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 3919092' -s rattrapage -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 : 41623 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 : 3995, datou_cur_ids : ['3919092'] with mtr_portfolio_ids : ['27677754'] and first list_photo_ids : [] new path : /proc/41623/ 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 ! 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 11524 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11533 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11532 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11528 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11528 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11531 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11531 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11525 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11525 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11578 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11578 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11527 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11526 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11526 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11535 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 : type of output 1 of step 11527 doesn't seem to be define in the database( WARNING : type of input 3 of step 11526 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11524 doesn't seem to be define in the database( WARNING : type of input 2 of step 11528 doesn't seem to be define in the database( WARNING : output 1 of step 11524 have datatype=2 whereas input 1 of step 11531 have datatype=7 WARNING : type of output 2 of step 11531 doesn't seem to be define in the database( WARNING : type of input 1 of step 11525 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11527 have datatype=10 whereas input 3 of step 11534 have datatype=6 WARNING : type of input 2 of step 11578 doesn't seem to be define in the database( WARNING : output 1 of step 11525 have datatype=7 whereas input 2 of step 11578 have datatype=None WARNING : type of output 3 of step 11578 doesn't seem to be define in the database( WARNING : type of input 1 of step 11527 doesn't seem to be define in the database( WARNING : output 0 of step 11527 have datatype=10 whereas input 0 of step 11584 have datatype=18 WARNING : type of input 5 of step 11534 doesn't seem to be define in the database( WARNING : output 0 of step 11584 have datatype=11 whereas input 5 of step 11534 have datatype=None WARNING : type of output 1 of step 11533 doesn't seem to be define in the database( WARNING : type of input 3 of step 11528 doesn't seem to be define in the database( WARNING : type of output 1 of step 11532 doesn't seem to be define in the database( WARNING : type of input 3 of step 11528 doesn't seem to be define in the database( WARNING : output 0 of step 11531 have datatype=1 whereas input 0 of step 11525 have datatype=2 DataTypes for each output/input checked ! List Step Type Loaded in datou : mask_detect, blur_detection, brightness, crop_condition, thcl, merge_mask_thcl_custom, rle_unique_nms_with_priority, crop_condition, ventilate_hashtags_in_portfolio, final, velours_tree, send_mail_cod, split_time_score over limit max, limiting to limit_max 20 list_input_json : [] origin We have 1 , BFBFBFBFBFBFBFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 7 ; length of list_pids : 7 ; length of list_args : 7 time to download the photos : 1.6359288692474365 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 : 13 step1:mask_detect Fri Oct 10 10:19:00 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Beginning of datou step mask_detect ! save_polygon : True begin detect begin to check gpu status inside check gpu memory l 3637 free memory gpu now : 10998 max_wait_temp : 1 max_wait : 0 gpu_flag : 0 2025-10-10 10:19:03.019931: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2025-10-10 10:19:03.027138: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493010000 Hz 2025-10-10 10:19:03.028504: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7faa34000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-10-10 10:19:03.028542: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-10-10 10:19:03.030708: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-10-10 10:19:03.306469: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x31692220 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-10-10 10:19:03.306532: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-10-10 10:19:03.308330: 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 2025-10-10 10:19:03.308847: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-10-10 10:19:03.312641: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-10-10 10:19:03.315861: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-10-10 10:19:03.316321: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-10-10 10:19:03.319460: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-10-10 10:19:03.321040: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-10-10 10:19:03.325568: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-10-10 10:19:03.327084: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-10-10 10:19:03.327154: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-10-10 10:19:03.327947: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-10-10 10:19:03.327963: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-10-10 10:19:03.327973: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-10-10 10:19:03.329371: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 10193 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:41:00.0, compute capability: 7.5) WARNING:tensorflow:From /home/admin/workarea/git/Velours/python/mtr/mask_rcnn/mask_detection.py:69: The name tf.keras.backend.set_session is deprecated. Please use tf.compat.v1.keras.backend.set_session instead. 2025-10-10 10:19:03.752389: 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 2025-10-10 10:19:03.752489: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-10-10 10:19:03.752517: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-10-10 10:19:03.752542: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-10-10 10:19:03.752567: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-10-10 10:19:03.752591: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-10-10 10:19:03.752614: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-10-10 10:19:03.752638: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-10-10 10:19:03.754812: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-10-10 10:19:03.756249: 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 2025-10-10 10:19:03.756287: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-10-10 10:19:03.756305: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-10-10 10:19:03.756321: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-10-10 10:19:03.756337: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-10-10 10:19:03.756353: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-10-10 10:19:03.756368: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-10-10 10:19:03.756384: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-10-10 10:19:03.757685: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-10-10 10:19:03.757712: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-10-10 10:19:03.757720: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-10-10 10:19:03.757727: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-10-10 10:19:03.759033: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 10193 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:41:00.0, compute capability: 7.5) Using TensorFlow backend. WARNING:tensorflow:From /home/admin/workarea/install/Mask_RCNN/model.py:396: calling crop_and_resize_v1 (from tensorflow.python.ops.image_ops_impl) with box_ind is deprecated and will be removed in a future version. Instructions for updating: box_ind is deprecated, use box_indices instead WARNING:tensorflow:From /home/admin/workarea/install/Mask_RCNN/model.py:703: to_int32 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.cast` instead. WARNING:tensorflow:From /home/admin/workarea/install/Mask_RCNN/model.py:729: to_float (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.cast` instead. Inside mask_sub_process Inside mask_detect About to load cache.load_thcl_param To do loadFromThcl(), then load ParamDescType : thcl2976 thcls : [{'id': 2976, 'mtr_user_id': 31, 'name': 'Mask_Limeil_Label_PEHD_080621', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,environnement,fibreux_cont,metal_cont,pet_clair_cont,pet_fonce_cont,pet_opaque_cont,barquette,film_plastique,autre_contaminant,etiquette_detachee', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3760, 'photo_desc_type': 5359, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0,0,0'}] thcl {'id': 2976, 'mtr_user_id': 31, 'name': 'Mask_Limeil_Label_PEHD_080621', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,environnement,fibreux_cont,metal_cont,pet_clair_cont,pet_fonce_cont,pet_opaque_cont,barquette,film_plastique,autre_contaminant,etiquette_detachee', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3760, 'photo_desc_type': 5359, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0,0,0'} Update svm_hashtag_type_desc : 5359 FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (5359, 'Mask_Limeil_Label_PEHD_080621', 16384, 25088, 'Mask_Limeil_Label_PEHD_080621', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 1, datetime.datetime(2021, 6, 9, 7, 22, 34), datetime.datetime(2021, 6, 9, 7, 22, 34)) {'thcl': {'id': 2976, 'mtr_user_id': 31, 'name': 'Mask_Limeil_Label_PEHD_080621', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,environnement,fibreux_cont,metal_cont,pet_clair_cont,pet_fonce_cont,pet_opaque_cont,barquette,film_plastique,autre_contaminant,etiquette_detachee', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3760, 'photo_desc_type': 5359, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0,0,0'}, 'list_hashtags': ['background', 'environnement', 'fibreux_cont', 'metal_cont', 'pet_clair_cont', 'pet_fonce_cont', 'pet_opaque_cont', 'barquette', 'film_plastique', 'autre_contaminant', 'etiquette_detachee'], 'list_hashtags_csv': 'background,environnement,fibreux_cont,metal_cont,pet_clair_cont,pet_fonce_cont,pet_opaque_cont,barquette,film_plastique,autre_contaminant,etiquette_detachee', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3760, 'svm_hashtag_type_desc': 5359, 'photo_desc_type': 5359, 'pb_hashtag_id_or_classifier': 0} list_class_names : ['background', 'environnement', 'fibreux_cont', 'metal_cont', 'pet_clair_cont', 'pet_fonce_cont', 'pet_opaque_cont', 'barquette', 'film_plastique', 'autre_contaminant', 'etiquette_detachee'] 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 Mask_Limeil_Label_PEHD_080621 NUM_CLASSES 11 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 : Mask_Limeil_Label_PEHD_080621 model_type : mask_rcnn list file need : ['mask_model.h5'] file exist in s3 : ['mask_model.h5'] file manque in s3 : [] 2025-10-10 10:19:11.229950: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-10-10 10:19:11.399991: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 local folder : /data/models_weight/Mask_Limeil_Label_PEHD_080621 /data/models_weight/Mask_Limeil_Label_PEHD_080621/mask_model.h5 size_local : 256052544 size in s3 : 256052544 create time local : 2021-08-11 19:43:15 create time in s3 : 2021-08-06 17:21:30 mask_model.h5 already exist and didn't need to update list_images length : 7 NEW PHOTO Processing 1 images image shape: (2160, 3840, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 19) min: 0.00000 max: 3840.00000 nb d'objets trouves : 57 NEW PHOTO Processing 1 images image shape: (2160, 3840, 3) min: 6.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 19) min: 0.00000 max: 3840.00000 nb d'objets trouves : 38 NEW PHOTO Processing 1 images image shape: (2160, 3840, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 19) min: 0.00000 max: 3840.00000 nb d'objets trouves : 66 NEW PHOTO Processing 1 images image shape: (2160, 3840, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 19) min: 0.00000 max: 3840.00000 nb d'objets trouves : 62 NEW PHOTO Processing 1 images image shape: (2160, 3840, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 19) min: 0.00000 max: 3840.00000 nb d'objets trouves : 63 NEW PHOTO Processing 1 images image shape: (2160, 3840, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 19) min: 0.00000 max: 3840.00000 nb d'objets trouves : 53 NEW PHOTO Processing 1 images image shape: (2160, 3840, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 19) min: 0.00000 max: 3840.00000 nb d'objets trouves : 52 Detection mask done ! Trying to reset tf kernel 41674 begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 5706 tf kernel not reseted sub process len(results) : 7 len(list_Values) 0 None max_time_sub_proc : 3600 parent process len(results) : 7 len(list_Values) 0 process is alive finish correctly or not : True after detect begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 10998 list_Values should be empty [] To do loadFromThcl(), then load ParamDescType : thcl2976 Catched exception ! Connect or reconnect ! thcls : [{'id': 2976, 'mtr_user_id': 31, 'name': 'Mask_Limeil_Label_PEHD_080621', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,environnement,fibreux_cont,metal_cont,pet_clair_cont,pet_fonce_cont,pet_opaque_cont,barquette,film_plastique,autre_contaminant,etiquette_detachee', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3760, 'photo_desc_type': 5359, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0,0,0'}] thcl {'id': 2976, 'mtr_user_id': 31, 'name': 'Mask_Limeil_Label_PEHD_080621', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,environnement,fibreux_cont,metal_cont,pet_clair_cont,pet_fonce_cont,pet_opaque_cont,barquette,film_plastique,autre_contaminant,etiquette_detachee', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3760, 'photo_desc_type': 5359, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0,0,0'} Update svm_hashtag_type_desc : 5359 ['background', 'environnement', 'fibreux_cont', 'metal_cont', 'pet_clair_cont', 'pet_fonce_cont', 'pet_opaque_cont', 'barquette', 'film_plastique', 'autre_contaminant', 'etiquette_detachee'] time for calcul the mask position with numpy : 0.01431894302368164 nb_pixel_total : 326735 time to create 1 rle with new method : 0.016749858856201172 length of segment : 773 time for calcul the mask position with numpy : 0.002654552459716797 nb_pixel_total : 57727 time to create 1 rle with old method : 0.06706833839416504 length of segment : 337 time for calcul the mask position with numpy : 0.0018074512481689453 nb_pixel_total : 36012 time to create 1 rle with old method : 0.039537668228149414 length of segment : 341 time for calcul the mask position with numpy : 0.014886140823364258 nb_pixel_total : 401560 time to create 1 rle with new method : 0.01917576789855957 length of segment : 938 time for calcul the mask position with numpy : 0.014424800872802734 nb_pixel_total : 320943 time to create 1 rle with new method : 0.021329641342163086 length of segment : 1127 time for calcul the mask position with numpy : 0.012747526168823242 nb_pixel_total : 373273 time to create 1 rle with new method : 0.01945018768310547 length of segment : 986 time for calcul the mask position with numpy : 0.0014955997467041016 nb_pixel_total : 29449 time to create 1 rle with old method : 0.03330636024475098 length of segment : 177 time for calcul the mask position with numpy : 0.001748800277709961 nb_pixel_total : 23150 time to create 1 rle with old method : 0.026662111282348633 length of segment : 217 time for calcul the mask position with numpy : 0.0026471614837646484 nb_pixel_total : 70374 time to create 1 rle with old method : 0.07904672622680664 length of segment : 263 time for calcul the mask position with numpy : 0.001947164535522461 nb_pixel_total : 59966 time to create 1 rle with old method : 0.06799888610839844 length of segment : 342 time for calcul the mask position with numpy : 0.002460002899169922 nb_pixel_total : 50651 time to create 1 rle with old method : 0.05838918685913086 length of segment : 231 time for calcul the mask position with numpy : 0.0009686946868896484 nb_pixel_total : 23800 time to create 1 rle with old method : 0.026312589645385742 length of segment : 191 time for calcul the mask position with numpy : 0.0025458335876464844 nb_pixel_total : 41997 time to create 1 rle with old method : 0.045983314514160156 length of segment : 539 time for calcul the mask position with numpy : 0.0019326210021972656 nb_pixel_total : 87542 time to create 1 rle with old method : 0.09314537048339844 length of segment : 406 time for calcul the mask position with numpy : 0.0008873939514160156 nb_pixel_total : 15201 time to create 1 rle with old method : 0.020659208297729492 length of segment : 111 time for calcul the mask position with numpy : 0.014247655868530273 nb_pixel_total : 16441 time to create 1 rle with old method : 0.042112112045288086 length of segment : 124 time for calcul the mask position with numpy : 0.00020074844360351562 nb_pixel_total : 1528 time to create 1 rle with old method : 0.0018749237060546875 length of segment : 45 time for calcul the mask position with numpy : 0.0005342960357666016 nb_pixel_total : 6502 time to create 1 rle with old method : 0.013105154037475586 length of segment : 69 time for calcul the mask position with numpy : 0.002210855484008789 nb_pixel_total : 42576 time to create 1 rle with old method : 0.04711556434631348 length of segment : 422 time for calcul the mask position with numpy : 0.0025136470794677734 nb_pixel_total : 62370 time to create 1 rle with old method : 0.07020998001098633 length of segment : 357 time for calcul the mask position with numpy : 0.00031113624572753906 nb_pixel_total : 6065 time to create 1 rle with old method : 0.009076118469238281 length of segment : 80 time for calcul the mask position with numpy : 0.003042459487915039 nb_pixel_total : 51165 time to create 1 rle with old method : 0.06436729431152344 length of segment : 198 time for calcul the mask position with numpy : 0.006797313690185547 nb_pixel_total : 120421 time to create 1 rle with old method : 0.1350107192993164 length of segment : 1103 time for calcul the mask position with numpy : 0.001650094985961914 nb_pixel_total : 23894 time to create 1 rle with old method : 0.02662491798400879 length of segment : 246 time for calcul the mask position with numpy : 0.0003864765167236328 nb_pixel_total : 9514 time to create 1 rle with old method : 0.011649370193481445 length of segment : 125 time for calcul the mask position with numpy : 0.0007026195526123047 nb_pixel_total : 12780 time to create 1 rle with old method : 0.015343666076660156 length of segment : 139 time for calcul the mask position with numpy : 0.0014269351959228516 nb_pixel_total : 28388 time to create 1 rle with old method : 0.0370182991027832 length of segment : 213 time for calcul the mask position with numpy : 0.005935192108154297 nb_pixel_total : 130943 time to create 1 rle with old method : 0.1464688777923584 length of segment : 670 time for calcul the mask position with numpy : 0.0024132728576660156 nb_pixel_total : 109774 time to create 1 rle with old method : 0.12784385681152344 length of segment : 646 time for calcul the mask position with numpy : 0.011632442474365234 nb_pixel_total : 272141 time to create 1 rle with new method : 0.017425060272216797 length of segment : 645 time for calcul the mask position with numpy : 0.006398916244506836 nb_pixel_total : 181292 time to create 1 rle with new method : 0.01570868492126465 length of segment : 684 time for calcul the mask position with numpy : 0.0001709461212158203 nb_pixel_total : 2150 time to create 1 rle with old method : 0.0026836395263671875 length of segment : 44 time for calcul the mask position with numpy : 0.00026535987854003906 nb_pixel_total : 3040 time to create 1 rle with old method : 0.0037107467651367188 length of segment : 69 time for calcul the mask position with numpy : 0.0022475719451904297 nb_pixel_total : 77986 time to create 1 rle with old method : 0.08673453330993652 length of segment : 286 time for calcul the mask position with numpy : 0.010776042938232422 nb_pixel_total : 347412 time to create 1 rle with new method : 0.017033100128173828 length of segment : 666 time for calcul the mask position with numpy : 0.0027093887329101562 nb_pixel_total : 82734 time to create 1 rle with old method : 0.08987164497375488 length of segment : 269 time for calcul the mask position with numpy : 0.0015711784362792969 nb_pixel_total : 49132 time to create 1 rle with old method : 0.056981563568115234 length of segment : 275 time for calcul the mask position with numpy : 0.008085250854492188 nb_pixel_total : 329283 time to create 1 rle with new method : 0.01399683952331543 length of segment : 547 time for calcul the mask position with numpy : 0.012301206588745117 nb_pixel_total : 394436 time to create 1 rle with new method : 0.019377470016479492 length of segment : 880 time for calcul the mask position with numpy : 0.009692668914794922 nb_pixel_total : 369772 time to create 1 rle with new method : 0.023084640502929688 length of segment : 1023 time for calcul the mask position with numpy : 0.011188030242919922 nb_pixel_total : 199636 time to create 1 rle with new method : 0.019758224487304688 length of segment : 518 time for calcul the mask position with numpy : 0.010106563568115234 nb_pixel_total : 337363 time to create 1 rle with new method : 0.016131877899169922 length of segment : 849 time for calcul the mask position with numpy : 0.012786388397216797 nb_pixel_total : 394182 time to create 1 rle with new method : 0.020683765411376953 length of segment : 891 time for calcul the mask position with numpy : 0.008536577224731445 nb_pixel_total : 241295 time to create 1 rle with new method : 0.01569223403930664 length of segment : 713 time for calcul the mask position with numpy : 0.014340877532958984 nb_pixel_total : 470357 time to create 1 rle with new method : 0.019750118255615234 length of segment : 976 time for calcul the mask position with numpy : 0.0012967586517333984 nb_pixel_total : 35035 time to create 1 rle with old method : 0.04058361053466797 length of segment : 220 time for calcul the mask position with numpy : 0.008912324905395508 nb_pixel_total : 365118 time to create 1 rle with new method : 0.01680612564086914 length of segment : 848 time for calcul the mask position with numpy : 0.0042269229888916016 nb_pixel_total : 151997 time to create 1 rle with new method : 0.006832122802734375 length of segment : 509 time for calcul the mask position with numpy : 0.00810694694519043 nb_pixel_total : 302043 time to create 1 rle with new method : 0.016483783721923828 length of segment : 912 time for calcul the mask position with numpy : 0.002809286117553711 nb_pixel_total : 110195 time to create 1 rle with old method : 0.126434326171875 length of segment : 552 time for calcul the mask position with numpy : 0.008456230163574219 nb_pixel_total : 218667 time to create 1 rle with new method : 0.015543937683105469 length of segment : 644 time for calcul the mask position with numpy : 0.0023696422576904297 nb_pixel_total : 65285 time to create 1 rle with old method : 0.07505559921264648 length of segment : 268 time for calcul the mask position with numpy : 0.016420364379882812 nb_pixel_total : 447800 time to create 1 rle with new method : 0.024576187133789062 length of segment : 839 time for calcul the mask position with numpy : 0.002541780471801758 nb_pixel_total : 61905 time to create 1 rle with old method : 0.06888556480407715 length of segment : 365 time for calcul the mask position with numpy : 0.004010438919067383 nb_pixel_total : 202234 time to create 1 rle with new method : 0.014594316482543945 length of segment : 712 time for calcul the mask position with numpy : 0.010591983795166016 nb_pixel_total : 243585 time to create 1 rle with new method : 0.02495574951171875 length of segment : 745 time for calcul the mask position with numpy : 0.004223346710205078 nb_pixel_total : 89634 time to create 1 rle with old method : 0.10137200355529785 length of segment : 534 time for calcul the mask position with numpy : 0.0018565654754638672 nb_pixel_total : 57412 time to create 1 rle with old method : 0.06478571891784668 length of segment : 285 time for calcul the mask position with numpy : 0.00902414321899414 nb_pixel_total : 225543 time to create 1 rle with new method : 0.01594710350036621 length of segment : 724 time for calcul the mask position with numpy : 0.0023992061614990234 nb_pixel_total : 141332 time to create 1 rle with old method : 0.16334128379821777 length of segment : 424 time for calcul the mask position with numpy : 0.006224870681762695 nb_pixel_total : 228474 time to create 1 rle with new method : 0.014362335205078125 length of segment : 558 time for calcul the mask position with numpy : 0.012180089950561523 nb_pixel_total : 272250 time to create 1 rle with new method : 0.01913142204284668 length of segment : 797 time for calcul the mask position with numpy : 0.013895511627197266 nb_pixel_total : 383226 time to create 1 rle with new method : 0.021548032760620117 length of segment : 676 time for calcul the mask position with numpy : 0.013688802719116211 nb_pixel_total : 369507 time to create 1 rle with new method : 0.020535945892333984 length of segment : 1194 time for calcul the mask position with numpy : 0.0014925003051757812 nb_pixel_total : 23357 time to create 1 rle with old method : 0.028089523315429688 length of segment : 173 time for calcul the mask position with numpy : 0.0028314590454101562 nb_pixel_total : 55816 time to create 1 rle with old method : 0.06275582313537598 length of segment : 281 time for calcul the mask position with numpy : 0.003675699234008789 nb_pixel_total : 76552 time to create 1 rle with old method : 0.08493232727050781 length of segment : 421 time for calcul the mask position with numpy : 0.015830039978027344 nb_pixel_total : 352776 time to create 1 rle with new method : 0.02193903923034668 length of segment : 747 time for calcul the mask position with numpy : 0.0005345344543457031 nb_pixel_total : 10597 time to create 1 rle with old method : 0.012554168701171875 length of segment : 113 time for calcul the mask position with numpy : 0.006304025650024414 nb_pixel_total : 120053 time to create 1 rle with old method : 0.1340172290802002 length of segment : 615 time for calcul the mask position with numpy : 0.0008609294891357422 nb_pixel_total : 42948 time to create 1 rle with old method : 0.04787921905517578 length of segment : 287 time for calcul the mask position with numpy : 0.012532949447631836 nb_pixel_total : 297499 time to create 1 rle with new method : 0.019727230072021484 length of segment : 967 time for calcul the mask position with numpy : 0.0028786659240722656 nb_pixel_total : 40179 time to create 1 rle with old method : 0.044737815856933594 length of segment : 314 time for calcul the mask position with numpy : 0.002621173858642578 nb_pixel_total : 53972 time to create 1 rle with old method : 0.06049156188964844 length of segment : 255 time for calcul the mask position with numpy : 0.0015463829040527344 nb_pixel_total : 35728 time to create 1 rle with old method : 0.04062509536743164 length of segment : 248 time for calcul the mask position with numpy : 0.0009195804595947266 nb_pixel_total : 32681 time to create 1 rle with old method : 0.03704833984375 length of segment : 299 time for calcul the mask position with numpy : 0.0008642673492431641 nb_pixel_total : 17699 time to create 1 rle with old method : 0.02056264877319336 length of segment : 130 time for calcul the mask position with numpy : 0.004927158355712891 nb_pixel_total : 84988 time to create 1 rle with old method : 0.09572434425354004 length of segment : 451 time for calcul the mask position with numpy : 0.002481222152709961 nb_pixel_total : 60262 time to create 1 rle with old method : 0.06840729713439941 length of segment : 313 time for calcul the mask position with numpy : 0.0041882991790771484 nb_pixel_total : 106604 time to create 1 rle with old method : 0.11976337432861328 length of segment : 317 time for calcul the mask position with numpy : 0.00027680397033691406 nb_pixel_total : 3152 time to create 1 rle with old method : 0.0037467479705810547 length of segment : 95 time for calcul the mask position with numpy : 0.0038628578186035156 nb_pixel_total : 79829 time to create 1 rle with old method : 0.08725261688232422 length of segment : 386 time for calcul the mask position with numpy : 0.001276254653930664 nb_pixel_total : 8786 time to create 1 rle with old method : 0.010391950607299805 length of segment : 118 time for calcul the mask position with numpy : 0.007986068725585938 nb_pixel_total : 324082 time to create 1 rle with new method : 0.01844930648803711 length of segment : 768 time for calcul the mask position with numpy : 0.002207517623901367 nb_pixel_total : 33102 time to create 1 rle with old method : 0.03775835037231445 length of segment : 276 time for calcul the mask position with numpy : 0.002209186553955078 nb_pixel_total : 50541 time to create 1 rle with old method : 0.05691409111022949 length of segment : 156 time for calcul the mask position with numpy : 0.003016948699951172 nb_pixel_total : 59392 time to create 1 rle with old method : 0.06902027130126953 length of segment : 307 time for calcul the mask position with numpy : 0.002477407455444336 nb_pixel_total : 57405 time to create 1 rle with old method : 0.06435155868530273 length of segment : 388 time for calcul the mask position with numpy : 0.0026199817657470703 nb_pixel_total : 40266 time to create 1 rle with old method : 0.04569602012634277 length of segment : 303 time for calcul the mask position with numpy : 0.00048732757568359375 nb_pixel_total : 8915 time to create 1 rle with old method : 0.010244131088256836 length of segment : 109 time for calcul the mask position with numpy : 0.0008251667022705078 nb_pixel_total : 10700 time to create 1 rle with old method : 0.012434959411621094 length of segment : 167 time for calcul the mask position with numpy : 0.0012369155883789062 nb_pixel_total : 22018 time to create 1 rle with old method : 0.02517843246459961 length of segment : 274 time for calcul the mask position with numpy : 0.0007309913635253906 nb_pixel_total : 15482 time to create 1 rle with old method : 0.027213096618652344 length of segment : 105 time for calcul the mask position with numpy : 0.0005514621734619141 nb_pixel_total : 6497 time to create 1 rle with old method : 0.00821065902709961 length of segment : 141 time for calcul the mask position with numpy : 0.002941608428955078 nb_pixel_total : 74165 time to create 1 rle with old method : 0.08188676834106445 length of segment : 630 time for calcul the mask position with numpy : 0.0004131793975830078 nb_pixel_total : 8682 time to create 1 rle with old method : 0.009920597076416016 length of segment : 88 time for calcul the mask position with numpy : 0.0019044876098632812 nb_pixel_total : 30235 time to create 1 rle with old method : 0.03467893600463867 length of segment : 232 time for calcul the mask position with numpy : 0.0002765655517578125 nb_pixel_total : 8797 time to create 1 rle with old method : 0.010134220123291016 length of segment : 124 time for calcul the mask position with numpy : 0.0011832714080810547 nb_pixel_total : 48210 time to create 1 rle with old method : 0.056748151779174805 length of segment : 330 time for calcul the mask position with numpy : 0.0008463859558105469 nb_pixel_total : 16760 time to create 1 rle with old method : 0.019588947296142578 length of segment : 190 time for calcul the mask position with numpy : 0.014126300811767578 nb_pixel_total : 348664 time to create 1 rle with new method : 0.021703243255615234 length of segment : 803 time for calcul the mask position with numpy : 0.0045359134674072266 nb_pixel_total : 83378 time to create 1 rle with old method : 0.09410572052001953 length of segment : 381 time for calcul the mask position with numpy : 0.016239166259765625 nb_pixel_total : 443036 time to create 1 rle with new method : 0.021637916564941406 length of segment : 704 time for calcul the mask position with numpy : 0.014153003692626953 nb_pixel_total : 448319 time to create 1 rle with new method : 0.019557952880859375 length of segment : 701 time for calcul the mask position with numpy : 0.0132293701171875 nb_pixel_total : 311365 time to create 1 rle with new method : 0.02256178855895996 length of segment : 1024 time for calcul the mask position with numpy : 0.007464885711669922 nb_pixel_total : 192870 time to create 1 rle with new method : 0.011912345886230469 length of segment : 521 time for calcul the mask position with numpy : 0.013898849487304688 nb_pixel_total : 355066 time to create 1 rle with new method : 0.020344972610473633 length of segment : 832 time for calcul the mask position with numpy : 0.0002079010009765625 nb_pixel_total : 6946 time to create 1 rle with old method : 0.007708311080932617 length of segment : 151 time for calcul the mask position with numpy : 0.002403736114501953 nb_pixel_total : 43617 time to create 1 rle with old method : 0.05053400993347168 length of segment : 327 time for calcul the mask position with numpy : 0.0014281272888183594 nb_pixel_total : 19073 time to create 1 rle with old method : 0.033081769943237305 length of segment : 203 time for calcul the mask position with numpy : 0.0027713775634765625 nb_pixel_total : 65030 time to create 1 rle with old method : 0.09393930435180664 length of segment : 290 time for calcul the mask position with numpy : 0.0008633136749267578 nb_pixel_total : 20750 time to create 1 rle with old method : 0.02382826805114746 length of segment : 183 time for calcul the mask position with numpy : 0.0006654262542724609 nb_pixel_total : 15610 time to create 1 rle with old method : 0.01802992820739746 length of segment : 174 time for calcul the mask position with numpy : 0.0017085075378417969 nb_pixel_total : 18868 time to create 1 rle with old method : 0.021254301071166992 length of segment : 258 time for calcul the mask position with numpy : 0.003442049026489258 nb_pixel_total : 48664 time to create 1 rle with old method : 0.05748271942138672 length of segment : 277 time for calcul the mask position with numpy : 0.001893758773803711 nb_pixel_total : 35547 time to create 1 rle with old method : 0.042452096939086914 length of segment : 237 time for calcul the mask position with numpy : 0.00135040283203125 nb_pixel_total : 22945 time to create 1 rle with old method : 0.04792618751525879 length of segment : 141 time for calcul the mask position with numpy : 0.0007424354553222656 nb_pixel_total : 9428 time to create 1 rle with old method : 0.010859012603759766 length of segment : 358 time for calcul the mask position with numpy : 0.0009167194366455078 nb_pixel_total : 24278 time to create 1 rle with old method : 0.027978181838989258 length of segment : 159 time for calcul the mask position with numpy : 0.00047969818115234375 nb_pixel_total : 8010 time to create 1 rle with old method : 0.009694814682006836 length of segment : 122 time for calcul the mask position with numpy : 0.0007600784301757812 nb_pixel_total : 17721 time to create 1 rle with old method : 0.021183490753173828 length of segment : 75 time for calcul the mask position with numpy : 0.0002701282501220703 nb_pixel_total : 6074 time to create 1 rle with old method : 0.007238864898681641 length of segment : 79 time for calcul the mask position with numpy : 0.0013301372528076172 nb_pixel_total : 24150 time to create 1 rle with old method : 0.028214216232299805 length of segment : 154 time for calcul the mask position with numpy : 0.0026712417602539062 nb_pixel_total : 58966 time to create 1 rle with old method : 0.06675577163696289 length of segment : 423 time for calcul the mask position with numpy : 0.011912345886230469 nb_pixel_total : 274031 time to create 1 rle with new method : 0.018849611282348633 length of segment : 551 time for calcul the mask position with numpy : 0.002593994140625 nb_pixel_total : 70716 time to create 1 rle with old method : 0.08057689666748047 length of segment : 326 time for calcul the mask position with numpy : 0.0007464885711669922 nb_pixel_total : 25657 time to create 1 rle with old method : 0.04148530960083008 length of segment : 351 time for calcul the mask position with numpy : 0.00011038780212402344 nb_pixel_total : 1880 time to create 1 rle with old method : 0.004346370697021484 length of segment : 52 time for calcul the mask position with numpy : 0.0011856555938720703 nb_pixel_total : 25021 time to create 1 rle with old method : 0.0282437801361084 length of segment : 139 time for calcul the mask position with numpy : 0.002196788787841797 nb_pixel_total : 44175 time to create 1 rle with old method : 0.0527493953704834 length of segment : 227 time for calcul the mask position with numpy : 0.0009253025054931641 nb_pixel_total : 14855 time to create 1 rle with old method : 0.017362356185913086 length of segment : 162 time for calcul the mask position with numpy : 0.013492584228515625 nb_pixel_total : 326772 time to create 1 rle with new method : 0.020689964294433594 length of segment : 758 time for calcul the mask position with numpy : 0.0005900859832763672 nb_pixel_total : 13689 time to create 1 rle with old method : 0.01611471176147461 length of segment : 80 time for calcul the mask position with numpy : 0.015482664108276367 nb_pixel_total : 422273 time to create 1 rle with new method : 0.020087003707885742 length of segment : 873 time for calcul the mask position with numpy : 0.011732339859008789 nb_pixel_total : 264930 time to create 1 rle with new method : 0.02203059196472168 length of segment : 883 time for calcul the mask position with numpy : 0.016371965408325195 nb_pixel_total : 419167 time to create 1 rle with new method : 0.020275354385375977 length of segment : 665 time for calcul the mask position with numpy : 0.019094467163085938 nb_pixel_total : 412571 time to create 1 rle with new method : 0.027907371520996094 length of segment : 698 time for calcul the mask position with numpy : 0.00445103645324707 nb_pixel_total : 101364 time to create 1 rle with old method : 0.1238255500793457 length of segment : 422 time for calcul the mask position with numpy : 0.0019156932830810547 nb_pixel_total : 40548 time to create 1 rle with old method : 0.04910778999328613 length of segment : 225 time for calcul the mask position with numpy : 0.011774539947509766 nb_pixel_total : 306898 time to create 1 rle with new method : 0.020846843719482422 length of segment : 808 time for calcul the mask position with numpy : 0.002630472183227539 nb_pixel_total : 54997 time to create 1 rle with old method : 0.06097102165222168 length of segment : 288 time for calcul the mask position with numpy : 0.0010569095611572266 nb_pixel_total : 28885 time to create 1 rle with old method : 0.03321647644042969 length of segment : 143 time for calcul the mask position with numpy : 0.0005497932434082031 nb_pixel_total : 11743 time to create 1 rle with old method : 0.015061616897583008 length of segment : 115 time for calcul the mask position with numpy : 0.0022172927856445312 nb_pixel_total : 33460 time to create 1 rle with old method : 0.04129958152770996 length of segment : 254 time for calcul the mask position with numpy : 0.0005469322204589844 nb_pixel_total : 10046 time to create 1 rle with old method : 0.012029409408569336 length of segment : 81 time for calcul the mask position with numpy : 0.001331329345703125 nb_pixel_total : 22481 time to create 1 rle with old method : 0.026692867279052734 length of segment : 106 time for calcul the mask position with numpy : 0.0027511119842529297 nb_pixel_total : 66744 time to create 1 rle with old method : 0.07811117172241211 length of segment : 177 time for calcul the mask position with numpy : 0.0003418922424316406 nb_pixel_total : 7698 time to create 1 rle with old method : 0.008891105651855469 length of segment : 92 time for calcul the mask position with numpy : 0.004851579666137695 nb_pixel_total : 87962 time to create 1 rle with old method : 0.10016584396362305 length of segment : 331 time for calcul the mask position with numpy : 0.017978668212890625 nb_pixel_total : 347173 time to create 1 rle with new method : 0.023970603942871094 length of segment : 895 time for calcul the mask position with numpy : 0.0021686553955078125 nb_pixel_total : 39047 time to create 1 rle with old method : 0.04384922981262207 length of segment : 416 time for calcul the mask position with numpy : 0.001546621322631836 nb_pixel_total : 34878 time to create 1 rle with old method : 0.03980064392089844 length of segment : 172 time for calcul the mask position with numpy : 0.0019750595092773438 nb_pixel_total : 26231 time to create 1 rle with old method : 0.03451704978942871 length of segment : 278 time for calcul the mask position with numpy : 0.00063323974609375 nb_pixel_total : 8204 time to create 1 rle with old method : 0.009523630142211914 length of segment : 87 time for calcul the mask position with numpy : 0.002262115478515625 nb_pixel_total : 35249 time to create 1 rle with old method : 0.03978300094604492 length of segment : 211 time for calcul the mask position with numpy : 0.0015807151794433594 nb_pixel_total : 33947 time to create 1 rle with old method : 0.03804922103881836 length of segment : 221 time for calcul the mask position with numpy : 0.00025200843811035156 nb_pixel_total : 4286 time to create 1 rle with old method : 0.005296945571899414 length of segment : 37 time for calcul the mask position with numpy : 0.0029795169830322266 nb_pixel_total : 70714 time to create 1 rle with old method : 0.07898712158203125 length of segment : 323 time for calcul the mask position with numpy : 0.012326717376708984 nb_pixel_total : 362634 time to create 1 rle with new method : 0.025382280349731445 length of segment : 852 time for calcul the mask position with numpy : 0.0012776851654052734 nb_pixel_total : 18099 time to create 1 rle with old method : 0.020977258682250977 length of segment : 221 time for calcul the mask position with numpy : 0.0004050731658935547 nb_pixel_total : 6310 time to create 1 rle with old method : 0.007592201232910156 length of segment : 75 time for calcul the mask position with numpy : 0.003306150436401367 nb_pixel_total : 69474 time to create 1 rle with old method : 0.07815027236938477 length of segment : 331 time for calcul the mask position with numpy : 0.0007212162017822266 nb_pixel_total : 16384 time to create 1 rle with old method : 0.017820119857788086 length of segment : 189 time for calcul the mask position with numpy : 0.00937509536743164 nb_pixel_total : 260007 time to create 1 rle with new method : 0.013866424560546875 length of segment : 717 time for calcul the mask position with numpy : 0.018922805786132812 nb_pixel_total : 470562 time to create 1 rle with new method : 0.027477264404296875 length of segment : 738 time for calcul the mask position with numpy : 0.013901233673095703 nb_pixel_total : 258786 time to create 1 rle with new method : 0.022124290466308594 length of segment : 884 time for calcul the mask position with numpy : 0.01334524154663086 nb_pixel_total : 414323 time to create 1 rle with new method : 0.019166946411132812 length of segment : 682 time for calcul the mask position with numpy : 0.0034987926483154297 nb_pixel_total : 75223 time to create 1 rle with old method : 0.08575868606567383 length of segment : 589 time for calcul the mask position with numpy : 0.0016474723815917969 nb_pixel_total : 17559 time to create 1 rle with old method : 0.02512812614440918 length of segment : 257 time for calcul the mask position with numpy : 0.0006384849548339844 nb_pixel_total : 42845 time to create 1 rle with old method : 0.04770541191101074 length of segment : 223 time for calcul the mask position with numpy : 0.00741124153137207 nb_pixel_total : 134211 time to create 1 rle with old method : 0.17012429237365723 length of segment : 379 time for calcul the mask position with numpy : 0.0098114013671875 nb_pixel_total : 326659 time to create 1 rle with new method : 0.018331527709960938 length of segment : 1143 time for calcul the mask position with numpy : 0.002810239791870117 nb_pixel_total : 92246 time to create 1 rle with old method : 0.10463213920593262 length of segment : 229 time for calcul the mask position with numpy : 0.012819528579711914 nb_pixel_total : 335048 time to create 1 rle with new method : 0.024796009063720703 length of segment : 991 time for calcul the mask position with numpy : 0.0036916732788085938 nb_pixel_total : 50234 time to create 1 rle with old method : 0.0942695140838623 length of segment : 270 time for calcul the mask position with numpy : 0.002579927444458008 nb_pixel_total : 87789 time to create 1 rle with old method : 0.1645512580871582 length of segment : 341 time for calcul the mask position with numpy : 0.0010104179382324219 nb_pixel_total : 19791 time to create 1 rle with old method : 0.04753446578979492 length of segment : 236 time for calcul the mask position with numpy : 0.0029125213623046875 nb_pixel_total : 43146 time to create 1 rle with old method : 0.0808713436126709 length of segment : 253 time for calcul the mask position with numpy : 0.0024585723876953125 nb_pixel_total : 32794 time to create 1 rle with old method : 0.0622861385345459 length of segment : 232 time for calcul the mask position with numpy : 0.0020215511322021484 nb_pixel_total : 26472 time to create 1 rle with old method : 0.04924464225769043 length of segment : 196 time for calcul the mask position with numpy : 0.0017771720886230469 nb_pixel_total : 27949 time to create 1 rle with old method : 0.052594900131225586 length of segment : 276 time for calcul the mask position with numpy : 0.0010249614715576172 nb_pixel_total : 14677 time to create 1 rle with old method : 0.028388500213623047 length of segment : 79 time for calcul the mask position with numpy : 0.0017404556274414062 nb_pixel_total : 27861 time to create 1 rle with old method : 0.05151963233947754 length of segment : 215 time for calcul the mask position with numpy : 0.0017135143280029297 nb_pixel_total : 17712 time to create 1 rle with old method : 0.03416562080383301 length of segment : 223 time for calcul the mask position with numpy : 0.0027587413787841797 nb_pixel_total : 44604 time to create 1 rle with old method : 0.08318614959716797 length of segment : 251 time for calcul the mask position with numpy : 0.0050504207611083984 nb_pixel_total : 101226 time to create 1 rle with old method : 0.11581134796142578 length of segment : 357 time for calcul the mask position with numpy : 0.0004642009735107422 nb_pixel_total : 14780 time to create 1 rle with old method : 0.01738429069519043 length of segment : 232 time for calcul the mask position with numpy : 0.004160881042480469 nb_pixel_total : 97348 time to create 1 rle with old method : 0.10984134674072266 length of segment : 355 time for calcul the mask position with numpy : 0.010277032852172852 nb_pixel_total : 306434 time to create 1 rle with new method : 0.016925573348999023 length of segment : 758 time for calcul the mask position with numpy : 0.016542911529541016 nb_pixel_total : 438440 time to create 1 rle with new method : 0.020877838134765625 length of segment : 641 time for calcul the mask position with numpy : 0.013284683227539062 nb_pixel_total : 405454 time to create 1 rle with new method : 0.01922130584716797 length of segment : 1016 time for calcul the mask position with numpy : 0.0024530887603759766 nb_pixel_total : 87373 time to create 1 rle with old method : 0.09380888938903809 length of segment : 318 time for calcul the mask position with numpy : 0.010201215744018555 nb_pixel_total : 351726 time to create 1 rle with new method : 0.015427827835083008 length of segment : 722 time for calcul the mask position with numpy : 0.012696504592895508 nb_pixel_total : 377088 time to create 1 rle with new method : 0.019294261932373047 length of segment : 861 time for calcul the mask position with numpy : 0.009710311889648438 nb_pixel_total : 307100 time to create 1 rle with new method : 0.02410268783569336 length of segment : 924 time for calcul the mask position with numpy : 0.0006566047668457031 nb_pixel_total : 8687 time to create 1 rle with old method : 0.010309696197509766 length of segment : 148 time for calcul the mask position with numpy : 0.008408784866333008 nb_pixel_total : 266440 time to create 1 rle with new method : 0.019102811813354492 length of segment : 792 time for calcul the mask position with numpy : 0.0011928081512451172 nb_pixel_total : 22170 time to create 1 rle with old method : 0.0307462215423584 length of segment : 152 time for calcul the mask position with numpy : 0.0003590583801269531 nb_pixel_total : 9112 time to create 1 rle with old method : 0.011216402053833008 length of segment : 149 time for calcul the mask position with numpy : 0.0003821849822998047 nb_pixel_total : 5385 time to create 1 rle with old method : 0.006636619567871094 length of segment : 134 time for calcul the mask position with numpy : 0.0015878677368164062 nb_pixel_total : 25830 time to create 1 rle with old method : 0.030550718307495117 length of segment : 249 time for calcul the mask position with numpy : 0.0007207393646240234 nb_pixel_total : 32883 time to create 1 rle with old method : 0.03862118721008301 length of segment : 198 time for calcul the mask position with numpy : 0.0033261775970458984 nb_pixel_total : 82636 time to create 1 rle with old method : 0.09795451164245605 length of segment : 434 time for calcul the mask position with numpy : 0.0003414154052734375 nb_pixel_total : 2558 time to create 1 rle with old method : 0.005212545394897461 length of segment : 47 time for calcul the mask position with numpy : 0.0003452301025390625 nb_pixel_total : 6391 time to create 1 rle with old method : 0.012017488479614258 length of segment : 89 time for calcul the mask position with numpy : 0.0029764175415039062 nb_pixel_total : 56135 time to create 1 rle with old method : 0.0643453598022461 length of segment : 426 time for calcul the mask position with numpy : 0.0008878707885742188 nb_pixel_total : 18038 time to create 1 rle with old method : 0.020992279052734375 length of segment : 182 time for calcul the mask position with numpy : 0.0021660327911376953 nb_pixel_total : 35861 time to create 1 rle with old method : 0.04239249229431152 length of segment : 296 time for calcul the mask position with numpy : 0.001386880874633789 nb_pixel_total : 26060 time to create 1 rle with old method : 0.04217338562011719 length of segment : 161 time for calcul the mask position with numpy : 0.0005567073822021484 nb_pixel_total : 6995 time to create 1 rle with old method : 0.00848078727722168 length of segment : 130 time for calcul the mask position with numpy : 0.001432657241821289 nb_pixel_total : 26265 time to create 1 rle with old method : 0.030757904052734375 length of segment : 202 time for calcul the mask position with numpy : 0.0014700889587402344 nb_pixel_total : 23912 time to create 1 rle with old method : 0.02809453010559082 length of segment : 205 time for calcul the mask position with numpy : 0.0008139610290527344 nb_pixel_total : 15227 time to create 1 rle with old method : 0.01729583740234375 length of segment : 177 time spent for convertir_results : 21.860234260559082 Inside saveOutput : final : False verbose : 0 eke 12-6-18 : saveMask need to be cleaned for new output ! Number saved : None batch 1 Loaded 213 chid ids of type : 3760 Number RLEs to save : 85126 save missing photos in datou_result : time spend for datou_step_exec : 88.68377900123596 time spend to save output : 8.420957803726196 total time spend for step 1 : 97.10473680496216 step2:blur_detection Fri Oct 10 10:20:37 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/1760084338_41623_1388607356_4feae2b60c73201395be33b5d77ceb70.jpg resize: (2160, 3840) 1388607356 3.7397318175490306 treat image : temp/1760084338_41623_1388607351_ad9612884254167d834fa004414b83d2.jpg resize: (2160, 3840) 1388607351 1.2133471737161563 treat image : temp/1760084338_41623_1388607327_81e3a5b54698baa1fa09c64e3943f087.jpg resize: (2160, 3840) 1388607327 -1.427640946705835 treat image : temp/1760084338_41623_1388607326_cb58e932fe5ab1e4b6b948f344f19e54.jpg resize: (2160, 3840) 1388607326 -3.246349801421127 treat image : temp/1760084338_41623_1388607251_da512109120c62ac38c1cec9a8b11cb3.jpg resize: (2160, 3840) 1388607251 3.5628499126995203 treat image : temp/1760084338_41623_1388607246_be2901cfcffb60c56b57173d1bc0ffbc.jpg resize: (2160, 3840) 1388607246 4.373083577919527 treat image : temp/1760084338_41623_1388607225_cf7e67936e9b6aeaaa95efd95c23d1df.jpg resize: (2160, 3840) 1388607225 2.816332015988374 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 : 7 time used for this insertion : 0.03469371795654297 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 7 time used for this insertion : 0.03572559356689453 save missing photos in datou_result : time spend for datou_step_exec : 22.621444940567017 time spend to save output : 0.087890625 total time spend for step 2 : 22.709335565567017 step3:brightness Fri Oct 10 10:21:00 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/1760084338_41623_1388607356_4feae2b60c73201395be33b5d77ceb70.jpg treat image : temp/1760084338_41623_1388607351_ad9612884254167d834fa004414b83d2.jpg treat image : temp/1760084338_41623_1388607327_81e3a5b54698baa1fa09c64e3943f087.jpg treat image : temp/1760084338_41623_1388607326_cb58e932fe5ab1e4b6b948f344f19e54.jpg treat image : temp/1760084338_41623_1388607251_da512109120c62ac38c1cec9a8b11cb3.jpg treat image : temp/1760084338_41623_1388607246_be2901cfcffb60c56b57173d1bc0ffbc.jpg treat image : temp/1760084338_41623_1388607225_cf7e67936e9b6aeaaa95efd95c23d1df.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 : 7 time used for this insertion : 0.03476405143737793 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 7 time used for this insertion : 0.03496837615966797 save missing photos in datou_result : time spend for datou_step_exec : 6.674891710281372 time spend to save output : 0.0874333381652832 total time spend for step 3 : 6.762325048446655 step4:crop_condition Fri Oct 10 10:21:06 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 Loading chi in step crop with photo_hashtag_type : 3760 Loading chi in step crop for list_pids : 7 ! batch 1 Loaded 213 chid ids of type : 3760 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ begin to crop the class : barquette param for this class : {'min_score': 0.7} filtre for class : barquette hashtag_id of this class : 492787675 we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! map_result returned by crop_photo_return_map_crop : length : 27 About to insert : list_path_to_insert length 27 new photo from crops ! we have finished the crop for the class : barquette begin to crop the class : fibreux_cont param for this class : {'min_score': 0.7} filtre for class : fibreux_cont hashtag_id of this class : 2107756748 we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles 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 ! we have finished the crop for the class : fibreux_cont begin to crop the class : film_plastique param for this class : {'min_score': 0.7} filtre for class : film_plastique hashtag_id of this class : 2107756122 we have both polygon and rles Next one ! map_result returned by crop_photo_return_map_crop : length : 1 About to insert : list_path_to_insert length 1 new photo from crops ! we have finished the crop for the class : film_plastique begin to crop the class : autre_contaminant param for this class : {'min_score': 0.7} filtre for class : autre_contaminant hashtag_id of this class : 2107756781 we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! map_result returned by crop_photo_return_map_crop : length : 49 About to insert : list_path_to_insert length 49 new photo from crops ! we have finished the crop for the class : autre_contaminant begin to crop the class : etiquette_detachee param for this class : {'min_score': 0.7} filtre for class : etiquette_detachee hashtag_id of this class : 2107756860 we have both polygon and rles Next one ! we have both polygon and rles 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 ! we have finished the crop for the class : etiquette_detachee begin to crop the class : pet_clair_cont param for this class : {'min_score': 0.7} filtre for class : pet_clair_cont hashtag_id of this class : 2107758154 we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! map_result returned by crop_photo_return_map_crop : length : 21 About to insert : list_path_to_insert length 21 new photo from crops ! we have finished the crop for the class : pet_clair_cont begin to crop the class : metal_cont param for this class : {'min_score': 0.7} filtre for class : metal_cont hashtag_id of this class : 2107756749 begin to crop the class : pet_fonce_cont param for this class : {'min_score': 0.7} filtre for class : pet_fonce_cont hashtag_id of this class : 2107758155 begin to crop the class : pet_opaque_cont param for this class : {'min_score': 0.7} filtre for class : pet_opaque_cont hashtag_id of this class : 2107758156 we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! map_result returned by crop_photo_return_map_crop : length : 32 About to insert : list_path_to_insert length 32 new photo from crops ! we have finished the crop for the class : pet_opaque_cont delete rles for these photos Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : crop_condition we use saveGeneral [1388607356, 1388607351, 1388607327, 1388607326, 1388607251, 1388607246, 1388607225] Looping around the photos to save general results len do output : 143 /-3992042292Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042294Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042287Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042342Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042321Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042337Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042322Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042319Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042343Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042333Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042331Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042372Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042361Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042396Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042391Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042429Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042437Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042424Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042427Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042431Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042432Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042434Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042471Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042456Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042477Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042493Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042473Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042364Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042382Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042367Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042354Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042401Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042395Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042403Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042463Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042469Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042465Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042497Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042438Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042308Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042313Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042301Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042296Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042304Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042311Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042298Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042336Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042339Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042335Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042377Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042380Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042383Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042385Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042368Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042381Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042370Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042371Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042355Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042350Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042375Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042376Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042358Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042384Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042356Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042387Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042405Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042408Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042402Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042414Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042393Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042416Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042428Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042430Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042435Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042442Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042441Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042448Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042426Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042436Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042462Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042467Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042468Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042491Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042486Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042492Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042496Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042490Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042484Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042297Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042445Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042305Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042306Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042299Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042378Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042359Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042415Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042400Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042398Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042412Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042444Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042423Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042443Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042466Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042460Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042464Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042470Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042455Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042487Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042483Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042494Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042498Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042314Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042288Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042307Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042295Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042309Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042315Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042312Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042345Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042374Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042352Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042373Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042365Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042362Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042351Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042360Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042397Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042410Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042394Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042399Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042411Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042406Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042404Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042409Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042447Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042418Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042440Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042458Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042453Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042472Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042454Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042461Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /-3992042488Didn'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 ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607356', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607351', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607327', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607326', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607251', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607246', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607225', None, None, None, None, None, '3919092') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 436 time used for this insertion : 0.046343326568603516 save_final save missing photos in datou_result : time spend for datou_step_exec : 41.47749042510986 time spend to save output : 0.050585031509399414 total time spend for step 4 : 41.52807545661926 step5:thcl Fri Oct 10 10:21:48 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec 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 3903 time to import caffe and check if the image exist : 0.013837099075317383 time to convert the images to numpy array : 0.06981563568115234 time to import caffe and check if the image exist : 0.014610528945922852 time to convert the images to numpy array : 0.09092497825622559 time to import caffe and check if the image exist : 0.01797938346862793 time to convert the images to numpy array : 0.11097216606140137 time to import caffe and check if the image exist : 0.01883244514465332 time to convert the images to numpy array : 0.12480425834655762 time to import caffe and check if the image exist : 0.022275686264038086 time to convert the images to numpy array : 0.1225731372833252 time to import caffe and check if the image exist : 0.016328811645507812 time to convert the images to numpy array : 0.13629889488220215 time to import caffe and check if the image exist : 0.01897573471069336 time to convert the images to numpy array : 0.13550376892089844 time to import caffe and check if the image exist : 0.019110441207885742 time to convert the images to numpy array : 0.13634204864501953 time to import caffe and check if the image exist : 0.017151832580566406 time to convert the images to numpy array : 0.13923096656799316 time to import caffe and check if the image exist : 0.007790088653564453 time to convert the images to numpy array : 0.15653324127197266 total time to convert the images to numpy array : 0.343858003616333 list photo_ids error: [] list photo_ids correct : [-3992042418, -3992042440, -3992042458, -3992042453, -3992042472, -3992042454, -3992042461, -3992042488, -3992042441, -3992042448, -3992042426, -3992042436, -3992042462, -3992042467, -3992042468, -3992042491, -3992042486, -3992042492, -3992042496, -3992042490, -3992042484, -3992042297, -3992042445, -3992042354, -3992042401, -3992042395, -3992042403, -3992042463, -3992042469, -3992042465, -3992042497, -3992042438, -3992042308, -3992042313, -3992042301, -3992042296, -3992042304, -3992042311, -3992042470, -3992042455, -3992042487, -3992042483, -3992042494, -3992042498, -3992042314, -3992042288, -3992042307, -3992042295, -3992042309, -3992042315, -3992042312, -3992042345, -3992042374, -3992042376, -3992042358, -3992042384, -3992042356, -3992042387, -3992042405, -3992042408, -3992042402, -3992042414, -3992042393, -3992042416, -3992042428, -3992042430, -3992042435, -3992042442, -3992042298, -3992042336, -3992042339, -3992042335, -3992042377, -3992042380, -3992042383, -3992042385, -3992042368, -3992042381, -3992042370, -3992042371, -3992042355, -3992042350, -3992042375, -3992042429, -3992042437, -3992042424, -3992042427, -3992042431, -3992042432, -3992042434, -3992042471, -3992042456, -3992042477, -3992042493, -3992042473, -3992042364, -3992042382, -3992042367, -3992042305, -3992042306, -3992042299, -3992042378, -3992042359, -3992042415, -3992042400, -3992042398, -3992042412, -3992042444, -3992042423, -3992042443, -3992042466, -3992042460, -3992042464, -3992042352, -3992042373, -3992042365, -3992042362, -3992042351, -3992042360, -3992042397, -3992042410, -3992042394, -3992042399, -3992042411, -3992042406, -3992042404, -3992042409, -3992042447, -3992042292, -3992042294, -3992042287, -3992042342, -3992042321, -3992042337, -3992042322, -3992042319, -3992042343, -3992042333, -3992042331, -3992042372, -3992042361, -3992042396, -3992042391] number of photos to traite : 143 try to delete the photos incorrect in DB tagging for thcl : 3903 To do loadFromThcl(), then load ParamDescType : thcl3903 thcls : [{'id': 3903, 'mtr_user_id': 31, 'name': 'learn_generique_28032025_6000_v2', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'barquette_opaque,carton,ela,environnement,etiquette,film_plastique,kraft,metal,papier,pehd,pet_clair,pet_fonce,pet_opaque,textiles_sanitaires', 'svm_portfolios_learning': '4825680,4829009,4825557,21852021,4824714,4824733,4825676,4824737,4824753,4829002,4824848,4824863,4825667,4825677', 'photo_hashtag_type': 5000, 'photo_desc_type': 6100, 'type_classification': 'caffe', 'hashtag_id_list': '2107760128,492774966,492741797,493012381,492636447,2107756122,493202403,492628673,492668766,628944319,2107755846,2107755900,2107759152,2107760129'}] thcl {'id': 3903, 'mtr_user_id': 31, 'name': 'learn_generique_28032025_6000_v2', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'barquette_opaque,carton,ela,environnement,etiquette,film_plastique,kraft,metal,papier,pehd,pet_clair,pet_fonce,pet_opaque,textiles_sanitaires', 'svm_portfolios_learning': '4825680,4829009,4825557,21852021,4824714,4824733,4825676,4824737,4824753,4829002,4824848,4824863,4825667,4825677', 'photo_hashtag_type': 5000, 'photo_desc_type': 6100, 'type_classification': 'caffe', 'hashtag_id_list': '2107760128,492774966,492741797,493012381,492636447,2107756122,493202403,492628673,492668766,628944319,2107755846,2107755900,2107759152,2107760129'} Update svm_hashtag_type_desc : 6100 FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (6100, 'learn_generique_28032025_6000_v2', 2048, 2048, 'learn_generique_28032025_6000_v2', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 3, datetime.datetime(2025, 3, 28, 19, 8, 3), datetime.datetime(2025, 3, 28, 19, 8, 3)) To loadFromThcl() : net_6100 begin to check gpu status inside check gpu memory l 3637 free memory gpu now : 10776 max_wait_temp : 1 max_wait : 0 FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (6100, 'learn_generique_28032025_6000_v2', 2048, 2048, 'learn_generique_28032025_6000_v2', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 3, datetime.datetime(2025, 3, 28, 19, 8, 3), datetime.datetime(2025, 3, 28, 19, 8, 3)) None mean_file_type : mean_file_path : prototxt_file_path : model : learn_generique_28032025_6000_v2 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_generique_28032025_6000_v2 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_generique_28032025_6000_v2 /data/models_weight/learn_generique_28032025_6000_v2/caffemodel size_local : 94383067 size in s3 : 94383067 create time local : 2025-04-07 17:53:37 create time in s3 : 2025-03-28 18:08:00 caffemodel already exist and didn't need to update /data/models_weight/learn_generique_28032025_6000_v2/deploy.prototxt size_local : 32544 size in s3 : 32544 create time local : 2025-04-07 17:53:37 create time in s3 : 2025-03-28 18:08:00 deploy.prototxt already exist and didn't need to update /data/models_weight/learn_generique_28032025_6000_v2/mean.npy size_local : 1572992 size in s3 : 1572992 create time local : 2025-04-07 17:53:37 create time in s3 : 2025-03-28 18:08:02 mean.npy already exist and didn't need to update /data/models_weight/learn_generique_28032025_6000_v2/synset_words.txt size_local : 455 size in s3 : 455 create time local : 2025-04-07 17:53:38 create time in s3 : 2025-03-28 18:08:03 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_generique_28032025_6000_v2/deploy.prototxt caffemodel_filename : /data/models_weight/learn_generique_28032025_6000_v2/caffemodel now we set caffe to gpu mode before predict begin to check gpu status inside check gpu memory l 3637 free memory gpu now : 10555 max_wait_temp : 1 max_wait : 0 dict_keys(['prob', 'pool5']) time used to do the prepocess of the images : 1.1579902172088623 time used to do the prediction : 0.577228307723999 save descriptor for thcl : 3903 time to traite the descriptors : 0.7907254695892334 storage_type for insertDescriptorsMulti : 3 Missing photo l117 : -3992042418 Missing photo l117 : -3992042440 Missing photo l117 : -3992042458 Missing photo l117 : -3992042453 Missing photo l117 : -3992042472 Missing photo l117 : -3992042454 Missing photo l117 : -3992042461 Missing photo l117 : -3992042488 Missing photo l117 : -3992042441 Missing photo l117 : -3992042448 Missing photo l117 : -3992042426 Missing photo l117 : -3992042436 Missing photo l117 : -3992042462 Missing photo l117 : -3992042467 Missing photo l117 : -3992042468 Missing photo l117 : -3992042491 Missing photo l117 : -3992042486 Missing photo l117 : -3992042492 Missing photo l117 : -3992042496 Missing photo l117 : -3992042490 Missing photo l117 : -3992042484 Missing photo l117 : -3992042297 Missing photo l117 : -3992042445 Missing photo l117 : -3992042354 Missing photo l117 : -3992042401 Missing photo l117 : -3992042395 Missing photo l117 : -3992042403 Missing photo l117 : -3992042463 Missing photo l117 : -3992042469 Missing photo l117 : -3992042465 Missing photo l117 : -3992042497 Missing photo l117 : -3992042438 Missing photo l117 : -3992042308 Missing photo l117 : -3992042313 Missing photo l117 : -3992042301 Missing photo l117 : -3992042296 Missing photo l117 : -3992042304 Missing photo l117 : -3992042311 Missing photo l117 : -3992042470 Missing photo l117 : -3992042455 Missing photo l117 : -3992042487 Missing photo l117 : -3992042483 Missing photo l117 : -3992042494 Missing photo l117 : -3992042498 Missing photo l117 : -3992042314 Missing photo l117 : -3992042288 Missing photo l117 : -3992042307 Missing photo l117 : -3992042295 Missing photo l117 : -3992042309 Missing photo l117 : -3992042315 Missing photo l117 : -3992042312 Missing photo l117 : -3992042345 Missing photo l117 : -3992042374 Missing photo l117 : -3992042376 Missing photo l117 : -3992042358 Missing photo l117 : -3992042384 Missing photo l117 : -3992042356 Missing photo l117 : -3992042387 Missing photo l117 : -3992042405 Missing photo l117 : -3992042408 Missing photo l117 : -3992042402 Missing photo l117 : -3992042414 Missing photo l117 : -3992042393 Missing photo l117 : -3992042416 Missing photo l117 : -3992042428 Missing photo l117 : -3992042430 Missing photo l117 : -3992042435 Missing photo l117 : -3992042442 Missing photo l117 : -3992042298 Missing photo l117 : -3992042336 Missing photo l117 : -3992042339 Missing photo l117 : -3992042335 Missing photo l117 : -3992042377 Missing photo l117 : -3992042380 Missing photo l117 : -3992042383 Missing photo l117 : -3992042385 Missing photo l117 : -3992042368 Missing photo l117 : -3992042381 Missing photo l117 : -3992042370 Missing photo l117 : -3992042371 Missing photo l117 : -3992042355 Missing photo l117 : -3992042350 Missing photo l117 : -3992042375 Missing photo l117 : -3992042429 Missing photo l117 : -3992042437 Missing photo l117 : -3992042424 Missing photo l117 : -3992042427 Missing photo l117 : -3992042431 Missing photo l117 : -3992042432 Missing photo l117 : -3992042434 Missing photo l117 : -3992042471 Missing photo l117 : -3992042456 Missing photo l117 : -3992042477 Missing photo l117 : -3992042493 Missing photo l117 : -3992042473 Missing photo l117 : -3992042364 Missing photo l117 : -3992042382 Missing photo l117 : -3992042367 Missing photo l117 : -3992042305 Missing photo l117 : -3992042306 Missing photo l117 : -3992042299 Missing photo l117 : -3992042378 Missing photo l117 : -3992042359 Missing photo l117 : -3992042415 Missing photo l117 : -3992042400 Missing photo l117 : -3992042398 Missing photo l117 : -3992042412 Missing photo l117 : -3992042444 Missing photo l117 : -3992042423 Missing photo l117 : -3992042443 Missing photo l117 : -3992042466 Missing photo l117 : -3992042460 Missing photo l117 : -3992042464 Missing photo l117 : -3992042352 Missing photo l117 : -3992042373 Missing photo l117 : -3992042365 Missing photo l117 : -3992042362 Missing photo l117 : -3992042351 Missing photo l117 : -3992042360 Missing photo l117 : -3992042397 Missing photo l117 : -3992042410 Missing photo l117 : -3992042394 Missing photo l117 : -3992042399 Missing photo l117 : -3992042411 Missing photo l117 : -3992042406 Missing photo l117 : -3992042404 Missing photo l117 : -3992042409 Missing photo l117 : -3992042447 Missing photo l117 : -3992042292 Missing photo l117 : -3992042294 Missing photo l117 : -3992042287 Missing photo l117 : -3992042342 Missing photo l117 : -3992042321 Missing photo l117 : -3992042337 Missing photo l117 : -3992042322 Missing photo l117 : -3992042319 Missing photo l117 : -3992042343 Missing photo l117 : -3992042333 Missing photo l117 : -3992042331 Missing photo l117 : -3992042372 Missing photo l117 : -3992042361 Missing photo l117 : -3992042396 Missing photo l117 : -3992042391 To insert : -3992042418 Missing photo l134 : -3992042418 To insert : -3992042440 Missing photo l134 : -3992042440 To insert : -3992042458 Missing photo l134 : -3992042458 To insert : -3992042453 Missing photo l134 : -3992042453 To insert : -3992042472 Missing photo l134 : -3992042472 To insert : -3992042454 Missing photo l134 : -3992042454 To insert : -3992042461 Missing photo l134 : -3992042461 To insert : -3992042488 Missing photo l134 : -3992042488 To insert : -3992042441 Missing photo l134 : -3992042441 To insert : -3992042448 Missing photo l134 : -3992042448 To insert : -3992042426 Missing photo l134 : -3992042426 To insert : -3992042436 Missing photo l134 : -3992042436 To insert : -3992042462 Missing photo l134 : -3992042462 To insert : -3992042467 Missing photo l134 : -3992042467 To insert : -3992042468 Missing photo l134 : -3992042468 To insert : -3992042491 Missing photo l134 : -3992042491 To insert : -3992042486 Missing photo l134 : -3992042486 To insert : -3992042492 Missing photo l134 : -3992042492 To insert : -3992042496 Missing photo l134 : -3992042496 To insert : -3992042490 Missing photo l134 : -3992042490 To insert : -3992042484 Missing photo l134 : -3992042484 To insert : -3992042297 Missing photo l134 : -3992042297 To insert : -3992042445 Missing photo l134 : -3992042445 To insert : -3992042354 Missing photo l134 : -3992042354 To insert : -3992042401 Missing photo l134 : -3992042401 To insert : -3992042395 Missing photo l134 : -3992042395 To insert : -3992042403 Missing photo l134 : -3992042403 To insert : -3992042463 Missing photo l134 : -3992042463 To insert : -3992042469 Missing photo l134 : -3992042469 To insert : -3992042465 Missing photo l134 : -3992042465 To insert : -3992042497 Missing photo l134 : -3992042497 To insert : -3992042438 Missing photo l134 : -3992042438 To insert : -3992042308 Missing photo l134 : -3992042308 To insert : -3992042313 Missing photo l134 : -3992042313 To insert : -3992042301 Missing photo l134 : -3992042301 To insert : -3992042296 Missing photo l134 : -3992042296 To insert : -3992042304 Missing photo l134 : -3992042304 To insert : -3992042311 Missing photo l134 : -3992042311 To insert : -3992042470 Missing photo l134 : -3992042470 To insert : -3992042455 Missing photo l134 : -3992042455 To insert : -3992042487 Missing photo l134 : -3992042487 To insert : -3992042483 Missing photo l134 : -3992042483 To insert : -3992042494 Missing photo l134 : -3992042494 To insert : -3992042498 Missing photo l134 : -3992042498 To insert : -3992042314 Missing photo l134 : -3992042314 To insert : -3992042288 Missing photo l134 : -3992042288 To insert : -3992042307 Missing photo l134 : -3992042307 To insert : -3992042295 Missing photo l134 : -3992042295 To insert : -3992042309 Missing photo l134 : -3992042309 To insert : -3992042315 Missing photo l134 : -3992042315 To insert : -3992042312 Missing photo l134 : -3992042312 To insert : -3992042345 Missing photo l134 : -3992042345 To insert : -3992042374 Missing photo l134 : -3992042374 To insert : -3992042376 Missing photo l134 : -3992042376 To insert : -3992042358 Missing photo l134 : -3992042358 To insert : -3992042384 Missing photo l134 : -3992042384 To insert : -3992042356 Missing photo l134 : -3992042356 To insert : -3992042387 Missing photo l134 : -3992042387 To insert : -3992042405 Missing photo l134 : -3992042405 To insert : -3992042408 Missing photo l134 : -3992042408 To insert : -3992042402 Missing photo l134 : -3992042402 To insert : -3992042414 Missing photo l134 : -3992042414 To insert : -3992042393 Missing photo l134 : -3992042393 To insert : -3992042416 Missing photo l134 : -3992042416 To insert : -3992042428 Missing photo l134 : -3992042428 To insert : -3992042430 Missing photo l134 : -3992042430 To insert : -3992042435 Missing photo l134 : -3992042435 To insert : -3992042442 Missing photo l134 : -3992042442 To insert : -3992042298 Missing photo l134 : -3992042298 To insert : -3992042336 Missing photo l134 : -3992042336 To insert : -3992042339 Missing photo l134 : -3992042339 To insert : -3992042335 Missing photo l134 : -3992042335 To insert : -3992042377 Missing photo l134 : -3992042377 To insert : -3992042380 Missing photo l134 : -3992042380 To insert : -3992042383 Missing photo l134 : -3992042383 To insert : -3992042385 Missing photo l134 : -3992042385 To insert : -3992042368 Missing photo l134 : -3992042368 To insert : -3992042381 Missing photo l134 : -3992042381 To insert : -3992042370 Missing photo l134 : -3992042370 To insert : -3992042371 Missing photo l134 : -3992042371 To insert : -3992042355 Missing photo l134 : -3992042355 To insert : -3992042350 Missing photo l134 : -3992042350 To insert : -3992042375 Missing photo l134 : -3992042375 To insert : -3992042429 Missing photo l134 : -3992042429 To insert : -3992042437 Missing photo l134 : -3992042437 To insert : -3992042424 Missing photo l134 : -3992042424 To insert : -3992042427 Missing photo l134 : -3992042427 To insert : -3992042431 Missing photo l134 : -3992042431 To insert : -3992042432 Missing photo l134 : -3992042432 To insert : -3992042434 Missing photo l134 : -3992042434 To insert : -3992042471 Missing photo l134 : -3992042471 To insert : -3992042456 Missing photo l134 : -3992042456 To insert : -3992042477 Missing photo l134 : -3992042477 To insert : -3992042493 Missing photo l134 : -3992042493 To insert : -3992042473 Missing photo l134 : -3992042473 To insert : -3992042364 Missing photo l134 : -3992042364 To insert : -3992042382 Missing photo l134 : -3992042382 To insert : -3992042367 Missing photo l134 : -3992042367 To insert : -3992042305 Missing photo l134 : -3992042305 To insert : -3992042306 Missing photo l134 : -3992042306 To insert : -3992042299 Missing photo l134 : -3992042299 To insert : -3992042378 Missing photo l134 : -3992042378 To insert : -3992042359 Missing photo l134 : -3992042359 To insert : -3992042415 Missing photo l134 : -3992042415 To insert : -3992042400 Missing photo l134 : -3992042400 To insert : -3992042398 Missing photo l134 : -3992042398 To insert : -3992042412 Missing photo l134 : -3992042412 To insert : -3992042444 Missing photo l134 : -3992042444 To insert : -3992042423 Missing photo l134 : -3992042423 To insert : -3992042443 Missing photo l134 : -3992042443 To insert : -3992042466 Missing photo l134 : -3992042466 To insert : -3992042460 Missing photo l134 : -3992042460 To insert : -3992042464 Missing photo l134 : -3992042464 To insert : -3992042352 Missing photo l134 : -3992042352 To insert : -3992042373 Missing photo l134 : -3992042373 To insert : -3992042365 Missing photo l134 : -3992042365 To insert : -3992042362 Missing photo l134 : -3992042362 To insert : -3992042351 Missing photo l134 : -3992042351 To insert : -3992042360 Missing photo l134 : -3992042360 To insert : -3992042397 Missing photo l134 : -3992042397 To insert : -3992042410 Missing photo l134 : -3992042410 To insert : -3992042394 Missing photo l134 : -3992042394 To insert : -3992042399 Missing photo l134 : -3992042399 To insert : -3992042411 Missing photo l134 : -3992042411 To insert : -3992042406 Missing photo l134 : -3992042406 To insert : -3992042404 Missing photo l134 : -3992042404 To insert : -3992042409 Missing photo l134 : -3992042409 To insert : -3992042447 Missing photo l134 : -3992042447 To insert : -3992042292 Missing photo l134 : -3992042292 To insert : -3992042294 Missing photo l134 : -3992042294 To insert : -3992042287 Missing photo l134 : -3992042287 To insert : -3992042342 Missing photo l134 : -3992042342 To insert : -3992042321 Missing photo l134 : -3992042321 To insert : -3992042337 Missing photo l134 : -3992042337 To insert : -3992042322 Missing photo l134 : -3992042322 To insert : -3992042319 Missing photo l134 : -3992042319 To insert : -3992042343 Missing photo l134 : -3992042343 To insert : -3992042333 Missing photo l134 : -3992042333 To insert : -3992042331 Missing photo l134 : -3992042331 To insert : -3992042372 Missing photo l134 : -3992042372 To insert : -3992042361 Missing photo l134 : -3992042361 To insert : -3992042396 Missing photo l134 : -3992042396 To insert : -3992042391 Missing photo l134 : -3992042391 time to insert the descriptors : 33.292322874069214 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 : 0 time used for this insertion : 4.291534423828125e-06 save missing photos in datou_result : time spend for datou_step_exec : 39.84542965888977 time spend to save output : 0.21248126029968262 total time spend for step 5 : 40.05791091918945 step6:merge_mask_thcl_custom Fri Oct 10 10:22:28 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 ! 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 VR 22-3-18 : For now we do not clean correctly the datou structure Begin step merge_mask_thcl_custom batch 1 Loaded 213 chid ids of type : 3760 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++As expected we have just one thcl present End of step merge_mask_thcl_custom Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : merge_mask_thcl_custom we use saveGeneral [1388607356, 1388607351, 1388607327, 1388607326, 1388607251, 1388607246, 1388607225] Looping around the photos to save general results len do output : 7 /1388607356Didn't retrieve data .Didn't retrieve data . /1388607351Didn't retrieve data .Didn't retrieve data . /1388607327Didn't retrieve data .Didn't retrieve data . /1388607326Didn't retrieve data .Didn't retrieve data . /1388607251Didn't retrieve data .Didn't retrieve data . /1388607246Didn't retrieve data .Didn't retrieve data . /1388607225Didn'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 : Managing all output in save final without adding information in the mtr_datou_result ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607356', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607351', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607327', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607326', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607251', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607246', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607225', None, None, None, None, None, '3919092') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 21 time used for this insertion : 0.03614187240600586 save_final save missing photos in datou_result : time spend for datou_step_exec : 0.16241979598999023 time spend to save output : 0.03656458854675293 total time spend for step 6 : 0.19898438453674316 step7:rle_unique_nms_with_priority Fri Oct 10 10:22:28 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 nb_obj : 21 nb_hashtags : 9 time to prepare the origin masks : 12.594082117080688 time for calcul the mask position with numpy : 0.7227168083190918 nb_pixel_total : 7047119 time to create 1 rle with new method : 0.809171199798584 time for calcul the mask position with numpy : 0.02677607536315918 nb_pixel_total : 5982 time to create 1 rle with old method : 0.0069620609283447266 time for calcul the mask position with numpy : 0.024268150329589844 nb_pixel_total : 29343 time to create 1 rle with old method : 0.033846139907836914 time for calcul the mask position with numpy : 0.025746822357177734 nb_pixel_total : 271858 time to create 1 rle with new method : 0.6521153450012207 time for calcul the mask position with numpy : 0.024143218994140625 nb_pixel_total : 65761 time to create 1 rle with old method : 0.07377815246582031 time for calcul the mask position with numpy : 0.0241549015045166 nb_pixel_total : 41976 time to create 1 rle with old method : 0.0464777946472168 time for calcul the mask position with numpy : 0.025174856185913086 nb_pixel_total : 16377 time to create 1 rle with old method : 0.018291950225830078 time for calcul the mask position with numpy : 0.024160385131835938 nb_pixel_total : 42476 time to create 1 rle with old method : 0.046982765197753906 time for calcul the mask position with numpy : 0.024822711944580078 nb_pixel_total : 28281 time to create 1 rle with old method : 0.030595779418945312 time for calcul the mask position with numpy : 0.02390885353088379 nb_pixel_total : 12754 time to create 1 rle with old method : 0.014171123504638672 time for calcul the mask position with numpy : 0.024394750595092773 nb_pixel_total : 62327 time to create 1 rle with old method : 0.06600356101989746 time for calcul the mask position with numpy : 0.024024248123168945 nb_pixel_total : 29153 time to create 1 rle with old method : 0.031411170959472656 time for calcul the mask position with numpy : 0.02394866943359375 nb_pixel_total : 23758 time to create 1 rle with old method : 0.02540278434753418 time for calcul the mask position with numpy : 0.024124860763549805 nb_pixel_total : 23854 time to create 1 rle with old method : 0.025447607040405273 time for calcul the mask position with numpy : 0.02506566047668457 nb_pixel_total : 50509 time to create 1 rle with old method : 0.05396437644958496 time for calcul the mask position with numpy : 0.024573802947998047 nb_pixel_total : 50958 time to create 1 rle with old method : 0.07825374603271484 time for calcul the mask position with numpy : 0.027768611907958984 nb_pixel_total : 130961 time to create 1 rle with old method : 0.14176106452941895 time for calcul the mask position with numpy : 0.025481700897216797 nb_pixel_total : 70229 time to create 1 rle with old method : 0.0773923397064209 time for calcul the mask position with numpy : 0.025140047073364258 nb_pixel_total : 109628 time to create 1 rle with old method : 0.11724734306335449 time for calcul the mask position with numpy : 0.023474931716918945 nb_pixel_total : 36008 time to create 1 rle with old method : 0.03865838050842285 time for calcul the mask position with numpy : 0.025092601776123047 nb_pixel_total : 57628 time to create 1 rle with old method : 0.062168121337890625 time for calcul the mask position with numpy : 0.026102781295776367 nb_pixel_total : 87460 time to create 1 rle with old method : 0.10025858879089355 create new chi : 3.8704965114593506 time to delete rle : 0.2247755527496338 batch 1 Loaded 22 chid ids of type : 4211 Number RLEs to save : 16097 TO DO : save crop sub photo not yet done ! save time : 1.6602911949157715 nb_obj : 12 nb_hashtags : 6 time to prepare the origin masks : 6.637617588043213 time for calcul the mask position with numpy : 0.32897472381591797 nb_pixel_total : 7155164 time to create 1 rle with new method : 0.66485595703125 time for calcul the mask position with numpy : 0.025884151458740234 nb_pixel_total : 141089 time to create 1 rle with old method : 0.15721654891967773 time for calcul the mask position with numpy : 0.02520132064819336 nb_pixel_total : 57292 time to create 1 rle with old method : 0.06290912628173828 time for calcul the mask position with numpy : 0.025243759155273438 nb_pixel_total : 61750 time to create 1 rle with old method : 0.06973409652709961 time for calcul the mask position with numpy : 0.02452230453491211 nb_pixel_total : 65149 time to create 1 rle with old method : 0.06992220878601074 time for calcul the mask position with numpy : 0.02467823028564453 nb_pixel_total : 151912 time to create 1 rle with new method : 0.4812917709350586 time for calcul the mask position with numpy : 0.02323627471923828 nb_pixel_total : 34828 time to create 1 rle with old method : 0.03709149360656738 time for calcul the mask position with numpy : 0.024265527725219727 nb_pixel_total : 49105 time to create 1 rle with old method : 0.05254387855529785 time for calcul the mask position with numpy : 0.025177478790283203 nb_pixel_total : 82652 time to create 1 rle with old method : 0.08897995948791504 time for calcul the mask position with numpy : 0.023746728897094727 nb_pixel_total : 77937 time to create 1 rle with old method : 0.08683085441589355 time for calcul the mask position with numpy : 0.024526596069335938 nb_pixel_total : 89271 time to create 1 rle with old method : 0.09653258323669434 time for calcul the mask position with numpy : 0.024507761001586914 nb_pixel_total : 109895 time to create 1 rle with old method : 0.11961984634399414 time for calcul the mask position with numpy : 0.02526998519897461 nb_pixel_total : 218356 time to create 1 rle with new method : 0.21464133262634277 create new chi : 2.914015293121338 time to delete rle : 0.0010035037994384766 batch 1 Loaded 13 chid ids of type : 4211 Number RLEs to save : 11424 TO DO : save crop sub photo not yet done ! save time : 1.1901791095733643 nb_obj : 30 nb_hashtags : 9 time to prepare the origin masks : 12.854210376739502 time for calcul the mask position with numpy : 0.09706449508666992 nb_pixel_total : 7085047 time to create 1 rle with new method : 0.17274832725524902 time for calcul the mask position with numpy : 0.033856868743896484 nb_pixel_total : 79588 time to create 1 rle with old method : 0.08631277084350586 time for calcul the mask position with numpy : 0.03332662582397461 nb_pixel_total : 16719 time to create 1 rle with old method : 0.01849532127380371 time for calcul the mask position with numpy : 0.032926082611083984 nb_pixel_total : 35716 time to create 1 rle with old method : 0.0385134220123291 time for calcul the mask position with numpy : 0.033928871154785156 nb_pixel_total : 60176 time to create 1 rle with old method : 0.06446051597595215 time for calcul the mask position with numpy : 0.03249382972717285 nb_pixel_total : 8497 time to create 1 rle with old method : 0.00957798957824707 time for calcul the mask position with numpy : 0.033217430114746094 nb_pixel_total : 59371 time to create 1 rle with old method : 0.06338143348693848 time for calcul the mask position with numpy : 0.03262066841125488 nb_pixel_total : 23322 time to create 1 rle with old method : 0.024602651596069336 time for calcul the mask position with numpy : 0.0338587760925293 nb_pixel_total : 8878 time to create 1 rle with old method : 0.009857892990112305 time for calcul the mask position with numpy : 0.03354692459106445 nb_pixel_total : 40115 time to create 1 rle with old method : 0.04469776153564453 time for calcul the mask position with numpy : 0.03425455093383789 nb_pixel_total : 15385 time to create 1 rle with old method : 0.017456531524658203 time for calcul the mask position with numpy : 0.03451943397521973 nb_pixel_total : 40158 time to create 1 rle with old method : 0.04613304138183594 time for calcul the mask position with numpy : 0.035860538482666016 nb_pixel_total : 53873 time to create 1 rle with old method : 0.05910921096801758 time for calcul the mask position with numpy : 0.03352761268615723 nb_pixel_total : 36751 time to create 1 rle with old method : 0.03990626335144043 time for calcul the mask position with numpy : 0.032756805419921875 nb_pixel_total : 50324 time to create 1 rle with old method : 0.05404043197631836 time for calcul the mask position with numpy : 0.03219246864318848 nb_pixel_total : 10672 time to create 1 rle with old method : 0.011813163757324219 time for calcul the mask position with numpy : 0.03422665596008301 nb_pixel_total : 119864 time to create 1 rle with old method : 0.14041662216186523 time for calcul the mask position with numpy : 0.033290863037109375 nb_pixel_total : 21964 time to create 1 rle with old method : 0.024075984954833984 time for calcul the mask position with numpy : 0.03272581100463867 nb_pixel_total : 42915 time to create 1 rle with old method : 0.04587960243225098 time for calcul the mask position with numpy : 0.03281545639038086 nb_pixel_total : 55763 time to create 1 rle with old method : 0.06018948554992676 time for calcul the mask position with numpy : 0.033616065979003906 nb_pixel_total : 57206 time to create 1 rle with old method : 0.06385612487792969 time for calcul the mask position with numpy : 0.032091617584228516 nb_pixel_total : 48045 time to create 1 rle with old method : 0.0516660213470459 time for calcul the mask position with numpy : 0.03284811973571777 nb_pixel_total : 8763 time to create 1 rle with old method : 0.011816263198852539 time for calcul the mask position with numpy : 0.03316307067871094 nb_pixel_total : 32816 time to create 1 rle with old method : 0.035300493240356445 time for calcul the mask position with numpy : 0.032990455627441406 nb_pixel_total : 76526 time to create 1 rle with old method : 0.08282089233398438 time for calcul the mask position with numpy : 0.03279566764831543 nb_pixel_total : 106374 time to create 1 rle with old method : 0.11339235305786133 time for calcul the mask position with numpy : 0.03293752670288086 nb_pixel_total : 32622 time to create 1 rle with old method : 0.03507399559020996 time for calcul the mask position with numpy : 0.03265690803527832 nb_pixel_total : 8660 time to create 1 rle with old method : 0.009817361831665039 time for calcul the mask position with numpy : 0.03383040428161621 nb_pixel_total : 30064 time to create 1 rle with old method : 0.03262066841125488 time for calcul the mask position with numpy : 0.03293442726135254 nb_pixel_total : 17647 time to create 1 rle with old method : 0.019499778747558594 time for calcul the mask position with numpy : 0.03989410400390625 nb_pixel_total : 10579 time to create 1 rle with old method : 0.01123046875 create new chi : 2.619570255279541 time to delete rle : 0.002549886703491211 batch 1 Loaded 31 chid ids of type : 4211 Number RLEs to save : 17548 TO DO : save crop sub photo not yet done ! save time : 1.7601094245910645 nb_obj : 24 nb_hashtags : 7 time to prepare the origin masks : 12.695367336273193 time for calcul the mask position with numpy : 0.6952917575836182 nb_pixel_total : 7129338 time to create 1 rle with new method : 0.5937693119049072 time for calcul the mask position with numpy : 0.026909828186035156 nb_pixel_total : 83223 time to create 1 rle with old method : 0.09772396087646484 time for calcul the mask position with numpy : 0.02552056312561035 nb_pixel_total : 15665 time to create 1 rle with old method : 0.01929759979248047 time for calcul the mask position with numpy : 0.02990269660949707 nb_pixel_total : 17626 time to create 1 rle with old method : 0.029490947723388672 time for calcul the mask position with numpy : 0.0276181697845459 nb_pixel_total : 24987 time to create 1 rle with old method : 0.035198211669921875 time for calcul the mask position with numpy : 0.02936410903930664 nb_pixel_total : 44012 time to create 1 rle with old method : 0.05093193054199219 time for calcul the mask position with numpy : 0.02351093292236328 nb_pixel_total : 20658 time to create 1 rle with old method : 0.022928953170776367 time for calcul the mask position with numpy : 0.024913311004638672 nb_pixel_total : 14814 time to create 1 rle with old method : 0.025065183639526367 time for calcul the mask position with numpy : 0.02695631980895996 nb_pixel_total : 22886 time to create 1 rle with old method : 0.0339047908782959 time for calcul the mask position with numpy : 0.02671051025390625 nb_pixel_total : 8003 time to create 1 rle with old method : 0.009154319763183594 time for calcul the mask position with numpy : 0.024724960327148438 nb_pixel_total : 15562 time to create 1 rle with old method : 0.017343997955322266 time for calcul the mask position with numpy : 0.024735450744628906 nb_pixel_total : 59466 time to create 1 rle with old method : 0.0653986930847168 time for calcul the mask position with numpy : 0.025283336639404297 nb_pixel_total : 24185 time to create 1 rle with old method : 0.02608203887939453 time for calcul the mask position with numpy : 0.02541637420654297 nb_pixel_total : 48545 time to create 1 rle with old method : 0.05397391319274902 time for calcul the mask position with numpy : 0.025641441345214844 nb_pixel_total : 24061 time to create 1 rle with old method : 0.02622818946838379 time for calcul the mask position with numpy : 0.024968862533569336 nb_pixel_total : 19020 time to create 1 rle with old method : 0.020531892776489258 time for calcul the mask position with numpy : 0.024989604949951172 nb_pixel_total : 64901 time to create 1 rle with old method : 0.07587981224060059 time for calcul the mask position with numpy : 0.02768087387084961 nb_pixel_total : 9309 time to create 1 rle with old method : 0.015315055847167969 time for calcul the mask position with numpy : 0.029440641403198242 nb_pixel_total : 273457 time to create 1 rle with new method : 0.5057878494262695 time for calcul the mask position with numpy : 0.024159669876098633 nb_pixel_total : 25331 time to create 1 rle with old method : 0.027619361877441406 time for calcul the mask position with numpy : 0.02546977996826172 nb_pixel_total : 35441 time to create 1 rle with old method : 0.039765119552612305 time for calcul the mask position with numpy : 0.02682185173034668 nb_pixel_total : 6940 time to create 1 rle with old method : 0.007663249969482422 time for calcul the mask position with numpy : 0.02653670310974121 nb_pixel_total : 192718 time to create 1 rle with new method : 0.5662875175476074 time for calcul the mask position with numpy : 0.027933359146118164 nb_pixel_total : 43543 time to create 1 rle with old method : 0.052196502685546875 time for calcul the mask position with numpy : 0.02557229995727539 nb_pixel_total : 70709 time to create 1 rle with old method : 0.07636499404907227 create new chi : 3.9084324836730957 time to delete rle : 0.0014069080352783203 batch 1 Loaded 25 chid ids of type : 4211 Number RLEs to save : 14259 TO DO : save crop sub photo not yet done ! save time : 1.4572837352752686 nb_obj : 23 nb_hashtags : 8 time to prepare the origin masks : 11.55228328704834 time for calcul the mask position with numpy : 0.4015212059020996 nb_pixel_total : 7102664 time to create 1 rle with new method : 0.7283966541290283 time for calcul the mask position with numpy : 0.024335145950317383 nb_pixel_total : 69387 time to create 1 rle with old method : 0.07401275634765625 time for calcul the mask position with numpy : 0.023676633834838867 nb_pixel_total : 10765 time to create 1 rle with old method : 0.011797666549682617 time for calcul the mask position with numpy : 0.022938013076782227 nb_pixel_total : 22292 time to create 1 rle with old method : 0.023336410522460938 time for calcul the mask position with numpy : 0.024085044860839844 nb_pixel_total : 26167 time to create 1 rle with old method : 0.028734207153320312 time for calcul the mask position with numpy : 0.026669979095458984 nb_pixel_total : 66566 time to create 1 rle with old method : 0.07247519493103027 time for calcul the mask position with numpy : 0.04395556449890137 nb_pixel_total : 362382 time to create 1 rle with new method : 0.6472971439361572 time for calcul the mask position with numpy : 0.039076805114746094 nb_pixel_total : 16328 time to create 1 rle with old method : 0.017489910125732422 time for calcul the mask position with numpy : 0.041547298431396484 nb_pixel_total : 39198 time to create 1 rle with old method : 0.043431997299194336 time for calcul the mask position with numpy : 0.04174494743347168 nb_pixel_total : 54990 time to create 1 rle with old method : 0.058866024017333984 time for calcul the mask position with numpy : 0.03924703598022461 nb_pixel_total : 101133 time to create 1 rle with old method : 0.10661101341247559 time for calcul the mask position with numpy : 0.03958773612976074 nb_pixel_total : 87913 time to create 1 rle with old method : 0.09601354598999023 time for calcul the mask position with numpy : 0.04351806640625 nb_pixel_total : 28853 time to create 1 rle with old method : 0.031058073043823242 time for calcul the mask position with numpy : 0.0398406982421875 nb_pixel_total : 11723 time to create 1 rle with old method : 0.012682437896728516 time for calcul the mask position with numpy : 0.03979921340942383 nb_pixel_total : 9997 time to create 1 rle with old method : 0.010941505432128906 time for calcul the mask position with numpy : 0.03847479820251465 nb_pixel_total : 34702 time to create 1 rle with old method : 0.03790545463562012 time for calcul the mask position with numpy : 0.04072093963623047 nb_pixel_total : 70605 time to create 1 rle with old method : 0.08092117309570312 time for calcul the mask position with numpy : 0.038895606994628906 nb_pixel_total : 13651 time to create 1 rle with old method : 0.016495227813720703 time for calcul the mask position with numpy : 0.0395050048828125 nb_pixel_total : 33338 time to create 1 rle with old method : 0.03551626205444336 time for calcul the mask position with numpy : 0.03854656219482422 nb_pixel_total : 18068 time to create 1 rle with old method : 0.01978325843811035 time for calcul the mask position with numpy : 0.03701615333557129 nb_pixel_total : 33872 time to create 1 rle with old method : 0.03520965576171875 time for calcul the mask position with numpy : 0.03170657157897949 nb_pixel_total : 40487 time to create 1 rle with old method : 0.04300427436828613 time for calcul the mask position with numpy : 0.02542257308959961 nb_pixel_total : 4236 time to create 1 rle with old method : 0.004834175109863281 time for calcul the mask position with numpy : 0.02449941635131836 nb_pixel_total : 35083 time to create 1 rle with old method : 0.03881406784057617 create new chi : 3.5493967533111572 time to delete rle : 0.0020203590393066406 batch 1 Loaded 24 chid ids of type : 4211 Number RLEs to save : 13808 TO DO : save crop sub photo not yet done ! save time : 1.4019980430603027 nb_obj : 18 nb_hashtags : 6 time to prepare the origin masks : 9.784599304199219 time for calcul the mask position with numpy : 0.5341110229492188 nb_pixel_total : 7431980 time to create 1 rle with new method : 0.5916337966918945 time for calcul the mask position with numpy : 0.0242002010345459 nb_pixel_total : 14576 time to create 1 rle with old method : 0.016666173934936523 time for calcul the mask position with numpy : 0.025207042694091797 nb_pixel_total : 32666 time to create 1 rle with old method : 0.03726482391357422 time for calcul the mask position with numpy : 0.024228334426879883 nb_pixel_total : 27808 time to create 1 rle with old method : 0.03144431114196777 time for calcul the mask position with numpy : 0.024344682693481445 nb_pixel_total : 17458 time to create 1 rle with old method : 0.01996445655822754 time for calcul the mask position with numpy : 0.024523019790649414 nb_pixel_total : 43090 time to create 1 rle with old method : 0.05272698402404785 time for calcul the mask position with numpy : 0.026534318923950195 nb_pixel_total : 101065 time to create 1 rle with old method : 0.12772822380065918 time for calcul the mask position with numpy : 0.02448415756225586 nb_pixel_total : 27887 time to create 1 rle with old method : 0.031438589096069336 time for calcul the mask position with numpy : 0.024483203887939453 nb_pixel_total : 6725 time to create 1 rle with old method : 0.007704257965087891 time for calcul the mask position with numpy : 0.024832963943481445 nb_pixel_total : 50069 time to create 1 rle with old method : 0.056491851806640625 time for calcul the mask position with numpy : 0.024636507034301758 nb_pixel_total : 17693 time to create 1 rle with old method : 0.020341157913208008 time for calcul the mask position with numpy : 0.024912118911743164 nb_pixel_total : 92106 time to create 1 rle with old method : 0.1278839111328125 time for calcul the mask position with numpy : 0.032503604888916016 nb_pixel_total : 19669 time to create 1 rle with old method : 0.02334904670715332 time for calcul the mask position with numpy : 0.031699180603027344 nb_pixel_total : 26391 time to create 1 rle with old method : 0.03265380859375 time for calcul the mask position with numpy : 0.03341794013977051 nb_pixel_total : 44494 time to create 1 rle with old method : 0.05468630790710449 time for calcul the mask position with numpy : 0.025873184204101562 nb_pixel_total : 42824 time to create 1 rle with old method : 0.05355978012084961 time for calcul the mask position with numpy : 0.027688026428222656 nb_pixel_total : 76322 time to create 1 rle with old method : 0.11022520065307617 time for calcul the mask position with numpy : 0.03097701072692871 nb_pixel_total : 133864 time to create 1 rle with old method : 0.1521306037902832 time for calcul the mask position with numpy : 0.03676342964172363 nb_pixel_total : 87713 time to create 1 rle with old method : 0.10087275505065918 create new chi : 2.718015193939209 time to delete rle : 0.0011889934539794922 batch 1 Loaded 19 chid ids of type : 4211 Number RLEs to save : 11539 TO DO : save crop sub photo not yet done ! save time : 1.2347421646118164 nb_obj : 15 nb_hashtags : 7 time to prepare the origin masks : 7.022068500518799 time for calcul the mask position with numpy : 0.6446712017059326 nb_pixel_total : 7730141 time to create 1 rle with new method : 0.768467903137207 time for calcul the mask position with numpy : 0.0251162052154541 nb_pixel_total : 56116 time to create 1 rle with old method : 0.06301450729370117 time for calcul the mask position with numpy : 0.026090383529663086 nb_pixel_total : 9089 time to create 1 rle with old method : 0.015264272689819336 time for calcul the mask position with numpy : 0.031674861907958984 nb_pixel_total : 35854 time to create 1 rle with old method : 0.053542137145996094 time for calcul the mask position with numpy : 0.0257720947265625 nb_pixel_total : 23744 time to create 1 rle with old method : 0.027072429656982422 time for calcul the mask position with numpy : 0.02490377426147461 nb_pixel_total : 22111 time to create 1 rle with old method : 0.024939298629760742 time for calcul the mask position with numpy : 0.025493383407592773 nb_pixel_total : 25968 time to create 1 rle with old method : 0.02920818328857422 time for calcul the mask position with numpy : 0.026823997497558594 nb_pixel_total : 18005 time to create 1 rle with old method : 0.0203402042388916 time for calcul the mask position with numpy : 0.02569413185119629 nb_pixel_total : 32826 time to create 1 rle with old method : 0.04259634017944336 time for calcul the mask position with numpy : 0.03222823143005371 nb_pixel_total : 15187 time to create 1 rle with old method : 0.0172882080078125 time for calcul the mask position with numpy : 0.04234051704406738 nb_pixel_total : 87236 time to create 1 rle with old method : 0.09786295890808105 time for calcul the mask position with numpy : 0.041434288024902344 nb_pixel_total : 25843 time to create 1 rle with old method : 0.028438806533813477 time for calcul the mask position with numpy : 0.039330244064331055 nb_pixel_total : 26172 time to create 1 rle with old method : 0.029143571853637695 time for calcul the mask position with numpy : 0.04085540771484375 nb_pixel_total : 97193 time to create 1 rle with old method : 0.13636493682861328 time for calcul the mask position with numpy : 0.042623043060302734 nb_pixel_total : 6361 time to create 1 rle with old method : 0.007280826568603516 time for calcul the mask position with numpy : 0.041028499603271484 nb_pixel_total : 82554 time to create 1 rle with old method : 0.09170126914978027 create new chi : 2.6347134113311768 time to delete rle : 0.0009632110595703125 batch 1 Loaded 16 chid ids of type : 4211 Number RLEs to save : 9386 TO DO : save crop sub photo not yet done ! save time : 1.011688232421875 map_output_result : {1388607356: (0.0, 'Should be the crop_list due to order', 0.0), 1388607351: (0.0, 'Should be the crop_list due to order', 0.0), 1388607327: (0.0, 'Should be the crop_list due to order', 0.0), 1388607326: (0.0, 'Should be the crop_list due to order', 0.0), 1388607251: (0.0, 'Should be the crop_list due to order', 0.0), 1388607246: (0.0, 'Should be the crop_list due to order', 0.0), 1388607225: (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 [1388607356, 1388607351, 1388607327, 1388607326, 1388607251, 1388607246, 1388607225] Looping around the photos to save general results len do output : 7 /1388607356.Didn't retrieve data . /1388607351.Didn't retrieve data . /1388607327.Didn't retrieve data . /1388607326.Didn't retrieve data . /1388607251.Didn't retrieve data . /1388607246.Didn't retrieve data . /1388607225.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 ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607356', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607351', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607327', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607326', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607251', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607246', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607225', None, None, None, None, None, '3919092') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 21 time used for this insertion : 0.036431074142456055 save_final save missing photos in datou_result : time spend for datou_step_exec : 106.02637577056885 time spend to save output : 0.03696298599243164 total time spend for step 7 : 106.06333875656128 step8:crop_condition Fri Oct 10 10:24:14 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 : 4211 Loading chi in step crop for list_pids : 7 ! batch 1 Loaded 150 chid ids of type : 4211 begin to crop the class : barquette_opaque param for this class : {'min_score': 0.5} filtre for class : barquette_opaque hashtag_id of this class : 2107760128 Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! 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 : 21 About to insert : list_path_to_insert length 21 new photo from crops ! About to upload 21 photos upload in portfolio : 4869462 init cache_photo without model_param we have 21 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1760084662_41623 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(1760084668), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607356_4feae2b60c73201395be33b5d77ceb70_rle_crop_3992051279_0.png', 0, 317, 646, 0, 1760084668,'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(1760084668), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607356_4feae2b60c73201395be33b5d77ceb70_rle_crop_3992051281_0.png', 0, 233, 334, 0, 1760084668,'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(1760084668), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607327_81e3a5b54698baa1fa09c64e3943f087_rle_crop_3992051321_0.png', 0, 272, 340, 0, 1760084668,'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(1760084668), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607327_81e3a5b54698baa1fa09c64e3943f087_rle_crop_3992051313_0.png', 0, 318, 254, 0, 1760084668,'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(1760084668), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607327_81e3a5b54698baa1fa09c64e3943f087_rle_crop_3992051307_0.png', 0, 382, 252, 0, 1760084668,'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(1760084668), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607327_81e3a5b54698baa1fa09c64e3943f087_rle_crop_3992051320_0.png', 0, 268, 271, 0, 1760084668,'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(1760084668), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607327_81e3a5b54698baa1fa09c64e3943f087_rle_crop_3992051304_0.png', 0, 192, 248, 0, 1760084668,'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(1760084668), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607327_81e3a5b54698baa1fa09c64e3943f087_rle_crop_3992051327_0.png', 0, 154, 284, 0, 1760084668,'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(1760084668), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607326_cb58e932fe5ab1e4b6b948f344f19e54_rle_crop_3992051451_0.png', 0, 291, 291, 0, 1760084668,'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(1760084668), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607326_cb58e932fe5ab1e4b6b948f344f19e54_rle_crop_3992051449_0.png', 0, 245, 147, 0, 1760084668,'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(1760084668), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607326_cb58e932fe5ab1e4b6b948f344f19e54_rle_crop_3992051455_0.png', 0, 275, 219, 0, 1760084668,'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(1760084668), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607326_cb58e932fe5ab1e4b6b948f344f19e54_rle_crop_3992051458_0.png', 0, 306, 268, 0, 1760084668,'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(1760084668), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607326_cb58e932fe5ab1e4b6b948f344f19e54_rle_crop_3992051459_0.png', 0, 292, 326, 0, 1760084668,'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(1760084668), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607326_cb58e932fe5ab1e4b6b948f344f19e54_rle_crop_3992051457_0.png', 0, 490, 522, 0, 1760084668,'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(1760084668), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607251_da512109120c62ac38c1cec9a8b11cb3_rle_crop_3992051732_0.png', 0, 219, 238, 0, 1760084668,'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(1760084668), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607251_da512109120c62ac38c1cec9a8b11cb3_rle_crop_3992051735_0.png', 0, 255, 224, 0, 1760084668,'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(1760084668), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607251_da512109120c62ac38c1cec9a8b11cb3_rle_crop_3992051734_0.png', 0, 222, 206, 0, 1760084668,'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(1760084668), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607246_be2901cfcffb60c56b57173d1bc0ffbc_rle_crop_3992051861_0.png', 0, 464, 378, 0, 1760084668,'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(1760084668), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607246_be2901cfcffb60c56b57173d1bc0ffbc_rle_crop_3992051859_0.png', 0, 249, 223, 0, 1760084668,'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(1760084668), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607246_be2901cfcffb60c56b57173d1bc0ffbc_rle_crop_3992051862_0.png', 0, 310, 341, 0, 1760084668,'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(1760084668), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607225_cf7e67936e9b6aeaaa95efd95c23d1df_rle_crop_3992051931_0.png', 0, 132, 177, 0, 1760084668,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 21 photos in the portfolio 4869462 time of upload the photos Elapsed time : 8.404117584228516 we have finished the crop for the class : barquette_opaque begin to crop the class : carton param for this class : {'min_score': 0.5} filtre for class : carton hashtag_id of this class : 492774966 Next one ! Next one ! Next one ! Next one ! map_result returned by crop_photo_return_map_crop : length : 4 About to insert : list_path_to_insert length 4 new photo from crops ! About to upload 4 photos upload in portfolio : 4869462 init cache_photo without model_param we have 4 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1760084672_41623 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(1760084673), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607356_4feae2b60c73201395be33b5d77ceb70_rle_crop_3992051277_0.png', 0, 534, 582, 0, 1760084673,'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(1760084673), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607356_4feae2b60c73201395be33b5d77ceb70_rle_crop_3992051274_0.png', 0, 153, 244, 0, 1760084673,'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(1760084673), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607356_4feae2b60c73201395be33b5d77ceb70_rle_crop_3992051269_0.png', 0, 239, 188, 0, 1760084673,'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(1760084673), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607246_be2901cfcffb60c56b57173d1bc0ffbc_rle_crop_3992051855_0.png', 0, 523, 229, 0, 1760084673,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 4 photos in the portfolio 4869462 time of upload the photos Elapsed time : 1.6239848136901855 we have finished the crop for the class : carton begin to crop the class : ela param for this class : {'min_score': 0.5} filtre for class : ela hashtag_id of this class : 492741797 begin to crop the class : environnement param for this class : {'min_score': 0.5} filtre for class : environnement hashtag_id of this class : 493012381 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 : 9 About to insert : list_path_to_insert length 9 new photo from crops ! About to upload 9 photos upload in portfolio : 4869462 init cache_photo without model_param we have 9 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1760084676_41623 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(1760084678), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607356_4feae2b60c73201395be33b5d77ceb70_rle_crop_3992051282_0.png', 0, 286, 403, 0, 1760084678,'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(1760084678), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607327_81e3a5b54698baa1fa09c64e3943f087_rle_crop_3992051328_0.png', 0, 137, 87, 0, 1760084678,'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(1760084678), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607326_cb58e932fe5ab1e4b6b948f344f19e54_rle_crop_3992051454_0.png', 0, 147, 261, 0, 1760084678,'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(1760084678), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607251_da512109120c62ac38c1cec9a8b11cb3_rle_crop_3992051729_0.png', 0, 258, 176, 0, 1760084678,'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(1760084678), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607251_da512109120c62ac38c1cec9a8b11cb3_rle_crop_3992051726_0.png', 0, 256, 143, 0, 1760084678,'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(1760084678), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607251_da512109120c62ac38c1cec9a8b11cb3_rle_crop_3992051728_0.png', 0, 182, 80, 0, 1760084678,'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(1760084678), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607251_da512109120c62ac38c1cec9a8b11cb3_rle_crop_3992051736_0.png', 0, 147, 35, 0, 1760084678,'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(1760084678), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607246_be2901cfcffb60c56b57173d1bc0ffbc_rle_crop_3992051858_0.png', 0, 243, 251, 0, 1760084678,'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(1760084678), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607225_cf7e67936e9b6aeaaa95efd95c23d1df_rle_crop_3992051930_0.png', 0, 191, 198, 0, 1760084678,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 9 photos in the portfolio 4869462 time of upload the photos Elapsed time : 2.953199863433838 we have finished the crop for the class : environnement begin to crop the class : etiquette param for this class : {'min_score': 0.5} filtre for class : etiquette hashtag_id of this class : 492636447 Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! map_result returned by crop_photo_return_map_crop : length : 7 About to insert : list_path_to_insert length 7 new photo from crops ! About to upload 7 photos upload in portfolio : 4869462 init cache_photo without model_param we have 7 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1760084681_41623 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(1760084682), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607356_4feae2b60c73201395be33b5d77ceb70_rle_crop_3992051273_0.png', 0, 177, 179, 0, 1760084682,'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(1760084682), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607327_81e3a5b54698baa1fa09c64e3943f087_rle_crop_3992051323_0.png', 0, 139, 113, 0, 1760084682,'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(1760084682), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607327_81e3a5b54698baa1fa09c64e3943f087_rle_crop_3992051331_0.png', 0, 144, 113, 0, 1760084682,'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(1760084682), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607251_da512109120c62ac38c1cec9a8b11cb3_rle_crop_3992051733_0.png', 0, 118, 222, 0, 1760084682,'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(1760084682), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607246_be2901cfcffb60c56b57173d1bc0ffbc_rle_crop_3992051857_0.png', 0, 214, 190, 0, 1760084682,'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(1760084682), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607225_cf7e67936e9b6aeaaa95efd95c23d1df_rle_crop_3992051934_0.png', 0, 189, 201, 0, 1760084682,'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(1760084682), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607225_cf7e67936e9b6aeaaa95efd95c23d1df_rle_crop_3992051936_0.png', 0, 103, 83, 0, 1760084682,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 7 photos in the portfolio 4869462 time of upload the photos Elapsed time : 2.2939224243164062 we have finished the crop for the class : etiquette begin to crop the class : film_plastique param for this class : {'min_score': 0.5} filtre for class : film_plastique hashtag_id of this class : 2107756122 Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! map_result returned by crop_photo_return_map_crop : length : 7 About to insert : list_path_to_insert length 7 new photo from crops ! About to upload 7 photos upload in portfolio : 4869462 init cache_photo without model_param we have 7 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1760084686_41623 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(1760084688), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607356_4feae2b60c73201395be33b5d77ceb70_rle_crop_3992051278_0.png', 0, 331, 263, 0, 1760084688,'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(1760084688), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607351_ad9612884254167d834fa004414b83d2_rle_crop_3992051291_0.png', 0, 352, 269, 0, 1760084688,'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(1760084688), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607351_ad9612884254167d834fa004414b83d2_rle_crop_3992051290_0.png', 0, 231, 276, 0, 1760084688,'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(1760084688), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607326_cb58e932fe5ab1e4b6b948f344f19e54_rle_crop_3992051445_0.png', 0, 125, 155, 0, 1760084688,'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(1760084688), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607251_da512109120c62ac38c1cec9a8b11cb3_rle_crop_3992051724_0.png', 0, 322, 420, 0, 1760084688,'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(1760084688), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607251_da512109120c62ac38c1cec9a8b11cb3_rle_crop_3992051725_0.png', 0, 408, 331, 0, 1760084688,'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(1760084688), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607225_cf7e67936e9b6aeaaa95efd95c23d1df_rle_crop_3992051935_0.png', 0, 388, 355, 0, 1760084688,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 7 photos in the portfolio 4869462 time of upload the photos Elapsed time : 2.94584321975708 we have finished the crop for the class : film_plastique begin to crop the class : kraft param for this class : {'min_score': 0.5} filtre for class : kraft hashtag_id of this class : 493202403 begin to crop the class : metal param for this class : {'min_score': 0.5} filtre for class : metal hashtag_id of this class : 492628673 Next one ! map_result returned by crop_photo_return_map_crop : length : 1 About to insert : list_path_to_insert length 1 new photo from crops ! About to upload 1 photos upload in portfolio : 4869462 init cache_photo without model_param we have 1 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1760084690_41623 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(1760084690), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607327_81e3a5b54698baa1fa09c64e3943f087_rle_crop_3992051316_0.png', 0, 129, 166, 0, 1760084690,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 1 photos in the portfolio 4869462 time of upload the photos Elapsed time : 1.0701780319213867 we have finished the crop for the class : metal begin to crop the class : pehd param for this class : {'min_score': 0.5} filtre for class : pehd hashtag_id of this class : 628944319 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/1760084692_41623 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(1760084692), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607351_ad9612884254167d834fa004414b83d2_rle_crop_3992051292_0.png', 0, 329, 285, 0, 1760084692,'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(1760084692), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607327_81e3a5b54698baa1fa09c64e3943f087_rle_crop_3992051319_0.png', 0, 202, 286, 0, 1760084692,'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 : 0.9717533588409424 we have finished the crop for the class : pehd begin to crop the class : pet_clair param for this class : {'min_score': 0.5} filtre for class : pet_clair hashtag_id of this class : 2107755846 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/1760084694_41623 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(1760084695), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607351_ad9612884254167d834fa004414b83d2_rle_crop_3992051289_0.png', 0, 196, 220, 0, 1760084695,'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(1760084695), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607251_da512109120c62ac38c1cec9a8b11cb3_rle_crop_3992051730_0.png', 0, 269, 320, 0, 1760084695,'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 : 1.1394686698913574 we have finished the crop for the class : pet_clair begin to crop the class : pet_opaque param for this class : {'min_score': 0.5} filtre for class : pet_opaque hashtag_id of this class : 2107759152 Next one ! Next one ! Next one ! Next one ! Next one ! map_result returned by crop_photo_return_map_crop : length : 5 About to insert : list_path_to_insert length 5 new photo from crops ! About to upload 5 photos upload in portfolio : 4869462 init cache_photo without model_param we have 5 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1760084698_41623 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(1760084699), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607356_4feae2b60c73201395be33b5d77ceb70_rle_crop_3992051280_0.png', 0, 149, 341, 0, 1760084699,'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(1760084699), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607327_81e3a5b54698baa1fa09c64e3943f087_rle_crop_3992051312_0.png', 0, 333, 238, 0, 1760084699,'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(1760084699), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607326_cb58e932fe5ab1e4b6b948f344f19e54_rle_crop_3992051453_0.png', 0, 675, 539, 0, 1760084699,'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(1760084699), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607326_cb58e932fe5ab1e4b6b948f344f19e54_rle_crop_3992051447_0.png', 0, 250, 145, 0, 1760084699,'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(1760084699), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607251_da512109120c62ac38c1cec9a8b11cb3_rle_crop_3992051727_0.png', 0, 122, 115, 0, 1760084699,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 5 photos in the portfolio 4869462 time of upload the photos Elapsed time : 2.0146312713623047 we have finished the crop for the class : pet_opaque begin to crop the class : textiles_sanitaires param for this class : {'min_score': 0.5} filtre for class : textiles_sanitaires hashtag_id of this class : 2107760129 begin to crop the class : pet_fonce param for this class : {'min_score': 0.5} filtre for class : pet_fonce hashtag_id of this class : 2107755900 begin to crop the class : papier param for this class : {'min_score': 0.5} 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 ! map_result returned by crop_photo_return_map_crop : length : 28 About to insert : list_path_to_insert length 28 new photo from crops ! About to upload 28 photos upload in portfolio : 4869462 init cache_photo without model_param we have 28 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1760084708_41623 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(1760084714), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607356_4feae2b60c73201395be33b5d77ceb70_rle_crop_3992051276_0.png', 0, 406, 195, 0, 1760084714,'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(1760084714), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607356_4feae2b60c73201395be33b5d77ceb70_rle_crop_3992051275_0.png', 0, 404, 231, 0, 1760084714,'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(1760084714), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607356_4feae2b60c73201395be33b5d77ceb70_rle_crop_3992051271_0.png', 0, 211, 355, 0, 1760084714,'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(1760084714), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607356_4feae2b60c73201395be33b5d77ceb70_rle_crop_3992051270_0.png', 0, 130, 139, 0, 1760084714,'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(1760084714), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607351_ad9612884254167d834fa004414b83d2_rle_crop_3992051295_0.png', 0, 599, 643, 0, 1760084714,'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(1760084714), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607351_ad9612884254167d834fa004414b83d2_rle_crop_3992051293_0.png', 0, 263, 511, 0, 1760084714,'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(1760084714), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607351_ad9612884254167d834fa004414b83d2_rle_crop_3992051294_0.png', 0, 418, 402, 0, 1760084714,'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(1760084714), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607327_81e3a5b54698baa1fa09c64e3943f087_rle_crop_3992051305_0.png', 0, 270, 313, 0, 1760084714,'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(1760084714), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607327_81e3a5b54698baa1fa09c64e3943f087_rle_crop_3992051329_0.png', 0, 249, 190, 0, 1760084714,'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(1760084714), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607327_81e3a5b54698baa1fa09c64e3943f087_rle_crop_3992051302_0.png', 0, 275, 368, 0, 1760084714,'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(1760084714), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607327_81e3a5b54698baa1fa09c64e3943f087_rle_crop_3992051330_0.png', 0, 235, 121, 0, 1760084714,'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(1760084714), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607327_81e3a5b54698baa1fa09c64e3943f087_rle_crop_3992051308_0.png', 0, 192, 171, 0, 1760084714,'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(1760084714), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607326_cb58e932fe5ab1e4b6b948f344f19e54_rle_crop_3992051448_0.png', 0, 337, 278, 0, 1760084714,'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(1760084714), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607326_cb58e932fe5ab1e4b6b948f344f19e54_rle_crop_3992051450_0.png', 0, 134, 203, 0, 1760084714,'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(1760084714), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607326_cb58e932fe5ab1e4b6b948f344f19e54_rle_crop_3992051452_0.png', 0, 103, 209, 0, 1760084714,'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(1760084714), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607326_cb58e932fe5ab1e4b6b948f344f19e54_rle_crop_3992051456_0.png', 0, 67, 146, 0, 1760084714,'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(1760084714), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607326_cb58e932fe5ab1e4b6b948f344f19e54_rle_crop_3992051446_0.png', 0, 273, 380, 0, 1760084714,'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(1760084714), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607251_da512109120c62ac38c1cec9a8b11cb3_rle_crop_3992051731_0.png', 0, 216, 75, 0, 1760084714,'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(1760084714), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607251_da512109120c62ac38c1cec9a8b11cb3_rle_crop_3992051737_0.png', 0, 261, 210, 0, 1760084714,'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(1760084714), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607246_be2901cfcffb60c56b57173d1bc0ffbc_rle_crop_3992051856_0.png', 0, 216, 216, 0, 1760084714,'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(1760084714), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607246_be2901cfcffb60c56b57173d1bc0ffbc_rle_crop_3992051860_0.png', 0, 268, 449, 0, 1760084714,'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(1760084714), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607246_be2901cfcffb60c56b57173d1bc0ffbc_rle_crop_3992051852_0.png', 0, 98, 232, 0, 1760084714,'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(1760084714), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607246_be2901cfcffb60c56b57173d1bc0ffbc_rle_crop_3992051851_0.png', 0, 177, 267, 0, 1760084714,'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(1760084714), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607246_be2901cfcffb60c56b57173d1bc0ffbc_rle_crop_3992051854_0.png', 0, 141, 221, 0, 1760084714,'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(1760084714), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607246_be2901cfcffb60c56b57173d1bc0ffbc_rle_crop_3992051853_0.png', 0, 239, 266, 0, 1760084714,'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(1760084714), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607225_cf7e67936e9b6aeaaa95efd95c23d1df_rle_crop_3992051932_0.png', 0, 451, 266, 0, 1760084714,'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(1760084714), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607225_cf7e67936e9b6aeaaa95efd95c23d1df_rle_crop_3992051933_0.png', 0, 200, 209, 0, 1760084714,'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(1760084714), 0.0, 0.0, 14, '', 0, 0, '1760084338_41623_1388607225_cf7e67936e9b6aeaaa95efd95c23d1df_rle_crop_3992051937_0.png', 0, 286, 434, 0, 1760084714,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 28 photos in the portfolio 4869462 time of upload the photos Elapsed time : 9.942139148712158 we have finished the crop for the class : papier delete rles for these photos Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : crop_condition we use saveGeneral [1388607356, 1388607351, 1388607327, 1388607326, 1388607251, 1388607246, 1388607225] Looping around the photos to save general results len do output : 86 /1388656785Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656786Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656788Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656789Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656790Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656791Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656792Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656793Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656794Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656795Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656797Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656798Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656799Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656800Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656801Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656802Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656803Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656804Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656805Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656806Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656807Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656810Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656811Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656812Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656813Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656816Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656817Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656818Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656819Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656820Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656821Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656822Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656823Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656824Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656825Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656827Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656828Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656829Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656830Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656831Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656832Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656833Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656834Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656835Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656836Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656837Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656838Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656839Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656846Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656980Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656981Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656989Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656990Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656991Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656992Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656993Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656994Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388656995Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388657063Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388657064Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388657065Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388657066Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388657067Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388657068Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388657069Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388657070Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388657071Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388657072Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388657073Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388657074Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388657075Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388657077Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388657078Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388657079Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388657080Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388657081Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388657082Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388657083Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388657091Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388657094Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388657095Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388657096Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388657097Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388657098Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388657099Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1388657100Didn'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 ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607356', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607351', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607327', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607326', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607251', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607246', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607225', None, None, None, None, None, '3919092') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 265 time used for this insertion : 0.04471874237060547 save_final save missing photos in datou_result : time spend for datou_step_exec : 63.33289098739624 time spend to save output : 0.04670906066894531 total time spend for step 8 : 63.379600048065186 step9:ventilate_hashtags_in_portfolio Fri Oct 10 10:25:18 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 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 : 27677754 get user id for portfolio 27677754 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`=27677754 AND mptpi.`type`=4211 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('flou','autre','kraft','environnement','pet_opaque','ela','carton','film_plastique','textiles_sanitaires','metal','etiquette','barquette_opaque','pet_clair','pehd','papier','mal_croppe','pet_fonce')) AND mptpi.`min_score`=0.5 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`=27677754 AND mptpi.`type`=4211 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('flou','autre','kraft','environnement','pet_opaque','ela','carton','film_plastique','textiles_sanitaires','metal','etiquette','barquette_opaque','pet_clair','pehd','papier','mal_croppe','pet_fonce')) AND mptpi.`min_score`=0.5 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") 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`=27677754 AND mptpi.`type`=4211 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('flou','autre','kraft','environnement','pet_opaque','ela','carton','film_plastique','textiles_sanitaires','metal','etiquette','barquette_opaque','pet_clair','pehd','papier','mal_croppe','pet_fonce')) AND mptpi.`min_score`=0.5 To do lien utilise dans velours : https://marlene.fotonower.com/velours/27689418,27689419,27689420,27689421,27689422,27689423,27689424,27689425,27689426,27689427,27689428,27689429,27689430,27689431,27689432,27689433,27689434?tags=flou,autre,kraft,environnement,pet_opaque,ela,carton,film_plastique,textiles_sanitaires,metal,etiquette,barquette_opaque,pet_clair,pehd,papier,mal_croppe,pet_fonce Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : ventilate_hashtags_in_portfolio we use saveGeneral [1388607356, 1388607351, 1388607327, 1388607326, 1388607251, 1388607246, 1388607225] Looping around the photos to save general results len do output : 1 /27677754. 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 ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607356', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607351', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607327', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607326', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607251', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607246', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607225', None, None, None, None, None, '3919092') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 8 time used for this insertion : 0.036936044692993164 save_final save missing photos in datou_result : time spend for datou_step_exec : 8.334480047225952 time spend to save output : 0.03711128234863281 total time spend for step 9 : 8.371591329574585 step10:final Fri Oct 10 10:25:26 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed 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 : {1388607356: ('0.06558784415627442',), 1388607351: ('0.06558784415627442',), 1388607327: ('0.06558784415627442',), 1388607326: ('0.06558784415627442',), 1388607251: ('0.06558784415627442',), 1388607246: ('0.06558784415627442',), 1388607225: ('0.06558784415627442',)} new output for save of step final : {1388607356: ('0.06558784415627442',), 1388607351: ('0.06558784415627442',), 1388607327: ('0.06558784415627442',), 1388607326: ('0.06558784415627442',), 1388607251: ('0.06558784415627442',), 1388607246: ('0.06558784415627442',), 1388607225: ('0.06558784415627442',)} [1388607356, 1388607351, 1388607327, 1388607326, 1388607251, 1388607246, 1388607225] Looping around the photos to save general results len do output : 7 /1388607356.Didn't retrieve data . /1388607351.Didn't retrieve data . /1388607327.Didn't retrieve data . /1388607326.Didn't retrieve data . /1388607251.Didn't retrieve data . /1388607246.Didn't retrieve data . /1388607225.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 ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607356', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607351', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607327', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607326', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607251', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607246', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607225', None, None, None, None, None, '3919092') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 21 time used for this insertion : 0.03608870506286621 save_final save missing photos in datou_result : time spend for datou_step_exec : 0.3760406970977783 time spend to save output : 0.03648686408996582 total time spend for step 10 : 0.41252756118774414 step11:velours_tree Fri Oct 10 10:25:26 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 VR 22-3-18 : For now we do not clean correctly the datou structure can't find the photo_desc_type Inside saveOutput : final : False verbose : 0 ouput is None No outpout to save, returning out of save general time spend for datou_step_exec : 0.049184322357177734 time spend to save output : 3.3855438232421875e-05 total time spend for step 11 : 0.049218177795410156 step12:send_mail_cod Fri Oct 10 10:25:26 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 complete output_args for input 1 complete output_args for input 2 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 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_Auto_P27677754_10-10-2025_10_25_26.pdf 27689418 imagette276894181760084727 27689419 imagette276894191760084727 27689420 imagette276894201760084727 27689422 change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .imagette276894221760084727 27689423 imagette276894231760084727 27689424 change filename to text .change filename to text .change filename to text .change filename to text .imagette276894241760084727 27689425 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 .imagette276894251760084728 27689426 imagette276894261760084728 27689427 change filename to text .imagette276894271760084728 27689428 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 .imagette276894281760084728 27689429 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 .imagette276894291760084729 27689430 change filename to text .change filename to text .imagette276894301760084731 27689432 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 .imagette276894321760084731 27689433 imagette276894331760084733 27689434 imagette276894341760084733 SELECT h.hashtag,pcr.value FROM MTRUser.portfolio_carac_ratio pcr, MTRBack.hashtags h where pcr.portfolio_id=27677754 and hashtag_type = 4211 and pcr.hashtag_id = h.hashtag_id; velour_link : https://marlene.fotonower.com/velours/27689418,27689419,27689420,27689421,27689422,27689423,27689424,27689425,27689426,27689427,27689428,27689429,27689430,27689431,27689432,27689433,27689434?tags=flou,autre,kraft,environnement,pet_opaque,ela,carton,film_plastique,textiles_sanitaires,metal,etiquette,barquette_opaque,pet_clair,pehd,papier,mal_croppe,pet_fonce your option no_mail is active, we will not send the real mail to your client args[1388607356] : ((1388607356, 3.7397318175490306, 492688767), (1388607356, -0.2249683204216384, 496442774), '0.06558784415627442') We are sending mail with results at report@fotonower.com args[1388607351] : ((1388607351, 1.2133471737161563, 492688767), (1388607351, 0.27186968638827164, 2107752395), '0.06558784415627442') We are sending mail with results at report@fotonower.com args[1388607327] : ((1388607327, -1.427640946705835, 492688767), (1388607327, -0.20603860817466305, 496442774), '0.06558784415627442') We are sending mail with results at report@fotonower.com args[1388607326] : ((1388607326, -3.246349801421127, 492609224), (1388607326, -0.140881750588755, 496442774), '0.06558784415627442') We are sending mail with results at report@fotonower.com args[1388607251] : ((1388607251, 3.5628499126995203, 492688767), (1388607251, -0.25480545540520416, 496442774), '0.06558784415627442') We are sending mail with results at report@fotonower.com args[1388607246] : ((1388607246, 4.373083577919527, 492688767), (1388607246, -0.061862164178942906, 2107752395), '0.06558784415627442') We are sending mail with results at report@fotonower.com args[1388607225] : ((1388607225, 2.816332015988374, 492688767), (1388607225, -0.25017963978676044, 496442774), '0.06558784415627442') We are sending mail with results at report@fotonower.com refus_total : 0.06558784415627442 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=27677754 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_Auto_P27677754_10-10-2025_10_25_26.pdf results_Auto_P27677754_10-10-2025_10_25_26.pdf uploaded to url https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27677754_10-10-2025_10_25_26.pdf start insert file to database insert into MTRUser.mtr_files (mtd_id,mtr_portfolio_id,text,url,format,tags,file_size,value) values ('3995','27677754','results_Auto_P27677754_10-10-2025_10_25_26.pdf','https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27677754_10-10-2025_10_25_26.pdf','pdf','','0.64','0.06558784415627442') Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : send_mail_cod we use saveGeneral [1388607356, 1388607351, 1388607327, 1388607326, 1388607251, 1388607246, 1388607225] 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 ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607356', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607351', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607327', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607326', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607251', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607246', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607225', None, None, None, None, None, '3919092') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 7 time used for this insertion : 0.03518342971801758 save_final save missing photos in datou_result : time spend for datou_step_exec : 8.292984962463379 time spend to save output : 0.03534364700317383 total time spend for step 12 : 8.328328609466553 step13:split_time_score Fri Oct 10 10:25:35 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 ! complete output_args for input 1 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': 861, 'mtr_user_id': 31, 'name': 'Rungis_class_dechets_1212', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'Rungis_Aluminium,Rungis_Carton,Rungis_Papier,Rungis_Plastique_clair,Rungis_Plastique_dur,Rungis_Plastique_fonce,Rungis_Tapis_vide,Rungis_Tetrapak', 'svm_portfolios_learning': '1160730,571842,571844,571839,571933,571840,571841,572307', 'photo_hashtag_type': 999, 'photo_desc_type': 3963, 'type_classification': 'caffe', 'hashtag_id_list': '2107751280,2107750907,2107750908,2107750909,2107750910,2107750911,2107750912,2107750913'}] 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'}] (('05', 7),) ERROR counted https://github.com/fotonower/Velours/issues/663#issuecomment-421136223 {} 10102025 27677754 Nombre de photos uploadées : 7 / 23040 (0%) 10102025 27677754 Nombre de photos taguées (types de déchets): 0 / 7 (0%) 10102025 27677754 Nombre de photos taguées (volume) : 0 / 7 (0%) elapsed_time : load_data_split_time_score 3.337860107421875e-06 elapsed_time : order_list_meta_photo_and_scores 9.298324584960938e-06 ??????? elapsed_time : fill_and_build_computed_from_old_data 0.0007817745208740234 Catched exception ! Connect or reconnect ! Catched exception ! Connect or reconnect ! elapsed_time : insert_dashboard_record_day_entry 0.6322453022003174 We will return after consolidate but for now we need the day, how to get it, for now depending on the previous heavy steps find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27677609_10-10-2025_09_43_29.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27677609 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27677611 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27677614 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27677617 order by id desc limit 1 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27677623_10-10-2025_09_41_30.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27677623 order by id desc limit 1 Qualite : 0.054208301451222074 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27677626_10-10-2025_09_59_03.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27677626 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 ! 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 11560 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11567 mask_detect have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11567 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11563 crop_condition is not consistent : 4 used against 2 in the step definition ! Step 11563 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11564 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11564 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11565 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11565 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11573 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11573 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11568 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11568 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11566 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11566 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! 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 ! WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 1 of step 11560 have datatype=2 whereas input 1 of step 11564 have datatype=7 WARNING : type of output 2 of step 11564 doesn't seem to be define in the database( WARNING : type of input 1 of step 11565 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11567 doesn't seem to be define in the database( WARNING : type of input 3 of step 11563 doesn't seem to be define in the database( WARNING : type of output 3 of step 11564 doesn't seem to be define in the database( WARNING : type of input 1 of step 11568 doesn't seem to be define in the database( WARNING : type of output 1 of step 11568 doesn't seem to be define in the database( WARNING : type of input 3 of step 11566 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 0 of step 11570 have datatype=6 whereas input 2 of step 11563 have datatype=None WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 0 of step 11569 have datatype=6 whereas input 2 of step 11563 have datatype=None WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 1 of step 11570 doesn't seem to be define in the database( WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 1 of step 11569 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11568 have datatype=10 whereas input 3 of step 11571 have datatype=6 WARNING : type of input 2 of step 11573 doesn't seem to be define in the database( WARNING : output 1 of step 11565 have datatype=7 whereas input 2 of step 11573 have datatype=None WARNING : type of output 3 of step 11573 doesn't seem to be define in the database( WARNING : type of input 3 of step 11568 doesn't seem to be define in the database( WARNING : output 0 of step 11568 have datatype=10 whereas input 0 of step 11587 have datatype=18 WARNING : type of input 5 of step 11571 doesn't seem to be define in the database( WARNING : output 0 of step 11587 have datatype=11 whereas input 5 of step 11571 have datatype=None WARNING : output 0 of step 11564 have datatype=1 whereas input 0 of step 11565 have datatype=2 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`=27677626 AND mptpi.`type`=3327 To do find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27677629 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27677634 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27677637 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27677644 order by id desc limit 1 Qualite : 0.08331168364838167 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27677648_10-10-2025_09_54_59.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27677648 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 ! 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 11560 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11567 mask_detect have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11567 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11563 crop_condition is not consistent : 4 used against 2 in the step definition ! Step 11563 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11564 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11564 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11565 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11565 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11573 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11573 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11568 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11568 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11566 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11566 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! 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 ! WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 1 of step 11560 have datatype=2 whereas input 1 of step 11564 have datatype=7 WARNING : type of output 2 of step 11564 doesn't seem to be define in the database( WARNING : type of input 1 of step 11565 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11567 doesn't seem to be define in the database( WARNING : type of input 3 of step 11563 doesn't seem to be define in the database( WARNING : type of output 3 of step 11564 doesn't seem to be define in the database( WARNING : type of input 1 of step 11568 doesn't seem to be define in the database( WARNING : type of output 1 of step 11568 doesn't seem to be define in the database( WARNING : type of input 3 of step 11566 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 0 of step 11570 have datatype=6 whereas input 2 of step 11563 have datatype=None WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 0 of step 11569 have datatype=6 whereas input 2 of step 11563 have datatype=None WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 1 of step 11570 doesn't seem to be define in the database( WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 1 of step 11569 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11568 have datatype=10 whereas input 3 of step 11571 have datatype=6 WARNING : type of input 2 of step 11573 doesn't seem to be define in the database( WARNING : output 1 of step 11565 have datatype=7 whereas input 2 of step 11573 have datatype=None WARNING : type of output 3 of step 11573 doesn't seem to be define in the database( WARNING : type of input 3 of step 11568 doesn't seem to be define in the database( WARNING : output 0 of step 11568 have datatype=10 whereas input 0 of step 11587 have datatype=18 WARNING : type of input 5 of step 11571 doesn't seem to be define in the database( WARNING : output 0 of step 11587 have datatype=11 whereas input 5 of step 11571 have datatype=None WARNING : output 0 of step 11564 have datatype=1 whereas input 0 of step 11565 have datatype=2 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`=27677648 AND mptpi.`type`=3327 To do find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27677657_10-10-2025_09_28_40.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27677657 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27677684 order by id desc limit 1 Qualite : 0.07040079841186098 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27677704_10-10-2025_10_21_13.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27677704 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 ! 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 11524 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11533 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11532 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11528 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11528 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11531 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11531 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11525 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11525 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11578 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11578 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11527 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11526 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11526 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11535 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 : type of output 1 of step 11527 doesn't seem to be define in the database( WARNING : type of input 3 of step 11526 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11524 doesn't seem to be define in the database( WARNING : type of input 2 of step 11528 doesn't seem to be define in the database( WARNING : output 1 of step 11524 have datatype=2 whereas input 1 of step 11531 have datatype=7 WARNING : type of output 2 of step 11531 doesn't seem to be define in the database( WARNING : type of input 1 of step 11525 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11527 have datatype=10 whereas input 3 of step 11534 have datatype=6 WARNING : type of input 2 of step 11578 doesn't seem to be define in the database( WARNING : output 1 of step 11525 have datatype=7 whereas input 2 of step 11578 have datatype=None WARNING : type of output 3 of step 11578 doesn't seem to be define in the database( WARNING : type of input 1 of step 11527 doesn't seem to be define in the database( WARNING : output 0 of step 11527 have datatype=10 whereas input 0 of step 11584 have datatype=18 WARNING : type of input 5 of step 11534 doesn't seem to be define in the database( WARNING : output 0 of step 11584 have datatype=11 whereas input 5 of step 11534 have datatype=None WARNING : type of output 1 of step 11533 doesn't seem to be define in the database( WARNING : type of input 3 of step 11528 doesn't seem to be define in the database( WARNING : type of output 1 of step 11532 doesn't seem to be define in the database( WARNING : type of input 3 of step 11528 doesn't seem to be define in the database( WARNING : output 0 of step 11531 have datatype=1 whereas input 0 of step 11525 have datatype=2 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`=27677704 AND mptpi.`type`=4211 To do find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27677725 order by id desc limit 1 Qualite : 0.0528412693706337 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27677728_10-10-2025_09_47_13.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27677728 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 ! 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 11560 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11567 mask_detect have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11567 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11563 crop_condition is not consistent : 4 used against 2 in the step definition ! Step 11563 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11564 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11564 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11565 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11565 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11573 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11573 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11568 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11568 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11566 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11566 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! 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 ! WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 1 of step 11560 have datatype=2 whereas input 1 of step 11564 have datatype=7 WARNING : type of output 2 of step 11564 doesn't seem to be define in the database( WARNING : type of input 1 of step 11565 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11567 doesn't seem to be define in the database( WARNING : type of input 3 of step 11563 doesn't seem to be define in the database( WARNING : type of output 3 of step 11564 doesn't seem to be define in the database( WARNING : type of input 1 of step 11568 doesn't seem to be define in the database( WARNING : type of output 1 of step 11568 doesn't seem to be define in the database( WARNING : type of input 3 of step 11566 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 0 of step 11570 have datatype=6 whereas input 2 of step 11563 have datatype=None WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 0 of step 11569 have datatype=6 whereas input 2 of step 11563 have datatype=None WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 1 of step 11570 doesn't seem to be define in the database( WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 1 of step 11569 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11568 have datatype=10 whereas input 3 of step 11571 have datatype=6 WARNING : type of input 2 of step 11573 doesn't seem to be define in the database( WARNING : output 1 of step 11565 have datatype=7 whereas input 2 of step 11573 have datatype=None WARNING : type of output 3 of step 11573 doesn't seem to be define in the database( WARNING : type of input 3 of step 11568 doesn't seem to be define in the database( WARNING : output 0 of step 11568 have datatype=10 whereas input 0 of step 11587 have datatype=18 WARNING : type of input 5 of step 11571 doesn't seem to be define in the database( WARNING : output 0 of step 11587 have datatype=11 whereas input 5 of step 11571 have datatype=None WARNING : output 0 of step 11564 have datatype=1 whereas input 0 of step 11565 have datatype=2 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`=27677728 AND mptpi.`type`=3327 To do find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27677730 order by id desc limit 1 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27677736_10-10-2025_09_23_06.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27677736 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27677745 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27677748 order by id desc limit 1 Qualite : 0.03550447758439888 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27677751_10-10-2025_09_42_13.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27677751 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 ! 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 11560 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11567 mask_detect have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11567 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11563 crop_condition is not consistent : 4 used against 2 in the step definition ! Step 11563 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11564 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11564 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11565 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11565 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11573 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11573 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11568 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11568 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11566 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11566 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! 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 ! WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 1 of step 11560 have datatype=2 whereas input 1 of step 11564 have datatype=7 WARNING : type of output 2 of step 11564 doesn't seem to be define in the database( WARNING : type of input 1 of step 11565 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11567 doesn't seem to be define in the database( WARNING : type of input 3 of step 11563 doesn't seem to be define in the database( WARNING : type of output 3 of step 11564 doesn't seem to be define in the database( WARNING : type of input 1 of step 11568 doesn't seem to be define in the database( WARNING : type of output 1 of step 11568 doesn't seem to be define in the database( WARNING : type of input 3 of step 11566 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 0 of step 11570 have datatype=6 whereas input 2 of step 11563 have datatype=None WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 0 of step 11569 have datatype=6 whereas input 2 of step 11563 have datatype=None WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 1 of step 11570 doesn't seem to be define in the database( WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 1 of step 11569 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11568 have datatype=10 whereas input 3 of step 11571 have datatype=6 WARNING : type of input 2 of step 11573 doesn't seem to be define in the database( WARNING : output 1 of step 11565 have datatype=7 whereas input 2 of step 11573 have datatype=None WARNING : type of output 3 of step 11573 doesn't seem to be define in the database( WARNING : type of input 3 of step 11568 doesn't seem to be define in the database( WARNING : output 0 of step 11568 have datatype=10 whereas input 0 of step 11587 have datatype=18 WARNING : type of input 5 of step 11571 doesn't seem to be define in the database( WARNING : output 0 of step 11587 have datatype=11 whereas input 5 of step 11571 have datatype=None WARNING : output 0 of step 11564 have datatype=1 whereas input 0 of step 11565 have datatype=2 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`=27677751 AND mptpi.`type`=3327 To do Qualite : 0.06558784415627442 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27677754_10-10-2025_10_25_26.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27677754 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 ! 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 11524 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11533 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11532 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11528 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11528 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11531 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11531 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11525 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11525 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11578 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11578 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11527 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11526 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11526 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11535 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 : type of output 1 of step 11527 doesn't seem to be define in the database( WARNING : type of input 3 of step 11526 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11524 doesn't seem to be define in the database( WARNING : type of input 2 of step 11528 doesn't seem to be define in the database( WARNING : output 1 of step 11524 have datatype=2 whereas input 1 of step 11531 have datatype=7 WARNING : type of output 2 of step 11531 doesn't seem to be define in the database( WARNING : type of input 1 of step 11525 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11527 have datatype=10 whereas input 3 of step 11534 have datatype=6 WARNING : type of input 2 of step 11578 doesn't seem to be define in the database( WARNING : output 1 of step 11525 have datatype=7 whereas input 2 of step 11578 have datatype=None WARNING : type of output 3 of step 11578 doesn't seem to be define in the database( WARNING : type of input 1 of step 11527 doesn't seem to be define in the database( WARNING : output 0 of step 11527 have datatype=10 whereas input 0 of step 11584 have datatype=18 WARNING : type of input 5 of step 11534 doesn't seem to be define in the database( WARNING : output 0 of step 11584 have datatype=11 whereas input 5 of step 11534 have datatype=None WARNING : type of output 1 of step 11533 doesn't seem to be define in the database( WARNING : type of input 3 of step 11528 doesn't seem to be define in the database( WARNING : type of output 1 of step 11532 doesn't seem to be define in the database( WARNING : type of input 3 of step 11528 doesn't seem to be define in the database( WARNING : output 0 of step 11531 have datatype=1 whereas input 0 of step 11525 have datatype=2 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`=27677754 AND mptpi.`type`=4211 To do Qualite : 0.04664251382458848 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27677756_10-10-2025_08_37_04.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27677756 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 ! 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 11500 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11508 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11509 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11504 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11504 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11507 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11507 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11576 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11576 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11503 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11502 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11502 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11511 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 : type of output 1 of step 11503 doesn't seem to be define in the database( WARNING : type of input 3 of step 11502 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11500 doesn't seem to be define in the database( WARNING : type of input 2 of step 11504 doesn't seem to be define in the database( WARNING : output 1 of step 11500 have datatype=2 whereas input 1 of step 11507 have datatype=7 WARNING : type of output 2 of step 11507 doesn't seem to be define in the database( WARNING : type of input 1 of step 11501 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11503 have datatype=10 whereas input 3 of step 11510 have datatype=6 WARNING : type of input 2 of step 11576 doesn't seem to be define in the database( WARNING : output 1 of step 11501 have datatype=7 whereas input 2 of step 11576 have datatype=None WARNING : type of output 3 of step 11576 doesn't seem to be define in the database( WARNING : type of input 1 of step 11503 doesn't seem to be define in the database( WARNING : output 0 of step 11503 have datatype=10 whereas input 0 of step 11582 have datatype=18 WARNING : type of input 5 of step 11510 doesn't seem to be define in the database( WARNING : output 0 of step 11582 have datatype=11 whereas input 5 of step 11510 have datatype=None WARNING : type of output 1 of step 11508 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : type of output 1 of step 11509 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : output 0 of step 11507 have datatype=1 whereas input 0 of step 11501 have datatype=2 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`=27677756 AND mptpi.`type`=4207 To do find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27677759_10-10-2025_09_18_57.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27677759 order by id desc limit 1 Qualite : 0.06753654910232068 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27677761_10-10-2025_09_33_59.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27677761 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 ! 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 11560 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11567 mask_detect have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11567 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11563 crop_condition is not consistent : 4 used against 2 in the step definition ! Step 11563 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11564 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11564 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11565 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11565 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11573 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11573 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11568 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11568 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11566 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11566 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! 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 ! WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 1 of step 11560 have datatype=2 whereas input 1 of step 11564 have datatype=7 WARNING : type of output 2 of step 11564 doesn't seem to be define in the database( WARNING : type of input 1 of step 11565 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11567 doesn't seem to be define in the database( WARNING : type of input 3 of step 11563 doesn't seem to be define in the database( WARNING : type of output 3 of step 11564 doesn't seem to be define in the database( WARNING : type of input 1 of step 11568 doesn't seem to be define in the database( WARNING : type of output 1 of step 11568 doesn't seem to be define in the database( WARNING : type of input 3 of step 11566 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 0 of step 11570 have datatype=6 whereas input 2 of step 11563 have datatype=None WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 0 of step 11569 have datatype=6 whereas input 2 of step 11563 have datatype=None WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 1 of step 11570 doesn't seem to be define in the database( WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 1 of step 11569 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11568 have datatype=10 whereas input 3 of step 11571 have datatype=6 WARNING : type of input 2 of step 11573 doesn't seem to be define in the database( WARNING : output 1 of step 11565 have datatype=7 whereas input 2 of step 11573 have datatype=None WARNING : type of output 3 of step 11573 doesn't seem to be define in the database( WARNING : type of input 3 of step 11568 doesn't seem to be define in the database( WARNING : output 0 of step 11568 have datatype=10 whereas input 0 of step 11587 have datatype=18 WARNING : type of input 5 of step 11571 doesn't seem to be define in the database( WARNING : output 0 of step 11587 have datatype=11 whereas input 5 of step 11571 have datatype=None WARNING : output 0 of step 11564 have datatype=1 whereas input 0 of step 11565 have datatype=2 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`=27677761 AND mptpi.`type`=3327 To do Qualite : 0.02767923314699753 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27677767_10-10-2025_07_13_02.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27677767 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 ! 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 11500 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11508 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11509 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11504 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11504 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11507 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11507 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11576 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11576 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11503 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11502 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11502 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11511 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 : type of output 1 of step 11503 doesn't seem to be define in the database( WARNING : type of input 3 of step 11502 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11500 doesn't seem to be define in the database( WARNING : type of input 2 of step 11504 doesn't seem to be define in the database( WARNING : output 1 of step 11500 have datatype=2 whereas input 1 of step 11507 have datatype=7 WARNING : type of output 2 of step 11507 doesn't seem to be define in the database( WARNING : type of input 1 of step 11501 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11503 have datatype=10 whereas input 3 of step 11510 have datatype=6 WARNING : type of input 2 of step 11576 doesn't seem to be define in the database( WARNING : output 1 of step 11501 have datatype=7 whereas input 2 of step 11576 have datatype=None WARNING : type of output 3 of step 11576 doesn't seem to be define in the database( WARNING : type of input 1 of step 11503 doesn't seem to be define in the database( WARNING : output 0 of step 11503 have datatype=10 whereas input 0 of step 11582 have datatype=18 WARNING : type of input 5 of step 11510 doesn't seem to be define in the database( WARNING : output 0 of step 11582 have datatype=11 whereas input 5 of step 11510 have datatype=None WARNING : type of output 1 of step 11508 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : type of output 1 of step 11509 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : output 0 of step 11507 have datatype=1 whereas input 0 of step 11501 have datatype=2 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`=27677767 AND mptpi.`type`=4207 To do find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27678536 order by id desc limit 1 Qualite : 0.04408803273542409 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27678538_10-10-2025_08_59_53.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27678538 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 ! 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 11488 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11496 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11497 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11492 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11492 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11495 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11495 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11489 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11489 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11575 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11575 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11491 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11490 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11490 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11498 send_mail_cod have less outputs used (0) than in the step definition (1) : some outputs may be not used ! Step 11499 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 : type of output 1 of step 11491 doesn't seem to be define in the database( WARNING : type of input 3 of step 11490 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11488 doesn't seem to be define in the database( WARNING : type of input 2 of step 11492 doesn't seem to be define in the database( WARNING : output 1 of step 11488 have datatype=2 whereas input 1 of step 11495 have datatype=7 WARNING : type of output 2 of step 11495 doesn't seem to be define in the database( WARNING : type of input 1 of step 11489 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11491 have datatype=10 whereas input 3 of step 11498 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11575 doesn't seem to be define in the database( WARNING : output 1 of step 11489 have datatype=7 whereas input 2 of step 11575 have datatype=None WARNING : type of output 3 of step 11575 doesn't seem to be define in the database( WARNING : type of input 1 of step 11491 doesn't seem to be define in the database( WARNING : output 0 of step 11491 have datatype=10 whereas input 0 of step 11581 have datatype=18 WARNING : type of input 5 of step 11498 doesn't seem to be define in the database( WARNING : output 0 of step 11581 have datatype=11 whereas input 5 of step 11498 have datatype=None WARNING : type of output 1 of step 11496 doesn't seem to be define in the database( WARNING : type of input 3 of step 11492 doesn't seem to be define in the database( WARNING : type of output 1 of step 11497 doesn't seem to be define in the database( WARNING : type of input 3 of step 11492 doesn't seem to be define in the database( WARNING : output 0 of step 11495 have datatype=1 whereas input 0 of step 11489 have datatype=2 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`=27678538 AND mptpi.`type`=4209 To do Qualite : 0.05287046086131051 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27678540_10-10-2025_08_18_58.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27678540 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 ! 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 11500 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11508 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11509 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11504 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11504 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11507 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11507 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11576 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11576 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11503 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11502 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11502 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11511 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 : type of output 1 of step 11503 doesn't seem to be define in the database( WARNING : type of input 3 of step 11502 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11500 doesn't seem to be define in the database( WARNING : type of input 2 of step 11504 doesn't seem to be define in the database( WARNING : output 1 of step 11500 have datatype=2 whereas input 1 of step 11507 have datatype=7 WARNING : type of output 2 of step 11507 doesn't seem to be define in the database( WARNING : type of input 1 of step 11501 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11503 have datatype=10 whereas input 3 of step 11510 have datatype=6 WARNING : type of input 2 of step 11576 doesn't seem to be define in the database( WARNING : output 1 of step 11501 have datatype=7 whereas input 2 of step 11576 have datatype=None WARNING : type of output 3 of step 11576 doesn't seem to be define in the database( WARNING : type of input 1 of step 11503 doesn't seem to be define in the database( WARNING : output 0 of step 11503 have datatype=10 whereas input 0 of step 11582 have datatype=18 WARNING : type of input 5 of step 11510 doesn't seem to be define in the database( WARNING : output 0 of step 11582 have datatype=11 whereas input 5 of step 11510 have datatype=None WARNING : type of output 1 of step 11508 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : type of output 1 of step 11509 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : output 0 of step 11507 have datatype=1 whereas input 0 of step 11501 have datatype=2 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`=27678540 AND mptpi.`type`=4207 To do find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27678543_10-10-2025_09_16_55.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27678543 order by id desc limit 1 Qualite : 0.1083228152684982 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27678546_10-10-2025_09_31_04.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27678546 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 ! 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 11560 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11567 mask_detect have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11567 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11563 crop_condition is not consistent : 4 used against 2 in the step definition ! Step 11563 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11564 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11564 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11565 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11565 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11573 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11573 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11568 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11568 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11566 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11566 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! 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 ! WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 1 of step 11560 have datatype=2 whereas input 1 of step 11564 have datatype=7 WARNING : type of output 2 of step 11564 doesn't seem to be define in the database( WARNING : type of input 1 of step 11565 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11567 doesn't seem to be define in the database( WARNING : type of input 3 of step 11563 doesn't seem to be define in the database( WARNING : type of output 3 of step 11564 doesn't seem to be define in the database( WARNING : type of input 1 of step 11568 doesn't seem to be define in the database( WARNING : type of output 1 of step 11568 doesn't seem to be define in the database( WARNING : type of input 3 of step 11566 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 0 of step 11570 have datatype=6 whereas input 2 of step 11563 have datatype=None WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 0 of step 11569 have datatype=6 whereas input 2 of step 11563 have datatype=None WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 1 of step 11570 doesn't seem to be define in the database( WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 1 of step 11569 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11568 have datatype=10 whereas input 3 of step 11571 have datatype=6 WARNING : type of input 2 of step 11573 doesn't seem to be define in the database( WARNING : output 1 of step 11565 have datatype=7 whereas input 2 of step 11573 have datatype=None WARNING : type of output 3 of step 11573 doesn't seem to be define in the database( WARNING : type of input 3 of step 11568 doesn't seem to be define in the database( WARNING : output 0 of step 11568 have datatype=10 whereas input 0 of step 11587 have datatype=18 WARNING : type of input 5 of step 11571 doesn't seem to be define in the database( WARNING : output 0 of step 11587 have datatype=11 whereas input 5 of step 11571 have datatype=None WARNING : output 0 of step 11564 have datatype=1 whereas input 0 of step 11565 have datatype=2 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`=27678546 AND mptpi.`type`=3327 To do Qualite : 0.04344188046553497 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27678649_10-10-2025_07_25_20.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27678649 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 ! 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 11500 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11508 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11509 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11504 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11504 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11507 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11507 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11576 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11576 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11503 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11502 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11502 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11511 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 : type of output 1 of step 11503 doesn't seem to be define in the database( WARNING : type of input 3 of step 11502 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11500 doesn't seem to be define in the database( WARNING : type of input 2 of step 11504 doesn't seem to be define in the database( WARNING : output 1 of step 11500 have datatype=2 whereas input 1 of step 11507 have datatype=7 WARNING : type of output 2 of step 11507 doesn't seem to be define in the database( WARNING : type of input 1 of step 11501 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11503 have datatype=10 whereas input 3 of step 11510 have datatype=6 WARNING : type of input 2 of step 11576 doesn't seem to be define in the database( WARNING : output 1 of step 11501 have datatype=7 whereas input 2 of step 11576 have datatype=None WARNING : type of output 3 of step 11576 doesn't seem to be define in the database( WARNING : type of input 1 of step 11503 doesn't seem to be define in the database( WARNING : output 0 of step 11503 have datatype=10 whereas input 0 of step 11582 have datatype=18 WARNING : type of input 5 of step 11510 doesn't seem to be define in the database( WARNING : output 0 of step 11582 have datatype=11 whereas input 5 of step 11510 have datatype=None WARNING : type of output 1 of step 11508 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : type of output 1 of step 11509 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : output 0 of step 11507 have datatype=1 whereas input 0 of step 11501 have datatype=2 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`=27678649 AND mptpi.`type`=4207 To do Qualite : 0.08209205410064205 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27679323_10-10-2025_07_49_03.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27679323 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 ! 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 11500 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11508 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11509 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11504 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11504 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11507 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11507 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11576 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11576 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11503 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11502 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11502 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11511 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 : type of output 1 of step 11503 doesn't seem to be define in the database( WARNING : type of input 3 of step 11502 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11500 doesn't seem to be define in the database( WARNING : type of input 2 of step 11504 doesn't seem to be define in the database( WARNING : output 1 of step 11500 have datatype=2 whereas input 1 of step 11507 have datatype=7 WARNING : type of output 2 of step 11507 doesn't seem to be define in the database( WARNING : type of input 1 of step 11501 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11503 have datatype=10 whereas input 3 of step 11510 have datatype=6 WARNING : type of input 2 of step 11576 doesn't seem to be define in the database( WARNING : output 1 of step 11501 have datatype=7 whereas input 2 of step 11576 have datatype=None WARNING : type of output 3 of step 11576 doesn't seem to be define in the database( WARNING : type of input 1 of step 11503 doesn't seem to be define in the database( WARNING : output 0 of step 11503 have datatype=10 whereas input 0 of step 11582 have datatype=18 WARNING : type of input 5 of step 11510 doesn't seem to be define in the database( WARNING : output 0 of step 11582 have datatype=11 whereas input 5 of step 11510 have datatype=None WARNING : type of output 1 of step 11508 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : type of output 1 of step 11509 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : output 0 of step 11507 have datatype=1 whereas input 0 of step 11501 have datatype=2 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`=27679323 AND mptpi.`type`=4207 To do Qualite : 0.07083419300862219 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27679553_10-10-2025_09_27_28.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27679553 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 ! 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 11560 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11567 mask_detect have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11567 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11563 crop_condition is not consistent : 4 used against 2 in the step definition ! Step 11563 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11564 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11564 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11565 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11565 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11573 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11573 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11568 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11568 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11566 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11566 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! 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 ! WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 1 of step 11560 have datatype=2 whereas input 1 of step 11564 have datatype=7 WARNING : type of output 2 of step 11564 doesn't seem to be define in the database( WARNING : type of input 1 of step 11565 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11567 doesn't seem to be define in the database( WARNING : type of input 3 of step 11563 doesn't seem to be define in the database( WARNING : type of output 3 of step 11564 doesn't seem to be define in the database( WARNING : type of input 1 of step 11568 doesn't seem to be define in the database( WARNING : type of output 1 of step 11568 doesn't seem to be define in the database( WARNING : type of input 3 of step 11566 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 0 of step 11570 have datatype=6 whereas input 2 of step 11563 have datatype=None WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 0 of step 11569 have datatype=6 whereas input 2 of step 11563 have datatype=None WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 1 of step 11570 doesn't seem to be define in the database( WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 1 of step 11569 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11568 have datatype=10 whereas input 3 of step 11571 have datatype=6 WARNING : type of input 2 of step 11573 doesn't seem to be define in the database( WARNING : output 1 of step 11565 have datatype=7 whereas input 2 of step 11573 have datatype=None WARNING : type of output 3 of step 11573 doesn't seem to be define in the database( WARNING : type of input 3 of step 11568 doesn't seem to be define in the database( WARNING : output 0 of step 11568 have datatype=10 whereas input 0 of step 11587 have datatype=18 WARNING : type of input 5 of step 11571 doesn't seem to be define in the database( WARNING : output 0 of step 11587 have datatype=11 whereas input 5 of step 11571 have datatype=None WARNING : output 0 of step 11564 have datatype=1 whereas input 0 of step 11565 have datatype=2 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`=27679553 AND mptpi.`type`=3327 To do find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27679965_10-10-2025_09_14_06.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27679965 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27680218 order by id desc limit 1 Qualite : 0.046820308355316274 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27680363_10-10-2025_08_13_01.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27680363 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 ! 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 11500 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11508 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11509 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11504 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11504 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11507 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11507 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11576 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11576 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11503 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11502 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11502 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11511 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 : type of output 1 of step 11503 doesn't seem to be define in the database( WARNING : type of input 3 of step 11502 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11500 doesn't seem to be define in the database( WARNING : type of input 2 of step 11504 doesn't seem to be define in the database( WARNING : output 1 of step 11500 have datatype=2 whereas input 1 of step 11507 have datatype=7 WARNING : type of output 2 of step 11507 doesn't seem to be define in the database( WARNING : type of input 1 of step 11501 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11503 have datatype=10 whereas input 3 of step 11510 have datatype=6 WARNING : type of input 2 of step 11576 doesn't seem to be define in the database( WARNING : output 1 of step 11501 have datatype=7 whereas input 2 of step 11576 have datatype=None WARNING : type of output 3 of step 11576 doesn't seem to be define in the database( WARNING : type of input 1 of step 11503 doesn't seem to be define in the database( WARNING : output 0 of step 11503 have datatype=10 whereas input 0 of step 11582 have datatype=18 WARNING : type of input 5 of step 11510 doesn't seem to be define in the database( WARNING : output 0 of step 11582 have datatype=11 whereas input 5 of step 11510 have datatype=None WARNING : type of output 1 of step 11508 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : type of output 1 of step 11509 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : output 0 of step 11507 have datatype=1 whereas input 0 of step 11501 have datatype=2 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`=27680363 AND mptpi.`type`=4207 To do Qualite : 0.047776068738034 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27680924_10-10-2025_09_16_01.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27680924 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 ! 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 11560 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11567 mask_detect have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11567 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11563 crop_condition is not consistent : 4 used against 2 in the step definition ! Step 11563 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11564 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11564 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11565 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11565 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11573 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11573 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11568 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11568 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11566 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11566 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! 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 ! WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 1 of step 11560 have datatype=2 whereas input 1 of step 11564 have datatype=7 WARNING : type of output 2 of step 11564 doesn't seem to be define in the database( WARNING : type of input 1 of step 11565 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11567 doesn't seem to be define in the database( WARNING : type of input 3 of step 11563 doesn't seem to be define in the database( WARNING : type of output 3 of step 11564 doesn't seem to be define in the database( WARNING : type of input 1 of step 11568 doesn't seem to be define in the database( WARNING : type of output 1 of step 11568 doesn't seem to be define in the database( WARNING : type of input 3 of step 11566 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 0 of step 11570 have datatype=6 whereas input 2 of step 11563 have datatype=None WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 0 of step 11569 have datatype=6 whereas input 2 of step 11563 have datatype=None WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 1 of step 11570 doesn't seem to be define in the database( WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 1 of step 11569 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11568 have datatype=10 whereas input 3 of step 11571 have datatype=6 WARNING : type of input 2 of step 11573 doesn't seem to be define in the database( WARNING : output 1 of step 11565 have datatype=7 whereas input 2 of step 11573 have datatype=None WARNING : type of output 3 of step 11573 doesn't seem to be define in the database( WARNING : type of input 3 of step 11568 doesn't seem to be define in the database( WARNING : output 0 of step 11568 have datatype=10 whereas input 0 of step 11587 have datatype=18 WARNING : type of input 5 of step 11571 doesn't seem to be define in the database( WARNING : output 0 of step 11587 have datatype=11 whereas input 5 of step 11571 have datatype=None WARNING : output 0 of step 11564 have datatype=1 whereas input 0 of step 11565 have datatype=2 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`=27680924 AND mptpi.`type`=3327 To do Qualite : 0.0566785656898601 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27681304_10-10-2025_09_48_41.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27681304 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 ! 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 11524 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11533 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11532 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11528 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11528 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11531 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11531 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11525 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11525 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11578 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11578 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11527 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11526 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11526 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11535 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 : type of output 1 of step 11527 doesn't seem to be define in the database( WARNING : type of input 3 of step 11526 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11524 doesn't seem to be define in the database( WARNING : type of input 2 of step 11528 doesn't seem to be define in the database( WARNING : output 1 of step 11524 have datatype=2 whereas input 1 of step 11531 have datatype=7 WARNING : type of output 2 of step 11531 doesn't seem to be define in the database( WARNING : type of input 1 of step 11525 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11527 have datatype=10 whereas input 3 of step 11534 have datatype=6 WARNING : type of input 2 of step 11578 doesn't seem to be define in the database( WARNING : output 1 of step 11525 have datatype=7 whereas input 2 of step 11578 have datatype=None WARNING : type of output 3 of step 11578 doesn't seem to be define in the database( WARNING : type of input 1 of step 11527 doesn't seem to be define in the database( WARNING : output 0 of step 11527 have datatype=10 whereas input 0 of step 11584 have datatype=18 WARNING : type of input 5 of step 11534 doesn't seem to be define in the database( WARNING : output 0 of step 11584 have datatype=11 whereas input 5 of step 11534 have datatype=None WARNING : type of output 1 of step 11533 doesn't seem to be define in the database( WARNING : type of input 3 of step 11528 doesn't seem to be define in the database( WARNING : type of output 1 of step 11532 doesn't seem to be define in the database( WARNING : type of input 3 of step 11528 doesn't seem to be define in the database( WARNING : output 0 of step 11531 have datatype=1 whereas input 0 of step 11525 have datatype=2 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`=27681304 AND mptpi.`type`=4211 To do find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27681854_10-10-2025_09_05_30.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27681854 order by id desc limit 1 Qualite : 0.047250673249276 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27681984_10-10-2025_08_43_18.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27681984 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 ! 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 11500 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11508 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11509 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11504 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11504 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11507 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11507 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11576 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11576 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11503 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11502 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11502 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11511 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 : type of output 1 of step 11503 doesn't seem to be define in the database( WARNING : type of input 3 of step 11502 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11500 doesn't seem to be define in the database( WARNING : type of input 2 of step 11504 doesn't seem to be define in the database( WARNING : output 1 of step 11500 have datatype=2 whereas input 1 of step 11507 have datatype=7 WARNING : type of output 2 of step 11507 doesn't seem to be define in the database( WARNING : type of input 1 of step 11501 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11503 have datatype=10 whereas input 3 of step 11510 have datatype=6 WARNING : type of input 2 of step 11576 doesn't seem to be define in the database( WARNING : output 1 of step 11501 have datatype=7 whereas input 2 of step 11576 have datatype=None WARNING : type of output 3 of step 11576 doesn't seem to be define in the database( WARNING : type of input 1 of step 11503 doesn't seem to be define in the database( WARNING : output 0 of step 11503 have datatype=10 whereas input 0 of step 11582 have datatype=18 WARNING : type of input 5 of step 11510 doesn't seem to be define in the database( WARNING : output 0 of step 11582 have datatype=11 whereas input 5 of step 11510 have datatype=None WARNING : type of output 1 of step 11508 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : type of output 1 of step 11509 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : output 0 of step 11507 have datatype=1 whereas input 0 of step 11501 have datatype=2 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`=27681984 AND mptpi.`type`=4207 To do find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27682610 order by id desc limit 1 Qualite : 0.06944022370679406 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27683341_10-10-2025_09_06_20.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27683341 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 ! 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 11524 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11533 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11532 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11528 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11528 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11531 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11531 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11525 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11525 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11578 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11578 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11527 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11526 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11526 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11535 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 : type of output 1 of step 11527 doesn't seem to be define in the database( WARNING : type of input 3 of step 11526 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11524 doesn't seem to be define in the database( WARNING : type of input 2 of step 11528 doesn't seem to be define in the database( WARNING : output 1 of step 11524 have datatype=2 whereas input 1 of step 11531 have datatype=7 WARNING : type of output 2 of step 11531 doesn't seem to be define in the database( WARNING : type of input 1 of step 11525 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11527 have datatype=10 whereas input 3 of step 11534 have datatype=6 WARNING : type of input 2 of step 11578 doesn't seem to be define in the database( WARNING : output 1 of step 11525 have datatype=7 whereas input 2 of step 11578 have datatype=None WARNING : type of output 3 of step 11578 doesn't seem to be define in the database( WARNING : type of input 1 of step 11527 doesn't seem to be define in the database( WARNING : output 0 of step 11527 have datatype=10 whereas input 0 of step 11584 have datatype=18 WARNING : type of input 5 of step 11534 doesn't seem to be define in the database( WARNING : output 0 of step 11584 have datatype=11 whereas input 5 of step 11534 have datatype=None WARNING : type of output 1 of step 11533 doesn't seem to be define in the database( WARNING : type of input 3 of step 11528 doesn't seem to be define in the database( WARNING : type of output 1 of step 11532 doesn't seem to be define in the database( WARNING : type of input 3 of step 11528 doesn't seem to be define in the database( WARNING : output 0 of step 11531 have datatype=1 whereas input 0 of step 11525 have datatype=2 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`=27683341 AND mptpi.`type`=4211 To do Qualite : 0.030589273083847745 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27683972_10-10-2025_09_19_01.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27683972 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 ! 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 11500 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11508 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11509 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11504 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11504 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11507 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11507 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11576 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11576 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11503 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11502 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11502 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11511 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 : type of output 1 of step 11503 doesn't seem to be define in the database( WARNING : type of input 3 of step 11502 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11500 doesn't seem to be define in the database( WARNING : type of input 2 of step 11504 doesn't seem to be define in the database( WARNING : output 1 of step 11500 have datatype=2 whereas input 1 of step 11507 have datatype=7 WARNING : type of output 2 of step 11507 doesn't seem to be define in the database( WARNING : type of input 1 of step 11501 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11503 have datatype=10 whereas input 3 of step 11510 have datatype=6 WARNING : type of input 2 of step 11576 doesn't seem to be define in the database( WARNING : output 1 of step 11501 have datatype=7 whereas input 2 of step 11576 have datatype=None WARNING : type of output 3 of step 11576 doesn't seem to be define in the database( WARNING : type of input 1 of step 11503 doesn't seem to be define in the database( WARNING : output 0 of step 11503 have datatype=10 whereas input 0 of step 11582 have datatype=18 WARNING : type of input 5 of step 11510 doesn't seem to be define in the database( WARNING : output 0 of step 11582 have datatype=11 whereas input 5 of step 11510 have datatype=None WARNING : type of output 1 of step 11508 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : type of output 1 of step 11509 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : output 0 of step 11507 have datatype=1 whereas input 0 of step 11501 have datatype=2 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`=27683972 AND mptpi.`type`=4207 To do find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27686506 order by id desc limit 1 Qualite : 0.06810780256636637 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27688836_10-10-2025_10_19_11.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27688836 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 ! 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 11524 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11533 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11532 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11528 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11528 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11531 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11531 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11525 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11525 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11578 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11578 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11527 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11526 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11526 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11535 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 : type of output 1 of step 11527 doesn't seem to be define in the database( WARNING : type of input 3 of step 11526 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11524 doesn't seem to be define in the database( WARNING : type of input 2 of step 11528 doesn't seem to be define in the database( WARNING : output 1 of step 11524 have datatype=2 whereas input 1 of step 11531 have datatype=7 WARNING : type of output 2 of step 11531 doesn't seem to be define in the database( WARNING : type of input 1 of step 11525 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11527 have datatype=10 whereas input 3 of step 11534 have datatype=6 WARNING : type of input 2 of step 11578 doesn't seem to be define in the database( WARNING : output 1 of step 11525 have datatype=7 whereas input 2 of step 11578 have datatype=None WARNING : type of output 3 of step 11578 doesn't seem to be define in the database( WARNING : type of input 1 of step 11527 doesn't seem to be define in the database( WARNING : output 0 of step 11527 have datatype=10 whereas input 0 of step 11584 have datatype=18 WARNING : type of input 5 of step 11534 doesn't seem to be define in the database( WARNING : output 0 of step 11584 have datatype=11 whereas input 5 of step 11534 have datatype=None WARNING : type of output 1 of step 11533 doesn't seem to be define in the database( WARNING : type of input 3 of step 11528 doesn't seem to be define in the database( WARNING : type of output 1 of step 11532 doesn't seem to be define in the database( WARNING : type of input 3 of step 11528 doesn't seem to be define in the database( WARNING : output 0 of step 11531 have datatype=1 whereas input 0 of step 11525 have datatype=2 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`=27688836 AND mptpi.`type`=4211 To do Qualite : 0.11078185915006172 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27688837_10-10-2025_10_23_56.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27688837 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 ! 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 11560 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11567 mask_detect have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11567 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11563 crop_condition is not consistent : 4 used against 2 in the step definition ! Step 11563 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11564 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11564 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11565 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11565 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11573 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11573 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11568 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11568 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11566 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11566 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! 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 ! WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 1 of step 11560 have datatype=2 whereas input 1 of step 11564 have datatype=7 WARNING : type of output 2 of step 11564 doesn't seem to be define in the database( WARNING : type of input 1 of step 11565 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11567 doesn't seem to be define in the database( WARNING : type of input 3 of step 11563 doesn't seem to be define in the database( WARNING : type of output 3 of step 11564 doesn't seem to be define in the database( WARNING : type of input 1 of step 11568 doesn't seem to be define in the database( WARNING : type of output 1 of step 11568 doesn't seem to be define in the database( WARNING : type of input 3 of step 11566 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 0 of step 11570 have datatype=6 whereas input 2 of step 11563 have datatype=None WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 0 of step 11569 have datatype=6 whereas input 2 of step 11563 have datatype=None WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 1 of step 11570 doesn't seem to be define in the database( WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 1 of step 11569 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11568 have datatype=10 whereas input 3 of step 11571 have datatype=6 WARNING : type of input 2 of step 11573 doesn't seem to be define in the database( WARNING : output 1 of step 11565 have datatype=7 whereas input 2 of step 11573 have datatype=None WARNING : type of output 3 of step 11573 doesn't seem to be define in the database( WARNING : type of input 3 of step 11568 doesn't seem to be define in the database( WARNING : output 0 of step 11568 have datatype=10 whereas input 0 of step 11587 have datatype=18 WARNING : type of input 5 of step 11571 doesn't seem to be define in the database( WARNING : output 0 of step 11587 have datatype=11 whereas input 5 of step 11571 have datatype=None WARNING : output 0 of step 11564 have datatype=1 whereas input 0 of step 11565 have datatype=2 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`=27688837 AND mptpi.`type`=3327 To do NUMBER BATCH : 0 # DISPLAY ALL COLLECTED DATA : {'10102025': {'nb_upload': 7, 'nb_taggue_class': 0, 'nb_taggue_densite': 0}} Inside saveOutput : final : True verbose : 0 saveOutput not yet implemented for datou_step.type : split_time_score we use saveGeneral [1388607356, 1388607351, 1388607327, 1388607326, 1388607251, 1388607246, 1388607225] Looping around the photos to save general results len do output : 1 /27677754Didn'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 ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607356', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607351', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607327', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607326', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607251', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607246', None, None, None, None, None, '3919092') ('3995', None, None, None, None, None, None, None, '3919092') ('3995', '27677754', '1388607225', None, None, None, None, None, '3919092') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 8 time used for this insertion : 0.035382747650146484 save_final save missing photos in datou_result : time spend for datou_step_exec : 19.35989785194397 time spend to save output : 0.03564023971557617 total time spend for step 13 : 19.395538091659546 caffe_path_current : About to save ! 2 After save, about to update current ! ret : 2 len(input) + len(total_photo_id_missing) : 7 set_done_treatment 214.75user 101.04system 6:58.84elapsed 75%CPU (0avgtext+0avgdata 6667552maxresident)k 765424inputs+103856outputs (2065major+18692323minor)pagefaults 0swaps