789062 time for calcul the mask position with numpy : 0.0060083866119384766 nb_pixel_total : 1040 time to create 1 rle with old method : 0.001161336898803711 time for calcul the mask position with numpy : 0.00589299201965332 nb_pixel_total : 127 time to create 1 rle with old method : 0.00016307830810546875 time for calcul the mask position with numpy : 0.005685091018676758 nb_pixel_total : 8691 time to create 1 rle with old method : 0.009126424789428711 time for calcul the mask position with numpy : 0.005975961685180664 nb_pixel_total : 137 time to create 1 rle with old method : 0.00018095970153808594 time for calcul the mask position with numpy : 0.006351470947265625 nb_pixel_total : 172 time to create 1 rle with old method : 0.00021028518676757812 time for calcul the mask position with numpy : 0.005835533142089844 nb_pixel_total : 105 time to create 1 rle with old method : 0.0001971721649169922 time for calcul the mask position with numpy : 0.005970478057861328 nb_pixel_total : 580 time to create 1 rle with old method : 0.0006721019744873047 time for calcul the mask position with numpy : 0.006065845489501953 nb_pixel_total : 12 time to create 1 rle with old method : 3.075599670410156e-05 time for calcul the mask position with numpy : 0.0058705806732177734 nb_pixel_total : 7479 time to create 1 rle with old method : 0.007842302322387695 time for calcul the mask position with numpy : 0.005734443664550781 nb_pixel_total : 844 time to create 1 rle with old method : 0.0009112358093261719 time for calcul the mask position with numpy : 0.00569462776184082 nb_pixel_total : 317 time to create 1 rle with old method : 0.0003552436828613281 time for calcul the mask position with numpy : 0.006346464157104492 nb_pixel_total : 44 time to create 1 rle with old method : 9.250640869140625e-05 time for calcul the mask position with numpy : 0.0057141780853271484 nb_pixel_total : 302 time to create 1 rle with old method : 0.000408172607421875 time for calcul the mask position with numpy : 0.005767822265625 nb_pixel_total : 274 time to create 1 rle with old method : 0.00028967857360839844 time for calcul the mask position with numpy : 0.0057370662689208984 nb_pixel_total : 306 time to create 1 rle with old method : 0.0003566741943359375 create new chi : 1.2570674419403076 after preparing all the mask , begin to delete the rle from the crop_hashtag_id => VR 28-11-20 : il faut déplacer cela apres le save_crop_hashtag_ids_obj de la ligne 9514 ! we have 0 chi objets contains the rles time to delete rle : 0.002070903778076172 batch 1 Loaded 108 chid ids of type : 4230 Number RLEs to save : 11977 TO DO : save crop sub photo not yet done ! save time : 0.6623494625091553 nb_obj : 91 nb_hashtags : 6 time to prepare the origin masks : 2.44179368019104 time for calcul the mask position with numpy : 0.16732525825500488 nb_pixel_total : 1664397 time to create 1 rle with new method : 0.08632588386535645 time for calcul the mask position with numpy : 0.009986639022827148 nb_pixel_total : 890 time to create 1 rle with old method : 0.0010941028594970703 time for calcul the mask position with numpy : 0.009985685348510742 nb_pixel_total : 1 time to create 1 rle with old method : 2.3603439331054688e-05 time for calcul the mask position with numpy : 0.009444713592529297 nb_pixel_total : 154 time to create 1 rle with old method : 0.0002532005310058594 time for calcul the mask position with numpy : 0.009845972061157227 nb_pixel_total : 580 time to create 1 rle with old method : 0.0006954669952392578 time for calcul the mask position with numpy : 0.009763717651367188 nb_pixel_total : 54 time to create 1 rle with old method : 0.00011014938354492188 time for calcul the mask position with numpy : 0.01000833511352539 nb_pixel_total : 262 time to create 1 rle with old method : 0.000331878662109375 time for calcul the mask position with numpy : 0.010059356689453125 nb_pixel_total : 47826 time to create 1 rle with old method : 0.05042886734008789 time for calcul the mask position with numpy : 0.010076761245727539 nb_pixel_total : 185 time to create 1 rle with old method : 0.00024771690368652344 time for calcul the mask position with numpy : 0.009555339813232422 nb_pixel_total : 3712 time to create 1 rle with old method : 0.003987312316894531 time for calcul the mask position with numpy : 0.012983322143554688 nb_pixel_total : 748 time to create 1 rle with old method : 0.0009179115295410156 time for calcul the mask position with numpy : 0.009779691696166992 nb_pixel_total : 2819 time to create 1 rle with old method : 0.0034210681915283203 time for calcul the mask position with numpy : 0.00940084457397461 nb_pixel_total : 273 time to create 1 rle with old method : 0.00034928321838378906 time for calcul the mask position with numpy : 0.009835481643676758 nb_pixel_total : 395 time to create 1 rle with old method : 0.0004525184631347656 time for calcul the mask position with numpy : 0.00954890251159668 nb_pixel_total : 981 time to create 1 rle with old method : 0.0011584758758544922 time for calcul the mask position with numpy : 0.009738683700561523 nb_pixel_total : 345 time to create 1 rle with old method : 0.00043845176696777344 time for calcul the mask position with numpy : 0.009970903396606445 nb_pixel_total : 3769 time to create 1 rle with old method : 0.0041332244873046875 time for calcul the mask position with numpy : 0.010054588317871094 nb_pixel_total : 415 time to create 1 rle with old method : 0.0005354881286621094 time for calcul the mask position with numpy : 0.01011347770690918 nb_pixel_total : 86 time to create 1 rle with old method : 0.000141143798828125 time for calcul the mask position with numpy : 0.009791135787963867 nb_pixel_total : 6762 time to create 1 rle with old method : 0.007458686828613281 time for calcul the mask position with numpy : 0.010747671127319336 nb_pixel_total : 561 time to create 1 rle with old method : 0.0007565021514892578 time for calcul the mask position with numpy : 0.010458946228027344 nb_pixel_total : 523 time to create 1 rle with old method : 0.0006439685821533203 time for calcul the mask position with numpy : 0.009974479675292969 nb_pixel_total : 228 time to create 1 rle with old method : 0.0002892017364501953 time for calcul the mask position with numpy : 0.010751962661743164 nb_pixel_total : 149111 time to create 1 rle with old method : 0.18888306617736816 time for calcul the mask position with numpy : 0.012453794479370117 nb_pixel_total : 2565 time to create 1 rle with old method : 0.004960775375366211 time for calcul the mask position with numpy : 0.02019977569580078 nb_pixel_total : 54 time to create 1 rle with old method : 0.00017690658569335938 time for calcul the mask position with numpy : 0.016415119171142578 nb_pixel_total : 3822 time to create 1 rle with old method : 0.007696866989135742 time for calcul the mask position with numpy : 0.012650251388549805 nb_pixel_total : 1753 time to create 1 rle with old method : 0.0028586387634277344 time for calcul the mask position with numpy : 0.011636972427368164 nb_pixel_total : 108 time to create 1 rle with old method : 0.00020694732666015625 time for calcul the mask position with numpy : 0.01147913932800293 nb_pixel_total : 64 time to create 1 rle with old method : 0.0001537799835205078 time for calcul the mask position with numpy : 0.011713504791259766 nb_pixel_total : 757 time to create 1 rle with old method : 0.00127410888671875 time for calcul the mask position with numpy : 0.012298583984375 nb_pixel_total : 1690 time to create 1 rle with old method : 0.0031180381774902344 time for calcul the mask position with numpy : 0.013285636901855469 nb_pixel_total : 995 time to create 1 rle with old method : 0.0018286705017089844 time for calcul the mask position with numpy : 0.013628482818603516 nb_pixel_total : 13467 time to create 1 rle with old method : 0.023884296417236328 time for calcul the mask position with numpy : 0.012935638427734375 nb_pixel_total : 384 time to create 1 rle with old method : 0.0008182525634765625 time for calcul the mask position with numpy : 0.014275789260864258 nb_pixel_total : 178 time to create 1 rle with old method : 0.0005910396575927734 time for calcul the mask position with numpy : 0.01437687873840332 nb_pixel_total : 1290 time to create 1 rle with old method : 0.002507925033569336 time for calcul the mask position with numpy : 0.01583695411682129 nb_pixel_total : 1043 time to create 1 rle with old method : 0.0019636154174804688 time for calcul the mask position with numpy : 0.01518106460571289 nb_pixel_total : 40 time to create 1 rle with old method : 0.00015783309936523438 time for calcul the mask position with numpy : 0.015772104263305664 nb_pixel_total : 4168 time to create 1 rle with old method : 0.007988214492797852 time for calcul the mask position with numpy : 0.015150070190429688 nb_pixel_total : 1006 time to create 1 rle with old method : 0.001809835433959961 time for calcul the mask position with numpy : 0.014777660369873047 nb_pixel_total : 3376 time to create 1 rle with old method : 0.006443977355957031 time for calcul the mask position with numpy : 0.01505422592163086 nb_pixel_total : 202 time to create 1 rle with old method : 0.0004131793975830078 time for calcul the mask position with numpy : 0.014408588409423828 nb_pixel_total : 401 time to create 1 rle with old method : 0.0008401870727539062 time for calcul the mask position with numpy : 0.014313697814941406 nb_pixel_total : 21653 time to create 1 rle with old method : 0.04092550277709961 time for calcul the mask position with numpy : 0.014421701431274414 nb_pixel_total : 1656 time to create 1 rle with old method : 0.003227710723876953 time for calcul the mask position with numpy : 0.014792919158935547 nb_pixel_total : 4 time to create 1 rle with old method : 0.00011563301086425781 time for calcul the mask position with numpy : 0.012546777725219727 nb_pixel_total : 454 time to create 1 rle with old method : 0.0009832382202148438 time for calcul the mask position with numpy : 0.011606931686401367 nb_pixel_total : 304 time to create 1 rle with old method : 0.002128124237060547 time for calcul the mask position with numpy : 0.01857471466064453 nb_pixel_total : 184 time to create 1 rle with old method : 0.00035643577575683594 time for calcul the mask position with numpy : 0.015241622924804688 nb_pixel_total : 336 time to create 1 rle with old method : 0.0006589889526367188 time for calcul the mask position with numpy : 0.014989137649536133 nb_pixel_total : 547 time to create 1 rle with old method : 0.0010547637939453125 time for calcul the mask position with numpy : 0.014559030532836914 nb_pixel_total : 34 time to create 1 rle with old method : 0.00010585784912109375 time for calcul the mask position with numpy : 0.014328241348266602 nb_pixel_total : 10 time to create 1 rle with old method : 8.654594421386719e-05 time for calcul the mask position with numpy : 0.014498710632324219 nb_pixel_total : 64 time to create 1 rle with old method : 0.00015616416931152344 time for calcul the mask position with numpy : 0.023946046829223633 nb_pixel_total : 1439 time to create 1 rle with old method : 0.002827882766723633 time for calcul the mask position with numpy : 0.015267133712768555 nb_pixel_total : 10 time to create 1 rle with old method : 9.226799011230469e-05 time for calcul the mask position with numpy : 0.015126943588256836 nb_pixel_total : 520 time to create 1 rle with old method : 0.0010344982147216797 time for calcul the mask position with numpy : 0.014676809310913086 nb_pixel_total : 485 time to create 1 rle with old method : 0.000993967056274414 time for calcul the mask position with numpy : 0.014416694641113281 nb_pixel_total : 11 time to create 1 rle with old method : 8.440017700195312e-05 time for calcul the mask position with numpy : 0.014244318008422852 nb_pixel_total : 99 time to create 1 rle with old method : 0.00015592575073242188 time for calcul the mask position with numpy : 0.011984586715698242 nb_pixel_total : 176 time to create 1 rle with old method : 0.00024271011352539062 time for calcul the mask position with numpy : 0.012681245803833008 nb_pixel_total : 179 time to create 1 rle with old method : 0.0003542900085449219 time for calcul the mask position with numpy : 0.014149665832519531 nb_pixel_total : 233 time to create 1 rle with old method : 0.00046634674072265625 time for calcul the mask position with numpy : 0.015449762344360352 nb_pixel_total : 106594 time to create 1 rle with old method : 0.1556534767150879 time for calcul the mask position with numpy : 0.011246204376220703 nb_pixel_total : 241 time to create 1 rle with old method : 0.0003299713134765625 time for calcul the mask position with numpy : 0.01099395751953125 nb_pixel_total : 219 time to create 1 rle with old method : 0.00028634071350097656 time for calcul the mask position with numpy : 0.010907649993896484 nb_pixel_total : 161 time to create 1 rle with old method : 0.00023174285888671875 time for calcul the mask position with numpy : 0.01085209846496582 nb_pixel_total : 1680 time to create 1 rle with old method : 0.0019698143005371094 time for calcul the mask position with numpy : 0.011095523834228516 nb_pixel_total : 384 time to create 1 rle with old method : 0.0004820823669433594 time for calcul the mask position with numpy : 0.01073598861694336 nb_pixel_total : 411 time to create 1 rle with old method : 0.0005700588226318359 time for calcul the mask position with numpy : 0.013473272323608398 nb_pixel_total : 3 time to create 1 rle with old method : 5.4836273193359375e-05 time for calcul the mask position with numpy : 0.013907194137573242 nb_pixel_total : 13 time to create 1 rle with old method : 8.96453857421875e-05 time for calcul the mask position with numpy : 0.013309240341186523 nb_pixel_total : 421 time to create 1 rle with old method : 0.0008375644683837891 time for calcul the mask position with numpy : 0.013060808181762695 nb_pixel_total : 1517 time to create 1 rle with old method : 0.0028972625732421875 time for calcul the mask position with numpy : 0.01328277587890625 nb_pixel_total : 4 time to create 1 rle with old method : 3.4332275390625e-05 time for calcul the mask position with numpy : 0.012829780578613281 nb_pixel_total : 3 time to create 1 rle with old method : 3.600120544433594e-05 time for calcul the mask position with numpy : 0.012689590454101562 nb_pixel_total : 196 time to create 1 rle with old method : 0.00041556358337402344 time for calcul the mask position with numpy : 0.012745380401611328 nb_pixel_total : 114 time to create 1 rle with old method : 0.0003542900085449219 time for calcul the mask position with numpy : 0.013262510299682617 nb_pixel_total : 47 time to create 1 rle with old method : 0.0002086162567138672 time for calcul the mask position with numpy : 0.012603282928466797 nb_pixel_total : 189 time to create 1 rle with old method : 0.0003590583801269531 time for calcul the mask position with numpy : 0.013076066970825195 nb_pixel_total : 598 time to create 1 rle with old method : 0.0012180805206298828 time for calcul the mask position with numpy : 0.013064384460449219 nb_pixel_total : 7478 time to create 1 rle with old method : 0.013130664825439453 time for calcul the mask position with numpy : 0.011487960815429688 nb_pixel_total : 34 time to create 1 rle with old method : 0.00015592575073242188 time for calcul the mask position with numpy : 0.01072239875793457 nb_pixel_total : 967 time to create 1 rle with old method : 0.001157999038696289 time for calcul the mask position with numpy : 0.014793872833251953 nb_pixel_total : 329 time to create 1 rle with old method : 0.0004184246063232422 time for calcul the mask position with numpy : 0.010696887969970703 nb_pixel_total : 10 time to create 1 rle with old method : 5.53131103515625e-05 time for calcul the mask position with numpy : 0.010879039764404297 nb_pixel_total : 7 time to create 1 rle with old method : 3.933906555175781e-05 time for calcul the mask position with numpy : 0.01097726821899414 nb_pixel_total : 521 time to create 1 rle with old method : 0.0006585121154785156 time for calcul the mask position with numpy : 0.011542320251464844 nb_pixel_total : 33 time to create 1 rle with old method : 0.000102996826171875 time for calcul the mask position with numpy : 0.011260509490966797 nb_pixel_total : 263 time to create 1 rle with old method : 0.00033211708068847656 time for calcul the mask position with numpy : 0.008592605590820312 nb_pixel_total : 325 time to create 1 rle with old method : 0.00039577484130859375 create new chi : 1.993346929550171 after preparing all the mask , begin to delete the rle from the crop_hashtag_id => VR 28-11-20 : il faut déplacer cela apres le save_crop_hashtag_ids_obj de la ligne 9514 ! we have 0 chi objets contains the rles time to delete rle : 0.0030028820037841797 batch 1 Loaded 100 chid ids of type : 4230 Number RLEs to save : 10245 TO DO : save crop sub photo not yet done ! save time : 0.6203374862670898 nb_obj : 93 nb_hashtags : 6 time to prepare the origin masks : 2.1834359169006348 time for calcul the mask position with numpy : 0.26805639266967773 nb_pixel_total : 1719195 time to create 1 rle with new method : 0.09410691261291504 time for calcul the mask position with numpy : 0.010621309280395508 nb_pixel_total : 132 time to create 1 rle with old method : 0.00020170211791992188 time for calcul the mask position with numpy : 0.00661468505859375 nb_pixel_total : 19 time to create 1 rle with old method : 4.291534423828125e-05 time for calcul the mask position with numpy : 0.006409168243408203 nb_pixel_total : 1010 time to create 1 rle with old method : 0.001199960708618164 time for calcul the mask position with numpy : 0.009968996047973633 nb_pixel_total : 47 time to create 1 rle with old method : 0.00010442733764648438 time for calcul the mask position with numpy : 0.010649919509887695 nb_pixel_total : 75 time to create 1 rle with old method : 0.00013780593872070312 time for calcul the mask position with numpy : 0.01011800765991211 nb_pixel_total : 43 time to create 1 rle with old method : 8.487701416015625e-05 time for calcul the mask position with numpy : 0.009799957275390625 nb_pixel_total : 291 time to create 1 rle with old method : 0.0003261566162109375 time for calcul the mask position with numpy : 0.00993037223815918 nb_pixel_total : 394 time to create 1 rle with old method : 0.0005402565002441406 time for calcul the mask position with numpy : 0.01029062271118164 nb_pixel_total : 282 time to create 1 rle with old method : 0.0005965232849121094 time for calcul the mask position with numpy : 0.011427879333496094 nb_pixel_total : 2076 time to create 1 rle with old method : 0.003373861312866211 time for calcul the mask position with numpy : 0.010878801345825195 nb_pixel_total : 15 time to create 1 rle with old method : 0.00011849403381347656 time for calcul the mask position with numpy : 0.01129293441772461 nb_pixel_total : 3314 time to create 1 rle with old method : 0.005340576171875 time for calcul the mask position with numpy : 0.011343240737915039 nb_pixel_total : 387 time to create 1 rle with old method : 0.000675201416015625 time for calcul the mask position with numpy : 0.011153936386108398 nb_pixel_total : 43 time to create 1 rle with old method : 0.00011873245239257812 time for calcul the mask position with numpy : 0.010711193084716797 nb_pixel_total : 793 time to create 1 rle with old method : 0.0013222694396972656 time for calcul the mask position with numpy : 0.009660482406616211 nb_pixel_total : 86 time to create 1 rle with old method : 0.0001533031463623047 time for calcul the mask position with numpy : 0.009508609771728516 nb_pixel_total : 317 time to create 1 rle with old method : 0.0004241466522216797 time for calcul the mask position with numpy : 0.008699178695678711 nb_pixel_total : 790 time to create 1 rle with old method : 0.0009369850158691406 time for calcul the mask position with numpy : 0.009935855865478516 nb_pixel_total : 2860 time to create 1 rle with old method : 0.003408193588256836 time for calcul the mask position with numpy : 0.009259700775146484 nb_pixel_total : 30 time to create 1 rle with old method : 0.00011396408081054688 time for calcul the mask position with numpy : 0.009807586669921875 nb_pixel_total : 902 time to create 1 rle with old method : 0.0011906623840332031 time for calcul the mask position with numpy : 0.010036706924438477 nb_pixel_total : 2153 time to create 1 rle with old method : 0.002588510513305664 time for calcul the mask position with numpy : 0.01000523567199707 nb_pixel_total : 724 time to create 1 rle with old method : 0.0008647441864013672 time for calcul the mask position with numpy : 0.009853601455688477 nb_pixel_total : 6555 time to create 1 rle with old method : 0.007581949234008789 time for calcul the mask position with numpy : 0.009766101837158203 nb_pixel_total : 5627 time to create 1 rle with old method : 0.00650787353515625 time for calcul the mask position with numpy : 0.011265039443969727 nb_pixel_total : 465 time to create 1 rle with old method : 0.0005702972412109375 time for calcul the mask position with numpy : 0.006109952926635742 nb_pixel_total : 99 time to create 1 rle with old method : 0.0001399517059326172 time for calcul the mask position with numpy : 0.007175445556640625 nb_pixel_total : 151991 time to create 1 rle with new method : 0.22455835342407227 time for calcul the mask position with numpy : 0.0059168338775634766 nb_pixel_total : 4352 time to create 1 rle with old method : 0.0049283504486083984 time for calcul the mask position with numpy : 0.006320953369140625 nb_pixel_total : 141 time to create 1 rle with old method : 0.0003132820129394531 time for calcul the mask position with numpy : 0.006709098815917969 nb_pixel_total : 668 time to create 1 rle with old method : 0.0008003711700439453 time for calcul the mask position with numpy : 0.005901813507080078 nb_pixel_total : 264 time to create 1 rle with old method : 0.00035190582275390625 time for calcul the mask position with numpy : 0.005887269973754883 nb_pixel_total : 1849 time to create 1 rle with old method : 0.0021982192993164062 time for calcul the mask position with numpy : 0.005995273590087891 nb_pixel_total : 830 time to create 1 rle with old method : 0.0009403228759765625 time for calcul the mask position with numpy : 0.00589752197265625 nb_pixel_total : 30 time to create 1 rle with old method : 7.43865966796875e-05 time for calcul the mask position with numpy : 0.005945444107055664 nb_pixel_total : 1593 time to create 1 rle with old method : 0.001903533935546875 time for calcul the mask position with numpy : 0.005922079086303711 nb_pixel_total : 1544 time to create 1 rle with old method : 0.0019779205322265625 time for calcul the mask position with numpy : 0.005903959274291992 nb_pixel_total : 321 time to create 1 rle with old method : 0.00037217140197753906 time for calcul the mask position with numpy : 0.005930900573730469 nb_pixel_total : 12035 time to create 1 rle with old method : 0.012675046920776367 time for calcul the mask position with numpy : 0.005918741226196289 nb_pixel_total : 67 time to create 1 rle with old method : 0.00023436546325683594 time for calcul the mask position with numpy : 0.00598907470703125 nb_pixel_total : 1341 time to create 1 rle with old method : 0.0015802383422851562 time for calcul the mask position with numpy : 0.00596308708190918 nb_pixel_total : 2150 time to create 1 rle with old method : 0.0026085376739501953 time for calcul the mask position with numpy : 0.005981922149658203 nb_pixel_total : 992 time to create 1 rle with old method : 0.0011219978332519531 time for calcul the mask position with numpy : 0.006094932556152344 nb_pixel_total : 5328 time to create 1 rle with old method : 0.005769014358520508 time for calcul the mask position with numpy : 0.0059473514556884766 nb_pixel_total : 3007 time to create 1 rle with old method : 0.0036406517028808594 time for calcul the mask position with numpy : 0.005690336227416992 nb_pixel_total : 124 time to create 1 rle with old method : 0.0001571178436279297 time for calcul the mask position with numpy : 0.005877494812011719 nb_pixel_total : 77 time to create 1 rle with old method : 0.00016880035400390625 time for calcul the mask position with numpy : 0.005790233612060547 nb_pixel_total : 437 time to create 1 rle with old method : 0.0005402565002441406 time for calcul the mask position with numpy : 0.005961418151855469 nb_pixel_total : 1581 time to create 1 rle with old method : 0.0018360614776611328 time for calcul the mask position with numpy : 0.00571441650390625 nb_pixel_total : 5 time to create 1 rle with old method : 7.510185241699219e-05 time for calcul the mask position with numpy : 0.00589299201965332 nb_pixel_total : 199 time to create 1 rle with old method : 0.0002503395080566406 time for calcul the mask position with numpy : 0.005688190460205078 nb_pixel_total : 187 time to create 1 rle with old method : 0.00022268295288085938 time for calcul the mask position with numpy : 0.005555152893066406 nb_pixel_total : 285 time to create 1 rle with old method : 0.0003311634063720703 time for calcul the mask position with numpy : 0.005868434906005859 nb_pixel_total : 21 time to create 1 rle with old method : 6.818771362304688e-05 time for calcul the mask position with numpy : 0.00578761100769043 nb_pixel_total : 532 time to create 1 rle with old method : 0.0005981922149658203 time for calcul the mask position with numpy : 0.005706310272216797 nb_pixel_total : 35 time to create 1 rle with old method : 6.580352783203125e-05 time for calcul the mask position with numpy : 0.005538225173950195 nb_pixel_total : 3172 time to create 1 rle with old method : 0.003587961196899414 time for calcul the mask position with numpy : 0.005522966384887695 nb_pixel_total : 76 time to create 1 rle with old method : 0.00010085105895996094 time for calcul the mask position with numpy : 0.0055201053619384766 nb_pixel_total : 62 time to create 1 rle with old method : 0.00015997886657714844 time for calcul the mask position with numpy : 0.005751848220825195 nb_pixel_total : 1252 time to create 1 rle with old method : 0.0013866424560546875 time for calcul the mask position with numpy : 0.0055315494537353516 nb_pixel_total : 20 time to create 1 rle with old method : 4.935264587402344e-05 time for calcul the mask position with numpy : 0.005744218826293945 nb_pixel_total : 462 time to create 1 rle with old method : 0.000537872314453125 time for calcul the mask position with numpy : 0.0054836273193359375 nb_pixel_total : 455 time to create 1 rle with old method : 0.0005404949188232422 time for calcul the mask position with numpy : 0.005497932434082031 nb_pixel_total : 879 time to create 1 rle with old method : 0.001054525375366211 time for calcul the mask position with numpy : 0.00563812255859375 nb_pixel_total : 103 time to create 1 rle with old method : 0.00013256072998046875 time for calcul the mask position with numpy : 0.005664825439453125 nb_pixel_total : 228 time to create 1 rle with old method : 0.0002789497375488281 time for calcul the mask position with numpy : 0.005742311477661133 nb_pixel_total : 275 time to create 1 rle with old method : 0.00033164024353027344 time for calcul the mask position with numpy : 0.00606989860534668 nb_pixel_total : 107083 time to create 1 rle with old method : 0.11458349227905273 time for calcul the mask position with numpy : 0.005779743194580078 nb_pixel_total : 2249 time to create 1 rle with old method : 0.0023975372314453125 time for calcul the mask position with numpy : 0.005602121353149414 nb_pixel_total : 248 time to create 1 rle with old method : 0.0002980232238769531 time for calcul the mask position with numpy : 0.005678892135620117 nb_pixel_total : 155 time to create 1 rle with old method : 0.00019812583923339844 time for calcul the mask position with numpy : 0.005675554275512695 nb_pixel_total : 198 time to create 1 rle with old method : 0.0002505779266357422 time for calcul the mask position with numpy : 0.005501508712768555 nb_pixel_total : 1676 time to create 1 rle with old method : 0.0018279552459716797 time for calcul the mask position with numpy : 0.005473613739013672 nb_pixel_total : 98 time to create 1 rle with old method : 0.000133514404296875 time for calcul the mask position with numpy : 0.005464076995849609 nb_pixel_total : 387 time to create 1 rle with old method : 0.0004303455352783203 time for calcul the mask position with numpy : 0.005527496337890625 nb_pixel_total : 389 time to create 1 rle with old method : 0.0004508495330810547 time for calcul the mask position with numpy : 0.00555109977722168 nb_pixel_total : 1581 time to create 1 rle with old method : 0.0017802715301513672 time for calcul the mask position with numpy : 0.005896091461181641 nb_pixel_total : 213 time to create 1 rle with old method : 0.0002808570861816406 time for calcul the mask position with numpy : 0.00568699836730957 nb_pixel_total : 6 time to create 1 rle with old method : 3.719329833984375e-05 time for calcul the mask position with numpy : 0.0056722164154052734 nb_pixel_total : 48 time to create 1 rle with old method : 9.560585021972656e-05 time for calcul the mask position with numpy : 0.0057790279388427734 nb_pixel_total : 529 time to create 1 rle with old method : 0.0005676746368408203 time for calcul the mask position with numpy : 0.0057239532470703125 nb_pixel_total : 448 time to create 1 rle with old method : 0.0006210803985595703 time for calcul the mask position with numpy : 0.005724906921386719 nb_pixel_total : 152 time to create 1 rle with old method : 0.00019407272338867188 time for calcul the mask position with numpy : 0.005850076675415039 nb_pixel_total : 166 time to create 1 rle with old method : 0.00021719932556152344 time for calcul the mask position with numpy : 0.006102561950683594 nb_pixel_total : 4 time to create 1 rle with old method : 4.863739013671875e-05 time for calcul the mask position with numpy : 0.005995273590087891 nb_pixel_total : 14 time to create 1 rle with old method : 4.291534423828125e-05 time for calcul the mask position with numpy : 0.005964994430541992 nb_pixel_total : 418 time to create 1 rle with old method : 0.0005695819854736328 time for calcul the mask position with numpy : 0.006042003631591797 nb_pixel_total : 565 time to create 1 rle with old method : 0.000614166259765625 time for calcul the mask position with numpy : 0.0061533451080322266 nb_pixel_total : 7503 time to create 1 rle with old method : 0.008478641510009766 time for calcul the mask position with numpy : 0.005840301513671875 nb_pixel_total : 335 time to create 1 rle with old method : 0.0004286766052246094 time for calcul the mask position with numpy : 0.005952358245849609 nb_pixel_total : 194 time to create 1 rle with old method : 0.0002644062042236328 time for calcul the mask position with numpy : 0.007990360260009766 nb_pixel_total : 913 time to create 1 rle with old method : 0.0009868144989013672 time for calcul the mask position with numpy : 0.007936716079711914 nb_pixel_total : 334 time to create 1 rle with old method : 0.00035381317138671875 create new chi : 1.4821672439575195 after preparing all the mask , begin to delete the rle from the crop_hashtag_id => VR 28-11-20 : il faut déplacer cela apres le save_crop_hashtag_ids_obj de la ligne 9514 ! we have 0 chi objets contains the rles time to delete rle : 0.0021512508392333984 batch 1 Loaded 101 chid ids of type : 4230 Number RLEs to save : 10106 TO DO : save crop sub photo not yet done ! save time : 0.5907113552093506 nb_obj : 80 nb_hashtags : 7 time to prepare the origin masks : 1.462083101272583 time for calcul the mask position with numpy : 0.018178462982177734 nb_pixel_total : 1736547 time to create 1 rle with new method : 0.03277277946472168 time for calcul the mask position with numpy : 0.006051063537597656 nb_pixel_total : 783 time to create 1 rle with old method : 0.0009341239929199219 time for calcul the mask position with numpy : 0.005830526351928711 nb_pixel_total : 11 time to create 1 rle with old method : 3.4332275390625e-05 time for calcul the mask position with numpy : 0.005974769592285156 nb_pixel_total : 185 time to create 1 rle with old method : 0.00025463104248046875 time for calcul the mask position with numpy : 0.005896568298339844 nb_pixel_total : 673 time to create 1 rle with old method : 0.0008356571197509766 time for calcul the mask position with numpy : 0.0059130191802978516 nb_pixel_total : 240 time to create 1 rle with old method : 0.00031065940856933594 time for calcul the mask position with numpy : 0.005870819091796875 nb_pixel_total : 617 time to create 1 rle with old method : 0.0007741451263427734 time for calcul the mask position with numpy : 0.005959033966064453 nb_pixel_total : 4105 time to create 1 rle with old method : 0.004462480545043945 time for calcul the mask position with numpy : 0.0057735443115234375 nb_pixel_total : 452 time to create 1 rle with old method : 0.0005357265472412109 time for calcul the mask position with numpy : 0.0066411495208740234 nb_pixel_total : 827 time to create 1 rle with old method : 0.0012764930725097656 time for calcul the mask position with numpy : 0.006509065628051758 nb_pixel_total : 236 time to create 1 rle with old method : 0.0003352165222167969 time for calcul the mask position with numpy : 0.005797863006591797 nb_pixel_total : 828 time to create 1 rle with old method : 0.0009632110595703125 time for calcul the mask position with numpy : 0.005829334259033203 nb_pixel_total : 4146 time to create 1 rle with old method : 0.004916667938232422 time for calcul the mask position with numpy : 0.005852460861206055 nb_pixel_total : 1003 time to create 1 rle with old method : 0.0012595653533935547 time for calcul the mask position with numpy : 0.006470441818237305 nb_pixel_total : 6064 time to create 1 rle with old method : 0.006934165954589844 time for calcul the mask position with numpy : 0.006150245666503906 nb_pixel_total : 4084 time to create 1 rle with old method : 0.0046002864837646484 time for calcul the mask position with numpy : 0.0060808658599853516 nb_pixel_total : 4104 time to create 1 rle with old method : 0.0047664642333984375 time for calcul the mask position with numpy : 0.006045341491699219 nb_pixel_total : 261 time to create 1 rle with old method : 0.00032639503479003906 time for calcul the mask position with numpy : 0.006090402603149414 nb_pixel_total : 494 time to create 1 rle with old method : 0.0006148815155029297 time for calcul the mask position with numpy : 0.006063222885131836 nb_pixel_total : 227 time to create 1 rle with old method : 0.00030159950256347656 time for calcul the mask position with numpy : 0.006871223449707031 nb_pixel_total : 150562 time to create 1 rle with new method : 0.028124332427978516 time for calcul the mask position with numpy : 0.006108283996582031 nb_pixel_total : 2391 time to create 1 rle with old method : 0.0028319358825683594 time for calcul the mask position with numpy : 0.006177663803100586 nb_pixel_total : 755 time to create 1 rle with old method : 0.0009064674377441406 time for calcul the mask position with numpy : 0.0061092376708984375 nb_pixel_total : 675 time to create 1 rle with old method : 0.0007991790771484375 time for calcul the mask position with numpy : 0.006007671356201172 nb_pixel_total : 103 time to create 1 rle with old method : 0.00019168853759765625 time for calcul the mask position with numpy : 0.005962848663330078 nb_pixel_total : 1779 time to create 1 rle with old method : 0.002057790756225586 time for calcul the mask position with numpy : 0.006674528121948242 nb_pixel_total : 718 time to create 1 rle with old method : 0.0008127689361572266 time for calcul the mask position with numpy : 0.006068706512451172 nb_pixel_total : 1096 time to create 1 rle with old method : 0.0013041496276855469 time for calcul the mask position with numpy : 0.006102323532104492 nb_pixel_total : 1347 time to create 1 rle with old method : 0.0016021728515625 time for calcul the mask position with numpy : 0.006102085113525391 nb_pixel_total : 229 time to create 1 rle with old method : 0.0003085136413574219 time for calcul the mask position with numpy : 0.006103515625 nb_pixel_total : 548 time to create 1 rle with old method : 0.0006456375122070312 time for calcul the mask position with numpy : 0.01021575927734375 nb_pixel_total : 780 time to create 1 rle with old method : 0.0009360313415527344 time for calcul the mask position with numpy : 0.009946107864379883 nb_pixel_total : 687 time to create 1 rle with old method : 0.0008721351623535156 time for calcul the mask position with numpy : 0.010020256042480469 nb_pixel_total : 999 time to create 1 rle with old method : 0.0012574195861816406 time for calcul the mask position with numpy : 0.010019302368164062 nb_pixel_total : 143 time to create 1 rle with old method : 0.0002486705780029297 time for calcul the mask position with numpy : 0.009989500045776367 nb_pixel_total : 1736 time to create 1 rle with old method : 0.0020923614501953125 time for calcul the mask position with numpy : 0.009929656982421875 nb_pixel_total : 3134 time to create 1 rle with old method : 0.003638029098510742 time for calcul the mask position with numpy : 0.009910345077514648 nb_pixel_total : 106 time to create 1 rle with old method : 0.00014662742614746094 time for calcul the mask position with numpy : 0.009992837905883789 nb_pixel_total : 980 time to create 1 rle with old method : 0.001157999038696289 time for calcul the mask position with numpy : 0.01402425765991211 nb_pixel_total : 404 time to create 1 rle with old method : 0.0006709098815917969 time for calcul the mask position with numpy : 0.011298418045043945 nb_pixel_total : 1452 time to create 1 rle with old method : 0.0017139911651611328 time for calcul the mask position with numpy : 0.010267496109008789 nb_pixel_total : 306 time to create 1 rle with old method : 0.0003902912139892578 time for calcul the mask position with numpy : 0.010401010513305664 nb_pixel_total : 191 time to create 1 rle with old method : 0.0002467632293701172 time for calcul the mask position with numpy : 0.009757041931152344 nb_pixel_total : 11 time to create 1 rle with old method : 5.269050598144531e-05 time for calcul the mask position with numpy : 0.009803533554077148 nb_pixel_total : 309 time to create 1 rle with old method : 0.0003638267517089844 time for calcul the mask position with numpy : 0.010950565338134766 nb_pixel_total : 518 time to create 1 rle with old method : 0.0006468296051025391 time for calcul the mask position with numpy : 0.010817289352416992 nb_pixel_total : 612 time to create 1 rle with old method : 0.000736236572265625 time for calcul the mask position with numpy : 0.009882926940917969 nb_pixel_total : 39 time to create 1 rle with old method : 6.914138793945312e-05 time for calcul the mask position with numpy : 0.009865999221801758 nb_pixel_total : 81 time to create 1 rle with old method : 0.00012135505676269531 time for calcul the mask position with numpy : 0.009959220886230469 nb_pixel_total : 1404 time to create 1 rle with old method : 0.001741647720336914 time for calcul the mask position with numpy : 0.007468700408935547 nb_pixel_total : 374 time to create 1 rle with old method : 0.00048279762268066406 time for calcul the mask position with numpy : 0.0059299468994140625 nb_pixel_total : 1345 time to create 1 rle with old method : 0.0015964508056640625 time for calcul the mask position with numpy : 0.0062487125396728516 nb_pixel_total : 102 time to create 1 rle with old method : 0.00020503997802734375 time for calcul the mask position with numpy : 0.0064923763275146484 nb_pixel_total : 192 time to create 1 rle with old method : 0.0003464221954345703 time for calcul the mask position with numpy : 0.0063877105712890625 nb_pixel_total : 73 time to create 1 rle with old method : 0.00016450881958007812 time for calcul the mask position with numpy : 0.006390810012817383 nb_pixel_total : 309 time to create 1 rle with old method : 0.0005152225494384766 time for calcul the mask position with numpy : 0.0064280033111572266 nb_pixel_total : 245 time to create 1 rle with old method : 0.00045561790466308594 time for calcul the mask position with numpy : 0.006424665451049805 nb_pixel_total : 254 time to create 1 rle with old method : 0.0004279613494873047 time for calcul the mask position with numpy : 0.007120847702026367 nb_pixel_total : 106825 time to create 1 rle with old method : 0.12501859664916992 time for calcul the mask position with numpy : 0.006415128707885742 nb_pixel_total : 3453 time to create 1 rle with old method : 0.0039865970611572266 time for calcul the mask position with numpy : 0.0063784122467041016 nb_pixel_total : 152 time to create 1 rle with old method : 0.0002262592315673828 time for calcul the mask position with numpy : 0.006903886795043945 nb_pixel_total : 193 time to create 1 rle with old method : 0.0002689361572265625 time for calcul the mask position with numpy : 0.0062487125396728516 nb_pixel_total : 1575 time to create 1 rle with old method : 0.00203704833984375 time for calcul the mask position with numpy : 0.00626826286315918 nb_pixel_total : 1710 time to create 1 rle with old method : 0.002222299575805664 time for calcul the mask position with numpy : 0.006127595901489258 nb_pixel_total : 369 time to create 1 rle with old method : 0.0004420280456542969 time for calcul the mask position with numpy : 0.0062291622161865234 nb_pixel_total : 431 time to create 1 rle with old method : 0.0005402565002441406 time for calcul the mask position with numpy : 0.006103992462158203 nb_pixel_total : 1548 time to create 1 rle with old method : 0.0018546581268310547 time for calcul the mask position with numpy : 0.006173372268676758 nb_pixel_total : 2644 time to create 1 rle with old method : 0.0029544830322265625 time for calcul the mask position with numpy : 0.00622248649597168 nb_pixel_total : 442 time to create 1 rle with old method : 0.0005376338958740234 time for calcul the mask position with numpy : 0.006087779998779297 nb_pixel_total : 122 time to create 1 rle with old method : 0.00015974044799804688 time for calcul the mask position with numpy : 0.006086111068725586 nb_pixel_total : 165 time to create 1 rle with old method : 0.0002148151397705078 time for calcul the mask position with numpy : 0.0062007904052734375 nb_pixel_total : 152 time to create 1 rle with old method : 0.00025177001953125 time for calcul the mask position with numpy : 0.006101131439208984 nb_pixel_total : 662 time to create 1 rle with old method : 0.0008301734924316406 time for calcul the mask position with numpy : 0.006116628646850586 nb_pixel_total : 519 time to create 1 rle with old method : 0.0006251335144042969 time for calcul the mask position with numpy : 0.006175041198730469 nb_pixel_total : 235 time to create 1 rle with old method : 0.0003292560577392578 time for calcul the mask position with numpy : 0.006096839904785156 nb_pixel_total : 7418 time to create 1 rle with old method : 0.008498191833496094 time for calcul the mask position with numpy : 0.006167173385620117 nb_pixel_total : 906 time to create 1 rle with old method : 0.0010690689086914062 time for calcul the mask position with numpy : 0.006342172622680664 nb_pixel_total : 374 time to create 1 rle with old method : 0.0004642009735107422 time for calcul the mask position with numpy : 0.006316661834716797 nb_pixel_total : 22 time to create 1 rle with old method : 5.7220458984375e-05 time for calcul the mask position with numpy : 0.006325483322143555 nb_pixel_total : 493 time to create 1 rle with old method : 0.0006322860717773438 time for calcul the mask position with numpy : 0.006301164627075195 nb_pixel_total : 314 time to create 1 rle with old method : 0.00038170814514160156 create new chi : 0.8831403255462646 after preparing all the mask , begin to delete the rle from the crop_hashtag_id => VR 28-11-20 : il faut déplacer cela apres le save_crop_hashtag_ids_obj de la ligne 9514 ! we have 0 chi objets contains the rles time to delete rle : 0.001760721206665039 batch 1 Loaded 86 chid ids of type : 4230 Number RLEs to save : 9046 TO DO : save crop sub photo not yet done ! save time : 0.5463507175445557 nb_obj : 83 nb_hashtags : 6 time to prepare the origin masks : 1.6094801425933838 time for calcul the mask position with numpy : 0.027356624603271484 nb_pixel_total : 1695991 time to create 1 rle with new method : 0.0494229793548584 time for calcul the mask position with numpy : 0.0061876773834228516 nb_pixel_total : 11 time to create 1 rle with old method : 3.933906555175781e-05 time for calcul the mask position with numpy : 0.005968570709228516 nb_pixel_total : 1067 time to create 1 rle with old method : 0.0012156963348388672 time for calcul the mask position with numpy : 0.005970478057861328 nb_pixel_total : 334 time to create 1 rle with old method : 0.0004410743713378906 time for calcul the mask position with numpy : 0.005970954895019531 nb_pixel_total : 284 time to create 1 rle with old method : 0.00033855438232421875 time for calcul the mask position with numpy : 0.006103992462158203 nb_pixel_total : 613 time to create 1 rle with old method : 0.0007603168487548828 time for calcul the mask position with numpy : 0.0060596466064453125 nb_pixel_total : 80 time to create 1 rle with old method : 0.00015091896057128906 time for calcul the mask position with numpy : 0.006204128265380859 nb_pixel_total : 29 time to create 1 rle with old method : 5.364418029785156e-05 time for calcul the mask position with numpy : 0.006170749664306641 nb_pixel_total : 1048 time to create 1 rle with old method : 0.0012722015380859375 time for calcul the mask position with numpy : 0.006092071533203125 nb_pixel_total : 533 time to create 1 rle with old method : 0.0006563663482666016 time for calcul the mask position with numpy : 0.00628662109375 nb_pixel_total : 139 time to create 1 rle with old method : 0.00023174285888671875 time for calcul the mask position with numpy : 0.00617218017578125 nb_pixel_total : 2975 time to create 1 rle with old method : 0.0035393238067626953 time for calcul the mask position with numpy : 0.0061969757080078125 nb_pixel_total : 241 time to create 1 rle with old method : 0.0003147125244140625 time for calcul the mask position with numpy : 0.0061626434326171875 nb_pixel_total : 1580 time to create 1 rle with old method : 0.0017962455749511719 time for calcul the mask position with numpy : 0.0067899227142333984 nb_pixel_total : 31 time to create 1 rle with old method : 6.222724914550781e-05 time for calcul the mask position with numpy : 0.006124258041381836 nb_pixel_total : 381 time to create 1 rle with old method : 0.0005030632019042969 time for calcul the mask position with numpy : 0.006455659866333008 nb_pixel_total : 185 time to create 1 rle with old method : 0.00023436546325683594 time for calcul the mask position with numpy : 0.006303071975708008 nb_pixel_total : 5340 time to create 1 rle with old method : 0.006279468536376953 time for calcul the mask position with numpy : 0.007801055908203125 nb_pixel_total : 294 time to create 1 rle with old method : 0.0004582405090332031 time for calcul the mask position with numpy : 0.006450653076171875 nb_pixel_total : 6238 time to create 1 rle with old method : 0.0072002410888671875 time for calcul the mask position with numpy : 0.006186008453369141 nb_pixel_total : 398 time to create 1 rle with old method : 0.0005214214324951172 time for calcul the mask position with numpy : 0.00619816780090332 nb_pixel_total : 5124 time to create 1 rle with old method : 0.009040117263793945 time for calcul the mask position with numpy : 0.008233785629272461 nb_pixel_total : 11 time to create 1 rle with old method : 0.00010824203491210938 time for calcul the mask position with numpy : 0.0060825347900390625 nb_pixel_total : 562 time to create 1 rle with old method : 0.0006992816925048828 time for calcul the mask position with numpy : 0.007797956466674805 nb_pixel_total : 151000 time to create 1 rle with new method : 0.033293724060058594 time for calcul the mask position with numpy : 0.006128549575805664 nb_pixel_total : 1910 time to create 1 rle with old method : 0.002187967300415039 time for calcul the mask position with numpy : 0.006228446960449219 nb_pixel_total : 3877 time to create 1 rle with old method : 0.004365444183349609 time for calcul the mask position with numpy : 0.006220579147338867 nb_pixel_total : 648 time to create 1 rle with old method : 0.0007522106170654297 time for calcul the mask position with numpy : 0.006211280822753906 nb_pixel_total : 1377 time to create 1 rle with old method : 0.0016505718231201172 time for calcul the mask position with numpy : 0.006203413009643555 nb_pixel_total : 949 time to create 1 rle with old method : 0.0012257099151611328 time for calcul the mask position with numpy : 0.006278038024902344 nb_pixel_total : 1323 time to create 1 rle with old method : 0.001627206802368164 time for calcul the mask position with numpy : 0.00639033317565918 nb_pixel_total : 607 time to create 1 rle with old method : 0.0007474422454833984 time for calcul the mask position with numpy : 0.0064601898193359375 nb_pixel_total : 22085 time to create 1 rle with old method : 0.02505636215209961 time for calcul the mask position with numpy : 0.006345033645629883 nb_pixel_total : 60 time to create 1 rle with old method : 9.083747863769531e-05 time for calcul the mask position with numpy : 0.006293773651123047 nb_pixel_total : 269 time to create 1 rle with old method : 0.0003249645233154297 time for calcul the mask position with numpy : 0.006398677825927734 nb_pixel_total : 1077 time to create 1 rle with old method : 0.0012843608856201172 time for calcul the mask position with numpy : 0.0064029693603515625 nb_pixel_total : 656 time to create 1 rle with old method : 0.0008013248443603516 time for calcul the mask position with numpy : 0.006040096282958984 nb_pixel_total : 2735 time to create 1 rle with old method : 0.0029935836791992188 time for calcul the mask position with numpy : 0.006488323211669922 nb_pixel_total : 1459 time to create 1 rle with old method : 0.0019068717956542969 time for calcul the mask position with numpy : 0.008288860321044922 nb_pixel_total : 680 time to create 1 rle with old method : 0.00086212158203125 time for calcul the mask position with numpy : 0.010089635848999023 nb_pixel_total : 55 time to create 1 rle with old method : 0.00010323524475097656 time for calcul the mask position with numpy : 0.01027369499206543 nb_pixel_total : 3301 time to create 1 rle with old method : 0.00401759147644043 time for calcul the mask position with numpy : 0.01030588150024414 nb_pixel_total : 124 time to create 1 rle with old method : 0.00017189979553222656 time for calcul the mask position with numpy : 0.009977102279663086 nb_pixel_total : 889 time to create 1 rle with old method : 0.001115560531616211 time for calcul the mask position with numpy : 0.009911537170410156 nb_pixel_total : 426 time to create 1 rle with old method : 0.0004956722259521484 time for calcul the mask position with numpy : 0.009922266006469727 nb_pixel_total : 144 time to create 1 rle with old method : 0.00019860267639160156 time for calcul the mask position with numpy : 0.009907245635986328 nb_pixel_total : 244 time to create 1 rle with old method : 0.00029730796813964844 time for calcul the mask position with numpy : 0.010087728500366211 nb_pixel_total : 99 time to create 1 rle with old method : 0.00015664100646972656 time for calcul the mask position with numpy : 0.009774446487426758 nb_pixel_total : 564 time to create 1 rle with old method : 0.0007221698760986328 time for calcul the mask position with numpy : 0.009910106658935547 nb_pixel_total : 33 time to create 1 rle with old method : 5.984306335449219e-05 time for calcul the mask position with numpy : 0.009670734405517578 nb_pixel_total : 97 time to create 1 rle with old method : 0.00013780593872070312 time for calcul the mask position with numpy : 0.009775876998901367 nb_pixel_total : 1375 time to create 1 rle with old method : 0.0017268657684326172 time for calcul the mask position with numpy : 0.009768486022949219 nb_pixel_total : 378 time to create 1 rle with old method : 0.00047516822814941406 time for calcul the mask position with numpy : 0.009725332260131836 nb_pixel_total : 461 time to create 1 rle with old method : 0.0005810260772705078 time for calcul the mask position with numpy : 0.005864858627319336 nb_pixel_total : 405 time to create 1 rle with old method : 0.0005345344543457031 time for calcul the mask position with numpy : 0.009154558181762695 nb_pixel_total : 354 time to create 1 rle with old method : 0.00044226646423339844 time for calcul the mask position with numpy : 0.005906581878662109 nb_pixel_total : 207 time to create 1 rle with old method : 0.0002512931823730469 time for calcul the mask position with numpy : 0.006049633026123047 nb_pixel_total : 313 time to create 1 rle with old method : 0.0004127025604248047 time for calcul the mask position with numpy : 0.005908966064453125 nb_pixel_total : 246 time to create 1 rle with old method : 0.00031685829162597656 time for calcul the mask position with numpy : 0.005927324295043945 nb_pixel_total : 232 time to create 1 rle with old method : 0.0002899169921875 time for calcul the mask position with numpy : 0.0063970088958740234 nb_pixel_total : 106290 time to create 1 rle with old method : 0.11736297607421875 time for calcul the mask position with numpy : 0.006193876266479492 nb_pixel_total : 1396 time to create 1 rle with old method : 0.0016715526580810547 time for calcul the mask position with numpy : 0.006191730499267578 nb_pixel_total : 24360 time to create 1 rle with old method : 0.028405189514160156 time for calcul the mask position with numpy : 0.0062410831451416016 nb_pixel_total : 133 time to create 1 rle with old method : 0.0001823902130126953 time for calcul the mask position with numpy : 0.005956411361694336 nb_pixel_total : 125 time to create 1 rle with old method : 0.0001785755157470703 time for calcul the mask position with numpy : 0.006129026412963867 nb_pixel_total : 244 time to create 1 rle with old method : 0.000438690185546875 time for calcul the mask position with numpy : 0.006476879119873047 nb_pixel_total : 378 time to create 1 rle with old method : 0.0006432533264160156 time for calcul the mask position with numpy : 0.006430625915527344 nb_pixel_total : 421 time to create 1 rle with old method : 0.0007193088531494141 time for calcul the mask position with numpy : 0.006455183029174805 nb_pixel_total : 1563 time to create 1 rle with old method : 0.0025262832641601562 time for calcul the mask position with numpy : 0.0064334869384765625 nb_pixel_total : 475 time to create 1 rle with old method : 0.0008697509765625 time for calcul the mask position with numpy : 0.006436824798583984 nb_pixel_total : 46 time to create 1 rle with old method : 0.0001952648162841797 time for calcul the mask position with numpy : 0.006484508514404297 nb_pixel_total : 9 time to create 1 rle with old method : 0.0001385211944580078 time for calcul the mask position with numpy : 0.006472349166870117 nb_pixel_total : 2631 time to create 1 rle with old method : 0.004230976104736328 time for calcul the mask position with numpy : 0.006446361541748047 nb_pixel_total : 129 time to create 1 rle with old method : 0.0003135204315185547 time for calcul the mask position with numpy : 0.006705284118652344 nb_pixel_total : 441 time to create 1 rle with old method : 0.0007450580596923828 time for calcul the mask position with numpy : 0.006460905075073242 nb_pixel_total : 242 time to create 1 rle with old method : 0.0004277229309082031 time for calcul the mask position with numpy : 0.006518363952636719 nb_pixel_total : 629 time to create 1 rle with old method : 0.0007865428924560547 time for calcul the mask position with numpy : 0.0059621334075927734 nb_pixel_total : 464 time to create 1 rle with old method : 0.0005726814270019531 time for calcul the mask position with numpy : 0.00604248046875 nb_pixel_total : 7570 time to create 1 rle with old method : 0.00826263427734375 time for calcul the mask position with numpy : 0.006194591522216797 nb_pixel_total : 953 time to create 1 rle with old method : 0.0010783672332763672 time for calcul the mask position with numpy : 0.005991697311401367 nb_pixel_total : 313 time to create 1 rle with old method : 0.00039005279541015625 time for calcul the mask position with numpy : 0.006094217300415039 nb_pixel_total : 339 time to create 1 rle with old method : 0.0004181861877441406 time for calcul the mask position with numpy : 0.006132364273071289 nb_pixel_total : 10 time to create 1 rle with old method : 6.723403930664062e-05 time for calcul the mask position with numpy : 0.006008625030517578 nb_pixel_total : 291 time to create 1 rle with old method : 0.0003578662872314453 create new chi : 0.9577314853668213 after preparing all the mask , begin to delete the rle from the crop_hashtag_id => VR 28-11-20 : il faut déplacer cela apres le save_crop_hashtag_ids_obj de la ligne 9514 ! we have 0 chi objets contains the rles time to delete rle : 0.0017268657684326172 batch 1 Loaded 93 chid ids of type : 4230 Number RLEs to save : 10360 TO DO : save crop sub photo not yet done ! save time : 0.6808183193206787 nb_obj : 89 nb_hashtags : 5 time to prepare the origin masks : 2.2731881141662598 time for calcul the mask position with numpy : 0.027053356170654297 nb_pixel_total : 1654808 time to create 1 rle with new method : 0.0622098445892334 time for calcul the mask position with numpy : 0.0063915252685546875 nb_pixel_total : 633 time to create 1 rle with old method : 0.0009992122650146484 time for calcul the mask position with numpy : 0.006880998611450195 nb_pixel_total : 61825 time to create 1 rle with old method : 0.06662106513977051 time for calcul the mask position with numpy : 0.006525516510009766 nb_pixel_total : 89 time to create 1 rle with old method : 0.00014495849609375 time for calcul the mask position with numpy : 0.006509065628051758 nb_pixel_total : 25 time to create 1 rle with old method : 5.91278076171875e-05 time for calcul the mask position with numpy : 0.006155729293823242 nb_pixel_total : 1061 time to create 1 rle with old method : 0.001285552978515625 time for calcul the mask position with numpy : 0.006429195404052734 nb_pixel_total : 200 time to create 1 rle with old method : 0.00026297569274902344 time for calcul the mask position with numpy : 0.006192922592163086 nb_pixel_total : 507 time to create 1 rle with old method : 0.0006546974182128906 time for calcul the mask position with numpy : 0.006109714508056641 nb_pixel_total : 687 time to create 1 rle with old method : 0.0007975101470947266 time for calcul the mask position with numpy : 0.006086111068725586 nb_pixel_total : 3728 time to create 1 rle with old method : 0.004443168640136719 time for calcul the mask position with numpy : 0.006345033645629883 nb_pixel_total : 308 time to create 1 rle with old method : 0.00044083595275878906 time for calcul the mask position with numpy : 0.006124258041381836 nb_pixel_total : 1146 time to create 1 rle with old method : 0.0013651847839355469 time for calcul the mask position with numpy : 0.00621485710144043 nb_pixel_total : 6 time to create 1 rle with old method : 3.886222839355469e-05 time for calcul the mask position with numpy : 0.005979299545288086 nb_pixel_total : 245 time to create 1 rle with old method : 0.00030422210693359375 time for calcul the mask position with numpy : 0.0059354305267333984 nb_pixel_total : 377 time to create 1 rle with old method : 0.0004684925079345703 time for calcul the mask position with numpy : 0.006068706512451172 nb_pixel_total : 775 time to create 1 rle with old method : 0.0009341239929199219 time for calcul the mask position with numpy : 0.006125926971435547 nb_pixel_total : 118 time to create 1 rle with old method : 0.00017118453979492188 time for calcul the mask position with numpy : 0.010023117065429688 nb_pixel_total : 3962 time to create 1 rle with old method : 0.004625082015991211 time for calcul the mask position with numpy : 0.010101556777954102 nb_pixel_total : 6145 time to create 1 rle with old method : 0.006925344467163086 time for calcul the mask position with numpy : 0.013344764709472656 nb_pixel_total : 389 time to create 1 rle with old method : 0.00048661231994628906 time for calcul the mask position with numpy : 0.010285615921020508 nb_pixel_total : 4735 time to create 1 rle with old method : 0.005483150482177734 time for calcul the mask position with numpy : 0.010056257247924805 nb_pixel_total : 3485 time to create 1 rle with old method : 0.004135608673095703 time for calcul the mask position with numpy : 0.010139703750610352 nb_pixel_total : 502 time to create 1 rle with old method : 0.0006198883056640625 time for calcul the mask position with numpy : 0.01111149787902832 nb_pixel_total : 150002 time to create 1 rle with new method : 0.056345224380493164 time for calcul the mask position with numpy : 0.010032176971435547 nb_pixel_total : 4581 time to create 1 rle with old method : 0.00529932975769043 time for calcul the mask position with numpy : 0.01040792465209961 nb_pixel_total : 932 time to create 1 rle with old method : 0.001165151596069336 time for calcul the mask position with numpy : 0.00974416732788086 nb_pixel_total : 651 time to create 1 rle with old method : 0.0007658004760742188 time for calcul the mask position with numpy : 0.010252237319946289 nb_pixel_total : 1248 time to create 1 rle with old method : 0.0014042854309082031 time for calcul the mask position with numpy : 0.010431528091430664 nb_pixel_total : 21 time to create 1 rle with old method : 6.818771362304688e-05 time for calcul the mask position with numpy : 0.010300159454345703 nb_pixel_total : 823 time to create 1 rle with old method : 0.0009913444519042969 time for calcul the mask position with numpy : 0.010106801986694336 nb_pixel_total : 1856 time to create 1 rle with old method : 0.0022192001342773438 time for calcul the mask position with numpy : 0.0060291290283203125 nb_pixel_total : 14391 time to create 1 rle with old method : 0.016611576080322266 time for calcul the mask position with numpy : 0.0064661502838134766 nb_pixel_total : 267 time to create 1 rle with old method : 0.0003352165222167969 time for calcul the mask position with numpy : 0.006324052810668945 nb_pixel_total : 106 time to create 1 rle with old method : 0.00014090538024902344 time for calcul the mask position with numpy : 0.006208896636962891 nb_pixel_total : 1325 time to create 1 rle with old method : 0.0017080307006835938 time for calcul the mask position with numpy : 0.006120443344116211 nb_pixel_total : 486 time to create 1 rle with old method : 0.0006387233734130859 time for calcul the mask position with numpy : 0.006059885025024414 nb_pixel_total : 830 time to create 1 rle with old method : 0.0009379386901855469 time for calcul the mask position with numpy : 0.009995460510253906 nb_pixel_total : 4374 time to create 1 rle with old method : 0.00494694709777832 time for calcul the mask position with numpy : 0.009786128997802734 nb_pixel_total : 3412 time to create 1 rle with old method : 0.003808736801147461 time for calcul the mask position with numpy : 0.0060002803802490234 nb_pixel_total : 120 time to create 1 rle with old method : 0.00017452239990234375 time for calcul the mask position with numpy : 0.006220579147338867 nb_pixel_total : 321 time to create 1 rle with old method : 0.0005688667297363281 time for calcul the mask position with numpy : 0.006018877029418945 nb_pixel_total : 1108 time to create 1 rle with old method : 0.0014452934265136719 time for calcul the mask position with numpy : 0.005993366241455078 nb_pixel_total : 980 time to create 1 rle with old method : 0.001234292984008789 time for calcul the mask position with numpy : 0.006050825119018555 nb_pixel_total : 264 time to create 1 rle with old method : 0.0003552436828613281 time for calcul the mask position with numpy : 0.006020784378051758 nb_pixel_total : 216 time to create 1 rle with old method : 0.0002892017364501953 time for calcul the mask position with numpy : 0.006098508834838867 nb_pixel_total : 230 time to create 1 rle with old method : 0.0002868175506591797 time for calcul the mask position with numpy : 0.006113529205322266 nb_pixel_total : 518 time to create 1 rle with old method : 0.0006506443023681641 time for calcul the mask position with numpy : 0.006066322326660156 nb_pixel_total : 24 time to create 1 rle with old method : 7.581710815429688e-05 time for calcul the mask position with numpy : 0.006103992462158203 nb_pixel_total : 295 time to create 1 rle with old method : 0.0003809928894042969 time for calcul the mask position with numpy : 0.006216764450073242 nb_pixel_total : 538 time to create 1 rle with old method : 0.0006551742553710938 time for calcul the mask position with numpy : 0.006279706954956055 nb_pixel_total : 32 time to create 1 rle with old method : 5.9604644775390625e-05 time for calcul the mask position with numpy : 0.0059354305267333984 nb_pixel_total : 8 time to create 1 rle with old method : 3.886222839355469e-05 time for calcul the mask position with numpy : 0.00580596923828125 nb_pixel_total : 85 time to create 1 rle with old method : 0.00010991096496582031 time for calcul the mask position with numpy : 0.005923271179199219 nb_pixel_total : 2679 time to create 1 rle with old method : 0.002888917922973633 time for calcul the mask position with numpy : 0.0058939456939697266 nb_pixel_total : 88 time to create 1 rle with old method : 0.00019216537475585938 time for calcul the mask position with numpy : 0.005867481231689453 nb_pixel_total : 1322 time to create 1 rle with old method : 0.0016870498657226562 time for calcul the mask position with numpy : 0.0058100223541259766 nb_pixel_total : 19 time to create 1 rle with old method : 7.343292236328125e-05 time for calcul the mask position with numpy : 0.005838155746459961 nb_pixel_total : 15 time to create 1 rle with old method : 5.2928924560546875e-05 time for calcul the mask position with numpy : 0.006042003631591797 nb_pixel_total : 384 time to create 1 rle with old method : 0.0005049705505371094 time for calcul the mask position with numpy : 0.005864381790161133 nb_pixel_total : 367 time to create 1 rle with old method : 0.00045752525329589844 time for calcul the mask position with numpy : 0.0060312747955322266 nb_pixel_total : 165 time to create 1 rle with old method : 0.00022745132446289062 time for calcul the mask position with numpy : 0.005837440490722656 nb_pixel_total : 172 time to create 1 rle with old method : 0.00022840499877929688 time for calcul the mask position with numpy : 0.006090641021728516 nb_pixel_total : 266 time to create 1 rle with old method : 0.0003345012664794922 time for calcul the mask position with numpy : 0.005982875823974609 nb_pixel_total : 192 time to create 1 rle with old method : 0.00026535987854003906 time for calcul the mask position with numpy : 0.005819082260131836 nb_pixel_total : 250 time to create 1 rle with old method : 0.0002999305725097656 time for calcul the mask position with numpy : 0.009842872619628906 nb_pixel_total : 106638 time to create 1 rle with old method : 0.11791753768920898 time for calcul the mask position with numpy : 0.01027822494506836 nb_pixel_total : 3147 time to create 1 rle with old method : 0.003631114959716797 time for calcul the mask position with numpy : 0.010280609130859375 nb_pixel_total : 66 time to create 1 rle with old method : 0.0001513957977294922 time for calcul the mask position with numpy : 0.010154008865356445 nb_pixel_total : 281 time to create 1 rle with old method : 0.0003571510314941406 time for calcul the mask position with numpy : 0.00997781753540039 nb_pixel_total : 194 time to create 1 rle with old method : 0.0002815723419189453 time for calcul the mask position with numpy : 0.010562419891357422 nb_pixel_total : 1634 time to create 1 rle with old method : 0.001940011978149414 time for calcul the mask position with numpy : 0.0066394805908203125 nb_pixel_total : 414 time to create 1 rle with old method : 0.0005478858947753906 time for calcul the mask position with numpy : 0.006421327590942383 nb_pixel_total : 398 time to create 1 rle with old method : 0.0005240440368652344 time for calcul the mask position with numpy : 0.006197929382324219 nb_pixel_total : 348 time to create 1 rle with old method : 0.00047326087951660156 time for calcul the mask position with numpy : 0.006123542785644531 nb_pixel_total : 1658 time to create 1 rle with old method : 0.001985788345336914 time for calcul the mask position with numpy : 0.006392717361450195 nb_pixel_total : 58 time to create 1 rle with old method : 0.00012254714965820312 time for calcul the mask position with numpy : 0.008336544036865234 nb_pixel_total : 2510 time to create 1 rle with old method : 0.0029354095458984375 time for calcul the mask position with numpy : 0.010224103927612305 nb_pixel_total : 203 time to create 1 rle with old method : 0.00028014183044433594 time for calcul the mask position with numpy : 0.010348320007324219 nb_pixel_total : 3056 time to create 1 rle with old method : 0.0038061141967773438 time for calcul the mask position with numpy : 0.010423898696899414 nb_pixel_total : 451 time to create 1 rle with old method : 0.0005986690521240234 time for calcul the mask position with numpy : 0.010539054870605469 nb_pixel_total : 124 time to create 1 rle with old method : 0.00018310546875 time for calcul the mask position with numpy : 0.010968923568725586 nb_pixel_total : 289 time to create 1 rle with old method : 0.00039577484130859375 time for calcul the mask position with numpy : 0.010736942291259766 nb_pixel_total : 7478 time to create 1 rle with old method : 0.009125232696533203 time for calcul the mask position with numpy : 0.010540246963500977 nb_pixel_total : 900 time to create 1 rle with old method : 0.0014710426330566406 time for calcul the mask position with numpy : 0.010893106460571289 nb_pixel_total : 330 time to create 1 rle with old method : 0.0004200935363769531 time for calcul the mask position with numpy : 0.010404586791992188 nb_pixel_total : 1066 time to create 1 rle with old method : 0.0012924671173095703 time for calcul the mask position with numpy : 0.010402679443359375 nb_pixel_total : 18 time to create 1 rle with old method : 6.67572021484375e-05 time for calcul the mask position with numpy : 0.010500669479370117 nb_pixel_total : 11 time to create 1 rle with old method : 7.748603820800781e-05 time for calcul the mask position with numpy : 0.010170221328735352 nb_pixel_total : 285 time to create 1 rle with old method : 0.00038623809814453125 time for calcul the mask position with numpy : 0.01172494888305664 nb_pixel_total : 324 time to create 1 rle with old method : 0.0004038810729980469 create new chi : 1.1594007015228271 after preparing all the mask , begin to delete the rle from the crop_hashtag_id => VR 28-11-20 : il faut déplacer cela apres le save_crop_hashtag_ids_obj de la ligne 9514 ! we have 0 chi objets contains the rles time to delete rle : 0.0033211708068847656 batch 1 Loaded 96 chid ids of type : 4230 Number RLEs to save : 10611 TO DO : save crop sub photo not yet done ! save time : 2.6554648876190186 nb_obj : 79 nb_hashtags : 6 time to prepare the origin masks : 1.9148507118225098 time for calcul the mask position with numpy : 0.05351591110229492 nb_pixel_total : 1726476 time to create 1 rle with new method : 0.0985410213470459 time for calcul the mask position with numpy : 0.006710052490234375 nb_pixel_total : 14 time to create 1 rle with old method : 0.00013065338134765625 time for calcul the mask position with numpy : 0.0064432621002197266 nb_pixel_total : 154 time to create 1 rle with old method : 0.0002799034118652344 time for calcul the mask position with numpy : 0.006324052810668945 nb_pixel_total : 1787 time to create 1 rle with old method : 0.0021636486053466797 time for calcul the mask position with numpy : 0.006486654281616211 nb_pixel_total : 172 time to create 1 rle with old method : 0.0002498626708984375 time for calcul the mask position with numpy : 0.006420612335205078 nb_pixel_total : 256 time to create 1 rle with old method : 0.00031065940856933594 time for calcul the mask position with numpy : 0.006577968597412109 nb_pixel_total : 928 time to create 1 rle with old method : 0.001165151596069336 time for calcul the mask position with numpy : 0.006489992141723633 nb_pixel_total : 12 time to create 1 rle with old method : 4.6253204345703125e-05 time for calcul the mask position with numpy : 0.006312847137451172 nb_pixel_total : 495 time to create 1 rle with old method : 0.0006163120269775391 time for calcul the mask position with numpy : 0.006239891052246094 nb_pixel_total : 3680 time to create 1 rle with old method : 0.004546642303466797 time for calcul the mask position with numpy : 0.006695747375488281 nb_pixel_total : 948 time to create 1 rle with old method : 0.0011386871337890625 time for calcul the mask position with numpy : 0.008752584457397461 nb_pixel_total : 244 time to create 1 rle with old method : 0.0005364418029785156 time for calcul the mask position with numpy : 0.0069789886474609375 nb_pixel_total : 242 time to create 1 rle with old method : 0.00031185150146484375 time for calcul the mask position with numpy : 0.006411314010620117 nb_pixel_total : 387 time to create 1 rle with old method : 0.00048160552978515625 time for calcul the mask position with numpy : 0.006607532501220703 nb_pixel_total : 723 time to create 1 rle with old method : 0.0050737857818603516 time for calcul the mask position with numpy : 0.011683225631713867 nb_pixel_total : 1396 time to create 1 rle with old method : 0.0015647411346435547 time for calcul the mask position with numpy : 0.010529279708862305 nb_pixel_total : 14 time to create 1 rle with old method : 7.843971252441406e-05 time for calcul the mask position with numpy : 0.00995326042175293 nb_pixel_total : 2096 time to create 1 rle with old method : 0.002538919448852539 time for calcul the mask position with numpy : 0.0066301822662353516 nb_pixel_total : 2659 time to create 1 rle with old method : 0.0030279159545898438 time for calcul the mask position with numpy : 0.006475210189819336 nb_pixel_total : 7288 time to create 1 rle with old method : 0.008435726165771484 time for calcul the mask position with numpy : 0.006338596343994141 nb_pixel_total : 282 time to create 1 rle with old method : 0.0003635883331298828 time for calcul the mask position with numpy : 0.006432056427001953 nb_pixel_total : 550 time to create 1 rle with old method : 0.0006673336029052734 time for calcul the mask position with numpy : 0.007924318313598633 nb_pixel_total : 151730 time to create 1 rle with new method : 0.058274269104003906 time for calcul the mask position with numpy : 0.00613856315612793 nb_pixel_total : 4530 time to create 1 rle with old method : 0.005197048187255859 time for calcul the mask position with numpy : 0.0062258243560791016 nb_pixel_total : 45 time to create 1 rle with old method : 0.0001125335693359375 time for calcul the mask position with numpy : 0.006511211395263672 nb_pixel_total : 1461 time to create 1 rle with old method : 0.0017423629760742188 time for calcul the mask position with numpy : 0.006424665451049805 nb_pixel_total : 57 time to create 1 rle with old method : 0.00013494491577148438 time for calcul the mask position with numpy : 0.006632328033447266 nb_pixel_total : 644 time to create 1 rle with old method : 0.0008082389831542969 time for calcul the mask position with numpy : 0.006722450256347656 nb_pixel_total : 91 time to create 1 rle with old method : 0.00013446807861328125 time for calcul the mask position with numpy : 0.010630607604980469 nb_pixel_total : 806 time to create 1 rle with old method : 0.000982046127319336 time for calcul the mask position with numpy : 0.010986328125 nb_pixel_total : 16 time to create 1 rle with old method : 5.459785461425781e-05 time for calcul the mask position with numpy : 0.010775327682495117 nb_pixel_total : 1805 time to create 1 rle with old method : 0.0022668838500976562 time for calcul the mask position with numpy : 0.01054072380065918 nb_pixel_total : 304 time to create 1 rle with old method : 0.0004067420959472656 time for calcul the mask position with numpy : 0.01107478141784668 nb_pixel_total : 2 time to create 1 rle with old method : 3.6716461181640625e-05 time for calcul the mask position with numpy : 0.010281562805175781 nb_pixel_total : 166 time to create 1 rle with old method : 0.00022602081298828125 time for calcul the mask position with numpy : 0.014221668243408203 nb_pixel_total : 157 time to create 1 rle with old method : 0.000331878662109375 time for calcul the mask position with numpy : 0.01127767562866211 nb_pixel_total : 299 time to create 1 rle with old method : 0.0003724098205566406 time for calcul the mask position with numpy : 0.010691165924072266 nb_pixel_total : 13043 time to create 1 rle with old method : 0.016532182693481445 time for calcul the mask position with numpy : 0.010939836502075195 nb_pixel_total : 1316 time to create 1 rle with old method : 0.0015456676483154297 time for calcul the mask position with numpy : 0.011294841766357422 nb_pixel_total : 6978 time to create 1 rle with old method : 0.008047103881835938 time for calcul the mask position with numpy : 0.011031389236450195 nb_pixel_total : 756 time to create 1 rle with old method : 0.0009083747863769531 time for calcul the mask position with numpy : 0.01076054573059082 nb_pixel_total : 137 time to create 1 rle with old method : 0.0001900196075439453 time for calcul the mask position with numpy : 0.010808229446411133 nb_pixel_total : 3003 time to create 1 rle with old method : 0.0035338401794433594 time for calcul the mask position with numpy : 0.010700702667236328 nb_pixel_total : 21 time to create 1 rle with old method : 8.797645568847656e-05 time for calcul the mask position with numpy : 0.010549545288085938 nb_pixel_total : 977 time to create 1 rle with old method : 0.0012671947479248047 time for calcul the mask position with numpy : 0.010696887969970703 nb_pixel_total : 360 time to create 1 rle with old method : 0.00046253204345703125 time for calcul the mask position with numpy : 0.011106014251708984 nb_pixel_total : 1737 time to create 1 rle with old method : 0.0021355152130126953 time for calcul the mask position with numpy : 0.010931253433227539 nb_pixel_total : 165 time to create 1 rle with old method : 0.0002105236053466797 time for calcul the mask position with numpy : 0.01363229751586914 nb_pixel_total : 555 time to create 1 rle with old method : 0.0006799697875976562 time for calcul the mask position with numpy : 0.010621070861816406 nb_pixel_total : 393 time to create 1 rle with old method : 0.0004875659942626953 time for calcul the mask position with numpy : 0.010634899139404297 nb_pixel_total : 538 time to create 1 rle with old method : 0.0006442070007324219 time for calcul the mask position with numpy : 0.011214494705200195 nb_pixel_total : 31 time to create 1 rle with old method : 6.103515625e-05 time for calcul the mask position with numpy : 0.011165618896484375 nb_pixel_total : 3312 time to create 1 rle with old method : 0.0037419795989990234 time for calcul the mask position with numpy : 0.011405229568481445 nb_pixel_total : 84 time to create 1 rle with old method : 0.00013256072998046875 time for calcul the mask position with numpy : 0.019186973571777344 nb_pixel_total : 1229 time to create 1 rle with old method : 0.0015854835510253906 time for calcul the mask position with numpy : 0.010728597640991211 nb_pixel_total : 312 time to create 1 rle with old method : 0.0003933906555175781 time for calcul the mask position with numpy : 0.011467933654785156 nb_pixel_total : 456 time to create 1 rle with old method : 0.0005712509155273438 time for calcul the mask position with numpy : 0.010749101638793945 nb_pixel_total : 208 time to create 1 rle with old method : 0.00027632713317871094 time for calcul the mask position with numpy : 0.010833263397216797 nb_pixel_total : 536 time to create 1 rle with old method : 0.0006556510925292969 time for calcul the mask position with numpy : 0.010676145553588867 nb_pixel_total : 244 time to create 1 rle with old method : 0.0002956390380859375 time for calcul the mask position with numpy : 0.011012554168701172 nb_pixel_total : 106254 time to create 1 rle with old method : 0.11467647552490234 time for calcul the mask position with numpy : 0.010734081268310547 nb_pixel_total : 189 time to create 1 rle with old method : 0.00024437904357910156 time for calcul the mask position with numpy : 0.010293960571289062 nb_pixel_total : 156 time to create 1 rle with old method : 0.00021600723266601562 time for calcul the mask position with numpy : 0.010566473007202148 nb_pixel_total : 1683 time to create 1 rle with old method : 0.0020804405212402344 time for calcul the mask position with numpy : 0.010691404342651367 nb_pixel_total : 151 time to create 1 rle with old method : 0.00019598007202148438 time for calcul the mask position with numpy : 0.010855913162231445 nb_pixel_total : 380 time to create 1 rle with old method : 0.00047206878662109375 time for calcul the mask position with numpy : 0.010707616806030273 nb_pixel_total : 396 time to create 1 rle with old method : 0.0005004405975341797 time for calcul the mask position with numpy : 0.014223098754882812 nb_pixel_total : 1613 time to create 1 rle with old method : 0.0019173622131347656 time for calcul the mask position with numpy : 0.010348081588745117 nb_pixel_total : 2543 time to create 1 rle with old method : 0.0029616355895996094 time for calcul the mask position with numpy : 0.010433435440063477 nb_pixel_total : 118 time to create 1 rle with old method : 0.00016999244689941406 time for calcul the mask position with numpy : 0.00844264030456543 nb_pixel_total : 211 time to create 1 rle with old method : 0.00025200843811035156 time for calcul the mask position with numpy : 0.008442878723144531 nb_pixel_total : 447 time to create 1 rle with old method : 0.0005695819854736328 time for calcul the mask position with numpy : 0.008180856704711914 nb_pixel_total : 7400 time to create 1 rle with old method : 0.008390665054321289 time for calcul the mask position with numpy : 0.008211612701416016 nb_pixel_total : 673 time to create 1 rle with old method : 0.0007894039154052734 time for calcul the mask position with numpy : 0.008420228958129883 nb_pixel_total : 941 time to create 1 rle with old method : 0.00113677978515625 time for calcul the mask position with numpy : 0.008433818817138672 nb_pixel_total : 284 time to create 1 rle with old method : 0.000339508056640625 time for calcul the mask position with numpy : 0.00834798812866211 nb_pixel_total : 12 time to create 1 rle with old method : 3.5762786865234375e-05 time for calcul the mask position with numpy : 0.00838780403137207 nb_pixel_total : 12 time to create 1 rle with old method : 4.482269287109375e-05 time for calcul the mask position with numpy : 0.008405447006225586 nb_pixel_total : 521 time to create 1 rle with old method : 0.0006470680236816406 time for calcul the mask position with numpy : 0.010863780975341797 nb_pixel_total : 309 time to create 1 rle with old method : 0.00037789344787597656 create new chi : 1.193615198135376 after preparing all the mask , begin to delete the rle from the crop_hashtag_id => VR 28-11-20 : il faut déplacer cela apres le save_crop_hashtag_ids_obj de la ligne 9514 ! we have 0 chi objets contains the rles time to delete rle : 0.0014977455139160156 batch 1 Loaded 87 chid ids of type : 4230 Number RLEs to save : 8834 TO DO : save crop sub photo not yet done ! save time : 1.9939215183258057 nb_obj : 94 nb_hashtags : 7 time to prepare the origin masks : 2.2800915241241455 time for calcul the mask position with numpy : 0.13407206535339355 nb_pixel_total : 1728575 time to create 1 rle with new method : 0.09804034233093262 time for calcul the mask position with numpy : 0.01086878776550293 nb_pixel_total : 148 time to create 1 rle with old method : 0.000232696533203125 time for calcul the mask position with numpy : 0.01031184196472168 nb_pixel_total : 30 time to create 1 rle with old method : 7.605552673339844e-05 time for calcul the mask position with numpy : 0.011760234832763672 nb_pixel_total : 1009 time to create 1 rle with old method : 0.0013453960418701172 time for calcul the mask position with numpy : 0.011089801788330078 nb_pixel_total : 2059 time to create 1 rle with old method : 0.0024640560150146484 time for calcul the mask position with numpy : 0.01085972785949707 nb_pixel_total : 270 time to create 1 rle with old method : 0.0003552436828613281 time for calcul the mask position with numpy : 0.010754585266113281 nb_pixel_total : 92 time to create 1 rle with old method : 0.0002913475036621094 time for calcul the mask position with numpy : 0.011011362075805664 nb_pixel_total : 4287 time to create 1 rle with old method : 0.0053217411041259766 time for calcul the mask position with numpy : 0.011787652969360352 nb_pixel_total : 1205 time to create 1 rle with old method : 0.0015406608581542969 time for calcul the mask position with numpy : 0.011066198348999023 nb_pixel_total : 253 time to create 1 rle with old method : 0.00033402442932128906 time for calcul the mask position with numpy : 0.010190486907958984 nb_pixel_total : 401 time to create 1 rle with old method : 0.0005245208740234375 time for calcul the mask position with numpy : 0.006479024887084961 nb_pixel_total : 825 time to create 1 rle with old method : 0.0010058879852294922 time for calcul the mask position with numpy : 0.00736236572265625 nb_pixel_total : 2340 time to create 1 rle with old method : 0.0030219554901123047 time for calcul the mask position with numpy : 0.006582021713256836 nb_pixel_total : 914 time to create 1 rle with old method : 0.0011911392211914062 time for calcul the mask position with numpy : 0.010991096496582031 nb_pixel_total : 36 time to create 1 rle with old method : 0.00012826919555664062 time for calcul the mask position with numpy : 0.012210369110107422 nb_pixel_total : 6574 time to create 1 rle with old method : 0.008123397827148438 time for calcul the mask position with numpy : 0.011991262435913086 nb_pixel_total : 13 time to create 1 rle with old method : 9.512901306152344e-05 time for calcul the mask position with numpy : 0.011115312576293945 nb_pixel_total : 418 time to create 1 rle with old method : 0.0005450248718261719 time for calcul the mask position with numpy : 0.011249780654907227 nb_pixel_total : 4491 time to create 1 rle with old method : 0.005162715911865234 time for calcul the mask position with numpy : 0.011617898941040039 nb_pixel_total : 2419 time to create 1 rle with old method : 0.0039484500885009766 time for calcul the mask position with numpy : 0.007635593414306641 nb_pixel_total : 542 time to create 1 rle with old method : 0.0009329319000244141 time for calcul the mask position with numpy : 0.00965428352355957 nb_pixel_total : 149822 time to create 1 rle with old method : 0.1838514804840088 time for calcul the mask position with numpy : 0.006755352020263672 nb_pixel_total : 1256 time to create 1 rle with old method : 0.001552581787109375 time for calcul the mask position with numpy : 0.00652003288269043 nb_pixel_total : 47 time to create 1 rle with old method : 0.00019097328186035156 time for calcul the mask position with numpy : 0.006367206573486328 nb_pixel_total : 25 time to create 1 rle with old method : 9.369850158691406e-05 time for calcul the mask position with numpy : 0.007077693939208984 nb_pixel_total : 2649 time to create 1 rle with old method : 0.003163576126098633 time for calcul the mask position with numpy : 0.00719761848449707 nb_pixel_total : 3261 time to create 1 rle with old method : 0.003902435302734375 time for calcul the mask position with numpy : 0.010407209396362305 nb_pixel_total : 660 time to create 1 rle with old method : 0.0008072853088378906 time for calcul the mask position with numpy : 0.014152288436889648 nb_pixel_total : 176 time to create 1 rle with old method : 0.00039839744567871094 time for calcul the mask position with numpy : 0.013643264770507812 nb_pixel_total : 778 time to create 1 rle with old method : 0.0012362003326416016 time for calcul the mask position with numpy : 0.05277609825134277 nb_pixel_total : 1975 time to create 1 rle with old method : 0.01730942726135254 time for calcul the mask position with numpy : 0.011020898818969727 nb_pixel_total : 49 time to create 1 rle with old method : 0.00010251998901367188 time for calcul the mask position with numpy : 0.01087808609008789 nb_pixel_total : 1071 time to create 1 rle with old method : 0.0013189315795898438 time for calcul the mask position with numpy : 0.010699272155761719 nb_pixel_total : 295 time to create 1 rle with old method : 0.0003829002380371094 time for calcul the mask position with numpy : 0.010429620742797852 nb_pixel_total : 175 time to create 1 rle with old method : 0.00023436546325683594 time for calcul the mask position with numpy : 0.010738134384155273 nb_pixel_total : 1958 time to create 1 rle with old method : 0.0024421215057373047 time for calcul the mask position with numpy : 0.010797262191772461 nb_pixel_total : 532 time to create 1 rle with old method : 0.0006501674652099609 time for calcul the mask position with numpy : 0.010938882827758789 nb_pixel_total : 1288 time to create 1 rle with old method : 0.0015370845794677734 time for calcul the mask position with numpy : 0.01331329345703125 nb_pixel_total : 660 time to create 1 rle with old method : 0.0010941028594970703 time for calcul the mask position with numpy : 0.01376652717590332 nb_pixel_total : 2 time to create 1 rle with old method : 4.8160552978515625e-05 time for calcul the mask position with numpy : 0.01532125473022461 nb_pixel_total : 257 time to create 1 rle with old method : 0.0005412101745605469 time for calcul the mask position with numpy : 0.015026330947875977 nb_pixel_total : 763 time to create 1 rle with old method : 0.0009558200836181641 time for calcul the mask position with numpy : 0.011185646057128906 nb_pixel_total : 10 time to create 1 rle with old method : 6.461143493652344e-05 time for calcul the mask position with numpy : 0.011144638061523438 nb_pixel_total : 2790 time to create 1 rle with old method : 0.0032472610473632812 time for calcul the mask position with numpy : 0.010800838470458984 nb_pixel_total : 4782 time to create 1 rle with old method : 0.00537419319152832 time for calcul the mask position with numpy : 0.011558771133422852 nb_pixel_total : 132 time to create 1 rle with old method : 0.0001857280731201172 time for calcul the mask position with numpy : 0.01084589958190918 nb_pixel_total : 229 time to create 1 rle with old method : 0.0005829334259033203 time for calcul the mask position with numpy : 0.01077580451965332 nb_pixel_total : 1112 time to create 1 rle with old method : 0.001468658447265625 time for calcul the mask position with numpy : 0.010762929916381836 nb_pixel_total : 1223 time to create 1 rle with old method : 0.0015268325805664062 time for calcul the mask position with numpy : 0.011445045471191406 nb_pixel_total : 416 time to create 1 rle with old method : 0.0005476474761962891 time for calcul the mask position with numpy : 0.01116323471069336 nb_pixel_total : 128 time to create 1 rle with old method : 0.00023818016052246094 time for calcul the mask position with numpy : 0.011129617691040039 nb_pixel_total : 1543 time to create 1 rle with old method : 0.0021381378173828125 time for calcul the mask position with numpy : 0.011695146560668945 nb_pixel_total : 182 time to create 1 rle with old method : 0.00038909912109375 time for calcul the mask position with numpy : 0.01178431510925293 nb_pixel_total : 37 time to create 1 rle with old method : 9.72747802734375e-05 time for calcul the mask position with numpy : 0.012612342834472656 nb_pixel_total : 522 time to create 1 rle with old method : 0.001165151596069336 time for calcul the mask position with numpy : 0.013964653015136719 nb_pixel_total : 224 time to create 1 rle with old method : 0.0004162788391113281 time for calcul the mask position with numpy : 0.013894319534301758 nb_pixel_total : 33 time to create 1 rle with old method : 9.250640869140625e-05 time for calcul the mask position with numpy : 0.013417243957519531 nb_pixel_total : 76 time to create 1 rle with old method : 0.00016808509826660156 time for calcul the mask position with numpy : 0.01336050033569336 nb_pixel_total : 25 time to create 1 rle with old method : 0.000164031982421875 time for calcul the mask position with numpy : 0.012801408767700195 nb_pixel_total : 1224 time to create 1 rle with old method : 0.0020780563354492188 time for calcul the mask position with numpy : 0.013032197952270508 nb_pixel_total : 29 time to create 1 rle with old method : 0.0001049041748046875 time for calcul the mask position with numpy : 0.01313018798828125 nb_pixel_total : 364 time to create 1 rle with old method : 0.0006375312805175781 time for calcul the mask position with numpy : 0.012811660766601562 nb_pixel_total : 340 time to create 1 rle with old method : 0.0005831718444824219 time for calcul the mask position with numpy : 0.01319575309753418 nb_pixel_total : 488 time to create 1 rle with old method : 0.0010271072387695312 time for calcul the mask position with numpy : 0.01417994499206543 nb_pixel_total : 180 time to create 1 rle with old method : 0.00041222572326660156 time for calcul the mask position with numpy : 0.01322627067565918 nb_pixel_total : 166 time to create 1 rle with old method : 0.0003159046173095703 time for calcul the mask position with numpy : 0.013183116912841797 nb_pixel_total : 194 time to create 1 rle with old method : 0.0003674030303955078 time for calcul the mask position with numpy : 0.013285160064697266 nb_pixel_total : 233 time to create 1 rle with old method : 0.0011563301086425781 time for calcul the mask position with numpy : 0.013061285018920898 nb_pixel_total : 86 time to create 1 rle with old method : 0.00018858909606933594 time for calcul the mask position with numpy : 0.01224064826965332 nb_pixel_total : 252 time to create 1 rle with old method : 0.0003261566162109375 time for calcul the mask position with numpy : 0.011938095092773438 nb_pixel_total : 106587 time to create 1 rle with old method : 0.11726188659667969 time for calcul the mask position with numpy : 0.010695219039916992 nb_pixel_total : 343 time to create 1 rle with old method : 0.0004825592041015625 time for calcul the mask position with numpy : 0.010680675506591797 nb_pixel_total : 3243 time to create 1 rle with old method : 0.0037755966186523438 time for calcul the mask position with numpy : 0.010803461074829102 nb_pixel_total : 223 time to create 1 rle with old method : 0.0003006458282470703 time for calcul the mask position with numpy : 0.010976791381835938 nb_pixel_total : 1673 time to create 1 rle with old method : 0.002064228057861328 time for calcul the mask position with numpy : 0.011310338973999023 nb_pixel_total : 363 time to create 1 rle with old method : 0.00047087669372558594 time for calcul the mask position with numpy : 0.014565229415893555 nb_pixel_total : 378 time to create 1 rle with old method : 0.00048232078552246094 time for calcul the mask position with numpy : 0.010766744613647461 nb_pixel_total : 403 time to create 1 rle with old method : 0.0005102157592773438 time for calcul the mask position with numpy : 0.010558128356933594 nb_pixel_total : 65 time to create 1 rle with old method : 0.0002276897430419922 time for calcul the mask position with numpy : 0.01063847541809082 nb_pixel_total : 1605 time to create 1 rle with old method : 0.0018894672393798828 time for calcul the mask position with numpy : 0.007517337799072266 nb_pixel_total : 2607 time to create 1 rle with old method : 0.0030546188354492188 time for calcul the mask position with numpy : 0.011391878128051758 nb_pixel_total : 137 time to create 1 rle with old method : 0.00035834312438964844 time for calcul the mask position with numpy : 0.008491277694702148 nb_pixel_total : 2786 time to create 1 rle with old method : 0.0032186508178710938 time for calcul the mask position with numpy : 0.008489370346069336 nb_pixel_total : 133 time to create 1 rle with old method : 0.00017833709716796875 time for calcul the mask position with numpy : 0.00854802131652832 nb_pixel_total : 273 time to create 1 rle with old method : 0.00032591819763183594 time for calcul the mask position with numpy : 0.00846552848815918 nb_pixel_total : 239 time to create 1 rle with old method : 0.0003273487091064453 time for calcul the mask position with numpy : 0.008543014526367188 nb_pixel_total : 67 time to create 1 rle with old method : 0.00019240379333496094 time for calcul the mask position with numpy : 0.008678197860717773 nb_pixel_total : 7437 time to create 1 rle with old method : 0.008792877197265625 time for calcul the mask position with numpy : 0.008716344833374023 nb_pixel_total : 24 time to create 1 rle with old method : 6.699562072753906e-05 time for calcul the mask position with numpy : 0.008881568908691406 nb_pixel_total : 974 time to create 1 rle with old method : 0.0011668205261230469 time for calcul the mask position with numpy : 0.008572578430175781 nb_pixel_total : 254 time to create 1 rle with old method : 0.0003216266632080078 time for calcul the mask position with numpy : 0.008455514907836914 nb_pixel_total : 1277 time to create 1 rle with old method : 0.0015118122100830078 time for calcul the mask position with numpy : 0.008500099182128906 nb_pixel_total : 441 time to create 1 rle with old method : 0.0005633831024169922 time for calcul the mask position with numpy : 0.008542776107788086 nb_pixel_total : 136 time to create 1 rle with old method : 0.00019073486328125 time for calcul the mask position with numpy : 0.00859975814819336 nb_pixel_total : 312 time to create 1 rle with old method : 0.0004584789276123047 create new chi : 1.7413675785064697 after preparing all the mask , begin to delete the rle from the crop_hashtag_id => VR 28-11-20 : il faut déplacer cela apres le save_crop_hashtag_ids_obj de la ligne 9514 ! we have 0 chi objets contains the rles time to delete rle : 0.002676725387573242 batch 1 Loaded 100 chid ids of type : 4230 Number RLEs to save : 10182 TO DO : save crop sub photo not yet done ! save time : 0.5895307064056396 nb_obj : 77 nb_hashtags : 6 time to prepare the origin masks : 1.7328612804412842 time for calcul the mask position with numpy : 0.02790069580078125 nb_pixel_total : 1832211 time to create 1 rle with new method : 0.04254007339477539 time for calcul the mask position with numpy : 0.00716853141784668 nb_pixel_total : 669 time to create 1 rle with old method : 0.0007913112640380859 time for calcul the mask position with numpy : 0.00693202018737793 nb_pixel_total : 1059 time to create 1 rle with old method : 0.0012850761413574219 time for calcul the mask position with numpy : 0.007064104080200195 nb_pixel_total : 19 time to create 1 rle with old method : 6.079673767089844e-05 time for calcul the mask position with numpy : 0.0069653987884521484 nb_pixel_total : 140 time to create 1 rle with old method : 0.00020360946655273438 time for calcul the mask position with numpy : 0.00684666633605957 nb_pixel_total : 251 time to create 1 rle with old method : 0.00035834312438964844 time for calcul the mask position with numpy : 0.006983280181884766 nb_pixel_total : 44 time to create 1 rle with old method : 0.00012564659118652344 time for calcul the mask position with numpy : 0.007612705230712891 nb_pixel_total : 47721 time to create 1 rle with old method : 0.05288362503051758 time for calcul the mask position with numpy : 0.007165193557739258 nb_pixel_total : 2124 time to create 1 rle with old method : 0.0023987293243408203 time for calcul the mask position with numpy : 0.0070667266845703125 nb_pixel_total : 115 time to create 1 rle with old method : 0.00023245811462402344 time for calcul the mask position with numpy : 0.006994962692260742 nb_pixel_total : 2017 time to create 1 rle with old method : 0.002458333969116211 time for calcul the mask position with numpy : 0.007101774215698242 nb_pixel_total : 262 time to create 1 rle with old method : 0.00034236907958984375 time for calcul the mask position with numpy : 0.007250547409057617 nb_pixel_total : 733 time to create 1 rle with old method : 0.0008981227874755859 time for calcul the mask position with numpy : 0.007283210754394531 nb_pixel_total : 323 time to create 1 rle with old method : 0.00043082237243652344 time for calcul the mask position with numpy : 0.007635831832885742 nb_pixel_total : 788 time to create 1 rle with old method : 0.0009305477142333984 time for calcul the mask position with numpy : 0.007384538650512695 nb_pixel_total : 4174 time to create 1 rle with old method : 0.004930734634399414 time for calcul the mask position with numpy : 0.0072596073150634766 nb_pixel_total : 678 time to create 1 rle with old method : 0.0008404254913330078 time for calcul the mask position with numpy : 0.007387399673461914 nb_pixel_total : 5703 time to create 1 rle with old method : 0.0067636966705322266 time for calcul the mask position with numpy : 0.007413625717163086 nb_pixel_total : 4926 time to create 1 rle with old method : 0.005803108215332031 time for calcul the mask position with numpy : 0.007376432418823242 nb_pixel_total : 504 time to create 1 rle with old method : 0.0006372928619384766 time for calcul the mask position with numpy : 0.007329225540161133 nb_pixel_total : 4543 time to create 1 rle with old method : 0.0052912235260009766 time for calcul the mask position with numpy : 0.007405519485473633 nb_pixel_total : 663 time to create 1 rle with old method : 0.0007944107055664062 time for calcul the mask position with numpy : 0.007500171661376953 nb_pixel_total : 1444 time to create 1 rle with old method : 0.001748800277709961 time for calcul the mask position with numpy : 0.0074465274810791016 nb_pixel_total : 708 time to create 1 rle with old method : 0.0008666515350341797 time for calcul the mask position with numpy : 0.007489919662475586 nb_pixel_total : 1691 time to create 1 rle with old method : 0.0021021366119384766 time for calcul the mask position with numpy : 0.007194042205810547 nb_pixel_total : 178 time to create 1 rle with old method : 0.00025010108947753906 time for calcul the mask position with numpy : 0.007494688034057617 nb_pixel_total : 15766 time to create 1 rle with old method : 0.018456697463989258 time for calcul the mask position with numpy : 0.0074579715728759766 nb_pixel_total : 1076 time to create 1 rle with old method : 0.0013017654418945312 time for calcul the mask position with numpy : 0.0071828365325927734 nb_pixel_total : 647 time to create 1 rle with old method : 0.0007998943328857422 time for calcul the mask position with numpy : 0.007299900054931641 nb_pixel_total : 6117 time to create 1 rle with old method : 0.007228374481201172 time for calcul the mask position with numpy : 0.007134675979614258 nb_pixel_total : 706 time to create 1 rle with old method : 0.0012807846069335938 time for calcul the mask position with numpy : 0.006882429122924805 nb_pixel_total : 188 time to create 1 rle with old method : 0.00028514862060546875 time for calcul the mask position with numpy : 0.007025957107543945 nb_pixel_total : 136 time to create 1 rle with old method : 0.00020122528076171875 time for calcul the mask position with numpy : 0.0070531368255615234 nb_pixel_total : 756 time to create 1 rle with old method : 0.0009200572967529297 time for calcul the mask position with numpy : 0.0070459842681884766 nb_pixel_total : 3019 time to create 1 rle with old method : 0.0036454200744628906 time for calcul the mask position with numpy : 0.00724339485168457 nb_pixel_total : 881 time to create 1 rle with old method : 0.001115560531616211 time for calcul the mask position with numpy : 0.0075490474700927734 nb_pixel_total : 270 time to create 1 rle with old method : 0.00037789344787597656 time for calcul the mask position with numpy : 0.00796055793762207 nb_pixel_total : 600 time to create 1 rle with old method : 0.0008902549743652344 time for calcul the mask position with numpy : 0.0073893070220947266 nb_pixel_total : 100 time to create 1 rle with old method : 0.0001761913299560547 time for calcul the mask position with numpy : 0.0072519779205322266 nb_pixel_total : 25 time to create 1 rle with old method : 8.916854858398438e-05 time for calcul the mask position with numpy : 0.007385969161987305 nb_pixel_total : 498 time to create 1 rle with old method : 0.0006368160247802734 time for calcul the mask position with numpy : 0.007293701171875 nb_pixel_total : 10 time to create 1 rle with old method : 5.507469177246094e-05 time for calcul the mask position with numpy : 0.007411479949951172 nb_pixel_total : 2 time to create 1 rle with old method : 3.528594970703125e-05 time for calcul the mask position with numpy : 0.007588624954223633 nb_pixel_total : 274 time to create 1 rle with old method : 0.0003478527069091797 time for calcul the mask position with numpy : 0.007510662078857422 nb_pixel_total : 36 time to create 1 rle with old method : 7.605552673339844e-05 time for calcul the mask position with numpy : 0.007392406463623047 nb_pixel_total : 105 time to create 1 rle with old method : 0.00015306472778320312 time for calcul the mask position with numpy : 0.007388114929199219 nb_pixel_total : 1305 time to create 1 rle with old method : 0.0015273094177246094 time for calcul the mask position with numpy : 0.007595539093017578 nb_pixel_total : 378 time to create 1 rle with old method : 0.00046825408935546875 time for calcul the mask position with numpy : 0.007458925247192383 nb_pixel_total : 385 time to create 1 rle with old method : 0.00048160552978515625 time for calcul the mask position with numpy : 0.007443904876708984 nb_pixel_total : 373 time to create 1 rle with old method : 0.0004711151123046875 time for calcul the mask position with numpy : 0.007417440414428711 nb_pixel_total : 118 time to create 1 rle with old method : 0.0001780986785888672 time for calcul the mask position with numpy : 0.0076940059661865234 nb_pixel_total : 158 time to create 1 rle with old method : 0.00021409988403320312 time for calcul the mask position with numpy : 0.007674217224121094 nb_pixel_total : 284 time to create 1 rle with old method : 0.00035858154296875 time for calcul the mask position with numpy : 0.00761866569519043 nb_pixel_total : 173 time to create 1 rle with old method : 0.00023865699768066406 time for calcul the mask position with numpy : 0.008406639099121094 nb_pixel_total : 91 time to create 1 rle with old method : 0.0002627372741699219 time for calcul the mask position with numpy : 0.008691072463989258 nb_pixel_total : 5 time to create 1 rle with old method : 4.863739013671875e-05 time for calcul the mask position with numpy : 0.008300065994262695 nb_pixel_total : 250 time to create 1 rle with old method : 0.0005130767822265625 time for calcul the mask position with numpy : 0.009294271469116211 nb_pixel_total : 106344 time to create 1 rle with old method : 0.1250169277191162 time for calcul the mask position with numpy : 0.008150815963745117 nb_pixel_total : 227 time to create 1 rle with old method : 0.0003273487091064453 time for calcul the mask position with numpy : 0.007771968841552734 nb_pixel_total : 169 time to create 1 rle with old method : 0.00025391578674316406 time for calcul the mask position with numpy : 0.008124351501464844 nb_pixel_total : 238 time to create 1 rle with old method : 0.0003476142883300781 time for calcul the mask position with numpy : 0.008361577987670898 nb_pixel_total : 485 time to create 1 rle with old method : 0.0006515979766845703 time for calcul the mask position with numpy : 0.007608890533447266 nb_pixel_total : 395 time to create 1 rle with old method : 0.00048661231994628906 time for calcul the mask position with numpy : 0.008323907852172852 nb_pixel_total : 1639 time to create 1 rle with old method : 0.0019447803497314453 time for calcul the mask position with numpy : 0.00789189338684082 nb_pixel_total : 167 time to create 1 rle with old method : 0.00025153160095214844 time for calcul the mask position with numpy : 0.007807016372680664 nb_pixel_total : 2451 time to create 1 rle with old method : 0.0030241012573242188 time for calcul the mask position with numpy : 0.007296323776245117 nb_pixel_total : 333 time to create 1 rle with old method : 0.00045609474182128906 time for calcul the mask position with numpy : 0.00748896598815918 nb_pixel_total : 349 time to create 1 rle with old method : 0.0005028247833251953 time for calcul the mask position with numpy : 0.00765538215637207 nb_pixel_total : 539 time to create 1 rle with old method : 0.0006721019744873047 time for calcul the mask position with numpy : 0.007716178894042969 nb_pixel_total : 36 time to create 1 rle with old method : 0.00011396408081054688 time for calcul the mask position with numpy : 0.008384943008422852 nb_pixel_total : 486 time to create 1 rle with old method : 0.0006117820739746094 time for calcul the mask position with numpy : 0.008250236511230469 nb_pixel_total : 7523 time to create 1 rle with old method : 0.008875608444213867 time for calcul the mask position with numpy : 0.007853507995605469 nb_pixel_total : 2239 time to create 1 rle with old method : 0.0027184486389160156 time for calcul the mask position with numpy : 0.007775068283081055 nb_pixel_total : 900 time to create 1 rle with old method : 0.0010342597961425781 time for calcul the mask position with numpy : 0.007767915725708008 nb_pixel_total : 26 time to create 1 rle with old method : 0.00010323524475097656 time for calcul the mask position with numpy : 0.008253812789916992 nb_pixel_total : 327 time to create 1 rle with old method : 0.00042510032653808594 time for calcul the mask position with numpy : 0.0074443817138671875 nb_pixel_total : 2 time to create 1 rle with old method : 6.0558319091796875e-05 time for calcul the mask position with numpy : 0.00794076919555664 nb_pixel_total : 305 time to create 1 rle with old method : 0.0003600120544433594 create new chi : 0.9400982856750488 after preparing all the mask , begin to delete the rle from the crop_hashtag_id => VR 28-11-20 : il faut déplacer cela apres le save_crop_hashtag_ids_obj de la ligne 9514 ! we have 0 chi objets contains the rles time to delete rle : 0.0020456314086914062 batch 1 Loaded 85 chid ids of type : 4230 Number RLEs to save : 8190 TO DO : save crop sub photo not yet done ! save time : 0.4812800884246826 nb_obj : 74 nb_hashtags : 6 time to prepare the origin masks : 1.91807222366333 time for calcul the mask position with numpy : 0.048666954040527344 nb_pixel_total : 1649391 time to create 1 rle with new method : 0.09312891960144043 time for calcul the mask position with numpy : 0.012505054473876953 nb_pixel_total : 846 time to create 1 rle with old method : 0.0009753704071044922 time for calcul the mask position with numpy : 0.01103067398071289 nb_pixel_total : 503 time to create 1 rle with old method : 0.0009543895721435547 time for calcul the mask position with numpy : 0.011512279510498047 nb_pixel_total : 41442 time to create 1 rle with old method : 0.04371190071105957 time for calcul the mask position with numpy : 0.01103830337524414 nb_pixel_total : 87 time to create 1 rle with old method : 0.00015616416931152344 time for calcul the mask position with numpy : 0.011316537857055664 nb_pixel_total : 223 time to create 1 rle with old method : 0.00034737586975097656 time for calcul the mask position with numpy : 0.01152801513671875 nb_pixel_total : 28 time to create 1 rle with old method : 7.82012939453125e-05 time for calcul the mask position with numpy : 0.016655683517456055 nb_pixel_total : 1018 time to create 1 rle with old method : 0.0011556148529052734 time for calcul the mask position with numpy : 0.011174917221069336 nb_pixel_total : 256 time to create 1 rle with old method : 0.0003249645233154297 time for calcul the mask position with numpy : 0.01114034652709961 nb_pixel_total : 257 time to create 1 rle with old method : 0.0003426074981689453 time for calcul the mask position with numpy : 0.011501073837280273 nb_pixel_total : 902 time to create 1 rle with old method : 0.0011358261108398438 time for calcul the mask position with numpy : 0.011466503143310547 nb_pixel_total : 204 time to create 1 rle with old method : 0.00029850006103515625 time for calcul the mask position with numpy : 0.011525154113769531 nb_pixel_total : 2258 time to create 1 rle with old method : 0.002582550048828125 time for calcul the mask position with numpy : 0.01110219955444336 nb_pixel_total : 99 time to create 1 rle with old method : 0.00014162063598632812 time for calcul the mask position with numpy : 0.011674642562866211 nb_pixel_total : 1807 time to create 1 rle with old method : 0.0020067691802978516 time for calcul the mask position with numpy : 0.011504411697387695 nb_pixel_total : 106 time to create 1 rle with old method : 0.0001819133758544922 time for calcul the mask position with numpy : 0.011028051376342773 nb_pixel_total : 4625 time to create 1 rle with old method : 0.004773378372192383 time for calcul the mask position with numpy : 0.0111541748046875 nb_pixel_total : 372 time to create 1 rle with old method : 0.0004603862762451172 time for calcul the mask position with numpy : 0.011095523834228516 nb_pixel_total : 4455 time to create 1 rle with old method : 0.004837512969970703 time for calcul the mask position with numpy : 0.011301994323730469 nb_pixel_total : 6365 time to create 1 rle with old method : 0.006939411163330078 time for calcul the mask position with numpy : 0.011139154434204102 nb_pixel_total : 744 time to create 1 rle with old method : 0.0010025501251220703 time for calcul the mask position with numpy : 0.011139392852783203 nb_pixel_total : 40 time to create 1 rle with old method : 0.0001308917999267578 time for calcul the mask position with numpy : 0.010951519012451172 nb_pixel_total : 509 time to create 1 rle with old method : 0.0005867481231689453 time for calcul the mask position with numpy : 0.01209115982055664 nb_pixel_total : 149998 time to create 1 rle with old method : 0.1497175693511963 time for calcul the mask position with numpy : 0.019065141677856445 nb_pixel_total : 698 time to create 1 rle with old method : 0.0008165836334228516 time for calcul the mask position with numpy : 0.013699054718017578 nb_pixel_total : 1860 time to create 1 rle with old method : 0.002034425735473633 time for calcul the mask position with numpy : 0.013656139373779297 nb_pixel_total : 701 time to create 1 rle with old method : 0.0008466243743896484 time for calcul the mask position with numpy : 0.013768911361694336 nb_pixel_total : 487 time to create 1 rle with old method : 0.0005908012390136719 time for calcul the mask position with numpy : 0.013475656509399414 nb_pixel_total : 1008 time to create 1 rle with old method : 0.0013492107391357422 time for calcul the mask position with numpy : 0.013662099838256836 nb_pixel_total : 7820 time to create 1 rle with old method : 0.008975982666015625 time for calcul the mask position with numpy : 0.013965129852294922 nb_pixel_total : 672 time to create 1 rle with old method : 0.0008232593536376953 time for calcul the mask position with numpy : 0.013726234436035156 nb_pixel_total : 217 time to create 1 rle with old method : 0.0003228187561035156 time for calcul the mask position with numpy : 0.01199650764465332 nb_pixel_total : 3049 time to create 1 rle with old method : 0.0034859180450439453 time for calcul the mask position with numpy : 0.011764049530029297 nb_pixel_total : 143 time to create 1 rle with old method : 0.0002186298370361328 time for calcul the mask position with numpy : 0.011721372604370117 nb_pixel_total : 921 time to create 1 rle with old method : 0.0011017322540283203 time for calcul the mask position with numpy : 0.011938333511352539 nb_pixel_total : 1708 time to create 1 rle with old method : 0.001897573471069336 time for calcul the mask position with numpy : 0.01146078109741211 nb_pixel_total : 749 time to create 1 rle with old method : 0.0009045600891113281 time for calcul the mask position with numpy : 0.011400222778320312 nb_pixel_total : 404 time to create 1 rle with old method : 0.0005311965942382812 time for calcul the mask position with numpy : 0.011070489883422852 nb_pixel_total : 209 time to create 1 rle with old method : 0.0002722740173339844 time for calcul the mask position with numpy : 0.011156320571899414 nb_pixel_total : 5 time to create 1 rle with old method : 5.316734313964844e-05 time for calcul the mask position with numpy : 0.011492490768432617 nb_pixel_total : 556 time to create 1 rle with old method : 0.0006444454193115234 time for calcul the mask position with numpy : 0.010649442672729492 nb_pixel_total : 212 time to create 1 rle with old method : 0.0002694129943847656 time for calcul the mask position with numpy : 0.006561756134033203 nb_pixel_total : 34 time to create 1 rle with old method : 7.081031799316406e-05 time for calcul the mask position with numpy : 0.006497383117675781 nb_pixel_total : 3448 time to create 1 rle with old method : 0.003769397735595703 time for calcul the mask position with numpy : 0.0067365169525146484 nb_pixel_total : 1330 time to create 1 rle with old method : 0.0014982223510742188 time for calcul the mask position with numpy : 0.011460065841674805 nb_pixel_total : 347 time to create 1 rle with old method : 0.0004391670227050781 time for calcul the mask position with numpy : 0.010990381240844727 nb_pixel_total : 19 time to create 1 rle with old method : 7.271766662597656e-05 time for calcul the mask position with numpy : 0.011307477951049805 nb_pixel_total : 428 time to create 1 rle with old method : 0.0005056858062744141 time for calcul the mask position with numpy : 0.011038780212402344 nb_pixel_total : 597 time to create 1 rle with old method : 0.0007274150848388672 time for calcul the mask position with numpy : 0.011114358901977539 nb_pixel_total : 118 time to create 1 rle with old method : 0.0001842975616455078 time for calcul the mask position with numpy : 0.011061429977416992 nb_pixel_total : 170 time to create 1 rle with old method : 0.0002315044403076172 time for calcul the mask position with numpy : 0.011330842971801758 nb_pixel_total : 255 time to create 1 rle with old method : 0.00030684471130371094 time for calcul the mask position with numpy : 0.01177978515625 nb_pixel_total : 106032 time to create 1 rle with old method : 0.10702013969421387 time for calcul the mask position with numpy : 0.011687040328979492 nb_pixel_total : 3447 time to create 1 rle with old method : 0.0038709640502929688 time for calcul the mask position with numpy : 0.011894464492797852 nb_pixel_total : 39796 time to create 1 rle with old method : 0.04194760322570801 time for calcul the mask position with numpy : 0.012217998504638672 nb_pixel_total : 139 time to create 1 rle with old method : 0.000392913818359375 time for calcul the mask position with numpy : 0.012066364288330078 nb_pixel_total : 188 time to create 1 rle with old method : 0.0002579689025878906 time for calcul the mask position with numpy : 0.011876344680786133 nb_pixel_total : 1620 time to create 1 rle with old method : 0.0018475055694580078 time for calcul the mask position with numpy : 0.01173543930053711 nb_pixel_total : 2 time to create 1 rle with old method : 4.2438507080078125e-05 time for calcul the mask position with numpy : 0.011425971984863281 nb_pixel_total : 440 time to create 1 rle with old method : 0.0005762577056884766 time for calcul the mask position with numpy : 0.011468172073364258 nb_pixel_total : 374 time to create 1 rle with old method : 0.0004763603210449219 time for calcul the mask position with numpy : 0.011596202850341797 nb_pixel_total : 350 time to create 1 rle with old method : 0.0004494190216064453 time for calcul the mask position with numpy : 0.011557817459106445 nb_pixel_total : 91 time to create 1 rle with old method : 0.000156402587890625 time for calcul the mask position with numpy : 0.011662721633911133 nb_pixel_total : 1643 time to create 1 rle with old method : 0.002031087875366211 time for calcul the mask position with numpy : 0.011990547180175781 nb_pixel_total : 9188 time to create 1 rle with old method : 0.010384798049926758 time for calcul the mask position with numpy : 0.012451410293579102 nb_pixel_total : 2566 time to create 1 rle with old method : 0.003034353256225586 time for calcul the mask position with numpy : 0.012525081634521484 nb_pixel_total : 2875 time to create 1 rle with old method : 0.003415346145629883 time for calcul the mask position with numpy : 0.008754968643188477 nb_pixel_total : 161 time to create 1 rle with old method : 0.0002205371856689453 time for calcul the mask position with numpy : 0.008654117584228516 nb_pixel_total : 237 time to create 1 rle with old method : 0.00030493736267089844 time for calcul the mask position with numpy : 0.008740901947021484 nb_pixel_total : 7515 time to create 1 rle with old method : 0.008419036865234375 time for calcul the mask position with numpy : 0.008725404739379883 nb_pixel_total : 885 time to create 1 rle with old method : 0.0010745525360107422 time for calcul the mask position with numpy : 0.008678674697875977 nb_pixel_total : 476 time to create 1 rle with old method : 0.0006275177001953125 time for calcul the mask position with numpy : 0.008638381958007812 nb_pixel_total : 272 time to create 1 rle with old method : 0.00035858154296875 time for calcul the mask position with numpy : 0.008644580841064453 nb_pixel_total : 294 time to create 1 rle with old method : 0.0003638267517089844 time for calcul the mask position with numpy : 0.008570194244384766 nb_pixel_total : 309 time to create 1 rle with old method : 0.0003795623779296875 create new chi : 1.439854621887207 after preparing all the mask , begin to delete the rle from the crop_hashtag_id => VR 28-11-20 : il faut déplacer cela apres le save_crop_hashtag_ids_obj de la ligne 9514 ! we have 0 chi objets contains the rles time to delete rle : 0.003843545913696289 batch 1 Loaded 83 chid ids of type : 4230 Number RLEs to save : 10225 TO DO : save crop sub photo not yet done ! save time : 0.5872716903686523 nb_obj : 86 nb_hashtags : 5 time to prepare the origin masks : 2.2693064212799072 time for calcul the mask position with numpy : 0.06872224807739258 nb_pixel_total : 1715201 time to create 1 rle with new method : 0.19553852081298828 time for calcul the mask position with numpy : 0.010497093200683594 nb_pixel_total : 894 time to create 1 rle with old method : 0.0010788440704345703 time for calcul the mask position with numpy : 0.010494470596313477 nb_pixel_total : 262 time to create 1 rle with old method : 0.0003414154052734375 time for calcul the mask position with numpy : 0.010811328887939453 nb_pixel_total : 7793 time to create 1 rle with old method : 0.00891733169555664 time for calcul the mask position with numpy : 0.010086536407470703 nb_pixel_total : 9 time to create 1 rle with old method : 3.6716461181640625e-05 time for calcul the mask position with numpy : 0.010092735290527344 nb_pixel_total : 85 time to create 1 rle with old method : 0.00016427040100097656 time for calcul the mask position with numpy : 0.010275602340698242 nb_pixel_total : 13 time to create 1 rle with old method : 4.2438507080078125e-05 time for calcul the mask position with numpy : 0.010421037673950195 nb_pixel_total : 1006 time to create 1 rle with old method : 0.001199483871459961 time for calcul the mask position with numpy : 0.007661104202270508 nb_pixel_total : 1738 time to create 1 rle with old method : 0.002328157424926758 time for calcul the mask position with numpy : 0.008148431777954102 nb_pixel_total : 215 time to create 1 rle with old method : 0.00026702880859375 time for calcul the mask position with numpy : 0.006718158721923828 nb_pixel_total : 486 time to create 1 rle with old method : 0.0009374618530273438 time for calcul the mask position with numpy : 0.008352518081665039 nb_pixel_total : 92 time to create 1 rle with old method : 0.0003178119659423828 time for calcul the mask position with numpy : 0.007943391799926758 nb_pixel_total : 2215 time to create 1 rle with old method : 0.003831148147583008 time for calcul the mask position with numpy : 0.01658320426940918 nb_pixel_total : 661 time to create 1 rle with old method : 0.0008733272552490234 time for calcul the mask position with numpy : 0.010949373245239258 nb_pixel_total : 1134 time to create 1 rle with old method : 0.0016143321990966797 time for calcul the mask position with numpy : 0.011144638061523438 nb_pixel_total : 4 time to create 1 rle with old method : 3.4809112548828125e-05 time for calcul the mask position with numpy : 0.010555028915405273 nb_pixel_total : 284 time to create 1 rle with old method : 0.00040602684020996094 time for calcul the mask position with numpy : 0.010480642318725586 nb_pixel_total : 524 time to create 1 rle with old method : 0.0006792545318603516 time for calcul the mask position with numpy : 0.010290384292602539 nb_pixel_total : 4 time to create 1 rle with old method : 3.0040740966796875e-05 time for calcul the mask position with numpy : 0.010469436645507812 nb_pixel_total : 837 time to create 1 rle with old method : 0.0010035037994384766 time for calcul the mask position with numpy : 0.010752201080322266 nb_pixel_total : 3471 time to create 1 rle with old method : 0.00410914421081543 time for calcul the mask position with numpy : 0.01065683364868164 nb_pixel_total : 212 time to create 1 rle with old method : 0.00033855438232421875 time for calcul the mask position with numpy : 0.010339021682739258 nb_pixel_total : 64 time to create 1 rle with old method : 0.00015354156494140625 time for calcul the mask position with numpy : 0.010985851287841797 nb_pixel_total : 3465 time to create 1 rle with old method : 0.0042307376861572266 time for calcul the mask position with numpy : 0.011371374130249023 nb_pixel_total : 5989 time to create 1 rle with old method : 0.006788015365600586 time for calcul the mask position with numpy : 0.010597467422485352 nb_pixel_total : 22 time to create 1 rle with old method : 0.00017023086547851562 time for calcul the mask position with numpy : 0.010667800903320312 nb_pixel_total : 1099 time to create 1 rle with old method : 0.001371145248413086 time for calcul the mask position with numpy : 0.010461807250976562 nb_pixel_total : 805 time to create 1 rle with old method : 0.0010128021240234375 time for calcul the mask position with numpy : 0.010556936264038086 nb_pixel_total : 362 time to create 1 rle with old method : 0.0004520416259765625 time for calcul the mask position with numpy : 0.010348320007324219 nb_pixel_total : 554 time to create 1 rle with old method : 0.0006737709045410156 time for calcul the mask position with numpy : 0.01038503646850586 nb_pixel_total : 150519 time to create 1 rle with new method : 0.1235041618347168 time for calcul the mask position with numpy : 0.010704994201660156 nb_pixel_total : 96 time to create 1 rle with old method : 0.00014400482177734375 time for calcul the mask position with numpy : 0.010739564895629883 nb_pixel_total : 92 time to create 1 rle with old method : 0.00013589859008789062 time for calcul the mask position with numpy : 0.011098623275756836 nb_pixel_total : 756 time to create 1 rle with old method : 0.000911712646484375 time for calcul the mask position with numpy : 0.009651899337768555 nb_pixel_total : 1689 time to create 1 rle with old method : 0.0020437240600585938 time for calcul the mask position with numpy : 0.006289482116699219 nb_pixel_total : 1301 time to create 1 rle with old method : 0.0016589164733886719 time for calcul the mask position with numpy : 0.006298542022705078 nb_pixel_total : 1213 time to create 1 rle with old method : 0.0014424324035644531 time for calcul the mask position with numpy : 0.007105827331542969 nb_pixel_total : 1492 time to create 1 rle with old method : 0.0017910003662109375 time for calcul the mask position with numpy : 0.006916046142578125 nb_pixel_total : 146 time to create 1 rle with old method : 0.0002396106719970703 time for calcul the mask position with numpy : 0.007832765579223633 nb_pixel_total : 636 time to create 1 rle with old method : 0.0007793903350830078 time for calcul the mask position with numpy : 0.0069658756256103516 nb_pixel_total : 499 time to create 1 rle with old method : 0.0006430149078369141 time for calcul the mask position with numpy : 0.00693511962890625 nb_pixel_total : 1567 time to create 1 rle with old method : 0.0019526481628417969 time for calcul the mask position with numpy : 0.00648808479309082 nb_pixel_total : 1340 time to create 1 rle with old method : 0.0017714500427246094 time for calcul the mask position with numpy : 0.006369352340698242 nb_pixel_total : 782 time to create 1 rle with old method : 0.0009675025939941406 time for calcul the mask position with numpy : 0.01099252700805664 nb_pixel_total : 3051 time to create 1 rle with old method : 0.0035915374755859375 time for calcul the mask position with numpy : 0.006451845169067383 nb_pixel_total : 20 time to create 1 rle with old method : 5.817413330078125e-05 time for calcul the mask position with numpy : 0.006234884262084961 nb_pixel_total : 117 time to create 1 rle with old method : 0.00017189979553222656 time for calcul the mask position with numpy : 0.006303548812866211 nb_pixel_total : 878 time to create 1 rle with old method : 0.001131296157836914 time for calcul the mask position with numpy : 0.0061795711517333984 nb_pixel_total : 29 time to create 1 rle with old method : 7.867813110351562e-05 time for calcul the mask position with numpy : 0.006612300872802734 nb_pixel_total : 1647 time to create 1 rle with old method : 0.0019845962524414062 time for calcul the mask position with numpy : 0.006371498107910156 nb_pixel_total : 21298 time to create 1 rle with old method : 0.024180889129638672 time for calcul the mask position with numpy : 0.0064220428466796875 nb_pixel_total : 295 time to create 1 rle with old method : 0.00037980079650878906 time for calcul the mask position with numpy : 0.006399631500244141 nb_pixel_total : 11 time to create 1 rle with old method : 7.915496826171875e-05 time for calcul the mask position with numpy : 0.010421037673950195 nb_pixel_total : 200 time to create 1 rle with old method : 0.0002446174621582031 time for calcul the mask position with numpy : 0.010473489761352539 nb_pixel_total : 449 time to create 1 rle with old method : 0.0005581378936767578 time for calcul the mask position with numpy : 0.010619401931762695 nb_pixel_total : 570 time to create 1 rle with old method : 0.0006921291351318359 time for calcul the mask position with numpy : 0.012315988540649414 nb_pixel_total : 21 time to create 1 rle with old method : 5.91278076171875e-05 time for calcul the mask position with numpy : 0.012331724166870117 nb_pixel_total : 250 time to create 1 rle with old method : 0.00033473968505859375 time for calcul the mask position with numpy : 0.012615680694580078 nb_pixel_total : 40 time to create 1 rle with old method : 7.176399230957031e-05 time for calcul the mask position with numpy : 0.0131072998046875 nb_pixel_total : 3061 time to create 1 rle with old method : 0.0036308765411376953 time for calcul the mask position with numpy : 0.014178752899169922 nb_pixel_total : 1305 time to create 1 rle with old method : 0.0016434192657470703 time for calcul the mask position with numpy : 0.014568567276000977 nb_pixel_total : 419 time to create 1 rle with old method : 0.00057220458984375 time for calcul the mask position with numpy : 0.013659000396728516 nb_pixel_total : 433 time to create 1 rle with old method : 0.0005686283111572266 time for calcul the mask position with numpy : 0.013547182083129883 nb_pixel_total : 175 time to create 1 rle with old method : 0.0003657341003417969 time for calcul the mask position with numpy : 0.013223409652709961 nb_pixel_total : 102 time to create 1 rle with old method : 0.0002110004425048828 time for calcul the mask position with numpy : 0.014102458953857422 nb_pixel_total : 251 time to create 1 rle with old method : 0.00044417381286621094 time for calcul the mask position with numpy : 0.014687776565551758 nb_pixel_total : 105720 time to create 1 rle with old method : 0.13037776947021484 time for calcul the mask position with numpy : 0.013359785079956055 nb_pixel_total : 605 time to create 1 rle with old method : 0.0008380413055419922 time for calcul the mask position with numpy : 0.014524221420288086 nb_pixel_total : 2971 time to create 1 rle with old method : 0.0035429000854492188 time for calcul the mask position with numpy : 0.014013051986694336 nb_pixel_total : 134 time to create 1 rle with old method : 0.0002162456512451172 time for calcul the mask position with numpy : 0.017882823944091797 nb_pixel_total : 156 time to create 1 rle with old method : 0.00023674964904785156 time for calcul the mask position with numpy : 0.012799501419067383 nb_pixel_total : 1698 time to create 1 rle with old method : 0.0020334720611572266 time for calcul the mask position with numpy : 0.012198686599731445 nb_pixel_total : 406 time to create 1 rle with old method : 0.0005164146423339844 time for calcul the mask position with numpy : 0.01216888427734375 nb_pixel_total : 430 time to create 1 rle with old method : 0.0005507469177246094 time for calcul the mask position with numpy : 0.013129472732543945 nb_pixel_total : 1750 time to create 1 rle with old method : 0.0035467147827148438 time for calcul the mask position with numpy : 0.013716936111450195 nb_pixel_total : 178 time to create 1 rle with old method : 0.0002739429473876953 time for calcul the mask position with numpy : 0.00865793228149414 nb_pixel_total : 1745 time to create 1 rle with old method : 0.0022521018981933594 time for calcul the mask position with numpy : 0.00852656364440918 nb_pixel_total : 134 time to create 1 rle with old method : 0.00018095970153808594 time for calcul the mask position with numpy : 0.008518457412719727 nb_pixel_total : 183 time to create 1 rle with old method : 0.00023174285888671875 time for calcul the mask position with numpy : 0.011869668960571289 nb_pixel_total : 339 time to create 1 rle with old method : 0.0004496574401855469 time for calcul the mask position with numpy : 0.009368181228637695 nb_pixel_total : 7235 time to create 1 rle with old method : 0.008435726165771484 time for calcul the mask position with numpy : 0.008722066879272461 nb_pixel_total : 1807 time to create 1 rle with old method : 0.002621889114379883 time for calcul the mask position with numpy : 0.011556625366210938 nb_pixel_total : 859 time to create 1 rle with old method : 0.0010292530059814453 time for calcul the mask position with numpy : 0.008495092391967773 nb_pixel_total : 419 time to create 1 rle with old method : 0.0004889965057373047 time for calcul the mask position with numpy : 0.008601903915405273 nb_pixel_total : 19 time to create 1 rle with old method : 5.412101745605469e-05 time for calcul the mask position with numpy : 0.010468721389770508 nb_pixel_total : 256 time to create 1 rle with old method : 0.0003712177276611328 time for calcul the mask position with numpy : 0.008859395980834961 nb_pixel_total : 306 time to create 1 rle with old method : 0.0004322528839111328 create new chi : 1.5408124923706055 after preparing all the mask , begin to delete the rle from the crop_hashtag_id => VR 28-11-20 : il faut déplacer cela apres le save_crop_hashtag_ids_obj de la ligne 9514 ! we have 0 chi objets contains the rles time to delete rle : 0.003500699996948242 batch 1 Loaded 96 chid ids of type : 4230 Number RLEs to save : 9697 TO DO : save crop sub photo not yet done ! save time : 0.6127307415008545 nb_obj : 80 nb_hashtags : 5 time to prepare the origin masks : 1.9678692817687988 time for calcul the mask position with numpy : 0.03487658500671387 nb_pixel_total : 1733709 time to create 1 rle with new method : 0.04824519157409668 time for calcul the mask position with numpy : 0.012169122695922852 nb_pixel_total : 13213 time to create 1 rle with old method : 0.01437687873840332 time for calcul the mask position with numpy : 0.011861324310302734 nb_pixel_total : 38 time to create 1 rle with old method : 0.00010776519775390625 time for calcul the mask position with numpy : 0.01263284683227539 nb_pixel_total : 166 time to create 1 rle with old method : 0.0002448558807373047 time for calcul the mask position with numpy : 0.012195110321044922 nb_pixel_total : 313 time to create 1 rle with old method : 0.0003921985626220703 time for calcul the mask position with numpy : 0.01201319694519043 nb_pixel_total : 1004 time to create 1 rle with old method : 0.001249551773071289 time for calcul the mask position with numpy : 0.01251363754272461 nb_pixel_total : 90 time to create 1 rle with old method : 0.00021958351135253906 time for calcul the mask position with numpy : 0.013637781143188477 nb_pixel_total : 2422 time to create 1 rle with old method : 0.0027632713317871094 time for calcul the mask position with numpy : 0.014884471893310547 nb_pixel_total : 2117 time to create 1 rle with old method : 0.0025942325592041016 time for calcul the mask position with numpy : 0.014066457748413086 nb_pixel_total : 257 time to create 1 rle with old method : 0.000362396240234375 time for calcul the mask position with numpy : 0.007309913635253906 nb_pixel_total : 873 time to create 1 rle with old method : 0.0011303424835205078 time for calcul the mask position with numpy : 0.00753474235534668 nb_pixel_total : 51 time to create 1 rle with old method : 0.00014352798461914062 time for calcul the mask position with numpy : 0.0075800418853759766 nb_pixel_total : 177 time to create 1 rle with old method : 0.0002703666687011719 time for calcul the mask position with numpy : 0.006952524185180664 nb_pixel_total : 771 time to create 1 rle with old method : 0.0009226799011230469 time for calcul the mask position with numpy : 0.00687861442565918 nb_pixel_total : 108 time to create 1 rle with old method : 0.00016736984252929688 time for calcul the mask position with numpy : 0.007090330123901367 nb_pixel_total : 12 time to create 1 rle with old method : 9.799003601074219e-05 time for calcul the mask position with numpy : 0.011720418930053711 nb_pixel_total : 1383 time to create 1 rle with old method : 0.0017554759979248047 time for calcul the mask position with numpy : 0.012027263641357422 nb_pixel_total : 6320 time to create 1 rle with old method : 0.006494760513305664 time for calcul the mask position with numpy : 0.012139558792114258 nb_pixel_total : 248 time to create 1 rle with old method : 0.00032520294189453125 time for calcul the mask position with numpy : 0.011963844299316406 nb_pixel_total : 108 time to create 1 rle with old method : 0.00017261505126953125 time for calcul the mask position with numpy : 0.012052297592163086 nb_pixel_total : 5555 time to create 1 rle with old method : 0.006520986557006836 time for calcul the mask position with numpy : 0.011704444885253906 nb_pixel_total : 541 time to create 1 rle with old method : 0.0006754398345947266 time for calcul the mask position with numpy : 0.012983322143554688 nb_pixel_total : 151281 time to create 1 rle with new method : 0.05897331237792969 time for calcul the mask position with numpy : 0.011064767837524414 nb_pixel_total : 804 time to create 1 rle with old method : 0.0011065006256103516 time for calcul the mask position with numpy : 0.011519432067871094 nb_pixel_total : 2197 time to create 1 rle with old method : 0.002516031265258789 time for calcul the mask position with numpy : 0.012119770050048828 nb_pixel_total : 1051 time to create 1 rle with old method : 0.0012660026550292969 time for calcul the mask position with numpy : 0.014044523239135742 nb_pixel_total : 230 time to create 1 rle with old method : 0.00035691261291503906 time for calcul the mask position with numpy : 0.015260457992553711 nb_pixel_total : 1246 time to create 1 rle with old method : 0.001554250717163086 time for calcul the mask position with numpy : 0.014560461044311523 nb_pixel_total : 1239 time to create 1 rle with old method : 0.001546621322631836 time for calcul the mask position with numpy : 0.014809370040893555 nb_pixel_total : 630 time to create 1 rle with old method : 0.0007481575012207031 time for calcul the mask position with numpy : 0.008738279342651367 nb_pixel_total : 676 time to create 1 rle with old method : 0.0007936954498291016 time for calcul the mask position with numpy : 0.009771108627319336 nb_pixel_total : 10 time to create 1 rle with old method : 8.392333984375e-05 time for calcul the mask position with numpy : 0.009865045547485352 nb_pixel_total : 690 time to create 1 rle with old method : 0.0008258819580078125 time for calcul the mask position with numpy : 0.00817108154296875 nb_pixel_total : 772 time to create 1 rle with old method : 0.000993490219116211 time for calcul the mask position with numpy : 0.008513450622558594 nb_pixel_total : 3127 time to create 1 rle with old method : 0.003896474838256836 time for calcul the mask position with numpy : 0.008363962173461914 nb_pixel_total : 143 time to create 1 rle with old method : 0.0003669261932373047 time for calcul the mask position with numpy : 0.008711099624633789 nb_pixel_total : 1468 time to create 1 rle with old method : 0.001871347427368164 time for calcul the mask position with numpy : 0.008365154266357422 nb_pixel_total : 221 time to create 1 rle with old method : 0.0003859996795654297 time for calcul the mask position with numpy : 0.008200407028198242 nb_pixel_total : 719 time to create 1 rle with old method : 0.0009062290191650391 time for calcul the mask position with numpy : 0.008414030075073242 nb_pixel_total : 204 time to create 1 rle with old method : 0.0003027915954589844 time for calcul the mask position with numpy : 0.008202552795410156 nb_pixel_total : 495 time to create 1 rle with old method : 0.0006403923034667969 time for calcul the mask position with numpy : 0.00821232795715332 nb_pixel_total : 325 time to create 1 rle with old method : 0.00046634674072265625 time for calcul the mask position with numpy : 0.008212089538574219 nb_pixel_total : 523 time to create 1 rle with old method : 0.0006577968597412109 time for calcul the mask position with numpy : 0.008237600326538086 nb_pixel_total : 3109 time to create 1 rle with old method : 0.003555774688720703 time for calcul the mask position with numpy : 0.00784611701965332 nb_pixel_total : 269 time to create 1 rle with old method : 0.0003867149353027344 time for calcul the mask position with numpy : 0.008345365524291992 nb_pixel_total : 118 time to create 1 rle with old method : 0.0001995563507080078 time for calcul the mask position with numpy : 0.008408069610595703 nb_pixel_total : 166 time to create 1 rle with old method : 0.00026416778564453125 time for calcul the mask position with numpy : 0.008313894271850586 nb_pixel_total : 230 time to create 1 rle with old method : 0.0003345012664794922 time for calcul the mask position with numpy : 0.009218692779541016 nb_pixel_total : 260 time to create 1 rle with old method : 0.0003592967987060547 time for calcul the mask position with numpy : 0.009047985076904297 nb_pixel_total : 108 time to create 1 rle with old method : 0.0001952648162841797 time for calcul the mask position with numpy : 0.009543657302856445 nb_pixel_total : 106568 time to create 1 rle with old method : 0.12192535400390625 time for calcul the mask position with numpy : 0.014386177062988281 nb_pixel_total : 305 time to create 1 rle with old method : 0.0005090236663818359 time for calcul the mask position with numpy : 0.014255762100219727 nb_pixel_total : 3318 time to create 1 rle with old method : 0.003966093063354492 time for calcul the mask position with numpy : 0.014145851135253906 nb_pixel_total : 2798 time to create 1 rle with old method : 0.0034253597259521484 time for calcul the mask position with numpy : 0.009813308715820312 nb_pixel_total : 132 time to create 1 rle with old method : 0.0002224445343017578 time for calcul the mask position with numpy : 0.009259700775146484 nb_pixel_total : 36 time to create 1 rle with old method : 0.00014281272888183594 time for calcul the mask position with numpy : 0.009805440902709961 nb_pixel_total : 167 time to create 1 rle with old method : 0.00031638145446777344 time for calcul the mask position with numpy : 0.008654594421386719 nb_pixel_total : 7 time to create 1 rle with old method : 7.963180541992188e-05 time for calcul the mask position with numpy : 0.014938116073608398 nb_pixel_total : 36 time to create 1 rle with old method : 0.00011396408081054688 time for calcul the mask position with numpy : 0.015424966812133789 nb_pixel_total : 1672 time to create 1 rle with old method : 0.002073049545288086 time for calcul the mask position with numpy : 0.014492511749267578 nb_pixel_total : 2 time to create 1 rle with old method : 5.841255187988281e-05 time for calcul the mask position with numpy : 0.014599084854125977 nb_pixel_total : 69 time to create 1 rle with old method : 0.00014853477478027344 time for calcul the mask position with numpy : 0.014520406723022461 nb_pixel_total : 428 time to create 1 rle with old method : 0.0007174015045166016 time for calcul the mask position with numpy : 0.015097856521606445 nb_pixel_total : 379 time to create 1 rle with old method : 0.0004978179931640625 time for calcul the mask position with numpy : 0.014909029006958008 nb_pixel_total : 378 time to create 1 rle with old method : 0.0005180835723876953 time for calcul the mask position with numpy : 0.014890193939208984 nb_pixel_total : 1710 time to create 1 rle with old method : 0.0020210742950439453 time for calcul the mask position with numpy : 0.014849424362182617 nb_pixel_total : 185 time to create 1 rle with old method : 0.0002906322479248047 time for calcul the mask position with numpy : 0.01436471939086914 nb_pixel_total : 2635 time to create 1 rle with old method : 0.0030083656311035156 time for calcul the mask position with numpy : 0.01426386833190918 nb_pixel_total : 127 time to create 1 rle with old method : 0.00020456314086914062 time for calcul the mask position with numpy : 0.014161825180053711 nb_pixel_total : 446 time to create 1 rle with old method : 0.0005497932434082031 time for calcul the mask position with numpy : 0.014061212539672852 nb_pixel_total : 127 time to create 1 rle with old method : 0.0002124309539794922 time for calcul the mask position with numpy : 0.013957977294921875 nb_pixel_total : 271 time to create 1 rle with old method : 0.00035762786865234375 time for calcul the mask position with numpy : 0.014070272445678711 nb_pixel_total : 74 time to create 1 rle with old method : 0.00023317337036132812 time for calcul the mask position with numpy : 0.013971328735351562 nb_pixel_total : 7580 time to create 1 rle with old method : 0.008117914199829102 time for calcul the mask position with numpy : 0.015064001083374023 nb_pixel_total : 877 time to create 1 rle with old method : 0.0011179447174072266 time for calcul the mask position with numpy : 0.02453446388244629 nb_pixel_total : 359 time to create 1 rle with old method : 0.0005040168762207031 time for calcul the mask position with numpy : 0.015666961669921875 nb_pixel_total : 313 time to create 1 rle with old method : 0.0004363059997558594 time for calcul the mask position with numpy : 0.015515565872192383 nb_pixel_total : 176 time to create 1 rle with old method : 0.00027370452880859375 time for calcul the mask position with numpy : 0.013910531997680664 nb_pixel_total : 319 time to create 1 rle with old method : 0.00043582916259765625 time for calcul the mask position with numpy : 0.013567447662353516 nb_pixel_total : 315 time to create 1 rle with old method : 0.0003948211669921875 time for calcul the mask position with numpy : 0.013823270797729492 nb_pixel_total : 4 time to create 1 rle with old method : 6.222724914550781e-05 create new chi : 1.3106977939605713 after preparing all the mask , begin to delete the rle from the crop_hashtag_id => VR 28-11-20 : il faut déplacer cela apres le save_crop_hashtag_ids_obj de la ligne 9514 ! we have 0 chi objets contains the rles time to delete rle : 0.002997875213623047 batch 1 Loaded 87 chid ids of type : 4230 Number RLEs to save : 8763 TO DO : save crop sub photo not yet done ! save time : 0.5262069702148438 nb_obj : 80 nb_hashtags : 5 time to prepare the origin masks : 1.5565016269683838 time for calcul the mask position with numpy : 0.02980327606201172 nb_pixel_total : 1836916 time to create 1 rle with new method : 0.1506960391998291 time for calcul the mask position with numpy : 0.012355804443359375 nb_pixel_total : 934 time to create 1 rle with old method : 0.001565694808959961 time for calcul the mask position with numpy : 0.012820243835449219 nb_pixel_total : 31 time to create 1 rle with old method : 7.486343383789062e-05 time for calcul the mask position with numpy : 0.012996673583984375 nb_pixel_total : 4206 time to create 1 rle with old method : 0.007175922393798828 time for calcul the mask position with numpy : 0.01338505744934082 nb_pixel_total : 218 time to create 1 rle with old method : 0.0004425048828125 time for calcul the mask position with numpy : 0.014591455459594727 nb_pixel_total : 126 time to create 1 rle with old method : 0.0003180503845214844 time for calcul the mask position with numpy : 0.013701915740966797 nb_pixel_total : 1825 time to create 1 rle with old method : 0.002190828323364258 time for calcul the mask position with numpy : 0.010365962982177734 nb_pixel_total : 1079 time to create 1 rle with old method : 0.0014348030090332031 time for calcul the mask position with numpy : 0.010699033737182617 nb_pixel_total : 2283 time to create 1 rle with old method : 0.00279998779296875 time for calcul the mask position with numpy : 0.010577917098999023 nb_pixel_total : 10 time to create 1 rle with old method : 4.506111145019531e-05 time for calcul the mask position with numpy : 0.010538339614868164 nb_pixel_total : 1959 time to create 1 rle with old method : 0.002429485321044922 time for calcul the mask position with numpy : 0.011492729187011719 nb_pixel_total : 45106 time to create 1 rle with old method : 0.05709671974182129 time for calcul the mask position with numpy : 0.011162996292114258 nb_pixel_total : 269 time to create 1 rle with old method : 0.0003566741943359375 time for calcul the mask position with numpy : 0.010495185852050781 nb_pixel_total : 393 time to create 1 rle with old method : 0.0004951953887939453 time for calcul the mask position with numpy : 0.006348609924316406 nb_pixel_total : 745 time to create 1 rle with old method : 0.0009090900421142578 time for calcul the mask position with numpy : 0.006338357925415039 nb_pixel_total : 723 time to create 1 rle with old method : 0.0009038448333740234 time for calcul the mask position with numpy : 0.010123491287231445 nb_pixel_total : 292 time to create 1 rle with old method : 0.0003731250762939453 time for calcul the mask position with numpy : 0.006488323211669922 nb_pixel_total : 3690 time to create 1 rle with old method : 0.004837989807128906 time for calcul the mask position with numpy : 0.010121822357177734 nb_pixel_total : 6157 time to create 1 rle with old method : 0.006983041763305664 time for calcul the mask position with numpy : 0.010559320449829102 nb_pixel_total : 170 time to create 1 rle with old method : 0.0002741813659667969 time for calcul the mask position with numpy : 0.011757135391235352 nb_pixel_total : 1417 time to create 1 rle with old method : 0.0016710758209228516 time for calcul the mask position with numpy : 0.01085805892944336 nb_pixel_total : 221 time to create 1 rle with old method : 0.0002818107604980469 time for calcul the mask position with numpy : 0.01086282730102539 nb_pixel_total : 479 time to create 1 rle with old method : 0.0005910396575927734 time for calcul the mask position with numpy : 0.006649017333984375 nb_pixel_total : 2075 time to create 1 rle with old method : 0.002521514892578125 time for calcul the mask position with numpy : 0.006514787673950195 nb_pixel_total : 691 time to create 1 rle with old method : 0.0008363723754882812 time for calcul the mask position with numpy : 0.006344318389892578 nb_pixel_total : 1224 time to create 1 rle with old method : 0.0014705657958984375 time for calcul the mask position with numpy : 0.006612539291381836 nb_pixel_total : 905 time to create 1 rle with old method : 0.0010788440704345703 time for calcul the mask position with numpy : 0.007050514221191406 nb_pixel_total : 2190 time to create 1 rle with old method : 0.0026044845581054688 time for calcul the mask position with numpy : 0.00645899772644043 nb_pixel_total : 7362 time to create 1 rle with old method : 0.008506298065185547 time for calcul the mask position with numpy : 0.006405353546142578 nb_pixel_total : 1179 time to create 1 rle with old method : 0.0014643669128417969 time for calcul the mask position with numpy : 0.0066912174224853516 nb_pixel_total : 793 time to create 1 rle with old method : 0.0009851455688476562 time for calcul the mask position with numpy : 0.006907224655151367 nb_pixel_total : 256 time to create 1 rle with old method : 0.00045680999755859375 time for calcul the mask position with numpy : 0.007739543914794922 nb_pixel_total : 950 time to create 1 rle with old method : 0.0012962818145751953 time for calcul the mask position with numpy : 0.007279157638549805 nb_pixel_total : 710 time to create 1 rle with old method : 0.0008573532104492188 time for calcul the mask position with numpy : 0.007233381271362305 nb_pixel_total : 1557 time to create 1 rle with old method : 0.0030269622802734375 time for calcul the mask position with numpy : 0.008513689041137695 nb_pixel_total : 3130 time to create 1 rle with old method : 0.005299091339111328 time for calcul the mask position with numpy : 0.008135080337524414 nb_pixel_total : 1656 time to create 1 rle with old method : 0.0028781890869140625 time for calcul the mask position with numpy : 0.008035898208618164 nb_pixel_total : 1597 time to create 1 rle with old method : 0.0026350021362304688 time for calcul the mask position with numpy : 0.0077173709869384766 nb_pixel_total : 216 time to create 1 rle with old method : 0.0004246234893798828 time for calcul the mask position with numpy : 0.013036489486694336 nb_pixel_total : 13 time to create 1 rle with old method : 9.369850158691406e-05 time for calcul the mask position with numpy : 0.012635231018066406 nb_pixel_total : 555 time to create 1 rle with old method : 0.0007460117340087891 time for calcul the mask position with numpy : 0.0167999267578125 nb_pixel_total : 32 time to create 1 rle with old method : 7.510185241699219e-05 time for calcul the mask position with numpy : 0.01109170913696289 nb_pixel_total : 2738 time to create 1 rle with old method : 0.005647182464599609 time for calcul the mask position with numpy : 0.012771129608154297 nb_pixel_total : 182 time to create 1 rle with old method : 0.0002570152282714844 time for calcul the mask position with numpy : 0.011234283447265625 nb_pixel_total : 70 time to create 1 rle with old method : 0.00010085105895996094 time for calcul the mask position with numpy : 0.010702848434448242 nb_pixel_total : 449 time to create 1 rle with old method : 0.0005545616149902344 time for calcul the mask position with numpy : 0.010806083679199219 nb_pixel_total : 614 time to create 1 rle with old method : 0.0007534027099609375 time for calcul the mask position with numpy : 0.010487794876098633 nb_pixel_total : 260 time to create 1 rle with old method : 0.0003464221954345703 time for calcul the mask position with numpy : 0.010578393936157227 nb_pixel_total : 3 time to create 1 rle with old method : 2.574920654296875e-05 time for calcul the mask position with numpy : 0.010374307632446289 nb_pixel_total : 157 time to create 1 rle with old method : 0.00021576881408691406 time for calcul the mask position with numpy : 0.010368108749389648 nb_pixel_total : 224 time to create 1 rle with old method : 0.00028896331787109375 time for calcul the mask position with numpy : 0.01062321662902832 nb_pixel_total : 893 time to create 1 rle with old method : 0.0010771751403808594 time for calcul the mask position with numpy : 0.01035165786743164 nb_pixel_total : 320 time to create 1 rle with old method : 0.0003914833068847656 time for calcul the mask position with numpy : 0.010010957717895508 nb_pixel_total : 104 time to create 1 rle with old method : 0.00015306472778320312 time for calcul the mask position with numpy : 0.011152982711791992 nb_pixel_total : 106746 time to create 1 rle with old method : 0.11664986610412598 time for calcul the mask position with numpy : 0.010656356811523438 nb_pixel_total : 414 time to create 1 rle with old method : 0.0005681514739990234 time for calcul the mask position with numpy : 0.010474443435668945 nb_pixel_total : 2792 time to create 1 rle with old method : 0.0033452510833740234 time for calcul the mask position with numpy : 0.010576486587524414 nb_pixel_total : 153 time to create 1 rle with old method : 0.00020766258239746094 time for calcul the mask position with numpy : 0.010302066802978516 nb_pixel_total : 235 time to create 1 rle with old method : 0.0003151893615722656 time for calcul the mask position with numpy : 0.010172128677368164 nb_pixel_total : 1648 time to create 1 rle with old method : 0.0019137859344482422 time for calcul the mask position with numpy : 0.010221719741821289 nb_pixel_total : 411 time to create 1 rle with old method : 0.0005354881286621094 time for calcul the mask position with numpy : 0.01016998291015625 nb_pixel_total : 571 time to create 1 rle with old method : 0.0007064342498779297 time for calcul the mask position with numpy : 0.010240793228149414 nb_pixel_total : 1852 time to create 1 rle with old method : 0.002182483673095703 time for calcul the mask position with numpy : 0.016290664672851562 nb_pixel_total : 151 time to create 1 rle with old method : 0.0003159046173095703 time for calcul the mask position with numpy : 0.012705802917480469 nb_pixel_total : 143 time to create 1 rle with old method : 0.00029015541076660156 time for calcul the mask position with numpy : 0.011944055557250977 nb_pixel_total : 2449 time to create 1 rle with old method : 0.0040547847747802734 time for calcul the mask position with numpy : 0.01155710220336914 nb_pixel_total : 138 time to create 1 rle with old method : 0.0001842975616455078 time for calcul the mask position with numpy : 0.010092973709106445 nb_pixel_total : 462 time to create 1 rle with old method : 0.0005688667297363281 time for calcul the mask position with numpy : 0.010097265243530273 nb_pixel_total : 129 time to create 1 rle with old method : 0.000179290771484375 time for calcul the mask position with numpy : 0.01005864143371582 nb_pixel_total : 175 time to create 1 rle with old method : 0.000232696533203125 time for calcul the mask position with numpy : 0.010387182235717773 nb_pixel_total : 461 time to create 1 rle with old method : 0.0006093978881835938 time for calcul the mask position with numpy : 0.010347366333007812 nb_pixel_total : 623 time to create 1 rle with old method : 0.0007832050323486328 time for calcul the mask position with numpy : 0.010895490646362305 nb_pixel_total : 7733 time to create 1 rle with old method : 0.008843660354614258 time for calcul the mask position with numpy : 0.010244607925415039 nb_pixel_total : 1 time to create 1 rle with old method : 2.1696090698242188e-05 time for calcul the mask position with numpy : 0.010136127471923828 nb_pixel_total : 1975 time to create 1 rle with old method : 0.002427816390991211 time for calcul the mask position with numpy : 0.010144233703613281 nb_pixel_total : 253 time to create 1 rle with old method : 0.0003273487091064453 time for calcul the mask position with numpy : 0.010307550430297852 nb_pixel_total : 738 time to create 1 rle with old method : 0.0009119510650634766 time for calcul the mask position with numpy : 0.010178089141845703 nb_pixel_total : 40 time to create 1 rle with old method : 0.000110626220703125 time for calcul the mask position with numpy : 0.010100603103637695 nb_pixel_total : 280 time to create 1 rle with old method : 0.00034809112548828125 time for calcul the mask position with numpy : 0.010066747665405273 nb_pixel_total : 369 time to create 1 rle with old method : 0.0004515647888183594 time for calcul the mask position with numpy : 0.009994268417358398 nb_pixel_total : 304 time to create 1 rle with old method : 0.00037479400634765625 create new chi : 1.2864577770233154 after preparing all the mask , begin to delete the rle from the crop_hashtag_id => VR 28-11-20 : il faut déplacer cela apres le save_crop_hashtag_ids_obj de la ligne 9514 ! we have 0 chi objets contains the rles time to delete rle : 0.001833200454711914 batch 1 Loaded 87 chid ids of type : 4230 Number RLEs to save : 9015 TO DO : save crop sub photo not yet done ! save time : 0.5624446868896484 map_output_result : {1332404633: (0.0, 'Should be the crop_list due to order', 0.0), 1332404630: (0.0, 'Should be the crop_list due to order', 0.0), 1332404627: (0.0, 'Should be the crop_list due to order', 0.0), 1332404610: (0.0, 'Should be the crop_list due to order', 0.0), 1332404608: (0.0, 'Should be the crop_list due to order', 0.0), 1332404605: (0.0, 'Should be the crop_list due to order', 0.0), 1332404602: (0.0, 'Should be the crop_list due to order', 0.0), 1332404599: (0.0, 'Should be the crop_list due to order', 0.0), 1332404596: (0.0, 'Should be the crop_list due to order', 0.0), 1332404585: (0.0, 'Should be the crop_list due to order', 0.0), 1332404583: (0.0, 'Should be the crop_list due to order', 0.0), 1332404581: (0.0, 'Should be the crop_list due to order', 0.0), 1332404578: (0.0, 'Should be the crop_list due to order', 0.0), 1332404575: (0.0, 'Should be the crop_list due to order', 0.0), 1332404571: (0.0, 'Should be the crop_list due to order', 0.0), 1332404558: (0.0, 'Should be the crop_list due to order', 0.0), 1332404555: (0.0, 'Should be the crop_list due to order', 0.0), 1332404550: (0.0, 'Should be the crop_list due to order', 0.0), 1332404545: (0.0, 'Should be the crop_list due to order', 0.0), 1332404540: (0.0, 'Should be the crop_list due to order', 0.0), 1332404535: (0.0, 'Should be the crop_list due to order', 0.0)} End step rle-unique-nms Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : rle_unique_nms_with_priority we use saveGeneral [1332404633, 1332404630, 1332404627, 1332404610, 1332404608, 1332404605, 1332404602, 1332404599, 1332404596, 1332404585, 1332404583, 1332404581, 1332404578, 1332404575, 1332404571, 1332404558, 1332404555, 1332404550, 1332404545, 1332404540, 1332404535] Looping around the photos to save general results len do output : 21 /1332404633.Didn't retrieve data . /1332404630.Didn't retrieve data . /1332404627.Didn't retrieve data . /1332404610.Didn't retrieve data . /1332404608.Didn't retrieve data . /1332404605.Didn't retrieve data . /1332404602.Didn't retrieve data . /1332404599.Didn't retrieve data . /1332404596.Didn't retrieve data . /1332404585.Didn't retrieve data . /1332404583.Didn't retrieve data . /1332404581.Didn't retrieve data . /1332404578.Didn't retrieve data . /1332404575.Didn't retrieve data . /1332404571.Didn't retrieve data . /1332404558.Didn't retrieve data . /1332404555.Didn't retrieve data . /1332404550.Didn't retrieve data . /1332404545.Didn't retrieve data . /1332404540.Didn't retrieve data . /1332404535.Didn't retrieve data . before output type Used above Here is an output not treated by saveGeneral : Managing all output in save final without adding information in the mtr_datou_result ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404633', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404630', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404627', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404610', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404608', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404605', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404602', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404599', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404596', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404585', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404583', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404581', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404578', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404575', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404571', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404558', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404555', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404550', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404545', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404540', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404535', None, None, None, None, None, '2524174') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 63 time used for this insertion : 0.02228236198425293 save_final save missing photos in datou_result : time spend for datou_step_exec : 88.76097226142883 time spend to save output : 0.023379802703857422 total time spend for step 4 : 88.78435206413269 step5:crop_condition Wed Feb 12 08:51:12 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure some photos are not treated, begin crop_condition Loading chi in step crop with photo_hashtag_type : 4230 Loading chi in step crop for list_pids : 21 ! batch 1 Loaded 1952 chid ids of type : 4230 begin to crop the class : papier param for this class : {'min_score': 0.6} filtre for class : papier hashtag_id of this class : 492668766 Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! map_result returned by crop_photo_return_map_crop : length : 751 About to insert : list_path_to_insert length 751 new photo from crops ! About to upload 751 photos upload in portfolio : 4869462 init cache_photo without model_param we have 751 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1739346684_2473413 we have uploaded 751 photos in the portfolio 4869462 time of upload the photos Elapsed time : 163.20737981796265 we have finished the crop for the class : papier begin to crop the class : carton param for this class : {'min_score': 0.6} filtre for class : carton hashtag_id of this class : 492774966 Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! map_result returned by crop_photo_return_map_crop : length : 236 About to insert : list_path_to_insert length 236 new photo from crops ! About to upload 236 photos upload in portfolio : 4869462 init cache_photo without model_param we have 236 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1739346851_2473413 we have uploaded 236 photos in the portfolio 4869462 time of upload the photos Elapsed time : 51.46871209144592 we have finished the crop for the class : carton begin to crop the class : metal param for this class : {'min_score': 0.6} filtre for class : metal hashtag_id of this class : 492628673 begin to crop the class : pet_clair param for this class : {'min_score': 0.6} filtre for class : pet_clair hashtag_id of this class : 2107755846 Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! map_result returned by crop_photo_return_map_crop : length : 127 About to insert : list_path_to_insert length 127 new photo from crops ! About to upload 127 photos upload in portfolio : 4869462 init cache_photo without model_param we have 127 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1739346906_2473413 we have uploaded 127 photos in the portfolio 4869462 time of upload the photos Elapsed time : 32.88856530189514 we have finished the crop for the class : pet_clair begin to crop the class : autre param for this class : {'min_score': 0.6} filtre for class : autre hashtag_id of this class : 494826614 Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! map_result returned by crop_photo_return_map_crop : length : 242 About to insert : list_path_to_insert length 242 new photo from crops ! About to upload 242 photos upload in portfolio : 4869462 init cache_photo without model_param we have 242 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1739346943_2473413 we have uploaded 242 photos in the portfolio 4869462 time of upload the photos Elapsed time : 55.868696212768555 we have finished the crop for the class : autre begin to crop the class : pehd param for this class : {'min_score': 0.6} filtre for class : pehd hashtag_id of this class : 628944319 begin to crop the class : pet_fonce param for this class : {'min_score': 0.6} filtre for class : pet_fonce hashtag_id of this class : 2107755900 Next one ! Next one ! Next one ! Next one ! map_result returned by crop_photo_return_map_crop : length : 4 About to insert : list_path_to_insert length 4 new photo from crops ! About to upload 4 photos upload in portfolio : 4869462 init cache_photo without model_param we have 4 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1739346999_2473413 we have uploaded 4 photos in the portfolio 4869462 time of upload the photos Elapsed time : 1.2413291931152344 we have finished the crop for the class : pet_fonce delete rles for these photos Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : crop_condition we use saveGeneral [1332404633, 1332404630, 1332404627, 1332404610, 1332404608, 1332404605, 1332404602, 1332404599, 1332404596, 1332404585, 1332404583, 1332404581, 1332404578, 1332404575, 1332404571, 1332404558, 1332404555, 1332404550, 1332404545, 1332404540, 1332404535] Looping around the photos to save general results len do output : 1360 /1337040446Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040448Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040449Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040450Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040451Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040452Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040453Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040454Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040455Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040456Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040457Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040458Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040459Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040460Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040461Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040462Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040463Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040464Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040465Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040466Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040467Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040468Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040469Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040470Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040471Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040472Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040473Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040474Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040475Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040476Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040477Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040478Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040479Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040480Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040481Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040482Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040483Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040485Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040486Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040487Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040488Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040489Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040491Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040492Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040493Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040494Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040495Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040496Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040497Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040498Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040499Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040500Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040501Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040502Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040503Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040504Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040505Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040506Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040507Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040508Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040509Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040510Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040511Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040512Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040513Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040514Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040515Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040516Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040517Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040518Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040519Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040520Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040521Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040522Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040523Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040524Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040525Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040526Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040527Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040528Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040529Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040530Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040532Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040533Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040534Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040535Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040536Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040537Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040538Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040539Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040540Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040541Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040542Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040543Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040544Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040545Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040546Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040547Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040548Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040549Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040550Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040551Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040552Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040553Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040554Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040555Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040557Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040558Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040559Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040560Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040561Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040562Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040563Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040564Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040565Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040566Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040567Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040568Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040569Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040570Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040571Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040572Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040573Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040574Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040575Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040576Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040577Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040578Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040579Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040580Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040581Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040582Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040583Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040584Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040585Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040586Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040587Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040588Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040589Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040590Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040591Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040592Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040593Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040594Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040595Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040596Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040597Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040598Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040599Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040600Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040601Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040602Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040603Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040604Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040605Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040606Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040607Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040608Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040609Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040611Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040612Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040613Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040614Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040615Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040617Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040618Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040619Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040620Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040622Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040623Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040624Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040625Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040626Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040627Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040628Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040629Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040630Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040631Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040632Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040633Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040634Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040635Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040636Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040637Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040638Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040639Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040640Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040641Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040642Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040643Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040644Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040645Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040646Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040647Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040648Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040649Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040650Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040651Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040652Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040653Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040654Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040655Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040656Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040657Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040658Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040659Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040660Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040661Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040662Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040663Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040664Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040665Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040666Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040667Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040668Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040669Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040670Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040672Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040673Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040674Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040675Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040677Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040678Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040679Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040680Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040681Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040682Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040683Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040684Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040685Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040686Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040687Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040688Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040689Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040690Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040691Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040693Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040694Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040695Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040696Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040697Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040698Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040699Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040700Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040701Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040702Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040703Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040704Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040705Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040706Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040707Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040708Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040709Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040710Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040711Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040712Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040713Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040714Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040715Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040716Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040717Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040718Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040720Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040721Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040722Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040723Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040724Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040725Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040726Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040727Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040728Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040729Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040730Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040731Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040732Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040733Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040734Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040735Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040736Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040737Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040738Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040739Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040740Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040741Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040742Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040743Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040744Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040745Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040746Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040747Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040748Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040749Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040751Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040752Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040753Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040754Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040755Didn't retrieve data 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retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040769Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040770Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040771Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040772Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040773Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040774Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040775Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040776Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040777Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040778Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040779Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040780Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040781Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040782Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040783Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040784Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040785Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040786Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040787Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040788Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040789Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040790Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040791Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040792Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040793Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040794Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040795Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040796Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040798Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040799Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040800Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040801Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040802Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040803Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040804Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040805Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040806Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040807Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040808Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040809Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040810Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040811Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040812Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040813Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040814Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040815Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040816Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040817Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040818Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040819Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337040820Didn't retrieve data 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retrieve data . /1337041970Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . before output type Here is an output not treated by saveGeneral : Here is an output not treated by saveGeneral : Here is an output not treated by saveGeneral : Managing all output in save final without adding information in the mtr_datou_result ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404633', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404630', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404627', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404610', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404608', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404605', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404602', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404599', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404596', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404585', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404583', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404581', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404578', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404575', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404571', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404558', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404555', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404550', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404545', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404540', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404535', None, None, None, None, None, '2524174') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 4101 time used for this insertion : 0.1894516944885254 save_final save missing photos in datou_result : time spend for datou_step_exec : 328.4319341182709 time spend to save output : 0.2196662425994873 total time spend for step 5 : 328.65160036087036 step6:thcl Wed Feb 12 08:56:41 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 VR 22-3-18 : For now we do not clean correctly the datou structure Beginning of datou step Thcl ! we are using the classfication for only one thcl 3237 time to import caffe and check if the image exist : 0.08044695854187012 time to convert the images to numpy array : 0.5085256099700928 time to import caffe and check if the image exist : 0.07597494125366211 time to convert the images to numpy array : 0.5205285549163818 time to import caffe and check if the image exist : 0.08136582374572754 time to convert the images to numpy array : 0.5170667171478271 time to import caffe and check if the image exist : 0.07553839683532715 time to convert the images to numpy array : 0.5296285152435303 time to import caffe and check if the image exist : 0.08250832557678223 time to convert the images to numpy array : 0.5292713642120361 time to import caffe and check if the image exist : 0.07299971580505371 time to convert the images to numpy array : 0.5431716442108154 time to import caffe and check if the image exist : 0.06472325325012207 time to convert the images to numpy array : 0.5533778667449951 time to import caffe and check if the image exist : 0.09032511711120605 time to convert the images to numpy array : 0.5298807621002197 time to import caffe and check if the image exist : 0.09771370887756348 time to convert the images to numpy array : 0.5231978893280029 time to import caffe and check if the image exist : 0.10339069366455078 time to convert the images to numpy array : 0.5236392021179199 total time to convert the images to numpy array : 0.8843188285827637 list photo_ids error: [] list photo_ids correct : [1337040869, 1337040870, 1337040871, 1337040872, 1337040873, 1337040874, 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1337041242, 1337041243, 1337041244, 1337041245, 1337041246, 1337041247, 1337041248, 1337041249, 1337041250, 1337041251, 1337041252, 1337041253, 1337041254, 1337041255, 1337041256, 1337041257, 1337041258, 1337041259, 1337041260, 1337041261, 1337041262, 1337041263, 1337041264, 1337041265, 1337041266, 1337041267, 1337041268, 1337041269, 1337041270, 1337041271, 1337041272, 1337041273, 1337041274, 1337041275, 1337041276, 1337041277, 1337041278, 1337041279, 1337041280, 1337041281, 1337041282, 1337041283, 1337041284, 1337041285, 1337041286, 1337041287, 1337041288, 1337041289, 1337041290, 1337041291, 1337041292, 1337041293, 1337041294, 1337041295, 1337041296, 1337041297, 1337041435, 1337041436, 1337041437, 1337041438, 1337041439, 1337041440, 1337041441, 1337041442, 1337041443, 1337041444, 1337041445, 1337041446, 1337041447, 1337041448, 1337041449, 1337041450, 1337041451, 1337041452, 1337041453, 1337041454, 1337041455, 1337041456, 1337041457, 1337041459, 1337041461, 1337041463, 1337041465, 1337041467, 1337041469, 1337041471, 1337041473, 1337041475, 1337041477, 1337041479, 1337041481, 1337041495, 1337041496, 1337041500, 1337041501, 1337041502, 1337041503, 1337041504, 1337041505, 1337041506, 1337041507, 1337041508, 1337041509, 1337041510, 1337041511, 1337041512, 1337041513, 1337041514, 1337041515, 1337041516, 1337041517, 1337041518, 1337041519, 1337041520, 1337041521, 1337041522, 1337041523, 1337041524, 1337041525, 1337041526, 1337041527, 1337041528, 1337041529, 1337041530, 1337041531, 1337041532, 1337041533, 1337041535, 1337041536, 1337041537, 1337041538, 1337041539, 1337041540, 1337041541, 1337041542, 1337041543, 1337041544, 1337041545, 1337041546, 1337041547, 1337041548, 1337041549, 1337041550, 1337041551, 1337041552, 1337041553, 1337041554, 1337041555, 1337041556, 1337041557, 1337041558, 1337041559, 1337041560, 1337041561, 1337041562, 1337041563, 1337041564, 1337041565, 1337041566, 1337041567, 1337041568, 1337041569, 1337041570, 1337041571, 1337041572, 1337041573, 1337041574, 1337041575, 1337041576, 1337041577, 1337041578, 1337041579, 1337041580, 1337041581, 1337041582, 1337041583, 1337041584, 1337041585, 1337041586, 1337041587, 1337041588, 1337041589, 1337041590, 1337041591, 1337041592, 1337041593, 1337041594, 1337041595, 1337041596, 1337041597, 1337041598, 1337041599] number of photos to traite : 1360 try to delete the photos incorrect in DB tagging for thcl : 3237 To do loadFromThcl(), then load ParamDescType : thcl3237 thcls : [{'id': 3237, 'mtr_user_id': 31, 'name': 'learn_rubbia_refus_2500', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'Carton,Film_plastique,PEHD,PET_clair,PET_fonce,Papier,Tetrapak,flou,mal_croppe,metal,refus', 'svm_portfolios_learning': '4865689,4865690,4865686,4865684,4865685,4865688,4865691,4865693,4865692,4865687,4865683', 'photo_hashtag_type': 4158, 'photo_desc_type': 5561, 'type_classification': 'caffe', 'hashtag_id_list': '492774966,2107756122,628944319,2107755846,2107755900,492668766,609991870,492777938,2107755527,492628673,538914404'}] thcl {'id': 3237, 'mtr_user_id': 31, 'name': 'learn_rubbia_refus_2500', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'Carton,Film_plastique,PEHD,PET_clair,PET_fonce,Papier,Tetrapak,flou,mal_croppe,metal,refus', 'svm_portfolios_learning': '4865689,4865690,4865686,4865684,4865685,4865688,4865691,4865693,4865692,4865687,4865683', 'photo_hashtag_type': 4158, 'photo_desc_type': 5561, 'type_classification': 'caffe', 'hashtag_id_list': '492774966,2107756122,628944319,2107755846,2107755900,492668766,609991870,492777938,2107755527,492628673,538914404'} Update svm_hashtag_type_desc : 5561 FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (5561, 'learn_rubbia_refus_2500', 2048, 2048, 'learn_rubbia_refus_2500', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 3, datetime.datetime(2021, 12, 2, 19, 10, 8), datetime.datetime(2021, 12, 2, 19, 10, 8)) To loadFromThcl() : net_5561 begin to check gpu status inside check gpu memory l 3637 free memory gpu now : 10774 max_wait_temp : 1 max_wait : 0 FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (5561, 'learn_rubbia_refus_2500', 2048, 2048, 'learn_rubbia_refus_2500', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 3, datetime.datetime(2021, 12, 2, 19, 10, 8), datetime.datetime(2021, 12, 2, 19, 10, 8)) None mean_file_type : mean_file_path : prototxt_file_path : model : learn_rubbia_refus_2500 Inside get_net Inside get_net before cache_data_model model_param file didn't exist Inside get_net before CDM.load_model_par_type model_name : learn_rubbia_refus_2500 model_type : caffe list file need : ['caffemodel', 'deploy_conv_normal.prototxt', 'deploy_fc.prototxt', 'deploy.prototxt', 'mean.npy', 'synset_words.txt'] file exist in s3 : ['caffemodel', 'deploy.prototxt', 'mean.npy', 'synset_words.txt'] file manque in s3 : ['deploy_conv_normal.prototxt', 'deploy_fc.prototxt'] local folder : /data/models_weight/learn_rubbia_refus_2500 /data/models_weight/learn_rubbia_refus_2500/caffemodel size_local : 94358479 size in s3 : 94358479 create time local : 2021-12-03 18:29:39 create time in s3 : 2021-12-02 17:49:16 caffemodel already exist and didn't need to update /data/models_weight/learn_rubbia_refus_2500/deploy.prototxt size_local : 32544 size in s3 : 32544 create time local : 2021-12-03 18:29:39 create time in s3 : 2021-12-02 17:49:15 deploy.prototxt already exist and didn't need to update /data/models_weight/learn_rubbia_refus_2500/mean.npy size_local : 1572992 size in s3 : 1572992 create time local : 2021-12-03 18:29:40 create time in s3 : 2021-12-02 18:09:52 mean.npy already exist and didn't need to update /data/models_weight/learn_rubbia_refus_2500/synset_words.txt size_local : 334 size in s3 : 334 create time local : 2021-12-03 18:29:40 create time in s3 : 2021-12-02 18:10:06 synset_words.txt already exist and didn't need to update Inside get_net after CDM.load_model_par_type After if not only_with_local_cache: /home/admin/workarea/install/darknet/:/home/admin/workarea/git/Velours/python:/home/admin/workarea/install/caffe_frcnn_python3/py-faster-rcnn/caffe-fast-rcnn/python:/home/admin/mtr/.credentials:/home/admin/workarea/install/caffe/python:/home/admin/workarea/install/caffe_frcnn/py-faster-rcnn/tools/:/home/admin/workarea/git/fotonowerpip/:/home/admin/workarea/install/segment-anything:/home/admin//workarea/git/pyfvs/:/home/admin/workarea/git/apy/ Here before set mode gpu Doing nothing but we could set mode gpu after set mode gpu prototxt_filename : /data/models_weight/learn_rubbia_refus_2500/deploy.prototxt caffemodel_filename : /data/models_weight/learn_rubbia_refus_2500/caffemodel now we set caffe to gpu mode before predict begin to check gpu status inside check gpu memory l 3637 free memory gpu now : 10555 max_wait_temp : 1 max_wait : 0 dict_keys(['prob', 'pool5']) time used to do the prepocess of the images : 6.380622148513794 time used to do the prediction : 4.5206968784332275 save descriptor for thcl : 3237 time to traite the descriptors : 7.565124750137329 Catched exception ! Connect or reconnect ! storage_type for insertDescriptorsMulti : 3 To insert : 1337040869 To insert : 1337040870 To insert : 1337040871 To insert : 1337040872 To insert : 1337040873 To insert : 1337040874 To insert : 1337040875 To insert : 1337040876 To insert : 1337040877 To insert : 1337040878 To insert : 1337040879 To insert : 1337040880 To insert : 1337040881 To insert : 1337040882 To insert : 1337040883 To insert : 1337040884 To insert : 1337040886 To insert : 1337040887 To insert : 1337040888 To insert : 1337040889 To insert : 1337040890 To insert : 1337040891 To insert : 1337040892 To insert : 1337040893 To insert : 1337040894 To insert : 1337040895 To insert : 1337040896 To insert : 1337040897 To insert : 1337040898 To insert : 1337040899 To insert : 1337040900 To insert : 1337040901 To insert : 1337040902 To insert : 1337040903 To insert : 1337040904 To insert : 1337040905 To insert : 1337040906 To insert : 1337040907 To insert : 1337040908 To insert : 1337040909 To insert : 1337040910 To insert : 1337040911 To insert : 1337040912 To insert : 1337040913 To insert : 1337040914 To insert : 1337040915 To insert : 1337040916 To insert : 1337040917 To insert : 1337040918 To insert : 1337040919 To insert : 1337040920 To insert : 1337040921 To insert : 1337040922 To insert : 1337040923 To insert : 1337040924 To insert : 1337040925 To insert : 1337040926 To insert : 1337040927 To insert : 1337040928 To insert : 1337040929 To insert : 1337040930 To insert : 1337040931 To insert : 1337040932 To insert : 1337040933 To insert : 1337040934 To insert : 1337040935 To insert : 1337040936 To insert : 1337040937 To insert : 1337040938 To insert : 1337040939 To insert : 1337040940 To insert : 1337040941 To insert : 1337040942 To insert : 1337040943 To insert : 1337040944 To insert : 1337040945 To insert : 1337040946 To insert : 1337040947 To insert : 1337040948 To insert : 1337040949 To insert : 1337040950 To insert : 1337040951 To insert : 1337040952 To insert : 1337040953 To insert : 1337040954 To insert : 1337040955 To insert : 1337040956 To insert : 1337040957 To insert : 1337040958 To insert : 1337040959 To insert : 1337040960 To insert : 1337040961 To insert : 1337040962 To insert : 1337040963 To insert : 1337040964 To insert : 1337040965 To insert : 1337040966 To insert : 1337040967 To insert : 1337040968 To insert : 1337040969 To insert : 1337040970 To insert : 1337040971 To insert : 1337040973 To insert : 1337040974 To insert : 1337040975 To insert : 1337040976 To insert : 1337040977 To insert : 1337040978 To insert : 1337040979 To insert : 1337040980 To insert : 1337040981 To insert : 1337040982 To insert : 1337040983 To insert : 1337040984 To insert : 1337040985 To insert : 1337040986 To insert : 1337040987 To insert : 1337040988 To insert : 1337040989 To insert : 1337040990 To insert : 1337040991 To insert : 1337040992 To insert : 1337040993 To insert : 1337040994 To insert : 1337040995 To insert : 1337040996 To insert : 1337040997 To insert : 1337040998 To insert : 1337040999 To insert : 1337041000 To insert : 1337041001 To insert : 1337041002 To insert : 1337041003 To insert : 1337041004 To insert : 1337041005 To insert : 1337041006 To insert : 1337040587 To insert : 1337040588 To insert : 1337040589 To insert : 1337040590 To insert : 1337040591 To insert : 1337040592 To insert : 1337040593 To insert : 1337040594 To insert : 1337040595 To insert : 1337040596 To insert : 1337040597 To insert : 1337040598 To insert : 1337040599 To insert : 1337040600 To insert : 1337040601 To insert : 1337040602 To insert : 1337040603 To insert : 1337040604 To insert : 1337040605 To insert : 1337040606 To insert : 1337040607 To insert : 1337040608 To insert : 1337040609 To insert : 1337040611 To insert : 1337040612 To insert : 1337040613 To insert : 1337040614 To insert : 1337040615 To insert : 1337040617 To insert : 1337040618 To insert : 1337040619 To insert : 1337040620 To insert : 1337040622 To insert : 1337040623 To insert : 1337040624 To insert : 1337040625 To insert : 1337040626 To insert : 1337040627 To insert : 1337040628 To insert : 1337040629 To insert : 1337040630 To insert : 1337040631 To insert : 1337040632 To insert : 1337040633 To insert : 1337040634 To insert : 1337040635 To insert : 1337040636 To insert : 1337040637 To insert : 1337040638 To insert : 1337040639 To insert : 1337040640 To insert : 1337040641 To insert : 1337040642 To insert : 1337040643 To insert : 1337040644 To insert : 1337040645 To insert : 1337040646 To insert : 1337040647 To insert : 1337040648 To insert : 1337040649 To insert : 1337040650 To insert : 1337040651 To insert : 1337040652 To insert : 1337040653 To insert : 1337040654 To insert : 1337040655 To insert : 1337040656 To insert : 1337040657 To insert : 1337040658 To insert : 1337040659 To insert : 1337040660 To insert : 1337040661 To insert : 1337040662 To insert : 1337040663 To insert : 1337040664 To insert : 1337040665 To insert : 1337040666 To insert : 1337040667 To insert : 1337040668 To insert : 1337040669 To insert : 1337040670 To insert : 1337040672 To insert : 1337040673 To insert : 1337040674 To insert : 1337040675 To insert : 1337040677 To insert : 1337040678 To insert : 1337040679 To insert : 1337040680 To insert : 1337040681 To insert : 1337040682 To insert : 1337040683 To insert : 1337040684 To insert : 1337040685 To insert : 1337040686 To insert : 1337040687 To insert : 1337040688 To insert : 1337040689 To insert : 1337040690 To insert : 1337040691 To insert : 1337040693 To insert : 1337040694 To insert : 1337040695 To insert : 1337040696 To insert : 1337040697 To insert : 1337040698 To insert : 1337040699 To insert : 1337040700 To insert : 1337040701 To insert : 1337040702 To insert : 1337040703 To insert : 1337040704 To insert : 1337040705 To insert : 1337040706 To insert : 1337040707 To insert : 1337040708 To insert : 1337040709 To insert : 1337040710 To insert : 1337040711 To insert : 1337040712 To insert : 1337040713 To insert : 1337040714 To insert : 1337040715 To insert : 1337040716 To insert : 1337040717 To insert : 1337040718 To insert : 1337040720 To insert : 1337040721 To insert : 1337040722 To insert : 1337040723 To insert : 1337040724 To insert : 1337040725 To insert : 1337040726 To insert : 1337040727 To insert : 1337040728 To insert : 1337040729 To insert : 1337040730 To insert : 1337040731 To insert : 1337040732 To insert : 1337040733 To insert : 1337040734 To insert : 1337040735 To insert : 1337040736 To insert : 1337040737 To insert : 1337040738 To insert : 1337040739 To insert : 1337040740 To insert : 1337040741 To insert : 1337040742 To insert : 1337040743 To insert : 1337040744 To insert : 1337040745 To insert : 1337040746 To insert : 1337040747 To insert : 1337040748 To insert : 1337040749 To insert : 1337040751 To insert : 1337040752 To insert : 1337040753 To insert : 1337040754 To insert : 1337040755 To insert : 1337040756 To insert : 1337040757 To insert : 1337040758 To insert : 1337040759 To insert : 1337040760 To insert : 1337040761 To insert : 1337040762 To insert : 1337040763 To insert : 1337040764 To insert : 1337040765 To insert : 1337040766 To insert : 1337040767 To insert : 1337040768 To insert : 1337040769 To insert : 1337040770 To insert : 1337040771 To insert : 1337040772 To insert : 1337040773 To insert : 1337040774 To insert : 1337040775 To insert : 1337040776 To insert : 1337040777 To insert : 1337040778 To insert : 1337040779 To insert : 1337040780 To insert : 1337040781 To insert : 1337040782 To insert : 1337040783 To insert : 1337040784 To insert : 1337040785 To insert : 1337040786 To insert : 1337040787 To insert : 1337040788 To insert : 1337040789 To insert : 1337040790 To insert : 1337040791 To insert : 1337040792 To insert : 1337040793 To insert : 1337040794 To insert : 1337040795 To insert : 1337040796 To insert : 1337040798 To insert : 1337040799 To insert : 1337040800 To insert : 1337040801 To insert : 1337040802 To insert : 1337040803 To insert : 1337040804 To insert : 1337040805 To insert : 1337040806 To insert : 1337040807 To insert : 1337040808 To insert : 1337040809 To insert : 1337040810 To insert : 1337040811 To insert : 1337040812 To insert : 1337040813 To insert : 1337040814 To insert : 1337040815 To insert : 1337040816 To insert : 1337040817 To insert : 1337040818 To insert : 1337040819 To insert : 1337040820 To insert : 1337040821 To insert : 1337040822 To insert : 1337040823 To insert : 1337040824 To insert : 1337040825 To insert : 1337040826 To insert : 1337040827 To insert : 1337040828 To insert : 1337040829 To insert : 1337040830 To insert : 1337040831 To insert : 1337040832 To insert : 1337040833 To insert : 1337040834 To insert : 1337040835 To insert : 1337040836 To insert : 1337040837 To insert : 1337040838 To insert : 1337040839 To insert : 1337040840 To insert : 1337040841 To insert : 1337040842 To insert : 1337040843 To insert : 1337040844 To insert : 1337040845 To insert : 1337040846 To insert : 1337040847 To insert : 1337040848 To insert : 1337040850 To insert : 1337040851 To insert : 1337040852 To insert : 1337040853 To insert : 1337040854 To insert : 1337040855 To insert : 1337040856 To insert : 1337040857 To insert : 1337040858 To insert : 1337040859 To insert : 1337040860 To insert : 1337040861 To insert : 1337040862 To insert : 1337040863 To insert : 1337040864 To insert : 1337040865 To insert : 1337040866 To insert : 1337040867 To insert : 1337040868 To insert : 1337041007 To insert : 1337041008 To insert : 1337041009 To insert : 1337041010 To insert : 1337041011 To insert : 1337041012 To insert : 1337041013 To insert : 1337041014 To insert : 1337041015 To insert : 1337041016 To insert : 1337041017 To insert : 1337041018 To insert : 1337041019 To insert : 1337041020 To insert : 1337041021 To insert : 1337041022 To insert : 1337041023 To insert : 1337041024 To insert : 1337041025 To insert : 1337041026 To insert : 1337041027 To insert : 1337041028 To insert : 1337041029 To insert : 1337041030 To insert : 1337041031 To insert : 1337041032 To insert : 1337041033 To insert : 1337041034 To insert : 1337041035 To insert : 1337041036 To insert : 1337041037 To insert : 1337041038 To insert : 1337041039 To insert : 1337041040 To insert : 1337041041 To insert : 1337041042 To insert : 1337041043 To insert : 1337041044 To insert : 1337041045 To insert : 1337041046 To insert : 1337041047 To insert : 1337041048 To insert : 1337041049 To insert : 1337041050 To insert : 1337041051 To insert : 1337041052 To insert : 1337041053 To insert : 1337041054 To insert : 1337041055 To insert : 1337041056 To insert : 1337041057 To insert : 1337041058 To insert : 1337041059 To insert : 1337041060 To insert : 1337041061 To insert : 1337041062 To insert : 1337041063 To insert : 1337041064 To insert : 1337041065 To insert : 1337041066 To insert : 1337041067 To insert : 1337041068 To insert : 1337041069 To insert : 1337041070 To insert : 1337041071 To insert : 1337041072 To insert : 1337041073 To insert : 1337041074 To insert : 1337041075 To insert : 1337041076 To insert : 1337041077 To insert : 1337041078 To insert : 1337041079 To insert : 1337041080 To insert : 1337041081 To insert : 1337041082 To insert : 1337041083 To insert : 1337041084 To insert : 1337041085 To insert : 1337041086 To insert : 1337041087 To insert : 1337041088 To insert : 1337041089 To insert : 1337041090 To insert : 1337041091 To insert : 1337041092 To insert : 1337041093 To insert : 1337041094 To insert : 1337041095 To insert : 1337041096 To insert : 1337041097 To insert : 1337041098 To insert : 1337041099 To insert : 1337041100 To insert : 1337041101 To insert : 1337041102 To insert : 1337041103 To insert : 1337041104 To insert : 1337041105 To insert : 1337041106 To insert : 1337041107 To insert : 1337041108 To insert : 1337041109 To insert : 1337041110 To insert : 1337041111 To insert : 1337041112 To insert : 1337041113 To insert : 1337041114 To insert : 1337041115 To insert : 1337041116 To insert : 1337041117 To insert : 1337041118 To insert : 1337041119 To insert : 1337041120 To insert : 1337041121 To insert : 1337041122 To insert : 1337041123 To insert : 1337041124 To insert : 1337041125 To insert : 1337041126 To insert : 1337041127 To insert : 1337041128 To insert : 1337041129 To insert : 1337041130 To insert : 1337041131 To insert : 1337041132 To insert : 1337041133 To insert : 1337041134 To insert : 1337041135 To insert : 1337041136 To insert : 1337041137 To insert : 1337041138 To insert : 1337041139 To insert : 1337041140 To insert : 1337041141 To insert : 1337041142 To insert : 1337040446 To insert : 1337040448 To insert : 1337040449 To insert : 1337040450 To insert : 1337040451 To insert : 1337040452 To insert : 1337040453 To insert : 1337040454 To insert : 1337040455 To insert : 1337040456 To insert : 1337040457 To insert : 1337040458 To insert : 1337040459 To insert : 1337040460 To insert : 1337040461 To insert : 1337040462 To insert : 1337040463 To insert : 1337040464 To insert : 1337040465 To insert : 1337040466 To insert : 1337040467 To insert : 1337040468 To insert : 1337040469 To insert : 1337040470 To insert : 1337040471 To insert : 1337040472 To insert : 1337040473 To insert : 1337040474 To insert : 1337040475 To insert : 1337040476 To insert : 1337040477 To insert : 1337040478 To insert : 1337040479 To insert : 1337040480 To insert : 1337040481 To insert : 1337040482 To insert : 1337040483 To insert : 1337040485 To insert : 1337040486 To insert : 1337040487 To insert : 1337040488 To insert : 1337040489 To insert : 1337040491 To insert : 1337040492 To insert : 1337040493 To insert : 1337040494 To insert : 1337040495 To insert : 1337040496 To insert : 1337040497 To insert : 1337040498 To insert : 1337040499 To insert : 1337040500 To insert : 1337040501 To insert : 1337040502 To insert : 1337040503 To insert : 1337040504 To insert : 1337040505 To insert : 1337040506 To insert : 1337040507 To insert : 1337040508 To insert : 1337040509 To insert : 1337040510 To insert : 1337040511 To insert : 1337040512 To insert : 1337040513 To insert : 1337040514 To insert : 1337040515 To insert : 1337040516 To insert : 1337040517 To insert : 1337040518 To insert : 1337040519 To insert : 1337040520 To insert : 1337040521 To insert : 1337040522 To insert : 1337040523 To insert : 1337040524 To insert : 1337040525 To insert : 1337040526 To insert : 1337040527 To insert : 1337040528 To insert : 1337040529 To insert : 1337040530 To insert : 1337040532 To insert : 1337040533 To insert : 1337040534 To insert : 1337040535 To insert : 1337040536 To insert : 1337040537 To insert : 1337040538 To insert : 1337040539 To insert : 1337040540 To insert : 1337040541 To insert : 1337040542 To insert : 1337040543 To insert : 1337040544 To insert : 1337040545 To insert : 1337040546 To insert : 1337040547 To insert : 1337040548 To insert : 1337040549 To insert : 1337040550 To insert : 1337040551 To insert : 1337040552 To insert : 1337040553 To insert : 1337040554 To insert : 1337040555 To insert : 1337040557 To insert : 1337040558 To insert : 1337040559 To insert : 1337040560 To insert : 1337040561 To insert : 1337040562 To insert : 1337040563 To insert : 1337040564 To insert : 1337040565 To insert : 1337040566 To insert : 1337040567 To insert : 1337040568 To insert : 1337040569 To insert : 1337040570 To insert : 1337040571 To insert : 1337040572 To insert : 1337040573 To insert : 1337040574 To insert : 1337040575 To insert : 1337040576 To insert : 1337040577 To insert : 1337040578 To insert : 1337040579 To insert : 1337040580 To insert : 1337040581 To insert : 1337040582 To insert : 1337040583 To insert : 1337040584 To insert : 1337040585 To insert : 1337040586 To insert : 1337041830 To insert : 1337041831 To insert : 1337041832 To insert : 1337041834 To insert : 1337041835 To insert : 1337041836 To insert : 1337041837 To insert : 1337041838 To insert : 1337041839 To insert : 1337041840 To insert : 1337041841 To insert : 1337041842 To insert : 1337041843 To insert : 1337041844 To insert : 1337041845 To insert : 1337041846 To insert : 1337041847 To insert : 1337041848 To insert : 1337041849 To insert : 1337041850 To insert : 1337041851 To insert : 1337041852 To insert : 1337041853 To insert : 1337041854 To insert : 1337041855 To insert : 1337041856 To insert : 1337041857 To insert : 1337041858 To insert : 1337041859 To insert : 1337041860 To insert : 1337041861 To insert : 1337041862 To insert : 1337041863 To insert : 1337041864 To insert : 1337041865 To insert : 1337041866 To insert : 1337041867 To insert : 1337041868 To insert : 1337041869 To insert : 1337041870 To insert : 1337041871 To insert : 1337041872 To insert : 1337041873 To insert : 1337041874 To insert : 1337041876 To insert : 1337041877 To insert : 1337041878 To insert : 1337041879 To insert : 1337041880 To insert : 1337041881 To insert : 1337041882 To insert : 1337041883 To insert : 1337041884 To insert : 1337041885 To insert : 1337041886 To insert : 1337041887 To insert : 1337041888 To insert : 1337041889 To insert : 1337041890 To insert : 1337041891 To insert : 1337041892 To insert : 1337041893 To insert : 1337041894 To insert : 1337041895 To insert : 1337041896 To insert : 1337041897 To insert : 1337041898 To insert : 1337041899 To insert : 1337041900 To insert : 1337041901 To insert : 1337041902 To insert : 1337041903 To insert : 1337041904 To insert : 1337041905 To insert : 1337041906 To insert : 1337041907 To insert : 1337041908 To insert : 1337041909 To insert : 1337041910 To insert : 1337041911 To insert : 1337041912 To insert : 1337041913 To insert : 1337041914 To insert : 1337041915 To insert : 1337041916 To insert : 1337041917 To insert : 1337041918 To insert : 1337041919 To insert : 1337041920 To insert : 1337041921 To insert : 1337041922 To insert : 1337041923 To insert : 1337041924 To insert : 1337041925 To insert : 1337041926 To insert : 1337041927 To insert : 1337041928 To insert : 1337041929 To insert : 1337041930 To insert : 1337041931 To insert : 1337041932 To insert : 1337041933 To insert : 1337041936 To insert : 1337041937 To insert : 1337041938 To insert : 1337041940 To insert : 1337041941 To insert : 1337041942 To insert : 1337041943 To insert : 1337041944 To insert : 1337041945 To insert : 1337041946 To insert : 1337041947 To insert : 1337041948 To insert : 1337041949 To insert : 1337041950 To insert : 1337041951 To insert : 1337041952 To insert : 1337041953 To insert : 1337041954 To insert : 1337041955 To insert : 1337041956 To insert : 1337041957 To insert : 1337041958 To insert : 1337041959 To insert : 1337041960 To insert : 1337041961 To insert : 1337041962 To insert : 1337041963 To insert : 1337041964 To insert : 1337041965 To insert : 1337041966 To insert : 1337041967 To insert : 1337041968 To insert : 1337041969 To insert : 1337041970 To insert : 1337041298 To insert : 1337041299 To insert : 1337041300 To insert : 1337041301 To insert : 1337041302 To insert : 1337041303 To insert : 1337041304 To insert : 1337041305 To insert : 1337041306 To insert : 1337041307 To insert : 1337041308 To insert : 1337041309 To insert : 1337041310 To insert : 1337041311 To insert : 1337041312 To insert : 1337041313 To insert : 1337041314 To insert : 1337041315 To insert : 1337041316 To insert : 1337041317 To insert : 1337041318 To insert : 1337041319 To insert : 1337041320 To insert : 1337041322 To insert : 1337041323 To insert : 1337041324 To insert : 1337041325 To insert : 1337041326 To insert : 1337041327 To insert : 1337041328 To insert : 1337041329 To insert : 1337041330 To insert : 1337041331 To insert : 1337041332 To insert : 1337041333 To insert : 1337041334 To insert : 1337041335 To insert : 1337041336 To insert : 1337041337 To insert : 1337041338 To insert : 1337041339 To insert : 1337041340 To insert : 1337041341 To insert : 1337041342 To insert : 1337041343 To insert : 1337041344 To insert : 1337041345 To insert : 1337041346 To insert : 1337041347 To insert : 1337041348 To insert : 1337041349 To insert : 1337041350 To insert : 1337041351 To insert : 1337041352 To insert : 1337041353 To insert : 1337041354 To insert : 1337041355 To insert : 1337041356 To insert : 1337041357 To insert : 1337041358 To insert : 1337041359 To insert : 1337041360 To insert : 1337041361 To insert : 1337041362 To insert : 1337041363 To insert : 1337041364 To insert : 1337041365 To insert : 1337041366 To insert : 1337041367 To insert : 1337041368 To insert : 1337041369 To insert : 1337041370 To insert : 1337041371 To insert : 1337041372 To insert : 1337041373 To insert : 1337041374 To insert : 1337041375 To insert : 1337041376 To insert : 1337041377 To insert : 1337041378 To insert : 1337041379 To insert : 1337041380 To insert : 1337041381 To insert : 1337041382 To insert : 1337041383 To insert : 1337041384 To insert : 1337041385 To insert : 1337041386 To insert : 1337041387 To insert : 1337041388 To insert : 1337041389 To insert : 1337041390 To insert : 1337041391 To insert : 1337041392 To insert : 1337041393 To insert : 1337041394 To insert : 1337041395 To insert : 1337041396 To insert : 1337041397 To insert : 1337041398 To insert : 1337041399 To insert : 1337041400 To insert : 1337041401 To insert : 1337041402 To insert : 1337041403 To insert : 1337041404 To insert : 1337041405 To insert : 1337041406 To insert : 1337041407 To insert : 1337041408 To insert : 1337041409 To insert : 1337041410 To insert : 1337041411 To insert : 1337041412 To insert : 1337041413 To insert : 1337041414 To insert : 1337041415 To insert : 1337041416 To insert : 1337041417 To insert : 1337041418 To insert : 1337041419 To insert : 1337041420 To insert : 1337041421 To insert : 1337041422 To insert : 1337041423 To insert : 1337041424 To insert : 1337041425 To insert : 1337041426 To insert : 1337041427 To insert : 1337041428 To insert : 1337041429 To insert : 1337041430 To insert : 1337041431 To insert : 1337041432 To insert : 1337041433 To insert : 1337041434 To insert : 1337041601 To insert : 1337041602 To insert : 1337041604 To insert : 1337041605 To insert : 1337041606 To insert : 1337041607 To insert : 1337041608 To insert : 1337041609 To insert : 1337041610 To insert : 1337041611 To insert : 1337041612 To insert : 1337041613 To insert : 1337041614 To insert : 1337041615 To insert : 1337041616 To insert : 1337041617 To insert : 1337041618 To insert : 1337041619 To insert : 1337041620 To insert : 1337041621 To insert : 1337041622 To insert : 1337041623 To insert : 1337041624 To insert : 1337041625 To insert : 1337041626 To insert : 1337041627 To insert : 1337041718 To insert : 1337041719 To insert : 1337041720 To insert : 1337041721 To insert : 1337041722 To insert : 1337041723 To insert : 1337041724 To insert : 1337041725 To insert : 1337041726 To insert : 1337041727 To insert : 1337041728 To insert : 1337041729 To insert : 1337041730 To insert : 1337041731 To insert : 1337041732 To insert : 1337041733 To insert : 1337041734 To insert : 1337041735 To insert : 1337041736 To insert : 1337041737 To insert : 1337041738 To insert : 1337041739 To insert : 1337041740 To insert : 1337041741 To insert : 1337041742 To insert : 1337041743 To insert : 1337041744 To insert : 1337041745 To insert : 1337041746 To insert : 1337041747 To insert : 1337041748 To insert : 1337041749 To insert : 1337041750 To insert : 1337041751 To insert : 1337041752 To insert : 1337041753 To insert : 1337041754 To insert : 1337041755 To insert : 1337041756 To insert : 1337041757 To insert : 1337041758 To insert : 1337041759 To insert : 1337041760 To insert : 1337041761 To insert : 1337041762 To insert : 1337041763 To insert : 1337041764 To insert : 1337041765 To insert : 1337041766 To insert : 1337041768 To insert : 1337041769 To insert : 1337041770 To insert : 1337041771 To insert : 1337041772 To insert : 1337041773 To insert : 1337041774 To insert : 1337041775 To insert : 1337041776 To insert : 1337041777 To insert : 1337041778 To insert : 1337041779 To insert : 1337041780 To insert : 1337041781 To insert : 1337041782 To insert : 1337041783 To insert : 1337041784 To insert : 1337041785 To insert : 1337041786 To insert : 1337041787 To insert : 1337041788 To insert : 1337041789 To insert : 1337041790 To insert : 1337041791 To insert : 1337041792 To insert : 1337041793 To insert : 1337041794 To insert : 1337041795 To insert : 1337041796 To insert : 1337041797 To insert : 1337041798 To insert : 1337041799 To insert : 1337041800 To insert : 1337041801 To insert : 1337041802 To insert : 1337041803 To insert : 1337041804 To insert : 1337041805 To insert : 1337041806 To insert : 1337041807 To insert : 1337041808 To insert : 1337041809 To insert : 1337041810 To insert : 1337041811 To insert : 1337041812 To insert : 1337041813 To insert : 1337041814 To insert : 1337041815 To insert : 1337041816 To insert : 1337041818 To insert : 1337041819 To insert : 1337041820 To insert : 1337041821 To insert : 1337041822 To insert : 1337041823 To insert : 1337041824 To insert : 1337041825 To insert : 1337041826 To insert : 1337041827 To insert : 1337041828 To insert : 1337041829 To insert : 1337041143 To insert : 1337041144 To insert : 1337041145 To insert : 1337041146 To insert : 1337041147 To insert : 1337041148 To insert : 1337041149 To insert : 1337041150 To insert : 1337041151 To insert : 1337041152 To insert : 1337041153 To insert : 1337041154 To insert : 1337041155 To insert : 1337041156 To insert : 1337041157 To insert : 1337041158 To insert : 1337041159 To insert : 1337041160 To insert : 1337041161 To insert : 1337041162 To insert : 1337041163 To insert : 1337041164 To insert : 1337041165 To insert : 1337041166 To insert : 1337041167 To insert : 1337041168 To insert : 1337041169 To insert : 1337041170 To insert : 1337041171 To insert : 1337041172 To insert : 1337041173 To insert : 1337041174 To insert : 1337041175 To insert : 1337041176 To insert : 1337041177 To insert : 1337041178 To insert : 1337041179 To insert : 1337041180 To insert : 1337041181 To insert : 1337041182 To insert : 1337041183 To insert : 1337041184 To insert : 1337041185 To insert : 1337041186 To insert : 1337041187 To insert : 1337041188 To insert : 1337041189 To insert : 1337041190 To insert : 1337041191 To insert : 1337041192 To insert : 1337041193 To insert : 1337041194 To insert : 1337041195 To insert : 1337041196 To insert : 1337041197 To insert : 1337041198 To insert : 1337041199 To insert : 1337041200 To insert : 1337041201 To insert : 1337041202 To insert : 1337041203 To insert : 1337041204 To insert : 1337041205 To insert : 1337041206 To insert : 1337041207 To insert : 1337041208 To insert : 1337041209 To insert : 1337041210 To insert : 1337041211 To insert : 1337041212 To insert : 1337041213 To insert : 1337041232 To insert : 1337041233 To insert : 1337041234 To insert : 1337041235 To insert : 1337041237 To insert : 1337041238 To insert : 1337041239 To insert : 1337041240 To insert : 1337041241 To insert : 1337041242 To insert : 1337041243 To insert : 1337041244 To insert : 1337041245 To insert : 1337041246 To insert : 1337041247 To insert : 1337041248 To insert : 1337041249 To insert : 1337041250 To insert : 1337041251 To insert : 1337041252 To insert : 1337041253 To insert : 1337041254 To insert : 1337041255 To insert : 1337041256 To insert : 1337041257 To insert : 1337041258 To insert : 1337041259 To insert : 1337041260 To insert : 1337041261 To insert : 1337041262 To insert : 1337041263 To insert : 1337041264 To insert : 1337041265 To insert : 1337041266 To insert : 1337041267 To insert : 1337041268 To insert : 1337041269 To insert : 1337041270 To insert : 1337041271 To insert : 1337041272 To insert : 1337041273 To insert : 1337041274 To insert : 1337041275 To insert : 1337041276 To insert : 1337041277 To insert : 1337041278 To insert : 1337041279 To insert : 1337041280 To insert : 1337041281 To insert : 1337041282 To insert : 1337041283 To insert : 1337041284 To insert : 1337041285 To insert : 1337041286 To insert : 1337041287 To insert : 1337041288 To insert : 1337041289 To insert : 1337041290 To insert : 1337041291 To insert : 1337041292 To insert : 1337041293 To insert : 1337041294 To insert : 1337041295 To insert : 1337041296 To insert : 1337041297 To insert : 1337041435 To insert : 1337041436 To insert : 1337041437 To insert : 1337041438 To insert : 1337041439 To insert : 1337041440 To insert : 1337041441 To insert : 1337041442 To insert : 1337041443 To insert : 1337041444 To insert : 1337041445 To insert : 1337041446 To insert : 1337041447 To insert : 1337041448 To insert : 1337041449 To insert : 1337041450 To insert : 1337041451 To insert : 1337041452 To insert : 1337041453 To insert : 1337041454 To insert : 1337041455 To insert : 1337041456 To insert : 1337041457 To insert : 1337041459 To insert : 1337041461 To insert : 1337041463 To insert : 1337041465 To insert : 1337041467 To insert : 1337041469 To insert : 1337041471 To insert : 1337041473 To insert : 1337041475 To insert : 1337041477 To insert : 1337041479 To insert : 1337041481 To insert : 1337041495 To insert : 1337041496 To insert : 1337041500 To insert : 1337041501 To insert : 1337041502 To insert : 1337041503 To insert : 1337041504 To insert : 1337041505 To insert : 1337041506 To insert : 1337041507 To insert : 1337041508 To insert : 1337041509 To insert : 1337041510 To insert : 1337041511 To insert : 1337041512 To insert : 1337041513 To insert : 1337041514 To insert : 1337041515 To insert : 1337041516 To insert : 1337041517 To insert : 1337041518 To insert : 1337041519 To insert : 1337041520 To insert : 1337041521 To insert : 1337041522 To insert : 1337041523 To insert : 1337041524 To insert : 1337041525 To insert : 1337041526 To insert : 1337041527 To insert : 1337041528 To insert : 1337041529 To insert : 1337041530 To insert : 1337041531 To insert : 1337041532 To insert : 1337041533 To insert : 1337041535 To insert : 1337041536 To insert : 1337041537 To insert : 1337041538 To insert : 1337041539 To insert : 1337041540 To insert : 1337041541 To insert : 1337041542 To insert : 1337041543 To insert : 1337041544 To insert : 1337041545 To insert : 1337041546 To insert : 1337041547 To insert : 1337041548 To insert : 1337041549 To insert : 1337041550 To insert : 1337041551 To insert : 1337041552 To insert : 1337041553 To insert : 1337041554 To insert : 1337041555 To insert : 1337041556 To insert : 1337041557 To insert : 1337041558 To insert : 1337041559 To insert : 1337041560 To insert : 1337041561 To insert : 1337041562 To insert : 1337041563 To insert : 1337041564 To insert : 1337041565 To insert : 1337041566 To insert : 1337041567 To insert : 1337041568 To insert : 1337041569 To insert : 1337041570 To insert : 1337041571 To insert : 1337041572 To insert : 1337041573 To insert : 1337041574 To insert : 1337041575 To insert : 1337041576 To insert : 1337041577 To insert : 1337041578 To insert : 1337041579 To insert : 1337041580 To insert : 1337041581 To insert : 1337041582 To insert : 1337041583 To insert : 1337041584 To insert : 1337041585 To insert : 1337041586 To insert : 1337041587 To insert : 1337041588 To insert : 1337041589 To insert : 1337041590 To insert : 1337041591 To insert : 1337041592 To insert : 1337041593 To insert : 1337041594 To insert : 1337041595 To insert : 1337041596 To insert : 1337041597 To insert : 1337041598 To insert : 1337041599 time to insert the descriptors : 221.4448356628418 Inside saveOutput : final : False verbose : 0 time used to find the portfolios of the photos SAVE THCL : begin to insert list_values into class_photo_scores : length of list_valuse in save_photo_hashtag_id_thcl_score : 2101 time used for this insertion : 0.1329176425933838 save missing photos in datou_result : time spend for datou_step_exec : 245.33280849456787 time spend to save output : 0.29022884368896484 total time spend for step 6 : 245.62303733825684 step7:ventilate_hashtags_in_portfolio Wed Feb 12 09:00:47 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure beginning of datou step ventilate_hashtags_in_portfolio : To implement ! Iterating over portfolio : 20029321 get user id for portfolio 20029321 SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20029321 AND mptpi.`type`=4230 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('papier','Film_plastique','autre','Papier','pehd','PET_fonce','Carton','mal_croppe','PET_clair','refus','flou','carton','environnement','Tetrapak','pet_clair','PEHD','metal','pet_fonce')) AND mptpi.`min_score`=0.6 To do Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") To do ! Use context local managing function ! SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20029321 AND mptpi.`type`=4231 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('papier','Film_plastique','autre','Papier','pehd','PET_fonce','Carton','mal_croppe','PET_clair','refus','flou','carton','environnement','Tetrapak','pet_clair','PEHD','metal','pet_fonce')) AND mptpi.`min_score`=0.6 To do lien utilise dans velours : https://www.fotonower.com/velours/20256316,20256317,20256318,20256322,20256320,20256330,20256323,20256324,20256325,20256326,20256333,20256332,20256331?tags=flou,environnement,film_plastique,carton,metal,pet_clair,refus,autre,mal_croppe,tetrapak,papier,pehd,pet_fonce&datou_id_consolidate=4235&port_consolidate=20029321 Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : ventilate_hashtags_in_portfolio we use saveGeneral [1332404633, 1332404630, 1332404627, 1332404610, 1332404608, 1332404605, 1332404602, 1332404599, 1332404596, 1332404585, 1332404583, 1332404581, 1332404578, 1332404575, 1332404571, 1332404558, 1332404555, 1332404550, 1332404545, 1332404540, 1332404535] Looping around the photos to save general results len do output : 1 /20029321. before output type Here is an output not treated by saveGeneral : Managing all output in save final without adding information in the mtr_datou_result ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404633', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404630', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404627', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404610', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404608', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404605', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404602', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404599', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404596', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404585', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404583', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404581', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404578', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404575', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404571', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404558', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404555', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404550', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404545', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404540', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404535', None, None, None, None, None, '2524174') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 22 time used for this insertion : 0.014659643173217773 save_final save missing photos in datou_result : time spend for datou_step_exec : 2.6394097805023193 time spend to save output : 0.01503896713256836 total time spend for step 7 : 2.6544487476348877 step8:final Wed Feb 12 09:00:49 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! complete output_args for input 2 VR 22-3-18 : For now we do not clean correctly the datou structure Beginning of datou step final ! Catched exception ! Connect or reconnect ! Inside saveOutput : final : False verbose : 0 original output for save of step final : {1332404633: ('0.14403871543059713',), 1332404630: ('0.14403871543059713',), 1332404627: ('0.14403871543059713',), 1332404610: ('0.14403871543059713',), 1332404608: ('0.14403871543059713',), 1332404605: ('0.14403871543059713',), 1332404602: ('0.14403871543059713',), 1332404599: ('0.14403871543059713',), 1332404596: ('0.14403871543059713',), 1332404585: ('0.14403871543059713',), 1332404583: ('0.14403871543059713',), 1332404581: ('0.14403871543059713',), 1332404578: ('0.14403871543059713',), 1332404575: ('0.14403871543059713',), 1332404571: ('0.14403871543059713',), 1332404558: ('0.14403871543059713',), 1332404555: ('0.14403871543059713',), 1332404550: ('0.14403871543059713',), 1332404545: ('0.14403871543059713',), 1332404540: ('0.14403871543059713',), 1332404535: ('0.14403871543059713',)} new output for save of step final : {1332404633: ('0.14403871543059713',), 1332404630: ('0.14403871543059713',), 1332404627: ('0.14403871543059713',), 1332404610: ('0.14403871543059713',), 1332404608: ('0.14403871543059713',), 1332404605: ('0.14403871543059713',), 1332404602: ('0.14403871543059713',), 1332404599: ('0.14403871543059713',), 1332404596: ('0.14403871543059713',), 1332404585: ('0.14403871543059713',), 1332404583: ('0.14403871543059713',), 1332404581: ('0.14403871543059713',), 1332404578: ('0.14403871543059713',), 1332404575: ('0.14403871543059713',), 1332404571: ('0.14403871543059713',), 1332404558: ('0.14403871543059713',), 1332404555: ('0.14403871543059713',), 1332404550: ('0.14403871543059713',), 1332404545: ('0.14403871543059713',), 1332404540: ('0.14403871543059713',), 1332404535: ('0.14403871543059713',)} [1332404633, 1332404630, 1332404627, 1332404610, 1332404608, 1332404605, 1332404602, 1332404599, 1332404596, 1332404585, 1332404583, 1332404581, 1332404578, 1332404575, 1332404571, 1332404558, 1332404555, 1332404550, 1332404545, 1332404540, 1332404535] Looping around the photos to save general results len do output : 21 /1332404633.Didn't retrieve data . /1332404630.Didn't retrieve data . /1332404627.Didn't retrieve data . /1332404610.Didn't retrieve data . /1332404608.Didn't retrieve data . /1332404605.Didn't retrieve data . /1332404602.Didn't retrieve data . /1332404599.Didn't retrieve data . /1332404596.Didn't retrieve data . /1332404585.Didn't retrieve data . /1332404583.Didn't retrieve data . /1332404581.Didn't retrieve data . /1332404578.Didn't retrieve data . /1332404575.Didn't retrieve data . /1332404571.Didn't retrieve data . /1332404558.Didn't retrieve data . /1332404555.Didn't retrieve data . /1332404550.Didn't retrieve data . /1332404545.Didn't retrieve data . /1332404540.Didn't retrieve data . /1332404535.Didn't retrieve data . before output type Used above Used above Managing all output in save final without adding information in the mtr_datou_result ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404633', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404630', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404627', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404610', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404608', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404605', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404602', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404599', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404596', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404585', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404583', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404581', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404578', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404575', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404571', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404558', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404555', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404550', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404545', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404540', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404535', None, None, None, None, None, '2524174') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 63 time used for this insertion : 0.014665603637695312 save_final save missing photos in datou_result : time spend for datou_step_exec : 0.48084211349487305 time spend to save output : 0.015766620635986328 total time spend for step 8 : 0.4966087341308594 step9:velours_tree Wed Feb 12 09:00:50 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 VR 22-3-18 : For now we do not clean correctly the datou structure list_portfolios : 20256316,20256317,20256318,20256322,20256320,20256330,20256323,20256324,20256325,20256326,20256333,20256332,20256331 photo desc type : 5561 - Retrieving photos to tag... query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=20256316 ORDER BY ph.size desc query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=20256317 ORDER BY ph.size desc query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=20256318 ORDER BY ph.size desc query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=20256322 ORDER BY ph.size desc query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=20256320 ORDER BY ph.size desc query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=20256330 ORDER BY ph.size desc query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=20256323 ORDER BY ph.size desc query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=20256324 ORDER BY ph.size desc query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=20256325 ORDER BY ph.size desc query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=20256326 ORDER BY ph.size desc query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=20256333 ORDER BY ph.size desc query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=20256332 ORDER BY ph.size desc query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=20256331 ORDER BY ph.size desc - Loading descriptors... Size : 2048 len(descriptors) : 5000 Compute structured hierarchical clustering... ward : AgglomerativeClustering(n_clusters=6) ward.labels_ : [2 0 1 ... 1 1 1] Elapsed time: 18.378111362457275 graph_id used : 77864 - Beta version, working pretty good on 11-5-16 ! too many photos (6702 more than 5000) Inside saveOutput : final : False verbose : 0 ouput is None No outpout to save, returning out of save general time spend for datou_step_exec : 466.1471891403198 time spend to save output : 0.08766937255859375 total time spend for step 9 : 466.2348585128784 step10:send_mail_cod Wed Feb 12 09:08:36 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 complete output_args for input 1 Inconsistent number of input and output, step which parrallelize and manage error in input by avoiding sending an output for this data can't be used in tree dependencies of input and output complete output_args for input 2 complete output_args for input 3 We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure dans la step send mail cod work_area: /home/admin in order to get the selector url, please entre the license of selector results_Qualipapia_P20029321_12-02-2025_09_08_36.pdf 20256296 imagette202562961739347716 20256298 imagette202562981739347716 20256302 change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .imagette202563021739347716 20256300 change filename to text .change filename to text .imagette202563001739347718 20256310 change filename to text .change filename to text .change 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filename to text .imagette202563041739347720 20256305 imagette202563051739347722 20256306 imagette202563061739347722 20256313 change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .imagette202563131739347722 20256312 change filename to text .change filename to text .change filename to text .imagette202563121739347724 20256311 change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .imagette202563111739347724 SELECT h.hashtag,pcr.value FROM MTRUser.portfolio_carac_ratio pcr, MTRBack.hashtags h where pcr.portfolio_id=20029321 and hashtag_type = 4230 and pcr.hashtag_id = h.hashtag_id; velour_link : https://www.fotonower.com/velours/20256316,20256317,20256318,20256322,20256320,20256330,20256323,20256324,20256325,20256326,20256333,20256332,20256331?tags=flou,environnement,film_plastique,carton,metal,pet_clair,refus,autre,mal_croppe,tetrapak,papier,pehd,pet_fonce&datou_id_consolidate=4235&port_consolidate=20029321 your option no_mail is active, we will not send the real mail to your client args[1332404633] : ((1332404633, -6.897064333781125, 492609224), (1332404633, -0.49164030488855875, 501862349), '0.14403871543059713') apple ((1332404633, -6.897064333781125, 492609224), (1332404633, -0.49164030488855875, 501862349), '0.14403871543059713') We are sending mail with results at cod@fotonower.com args[1332404630] : ((1332404630, -6.885617531871497, 492609224), (1332404630, -0.4917372769692974, 501862349), '0.14403871543059713') apple ((1332404630, -6.885617531871497, 492609224), (1332404630, -0.4917372769692974, 501862349), '0.14403871543059713') We are sending mail with results at cod@fotonower.com args[1332404627] : ((1332404627, -6.901302299485353, 492609224), (1332404627, -0.48281307423229985, 501862349), '0.14403871543059713') apple ((1332404627, -6.901302299485353, 492609224), (1332404627, -0.48281307423229985, 501862349), '0.14403871543059713') We are sending mail with results at cod@fotonower.com args[1332404610] : ((1332404610, -6.8914866282913705, 492609224), (1332404610, -0.4804459732625727, 501862349), '0.14403871543059713') apple ((1332404610, -6.8914866282913705, 492609224), (1332404610, -0.4804459732625727, 501862349), '0.14403871543059713') We are sending mail with results at cod@fotonower.com args[1332404608] : ((1332404608, -6.90501317202887, 492609224), (1332404608, -0.4846853276213403, 501862349), '0.14403871543059713') apple ((1332404608, -6.90501317202887, 492609224), (1332404608, -0.4846853276213403, 501862349), '0.14403871543059713') We are sending mail with results at cod@fotonower.com args[1332404605] : ((1332404605, -6.907404045974517, 492609224), (1332404605, -0.4851575867089725, 501862349), '0.14403871543059713') apple ((1332404605, -6.907404045974517, 492609224), (1332404605, -0.4851575867089725, 501862349), '0.14403871543059713') We are sending mail with results at cod@fotonower.com args[1332404602] : ((1332404602, -6.908753310459022, 492609224), (1332404602, -0.48568775724708757, 501862349), '0.14403871543059713') apple ((1332404602, -6.908753310459022, 492609224), (1332404602, -0.48568775724708757, 501862349), '0.14403871543059713') We are sending mail with results at cod@fotonower.com args[1332404599] : ((1332404599, -6.906811749293834, 492609224), (1332404599, -0.47225593154992446, 496442774), '0.14403871543059713') apple ((1332404599, -6.906811749293834, 492609224), (1332404599, -0.47225593154992446, 496442774), '0.14403871543059713') We are sending mail with results at cod@fotonower.com args[1332404596] : ((1332404596, -6.895344367047699, 492609224), (1332404596, -0.4782130774446512, 496442774), '0.14403871543059713') apple ((1332404596, -6.895344367047699, 492609224), (1332404596, -0.4782130774446512, 496442774), '0.14403871543059713') We are sending mail with results at cod@fotonower.com args[1332404585] : ((1332404585, -6.8839312798471175, 492609224), (1332404585, -0.49847307877731595, 501862349), '0.14403871543059713') apple ((1332404585, -6.8839312798471175, 492609224), (1332404585, -0.49847307877731595, 501862349), '0.14403871543059713') We are sending mail with results at cod@fotonower.com args[1332404583] : ((1332404583, -6.879402909437718, 492609224), (1332404583, -0.5048587802662161, 501862349), '0.14403871543059713') apple ((1332404583, -6.879402909437718, 492609224), (1332404583, -0.5048587802662161, 501862349), '0.14403871543059713') We are sending mail with results at cod@fotonower.com args[1332404581] : ((1332404581, -6.878464210763026, 492609224), (1332404581, -0.4903588268946069, 501862349), '0.14403871543059713') apple ((1332404581, -6.878464210763026, 492609224), (1332404581, -0.4903588268946069, 501862349), '0.14403871543059713') We are sending mail with results at cod@fotonower.com args[1332404578] : ((1332404578, -6.86996101979846, 492609224), (1332404578, -0.48943540863642554, 501862349), '0.14403871543059713') apple ((1332404578, -6.86996101979846, 492609224), (1332404578, -0.48943540863642554, 501862349), '0.14403871543059713') We are sending mail with results at cod@fotonower.com args[1332404575] : ((1332404575, -6.881758720590853, 492609224), (1332404575, -0.47789739836915524, 496442774), '0.14403871543059713') apple ((1332404575, -6.881758720590853, 492609224), (1332404575, -0.47789739836915524, 496442774), '0.14403871543059713') We are sending mail with results at cod@fotonower.com args[1332404571] : ((1332404571, -6.88349410785495, 492609224), (1332404571, -0.48522868689136056, 501862349), '0.14403871543059713') apple ((1332404571, -6.88349410785495, 492609224), (1332404571, -0.48522868689136056, 501862349), '0.14403871543059713') We are sending mail with results at cod@fotonower.com args[1332404558] : ((1332404558, -6.853935340356413, 492609224), (1332404558, -0.5018706258268543, 501862349), '0.14403871543059713') apple ((1332404558, -6.853935340356413, 492609224), (1332404558, -0.5018706258268543, 501862349), '0.14403871543059713') We are sending mail with results at cod@fotonower.com args[1332404555] : ((1332404555, -6.892483721105581, 492609224), (1332404555, -0.4592497173808866, 496442774), '0.14403871543059713') apple ((1332404555, -6.892483721105581, 492609224), (1332404555, -0.4592497173808866, 496442774), '0.14403871543059713') We are sending mail with results at cod@fotonower.com args[1332404550] : ((1332404550, -6.830097098899389, 492609224), (1332404550, -0.5356527566854988, 501862349), '0.14403871543059713') apple ((1332404550, -6.830097098899389, 492609224), (1332404550, -0.5356527566854988, 501862349), '0.14403871543059713') We are sending mail with results at cod@fotonower.com args[1332404545] : ((1332404545, -6.885675706962043, 492609224), (1332404545, -0.5574295952525218, 501862349), '0.14403871543059713') apple ((1332404545, -6.885675706962043, 492609224), (1332404545, -0.5574295952525218, 501862349), '0.14403871543059713') We are sending mail with results at cod@fotonower.com args[1332404540] : ((1332404540, -6.855293276036565, 492609224), (1332404540, -0.570269680710895, 501862349), '0.14403871543059713') apple ((1332404540, -6.855293276036565, 492609224), (1332404540, -0.570269680710895, 501862349), '0.14403871543059713') We are sending mail with results at cod@fotonower.com args[1332404535] : ((1332404535, -6.95432985415064, 492609224), (1332404535, -0.623276631229744, 501862349), '0.14403871543059713') apple ((1332404535, -6.95432985415064, 492609224), (1332404535, -0.623276631229744, 501862349), '0.14403871543059713') We are sending mail with results at cod@fotonower.com refus_total : 0.14403871543059713 2022-04-13 10:29:59 0 SELECT ph.photo_id,ph.url,ph.username,ph.uploaded_at,ph.text FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=20029321 AND mpp.hide_status=0 ORDER BY mpp.order LIMIT 0, 1000 start upload file to ovh https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20029321_12-02-2025_09_08_36.pdf results_Qualipapia_P20029321_12-02-2025_09_08_36.pdf uploaded to url https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20029321_12-02-2025_09_08_36.pdf start insert file to database insert into MTRUser.mtr_files (mtd_id,mtr_portfolio_id,text,url,format,tags,file_size,value) values ('4234','20029321','results_Qualipapia_P20029321_12-02-2025_09_08_36.pdf','https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20029321_12-02-2025_09_08_36.pdf','pdf','','0.31','0.14403871543059713') Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : send_mail_cod we use saveGeneral [1332404633, 1332404630, 1332404627, 1332404610, 1332404608, 1332404605, 1332404602, 1332404599, 1332404596, 1332404585, 1332404583, 1332404581, 1332404578, 1332404575, 1332404571, 1332404558, 1332404555, 1332404550, 1332404545, 1332404540, 1332404535] Looping around the photos to save general results len do output : 0 before output type Used above Managing all output in save final without adding information in the mtr_datou_result ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404633', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404630', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404627', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404610', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404608', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404605', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404602', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404599', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404596', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404585', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404583', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404581', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404578', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404575', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404571', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404558', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404555', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404550', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404545', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404540', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404535', None, None, None, None, None, '2524174') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 21 time used for this insertion : 0.014376640319824219 save_final save missing photos in datou_result : time spend for datou_step_exec : 11.441779375076294 time spend to save output : 0.014722824096679688 total time spend for step 10 : 11.456502199172974 step11:split_time_score Wed Feb 12 09:08:47 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure begin split time score Catched exception ! Connect or reconnect ! TODO : Insert select and so on Begin split_port_in_batch_balle thcls : [{'id': 3442, 'mtr_user_id': 31, 'name': 'classifieur_2camions_valcor_021122_v1', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'deux_camions,camion_droite,camion_gauche,pas_de_camion', 'svm_portfolios_learning': '7659379,7659034,7657685,7657114', 'photo_hashtag_type': 4458, 'photo_desc_type': 5723, 'type_classification': 'tf_classification2', 'hashtag_id_list': '2107760533,2107760534,2107760535,2107760536'}] thcls : [{'id': 758, 'mtr_user_id': 31, 'name': 'Rungis_amount_dechets_fall_2018_v2', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': '05102018_Papier_non_papier_dense,05102018_Papier_non_papier_peu_dense,05102018_Papier_non_papier_presque_vide,05102018_Papier_non_papier_tres_dense,05102018_Papier_non_papier_tres_peu_dense', 'svm_portfolios_learning': '1108385,1108386,1108388,1108384,1108387', 'photo_hashtag_type': 856, 'photo_desc_type': 3853, 'type_classification': 'caffe', 'hashtag_id_list': '2107751013,2107751014,2107751015,2107751016,2107751017'}] (('14', 135), ('15', 70)) ERROR counted https://github.com/fotonower/Velours/issues/663#issuecomment-421136223 {} 28012025 20029321 Nombre de photos uploadées : 205 / 23040 (0%) 28012025 20029321 Nombre de photos taguées (types de déchets): 205 / 205 (100%) 28012025 20029321 Nombre de photos taguées (volume) : 0 / 205 (0%) elapsed_time : load_data_split_time_score 2.1457672119140625e-06 elapsed_time : order_list_meta_photo_and_scores 5.4836273193359375e-06 ????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????? elapsed_time : fill_and_build_computed_from_old_data 0.00802302360534668 elapsed_time : insert_dashboard_record_day_entry 0.023840904235839844 We will return after consolidate but for now we need the day, how to get it, for now depending on the previous heavy steps Qualite : 0.2863267335409182 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20008146_28-01-2025_10_17_51.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20008146 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20008146 AND mptpi.`type`=4230 To do Qualite : 0.22508372961743617 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20018394_28-01-2025_15_30_56.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20018394 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20018394 AND mptpi.`type`=4230 To do Qualite : 0.2192979642788335 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20018396_28-01-2025_15_33_03.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20018396 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20018396 AND mptpi.`type`=4230 To do Qualite : 0.2709028428485376 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20021653_31-01-2025_21_52_51.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20021653 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20021653 AND mptpi.`type`=4230 To do Qualite : 0.22775474792504805 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20020567_28-01-2025_16_32_43.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20020567 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20020567 AND mptpi.`type`=4230 To do Qualite : 0.23461741827802182 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20020569_28-01-2025_16_18_11.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20020569 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20020569 AND mptpi.`type`=4230 To do Qualite : 0.204945518097046 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20021689_31-01-2025_21_57_43.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20021689 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20021689 AND mptpi.`type`=4230 To do Qualite : 0.23160374228191413 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20021693_31-01-2025_22_03_24.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20021693 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20021693 AND mptpi.`type`=4230 To do Qualite : 0.23512316372924888 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20021695_31-01-2025_22_07_59.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20021695 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20021695 AND mptpi.`type`=4230 To do Qualite : 0.2291231842605102 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20021697_31-01-2025_22_14_21.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20021697 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20021697 AND mptpi.`type`=4230 To do Qualite : 0.2193074173048487 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20021700_31-01-2025_22_17_35.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20021700 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20021700 AND mptpi.`type`=4230 To do Qualite : 0.21510683946747872 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20021702_31-01-2025_22_23_25.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20021702 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20021702 AND mptpi.`type`=4230 To do Qualite : 0.21350702884767392 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20021703_28-01-2025_16_46_59.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20021703 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20021703 AND mptpi.`type`=4230 To do Qualite : 0.21583740817433747 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20021704_31-01-2025_22_37_39.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20021704 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20021704 AND mptpi.`type`=4230 To do Qualite : 0.24065026113431162 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20023408_31-01-2025_23_13_12.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20023408 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20023408 AND mptpi.`type`=4230 To do Qualite : 0.2965037206902108 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20023411_31-01-2025_23_08_10.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20023411 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20023411 AND mptpi.`type`=4230 To do Qualite : 0.274997044563035 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20023413_31-01-2025_23_18_18.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20023413 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20023413 AND mptpi.`type`=4230 To do Qualite : 0.2517500726789338 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20023415_31-01-2025_23_28_19.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20023415 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20023415 AND mptpi.`type`=4230 To do Qualite : 0.27792344986569767 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20023417_31-01-2025_23_40_26.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20023417 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20023417 AND mptpi.`type`=4230 To do Qualite : 0.26999732941174015 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20023419_31-01-2025_23_48_25.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20023419 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20023419 AND mptpi.`type`=4230 To do Qualite : 0.25345445342357387 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20023422_31-01-2025_23_55_18.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20023422 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20023422 AND mptpi.`type`=4230 To do Qualite : 0.24153005277220793 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20023423_05-02-2025_09_34_19.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20023423 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20023423 AND mptpi.`type`=4230 To do Qualite : 0.28469916270464835 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20023436_31-01-2025_23_59_17.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20023436 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20023436 AND mptpi.`type`=4230 To do Qualite : 0.2679385218370288 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20023437_01-02-2025_00_03_56.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20023437 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20023437 AND mptpi.`type`=4230 To do Qualite : 0.19718434623891135 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20023439_05-02-2025_09_48_07.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20023439 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20023439 AND mptpi.`type`=4230 To do Qualite : 0.2216499026841949 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20023440_01-02-2025_00_29_33.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20023440 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20023440 AND mptpi.`type`=4230 To do Qualite : 0.24209536320862207 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20023442_01-02-2025_00_35_36.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20023442 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20023442 AND mptpi.`type`=4230 To do Qualite : 0.18202999478216847 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20023444_01-02-2025_00_38_46.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20023444 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20023444 AND mptpi.`type`=4230 To do Qualite : 0.24308622281778397 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20024109_08-02-2025_12_13_43.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20024109 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20024109 AND mptpi.`type`=4230 To do Qualite : 0.2567735698965076 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20024111_05-02-2025_10_24_15.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20024111 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20024111 AND mptpi.`type`=4230 To do Qualite : 0.2559686691551984 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20024113_05-02-2025_10_04_18.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20024113 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20024113 AND mptpi.`type`=4230 To do Qualite : 0.26550505004547564 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20024140_11-02-2025_20_57_12.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20024140 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20024140 AND mptpi.`type`=4230 To do Qualite : 0.20267650122573252 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20024143_01-02-2025_01_23_51.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20024143 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20024143 AND mptpi.`type`=4230 To do Qualite : 0.23361866139210236 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20024145_01-02-2025_01_25_02.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20024145 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20024145 AND mptpi.`type`=4230 To do Qualite : 0.2551284067012479 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20024147_01-02-2025_01_26_35.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20024147 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20024147 AND mptpi.`type`=4230 To do Qualite : 0.23613911723576922 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20024149_01-02-2025_01_27_51.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20024149 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20024149 AND mptpi.`type`=4230 To do Qualite : 0.22065540237003822 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20024150_05-02-2025_09_57_43.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20024150 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20024150 AND mptpi.`type`=4230 To do Qualite : 0.2452236790467053 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20024151_01-02-2025_01_42_43.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20024151 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20024151 AND mptpi.`type`=4230 To do Qualite : 0.2383650174966491 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20024152_28-01-2025_18_17_40.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20024152 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20024152 AND mptpi.`type`=4230 To do Qualite : 0.25075441883821303 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20024153_28-01-2025_18_33_13.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20024153 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20024153 AND mptpi.`type`=4230 To do Qualite : 0.27129328784875373 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20024828_01-02-2025_01_53_39.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20024828 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20024828 AND mptpi.`type`=4230 To do Qualite : 0.22807993225367765 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20024830_01-02-2025_02_05_04.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20024830 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20024830 AND mptpi.`type`=4230 To do Qualite : 0.2453213227697547 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20024833_01-02-2025_02_03_33.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20024833 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20024833 AND mptpi.`type`=4230 To do Qualite : 0.22745782864797692 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20024835_01-02-2025_02_15_59.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20024835 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20024835 AND mptpi.`type`=4230 To do Qualite : 0.235939105510789 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20024837_01-02-2025_02_12_41.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20024837 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20024837 AND mptpi.`type`=4230 To do Qualite : 0.2228107985500643 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20024838_01-02-2025_02_19_45.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20024838 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20024838 AND mptpi.`type`=4230 To do Qualite : 0.24160861115136056 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20024851_01-02-2025_02_22_38.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20024851 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20024851 AND mptpi.`type`=4230 To do Qualite : 0.2426838903382056 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20024864_01-02-2025_02_27_36.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20024864 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20024864 AND mptpi.`type`=4230 To do Qualite : 0.20618839852014834 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20024865_01-02-2025_02_32_41.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20024865 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20024865 AND mptpi.`type`=4230 To do Qualite : 0.19056752053672152 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20024866_05-02-2025_10_14_28.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20024866 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20024866 AND mptpi.`type`=4230 To do Qualite : 0.21654368308005215 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20024867_01-02-2025_02_45_05.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20024867 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20024867 AND mptpi.`type`=4230 To do Qualite : 0.2761291654331784 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20024868_01-02-2025_02_48_29.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20024868 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20024868 AND mptpi.`type`=4230 To do Qualite : 0.2465896229134338 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20024869_01-02-2025_02_56_45.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20024869 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20024869 AND mptpi.`type`=4230 To do Qualite : 0.22392780702245077 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20024870_01-02-2025_03_11_24.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20024870 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20024870 AND mptpi.`type`=4230 To do Qualite : 0.23438248321116234 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20024871_01-02-2025_03_20_05.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20024871 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20024871 AND mptpi.`type`=4230 To do Qualite : 0.23719821912957495 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20024872_01-02-2025_03_22_49.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20024872 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20024872 AND mptpi.`type`=4230 To do Qualite : 0.2698943480481877 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20024873_01-02-2025_03_28_27.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20024873 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20024873 AND mptpi.`type`=4230 To do Qualite : 0.23517599119710517 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20024874_01-02-2025_03_33_06.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20024874 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20024874 AND mptpi.`type`=4230 To do Qualite : 0.23105097617989256 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20024875_01-02-2025_03_39_24.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20024875 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20024875 AND mptpi.`type`=4230 To do Qualite : 0.26142467803347064 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20024876_01-02-2025_03_43_24.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20024876 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20024876 AND mptpi.`type`=4230 To do Qualite : 0.19111724013424036 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20024877_01-02-2025_03_50_46.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20024877 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20024877 AND mptpi.`type`=4230 To do Qualite : 0.22008178332096137 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20024878_01-02-2025_03_54_33.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20024878 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20024878 AND mptpi.`type`=4230 To do Qualite : 0.22041760660322776 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20024879_05-02-2025_10_24_23.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20024879 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20024879 AND mptpi.`type`=4230 To do Qualite : 0.26358976941631707 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20024880_28-01-2025_18_47_24.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20024880 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20024880 AND mptpi.`type`=4230 To do Qualite : 0.2309569371487574 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20025633_01-02-2025_04_33_19.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20025633 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20025633 AND mptpi.`type`=4230 To do Qualite : 0.23957871176573434 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20025636_05-02-2025_10_46_15.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20025636 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20025636 AND mptpi.`type`=4230 To do Qualite : 0.19273360069183434 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20025638_01-02-2025_04_49_03.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20025638 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20025638 AND mptpi.`type`=4230 To do Qualite : 0.19345721022162685 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20025640_01-02-2025_04_38_56.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20025640 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20025640 AND mptpi.`type`=4230 To do Qualite : 0.2102224493696527 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20025641_01-02-2025_04_48_52.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20025641 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20025641 AND mptpi.`type`=4230 To do Qualite : 0.20392479115376405 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20025642_01-02-2025_04_47_34.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20025642 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20025642 AND mptpi.`type`=4230 To do Qualite : 0.22777159743009615 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20025643_01-02-2025_05_13_10.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20025643 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20025643 AND mptpi.`type`=4230 To do Qualite : 0.20671280458344787 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20025644_01-02-2025_05_01_11.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20025644 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20025644 AND mptpi.`type`=4230 To do Qualite : 0.18257565632059497 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20025646_01-02-2025_05_03_18.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20025646 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20025646 AND mptpi.`type`=4230 To do Qualite : 0.24824617897815027 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20025648_01-02-2025_05_16_40.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20025648 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20025648 AND mptpi.`type`=4230 To do Qualite : 0.23317380960353448 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20025650_01-02-2025_05_12_50.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20025650 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20025650 AND mptpi.`type`=4230 To do Qualite : 0.26810551852953707 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20025653_01-02-2025_05_18_34.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20025653 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20025653 AND mptpi.`type`=4230 To do Qualite : 0.27848584358141354 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20025657_01-02-2025_09_02_38.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20025657 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20025657 AND mptpi.`type`=4230 To do Qualite : 0.3009537101454553 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20025659_01-02-2025_05_27_55.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20025659 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20025659 AND mptpi.`type`=4230 To do Qualite : 0.27744165458165093 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20025662_05-02-2025_11_00_27.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20025662 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20025662 AND mptpi.`type`=4230 To do Qualite : 0.26816015574385665 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20025664_01-02-2025_05_46_43.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20025664 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20025664 AND mptpi.`type`=4230 To do Qualite : 0.2919836761758342 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20025667_01-02-2025_05_48_57.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20025667 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20025667 AND mptpi.`type`=4230 To do Qualite : 0.27332366002786723 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20025669_01-02-2025_05_55_28.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20025669 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20025669 AND mptpi.`type`=4230 To do Qualite : 0.2827721217047603 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20025672_01-02-2025_06_04_40.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20025672 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20025672 AND mptpi.`type`=4230 To do Qualite : 0.21652007353639235 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20025675_01-02-2025_06_03_28.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20025675 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20025675 AND mptpi.`type`=4230 To do Qualite : 0.206474470219582 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20025677_28-01-2025_19_32_52.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20025677 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20025677 AND mptpi.`type`=4230 To do Qualite : 0.29039240677223 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20025680_28-01-2025_19_25_24.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20025680 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20025680 AND mptpi.`type`=4230 To do Qualite : 0.28501245620499666 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20026767_01-02-2025_06_48_45.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20026767 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20026767 AND mptpi.`type`=4230 To do Qualite : 0.2555347520670635 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20026769_01-02-2025_06_53_01.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20026769 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20026769 AND mptpi.`type`=4230 To do Qualite : 0.2594065140897935 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20026771_01-02-2025_06_58_38.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20026771 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20026771 AND mptpi.`type`=4230 To do Qualite : 0.2557406890233243 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20026773_01-02-2025_07_04_55.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20026773 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20026773 AND mptpi.`type`=4230 To do Qualite : 0.2935648088251989 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20026798_05-02-2025_11_14_02.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20026798 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20026798 AND mptpi.`type`=4230 To do Qualite : 0.2770815406136396 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20026799_05-02-2025_11_04_53.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20026799 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20026799 AND mptpi.`type`=4230 To do Qualite : 0.2465929547069364 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20026800_01-02-2025_07_27_44.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20026800 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20026800 AND mptpi.`type`=4230 To do Qualite : 0.2802105432980099 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20026801_01-02-2025_07_32_53.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20026801 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20026801 AND mptpi.`type`=4230 To do Qualite : 0.26711760281037067 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20026803_01-02-2025_07_43_35.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20026803 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20026803 AND mptpi.`type`=4230 To do Qualite : 0.2696877608094265 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20026805_01-02-2025_07_45_47.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20026805 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20026805 AND mptpi.`type`=4230 To do Qualite : 0.25999220071616974 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20026807_01-02-2025_07_47_24.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20026807 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20026807 AND mptpi.`type`=4230 To do Qualite : 0.2489205421102428 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20026809_01-02-2025_07_52_32.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20026809 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20026809 AND mptpi.`type`=4230 To do Qualite : 0.1893886120409317 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20026811_01-02-2025_08_06_29.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20026811 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20026811 AND mptpi.`type`=4230 To do Qualite : 0.1955292822026263 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20026813_01-02-2025_08_02_34.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20026813 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20026813 AND mptpi.`type`=4230 To do Qualite : 0.22423053084691272 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20026815_01-02-2025_08_15_08.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20026815 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20026815 AND mptpi.`type`=4230 To do Qualite : 0.22642765616547947 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20026816_05-02-2025_11_14_23.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20026816 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20026816 AND mptpi.`type`=4230 To do Qualite : 0.22251355261761335 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20026828_01-02-2025_08_22_47.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20026828 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20026828 AND mptpi.`type`=4230 To do Qualite : 0.21753715834039727 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20026829_01-02-2025_08_30_07.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20026829 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20026829 AND mptpi.`type`=4230 To do Qualite : 0.22717589140502054 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20026830_28-01-2025_19_55_18.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20026830 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20026830 AND mptpi.`type`=4230 To do Qualite : 0.2323236230608528 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20028717_01-02-2025_10_41_17.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20028717 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20028717 AND mptpi.`type`=4230 To do Qualite : 0.2725070426390085 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20028732_05-02-2025_12_50_26.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20028732 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20028732 AND mptpi.`type`=4230 To do Qualite : 0.22925507863579023 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20028216_01-02-2025_09_02_24.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20028216 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20028216 AND mptpi.`type`=4230 To do Qualite : 0.29514481566160455 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20028230_01-02-2025_09_08_59.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20028230 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20028230 AND mptpi.`type`=4230 To do Qualite : 0.2617704416989119 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20028243_05-02-2025_11_33_32.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20028243 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20028243 AND mptpi.`type`=4230 To do Qualite : 0.2439740897722805 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20028244_01-02-2025_09_19_32.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20028244 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20028244 AND mptpi.`type`=4230 To do Qualite : 0.25947312026182706 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20028245_01-02-2025_09_29_52.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20028245 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20028245 AND mptpi.`type`=4230 To do Qualite : 0.2104963263647587 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20028247_01-02-2025_09_27_27.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20028247 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20028247 AND mptpi.`type`=4230 To do Qualite : 0.24672257678999313 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20028248_11-02-2025_09_44_27.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20028248 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20028248 AND mptpi.`type`=4230 To do Qualite : 0.22008442842505094 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20027812_01-02-2025_09_02_16.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20027812 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20027812 AND mptpi.`type`=4230 To do Qualite : 0.18958101163491609 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20028251_01-02-2025_09_50_09.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20028251 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20028251 AND mptpi.`type`=4230 To do Qualite : 0.18910519100911705 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20028253_01-02-2025_09_42_31.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20028253 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20028253 AND mptpi.`type`=4230 To do Qualite : 0.18245748443028506 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20028255_01-02-2025_09_48_24.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20028255 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20028255 AND mptpi.`type`=4230 To do Qualite : 0.15601343977296095 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20028745_01-02-2025_10_42_52.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20028745 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20028745 AND mptpi.`type`=4230 To do Qualite : 0.17589243586436976 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20028746_01-02-2025_10_47_23.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20028746 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20028746 AND mptpi.`type`=4230 To do Qualite : 0.16140887897465325 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20028747_11-02-2025_08_07_55.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20028747 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20028747 AND mptpi.`type`=4230 To do Qualite : 0.11921798633939734 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20028259_01-02-2025_09_52_59.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20028259 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20028259 AND mptpi.`type`=4230 To do Qualite : 0.15547413768501883 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20028260_01-02-2025_09_57_51.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20028260 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20028260 AND mptpi.`type`=4230 To do Qualite : 0.20451969605025053 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20028261_01-02-2025_10_03_20.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20028261 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20028261 AND mptpi.`type`=4230 To do Qualite : 0.17580755682540591 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20028262_08-02-2025_16_18_45.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20028262 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20028262 AND mptpi.`type`=4230 To do Qualite : 0.20184537510494882 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20028263_05-02-2025_12_36_31.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20028263 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20028263 AND mptpi.`type`=4230 To do Qualite : 0.22843919513215766 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20028264_05-02-2025_11_59_04.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20028264 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20028264 AND mptpi.`type`=4230 To do Qualite : 0.18913281511879976 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20028748_05-02-2025_11_51_43.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20028748 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20028748 AND mptpi.`type`=4230 To do Qualite : 0.15315532028432127 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20028749_28-01-2025_21_25_07.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20028749 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20028749 AND mptpi.`type`=4230 To do Qualite : 0.14752333764889064 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20029321_12-02-2025_09_08_36.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20029321 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20029321 AND mptpi.`type`=4230 To do Qualite : 0.16746138206797606 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20029335_10-02-2025_10_38_02.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20029335 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20029335 AND mptpi.`type`=4230 To do Qualite : 0.18286591649830336 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20029755_05-02-2025_12_08_17.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20029755 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20029755 AND mptpi.`type`=4230 To do Qualite : 0.17368499948003344 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20029770_11-02-2025_08_13_13.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20029770 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20029770 AND mptpi.`type`=4230 To do Qualite : 0.16526381428680542 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20029772_05-02-2025_12_17_51.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20029772 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20029772 AND mptpi.`type`=4230 To do Qualite : 0.16739773100554328 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20029775_11-02-2025_20_00_36.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20029775 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20029775 AND mptpi.`type`=4230 To do Qualite : 0.09562594924636353 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20029776_01-02-2025_11_37_20.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20029776 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20029776 AND mptpi.`type`=4230 To do Qualite : 0.1488551721768655 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20029777_01-02-2025_11_42_28.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20029777 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20029777 AND mptpi.`type`=4230 To do Qualite : 0.10924100707958963 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20029778_01-02-2025_11_47_23.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20029778 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20029778 AND mptpi.`type`=4230 To do Qualite : 0.13513598748904895 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20029779_01-02-2025_11_53_15.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20029779 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20029779 AND mptpi.`type`=4230 To do Qualite : 0.17495909346996102 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20029781_01-02-2025_11_57_27.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20029781 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20029781 AND mptpi.`type`=4230 To do Qualite : 0.1520795247588065 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20029783_01-02-2025_12_02_39.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20029783 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20029783 AND mptpi.`type`=4230 To do Qualite : 0.15855377695476236 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20029784_01-02-2025_12_15_23.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20029784 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20029784 AND mptpi.`type`=4230 To do Qualite : 0.18893627258551995 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20029786_01-02-2025_12_12_19.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20029786 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20029786 AND mptpi.`type`=4230 To do Qualite : 0.1563059243773074 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20029787_01-02-2025_12_21_08.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20029787 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20029787 AND mptpi.`type`=4230 To do Qualite : 0.17894223623713096 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20029788_28-01-2025_22_32_14.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20029788 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20029788 AND mptpi.`type`=4230 To do Qualite : 0.1977003338869479 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20030143_08-02-2025_17_12_11.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20030143 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20030143 AND mptpi.`type`=4230 To do Qualite : 0.1870174194672611 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20030158_01-02-2025_12_27_27.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20030158 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20030158 AND mptpi.`type`=4230 To do Qualite : 0.1609472248674475 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20030169_05-02-2025_12_42_32.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20030169 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20030169 AND mptpi.`type`=4230 To do Qualite : 0.12410168574143217 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20030173_01-02-2025_12_37_12.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20030173 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20030173 AND mptpi.`type`=4230 To do Qualite : 0.15265970920803026 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20030174_01-02-2025_12_42_25.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20030174 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20030174 AND mptpi.`type`=4230 To do Qualite : 0.179666582794064 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20030175_28-01-2025_23_48_31.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20030175 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20030175 AND mptpi.`type`=4230 To do Qualite : 0.17336119011926032 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20030176_01-02-2025_12_48_15.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20030176 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20030176 AND mptpi.`type`=4230 To do Qualite : 0.14097479690236392 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20030178_01-02-2025_12_53_50.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20030178 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20030178 AND mptpi.`type`=4230 To do Qualite : 0.17353481322514513 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20030179_01-02-2025_13_04_48.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20030179 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20030179 AND mptpi.`type`=4230 To do Qualite : 0.23323957703681192 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20030180_28-01-2025_22_46_59.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20030180 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20030180 AND mptpi.`type`=4230 To do Qualite : 0.13166575143646259 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031195_01-02-2025_13_16_38.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031195 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031195 AND mptpi.`type`=4230 To do Qualite : 0.18719129492852365 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031196_01-02-2025_13_20_11.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031196 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031196 AND mptpi.`type`=4230 To do Qualite : 0.15743538996420386 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031197_05-02-2025_15_07_26.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031197 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031197 AND mptpi.`type`=4230 To do Qualite : 0.14022915719000115 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031198_01-02-2025_13_30_31.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031198 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031198 AND mptpi.`type`=4230 To do Qualite : 0.19765733402105282 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031200_01-02-2025_13_37_47.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031200 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031200 AND mptpi.`type`=4230 To do Qualite : 0.18190762416213294 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031201_01-02-2025_13_47_01.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031201 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031201 AND mptpi.`type`=4230 To do Qualite : 0.20706978607020396 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031202_01-02-2025_13_43_32.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031202 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031202 AND mptpi.`type`=4230 To do Qualite : 0.2182387957897979 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031203_01-02-2025_13_48_52.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031203 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031203 AND mptpi.`type`=4230 To do Qualite : 0.2029867238840924 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031204_01-02-2025_13_52_21.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031204 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031204 AND mptpi.`type`=4230 To do Qualite : 0.11912917844170606 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031205_01-02-2025_13_57_40.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031205 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031205 AND mptpi.`type`=4230 To do Qualite : 0.1820526617459556 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031224_01-02-2025_14_02_46.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031224 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031224 AND mptpi.`type`=4230 To do Qualite : 0.20559819397191212 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031225_01-02-2025_14_08_20.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031225 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031225 AND mptpi.`type`=4230 To do Qualite : 0.16220353660655681 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031244_01-02-2025_14_12_14.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031244 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031244 AND mptpi.`type`=4230 To do Qualite : 0.18445652122652825 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031245_01-02-2025_14_18_19.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031245 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031245 AND mptpi.`type`=4230 To do Qualite : 0.19439637369943608 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031246_01-02-2025_14_27_48.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031246 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031246 AND mptpi.`type`=4230 To do Qualite : 0.19358629851763964 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031247_01-02-2025_14_29_21.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031247 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031247 AND mptpi.`type`=4230 To do Qualite : 0.1546447258790202 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031248_01-02-2025_14_32_53.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031248 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031248 AND mptpi.`type`=4230 To do Qualite : 0.16169979258589173 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031249_01-02-2025_14_37_27.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031249 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031249 AND mptpi.`type`=4230 To do Qualite : 0.19123909441078055 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031250_01-02-2025_14_45_11.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031250 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031250 AND mptpi.`type`=4230 To do Qualite : 0.1613949731395143 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031251_01-02-2025_14_49_18.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031251 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031251 AND mptpi.`type`=4230 To do Qualite : 0.17571277132040658 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031252_01-02-2025_14_57_47.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031252 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031252 AND mptpi.`type`=4230 To do Qualite : 0.16968392587873835 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031253_01-02-2025_15_08_02.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031253 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031253 AND mptpi.`type`=4230 To do Qualite : 0.15056427399423344 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031254_01-02-2025_15_11_59.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031254 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031254 AND mptpi.`type`=4230 To do Qualite : 0.13384762018812202 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031255_01-02-2025_15_13_17.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031255 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031255 AND mptpi.`type`=4230 To do Qualite : 0.16900217203356357 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031256_01-02-2025_15_13_59.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031256 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031256 AND mptpi.`type`=4230 To do Qualite : 0.14057832201479628 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031257_01-02-2025_15_19_08.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031257 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031257 AND mptpi.`type`=4230 To do Qualite : 0.1695259489131504 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031258_01-02-2025_15_29_40.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031258 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031258 AND mptpi.`type`=4230 To do Qualite : 0.1437417941441305 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031259_01-02-2025_15_27_38.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031259 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031259 AND mptpi.`type`=4230 To do Qualite : 0.12925024103777719 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031260_05-02-2025_19_22_26.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031260 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031260 AND mptpi.`type`=4230 To do Qualite : 0.1472336859235665 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031261_09-02-2025_08_14_12.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031261 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031261 AND mptpi.`type`=4230 To do Qualite : 0.15991512490654022 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031262_01-02-2025_15_42_25.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031262 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031262 AND mptpi.`type`=4230 To do Qualite : 0.14406405823812132 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031263_01-02-2025_15_48_37.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031263 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031263 AND mptpi.`type`=4230 To do Qualite : 0.15912164181735414 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031264_01-02-2025_15_53_56.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031264 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031264 AND mptpi.`type`=4230 To do Qualite : 0.1594045922392533 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031265_01-02-2025_15_57_30.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031265 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031265 AND mptpi.`type`=4230 To do Qualite : 0.16766599059351553 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031266_01-02-2025_16_02_44.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031266 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031266 AND mptpi.`type`=4230 To do Qualite : 0.1603782897624073 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031267_01-02-2025_16_07_45.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031267 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031267 AND mptpi.`type`=4230 To do Qualite : 0.16249621252297178 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031268_29-01-2025_07_48_12.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031268 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031268 AND mptpi.`type`=4230 To do Qualite : 0.2012595374104413 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031269_29-01-2025_05_47_22.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031269 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031269 AND mptpi.`type`=4230 To do Qualite : 0.1722001922860769 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031270_29-01-2025_06_45_08.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031270 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031270 AND mptpi.`type`=4230 To do Qualite : 0.182015523869177 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031271_29-01-2025_06_47_32.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031271 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031271 AND mptpi.`type`=4230 To do Qualite : 0.14782596987316016 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031272_29-01-2025_05_34_26.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031272 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031272 AND mptpi.`type`=4230 To do Qualite : 0.15857689310224563 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031273_29-01-2025_04_49_28.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031273 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031273 AND mptpi.`type`=4230 To do Qualite : 0.18879877868420938 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031274_29-01-2025_01_35_17.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031274 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031274 AND mptpi.`type`=4230 To do Qualite : 0.1844473003393099 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031275_29-01-2025_01_48_24.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031275 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031275 AND mptpi.`type`=4230 To do Qualite : 0.19854447229520153 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031276_29-01-2025_04_32_44.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031276 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031276 AND mptpi.`type`=4230 To do Qualite : 0.17405768829012647 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031277_29-01-2025_00_48_47.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031277 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031277 AND mptpi.`type`=4230 To do Qualite : 0.22243618687543576 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031278_29-01-2025_00_32_36.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031278 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031278 AND mptpi.`type`=4230 To do Qualite : 0.15874096573046934 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031279_29-01-2025_00_14_24.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031279 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031279 AND mptpi.`type`=4230 To do Qualite : 0.14790320935158704 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P20031280_29-01-2025_00_18_01.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 20031280 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11415 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11419 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11419 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11416 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11417 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11417 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11422 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 2 of step 11418 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11419 doesn't seem to be define in the database( WARNING : output 1 of step 11415 have datatype=7 whereas input 2 of step 11419 have datatype=None WARNING : type of output 3 of step 11419 doesn't seem to be define in the database( WARNING : type of input 1 of step 11416 doesn't seem to be define in the database( WARNING : type of output 1 of step 11416 doesn't seem to be define in the database( WARNING : type of input 3 of step 11417 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11416 have datatype=10 whereas input 0 of step 11420 have datatype=18 WARNING : type of input 5 of step 11418 doesn't seem to be define in the database( WARNING : output 0 of step 11420 have datatype=11 whereas input 5 of step 11418 have datatype=None WARNING : type of input 2 of step 11416 doesn't seem to be define in the database( WARNING : output 0 of step 11421 have datatype=5 whereas input 2 of step 11416 have datatype=None WARNING : output 0 of step 11418 have datatype=10 whereas input 0 of step 11422 have datatype=18 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20031280 AND mptpi.`type`=4230 To do NUMBER BATCH : 0 # DISPLAY ALL COLLECTED DATA : {'28012025': {'nb_upload': 205, 'nb_taggue_class': 205, 'nb_taggue_densite': 0}} Inside saveOutput : final : True verbose : 0 saveOutput not yet implemented for datou_step.type : split_time_score we use saveGeneral [1332404633, 1332404630, 1332404627, 1332404610, 1332404608, 1332404605, 1332404602, 1332404599, 1332404596, 1332404585, 1332404583, 1332404581, 1332404578, 1332404575, 1332404571, 1332404558, 1332404555, 1332404550, 1332404545, 1332404540, 1332404535] Looping around the photos to save general results len do output : 1 /20029321Didn't retrieve data . before output type Here is an output not treated by saveGeneral : Managing all output in save final without adding information in the mtr_datou_result ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404633', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404630', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404627', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404610', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404608', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404605', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404602', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404599', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404596', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404585', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404583', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404581', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404578', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404575', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404571', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404558', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404555', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404550', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404545', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404540', None, None, None, None, None, '2524174') ('4234', None, None, None, None, None, None, None, '2524174') ('4234', None, '1332404535', None, None, None, None, None, '2524174') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 22 time used for this insertion : 0.0179898738861084 save_final save missing photos in datou_result : time spend for datou_step_exec : 17.05465602874756 time spend to save output : 0.018336772918701172 total time spend for step 11 : 17.07299280166626 caffe_path_current : About to save ! 2 After save, about to update current ! update_current_state 236.55user 114.11system 21:23.46elapsed 27%CPU (0avgtext+0avgdata 2732628maxresident)k 194952inputs+117952outputs (7010major+10082391minor)pagefaults 0swaps