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 3804803' -s carac_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 : 2296103 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 : ['3804803'] with mtr_portfolio_ids : ['27393933'] and first list_photo_ids : [] new path : /proc/2296103/ 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 , BFBFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 2 ; length of list_pids : 2 ; length of list_args : 2 time to download the photos : 0.43347668647766113 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 Oct 1 10:50:13 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 : 10138 max_wait_temp : 1 max_wait : 0 gpu_flag : 0 2025-10-01 10:50:17.253688: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2025-10-01 10:50:17.284749: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3492910000 Hz 2025-10-01 10:50:17.286973: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f7f20000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-10-01 10:50:17.287036: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-10-01 10:50:17.291813: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-10-01 10:50:17.458981: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x38a29520 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-10-01 10:50:17.459040: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-10-01 10:50:17.460213: 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 2025-10-01 10:50:17.460650: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-10-01 10:50:17.464773: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-10-01 10:50:17.471407: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-10-01 10:50:17.472215: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-10-01 10:50:17.483675: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-10-01 10:50:17.486875: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-10-01 10:50:17.514374: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-10-01 10:50:17.516233: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-10-01 10:50:17.516363: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-10-01 10:50:17.517394: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-10-01 10:50:17.517416: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-10-01 10:50:17.517431: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-10-01 10:50:17.519161: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 9387 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. 2025-10-01 10:50:18.014655: 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 2025-10-01 10:50:18.014838: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-10-01 10:50:18.014867: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-10-01 10:50:18.014889: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-10-01 10:50:18.014932: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-10-01 10:50:18.014952: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-10-01 10:50:18.014971: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-10-01 10:50:18.014989: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-10-01 10:50:18.016720: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-10-01 10:50:18.018308: 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 2025-10-01 10:50:18.018379: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-10-01 10:50:18.018401: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-10-01 10:50:18.018422: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-10-01 10:50:18.018442: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-10-01 10:50:18.018461: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-10-01 10:50:18.018481: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-10-01 10:50:18.018501: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-10-01 10:50:18.020047: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-10-01 10:50:18.020082: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-10-01 10:50:18.020093: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-10-01 10:50:18.020102: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-10-01 10:50:18.021749: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 9387 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 : [] 2025-10-01 10:50:27.617471: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-10-01 10:50:27.829149: 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 : 2 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: -117.68438 max: 149.08437 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 8 time for calcul the mask position with numpy : 7.43865966796875e-05 nb_pixel_total : 53 time to create 1 rle with old method : 0.00021004676818847656 length of segment : 29 time for calcul the mask position with numpy : 7.62939453125e-05 nb_pixel_total : 1883 time to create 1 rle with old method : 0.0033359527587890625 length of segment : 41 time for calcul the mask position with numpy : 6.842613220214844e-05 nb_pixel_total : 648 time to create 1 rle with old method : 0.0012695789337158203 length of segment : 63 time for calcul the mask position with numpy : 5.555152893066406e-05 nb_pixel_total : 247 time to create 1 rle with old method : 0.0005846023559570312 length of segment : 43 time for calcul the mask position with numpy : 7.581710815429688e-05 nb_pixel_total : 894 time to create 1 rle with old method : 0.0019366741180419922 length of segment : 43 time for calcul the mask position with numpy : 8.273124694824219e-05 nb_pixel_total : 1936 time to create 1 rle with old method : 0.0037992000579833984 length of segment : 59 time for calcul the mask position with numpy : 5.316734313964844e-05 nb_pixel_total : 422 time to create 1 rle with old method : 0.0006606578826904297 length of segment : 48 time for calcul the mask position with numpy : 5.7220458984375e-05 nb_pixel_total : 271 time to create 1 rle with old method : 0.0006299018859863281 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: -115.52422 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 : 6.699562072753906e-05 nb_pixel_total : 1714 time to create 1 rle with old method : 0.0025768280029296875 length of segment : 31 time for calcul the mask position with numpy : 4.124641418457031e-05 nb_pixel_total : 181 time to create 1 rle with old method : 0.0002961158752441406 length of segment : 16 time for calcul the mask position with numpy : 9.036064147949219e-05 nb_pixel_total : 3833 time to create 1 rle with old method : 0.00542140007019043 length of segment : 56 time for calcul the mask position with numpy : 3.6716461181640625e-05 nb_pixel_total : 42 time to create 1 rle with old method : 9.703636169433594e-05 length of segment : 7 time for calcul the mask position with numpy : 5.340576171875e-05 nb_pixel_total : 1665 time to create 1 rle with old method : 0.0024743080139160156 length of segment : 26 time for calcul the mask position with numpy : 3.910064697265625e-05 nb_pixel_total : 95 time to create 1 rle with old method : 0.00017881393432617188 length of segment : 26 time for calcul the mask position with numpy : 9.942054748535156e-05 nb_pixel_total : 4152 time to create 1 rle with old method : 0.005792379379272461 length of segment : 61 time for calcul the mask position with numpy : 9.632110595703125e-05 nb_pixel_total : 3648 time to create 1 rle with old method : 0.0049991607666015625 length of segment : 55 Processing 1 images image shape: (400, 400, 3) min: 5.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -101.32109 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 : 0.0003654956817626953 nb_pixel_total : 7094 time to create 1 rle with old method : 0.011953592300415039 length of segment : 174 time for calcul the mask position with numpy : 0.00014281272888183594 nb_pixel_total : 733 time to create 1 rle with old method : 0.0016434192657470703 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: -116.10234 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 : 5.841255187988281e-05 nb_pixel_total : 1437 time to create 1 rle with old method : 0.0020599365234375 length of segment : 27 time for calcul the mask position with numpy : 7.104873657226562e-05 nb_pixel_total : 1975 time to create 1 rle with old method : 0.002384662628173828 length of segment : 56 time for calcul the mask position with numpy : 8.392333984375e-05 nb_pixel_total : 4198 time to create 1 rle with old method : 0.005124568939208984 length of segment : 56 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: 140.02969 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 4 time for calcul the mask position with numpy : 4.4345855712890625e-05 nb_pixel_total : 704 time to create 1 rle with old method : 0.0009970664978027344 length of segment : 24 time for calcul the mask position with numpy : 6.556510925292969e-05 nb_pixel_total : 1611 time to create 1 rle with old method : 0.0020744800567626953 length of segment : 150 time for calcul the mask position with numpy : 9.059906005859375e-05 nb_pixel_total : 2426 time to create 1 rle with old method : 0.0032494068145751953 length of segment : 71 time for calcul the mask position with numpy : 0.000148773193359375 nb_pixel_total : 2745 time to create 1 rle with old method : 0.0033540725708007812 length of segment : 114 Processing 1 images image shape: (400, 400, 3) min: 13.00000 max: 190.00000 molded_images shape: (1, 640, 640, 3) min: -87.39141 max: 62.98516 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: -112.20000 max: 136.81484 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 5 time for calcul the mask position with numpy : 0.00011539459228515625 nb_pixel_total : 3406 time to create 1 rle with old method : 0.004764556884765625 length of segment : 56 time for calcul the mask position with numpy : 0.00016498565673828125 nb_pixel_total : 4993 time to create 1 rle with old method : 0.006851673126220703 length of segment : 79 time for calcul the mask position with numpy : 6.341934204101562e-05 nb_pixel_total : 411 time to create 1 rle with old method : 0.0006773471832275391 length of segment : 19 time for calcul the mask position with numpy : 7.343292236328125e-05 nb_pixel_total : 1552 time to create 1 rle with old method : 0.0022101402282714844 length of segment : 66 time for calcul the mask position with numpy : 4.601478576660156e-05 nb_pixel_total : 284 time to create 1 rle with old method : 0.00048160552978515625 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: -118.50469 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 19 time for calcul the mask position with numpy : 8.7738037109375e-05 nb_pixel_total : 301 time to create 1 rle with old method : 0.0004811286926269531 length of segment : 43 time for calcul the mask position with numpy : 5.507469177246094e-05 nb_pixel_total : 595 time to create 1 rle with old method : 0.00101470947265625 length of segment : 31 time for calcul the mask position with numpy : 4.76837158203125e-05 nb_pixel_total : 831 time to create 1 rle with old method : 0.001252889633178711 length of segment : 51 time for calcul the mask position with numpy : 4.9114227294921875e-05 nb_pixel_total : 483 time to create 1 rle with old method : 0.0008020401000976562 length of segment : 36 time for calcul the mask position with numpy : 8.177757263183594e-05 nb_pixel_total : 576 time to create 1 rle with old method : 0.0010039806365966797 length of segment : 76 time for calcul the mask position with numpy : 8.106231689453125e-05 nb_pixel_total : 1618 time to create 1 rle with old method : 0.002402067184448242 length of segment : 91 time for calcul the mask position with numpy : 5.698204040527344e-05 nb_pixel_total : 538 time to create 1 rle with old method : 0.0008194446563720703 length of segment : 31 time for calcul the mask position with numpy : 6.985664367675781e-05 nb_pixel_total : 1174 time to create 1 rle with old method : 0.0017657279968261719 length of segment : 50 time for calcul the mask position with numpy : 5.4836273193359375e-05 nb_pixel_total : 515 time to create 1 rle with old method : 0.0008456707000732422 length of segment : 32 time for calcul the mask position with numpy : 7.867813110351562e-05 nb_pixel_total : 1926 time to create 1 rle with old method : 0.0028121471405029297 length of segment : 49 time for calcul the mask position with numpy : 4.291534423828125e-05 nb_pixel_total : 89 time to create 1 rle with old method : 0.00015687942504882812 length of segment : 35 time for calcul the mask position with numpy : 7.867813110351562e-05 nb_pixel_total : 1271 time to create 1 rle with old method : 0.001768350601196289 length of segment : 56 time for calcul the mask position with numpy : 9.584426879882812e-05 nb_pixel_total : 2127 time to create 1 rle with old method : 0.0028362274169921875 length of segment : 81 time for calcul the mask position with numpy : 4.935264587402344e-05 nb_pixel_total : 174 time to create 1 rle with old method : 0.0003066062927246094 length of segment : 16 time for calcul the mask position with numpy : 6.341934204101562e-05 nb_pixel_total : 867 time to create 1 rle with old method : 0.0012199878692626953 length of segment : 37 time for calcul the mask position with numpy : 6.985664367675781e-05 nb_pixel_total : 2381 time to create 1 rle with old method : 0.0027055740356445312 length of segment : 81 time for calcul the mask position with numpy : 4.1961669921875e-05 nb_pixel_total : 465 time to create 1 rle with old method : 0.0005726814270019531 length of segment : 37 time for calcul the mask position with numpy : 3.886222839355469e-05 nb_pixel_total : 755 time to create 1 rle with old method : 0.0009484291076660156 length of segment : 26 time for calcul the mask position with numpy : 5.078315734863281e-05 nb_pixel_total : 1039 time to create 1 rle with old method : 0.0013246536254882812 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: -119.21953 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 12 time for calcul the mask position with numpy : 6.270408630371094e-05 nb_pixel_total : 956 time to create 1 rle with old method : 0.0011899471282958984 length of segment : 65 time for calcul the mask position with numpy : 4.100799560546875e-05 nb_pixel_total : 475 time to create 1 rle with old method : 0.0007271766662597656 length of segment : 17 time for calcul the mask position with numpy : 0.00027632713317871094 nb_pixel_total : 14644 time to create 1 rle with old method : 0.017022132873535156 length of segment : 177 time for calcul the mask position with numpy : 0.00012159347534179688 nb_pixel_total : 1028 time to create 1 rle with old method : 0.0018651485443115234 length of segment : 91 time for calcul the mask position with numpy : 4.363059997558594e-05 nb_pixel_total : 79 time to create 1 rle with old method : 0.0001659393310546875 length of segment : 13 time for calcul the mask position with numpy : 4.6253204345703125e-05 nb_pixel_total : 151 time to create 1 rle with old method : 0.00029397010803222656 length of segment : 28 time for calcul the mask position with numpy : 0.0002071857452392578 nb_pixel_total : 4950 time to create 1 rle with old method : 0.007775306701660156 length of segment : 135 time for calcul the mask position with numpy : 7.963180541992188e-05 nb_pixel_total : 447 time to create 1 rle with old method : 0.000993967056274414 length of segment : 21 time for calcul the mask position with numpy : 0.0003943443298339844 nb_pixel_total : 14206 time to create 1 rle with old method : 0.023645401000976562 length of segment : 161 time for calcul the mask position with numpy : 0.00010228157043457031 nb_pixel_total : 805 time to create 1 rle with old method : 0.00127410888671875 length of segment : 117 time for calcul the mask position with numpy : 0.00017523765563964844 nb_pixel_total : 3152 time to create 1 rle with old method : 0.005032777786254883 length of segment : 107 time for calcul the mask position with numpy : 5.626678466796875e-05 nb_pixel_total : 880 time to create 1 rle with old method : 0.0012426376342773438 length of segment : 79 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: 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 : 9.393692016601562e-05 nb_pixel_total : 523 time to create 1 rle with old method : 0.001018524169921875 length of segment : 73 time for calcul the mask position with numpy : 6.031990051269531e-05 nb_pixel_total : 597 time to create 1 rle with old method : 0.0012111663818359375 length of segment : 19 time for calcul the mask position with numpy : 0.00012755393981933594 nb_pixel_total : 1316 time to create 1 rle with old method : 0.0022499561309814453 length of segment : 128 time for calcul the mask position with numpy : 7.414817810058594e-05 nb_pixel_total : 359 time to create 1 rle with old method : 0.0008153915405273438 length of segment : 21 time for calcul the mask position with numpy : 5.7697296142578125e-05 nb_pixel_total : 606 time to create 1 rle with old method : 0.0008647441864013672 length of segment : 21 time for calcul the mask position with numpy : 6.532669067382812e-05 nb_pixel_total : 810 time to create 1 rle with old method : 0.0010743141174316406 length of segment : 63 time for calcul the mask position with numpy : 0.00018596649169921875 nb_pixel_total : 3443 time to create 1 rle with old method : 0.004241466522216797 length of segment : 183 time for calcul the mask position with numpy : 8.463859558105469e-05 nb_pixel_total : 1245 time to create 1 rle with old method : 0.001516103744506836 length of segment : 88 time for calcul the mask position with numpy : 6.079673767089844e-05 nb_pixel_total : 808 time to create 1 rle with old method : 0.0010395050048828125 length of segment : 62 time for calcul the mask position with numpy : 0.00023317337036132812 nb_pixel_total : 2992 time to create 1 rle with old method : 0.004021167755126953 length of segment : 160 Processing 1 images image shape: (280, 400, 3) min: 4.00000 max: 166.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 39.21953 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: 148.39297 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 13 time for calcul the mask position with numpy : 0.00010967254638671875 nb_pixel_total : 838 time to create 1 rle with old method : 0.0018389225006103516 length of segment : 38 time for calcul the mask position with numpy : 8.821487426757812e-05 nb_pixel_total : 278 time to create 1 rle with old method : 0.0019676685333251953 length of segment : 18 time for calcul the mask position with numpy : 7.82012939453125e-05 nb_pixel_total : 577 time to create 1 rle with old method : 0.0042078495025634766 length of segment : 26 time for calcul the mask position with numpy : 0.00029015541076660156 nb_pixel_total : 9284 time to create 1 rle with old method : 0.026282072067260742 length of segment : 179 time for calcul the mask position with numpy : 8.0108642578125e-05 nb_pixel_total : 1151 time to create 1 rle with old method : 0.0024271011352539062 length of segment : 26 time for calcul the mask position with numpy : 8.678436279296875e-05 nb_pixel_total : 1382 time to create 1 rle with old method : 0.002949237823486328 length of segment : 31 time for calcul the mask position with numpy : 7.486343383789062e-05 nb_pixel_total : 1587 time to create 1 rle with old method : 0.0033245086669921875 length of segment : 39 time for calcul the mask position with numpy : 7.05718994140625e-05 nb_pixel_total : 1389 time to create 1 rle with old method : 0.001893758773803711 length of segment : 51 time for calcul the mask position with numpy : 5.7697296142578125e-05 nb_pixel_total : 286 time to create 1 rle with old method : 0.0006530284881591797 length of segment : 18 time for calcul the mask position with numpy : 8.678436279296875e-05 nb_pixel_total : 1675 time to create 1 rle with old method : 0.0029528141021728516 length of segment : 40 time for calcul the mask position with numpy : 4.982948303222656e-05 nb_pixel_total : 91 time to create 1 rle with old method : 0.000240325927734375 length of segment : 10 time for calcul the mask position with numpy : 6.794929504394531e-05 nb_pixel_total : 786 time to create 1 rle with old method : 0.0014519691467285156 length of segment : 39 time for calcul the mask position with numpy : 4.5299530029296875e-05 nb_pixel_total : 1116 time to create 1 rle with old method : 0.0019512176513671875 length of segment : 26 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: 148.51016 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 19 time for calcul the mask position with numpy : 6.4849853515625e-05 nb_pixel_total : 1170 time to create 1 rle with old method : 0.0015854835510253906 length of segment : 39 time for calcul the mask position with numpy : 3.981590270996094e-05 nb_pixel_total : 172 time to create 1 rle with old method : 0.00026035308837890625 length of segment : 17 time for calcul the mask position with numpy : 5.173683166503906e-05 nb_pixel_total : 842 time to create 1 rle with old method : 0.001096963882446289 length of segment : 52 time for calcul the mask position with numpy : 4.935264587402344e-05 nb_pixel_total : 300 time to create 1 rle with old method : 0.00047135353088378906 length of segment : 30 time for calcul the mask position with numpy : 3.647804260253906e-05 nb_pixel_total : 198 time to create 1 rle with old method : 0.00033473968505859375 length of segment : 15 time for calcul the mask position with numpy : 5.221366882324219e-05 nb_pixel_total : 837 time to create 1 rle with old method : 0.0010952949523925781 length of segment : 37 time for calcul the mask position with numpy : 4.100799560546875e-05 nb_pixel_total : 342 time to create 1 rle with old method : 0.0005095005035400391 length of segment : 22 time for calcul the mask position with numpy : 6.365776062011719e-05 nb_pixel_total : 399 time to create 1 rle with old method : 0.0010313987731933594 length of segment : 25 time for calcul the mask position with numpy : 3.457069396972656e-05 nb_pixel_total : 159 time to create 1 rle with old method : 0.0002448558807373047 length of segment : 19 time for calcul the mask position with numpy : 3.2901763916015625e-05 nb_pixel_total : 128 time to create 1 rle with old method : 0.0002465248107910156 length of segment : 12 time for calcul the mask position with numpy : 4.839897155761719e-05 nb_pixel_total : 774 time to create 1 rle with old method : 0.0010123252868652344 length of segment : 49 time for calcul the mask position with numpy : 6.794929504394531e-05 nb_pixel_total : 1087 time to create 1 rle with old method : 0.0018086433410644531 length of segment : 47 time for calcul the mask position with numpy : 3.647804260253906e-05 nb_pixel_total : 238 time to create 1 rle with old method : 0.00034499168395996094 length of segment : 20 time for calcul the mask position with numpy : 4.291534423828125e-05 nb_pixel_total : 627 time to create 1 rle with old method : 0.0008182525634765625 length of segment : 38 time for calcul the mask position with numpy : 3.886222839355469e-05 nb_pixel_total : 335 time to create 1 rle with old method : 0.00045180320739746094 length of segment : 26 time for calcul the mask position with numpy : 3.504753112792969e-05 nb_pixel_total : 209 time to create 1 rle with old method : 0.00030612945556640625 length of segment : 21 time for calcul the mask position with numpy : 3.4809112548828125e-05 nb_pixel_total : 217 time to create 1 rle with old method : 0.00031113624572753906 length of segment : 29 time for calcul the mask position with numpy : 3.314018249511719e-05 nb_pixel_total : 76 time to create 1 rle with old method : 0.0001163482666015625 length of segment : 20 time for calcul the mask position with numpy : 3.147125244140625e-05 nb_pixel_total : 155 time to create 1 rle with old method : 0.00025653839111328125 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: 150.12344 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 11 time for calcul the mask position with numpy : 8.0108642578125e-05 nb_pixel_total : 2720 time to create 1 rle with old method : 0.0039255619049072266 length of segment : 66 time for calcul the mask position with numpy : 0.00010323524475097656 nb_pixel_total : 1165 time to create 1 rle with old method : 0.0015132427215576172 length of segment : 67 time for calcul the mask position with numpy : 6.031990051269531e-05 nb_pixel_total : 949 time to create 1 rle with old method : 0.0014405250549316406 length of segment : 46 time for calcul the mask position with numpy : 6.914138793945312e-05 nb_pixel_total : 2075 time to create 1 rle with old method : 0.0028553009033203125 length of segment : 53 time for calcul the mask position with numpy : 0.0001747608184814453 nb_pixel_total : 6007 time to create 1 rle with old method : 0.007573604583740234 length of segment : 127 time for calcul the mask position with numpy : 4.458427429199219e-05 nb_pixel_total : 459 time to create 1 rle with old method : 0.0006303787231445312 length of segment : 25 time for calcul the mask position with numpy : 3.719329833984375e-05 nb_pixel_total : 470 time to create 1 rle with old method : 0.0006527900695800781 length of segment : 26 time for calcul the mask position with numpy : 4.506111145019531e-05 nb_pixel_total : 409 time to create 1 rle with old method : 0.0005536079406738281 length of segment : 26 time for calcul the mask position with numpy : 6.580352783203125e-05 nb_pixel_total : 2126 time to create 1 rle with old method : 0.0026755332946777344 length of segment : 52 time for calcul the mask position with numpy : 3.790855407714844e-05 nb_pixel_total : 410 time to create 1 rle with old method : 0.0005662441253662109 length of segment : 25 time for calcul the mask position with numpy : 0.00013566017150878906 nb_pixel_total : 4142 time to create 1 rle with old method : 0.012969255447387695 length of segment : 163 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 : 3.933906555175781e-05 nb_pixel_total : 210 time to create 1 rle with old method : 0.0003323554992675781 length of segment : 17 time for calcul the mask position with numpy : 5.5789947509765625e-05 nb_pixel_total : 1330 time to create 1 rle with old method : 0.0017647743225097656 length of segment : 60 time for calcul the mask position with numpy : 0.0001010894775390625 nb_pixel_total : 4166 time to create 1 rle with old method : 0.005071878433227539 length of segment : 88 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: -118.18828 max: 149.08437 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 7 time for calcul the mask position with numpy : 4.839897155761719e-05 nb_pixel_total : 125 time to create 1 rle with old method : 0.00027108192443847656 length of segment : 28 time for calcul the mask position with numpy : 4.863739013671875e-05 nb_pixel_total : 68 time to create 1 rle with old method : 0.00013971328735351562 length of segment : 12 time for calcul the mask position with numpy : 6.556510925292969e-05 nb_pixel_total : 2054 time to create 1 rle with old method : 0.0028159618377685547 length of segment : 34 time for calcul the mask position with numpy : 7.510185241699219e-05 nb_pixel_total : 452 time to create 1 rle with old method : 0.0007266998291015625 length of segment : 50 time for calcul the mask position with numpy : 8.463859558105469e-05 nb_pixel_total : 91 time to create 1 rle with old method : 0.0002384185791015625 length of segment : 17 time for calcul the mask position with numpy : 4.506111145019531e-05 nb_pixel_total : 398 time to create 1 rle with old method : 0.0005772113800048828 length of segment : 33 time for calcul the mask position with numpy : 7.796287536621094e-05 nb_pixel_total : 2116 time to create 1 rle with old method : 0.002895355224609375 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: -116.02031 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 : 6.67572021484375e-05 nb_pixel_total : 1544 time to create 1 rle with old method : 0.002161741256713867 length of segment : 28 time for calcul the mask position with numpy : 9.226799011230469e-05 nb_pixel_total : 3662 time to create 1 rle with old method : 0.004650115966796875 length of segment : 55 time for calcul the mask position with numpy : 6.508827209472656e-05 nb_pixel_total : 1451 time to create 1 rle with old method : 0.0019402503967285156 length of segment : 30 time for calcul the mask position with numpy : 5.8650970458984375e-05 nb_pixel_total : 219 time to create 1 rle with old method : 0.0003495216369628906 length of segment : 36 time for calcul the mask position with numpy : 7.510185241699219e-05 nb_pixel_total : 2039 time to create 1 rle with old method : 0.0025675296783447266 length of segment : 85 time for calcul the mask position with numpy : 0.00011730194091796875 nb_pixel_total : 4264 time to create 1 rle with old method : 0.005418062210083008 length of segment : 61 time for calcul the mask position with numpy : 4.5299530029296875e-05 nb_pixel_total : 232 time to create 1 rle with old method : 0.0003387928009033203 length of segment : 41 time for calcul the mask position with numpy : 8.845329284667969e-05 nb_pixel_total : 2222 time to create 1 rle with old method : 0.002908468246459961 length of segment : 89 Processing 1 images image shape: (400, 400, 3) min: 14.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -92.02813 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 : 0.0001785755157470703 nb_pixel_total : 9549 time to create 1 rle with old method : 0.012597084045410156 length of segment : 198 time for calcul the mask position with numpy : 0.00011849403381347656 nb_pixel_total : 913 time to create 1 rle with old method : 0.0013852119445800781 length of segment : 40 time for calcul the mask position with numpy : 8.320808410644531e-05 nb_pixel_total : 2081 time to create 1 rle with old method : 0.002686738967895508 length of segment : 57 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -119.70391 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 : 1356 time to create 1 rle with old method : 0.0019805431365966797 length of segment : 25 time for calcul the mask position with numpy : 5.412101745605469e-05 nb_pixel_total : 330 time to create 1 rle with old method : 0.0006582736968994141 length of segment : 22 time for calcul the mask position with numpy : 5.078315734863281e-05 nb_pixel_total : 91 time to create 1 rle with old method : 0.00018262863159179688 length of segment : 15 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: 139.15859 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 7 time for calcul the mask position with numpy : 5.4836273193359375e-05 nb_pixel_total : 717 time to create 1 rle with old method : 0.0011494159698486328 length of segment : 25 time for calcul the mask position with numpy : 0.00015020370483398438 nb_pixel_total : 2380 time to create 1 rle with old method : 0.003342151641845703 length of segment : 129 time for calcul the mask position with numpy : 0.0001609325408935547 nb_pixel_total : 3589 time to create 1 rle with old method : 0.004717588424682617 length of segment : 152 time for calcul the mask position with numpy : 9.131431579589844e-05 nb_pixel_total : 435 time to create 1 rle with old method : 0.0007867813110351562 length of segment : 78 time for calcul the mask position with numpy : 0.00012683868408203125 nb_pixel_total : 2303 time to create 1 rle with old method : 0.004082679748535156 length of segment : 152 time for calcul the mask position with numpy : 0.0007612705230712891 nb_pixel_total : 57447 time to create 1 rle with old method : 0.07677912712097168 length of segment : 294 time for calcul the mask position with numpy : 0.00013589859008789062 nb_pixel_total : 1342 time to create 1 rle with old method : 0.0023756027221679688 length of segment : 139 Processing 1 images image shape: (400, 400, 3) min: 15.00000 max: 186.00000 molded_images shape: (1, 640, 640, 3) min: -82.77031 max: 59.17656 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: -113.90313 max: 136.44375 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 5 time for calcul the mask position with numpy : 8.845329284667969e-05 nb_pixel_total : 452 time to create 1 rle with old method : 0.0011832714080810547 length of segment : 21 time for calcul the mask position with numpy : 0.00018548965454101562 nb_pixel_total : 4948 time to create 1 rle with old method : 0.009238958358764648 length of segment : 67 time for calcul the mask position with numpy : 0.00013589859008789062 nb_pixel_total : 2965 time to create 1 rle with old method : 0.005326986312866211 length of segment : 65 time for calcul the mask position with numpy : 0.000148773193359375 nb_pixel_total : 3228 time to create 1 rle with old method : 0.006622314453125 length of segment : 52 time for calcul the mask position with numpy : 8.749961853027344e-05 nb_pixel_total : 1400 time to create 1 rle with old method : 0.0020520687103271484 length of segment : 64 Processing 1 images image shape: (400, 400, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -115.97344 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 16 time for calcul the mask position with numpy : 7.82012939453125e-05 nb_pixel_total : 366 time to create 1 rle with old method : 0.0006136894226074219 length of segment : 18 time for calcul the mask position with numpy : 3.719329833984375e-05 nb_pixel_total : 182 time to create 1 rle with old method : 0.0002732276916503906 length of segment : 39 time for calcul the mask position with numpy : 3.910064697265625e-05 nb_pixel_total : 396 time to create 1 rle with old method : 0.0006592273712158203 length of segment : 24 time for calcul the mask position with numpy : 6.151199340820312e-05 nb_pixel_total : 413 time to create 1 rle with old method : 0.0008685588836669922 length of segment : 33 time for calcul the mask position with numpy : 7.867813110351562e-05 nb_pixel_total : 547 time to create 1 rle with old method : 0.0010478496551513672 length of segment : 48 time for calcul the mask position with numpy : 6.747245788574219e-05 nb_pixel_total : 453 time to create 1 rle with old method : 0.0008959770202636719 length of segment : 27 time for calcul the mask position with numpy : 5.412101745605469e-05 nb_pixel_total : 232 time to create 1 rle with old method : 0.0004918575286865234 length of segment : 21 time for calcul the mask position with numpy : 5.2928924560546875e-05 nb_pixel_total : 216 time to create 1 rle with old method : 0.0004737377166748047 length of segment : 16 time for calcul the mask position with numpy : 6.103515625e-05 nb_pixel_total : 413 time to create 1 rle with old method : 0.0008766651153564453 length of segment : 38 time for calcul the mask position with numpy : 0.00010037422180175781 nb_pixel_total : 987 time to create 1 rle with old method : 0.0018618106842041016 length of segment : 50 time for calcul the mask position with numpy : 5.340576171875e-05 nb_pixel_total : 277 time to create 1 rle with old method : 0.0004994869232177734 length of segment : 21 time for calcul the mask position with numpy : 5.6743621826171875e-05 nb_pixel_total : 102 time to create 1 rle with old method : 0.0002110004425048828 length of segment : 24 time for calcul the mask position with numpy : 7.772445678710938e-05 nb_pixel_total : 296 time to create 1 rle with old method : 0.0006916522979736328 length of segment : 60 time for calcul the mask position with numpy : 7.152557373046875e-05 nb_pixel_total : 901 time to create 1 rle with old method : 0.0015552043914794922 length of segment : 48 time for calcul the mask position with numpy : 0.00012493133544921875 nb_pixel_total : 390 time to create 1 rle with old method : 0.0014319419860839844 length of segment : 23 time for calcul the mask position with numpy : 7.009506225585938e-05 nb_pixel_total : 212 time to create 1 rle with old method : 0.0005769729614257812 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: -117.95781 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 : 0.0003955364227294922 nb_pixel_total : 20493 time to create 1 rle with old method : 0.0242464542388916 length of segment : 178 time for calcul the mask position with numpy : 8.511543273925781e-05 nb_pixel_total : 1852 time to create 1 rle with old method : 0.002319812774658203 length of segment : 110 time for calcul the mask position with numpy : 0.00016355514526367188 nb_pixel_total : 4485 time to create 1 rle with old method : 0.00567173957824707 length of segment : 145 time for calcul the mask position with numpy : 8.678436279296875e-05 nb_pixel_total : 2345 time to create 1 rle with old method : 0.0037603378295898438 length of segment : 41 time for calcul the mask position with numpy : 6.771087646484375e-05 nb_pixel_total : 778 time to create 1 rle with old method : 0.0011067390441894531 length of segment : 36 time for calcul the mask position with numpy : 4.00543212890625e-05 nb_pixel_total : 207 time to create 1 rle with old method : 0.00033664703369140625 length of segment : 18 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: 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 : 5.888938903808594e-05 nb_pixel_total : 592 time to create 1 rle with old method : 0.0007960796356201172 length of segment : 78 time for calcul the mask position with numpy : 4.6253204345703125e-05 nb_pixel_total : 399 time to create 1 rle with old method : 0.0006921291351318359 length of segment : 17 time for calcul the mask position with numpy : 6.008148193359375e-05 nb_pixel_total : 1003 time to create 1 rle with old method : 0.001325368881225586 length of segment : 62 time for calcul the mask position with numpy : 4.935264587402344e-05 nb_pixel_total : 613 time to create 1 rle with old method : 0.0008897781372070312 length of segment : 20 time for calcul the mask position with numpy : 4.315376281738281e-05 nb_pixel_total : 597 time to create 1 rle with old method : 0.0008866786956787109 length of segment : 20 time for calcul the mask position with numpy : 7.128715515136719e-05 nb_pixel_total : 1333 time to create 1 rle with old method : 0.0017025470733642578 length of segment : 89 time for calcul the mask position with numpy : 6.222724914550781e-05 nb_pixel_total : 854 time to create 1 rle with old method : 0.0010976791381835938 length of segment : 59 time for calcul the mask position with numpy : 0.00018525123596191406 nb_pixel_total : 3086 time to create 1 rle with old method : 0.0038292407989501953 length of segment : 174 Processing 1 images image shape: (280, 400, 3) min: 8.00000 max: 168.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 39.65703 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: 149.99062 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 12 time for calcul the mask position with numpy : 0.00010180473327636719 nb_pixel_total : 831 time to create 1 rle with old method : 0.001590728759765625 length of segment : 38 time for calcul the mask position with numpy : 6.008148193359375e-05 nb_pixel_total : 627 time to create 1 rle with old method : 0.0009944438934326172 length of segment : 27 time for calcul the mask position with numpy : 8.058547973632812e-05 nb_pixel_total : 1186 time to create 1 rle with old method : 0.0019135475158691406 length of segment : 27 time for calcul the mask position with numpy : 0.0001685619354248047 nb_pixel_total : 5262 time to create 1 rle with old method : 0.008326292037963867 length of segment : 106 time for calcul the mask position with numpy : 8.225440979003906e-05 nb_pixel_total : 253 time to create 1 rle with old method : 0.0005507469177246094 length of segment : 16 time for calcul the mask position with numpy : 7.748603820800781e-05 nb_pixel_total : 1370 time to create 1 rle with old method : 0.0022602081298828125 length of segment : 53 time for calcul the mask position with numpy : 5.626678466796875e-05 nb_pixel_total : 227 time to create 1 rle with old method : 0.0004284381866455078 length of segment : 16 time for calcul the mask position with numpy : 5.2928924560546875e-05 nb_pixel_total : 300 time to create 1 rle with old method : 0.0006184577941894531 length of segment : 19 time for calcul the mask position with numpy : 6.508827209472656e-05 nb_pixel_total : 741 time to create 1 rle with old method : 0.001416921615600586 length of segment : 21 time for calcul the mask position with numpy : 4.887580871582031e-05 nb_pixel_total : 111 time to create 1 rle with old method : 0.0002799034118652344 length of segment : 9 time for calcul the mask position with numpy : 4.553794860839844e-05 nb_pixel_total : 118 time to create 1 rle with old method : 0.000339508056640625 length of segment : 9 time for calcul the mask position with numpy : 7.295608520507812e-05 nb_pixel_total : 891 time to create 1 rle with old method : 0.0017328262329101562 length of segment : 40 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: 148.60000 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 27 time for calcul the mask position with numpy : 7.033348083496094e-05 nb_pixel_total : 935 time to create 1 rle with old method : 0.001251220703125 length of segment : 48 time for calcul the mask position with numpy : 4.1484832763671875e-05 nb_pixel_total : 250 time to create 1 rle with old method : 0.0003571510314941406 length of segment : 29 time for calcul the mask position with numpy : 4.124641418457031e-05 nb_pixel_total : 447 time to create 1 rle with old method : 0.0006213188171386719 length of segment : 29 time for calcul the mask position with numpy : 3.504753112792969e-05 nb_pixel_total : 155 time to create 1 rle with old method : 0.000240325927734375 length of segment : 15 time for calcul the mask position with numpy : 5.221366882324219e-05 nb_pixel_total : 526 time to create 1 rle with old method : 0.0008180141448974609 length of segment : 33 time for calcul the mask position with numpy : 5.054473876953125e-05 nb_pixel_total : 794 time to create 1 rle with old method : 0.0010466575622558594 length of segment : 37 time for calcul the mask position with numpy : 8.273124694824219e-05 nb_pixel_total : 2858 time to create 1 rle with old method : 0.0034804344177246094 length of segment : 66 time for calcul the mask position with numpy : 4.553794860839844e-05 nb_pixel_total : 510 time to create 1 rle with old method : 0.0007169246673583984 length of segment : 23 time for calcul the mask position with numpy : 3.838539123535156e-05 nb_pixel_total : 315 time to create 1 rle with old method : 0.00047969818115234375 length of segment : 20 time for calcul the mask position with numpy : 4.649162292480469e-05 nb_pixel_total : 701 time to create 1 rle with old method : 0.0008878707885742188 length of segment : 38 time for calcul the mask position with numpy : 4.8160552978515625e-05 nb_pixel_total : 768 time to create 1 rle with old method : 0.0009925365447998047 length of segment : 29 time for calcul the mask position with numpy : 3.457069396972656e-05 nb_pixel_total : 193 time to create 1 rle with old method : 0.00027179718017578125 length of segment : 22 time for calcul the mask position with numpy : 4.38690185546875e-05 nb_pixel_total : 638 time to create 1 rle with old method : 0.0009264945983886719 length of segment : 28 time for calcul the mask position with numpy : 7.772445678710938e-05 nb_pixel_total : 952 time to create 1 rle with old method : 0.0012214183807373047 length of segment : 86 time for calcul the mask position with numpy : 4.673004150390625e-05 nb_pixel_total : 411 time to create 1 rle with old method : 0.0005748271942138672 length of segment : 30 time for calcul the mask position with numpy : 7.557868957519531e-05 nb_pixel_total : 615 time to create 1 rle with old method : 0.0007901191711425781 length of segment : 39 time for calcul the mask position with numpy : 7.963180541992188e-05 nb_pixel_total : 2649 time to create 1 rle with old method : 0.0033864974975585938 length of segment : 76 time for calcul the mask position with numpy : 8.606910705566406e-05 nb_pixel_total : 1334 time to create 1 rle with old method : 0.001821279525756836 length of segment : 90 time for calcul the mask position with numpy : 4.00543212890625e-05 nb_pixel_total : 159 time to create 1 rle with old method : 0.00025463104248046875 length of segment : 14 time for calcul the mask position with numpy : 4.744529724121094e-05 nb_pixel_total : 749 time to create 1 rle with old method : 0.0009913444519042969 length of segment : 50 time for calcul the mask position with numpy : 0.00012493133544921875 nb_pixel_total : 3570 time to create 1 rle with old method : 0.004511594772338867 length of segment : 132 time for calcul the mask position with numpy : 5.1021575927734375e-05 nb_pixel_total : 183 time to create 1 rle with old method : 0.00027298927307128906 length of segment : 32 time for calcul the mask position with numpy : 3.9577484130859375e-05 nb_pixel_total : 303 time to create 1 rle with old method : 0.00041174888610839844 length of segment : 32 time for calcul the mask position with numpy : 4.029273986816406e-05 nb_pixel_total : 472 time to create 1 rle with old method : 0.0006172657012939453 length of segment : 32 time for calcul the mask position with numpy : 6.4849853515625e-05 nb_pixel_total : 1208 time to create 1 rle with old method : 0.0015180110931396484 length of segment : 39 time for calcul the mask position with numpy : 7.104873657226562e-05 nb_pixel_total : 1880 time to create 1 rle with old method : 0.0023033618927001953 length of segment : 92 time for calcul the mask position with numpy : 3.528594970703125e-05 nb_pixel_total : 96 time to create 1 rle with old method : 0.00017762184143066406 length of segment : 9 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: 150.44766 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 15 time for calcul the mask position with numpy : 7.05718994140625e-05 nb_pixel_total : 1091 time to create 1 rle with old method : 0.0014579296112060547 length of segment : 38 time for calcul the mask position with numpy : 0.00011444091796875 nb_pixel_total : 2409 time to create 1 rle with old method : 0.0032699108123779297 length of segment : 76 time for calcul the mask position with numpy : 0.00017952919006347656 nb_pixel_total : 6249 time to create 1 rle with old method : 0.0075719356536865234 length of segment : 129 time for calcul the mask position with numpy : 7.987022399902344e-05 nb_pixel_total : 753 time to create 1 rle with old method : 0.0010972023010253906 length of segment : 27 time for calcul the mask position with numpy : 6.461143493652344e-05 nb_pixel_total : 961 time to create 1 rle with old method : 0.0012514591217041016 length of segment : 58 time for calcul the mask position with numpy : 7.343292236328125e-05 nb_pixel_total : 1353 time to create 1 rle with old method : 0.0016913414001464844 length of segment : 76 time for calcul the mask position with numpy : 0.00012564659118652344 nb_pixel_total : 3141 time to create 1 rle with old method : 0.0038285255432128906 length of segment : 74 time for calcul the mask position with numpy : 4.7206878662109375e-05 nb_pixel_total : 394 time to create 1 rle with old method : 0.0006158351898193359 length of segment : 25 time for calcul the mask position with numpy : 7.843971252441406e-05 nb_pixel_total : 2232 time to create 1 rle with old method : 0.0028972625732421875 length of segment : 85 time for calcul the mask position with numpy : 5.2928924560546875e-05 nb_pixel_total : 145 time to create 1 rle with old method : 0.00022363662719726562 length of segment : 20 time for calcul the mask position with numpy : 7.009506225585938e-05 nb_pixel_total : 777 time to create 1 rle with old method : 0.0011761188507080078 length of segment : 30 time for calcul the mask position with numpy : 4.267692565917969e-05 nb_pixel_total : 344 time to create 1 rle with old method : 0.0004646778106689453 length of segment : 20 time for calcul the mask position with numpy : 7.677078247070312e-05 nb_pixel_total : 414 time to create 1 rle with old method : 0.0005831718444824219 length of segment : 37 time for calcul the mask position with numpy : 0.00012254714965820312 nb_pixel_total : 3610 time to create 1 rle with old method : 0.004601955413818359 length of segment : 103 time for calcul the mask position with numpy : 5.698204040527344e-05 nb_pixel_total : 365 time to create 1 rle with old method : 0.0005211830139160156 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: 136.66250 image_metas shape: (1, 17) min: 0.00000 max: 640.00000 nb d'objets trouves : 9 time for calcul the mask position with numpy : 0.00018167495727539062 nb_pixel_total : 1379 time to create 1 rle with old method : 0.0066699981689453125 length of segment : 59 time for calcul the mask position with numpy : 7.367134094238281e-05 nb_pixel_total : 164 time to create 1 rle with old method : 0.0004734992980957031 length of segment : 16 time for calcul the mask position with numpy : 0.00023293495178222656 nb_pixel_total : 4010 time to create 1 rle with old method : 0.008279085159301758 length of segment : 86 time for calcul the mask position with numpy : 5.221366882324219e-05 nb_pixel_total : 25 time to create 1 rle with old method : 9.751319885253906e-05 length of segment : 5 time for calcul the mask position with numpy : 9.393692016601562e-05 nb_pixel_total : 1563 time to create 1 rle with old method : 0.0025298595428466797 length of segment : 74 time for calcul the mask position with numpy : 5.888938903808594e-05 nb_pixel_total : 212 time to create 1 rle with old method : 0.0004181861877441406 length of segment : 18 time for calcul the mask position with numpy : 4.839897155761719e-05 nb_pixel_total : 90 time to create 1 rle with old method : 0.0002143383026123047 length of segment : 11 time for calcul the mask position with numpy : 0.00016450881958007812 nb_pixel_total : 3394 time to create 1 rle with old method : 0.005123138427734375 length of segment : 158 time for calcul the mask position with numpy : 5.269050598144531e-05 nb_pixel_total : 213 time to create 1 rle with old method : 0.000324249267578125 length of segment : 18 Detection mask done ! Trying to reset tf kernel 2296235 begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 4696 tf kernel not reseted sub process len(results) : 243 len(list_Values) 243 None max_time_sub_proc : 3600 parent process len(results) : 0 len(list_Values) 243 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 : 9985 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 243 chid ids of type : 4228 Number RLEs to save : 12828 save missing photos in datou_result : time spend for datou_step_exec : 27.471208095550537 time spend to save output : 1.9031493663787842 total time spend for step 1 : 29.37435746192932 step2:brightness Wed Oct 1 10:50:42 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/1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6.jpg treat image : temp/1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a.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 : 2 time used for this insertion : 0.03640127182006836 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 2 time used for this insertion : 0.034595489501953125 save missing photos in datou_result : time spend for datou_step_exec : 0.6173789501190186 time spend to save output : 0.08825564384460449 total time spend for step 2 : 0.705634593963623 step3:blur_detection Wed Oct 1 10:50:43 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/1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6.jpg resize: (1080, 1920) 1386931933 -7.476559459946674 treat image : temp/1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a.jpg resize: (1080, 1920) 1386931871 -7.413876185147374 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 : 2 time used for this insertion : 0.036084651947021484 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 2 time used for this insertion : 0.03542375564575195 save missing photos in datou_result : time spend for datou_step_exec : 2.4265096187591553 time spend to save output : 0.08998298645019531 total time spend for step 3 : 2.5164926052093506 step4:rle_unique_nms_with_priority Wed Oct 1 10:50:46 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 243 chid ids of type : 4228 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++nb_obj : 117 nb_hashtags : 4 time to prepare the origin masks : 1.02138352394104 time for calcul the mask position with numpy : 0.7597644329071045 nb_pixel_total : 1936500 time to create 1 rle with new method : 0.10008049011230469 time for calcul the mask position with numpy : 0.009154319763183594 nb_pixel_total : 733 time to create 1 rle with old method : 0.0009207725524902344 time for calcul the mask position with numpy : 0.008575439453125 nb_pixel_total : 648 time to create 1 rle with old method : 0.0007762908935546875 time for calcul the mask position with numpy : 0.00855398178100586 nb_pixel_total : 247 time to create 1 rle with old method : 0.0003306865692138672 time for calcul the mask position with numpy : 0.008474111557006836 nb_pixel_total : 231 time to create 1 rle with old method : 0.0003337860107421875 time for calcul the mask position with numpy : 0.00847172737121582 nb_pixel_total : 425 time to create 1 rle with old method : 0.000576019287109375 time for calcul the mask position with numpy : 0.008544921875 nb_pixel_total : 20 time to create 1 rle with old method : 5.4836273193359375e-05 time for calcul the mask position with numpy : 0.008523225784301758 nb_pixel_total : 1883 time to create 1 rle with old method : 0.0021042823791503906 time for calcul the mask position with numpy : 0.008484125137329102 nb_pixel_total : 95 time to create 1 rle with old method : 0.00011777877807617188 time for calcul the mask position with numpy : 0.008488655090332031 nb_pixel_total : 219 time to create 1 rle with old method : 0.0003237724304199219 time for calcul the mask position with numpy : 0.008490562438964844 nb_pixel_total : 42 time to create 1 rle with old method : 5.459785461425781e-05 time for calcul the mask position with numpy : 0.008483171463012695 nb_pixel_total : 53 time to create 1 rle with old method : 8.249282836914062e-05 time for calcul the mask position with numpy : 0.00856781005859375 nb_pixel_total : 7094 time to create 1 rle with old method : 0.008130550384521484 time for calcul the mask position with numpy : 0.009841680526733398 nb_pixel_total : 3833 time to create 1 rle with old method : 0.004380226135253906 time for calcul the mask position with numpy : 0.008455991744995117 nb_pixel_total : 358 time to create 1 rle with old method : 0.0004603862762451172 time for calcul the mask position with numpy : 0.008535146713256836 nb_pixel_total : 5 time to create 1 rle with old method : 1.3113021850585938e-05 time for calcul the mask position with numpy : 0.008599996566772461 nb_pixel_total : 1975 time to create 1 rle with old method : 0.0022695064544677734 time for calcul the mask position with numpy : 0.010170459747314453 nb_pixel_total : 181 time to create 1 rle with old method : 0.00021600723266601562 time for calcul the mask position with numpy : 0.008516788482666016 nb_pixel_total : 1714 time to create 1 rle with old method : 0.001985788345336914 time for calcul the mask position with numpy : 0.008467435836791992 nb_pixel_total : 71 time to create 1 rle with old method : 0.00015091896057128906 time for calcul the mask position with numpy : 0.008501052856445312 nb_pixel_total : 4198 time to create 1 rle with old method : 0.004780292510986328 time for calcul the mask position with numpy : 0.008505582809448242 nb_pixel_total : 1615 time to create 1 rle with old method : 0.0019276142120361328 time for calcul the mask position with numpy : 0.008457183837890625 nb_pixel_total : 1611 time to create 1 rle with old method : 0.0018668174743652344 time for calcul the mask position with numpy : 0.008515357971191406 nb_pixel_total : 2426 time to create 1 rle with old method : 0.0028142929077148438 time for calcul the mask position with numpy : 0.008471012115478516 nb_pixel_total : 1437 time to create 1 rle with old method : 0.0016765594482421875 time for calcul the mask position with numpy : 0.008478879928588867 nb_pixel_total : 704 time to create 1 rle with old method : 0.0008234977722167969 time for calcul the mask position with numpy : 0.008496284484863281 nb_pixel_total : 810 time to create 1 rle with old method : 0.0009381771087646484 time for calcul the mask position with numpy : 0.008486032485961914 nb_pixel_total : 359 time to create 1 rle with old method : 0.0004413127899169922 time for calcul the mask position with numpy : 0.008426904678344727 nb_pixel_total : 75 time to create 1 rle with old method : 0.00011920928955078125 time for calcul the mask position with numpy : 0.008418083190917969 nb_pixel_total : 4950 time to create 1 rle with old method : 0.0056645870208740234 time for calcul the mask position with numpy : 0.008452177047729492 nb_pixel_total : 221 time to create 1 rle with old method : 0.0002892017364501953 time for calcul the mask position with numpy : 0.008457422256469727 nb_pixel_total : 27 time to create 1 rle with old method : 6.29425048828125e-05 time for calcul the mask position with numpy : 0.008452892303466797 nb_pixel_total : 597 time to create 1 rle with old method : 0.0006959438323974609 time for calcul the mask position with numpy : 0.00844120979309082 nb_pixel_total : 1039 time to create 1 rle with old method : 0.0012335777282714844 time for calcul the mask position with numpy : 0.008420228958129883 nb_pixel_total : 1316 time to create 1 rle with old method : 0.0015425682067871094 time for calcul the mask position with numpy : 0.008442163467407227 nb_pixel_total : 301 time to create 1 rle with old method : 0.00034737586975097656 time for calcul the mask position with numpy : 0.009797811508178711 nb_pixel_total : 28 time to create 1 rle with old method : 5.1021575927734375e-05 time for calcul the mask position with numpy : 0.008418798446655273 nb_pixel_total : 210 time to create 1 rle with old method : 0.0002760887145996094 time for calcul the mask position with numpy : 0.008518218994140625 nb_pixel_total : 465 time to create 1 rle with old method : 0.0005395412445068359 time for calcul the mask position with numpy : 0.008447408676147461 nb_pixel_total : 151 time to create 1 rle with old method : 0.0001842975616455078 time for calcul the mask position with numpy : 0.008453130722045898 nb_pixel_total : 805 time to create 1 rle with old method : 0.0009546279907226562 time for calcul the mask position with numpy : 0.008460521697998047 nb_pixel_total : 538 time to create 1 rle with old method : 0.000621795654296875 time for calcul the mask position with numpy : 0.008448123931884766 nb_pixel_total : 483 time to create 1 rle with old method : 0.0005705356597900391 time for calcul the mask position with numpy : 0.008465766906738281 nb_pixel_total : 284 time to create 1 rle with old method : 0.00034499168395996094 time for calcul the mask position with numpy : 0.008458137512207031 nb_pixel_total : 14644 time to create 1 rle with old method : 0.01654648780822754 time for calcul the mask position with numpy : 0.008442163467407227 nb_pixel_total : 831 time to create 1 rle with old method : 0.0009653568267822266 time for calcul the mask position with numpy : 0.008428096771240234 nb_pixel_total : 448 time to create 1 rle with old method : 0.0006189346313476562 time for calcul the mask position with numpy : 0.008488178253173828 nb_pixel_total : 755 time to create 1 rle with old method : 0.0008878707885742188 time for calcul the mask position with numpy : 0.008452892303466797 nb_pixel_total : 3406 time to create 1 rle with old method : 0.003892660140991211 time for calcul the mask position with numpy : 0.00847625732421875 nb_pixel_total : 33 time to create 1 rle with old method : 8.440017700195312e-05 time for calcul the mask position with numpy : 0.008508920669555664 nb_pixel_total : 475 time to create 1 rle with old method : 0.0005714893341064453 time for calcul the mask position with numpy : 0.008435964584350586 nb_pixel_total : 426 time to create 1 rle with old method : 0.0005776882171630859 time for calcul the mask position with numpy : 0.008430957794189453 nb_pixel_total : 2127 time to create 1 rle with old method : 0.0024573802947998047 time for calcul the mask position with numpy : 0.00845026969909668 nb_pixel_total : 867 time to create 1 rle with old method : 0.001027822494506836 time for calcul the mask position with numpy : 0.008436441421508789 nb_pixel_total : 1926 time to create 1 rle with old method : 0.0021848678588867188 time for calcul the mask position with numpy : 0.00843954086303711 nb_pixel_total : 103 time to create 1 rle with old method : 0.00018906593322753906 time for calcul the mask position with numpy : 0.008416891098022461 nb_pixel_total : 1174 time to create 1 rle with old method : 0.0013506412506103516 time for calcul the mask position with numpy : 0.008439064025878906 nb_pixel_total : 1618 time to create 1 rle with old method : 0.001874685287475586 time for calcul the mask position with numpy : 0.008559942245483398 nb_pixel_total : 28 time to create 1 rle with old method : 6.079673767089844e-05 time for calcul the mask position with numpy : 0.008479833602905273 nb_pixel_total : 4993 time to create 1 rle with old method : 0.0057947635650634766 time for calcul the mask position with numpy : 0.008470296859741211 nb_pixel_total : 39 time to create 1 rle with old method : 5.626678466796875e-05 time for calcul the mask position with numpy : 0.008422613143920898 nb_pixel_total : 956 time to create 1 rle with old method : 0.001157522201538086 time for calcul the mask position with numpy : 0.008493661880493164 nb_pixel_total : 3443 time to create 1 rle with old method : 0.003977060317993164 time for calcul the mask position with numpy : 0.008429765701293945 nb_pixel_total : 576 time to create 1 rle with old method : 0.000732421875 time for calcul the mask position with numpy : 0.008512735366821289 nb_pixel_total : 523 time to create 1 rle with old method : 0.000644683837890625 time for calcul the mask position with numpy : 0.008531332015991211 nb_pixel_total : 22 time to create 1 rle with old method : 7.390975952148438e-05 time for calcul the mask position with numpy : 0.008455991744995117 nb_pixel_total : 595 time to create 1 rle with old method : 0.0007090568542480469 time for calcul the mask position with numpy : 0.00838017463684082 nb_pixel_total : 110 time to create 1 rle with old method : 0.00018453598022460938 time for calcul the mask position with numpy : 0.008433341979980469 nb_pixel_total : 1028 time to create 1 rle with old method : 0.0012145042419433594 time for calcul the mask position with numpy : 0.008411169052124023 nb_pixel_total : 1552 time to create 1 rle with old method : 0.0017764568328857422 time for calcul the mask position with numpy : 0.008440732955932617 nb_pixel_total : 515 time to create 1 rle with old method : 0.0006158351898193359 time for calcul the mask position with numpy : 0.00842595100402832 nb_pixel_total : 174 time to create 1 rle with old method : 0.00020360946655273438 time for calcul the mask position with numpy : 0.008448600769042969 nb_pixel_total : 62 time to create 1 rle with old method : 0.0001246929168701172 time for calcul the mask position with numpy : 0.008431196212768555 nb_pixel_total : 2075 time to create 1 rle with old method : 0.002395153045654297 time for calcul the mask position with numpy : 0.008467435836791992 nb_pixel_total : 15 time to create 1 rle with old method : 4.482269287109375e-05 time for calcul the mask position with numpy : 0.008463621139526367 nb_pixel_total : 278 time to create 1 rle with old method : 0.000335693359375 time for calcul the mask position with numpy : 0.008435249328613281 nb_pixel_total : 1382 time to create 1 rle with old method : 0.001615285873413086 time for calcul the mask position with numpy : 0.008412361145019531 nb_pixel_total : 627 time to create 1 rle with old method : 0.0007276535034179688 time for calcul the mask position with numpy : 0.008477210998535156 nb_pixel_total : 577 time to create 1 rle with old method : 0.0006852149963378906 time for calcul the mask position with numpy : 0.008430957794189453 nb_pixel_total : 786 time to create 1 rle with old method : 0.000911712646484375 time for calcul the mask position with numpy : 0.008425235748291016 nb_pixel_total : 4142 time to create 1 rle with old method : 0.004789829254150391 time for calcul the mask position with numpy : 0.008530855178833008 nb_pixel_total : 76 time to create 1 rle with old method : 0.00010061264038085938 time for calcul the mask position with numpy : 0.008510112762451172 nb_pixel_total : 1170 time to create 1 rle with old method : 0.0013370513916015625 time for calcul the mask position with numpy : 0.008530378341674805 nb_pixel_total : 399 time to create 1 rle with old method : 0.0004754066467285156 time for calcul the mask position with numpy : 0.008478879928588867 nb_pixel_total : 838 time to create 1 rle with old method : 0.0009810924530029297 time for calcul the mask position with numpy : 0.008602142333984375 nb_pixel_total : 198 time to create 1 rle with old method : 0.0002529621124267578 time for calcul the mask position with numpy : 0.008519172668457031 nb_pixel_total : 9 time to create 1 rle with old method : 2.7418136596679688e-05 time for calcul the mask position with numpy : 0.008556365966796875 nb_pixel_total : 210 time to create 1 rle with old method : 0.00026106834411621094 time for calcul the mask position with numpy : 0.008570194244384766 nb_pixel_total : 115 time to create 1 rle with old method : 0.00021338462829589844 time for calcul the mask position with numpy : 0.008568525314331055 nb_pixel_total : 172 time to create 1 rle with old method : 0.00022077560424804688 time for calcul the mask position with numpy : 0.008556604385375977 nb_pixel_total : 1587 time to create 1 rle with old method : 0.0018596649169921875 time for calcul the mask position with numpy : 0.009451627731323242 nb_pixel_total : 209 time to create 1 rle with old method : 0.00033974647521972656 time for calcul the mask position with numpy : 0.01068115234375 nb_pixel_total : 342 time to create 1 rle with old method : 0.0005497932434082031 time for calcul the mask position with numpy : 0.010396242141723633 nb_pixel_total : 774 time to create 1 rle with old method : 0.0009295940399169922 time for calcul the mask position with numpy : 0.00853419303894043 nb_pixel_total : 2720 time to create 1 rle with old method : 0.0037899017333984375 time for calcul the mask position with numpy : 0.011953592300415039 nb_pixel_total : 238 time to create 1 rle with old method : 0.0004305839538574219 time for calcul the mask position with numpy : 0.011473417282104492 nb_pixel_total : 6007 time to create 1 rle with old method : 0.01218724250793457 time for calcul the mask position with numpy : 0.012199878692626953 nb_pixel_total : 830 time to create 1 rle with old method : 0.001390218734741211 time for calcul the mask position with numpy : 0.011170387268066406 nb_pixel_total : 1330 time to create 1 rle with old method : 0.0022008419036865234 time for calcul the mask position with numpy : 0.011102914810180664 nb_pixel_total : 300 time to create 1 rle with old method : 0.0005297660827636719 time for calcul the mask position with numpy : 0.011047124862670898 nb_pixel_total : 1087 time to create 1 rle with old method : 0.0014297962188720703 time for calcul the mask position with numpy : 0.008708715438842773 nb_pixel_total : 459 time to create 1 rle with old method : 0.0005731582641601562 time for calcul the mask position with numpy : 0.008699893951416016 nb_pixel_total : 16 time to create 1 rle with old method : 5.984306335449219e-05 time for calcul the mask position with numpy : 0.008861303329467773 nb_pixel_total : 159 time to create 1 rle with old method : 0.0002377033233642578 time for calcul the mask position with numpy : 0.008946418762207031 nb_pixel_total : 1389 time to create 1 rle with old method : 0.0016531944274902344 time for calcul the mask position with numpy : 0.00875091552734375 nb_pixel_total : 9284 time to create 1 rle with old method : 0.010631322860717773 time for calcul the mask position with numpy : 0.008867740631103516 nb_pixel_total : 335 time to create 1 rle with old method : 0.00042128562927246094 time for calcul the mask position with numpy : 0.008666276931762695 nb_pixel_total : 837 time to create 1 rle with old method : 0.0009989738464355469 time for calcul the mask position with numpy : 0.008591890335083008 nb_pixel_total : 4166 time to create 1 rle with old method : 0.005026102066040039 time for calcul the mask position with numpy : 0.008984565734863281 nb_pixel_total : 14 time to create 1 rle with old method : 0.0002105236053466797 time for calcul the mask position with numpy : 0.010792970657348633 nb_pixel_total : 409 time to create 1 rle with old method : 0.000690460205078125 time for calcul the mask position with numpy : 0.01070713996887207 nb_pixel_total : 1165 time to create 1 rle with old method : 0.0018401145935058594 time for calcul the mask position with numpy : 0.01061701774597168 nb_pixel_total : 128 time to create 1 rle with old method : 0.0002467632293701172 time for calcul the mask position with numpy : 0.01054072380065918 nb_pixel_total : 842 time to create 1 rle with old method : 0.0013113021850585938 time for calcul the mask position with numpy : 0.009307622909545898 nb_pixel_total : 217 time to create 1 rle with old method : 0.00029659271240234375 time for calcul the mask position with numpy : 0.008745670318603516 nb_pixel_total : 19 time to create 1 rle with old method : 0.00011610984802246094 time for calcul the mask position with numpy : 0.008564233779907227 nb_pixel_total : 1151 time to create 1 rle with old method : 0.0013151168823242188 time for calcul the mask position with numpy : 0.008802175521850586 nb_pixel_total : 91 time to create 1 rle with old method : 0.0001316070556640625 create new chi : 2.0759987831115723 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 : 0.07023143768310547 batch 1 Loaded 118 chid ids of type : 4230 Number RLEs to save : 11669 TO DO : save crop sub photo not yet done ! save time : 1.2820971012115479 nb_obj : 126 nb_hashtags : 5 time to prepare the origin masks : 3.5517821311950684 time for calcul the mask position with numpy : 0.09884357452392578 nb_pixel_total : 1869694 time to create 1 rle with new method : 0.4619152545928955 time for calcul the mask position with numpy : 0.03352499008178711 nb_pixel_total : 91 time to create 1 rle with old method : 0.0001583099365234375 time for calcul the mask position with numpy : 0.06888818740844727 nb_pixel_total : 9549 time to create 1 rle with old method : 0.016045808792114258 time for calcul the mask position with numpy : 0.01631951332092285 nb_pixel_total : 57447 time to create 1 rle with old method : 0.07553529739379883 time for calcul the mask position with numpy : 0.011808395385742188 nb_pixel_total : 2054 time to create 1 rle with old method : 0.0023789405822753906 time for calcul the mask position with numpy : 0.02008533477783203 nb_pixel_total : 219 time to create 1 rle with old method : 0.0003845691680908203 time for calcul the mask position with numpy : 0.02727055549621582 nb_pixel_total : 385 time to create 1 rle with old method : 0.0008246898651123047 time for calcul the mask position with numpy : 0.02514791488647461 nb_pixel_total : 119 time to create 1 rle with old method : 0.00028014183044433594 time for calcul the mask position with numpy : 0.03166913986206055 nb_pixel_total : 452 time to create 1 rle with old method : 0.000705718994140625 time for calcul the mask position with numpy : 0.011106729507446289 nb_pixel_total : 68 time to create 1 rle with old method : 0.00015020370483398438 time for calcul the mask position with numpy : 0.03735923767089844 nb_pixel_total : 63 time to create 1 rle with old method : 0.00015926361083984375 time for calcul the mask position with numpy : 0.016909360885620117 nb_pixel_total : 125 time to create 1 rle with old method : 0.0002224445343017578 time for calcul the mask position with numpy : 0.047301530838012695 nb_pixel_total : 10 time to create 1 rle with old method : 8.726119995117188e-05 time for calcul the mask position with numpy : 0.07427811622619629 nb_pixel_total : 629 time to create 1 rle with old method : 0.0009963512420654297 time for calcul the mask position with numpy : 0.036229610443115234 nb_pixel_total : 3662 time to create 1 rle with old method : 0.005310773849487305 time for calcul the mask position with numpy : 0.09117436408996582 nb_pixel_total : 2081 time to create 1 rle with old method : 0.0029752254486083984 time for calcul the mask position with numpy : 0.09840202331542969 nb_pixel_total : 3589 time to create 1 rle with old method : 0.007607698440551758 time for calcul the mask position with numpy : 0.08820128440856934 nb_pixel_total : 826 time to create 1 rle with old method : 0.0012793540954589844 time for calcul the mask position with numpy : 0.07349300384521484 nb_pixel_total : 1544 time to create 1 rle with old method : 0.0021505355834960938 time for calcul the mask position with numpy : 0.06728792190551758 nb_pixel_total : 10 time to create 1 rle with old method : 0.00012135505676269531 time for calcul the mask position with numpy : 0.058327674865722656 nb_pixel_total : 2039 time to create 1 rle with old method : 0.0029511451721191406 time for calcul the mask position with numpy : 0.04714250564575195 nb_pixel_total : 290 time to create 1 rle with old method : 0.0004911422729492188 time for calcul the mask position with numpy : 0.016419410705566406 nb_pixel_total : 330 time to create 1 rle with old method : 0.0004715919494628906 time for calcul the mask position with numpy : 0.011647701263427734 nb_pixel_total : 419 time to create 1 rle with old method : 0.0005245208740234375 time for calcul the mask position with numpy : 0.012606143951416016 nb_pixel_total : 2380 time to create 1 rle with old method : 0.002941608428955078 time for calcul the mask position with numpy : 0.010817766189575195 nb_pixel_total : 497 time to create 1 rle with old method : 0.0007712841033935547 time for calcul the mask position with numpy : 0.012421846389770508 nb_pixel_total : 913 time to create 1 rle with old method : 0.0012705326080322266 time for calcul the mask position with numpy : 0.012430667877197266 nb_pixel_total : 1356 time to create 1 rle with old method : 0.0019350051879882812 time for calcul the mask position with numpy : 0.011997699737548828 nb_pixel_total : 717 time to create 1 rle with old method : 0.0008594989776611328 time for calcul the mask position with numpy : 0.01101827621459961 nb_pixel_total : 192 time to create 1 rle with old method : 0.0002551078796386719 time for calcul the mask position with numpy : 0.011277914047241211 nb_pixel_total : 854 time to create 1 rle with old method : 0.0009889602661132812 time for calcul the mask position with numpy : 0.01079249382019043 nb_pixel_total : 399 time to create 1 rle with old method : 0.0005970001220703125 time for calcul the mask position with numpy : 0.010494232177734375 nb_pixel_total : 2709 time to create 1 rle with old method : 0.003164052963256836 time for calcul the mask position with numpy : 0.011347055435180664 nb_pixel_total : 24 time to create 1 rle with old method : 8.392333984375e-05 time for calcul the mask position with numpy : 0.01640152931213379 nb_pixel_total : 613 time to create 1 rle with old method : 0.0007789134979248047 time for calcul the mask position with numpy : 0.011016607284545898 nb_pixel_total : 1003 time to create 1 rle with old method : 0.0012199878692626953 time for calcul the mask position with numpy : 0.011137723922729492 nb_pixel_total : 137 time to create 1 rle with old method : 0.00020265579223632812 time for calcul the mask position with numpy : 0.011235713958740234 nb_pixel_total : 182 time to create 1 rle with old method : 0.0002346038818359375 time for calcul the mask position with numpy : 0.011102676391601562 nb_pixel_total : 547 time to create 1 rle with old method : 0.0006668567657470703 time for calcul the mask position with numpy : 0.01106715202331543 nb_pixel_total : 20493 time to create 1 rle with old method : 0.02305459976196289 time for calcul the mask position with numpy : 0.011135101318359375 nb_pixel_total : 1333 time to create 1 rle with old method : 0.0016202926635742188 time for calcul the mask position with numpy : 0.010476350784301758 nb_pixel_total : 1 time to create 1 rle with old method : 2.1696090698242188e-05 time for calcul the mask position with numpy : 0.01026296615600586 nb_pixel_total : 1497 time to create 1 rle with old method : 0.0017554759979248047 time for calcul the mask position with numpy : 0.01036691665649414 nb_pixel_total : 413 time to create 1 rle with old method : 0.0005004405975341797 time for calcul the mask position with numpy : 0.010352611541748047 nb_pixel_total : 453 time to create 1 rle with old method : 0.0005419254302978516 time for calcul the mask position with numpy : 0.010614395141601562 nb_pixel_total : 778 time to create 1 rle with old method : 0.0008928775787353516 time for calcul the mask position with numpy : 0.010803699493408203 nb_pixel_total : 901 time to create 1 rle with old method : 0.0010387897491455078 time for calcul the mask position with numpy : 0.010639667510986328 nb_pixel_total : 366 time to create 1 rle with old method : 0.00044989585876464844 time for calcul the mask position with numpy : 0.010737895965576172 nb_pixel_total : 2669 time to create 1 rle with old method : 0.0030336380004882812 time for calcul the mask position with numpy : 0.01048421859741211 nb_pixel_total : 286 time to create 1 rle with old method : 0.00039196014404296875 time for calcul the mask position with numpy : 0.011262655258178711 nb_pixel_total : 216 time to create 1 rle with old method : 0.0003781318664550781 time for calcul the mask position with numpy : 0.011528253555297852 nb_pixel_total : 1 time to create 1 rle with old method : 2.8848648071289062e-05 time for calcul the mask position with numpy : 0.011937141418457031 nb_pixel_total : 452 time to create 1 rle with old method : 0.0008099079132080078 time for calcul the mask position with numpy : 0.01933145523071289 nb_pixel_total : 987 time to create 1 rle with old method : 0.0016269683837890625 time for calcul the mask position with numpy : 0.012390851974487305 nb_pixel_total : 4948 time to create 1 rle with old method : 0.008120298385620117 time for calcul the mask position with numpy : 0.011929988861083984 nb_pixel_total : 277 time to create 1 rle with old method : 0.0003311634063720703 time for calcul the mask position with numpy : 0.012031078338623047 nb_pixel_total : 102 time to create 1 rle with old method : 0.0002465248107910156 time for calcul the mask position with numpy : 0.011314153671264648 nb_pixel_total : 3086 time to create 1 rle with old method : 0.00360107421875 time for calcul the mask position with numpy : 0.012962579727172852 nb_pixel_total : 592 time to create 1 rle with old method : 0.0006949901580810547 time for calcul the mask position with numpy : 0.010903120040893555 nb_pixel_total : 390 time to create 1 rle with old method : 0.0005140304565429688 time for calcul the mask position with numpy : 0.011594772338867188 nb_pixel_total : 413 time to create 1 rle with old method : 0.0005321502685546875 time for calcul the mask position with numpy : 0.011659383773803711 nb_pixel_total : 396 time to create 1 rle with old method : 0.0005075931549072266 time for calcul the mask position with numpy : 0.011331558227539062 nb_pixel_total : 1400 time to create 1 rle with old method : 0.0016093254089355469 time for calcul the mask position with numpy : 0.010677814483642578 nb_pixel_total : 232 time to create 1 rle with old method : 0.00031566619873046875 time for calcul the mask position with numpy : 0.01288914680480957 nb_pixel_total : 96 time to create 1 rle with old method : 0.00013589859008789062 time for calcul the mask position with numpy : 0.012137889862060547 nb_pixel_total : 25 time to create 1 rle with old method : 6.389617919921875e-05 time for calcul the mask position with numpy : 0.012084007263183594 nb_pixel_total : 2232 time to create 1 rle with old method : 0.0027501583099365234 time for calcul the mask position with numpy : 0.01205301284790039 nb_pixel_total : 3394 time to create 1 rle with old method : 0.003947734832763672 time for calcul the mask position with numpy : 0.011847972869873047 nb_pixel_total : 8 time to create 1 rle with old method : 5.626678466796875e-05 time for calcul the mask position with numpy : 0.011712074279785156 nb_pixel_total : 111 time to create 1 rle with old method : 0.00016427040100097656 time for calcul the mask position with numpy : 0.01170659065246582 nb_pixel_total : 52 time to create 1 rle with old method : 9.322166442871094e-05 time for calcul the mask position with numpy : 0.016477584838867188 nb_pixel_total : 253 time to create 1 rle with old method : 0.0003466606140136719 time for calcul the mask position with numpy : 0.011449575424194336 nb_pixel_total : 638 time to create 1 rle with old method : 0.0007696151733398438 time for calcul the mask position with numpy : 0.011057615280151367 nb_pixel_total : 250 time to create 1 rle with old method : 0.0003266334533691406 time for calcul the mask position with numpy : 0.010965824127197266 nb_pixel_total : 90 time to create 1 rle with old method : 0.00014710426330566406 time for calcul the mask position with numpy : 0.010886669158935547 nb_pixel_total : 48 time to create 1 rle with old method : 9.179115295410156e-05 time for calcul the mask position with numpy : 0.010950088500976562 nb_pixel_total : 615 time to create 1 rle with old method : 0.005189418792724609 time for calcul the mask position with numpy : 0.012737512588500977 nb_pixel_total : 627 time to create 1 rle with old method : 0.0009527206420898438 time for calcul the mask position with numpy : 0.01093602180480957 nb_pixel_total : 159 time to create 1 rle with old method : 0.0002295970916748047 time for calcul the mask position with numpy : 0.010795831680297852 nb_pixel_total : 891 time to create 1 rle with old method : 0.001260995864868164 time for calcul the mask position with numpy : 0.011376380920410156 nb_pixel_total : 554 time to create 1 rle with old method : 0.0007333755493164062 time for calcul the mask position with numpy : 0.01092672348022461 nb_pixel_total : 1208 time to create 1 rle with old method : 0.0014314651489257812 time for calcul the mask position with numpy : 0.010969161987304688 nb_pixel_total : 3141 time to create 1 rle with old method : 0.0036821365356445312 time for calcul the mask position with numpy : 0.011149168014526367 nb_pixel_total : 831 time to create 1 rle with old method : 0.001043558120727539 time for calcul the mask position with numpy : 0.013065338134765625 nb_pixel_total : 447 time to create 1 rle with old method : 0.0005495548248291016 time for calcul the mask position with numpy : 0.010740280151367188 nb_pixel_total : 13 time to create 1 rle with old method : 4.673004150390625e-05 time for calcul the mask position with numpy : 0.010921716690063477 nb_pixel_total : 212 time to create 1 rle with old method : 0.0002715587615966797 time for calcul the mask position with numpy : 0.011141061782836914 nb_pixel_total : 164 time to create 1 rle with old method : 0.00024247169494628906 time for calcul the mask position with numpy : 0.010554075241088867 nb_pixel_total : 155 time to create 1 rle with old method : 0.0001983642578125 time for calcul the mask position with numpy : 0.010259628295898438 nb_pixel_total : 227 time to create 1 rle with old method : 0.0002818107604980469 time for calcul the mask position with numpy : 0.01027679443359375 nb_pixel_total : 701 time to create 1 rle with old method : 0.0008113384246826172 time for calcul the mask position with numpy : 0.01181173324584961 nb_pixel_total : 741 time to create 1 rle with old method : 0.0008971691131591797 time for calcul the mask position with numpy : 0.010242938995361328 nb_pixel_total : 935 time to create 1 rle with old method : 0.0010976791381835938 time for calcul the mask position with numpy : 0.010604143142700195 nb_pixel_total : 1497 time to create 1 rle with old method : 0.0017800331115722656 time for calcul the mask position with numpy : 0.010766029357910156 nb_pixel_total : 193 time to create 1 rle with old method : 0.0002655982971191406 time for calcul the mask position with numpy : 0.011775493621826172 nb_pixel_total : 83 time to create 1 rle with old method : 0.0001609325408935547 time for calcul the mask position with numpy : 0.012900352478027344 nb_pixel_total : 6249 time to create 1 rle with old method : 0.009510517120361328 time for calcul the mask position with numpy : 0.010706901550292969 nb_pixel_total : 675 time to create 1 rle with old method : 0.0008273124694824219 time for calcul the mask position with numpy : 0.011505603790283203 nb_pixel_total : 411 time to create 1 rle with old method : 0.0005323886871337891 time for calcul the mask position with numpy : 0.01113748550415039 nb_pixel_total : 1379 time to create 1 rle with old method : 0.0015871524810791016 time for calcul the mask position with numpy : 0.01128697395324707 nb_pixel_total : 768 time to create 1 rle with old method : 0.0009295940399169922 time for calcul the mask position with numpy : 0.010993480682373047 nb_pixel_total : 303 time to create 1 rle with old method : 0.0003693103790283203 time for calcul the mask position with numpy : 0.010704278945922852 nb_pixel_total : 794 time to create 1 rle with old method : 0.0009450912475585938 time for calcul the mask position with numpy : 0.010841131210327148 nb_pixel_total : 1091 time to create 1 rle with old method : 0.0012977123260498047 time for calcul the mask position with numpy : 0.010400772094726562 nb_pixel_total : 472 time to create 1 rle with old method : 0.0006244182586669922 time for calcul the mask position with numpy : 0.010363578796386719 nb_pixel_total : 414 time to create 1 rle with old method : 0.0004985332489013672 time for calcul the mask position with numpy : 0.010621309280395508 nb_pixel_total : 3563 time to create 1 rle with old method : 0.0041790008544921875 time for calcul the mask position with numpy : 0.010515928268432617 nb_pixel_total : 510 time to create 1 rle with old method : 0.0006234645843505859 time for calcul the mask position with numpy : 0.010596752166748047 nb_pixel_total : 952 time to create 1 rle with old method : 0.001171112060546875 time for calcul the mask position with numpy : 0.01130986213684082 nb_pixel_total : 1370 time to create 1 rle with old method : 0.0018475055694580078 time for calcul the mask position with numpy : 0.012308120727539062 nb_pixel_total : 961 time to create 1 rle with old method : 0.0012660026550292969 time for calcul the mask position with numpy : 0.012967586517333984 nb_pixel_total : 5262 time to create 1 rle with old method : 0.00701141357421875 time for calcul the mask position with numpy : 0.012986183166503906 nb_pixel_total : 749 time to create 1 rle with old method : 0.001371145248413086 time for calcul the mask position with numpy : 0.01347041130065918 nb_pixel_total : 4010 time to create 1 rle with old method : 0.006492137908935547 time for calcul the mask position with numpy : 0.012282371520996094 nb_pixel_total : 15 time to create 1 rle with old method : 7.867813110351562e-05 time for calcul the mask position with numpy : 0.018119335174560547 nb_pixel_total : 2136 time to create 1 rle with old method : 0.00915384292602539 time for calcul the mask position with numpy : 0.014318466186523438 nb_pixel_total : 1563 time to create 1 rle with old method : 0.0025892257690429688 time for calcul the mask position with numpy : 0.012786626815795898 nb_pixel_total : 394 time to create 1 rle with old method : 0.0004851818084716797 time for calcul the mask position with numpy : 0.008683204650878906 nb_pixel_total : 145 time to create 1 rle with old method : 0.00018858909606933594 time for calcul the mask position with numpy : 0.008632898330688477 nb_pixel_total : 1353 time to create 1 rle with old method : 0.0015380382537841797 time for calcul the mask position with numpy : 0.008729219436645508 nb_pixel_total : 7 time to create 1 rle with old method : 2.7179718017578125e-05 time for calcul the mask position with numpy : 0.0085906982421875 nb_pixel_total : 1334 time to create 1 rle with old method : 0.0015716552734375 time for calcul the mask position with numpy : 0.008612871170043945 nb_pixel_total : 2858 time to create 1 rle with old method : 0.0032231807708740234 time for calcul the mask position with numpy : 0.00863504409790039 nb_pixel_total : 526 time to create 1 rle with old method : 0.0006046295166015625 time for calcul the mask position with numpy : 0.00853419303894043 nb_pixel_total : 315 time to create 1 rle with old method : 0.0004143714904785156 time for calcul the mask position with numpy : 0.008542776107788086 nb_pixel_total : 1186 time to create 1 rle with old method : 0.0013353824615478516 time for calcul the mask position with numpy : 0.008538484573364258 nb_pixel_total : 344 time to create 1 rle with old method : 0.00039076805114746094 create new chi : 3.044757127761841 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 : 0.0068128108978271484 batch 1 Loaded 127 chid ids of type : 4230 Number RLEs to save : 12745 TO DO : save crop sub photo not yet done ! save time : 1.3766121864318848 map_output_result : {1386931933: (0.0, 'Should be the crop_list due to order', 0.0), 1386931871: (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 [1386931933, 1386931871] Looping around the photos to save general results len do output : 2 /1386931933.Didn't retrieve data . /1386931871.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, '3804803') ('4234', '27393933', '1386931933', None, None, None, None, None, '3804803') ('4234', None, None, None, None, None, None, None, '3804803') ('4234', '27393933', '1386931871', None, None, None, None, None, '3804803') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 6 time used for this insertion : 0.03653407096862793 save_final save missing photos in datou_result : time spend for datou_step_exec : 13.185917854309082 time spend to save output : 0.03933572769165039 total time spend for step 4 : 13.225253582000732 step5:crop_condition Wed Oct 1 10:50:59 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 : 2 ! batch 1 Loaded 245 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 ! map_result returned by crop_photo_return_map_crop : length : 86 About to insert : list_path_to_insert length 86 new photo from crops ! About to upload 86 photos upload in portfolio : 4869462 init cache_photo without model_param we have 86 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1759308661_2296103 INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085677_0.png', 0, 38, 28, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085685_0.png', 0, 6, 7, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085734_0.png', 0, 101, 70, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085750_0.png', 0, 27, 17, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085733_0.png', 0, 35, 7, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085723_0.png', 0, 79, 56, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085759_0.png', 0, 47, 38, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085792_0.png', 0, 12, 10, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085753_0.png', 0, 44, 26, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085688_0.png', 0, 85, 55, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085782_0.png', 0, 32, 37, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085752_0.png', 0, 24, 38, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085775_0.png', 0, 46, 46, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085720_0.png', 0, 29, 46, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085760_0.png', 0, 27, 12, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085770_0.png', 0, 17, 20, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085745_0.png', 0, 40, 32, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085717_0.png', 0, 32, 36, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085788_0.png', 0, 22, 52, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085710_0.png', 0, 11, 42, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085687_0.png', 0, 175, 135, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085711_0.png', 0, 3, 32, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085787_0.png', 0, 26, 12, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085716_0.png', 0, 25, 29, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085764_0.png', 0, 13, 17, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085778_0.png', 0, 14, 19, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085741_0.png', 0, 49, 31, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085757_0.png', 0, 38, 39, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085781_0.png', 0, 15, 26, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085714_0.png', 0, 14, 28, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085724_0.png', 0, 45, 13, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085691_0.png', 0, 56, 56, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085769_0.png', 0, 73, 66, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085699_0.png', 0, 112, 26, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085776_0.png', 0, 24, 25, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085772_0.png', 0, 60, 45, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085719_0.png', 0, 140, 145, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085704_0.png', 0, 124, 115, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085771_0.png', 0, 81, 127, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085773_0.png', 0, 39, 60, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085783_0.png', 0, 59, 88, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085709_0.png', 0, 33, 127, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085700_0.png', 0, 48, 20, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085899_0.png', 0, 19, 27, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085901_0.png', 0, 33, 26, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085947_0.png', 0, 107, 67, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085964_0.png', 0, 28, 16, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085945_0.png', 0, 51, 15, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085941_0.png', 0, 77, 49, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085976_0.png', 0, 47, 38, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085982_0.png', 0, 19, 16, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085970_0.png', 0, 44, 26, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085919_0.png', 0, 41, 34, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085995_0.png', 0, 30, 37, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982086017_0.png', 0, 29, 16, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085993_0.png', 0, 32, 29, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085954_0.png', 0, 40, 24, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085953_0.png', 0, 32, 25, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085991_0.png', 0, 22, 30, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085936_0.png', 0, 29, 33, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982086016_0.png', 0, 21, 33, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085956_0.png', 0, 16, 21, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085965_0.png', 0, 40, 25, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085930_0.png', 0, 9, 35, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085985_0.png', 0, 32, 40, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085981_0.png', 0, 14, 15, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085946_0.png', 0, 29, 50, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085943_0.png', 0, 19, 16, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085983_0.png', 0, 22, 38, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085895_0.png', 0, 100, 140, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085969_0.png', 0, 21, 39, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982086003_0.png', 0, 37, 40, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085938_0.png', 0, 26, 36, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085996_0.png', 0, 43, 38, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085986_0.png', 0, 63, 67, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085920_0.png', 0, 112, 24, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085990_0.png', 0, 61, 21, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085932_0.png', 0, 166, 167, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085925_0.png', 0, 113, 91, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085989_0.png', 0, 84, 129, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085992_0.png', 0, 41, 59, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982086006_0.png', 0, 54, 86, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085917_0.png', 0, 68, 85, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085928_0.png', 0, 44, 53, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085927_0.png', 0, 45, 20, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308680), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085921_0.png', 0, 48, 21, 0, 1759308680,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 86 photos in the portfolio 4869462 time of upload the photos Elapsed time : 29.196478366851807 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 ! map_result returned by crop_photo_return_map_crop : length : 35 About to insert : list_path_to_insert length 35 new photo from crops ! About to upload 35 photos upload in portfolio : 4869462 init cache_photo without model_param we have 35 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1759308691_2296103 INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308699), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085682_0.png', 0, 81, 27, 0, 1759308699,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308699), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085780_0.png', 0, 112, 108, 0, 1759308699,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308699), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085765_0.png', 0, 63, 38, 0, 1759308699,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308699), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085749_0.png', 0, 26, 15, 0, 1759308699,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308699), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085751_0.png', 0, 71, 30, 0, 1759308699,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308699), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085774_0.png', 0, 13, 30, 0, 1759308699,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308699), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085732_0.png', 0, 48, 57, 0, 1759308699,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308699), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085758_0.png', 0, 23, 24, 0, 1759308699,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308699), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085729_0.png', 0, 55, 46, 0, 1759308699,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308699), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085768_0.png', 0, 34, 39, 0, 1759308699,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308699), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085767_0.png', 0, 30, 21, 0, 1759308699,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308699), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085736_0.png', 0, 23, 59, 0, 1759308699,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308699), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085777_0.png', 0, 24, 20, 0, 1759308699,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308699), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085748_0.png', 0, 62, 52, 0, 1759308699,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308699), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085762_0.png', 0, 20, 17, 0, 1759308699,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308699), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085707_0.png', 0, 44, 19, 0, 1759308699,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308699), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085702_0.png', 0, 48, 14, 0, 1759308699,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308699), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085897_0.png', 0, 82, 30, 0, 1759308699,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308699), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982086004_0.png', 0, 100, 81, 0, 1759308699,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308699), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085942_0.png', 0, 81, 49, 0, 1759308699,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308699), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085940_0.png', 0, 26, 18, 0, 1759308699,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308699), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982086008_0.png', 0, 58, 74, 0, 1759308699,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308699), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085966_0.png', 0, 15, 26, 0, 1759308699,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308699), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085977_0.png', 0, 27, 28, 0, 1759308699,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308699), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085987_0.png', 0, 11, 22, 0, 1759308699,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308699), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982086011_0.png', 0, 12, 19, 0, 1759308699,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308699), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982086010_0.png', 0, 25, 25, 0, 1759308699,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308699), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982086019_0.png', 0, 22, 20, 0, 1759308699,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308699), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085959_0.png', 0, 80, 49, 0, 1759308699,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308699), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085922_0.png', 0, 24, 14, 0, 1759308699,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308699), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085909_0.png', 0, 68, 131, 0, 1759308699,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308699), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085958_0.png', 0, 7, 5, 0, 1759308699,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308699), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085924_0.png', 0, 52, 13, 0, 1759308699,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308699), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085926_0.png', 0, 41, 8, 0, 1759308699,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308699), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085980_0.png', 0, 15, 16, 0, 1759308699,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 35 photos in the portfolio 4869462 time of upload the photos Elapsed time : 12.144425392150879 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 ! map_result returned by crop_photo_return_map_crop : length : 11 About to insert : list_path_to_insert length 11 new photo from crops ! About to upload 11 photos upload in portfolio : 4869462 init cache_photo without model_param we have 11 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1759308704_2296103 INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308706), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085744_0.png', 0, 29, 66, 0, 1759308706,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308706), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085791_0.png', 0, 55, 26, 0, 1759308706,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308706), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085779_0.png', 0, 37, 51, 0, 1759308706,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308706), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085693_0.png', 0, 68, 30, 0, 1759308706,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308706), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085692_0.png', 0, 14, 16, 0, 1759308706,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308706), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085725_0.png', 0, 45, 17, 0, 1759308706,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308706), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982086018_0.png', 0, 55, 27, 0, 1759308706,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308706), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085912_0.png', 0, 45, 29, 0, 1759308706,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308706), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085931_0.png', 0, 34, 31, 0, 1759308706,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308706), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085937_0.png', 0, 22, 27, 0, 1759308706,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308706), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085988_0.png', 0, 52, 24, 0, 1759308706,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 11 photos in the portfolio 4869462 time of upload the photos Elapsed time : 4.388276815414429 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 ! map_result returned by crop_photo_return_map_crop : length : 25 About to insert : list_path_to_insert length 25 new photo from crops ! About to upload 25 photos upload in portfolio : 4869462 init cache_photo without model_param we have 25 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1759308708_2296103 INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308715), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085680_0.png', 0, 106, 29, 0, 1759308715,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308715), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085684_0.png', 0, 36, 23, 0, 1759308715,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308715), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085686_0.png', 0, 14, 15, 0, 1759308715,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308715), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085763_0.png', 0, 58, 37, 0, 1759308715,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308715), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085694_0.png', 0, 73, 22, 0, 1759308715,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308715), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085738_0.png', 0, 53, 55, 0, 1759308715,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308715), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085731_0.png', 0, 43, 50, 0, 1759308715,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308715), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085735_0.png', 0, 9, 10, 0, 1759308715,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308715), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085786_0.png', 0, 32, 66, 0, 1759308715,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308715), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085743_0.png', 0, 46, 85, 0, 1759308715,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308715), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085697_0.png', 0, 50, 68, 0, 1759308715,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308715), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931933_7e0c9cce81b97514a6fe07dfee9a81c6_rle_crop_3982085739_0.png', 0, 26, 73, 0, 1759308715,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308715), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085902_0.png', 0, 8, 22, 0, 1759308715,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308715), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085904_0.png', 0, 14, 18, 0, 1759308715,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308715), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085905_0.png', 0, 12, 14, 0, 1759308715,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308715), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982086002_0.png', 0, 36, 53, 0, 1759308715,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308715), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085911_0.png', 0, 63, 28, 0, 1759308715,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308715), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085907_0.png', 0, 76, 55, 0, 1759308715,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308715), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982086001_0.png', 0, 33, 80, 0, 1759308715,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308715), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982086000_0.png', 0, 31, 23, 0, 1759308715,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308715), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982086012_0.png', 0, 29, 76, 0, 1759308715,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308715), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085975_0.png', 0, 63, 72, 0, 1759308715,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308715), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085935_0.png', 0, 31, 96, 0, 1759308715,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308715), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982086009_0.png', 0, 44, 73, 0, 1759308715,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308715), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982085951_0.png', 0, 26, 78, 0, 1759308715,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 25 photos in the portfolio 4869462 time of upload the photos Elapsed time : 9.329042673110962 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 ! map_result returned by crop_photo_return_map_crop : length : 2 About to insert : list_path_to_insert length 2 new photo from crops ! About to upload 2 photos upload in portfolio : 4869462 init cache_photo without model_param we have 2 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1759308718_2296103 INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308718), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982086015_0.png', 0, 58, 64, 0, 1759308718,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759308718), 0.0, 0.0, 14, '', 0, 0, '1759308613_2296103_1386931871_f0f203a0d2e1f0ef6ac1439c4782698a_rle_crop_3982086014_0.png', 0, 73, 61, 0, 1759308718,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 2 photos in the portfolio 4869462 time of upload the photos Elapsed time : 1.1749334335327148 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 [1386931933, 1386931871] Looping around the photos to save general results len do output : 159 /1387125603Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125604Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125605Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125606Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125607Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125608Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125609Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125610Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125611Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125612Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125613Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125614Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125615Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125616Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125617Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125618Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125619Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125620Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125621Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125622Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125623Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125624Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125626Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125627Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125628Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125629Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125630Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125631Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125632Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125633Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125634Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125635Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125636Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125637Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125638Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125639Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125640Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125641Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125642Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125643Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125644Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125645Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125646Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125647Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125648Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125649Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125650Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125651Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125652Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125653Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125654Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125655Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125656Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125657Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125658Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125659Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125660Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125661Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125662Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125663Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125664Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125665Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125667Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125668Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125669Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125670Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125671Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125672Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125673Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125674Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125675Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125676Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125677Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125678Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125679Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125681Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125682Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125683Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125684Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125685Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125686Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125687Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125688Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125689Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125690Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387125691Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387126116Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387126130Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387126143Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387126157Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387126171Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387126184Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387126199Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387126209Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387126222Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387126236Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387126249Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387126262Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387126276Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387126290Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387126304Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387126317Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387126327Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387126341Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387126356Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387126370Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387126383Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387126397Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387126411Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387126424Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387126439Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387126453Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387126467Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387126480Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387126494Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387126508Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387126521Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387126534Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387126547Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387126561Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387126572Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387126993Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387127007Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387127022Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387127037Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387127052Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387127066Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387127067Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387127068Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387127069Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387127071Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387127072Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387127130Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387127132Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387127134Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387127136Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387127138Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387127140Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387127142Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387127144Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387127147Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387127149Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387127151Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387127153Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387127155Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387127156Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387127158Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387127160Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387127163Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387127166Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387127167Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387127169Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387127171Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387127173Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387127175Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387127178Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387127180Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387127192Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1387127194Didn'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, '3804803') ('4234', '27393933', '1386931933', None, None, None, None, None, '3804803') ('4234', None, None, None, None, None, None, None, '3804803') ('4234', '27393933', '1386931871', None, None, None, None, None, '3804803') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 479 time used for this insertion : 0.048105716705322266 save_final save missing photos in datou_result : time spend for datou_step_exec : 60.11900281906128 time spend to save output : 0.054003000259399414 total time spend for step 5 : 60.17300581932068 step6:thcl Wed Oct 1 10:51:59 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 : 0.0109710693359375 time to convert the images to numpy array : 0.04461407661437988 time to import caffe and check if the image exist : 0.01008915901184082 time to convert the images to numpy array : 0.051482439041137695 time to import caffe and check if the image exist : 0.01146078109741211 time to convert the images to numpy array : 0.0515286922454834 time to import caffe and check if the image exist : 0.019910812377929688 time to convert the images to numpy array : 0.044629812240600586 time to import caffe and check if the image exist : 0.009900093078613281 time to convert the images to numpy array : 0.05530142784118652 time to import caffe and check if the image exist : 0.012308359146118164 time to convert the images to numpy array : 0.05634641647338867 time to import caffe and check if the image exist : 0.026628494262695312 time to convert the images to numpy array : 0.04371809959411621 time to import caffe and check if the image exist : 0.013474702835083008 time to convert the images to numpy array : 0.057352542877197266 time to import caffe and check if the image exist : 0.01770925521850586 time to convert the images to numpy array : 0.05301785469055176 time to import caffe and check if the image exist : 0.024274826049804688 time to convert the images to numpy array : 0.04783749580383301 total time to convert the images to numpy array : 0.5650219917297363 list photo_ids error: [] list photo_ids correct : [1387125603, 1387125604, 1387125605, 1387125606, 1387125607, 1387125608, 1387125609, 1387125610, 1387125611, 1387125612, 1387125613, 1387125614, 1387125615, 1387125616, 1387125617, 1387125618, 1387127068, 1387127069, 1387127071, 1387127072, 1387127130, 1387127132, 1387127134, 1387127136, 1387127138, 1387127140, 1387127142, 1387127144, 1387127147, 1387127149, 1387127151, 1387127153, 1387127155, 1387127156, 1387127158, 1387127160, 1387127163, 1387127166, 1387127167, 1387127169, 1387127171, 1387127173, 1387127175, 1387127178, 1387127180, 1387127192, 1387127194, 1387125652, 1387125653, 1387125654, 1387125655, 1387125656, 1387125657, 1387125658, 1387125659, 1387125660, 1387125661, 1387125662, 1387125663, 1387125664, 1387125665, 1387125667, 1387125668, 1387126249, 1387126262, 1387126276, 1387126290, 1387126304, 1387126317, 1387126327, 1387126341, 1387126356, 1387126370, 1387126383, 1387126397, 1387126411, 1387126424, 1387126439, 1387126453, 1387126467, 1387126480, 1387126494, 1387126508, 1387126521, 1387126534, 1387126547, 1387126561, 1387126572, 1387126993, 1387127007, 1387127022, 1387127037, 1387127052, 1387127066, 1387127067, 1387125686, 1387125687, 1387125688, 1387125689, 1387125690, 1387125691, 1387126116, 1387126130, 1387126143, 1387126157, 1387126171, 1387126184, 1387126199, 1387126209, 1387126222, 1387126236, 1387125636, 1387125637, 1387125638, 1387125639, 1387125640, 1387125641, 1387125642, 1387125643, 1387125644, 1387125645, 1387125646, 1387125647, 1387125648, 1387125649, 1387125650, 1387125651, 1387125619, 1387125620, 1387125621, 1387125622, 1387125623, 1387125624, 1387125626, 1387125627, 1387125628, 1387125629, 1387125630, 1387125631, 1387125632, 1387125633, 1387125634, 1387125635, 1387125669, 1387125670, 1387125671, 1387125672, 1387125673, 1387125674, 1387125675, 1387125676, 1387125677, 1387125678, 1387125679, 1387125681, 1387125682, 1387125683, 1387125684, 1387125685] number of photos to traite : 159 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 : 4849 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 : 4630 max_wait_temp : 1 max_wait : 0 dict_keys(['pool5', 'prob']) time used to do the prepocess of the images : 0.858381986618042 time used to do the prediction : 0.7165427207946777 save descriptor for thcl : 3237 time to traite the descriptors : 0.9921855926513672 storage_type for insertDescriptorsMulti : 3 To insert : 1387125603 To insert : 1387125604 To insert : 1387125605 To insert : 1387125606 To insert : 1387125607 To insert : 1387125608 To insert : 1387125609 To insert : 1387125610 To insert : 1387125611 To insert : 1387125612 To insert : 1387125613 To insert : 1387125614 To insert : 1387125615 To insert : 1387125616 To insert : 1387125617 To insert : 1387125618 To insert : 1387127068 To insert : 1387127069 To insert : 1387127071 To insert : 1387127072 To insert : 1387127130 To insert : 1387127132 To insert : 1387127134 To insert : 1387127136 To insert : 1387127138 To insert : 1387127140 To insert : 1387127142 To insert : 1387127144 To insert : 1387127147 To insert : 1387127149 To insert : 1387127151 To insert : 1387127153 To insert : 1387127155 To insert : 1387127156 To insert : 1387127158 To insert : 1387127160 To insert : 1387127163 To insert : 1387127166 To insert : 1387127167 To insert : 1387127169 To insert : 1387127171 To insert : 1387127173 To insert : 1387127175 To insert : 1387127178 To insert : 1387127180 To insert : 1387127192 To insert : 1387127194 To insert : 1387125652 To insert : 1387125653 To insert : 1387125654 To insert : 1387125655 To insert : 1387125656 To insert : 1387125657 To insert : 1387125658 To insert : 1387125659 To insert : 1387125660 To insert : 1387125661 To insert : 1387125662 To insert : 1387125663 To insert : 1387125664 To insert : 1387125665 To insert : 1387125667 To insert : 1387125668 To insert : 1387126249 To insert : 1387126262 To insert : 1387126276 To insert : 1387126290 To insert : 1387126304 To insert : 1387126317 To insert : 1387126327 To insert : 1387126341 To insert : 1387126356 To insert : 1387126370 To insert : 1387126383 To insert : 1387126397 To insert : 1387126411 To insert : 1387126424 To insert : 1387126439 To insert : 1387126453 To insert : 1387126467 To insert : 1387126480 To insert : 1387126494 To insert : 1387126508 To insert : 1387126521 To insert : 1387126534 To insert : 1387126547 To insert : 1387126561 To insert : 1387126572 To insert : 1387126993 To insert : 1387127007 To insert : 1387127022 To insert : 1387127037 To insert : 1387127052 To insert : 1387127066 To insert : 1387127067 To insert : 1387125686 To insert : 1387125687 To insert : 1387125688 To insert : 1387125689 To insert : 1387125690 To insert : 1387125691 To insert : 1387126116 To insert : 1387126130 To insert : 1387126143 To insert : 1387126157 To insert : 1387126171 To insert : 1387126184 To insert : 1387126199 To insert : 1387126209 To insert : 1387126222 To insert : 1387126236 To insert : 1387125636 To insert : 1387125637 To insert : 1387125638 To insert : 1387125639 To insert : 1387125640 To insert : 1387125641 To insert : 1387125642 To insert : 1387125643 To insert : 1387125644 To insert : 1387125645 To insert : 1387125646 To insert : 1387125647 To insert : 1387125648 To insert : 1387125649 To insert : 1387125650 To insert : 1387125651 To insert : 1387125619 To insert : 1387125620 To insert : 1387125621 To insert : 1387125622 To insert : 1387125623 To insert : 1387125624 To insert : 1387125626 To insert : 1387125627 To insert : 1387125628 To insert : 1387125629 To insert : 1387125630 To insert : 1387125631 To insert : 1387125632 To insert : 1387125633 To insert : 1387125634 To insert : 1387125635 To insert : 1387125669 To insert : 1387125670 To insert : 1387125671 To insert : 1387125672 To insert : 1387125673 To insert : 1387125674 To insert : 1387125675 To insert : 1387125676 To insert : 1387125677 To insert : 1387125678 To insert : 1387125679 To insert : 1387125681 To insert : 1387125682 To insert : 1387125683 To insert : 1387125684 To insert : 1387125685 Catched exception ! Connect or reconnect ! time to insert the descriptors : 37.58445620536804 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 : 243 time used for this insertion : 0.04420757293701172 save missing photos in datou_result : time spend for datou_step_exec : 45.615265130996704 time spend to save output : 0.2546863555908203 total time spend for step 6 : 45.869951486587524 step7:ventilate_hashtags_in_portfolio Wed Oct 1 10:52:45 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 : 27393933 get user id for portfolio 27393933 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`=27393933 AND mptpi.`type`=4230 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('PET_clair','PEHD','pehd','metal','Tetrapak','refus','carton','pet_fonce','pet_clair','environnement','mal_croppe','Carton','Film_plastique','PET_fonce','papier','Papier','autre','flou')) AND mptpi.`min_score`=0.6 To do To do 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`=27393933 AND mptpi.`type`=4230 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('PET_clair','PEHD','pehd','metal','Tetrapak','refus','carton','pet_fonce','pet_clair','environnement','mal_croppe','Carton','Film_plastique','PET_fonce','papier','Papier','autre','flou')) 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`=27393933 AND mptpi.`type`=4231 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('PET_clair','PEHD','pehd','metal','Tetrapak','refus','carton','pet_fonce','pet_clair','environnement','mal_croppe','Carton','Film_plastique','PET_fonce','papier','Papier','autre','flou')) AND mptpi.`min_score`=0.6 To do To do 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`=27393933 AND mptpi.`type`=4231 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('PET_clair','PEHD','pehd','metal','Tetrapak','refus','carton','pet_fonce','pet_clair','environnement','mal_croppe','Carton','Film_plastique','PET_fonce','papier','Papier','autre','flou')) AND mptpi.`min_score`=0.6 To do lien utilise dans velours : https://marlene.fotonower.com/velours/27397929,27397923,27397924,27397925,27397926,27397932,27397934,27397930,27397931,27397933,27397936,27397937,27397938?tags=pet_clair,pehd,metal,tetrapak,refus,carton,pet_fonce,environnement,mal_croppe,film_plastique,papier,autre,flou&datou_id_consolidate=4235&port_consolidate=27393933 Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : ventilate_hashtags_in_portfolio we use saveGeneral [1386931933, 1386931871] Looping around the photos to save general results len do output : 1 /27393933. 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, '3804803') ('4234', '27393933', '1386931933', None, None, None, None, None, '3804803') ('4234', None, None, None, None, None, None, None, '3804803') ('4234', '27393933', '1386931871', None, None, None, None, None, '3804803') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 3 time used for this insertion : 0.03773045539855957 save_final save missing photos in datou_result : time spend for datou_step_exec : 8.166593074798584 time spend to save output : 0.03808474540710449 total time spend for step 7 : 8.204677820205688 step8:final Wed Oct 1 10:52:53 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 : {1386931933: ('0.2044504194711182',), 1386931871: ('0.2044504194711182',)} new output for save of step final : {1386931933: ('0.2044504194711182',), 1386931871: ('0.2044504194711182',)} [1386931933, 1386931871] Looping around the photos to save general results len do output : 2 /1386931933.Didn't retrieve data . /1386931871.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, '3804803') ('4234', '27393933', '1386931933', None, None, None, None, None, '3804803') ('4234', None, None, None, None, None, None, None, '3804803') ('4234', '27393933', '1386931871', None, None, None, None, None, '3804803') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 6 time used for this insertion : 0.03759574890136719 save_final save missing photos in datou_result : time spend for datou_step_exec : 0.43322014808654785 time spend to save output : 0.0379331111907959 total time spend for step 8 : 0.47115325927734375 step9:velours_tree Wed Oct 1 10:52:53 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 : 27397929,27397923,27397924,27397925,27397926,27397932,27397934,27397930,27397931,27397933,27397936,27397937,27397938 photo desc type : 5561 - Retrieving photos to tag... query : SELECT ph.photo_id FROM MTRBack.photos_view ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=27397929 ORDER BY ph.size desc query : SELECT ph.photo_id FROM MTRBack.photos_view ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=27397923 ORDER BY ph.size desc query : SELECT ph.photo_id FROM MTRBack.photos_view ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=27397924 ORDER BY ph.size desc query : SELECT ph.photo_id FROM MTRBack.photos_view ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=27397925 ORDER BY ph.size desc query : SELECT ph.photo_id FROM MTRBack.photos_view ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=27397926 ORDER BY ph.size desc query : SELECT ph.photo_id FROM MTRBack.photos_view ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=27397932 ORDER BY ph.size desc query : SELECT ph.photo_id FROM MTRBack.photos_view ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=27397934 ORDER BY ph.size desc query : SELECT ph.photo_id FROM MTRBack.photos_view ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=27397930 ORDER BY ph.size desc query : SELECT ph.photo_id FROM MTRBack.photos_view ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=27397931 ORDER BY ph.size desc query : SELECT ph.photo_id FROM MTRBack.photos_view ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=27397933 ORDER BY ph.size desc query : SELECT ph.photo_id FROM MTRBack.photos_view ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=27397936 ORDER BY ph.size desc query : SELECT ph.photo_id FROM MTRBack.photos_view ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=27397937 ORDER BY ph.size desc query : SELECT ph.photo_id FROM MTRBack.photos_view ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=27397938 ORDER BY ph.size desc - Loading descriptors... Size : 2048 len(descriptors) : 159 Compute structured hierarchical clustering... ward : AgglomerativeClustering(n_clusters=6) ward.labels_ : [5 3 0 1 3 1 4 3 4 0 1 1 4 4 2 2 4 4 1 2 0 3 2 2 2 2 0 1 1 3 3 0 4 0 2 0 0 0 0 0 0 4 2 1 5 0 1 2 1 4 2 4 2 1 1 1 4 2 2 4 1 2 2 2 1 2 1 2 1 0 0 2 3 4 4 0 2 0 0 0 0 0 4 4 2 2 5 0 0 3 0 1 0 1 1 1 2 2 3 0 2 2 2 5 0 3 2 4 2 1 2 2 4 2 0 2 4 2 2 3 2 1 1 1 0 3 3 1 3 3 1 3 3 3 3 3 3 0 0 3 0 4 4 0 3 3 3 1 0 0 4 0 0 0 0 0 0 0 0] Elapsed time: 0.02414560317993164 graph_id used : 121933 - Beta version, working pretty good on 11-5-16 ! https://marlene.fotonower.com/velours/27397929,27397923,27397924,27397925,27397926,27397932,27397934,27397930,27397931,27397933,27397936,27397937,27397938?tags=pet_clair,pehd,metal,tetrapak,refus,carton,pet_fonce,environnement,mal_croppe,film_plastique,papier,autre,flou&datou_id_consolidate=4235&port_consolidate=27393933&tree_id=121933 Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : velours_tree we use saveGeneral [1386931933, 1386931871] Looping around the photos to save general results len do output : 1 /27393933Didn'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, '3804803') ('4234', '27393933', '1386931933', None, None, None, None, None, '3804803') ('4234', None, None, None, None, None, None, None, '3804803') ('4234', '27393933', '1386931871', None, None, None, None, None, '3804803') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 3 time used for this insertion : 0.037194013595581055 save_final save missing photos in datou_result : time spend for datou_step_exec : 24.774311065673828 time spend to save output : 0.03741145133972168 total time spend for step 9 : 24.81172251701355 step10:send_mail_cod Wed Oct 1 10:53:18 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_P27393933_01-10-2025_10_53_18.pdf 27397909 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 .imagette273979091759308798 27397903 imagette273979031759308799 27397904 imagette273979041759308799 27397905 imagette273979051759308799 27397906 imagette273979061759308799 27397912 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 .imagette273979121759308799 27397914 change filename to text .change filename to text .imagette273979141759308801 27397911 imagette273979111759308801 27397913 imagette273979131759308801 27397916 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 .imagette273979161759308801 27397917 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 .imagette273979171759308802 27397918 imagette273979181759308803 SELECT h.hashtag,pcr.value FROM MTRUser.portfolio_carac_ratio pcr, MTRBack.hashtags h where pcr.portfolio_id=27393933 and hashtag_type = 4230 and pcr.hashtag_id = h.hashtag_id; velour_link : https://marlene.fotonower.com/velours/27397929,27397923,27397924,27397925,27397926,27397932,27397934,27397930,27397931,27397933,27397936,27397937,27397938?tags=pet_clair,pehd,metal,tetrapak,refus,carton,pet_fonce,environnement,mal_croppe,film_plastique,papier,autre,flou&datou_id_consolidate=4235&port_consolidate=27393933&tree_id=121933 your option no_mail is active, we will not send the real mail to your client args[1386931933] : ((1386931933, -7.476559459946674, 492609224), (1386931933, -0.640063985191894, 501862349), '0.2044504194711182') We are sending mail with results at cod@fotonower.com args[1386931871] : ((1386931871, -7.413876185147374, 492609224), (1386931871, -0.5239789919597448, 501862349), '0.2044504194711182') We are sending mail with results at cod@fotonower.com refus_total : 0.2044504194711182 2022-04-13 10:29:59 0 SELECT ph.photo_id,ph.url,ph.username,ph.uploaded_at,ph.text FROM MTRBack.photos_view ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=27393933 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_P27393933_01-10-2025_10_53_18.pdf results_Qualipapia_P27393933_01-10-2025_10_53_18.pdf uploaded to url https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P27393933_01-10-2025_10_53_18.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','27393933','results_Qualipapia_P27393933_01-10-2025_10_53_18.pdf','https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P27393933_01-10-2025_10_53_18.pdf','pdf','','0.15','0.2044504194711182') Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : send_mail_cod we use saveGeneral [1386931933, 1386931871] 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, '3804803') ('4234', '27393933', '1386931933', None, None, None, None, None, '3804803') ('4234', None, None, None, None, None, None, None, '3804803') ('4234', '27393933', '1386931871', None, None, None, None, None, '3804803') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 2 time used for this insertion : 0.036058664321899414 save_final save missing photos in datou_result : time spend for datou_step_exec : 6.240941286087036 time spend to save output : 0.0361783504486084 total time spend for step 10 : 6.2771196365356445 step11:split_time_score Wed Oct 1 10:53:25 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'}] (('13', 2),) ERROR counted https://github.com/fotonower/Velours/issues/663#issuecomment-421136223 {} 30092025 27393933 Nombre de photos uploadées : 2 / 23040 (0%) 30092025 27393933 Nombre de photos taguées (types de déchets): 2 / 2 (100%) 30092025 27393933 Nombre de photos taguées (volume) : 0 / 2 (0%) elapsed_time : load_data_split_time_score 1.9073486328125e-06 elapsed_time : order_list_meta_photo_and_scores 6.198883056640625e-06 ?? elapsed_time : fill_and_build_computed_from_old_data 0.00020575523376464844 Catched exception ! Connect or reconnect ! Catched exception ! Connect or reconnect ! elapsed_time : insert_dashboard_record_day_entry 0.650968074798584 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 : 0.12342032315918323 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P27343141_30-09-2025_12_43_19.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27343141 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`=27343141 AND mptpi.`type`=4230 To do Qualite : 0.12719036174542264 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P27343142_30-09-2025_12_39_21.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27343142 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`=27343142 AND mptpi.`type`=4230 To do Qualite : 0.19683768513176625 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P27343143_30-09-2025_12_33_50.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27343143 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`=27343143 AND mptpi.`type`=4230 To do Qualite : 0.19151311871402615 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P27343156_30-09-2025_12_36_59.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27343156 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`=27343156 AND mptpi.`type`=4230 To do Qualite : 0.1910909332455365 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P27343169_30-09-2025_12_32_59.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27343169 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`=27343169 AND mptpi.`type`=4230 To do Qualite : 0.17295143094849105 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P27343170_30-09-2025_12_27_46.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27343170 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`=27343170 AND mptpi.`type`=4230 To do Qualite : 0.1739245554863202 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P27343171_30-09-2025_12_28_54.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27343171 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`=27343171 AND mptpi.`type`=4230 To do Qualite : 0.17535108425844856 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P27343172_30-09-2025_12_34_19.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27343172 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`=27343172 AND mptpi.`type`=4230 To do Qualite : 0.17087297164186838 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P27343173_30-09-2025_12_23_47.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27343173 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`=27343173 AND mptpi.`type`=4230 To do Qualite : 0.167266986937012 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P27343174_30-09-2025_12_16_42.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27343174 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`=27343174 AND mptpi.`type`=4230 To do Qualite : 0.15716671282508085 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P27343175_30-09-2025_14_20_56.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27343175 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`=27343175 AND mptpi.`type`=4230 To do Qualite : 0.21007119583007797 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P27343176_30-09-2025_12_13_37.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27343176 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`=27343176 AND mptpi.`type`=4230 To do Qualite : 0.14654083614716418 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P27343177_30-09-2025_12_13_27.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27343177 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`=27343177 AND mptpi.`type`=4230 To do Qualite : 0.14517298197910936 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P27343178_30-09-2025_12_03_09.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27343178 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`=27343178 AND mptpi.`type`=4230 To do Qualite : 0.16058400023793862 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P27343196_30-09-2025_11_58_58.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27343196 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`=27343196 AND mptpi.`type`=4230 To do Qualite : 0.1876289825453009 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P27343197_30-09-2025_11_54_42.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27343197 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`=27343197 AND mptpi.`type`=4230 To do Qualite : 0.15314558585244492 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P27343198_30-09-2025_11_52_24.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27343198 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`=27343198 AND mptpi.`type`=4230 To do Qualite : 0.15763398519831487 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P27343200_30-09-2025_11_51_37.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27343200 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`=27343200 AND mptpi.`type`=4230 To do find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27393905 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27393905 order by id desc limit 1 Qualite : 0.17285052983730406 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P27393919_01-10-2025_10_51_38.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27393919 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`=27393919 AND mptpi.`type`=4230 To do Qualite : 0.2044504194711182 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P27393933_01-10-2025_10_53_18.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27393933 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`=27393933 AND mptpi.`type`=4230 To do Qualite : 0.1767545698211257 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P27393935_01-10-2025_09_27_14.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27393935 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`=27393935 AND mptpi.`type`=4230 To do Qualite : 0.1614377838643691 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P27393937_01-10-2025_09_29_16.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27393937 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`=27393937 AND mptpi.`type`=4230 To do find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27393938 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27393939 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27393940 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27393941 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27393942 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27393943 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27393944 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27393945 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27393946 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27393947 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27393964 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27393965 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27393967 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27393969 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27393970 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27393972 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27393974 order by id desc limit 1 Qualite : 0.17752895308306219 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P27393977_01-10-2025_10_51_20.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27393977 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`=27393977 AND mptpi.`type`=4230 To do find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27393980 order by id desc limit 1 Qualite : 0.18544430551053628 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P27393984_01-10-2025_10_44_24.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27393984 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`=27393984 AND mptpi.`type`=4230 To do find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27393987 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27394016 order by id desc limit 1 Qualite : 0.1601908093040712 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P27394032_01-10-2025_10_36_05.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27394032 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`=27394032 AND mptpi.`type`=4230 To do Qualite : 0.15937713603376988 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P27394035_01-10-2025_10_41_30.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27394035 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`=27394035 AND mptpi.`type`=4230 To do Qualite : 0.1646942780372724 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P27394038_01-10-2025_10_44_50.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27394038 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`=27394038 AND mptpi.`type`=4230 To do Qualite : 0.21006760296857604 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P27394040_01-10-2025_10_29_28.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27394040 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`=27394040 AND mptpi.`type`=4230 To do Qualite : 0.16928716956625042 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P27394042_01-10-2025_10_25_14.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27394042 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`=27394042 AND mptpi.`type`=4230 To do Qualite : 0.1702259020612228 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P27394044_01-10-2025_10_23_25.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27394044 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`=27394044 AND mptpi.`type`=4230 To do Qualite : 0.1668741019460691 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P27394046_01-10-2025_10_21_16.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27394046 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`=27394046 AND mptpi.`type`=4230 To do Qualite : 0.18520694818665365 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P27394048_01-10-2025_10_18_12.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27394048 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`=27394048 AND mptpi.`type`=4230 To do Qualite : 0.18068791425831218 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P27394050_01-10-2025_10_13_36.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27394050 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`=27394050 AND mptpi.`type`=4230 To do Qualite : 0.17948751934452958 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P27394052_01-10-2025_09_49_59.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27394052 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`=27394052 AND mptpi.`type`=4230 To do Qualite : 0.18853108612793937 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P27394053_01-10-2025_10_12_55.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27394053 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`=27394053 AND mptpi.`type`=4230 To do Qualite : 0.17401372668965198 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P27394055_01-10-2025_09_49_34.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27394055 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`=27394055 AND mptpi.`type`=4230 To do Qualite : 0.19543093754189436 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P27394056_01-10-2025_09_42_25.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27394056 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`=27394056 AND mptpi.`type`=4230 To do Qualite : 0.20361107053265745 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P27394057_01-10-2025_09_39_51.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27394057 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`=27394057 AND mptpi.`type`=4230 To do Qualite : 0.1870202867149052 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P27394058_01-10-2025_09_52_59.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27394058 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`=27394058 AND mptpi.`type`=4230 To do Qualite : 0.21251604027843551 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P27394059_01-10-2025_09_34_55.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27394059 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`=27394059 AND mptpi.`type`=4230 To do Qualite : 0.23890613147430387 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P27394060_01-10-2025_09_31_12.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27394060 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`=27394060 AND mptpi.`type`=4230 To do Qualite : 0.15059539514016618 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P27394062_01-10-2025_09_30_29.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27394062 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`=27394062 AND mptpi.`type`=4230 To do Qualite : 0.14006283468574982 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P27394064_01-10-2025_09_37_08.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27394064 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`=27394064 AND mptpi.`type`=4230 To do Qualite : 0.14006283468574982 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P27394064_01-10-2025_09_37_08.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27394064 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`=27394064 AND mptpi.`type`=4230 To do NUMBER BATCH : 0 # DISPLAY ALL COLLECTED DATA : {'30092025': {'nb_upload': 2, 'nb_taggue_class': 2, 'nb_taggue_densite': 0}} Inside saveOutput : final : True verbose : 0 saveOutput not yet implemented for datou_step.type : split_time_score we use saveGeneral [1386931933, 1386931871] Looping around the photos to save general results len do output : 1 /27393933Didn'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, '3804803') ('4234', '27393933', '1386931933', None, None, None, None, None, '3804803') ('4234', None, None, None, None, None, None, None, '3804803') ('4234', '27393933', '1386931871', None, None, None, None, None, '3804803') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 3 time used for this insertion : 0.036812782287597656 save_final save missing photos in datou_result : time spend for datou_step_exec : 24.312636375427246 time spend to save output : 0.03705716133117676 total time spend for step 11 : 24.349693536758423 caffe_path_current : About to save ! 2 After save, about to update current ! ret : 2 len(input) + len(total_photo_id_missing) : 2 set_done_treatment 36.29user 27.76system 3:38.80elapsed 29%CPU (0avgtext+0avgdata 2465556maxresident)k 1620984inputs+12864outputs (25167major+2563844minor)pagefaults 0swaps