python /home/admin/mtr/script_for_cron.py -j datou_current3 -m 20 -a ' -a 3318 ' -s datou_3318 -M 0 -S 0 -U 95,95,120 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/caffe_cuda8_python3/python', '/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', '/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 : 1294870 load datou : 3318 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of 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 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( 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 : chemin de la photo was removed should we ? (photo_id, hashtag_id, score_max) was removed should we ? [(photo_id, hashtag_id, hashtag_type, x0, x1, y0, y1, score, seg_temp, polygons), ...] was removed should we ? chemin de la photo was removed should we ? [ (photo_id_loc, hashtag_id, hashtag_type, x0, x1, y0, y1, score, None), ...] was removed should we ? chemin de la photo was removed should we ? id de la photo (peut être local ou global) was removed should we ? chemin de la photo was removed should we ? (x0, y0, x1, y1) was removed should we ? chemin de la photo was removed should we ? donnée sous forme de texte was removed should we ? [ (photo_id, photo_id_loc, hashtag_type, x0, x1, y0, y1, score), ...] was removed should we ? None was removed should we ? donnée sous forme de texte was removed should we ? (photo_id, hashtag_id, score_max) was removed should we ? id de la photo (peut être local ou global) was removed should we ? donnée sous forme de texte was removed should we ? donnée sous forme de texte was removed should we ? donnée sous forme de texte was removed should we ? chemin de la photo was removed should we ? (photo_id, hashtag_id, score_max) was removed should we ? chemin de la photo was removed should we ? (photo_id, hashtag_id, score_max) was removed should we ? None was removed should we ? donnée sous forme de nombre was removed should we ? (photo_id, hashtag_id, score_max) was removed should we ? (photo_id, hashtag_id, score_max) was removed should we ? (photo_id, hashtag_id, score_max) was removed should we ? (photo_id, hashtag_id, score_max) was removed should we ? (photo_id, hashtag_id, score_max) was removed should we ? donnée sous forme de texte was removed should we ? None was removed should we ? donnée sous forme de texte was removed should we ? [ptf_id0,ptf_id1...] was removed should we ? FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (5275, 'learn_RUBBIA_REFUS_AMIENS_23', 16384, 25088, 'learn_RUBBIA_REFUS_AMIENS_23', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 1, datetime.datetime(2021, 4, 23, 14, 19, 39), datetime.datetime(2021, 4, 23, 14, 19, 39)) load thcls load THCL from format json or kwargs add thcl : 2847 in CacheModelConfig load pdts add pdt : 5275 in CacheModelConfig 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 : 3318, datou_cur_ids : ['3759738'] with mtr_portfolio_ids : ['27102182'] and first list_photo_ids : [] new path : /proc/1294870/ 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 ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of 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 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! List Step Type Loaded in datou : mask_detect, crop_condition, rle_unique_nms_with_priority, ventilate_hashtags_in_portfolio, final, blur_detection, brightness, velours_tree, send_mail_cod, split_time_score over limit max, limiting to limit_max 40 list_input_json : [] origin We have 1 , BFBFBFBFBFBFBFBFBFBFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 10 ; length of list_pids : 10 ; length of list_args : 10 time to download the photos : 2.2761542797088623 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 : 10 step1:mask_detect Mon Sep 22 20:30:33 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 : 10362 max_wait_temp : 1 max_wait : 0 gpu_flag : 0 2025-09-22 20:30:36.303785: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2025-09-22 20:30:36.328688: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3492910000 Hz 2025-09-22 20:30:36.330756: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f59ec000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-09-22 20:30:36.330796: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-09-22 20:30:36.334431: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-09-22 20:30:36.483236: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x438ed2a0 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-09-22 20:30:36.483290: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-09-22 20:30:36.484741: 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 2025-09-22 20:30:36.485124: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-09-22 20:30:36.487937: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-09-22 20:30:36.490564: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-09-22 20:30:36.491072: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-09-22 20:30:36.494103: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-09-22 20:30:36.495193: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-09-22 20:30:36.499349: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-09-22 20:30:36.500918: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-09-22 20:30:36.501002: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-09-22 20:30:36.501795: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-09-22 20:30:36.501811: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-09-22 20:30:36.501820: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-09-22 20:30:36.504071: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 9454 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. 2025-09-22 20:30:36.849935: 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 2025-09-22 20:30:36.850075: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-09-22 20:30:36.850102: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-09-22 20:30:36.850127: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-09-22 20:30:36.850151: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-09-22 20:30:36.850173: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-09-22 20:30:36.850196: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-09-22 20:30:36.850219: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-09-22 20:30:36.852022: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-09-22 20:30:36.853568: 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 2025-09-22 20:30:36.853661: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-09-22 20:30:36.853678: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-09-22 20:30:36.853693: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-09-22 20:30:36.853707: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-09-22 20:30:36.853722: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-09-22 20:30:36.853736: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-09-22 20:30:36.853751: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-09-22 20:30:36.855086: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-09-22 20:30:36.855136: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-09-22 20:30:36.855145: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-09-22 20:30:36.855154: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-09-22 20:30:36.856628: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 9454 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:41:00.0, compute capability: 7.5) Using TensorFlow backend. WARNING:tensorflow:From /home/admin/workarea/install/Mask_RCNN/model.py:396: calling crop_and_resize_v1 (from tensorflow.python.ops.image_ops_impl) with box_ind is deprecated and will be removed in a future version. Instructions for updating: box_ind is deprecated, use box_indices instead WARNING:tensorflow:From /home/admin/workarea/install/Mask_RCNN/model.py:703: to_int32 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.cast` instead. WARNING:tensorflow:From /home/admin/workarea/install/Mask_RCNN/model.py:729: to_float (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.cast` instead. Inside mask_sub_process Inside mask_detect About to load cache.load_thcl_param To do loadFromThcl(), then load ParamDescType : thcl2847 thcls : [{'id': 2847, 'mtr_user_id': 31, 'name': 'learn_RUBBIA_REFUS_AMIENS_23', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'photo_desc_type': 5275, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'}] thcl {'id': 2847, 'mtr_user_id': 31, 'name': 'learn_RUBBIA_REFUS_AMIENS_23', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'photo_desc_type': 5275, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'} Update svm_hashtag_type_desc : 5275 FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (5275, 'learn_RUBBIA_REFUS_AMIENS_23', 16384, 25088, 'learn_RUBBIA_REFUS_AMIENS_23', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 1, datetime.datetime(2021, 4, 23, 14, 19, 39), datetime.datetime(2021, 4, 23, 14, 19, 39)) {'thcl': {'id': 2847, 'mtr_user_id': 31, 'name': 'learn_RUBBIA_REFUS_AMIENS_23', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'photo_desc_type': 5275, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'}, 'list_hashtags': ['background', 'papier', 'carton', 'metal', 'pet_clair', 'autre', 'pehd', 'pet_fonce', 'environnement'], 'list_hashtags_csv': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'svm_hashtag_type_desc': 5275, 'photo_desc_type': 5275, 'pb_hashtag_id_or_classifier': 0} list_class_names : ['background', 'papier', 'carton', 'metal', 'pet_clair', 'autre', 'pehd', 'pet_fonce', 'environnement'] Configurations: BACKBONE resnet101 BACKBONE_SHAPES [[160 160] [ 80 80] [ 40 40] [ 20 20] [ 10 10]] BACKBONE_STRIDES [4, 8, 16, 32, 64] BATCH_SIZE 1 BBOX_STD_DEV [0.1 0.1 0.2 0.2] DETECTION_MAX_INSTANCES 100 DETECTION_MIN_CONFIDENCE 0.3 DETECTION_NMS_THRESHOLD 0.3 GPU_COUNT 1 IMAGES_PER_GPU 1 IMAGE_MAX_DIM 640 IMAGE_MIN_DIM 640 IMAGE_PADDING True IMAGE_SHAPE [640 640 3] LEARNING_MOMENTUM 0.9 LEARNING_RATE 0.001 LOSS_WEIGHTS {'rpn_class_loss': 1.0, 'rpn_bbox_loss': 1.0, 'mrcnn_class_loss': 1.0, 'mrcnn_bbox_loss': 1.0, 'mrcnn_mask_loss': 1.0} MASK_POOL_SIZE 14 MASK_SHAPE [28, 28] MAX_GT_INSTANCES 100 MEAN_PIXEL [123.7 116.8 103.9] MINI_MASK_SHAPE (56, 56) NAME learn_RUBBIA_REFUS_AMIENS_23 NUM_CLASSES 9 POOL_SIZE 7 POST_NMS_ROIS_INFERENCE 1000 POST_NMS_ROIS_TRAINING 2000 ROI_POSITIVE_RATIO 0.33 RPN_ANCHOR_RATIOS [0.5, 1, 2] RPN_ANCHOR_SCALES (16, 32, 64, 128, 256) RPN_ANCHOR_STRIDE 1 RPN_BBOX_STD_DEV [0.1 0.1 0.2 0.2] RPN_NMS_THRESHOLD 0.7 RPN_TRAIN_ANCHORS_PER_IMAGE 256 STEPS_PER_EPOCH 1000 TRAIN_ROIS_PER_IMAGE 200 USE_MINI_MASK True USE_RPN_ROIS True VALIDATION_STEPS 50 WEIGHT_DECAY 0.0001 model_param file didn't exist model_name : learn_RUBBIA_REFUS_AMIENS_23 model_type : mask_rcnn list file need : ['mask_model.h5'] file exist in s3 : ['mask_model.h5'] file manque in s3 : [] 2025-09-22 20:30:48.511762: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-09-22 20:30:48.796090: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 local folder : /data/models_weight/learn_RUBBIA_REFUS_AMIENS_23 /data/models_weight/learn_RUBBIA_REFUS_AMIENS_23/mask_model.h5 size_local : 256009536 size in s3 : 256009536 create time local : 2021-08-09 09:43:22 create time in s3 : 2021-08-06 18:54:04 mask_model.h5 already exist and didn't need to update list_images length : 10 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, 17) min: 0.00000 max: 3840.00000 nb d'objets trouves : 22 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, 17) min: 0.00000 max: 3840.00000 nb d'objets trouves : 15 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, 17) min: 0.00000 max: 3840.00000 nb d'objets trouves : 12 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, 17) min: 0.00000 max: 3840.00000 nb d'objets trouves : 20 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, 17) min: 0.00000 max: 3840.00000 nb d'objets trouves : 26 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, 17) min: 0.00000 max: 3840.00000 nb d'objets trouves : 15 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, 17) min: 0.00000 max: 3840.00000 nb d'objets trouves : 20 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, 17) min: 0.00000 max: 3840.00000 nb d'objets trouves : 23 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, 17) min: 0.00000 max: 3840.00000 nb d'objets trouves : 21 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, 17) min: 0.00000 max: 3840.00000 nb d'objets trouves : 8 Detection mask done ! Trying to reset tf kernel 1295665 begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 5073 tf kernel not reseted sub process len(results) : 10 len(list_Values) 0 None max_time_sub_proc : 3600 parent process len(results) : 10 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 : 10362 list_Values should be empty [] To do loadFromThcl(), then load ParamDescType : thcl2847 Catched exception ! Connect or reconnect ! thcls : [{'id': 2847, 'mtr_user_id': 31, 'name': 'learn_RUBBIA_REFUS_AMIENS_23', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'photo_desc_type': 5275, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'}] thcl {'id': 2847, 'mtr_user_id': 31, 'name': 'learn_RUBBIA_REFUS_AMIENS_23', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'photo_desc_type': 5275, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'} Update svm_hashtag_type_desc : 5275 ['background', 'papier', 'carton', 'metal', 'pet_clair', 'autre', 'pehd', 'pet_fonce', 'environnement'] time for calcul the mask position with numpy : 0.0006744861602783203 nb_pixel_total : 15297 time to create 1 rle with old method : 0.017953157424926758 length of segment : 131 time for calcul the mask position with numpy : 0.0047152042388916016 nb_pixel_total : 140877 time to create 1 rle with old method : 0.17069649696350098 length of segment : 518 time for calcul the mask position with numpy : 0.0021822452545166016 nb_pixel_total : 89610 time to create 1 rle with old method : 0.10584664344787598 length of segment : 315 time for calcul the mask position with numpy : 0.0004336833953857422 nb_pixel_total : 12291 time to create 1 rle with old method : 0.014850378036499023 length of segment : 104 time for calcul the mask position with numpy : 0.0002956390380859375 nb_pixel_total : 7226 time to create 1 rle with old method : 0.008461952209472656 length of segment : 113 time for calcul the mask position with numpy : 0.0012271404266357422 nb_pixel_total : 35493 time to create 1 rle with old method : 0.04141569137573242 length of segment : 223 time for calcul the mask position with numpy : 0.00115966796875 nb_pixel_total : 65024 time to create 1 rle with old method : 0.0732264518737793 length of segment : 319 time for calcul the mask position with numpy : 0.0007872581481933594 nb_pixel_total : 40849 time to create 1 rle with old method : 0.04723024368286133 length of segment : 215 time for calcul the mask position with numpy : 0.0003376007080078125 nb_pixel_total : 15408 time to create 1 rle with old method : 0.01793956756591797 length of segment : 128 time for calcul the mask position with numpy : 0.0007281303405761719 nb_pixel_total : 27088 time to create 1 rle with old method : 0.030928373336791992 length of segment : 347 time for calcul the mask position with numpy : 0.0008080005645751953 nb_pixel_total : 27809 time to create 1 rle with old method : 0.03284335136413574 length of segment : 354 time for calcul the mask position with numpy : 0.0006134510040283203 nb_pixel_total : 25512 time to create 1 rle with old method : 0.030927419662475586 length of segment : 236 time for calcul the mask position with numpy : 0.00023555755615234375 nb_pixel_total : 7243 time to create 1 rle with old method : 0.008716821670532227 length of segment : 90 time for calcul the mask position with numpy : 0.0008690357208251953 nb_pixel_total : 43175 time to create 1 rle with old method : 0.04996538162231445 length of segment : 210 time for calcul the mask position with numpy : 0.0003147125244140625 nb_pixel_total : 9950 time to create 1 rle with old method : 0.011960506439208984 length of segment : 106 time for calcul the mask position with numpy : 0.00018644332885742188 nb_pixel_total : 4475 time to create 1 rle with old method : 0.0054662227630615234 length of segment : 82 time for calcul the mask position with numpy : 0.0011279582977294922 nb_pixel_total : 51570 time to create 1 rle with old method : 0.0603947639465332 length of segment : 350 time for calcul the mask position with numpy : 0.017087936401367188 nb_pixel_total : 329487 time to create 1 rle with new method : 0.0636448860168457 length of segment : 964 time for calcul the mask position with numpy : 0.0001773834228515625 nb_pixel_total : 6528 time to create 1 rle with old method : 0.007659435272216797 length of segment : 74 time for calcul the mask position with numpy : 0.00022411346435546875 nb_pixel_total : 8728 time to create 1 rle with old method : 0.01059103012084961 length of segment : 97 time for calcul the mask position with numpy : 0.0008699893951416016 nb_pixel_total : 35186 time to create 1 rle with old method : 0.046105146408081055 length of segment : 313 time for calcul the mask position with numpy : 0.010409116744995117 nb_pixel_total : 335667 time to create 1 rle with new method : 0.3949615955352783 length of segment : 966 time for calcul the mask position with numpy : 0.001497507095336914 nb_pixel_total : 65033 time to create 1 rle with old method : 0.08082318305969238 length of segment : 308 time for calcul the mask position with numpy : 0.004428863525390625 nb_pixel_total : 137694 time to create 1 rle with old method : 0.15612411499023438 length of segment : 552 time for calcul the mask position with numpy : 0.0015337467193603516 nb_pixel_total : 29624 time to create 1 rle with old method : 0.03467226028442383 length of segment : 220 time for calcul the mask position with numpy : 0.0019483566284179688 nb_pixel_total : 37564 time to create 1 rle with old method : 0.05520510673522949 length of segment : 404 time for calcul the mask position with numpy : 0.0005831718444824219 nb_pixel_total : 10699 time to create 1 rle with old method : 0.014330148696899414 length of segment : 105 time for calcul the mask position with numpy : 0.0010771751403808594 nb_pixel_total : 14756 time to create 1 rle with old method : 0.020994186401367188 length of segment : 106 time for calcul the mask position with numpy : 0.0022881031036376953 nb_pixel_total : 25681 time to create 1 rle with old method : 0.03781843185424805 length of segment : 169 time for calcul the mask position with numpy : 0.001512289047241211 nb_pixel_total : 46108 time to create 1 rle with old method : 0.05542421340942383 length of segment : 387 time for calcul the mask position with numpy : 0.000629425048828125 nb_pixel_total : 27847 time to create 1 rle with old method : 0.03251028060913086 length of segment : 296 time for calcul the mask position with numpy : 0.003603219985961914 nb_pixel_total : 113471 time to create 1 rle with old method : 0.1387789249420166 length of segment : 559 time for calcul the mask position with numpy : 0.013980388641357422 nb_pixel_total : 280369 time to create 1 rle with new method : 0.0589451789855957 length of segment : 732 time for calcul the mask position with numpy : 0.0008175373077392578 nb_pixel_total : 29059 time to create 1 rle with old method : 0.03344106674194336 length of segment : 245 time for calcul the mask position with numpy : 0.002935647964477539 nb_pixel_total : 83918 time to create 1 rle with old method : 0.10001897811889648 length of segment : 402 time for calcul the mask position with numpy : 0.0009479522705078125 nb_pixel_total : 23212 time to create 1 rle with old method : 0.030622243881225586 length of segment : 194 time for calcul the mask position with numpy : 0.0046863555908203125 nb_pixel_total : 138468 time to create 1 rle with old method : 0.15822649002075195 length of segment : 527 time for calcul the mask position with numpy : 0.0006532669067382812 nb_pixel_total : 11002 time to create 1 rle with old method : 0.012991666793823242 length of segment : 139 time for calcul the mask position with numpy : 0.0007491111755371094 nb_pixel_total : 15224 time to create 1 rle with old method : 0.018035411834716797 length of segment : 140 time for calcul the mask position with numpy : 0.004259824752807617 nb_pixel_total : 125162 time to create 1 rle with old method : 0.14122796058654785 length of segment : 343 time for calcul the mask position with numpy : 0.0022690296173095703 nb_pixel_total : 67857 time to create 1 rle with old method : 0.07693934440612793 length of segment : 351 time for calcul the mask position with numpy : 0.0054743289947509766 nb_pixel_total : 167675 time to create 1 rle with new method : 0.013121604919433594 length of segment : 484 time for calcul the mask position with numpy : 0.001687765121459961 nb_pixel_total : 60777 time to create 1 rle with old method : 0.07103276252746582 length of segment : 288 time for calcul the mask position with numpy : 0.002248048782348633 nb_pixel_total : 62020 time to create 1 rle with old method : 0.07343196868896484 length of segment : 485 time for calcul the mask position with numpy : 0.0025527477264404297 nb_pixel_total : 82607 time to create 1 rle with old method : 0.09525799751281738 length of segment : 369 time for calcul the mask position with numpy : 0.0006246566772460938 nb_pixel_total : 18489 time to create 1 rle with old method : 0.021700143814086914 length of segment : 145 time for calcul the mask position with numpy : 0.0034003257751464844 nb_pixel_total : 115146 time to create 1 rle with old method : 0.12807059288024902 length of segment : 552 time for calcul the mask position with numpy : 0.0007185935974121094 nb_pixel_total : 17886 time to create 1 rle with old method : 0.02182292938232422 length of segment : 102 time for calcul the mask position with numpy : 0.006361722946166992 nb_pixel_total : 175031 time to create 1 rle with new method : 0.010709524154663086 length of segment : 644 time for calcul the mask position with numpy : 0.005816459655761719 nb_pixel_total : 219575 time to create 1 rle with new method : 0.00917363166809082 length of segment : 597 time for calcul the mask position with numpy : 0.0017881393432617188 nb_pixel_total : 75032 time to create 1 rle with old method : 0.08653497695922852 length of segment : 321 time for calcul the mask position with numpy : 0.0010063648223876953 nb_pixel_total : 19477 time to create 1 rle with old method : 0.022433996200561523 length of segment : 271 time for calcul the mask position with numpy : 0.0030269622802734375 nb_pixel_total : 88971 time to create 1 rle with old method : 0.10150909423828125 length of segment : 357 time for calcul the mask position with numpy : 0.008179426193237305 nb_pixel_total : 271348 time to create 1 rle with new method : 0.016821622848510742 length of segment : 633 time for calcul the mask position with numpy : 0.003893136978149414 nb_pixel_total : 118916 time to create 1 rle with old method : 0.13589811325073242 length of segment : 475 time for calcul the mask position with numpy : 0.0013227462768554688 nb_pixel_total : 35632 time to create 1 rle with old method : 0.046950340270996094 length of segment : 219 time for calcul the mask position with numpy : 0.0034761428833007812 nb_pixel_total : 76688 time to create 1 rle with old method : 0.08667659759521484 length of segment : 527 time for calcul the mask position with numpy : 0.0007665157318115234 nb_pixel_total : 15602 time to create 1 rle with old method : 0.019049406051635742 length of segment : 172 time for calcul the mask position with numpy : 0.0015494823455810547 nb_pixel_total : 33679 time to create 1 rle with old method : 0.040007591247558594 length of segment : 369 time for calcul the mask position with numpy : 0.0028731822967529297 nb_pixel_total : 58461 time to create 1 rle with old method : 0.06892800331115723 length of segment : 422 time for calcul the mask position with numpy : 0.0009300708770751953 nb_pixel_total : 21085 time to create 1 rle with old method : 0.0247650146484375 length of segment : 174 time for calcul the mask position with numpy : 0.0010449886322021484 nb_pixel_total : 34069 time to create 1 rle with old method : 0.04996347427368164 length of segment : 204 time for calcul the mask position with numpy : 0.005537986755371094 nb_pixel_total : 79488 time to create 1 rle with old method : 0.09574437141418457 length of segment : 729 time for calcul the mask position with numpy : 0.0006251335144042969 nb_pixel_total : 10820 time to create 1 rle with old method : 0.016973495483398438 length of segment : 96 time for calcul the mask position with numpy : 0.0004980564117431641 nb_pixel_total : 11030 time to create 1 rle with old method : 0.014935493469238281 length of segment : 137 time for calcul the mask position with numpy : 0.0018887519836425781 nb_pixel_total : 44788 time to create 1 rle with old method : 0.05383706092834473 length of segment : 347 time for calcul the mask position with numpy : 0.006211519241333008 nb_pixel_total : 207143 time to create 1 rle with new method : 0.011200666427612305 length of segment : 581 time for calcul the mask position with numpy : 0.00899815559387207 nb_pixel_total : 320147 time to create 1 rle with new method : 0.03977036476135254 length of segment : 849 time for calcul the mask position with numpy : 0.0014584064483642578 nb_pixel_total : 29856 time to create 1 rle with old method : 0.03478431701660156 length of segment : 309 time for calcul the mask position with numpy : 0.0022611618041992188 nb_pixel_total : 119272 time to create 1 rle with old method : 0.1399679183959961 length of segment : 513 time for calcul the mask position with numpy : 0.003318309783935547 nb_pixel_total : 157387 time to create 1 rle with new method : 0.007000923156738281 length of segment : 406 time for calcul the mask position with numpy : 0.0008058547973632812 nb_pixel_total : 30007 time to create 1 rle with old method : 0.03423166275024414 length of segment : 227 time for calcul the mask position with numpy : 0.0010840892791748047 nb_pixel_total : 40495 time to create 1 rle with old method : 0.04565739631652832 length of segment : 365 time for calcul the mask position with numpy : 0.0013892650604248047 nb_pixel_total : 66418 time to create 1 rle with old method : 0.07499337196350098 length of segment : 361 time spent for convertir_results : 10.357027053833008 Inside saveOutput : final : False verbose : 0 eke 12-6-18 : saveMask need to be cleaned for new output ! Number saved : None batch 1 Loaded 74 chid ids of type : 3594 Number RLEs to save : 25164 save missing photos in datou_result : time spend for datou_step_exec : 76.91470193862915 time spend to save output : 1.6795952320098877 total time spend for step 1 : 78.59429717063904 step2:crop_condition Mon Sep 22 20:31:52 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 : 3594 Loading chi in step crop for list_pids : 10 ! batch 1 Loaded 74 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ begin to crop the class : papier param for this class : {'min_score': 0.7} filtre for class : papier hashtag_id of this class : 492668766 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 : 39 About to insert : list_path_to_insert length 39 new photo from crops ! About to upload 39 photos upload in portfolio : 3736932 init cache_photo without model_param we have 39 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1758565929_1294870 batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 39 photos in the portfolio 3736932 time of upload the photos Elapsed time : 10.290619611740112 we have finished the crop for the class : papier begin to crop the class : carton param for this class : {'min_score': 0.7} filtre for class : carton hashtag_id of this class : 492774966 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 : 8 About to insert : list_path_to_insert length 8 new photo from crops ! About to upload 8 photos upload in portfolio : 3736932 init cache_photo without model_param we have 8 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1758565944_1294870 batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 8 photos in the portfolio 3736932 time of upload the photos Elapsed time : 2.1948344707489014 we have finished the crop for the class : carton begin to crop the class : metal param for this class : {'min_score': 0.7} filtre for class : metal hashtag_id of this class : 492628673 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 : 6 About to insert : list_path_to_insert length 6 new photo from crops ! About to upload 6 photos upload in portfolio : 3736932 init cache_photo without model_param we have 6 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1758565949_1294870 batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 6 photos in the portfolio 3736932 time of upload the photos Elapsed time : 1.5333836078643799 we have finished the crop for the class : metal begin to crop the class : pet_clair param for this class : {'min_score': 0.7} filtre for class : pet_clair hashtag_id of this class : 2107755846 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 : 14 About to insert : list_path_to_insert length 14 new photo from crops ! About to upload 14 photos upload in portfolio : 3736932 init cache_photo without model_param we have 14 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1758565957_1294870 batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 14 photos in the portfolio 3736932 time of upload the photos Elapsed time : 3.723836660385132 we have finished the crop for the class : pet_clair begin to crop the class : autre param for this class : {'min_score': 0.7} filtre for class : autre hashtag_id of this class : 494826614 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 : 6 About to insert : list_path_to_insert length 6 new photo from crops ! About to upload 6 photos upload in portfolio : 3736932 init cache_photo without model_param we have 6 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1758565963_1294870 batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 6 photos in the portfolio 3736932 time of upload the photos Elapsed time : 1.8073463439941406 we have finished the crop for the class : autre begin to crop the class : pehd param for this class : {'min_score': 0.7} filtre for class : pehd hashtag_id of this class : 628944319 begin to crop the class : pet_fonce param for this class : {'min_score': 0.7} filtre for class : pet_fonce hashtag_id of this class : 2107755900 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 ! About to upload 1 photos upload in portfolio : 3736932 init cache_photo without model_param we have 1 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1758565967_1294870 batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 1 photos in the portfolio 3736932 time of upload the photos Elapsed time : 0.8764047622680664 we have finished the crop for the class : pet_fonce delete rles from all chi we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : crop_condition we use saveGeneral [1385498674, 1385498630, 1385498393, 1385498354, 1385498302, 1385498233, 1385498166, 1385498129, 1385497572, 1385497002] Looping around the photos to save general results len do output : 74 /1385516317Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516318Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516319Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516320Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516321Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516322Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516323Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516324Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516325Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516327Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516329Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516330Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516331Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516332Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516333Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516334Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516335Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516336Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516337Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516338Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516339Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516340Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516341Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516342Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516343Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516344Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516345Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516346Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516347Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516348Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516349Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516350Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516351Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516352Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516353Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516354Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516355Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516356Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516357Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516364Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516365Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516366Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516367Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516368Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516369Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516370Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516371Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516375Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516376Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516377Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516378Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516379Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516380Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516385Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516386Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516387Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516388Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516389Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516390Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516391Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516392Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516393Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516394Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516395Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516396Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516397Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516398Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516400Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516401Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516402Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516403Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516404Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516405Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385516406Didn'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 ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498674', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498630', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498393', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498354', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498302', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498233', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498166', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498129', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385497572', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385497002', None, None, None, None, None, '3759738') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 232 time used for this insertion : 0.0301663875579834 save_final save missing photos in datou_result : time spend for datou_step_exec : 56.002690076828 time spend to save output : 0.03389716148376465 total time spend for step 2 : 56.03658723831177 step3:rle_unique_nms_with_priority Mon Sep 22 20:32:48 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 We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array VR 22-3-18 : For now we do not clean correctly the datou structure Begin step rle-unique-nms batch 1 Loaded 74 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++nb_obj : 6 nb_hashtags : 3 time to prepare the origin masks : 2.229161500930786 time for calcul the mask position with numpy : 0.6889019012451172 nb_pixel_total : 7993606 time to create 1 rle with new method : 0.739511251449585 time for calcul the mask position with numpy : 0.0243685245513916 nb_pixel_total : 35493 time to create 1 rle with old method : 0.03808879852294922 time for calcul the mask position with numpy : 0.024785518646240234 nb_pixel_total : 7226 time to create 1 rle with old method : 0.00773310661315918 time for calcul the mask position with numpy : 0.024001359939575195 nb_pixel_total : 12291 time to create 1 rle with old method : 0.01299905776977539 time for calcul the mask position with numpy : 0.03904294967651367 nb_pixel_total : 89610 time to create 1 rle with old method : 0.10072946548461914 time for calcul the mask position with numpy : 0.05113816261291504 nb_pixel_total : 140877 time to create 1 rle with old method : 0.19670629501342773 time for calcul the mask position with numpy : 0.031301021575927734 nb_pixel_total : 15297 time to create 1 rle with old method : 0.0194699764251709 create new chi : 2.0400800704956055 time to delete rle : 0.0182802677154541 batch 1 Loaded 13 chid ids of type : 3594 ++++++Number RLEs to save : 4968 TO DO : save crop sub photo not yet done ! save time : 0.34929704666137695 nb_obj : 11 nb_hashtags : 4 time to prepare the origin masks : 5.5254106521606445 time for calcul the mask position with numpy : 0.6138772964477539 nb_pixel_total : 7976297 time to create 1 rle with new method : 0.8388872146606445 time for calcul the mask position with numpy : 0.024105310440063477 nb_pixel_total : 51570 time to create 1 rle with old method : 0.05666613578796387 time for calcul the mask position with numpy : 0.025089263916015625 nb_pixel_total : 4475 time to create 1 rle with old method : 0.005158901214599609 time for calcul the mask position with numpy : 0.030768871307373047 nb_pixel_total : 9950 time to create 1 rle with old method : 0.011490583419799805 time for calcul the mask position with numpy : 0.027951717376708984 nb_pixel_total : 43175 time to create 1 rle with old method : 0.04970502853393555 time for calcul the mask position with numpy : 0.03207135200500488 nb_pixel_total : 7243 time to create 1 rle with old method : 0.013443231582641602 time for calcul the mask position with numpy : 0.02797985076904297 nb_pixel_total : 25512 time to create 1 rle with old method : 0.03138160705566406 time for calcul the mask position with numpy : 0.02660512924194336 nb_pixel_total : 27809 time to create 1 rle with old method : 0.045744895935058594 time for calcul the mask position with numpy : 0.02912163734436035 nb_pixel_total : 27088 time to create 1 rle with old method : 0.029871463775634766 time for calcul the mask position with numpy : 0.026798009872436523 nb_pixel_total : 15408 time to create 1 rle with old method : 0.017605304718017578 time for calcul the mask position with numpy : 0.027100801467895508 nb_pixel_total : 40849 time to create 1 rle with old method : 0.05222320556640625 time for calcul the mask position with numpy : 0.030256032943725586 nb_pixel_total : 65024 time to create 1 rle with old method : 0.07465839385986328 create new chi : 2.1922128200531006 time to delete rle : 0.001264810562133789 batch 1 Loaded 23 chid ids of type : 3594 +++++++++++++++Number RLEs to save : 7034 TO DO : save crop sub photo not yet done ! save time : 0.48854517936706543 nb_obj : 6 nb_hashtags : 3 time to prepare the origin masks : 3.1816723346710205 time for calcul the mask position with numpy : 0.7280979156494141 nb_pixel_total : 7840733 time to create 1 rle with new method : 1.1111674308776855 time for calcul the mask position with numpy : 0.025554180145263672 nb_pixel_total : 65033 time to create 1 rle with old method : 0.0756382942199707 time for calcul the mask position with numpy : 0.025334835052490234 nb_pixel_total : 8705 time to create 1 rle with old method : 0.013054847717285156 time for calcul the mask position with numpy : 0.025736570358276367 nb_pixel_total : 35186 time to create 1 rle with old method : 0.039788246154785156 time for calcul the mask position with numpy : 0.027530193328857422 nb_pixel_total : 8728 time to create 1 rle with old method : 0.009726762771606445 time for calcul the mask position with numpy : 0.026033401489257812 nb_pixel_total : 6528 time to create 1 rle with old method : 0.00740814208984375 time for calcul the mask position with numpy : 0.029122352600097656 nb_pixel_total : 329487 time to create 1 rle with new method : 0.8051557540893555 create new chi : 3.0313236713409424 time to delete rle : 0.0009746551513671875 batch 1 Loaded 13 chid ids of type : 3594 ++++++Number RLEs to save : 6996 TO DO : save crop sub photo not yet done ! save time : 0.47528934478759766 nb_obj : 7 nb_hashtags : 4 time to prepare the origin masks : 3.970085382461548 time for calcul the mask position with numpy : 0.8041055202484131 nb_pixel_total : 7992274 time to create 1 rle with new method : 0.7010431289672852 time for calcul the mask position with numpy : 0.043267250061035156 nb_pixel_total : 46108 time to create 1 rle with old method : 0.05232858657836914 time for calcul the mask position with numpy : 0.041983604431152344 nb_pixel_total : 25681 time to create 1 rle with old method : 0.029358386993408203 time for calcul the mask position with numpy : 0.04034829139709473 nb_pixel_total : 14756 time to create 1 rle with old method : 0.016826629638671875 time for calcul the mask position with numpy : 0.038864850997924805 nb_pixel_total : 10699 time to create 1 rle with old method : 0.01223301887512207 time for calcul the mask position with numpy : 0.02616715431213379 nb_pixel_total : 37564 time to create 1 rle with old method : 0.04242062568664551 time for calcul the mask position with numpy : 0.025043249130249023 nb_pixel_total : 29624 time to create 1 rle with old method : 0.03335237503051758 time for calcul the mask position with numpy : 0.025994062423706055 nb_pixel_total : 137694 time to create 1 rle with old method : 0.1595447063446045 create new chi : 2.1465537548065186 time to delete rle : 0.001802206039428711 batch 1 Loaded 15 chid ids of type : 3594 +++++++Number RLEs to save : 6046 TO DO : save crop sub photo not yet done ! save time : 0.411144495010376 nb_obj : 9 nb_hashtags : 4 time to prepare the origin masks : 4.620742321014404 time for calcul the mask position with numpy : 0.4886932373046875 nb_pixel_total : 7571928 time to create 1 rle with new method : 0.7547261714935303 time for calcul the mask position with numpy : 0.03551626205444336 nb_pixel_total : 15224 time to create 1 rle with old method : 0.017054319381713867 time for calcul the mask position with numpy : 0.02575397491455078 nb_pixel_total : 11002 time to create 1 rle with old method : 0.012258768081665039 time for calcul the mask position with numpy : 0.029266357421875 nb_pixel_total : 138468 time to create 1 rle with old method : 0.1824951171875 time for calcul the mask position with numpy : 0.025910377502441406 nb_pixel_total : 23212 time to create 1 rle with old method : 0.02632880210876465 time for calcul the mask position with numpy : 0.025616884231567383 nb_pixel_total : 83918 time to create 1 rle with old method : 0.09470248222351074 time for calcul the mask position with numpy : 0.025141239166259766 nb_pixel_total : 29059 time to create 1 rle with old method : 0.0331878662109375 time for calcul the mask position with numpy : 0.02822113037109375 nb_pixel_total : 280369 time to create 1 rle with new method : 0.5205981731414795 time for calcul the mask position with numpy : 0.030533790588378906 nb_pixel_total : 113373 time to create 1 rle with old method : 0.12691617012023926 time for calcul the mask position with numpy : 0.04628610610961914 nb_pixel_total : 27847 time to create 1 rle with old method : 0.031223297119140625 create new chi : 2.6355276107788086 time to delete rle : 0.001546621322631836 batch 1 Loaded 19 chid ids of type : 3594 ++++++++++++Number RLEs to save : 8560 TO DO : save crop sub photo not yet done ! save time : 0.5688540935516357 nb_obj : 7 nb_hashtags : 3 time to prepare the origin masks : 4.810459613800049 time for calcul the mask position with numpy : 0.7025184631347656 nb_pixel_total : 7709813 time to create 1 rle with new method : 0.8187069892883301 time for calcul the mask position with numpy : 0.039498329162597656 nb_pixel_total : 18489 time to create 1 rle with old method : 0.021210193634033203 time for calcul the mask position with numpy : 0.037152767181396484 nb_pixel_total : 82607 time to create 1 rle with old method : 0.09297013282775879 time for calcul the mask position with numpy : 0.0244290828704834 nb_pixel_total : 62020 time to create 1 rle with old method : 0.06952118873596191 time for calcul the mask position with numpy : 0.025603294372558594 nb_pixel_total : 60777 time to create 1 rle with old method : 0.06774234771728516 time for calcul the mask position with numpy : 0.025598764419555664 nb_pixel_total : 167675 time to create 1 rle with new method : 0.8496131896972656 time for calcul the mask position with numpy : 0.025122642517089844 nb_pixel_total : 67857 time to create 1 rle with old method : 0.07575321197509766 time for calcul the mask position with numpy : 0.0258023738861084 nb_pixel_total : 125162 time to create 1 rle with old method : 0.1398630142211914 create new chi : 3.114729881286621 time to delete rle : 0.0010478496551513672 batch 1 Loaded 15 chid ids of type : 3594 +++++++Number RLEs to save : 7090 TO DO : save crop sub photo not yet done ! save time : 0.49907779693603516 nb_obj : 10 nb_hashtags : 3 time to prepare the origin masks : 5.130377769470215 time for calcul the mask position with numpy : 0.56028151512146 nb_pixel_total : 7157386 time to create 1 rle with new method : 0.7713432312011719 time for calcul the mask position with numpy : 0.024414539337158203 nb_pixel_total : 35632 time to create 1 rle with old method : 0.03816032409667969 time for calcul the mask position with numpy : 0.025015830993652344 nb_pixel_total : 118916 time to create 1 rle with old method : 0.1329665184020996 time for calcul the mask position with numpy : 0.02681446075439453 nb_pixel_total : 271348 time to create 1 rle with new method : 0.7660527229309082 time for calcul the mask position with numpy : 0.025197744369506836 nb_pixel_total : 88971 time to create 1 rle with old method : 0.09564900398254395 time for calcul the mask position with numpy : 0.023694515228271484 nb_pixel_total : 19477 time to create 1 rle with old method : 0.02135777473449707 time for calcul the mask position with numpy : 0.024230003356933594 nb_pixel_total : 75032 time to create 1 rle with old method : 0.07818412780761719 time for calcul the mask position with numpy : 0.025011539459228516 nb_pixel_total : 219575 time to create 1 rle with new method : 0.755605936050415 time for calcul the mask position with numpy : 0.02537393569946289 nb_pixel_total : 175031 time to create 1 rle with new method : 1.2160429954528809 time for calcul the mask position with numpy : 0.025804758071899414 nb_pixel_total : 17886 time to create 1 rle with old method : 0.020481109619140625 time for calcul the mask position with numpy : 0.026227951049804688 nb_pixel_total : 115146 time to create 1 rle with old method : 0.13059043884277344 create new chi : 4.961395740509033 time to delete rle : 0.0016531944274902344 batch 1 Loaded 21 chid ids of type : 3594 ++++++++++++Number RLEs to save : 10502 TO DO : save crop sub photo not yet done ! save time : 0.7029433250427246 nb_obj : 6 nb_hashtags : 2 time to prepare the origin masks : 2.647519826889038 time for calcul the mask position with numpy : 0.5078701972961426 nb_pixel_total : 8054816 time to create 1 rle with new method : 0.6995296478271484 time for calcul the mask position with numpy : 0.027152538299560547 nb_pixel_total : 34069 time to create 1 rle with old method : 0.0559535026550293 time for calcul the mask position with numpy : 0.0418698787689209 nb_pixel_total : 21085 time to create 1 rle with old method : 0.022976160049438477 time for calcul the mask position with numpy : 0.03933548927307129 nb_pixel_total : 58461 time to create 1 rle with old method : 0.06403064727783203 time for calcul the mask position with numpy : 0.0330350399017334 nb_pixel_total : 33679 time to create 1 rle with old method : 0.03810596466064453 time for calcul the mask position with numpy : 0.026959896087646484 nb_pixel_total : 15602 time to create 1 rle with old method : 0.016919612884521484 time for calcul the mask position with numpy : 0.024745941162109375 nb_pixel_total : 76688 time to create 1 rle with old method : 0.08462691307067871 create new chi : 1.7309951782226562 time to delete rle : 0.0008985996246337891 batch 1 Loaded 13 chid ids of type : 3594 +++++++++++++Number RLEs to save : 5896 TO DO : save crop sub photo not yet done ! save time : 0.38089632987976074 nb_obj : 8 nb_hashtags : 4 time to prepare the origin masks : 3.957070827484131 time for calcul the mask position with numpy : 0.4339592456817627 nb_pixel_total : 7472976 time to create 1 rle with new method : 0.9029192924499512 time for calcul the mask position with numpy : 0.04032540321350098 nb_pixel_total : 118152 time to create 1 rle with old method : 0.12865185737609863 time for calcul the mask position with numpy : 0.02371072769165039 nb_pixel_total : 29856 time to create 1 rle with old method : 0.03230452537536621 time for calcul the mask position with numpy : 0.025740861892700195 nb_pixel_total : 320147 time to create 1 rle with new method : 0.9634857177734375 time for calcul the mask position with numpy : 0.025641202926635742 nb_pixel_total : 207143 time to create 1 rle with new method : 0.7168736457824707 time for calcul the mask position with numpy : 0.025251150131225586 nb_pixel_total : 44788 time to create 1 rle with old method : 0.04837298393249512 time for calcul the mask position with numpy : 0.023749351501464844 nb_pixel_total : 11030 time to create 1 rle with old method : 0.01188039779663086 time for calcul the mask position with numpy : 0.02295970916748047 nb_pixel_total : 10820 time to create 1 rle with old method : 0.011347055435180664 time for calcul the mask position with numpy : 0.023493289947509766 nb_pixel_total : 79488 time to create 1 rle with old method : 0.0831747055053711 create new chi : 3.636336326599121 time to delete rle : 0.0013554096221923828 batch 1 Loaded 17 chid ids of type : 3594 +++++++++Number RLEs to save : 9270 TO DO : save crop sub photo not yet done ! save time : 0.6000494956970215 nb_obj : 4 nb_hashtags : 2 time to prepare the origin masks : 1.6203608512878418 time for calcul the mask position with numpy : 0.5721487998962402 nb_pixel_total : 8000093 time to create 1 rle with new method : 1.1358375549316406 time for calcul the mask position with numpy : 0.02312946319580078 nb_pixel_total : 66418 time to create 1 rle with old method : 0.07139229774475098 time for calcul the mask position with numpy : 0.023851394653320312 nb_pixel_total : 40495 time to create 1 rle with old method : 0.04281044006347656 time for calcul the mask position with numpy : 0.02366018295288086 nb_pixel_total : 30007 time to create 1 rle with old method : 0.03206586837768555 time for calcul the mask position with numpy : 0.024136781692504883 nb_pixel_total : 157387 time to create 1 rle with new method : 0.741926908493042 create new chi : 2.7558400630950928 time to delete rle : 0.0007469654083251953 batch 1 Loaded 9 chid ids of type : 3594 ++++Number RLEs to save : 4878 TO DO : save crop sub photo not yet done ! save time : 0.3522655963897705 map_output_result : {1385498674: (0.0, 'Should be the crop_list due to order', 0), 1385498630: (0.0, 'Should be the crop_list due to order', 0), 1385498393: (0.0, 'Should be the crop_list due to order', 0), 1385498354: (0.0, 'Should be the crop_list due to order', 0), 1385498302: (0.0, 'Should be the crop_list due to order', 0), 1385498233: (0.0, 'Should be the crop_list due to order', 0), 1385498166: (0.0, 'Should be the crop_list due to order', 0), 1385498129: (0.0, 'Should be the crop_list due to order', 0), 1385497572: (0.0, 'Should be the crop_list due to order', 0), 1385497002: (0.0, 'Should be the crop_list due to order', 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 [1385498674, 1385498630, 1385498393, 1385498354, 1385498302, 1385498233, 1385498166, 1385498129, 1385497572, 1385497002] Looping around the photos to save general results len do output : 10 /1385498674.Didn't retrieve data . /1385498630.Didn't retrieve data . /1385498393.Didn't retrieve data . /1385498354.Didn't retrieve data . /1385498302.Didn't retrieve data . /1385498233.Didn't retrieve data . /1385498166.Didn't retrieve data . /1385498129.Didn't retrieve data . /1385497572.Didn't retrieve data . /1385497002.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 ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498674', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498630', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498393', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498354', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498302', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498233', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498166', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498129', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385497572', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385497002', None, None, None, None, None, '3759738') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 30 time used for this insertion : 0.014425039291381836 save_final save missing photos in datou_result : time spend for datou_step_exec : 72.3056812286377 time spend to save output : 0.015189409255981445 total time spend for step 3 : 72.32087063789368 step4:ventilate_hashtags_in_portfolio Mon Sep 22 20:34:00 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 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 : 27102182 get user id for portfolio 27102182 SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=27102182 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('metal','pet_fonce','mal_croppe','papier','pet_clair','background','pehd','carton','environnement','flou','autre')) 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`=27102182 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('metal','pet_fonce','mal_croppe','papier','pet_clair','background','pehd','carton','environnement','flou','autre')) 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") 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`=27102182 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('metal','pet_fonce','mal_croppe','papier','pet_clair','background','pehd','carton','environnement','flou','autre')) AND mptpi.`min_score`=0.5 To do lien utilise dans velours : https://marlene.fotonower.com/velours/27104580,27104581,27104582,27104583,27104584,27104585,27104586,27104587,27104588,27104589,27104590?tags=metal,pet_fonce,mal_croppe,papier,pet_clair,background,pehd,carton,environnement,flou,autre Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : ventilate_hashtags_in_portfolio we use saveGeneral [1385498674, 1385498630, 1385498393, 1385498354, 1385498302, 1385498233, 1385498166, 1385498129, 1385497572, 1385497002] Looping around the photos to save general results len do output : 1 /27102182. 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 ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498674', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498630', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498393', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498354', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498302', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498233', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498166', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498129', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385497572', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385497002', None, None, None, None, None, '3759738') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 11 time used for this insertion : 0.017172813415527344 save_final save missing photos in datou_result : time spend for datou_step_exec : 1.713503122329712 time spend to save output : 0.017448902130126953 total time spend for step 4 : 1.7309520244598389 step5:final Mon Sep 22 20:34:02 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 : {1385498674: ('0.06238037712191356',), 1385498630: ('0.06238037712191356',), 1385498393: ('0.06238037712191356',), 1385498354: ('0.06238037712191356',), 1385498302: ('0.06238037712191356',), 1385498233: ('0.06238037712191356',), 1385498166: ('0.06238037712191356',), 1385498129: ('0.06238037712191356',), 1385497572: ('0.06238037712191356',), 1385497002: ('0.06238037712191356',)} new output for save of step final : {1385498674: ('0.06238037712191356',), 1385498630: ('0.06238037712191356',), 1385498393: ('0.06238037712191356',), 1385498354: ('0.06238037712191356',), 1385498302: ('0.06238037712191356',), 1385498233: ('0.06238037712191356',), 1385498166: ('0.06238037712191356',), 1385498129: ('0.06238037712191356',), 1385497572: ('0.06238037712191356',), 1385497002: ('0.06238037712191356',)} [1385498674, 1385498630, 1385498393, 1385498354, 1385498302, 1385498233, 1385498166, 1385498129, 1385497572, 1385497002] Looping around the photos to save general results len do output : 10 /1385498674.Didn't retrieve data . /1385498630.Didn't retrieve data . /1385498393.Didn't retrieve data . /1385498354.Didn't retrieve data . /1385498302.Didn't retrieve data . /1385498233.Didn't retrieve data . /1385498166.Didn't retrieve data . /1385498129.Didn't retrieve data . /1385497572.Didn't retrieve data . /1385497002.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 ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498674', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498630', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498393', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498354', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498302', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498233', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498166', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498129', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385497572', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385497002', None, None, None, None, None, '3759738') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 30 time used for this insertion : 0.019389867782592773 save_final save missing photos in datou_result : time spend for datou_step_exec : 0.12836742401123047 time spend to save output : 0.020108699798583984 total time spend for step 5 : 0.14847612380981445 step6:blur_detection Mon Sep 22 20:34:02 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 inside step blur_detection methode: ratio et variance treat image : temp/1758565831_1294870_1385498674_4cde8b585aedbb155c4a7d6cb0d4e5b4.jpg resize: (2160, 3840) 1385498674 -6.808443283744036 treat image : temp/1758565831_1294870_1385498630_7932360890dcce05b4a444784f63705b.jpg resize: (2160, 3840) 1385498630 -6.997757233757742 treat image : temp/1758565831_1294870_1385498393_14b4a76598c5c914b3a229a0deaf11bf.jpg resize: (2160, 3840) 1385498393 -7.126142208402309 treat image : temp/1758565831_1294870_1385498354_4b2cb45e317aec22a205de6cfe447d75.jpg resize: (2160, 3840) 1385498354 -7.070694936651752 treat image : temp/1758565831_1294870_1385498302_6ca63f9ba3850789623dc1b63874ded1.jpg resize: (2160, 3840) 1385498302 -6.915374994596135 treat image : temp/1758565831_1294870_1385498233_d02a9b0ec881cbb3df2384cf369db5f3.jpg resize: (2160, 3840) 1385498233 -6.962635822528561 treat image : temp/1758565831_1294870_1385498166_449b191406d4cb83c59ec7e3044fb7b2.jpg resize: (2160, 3840) 1385498166 -7.086447753429027 treat image : temp/1758565831_1294870_1385498129_c35ede04bf510c2c5a7a14b52a3f74af.jpg resize: (2160, 3840) 1385498129 -6.908581274439847 treat image : temp/1758565831_1294870_1385497572_cd9602d63d509537cfaeee1e881caf71.jpg resize: (2160, 3840) 1385497572 -7.054283639909519 treat image : temp/1758565831_1294870_1385497002_da7abe3161609374ac21bb437b6f632c.jpg resize: (2160, 3840) 1385497002 -7.059090112033004 treat image : temp/1758565831_1294870_1385498674_4cde8b585aedbb155c4a7d6cb0d4e5b4_rle_crop_3970396979_0.png resize: (507, 444) 1385516317 -4.054070233985973 treat image : temp/1758565831_1294870_1385498674_4cde8b585aedbb155c4a7d6cb0d4e5b4_rle_crop_3970396980_0.png resize: (315, 410) 1385516318 -3.329961342828363 treat image : temp/1758565831_1294870_1385498674_4cde8b585aedbb155c4a7d6cb0d4e5b4_rle_crop_3970396981_0.png resize: (104, 188) 1385516319 -4.48222038488302 treat image : temp/1758565831_1294870_1385498674_4cde8b585aedbb155c4a7d6cb0d4e5b4_rle_crop_3970396982_0.png resize: (113, 85) 1385516320 -3.952638807171557 treat image : temp/1758565831_1294870_1385498630_7932360890dcce05b4a444784f63705b_rle_crop_3970396984_0.png resize: (314, 255) 1385516321 -4.590792753016085 treat image : temp/1758565831_1294870_1385498630_7932360890dcce05b4a444784f63705b_rle_crop_3970396987_0.png resize: (326, 155) 1385516322 -4.4507825982978915 treat image : temp/1758565831_1294870_1385498630_7932360890dcce05b4a444784f63705b_rle_crop_3970396988_0.png resize: (277, 206) 1385516323 -4.377634521502661 treat image : temp/1758565831_1294870_1385498630_7932360890dcce05b4a444784f63705b_rle_crop_3970396989_0.png resize: (231, 160) 1385516324 -4.3654976376096934 treat image : temp/1758565831_1294870_1385498630_7932360890dcce05b4a444784f63705b_rle_crop_3970396991_0.png resize: (206, 317) 1385516325 -4.591546329805401 treat image : temp/1758565831_1294870_1385498630_7932360890dcce05b4a444784f63705b_rle_crop_3970396994_0.png resize: (309, 262) 1385516327 -4.306528993010974 treat image : temp/1758565831_1294870_1385498393_14b4a76598c5c914b3a229a0deaf11bf_rle_crop_3970396999_0.png resize: (966, 906) 1385516329 -1.259530161130143 treat image : temp/1758565831_1294870_1385498354_4b2cb45e317aec22a205de6cfe447d75_rle_crop_3970397003_0.png resize: (403, 145) 1385516330 -3.7217984338483374 treat image : temp/1758565831_1294870_1385498354_4b2cb45e317aec22a205de6cfe447d75_rle_crop_3970397005_0.png resize: (101, 194) 1385516331 -3.7387627605258644 treat image : temp/1758565831_1294870_1385498302_6ca63f9ba3850789623dc1b63874ded1_rle_crop_3970397009_0.png resize: (507, 412) 1385516332 -1.408285990303778 treat image : temp/1758565831_1294870_1385498302_6ca63f9ba3850789623dc1b63874ded1_rle_crop_3970397010_0.png resize: (686, 860) 1385516333 -2.5020896291567936 treat image : temp/1758565831_1294870_1385498302_6ca63f9ba3850789623dc1b63874ded1_rle_crop_3970397011_0.png resize: (245, 172) 1385516334 -4.083140870275715 treat image : temp/1758565831_1294870_1385498302_6ca63f9ba3850789623dc1b63874ded1_rle_crop_3970397012_0.png resize: (392, 305) 1385516335 -0.8397094556378056 treat image : temp/1758565831_1294870_1385498302_6ca63f9ba3850789623dc1b63874ded1_rle_crop_3970397015_0.png resize: (139, 113) 1385516336 -3.074782984605959 treat image : temp/1758565831_1294870_1385498233_d02a9b0ec881cbb3df2384cf369db5f3_rle_crop_3970397017_0.png resize: (340, 619) 1385516337 -4.330960426471402 treat image : temp/1758565831_1294870_1385498233_d02a9b0ec881cbb3df2384cf369db5f3_rle_crop_3970397018_0.png resize: (349, 298) 1385516338 -4.370572311790855 treat image : temp/1758565831_1294870_1385498233_d02a9b0ec881cbb3df2384cf369db5f3_rle_crop_3970397019_0.png resize: (484, 528) 1385516339 -5.429165884765065 treat image : temp/1758565831_1294870_1385498166_449b191406d4cb83c59ec7e3044fb7b2_rle_crop_3970397024_0.png resize: (548, 301) 1385516340 -0.9210077943343054 treat image : temp/1758565831_1294870_1385498166_449b191406d4cb83c59ec7e3044fb7b2_rle_crop_3970397025_0.png resize: (101, 242) 1385516341 -2.1676161868745676 treat image : temp/1758565831_1294870_1385498166_449b191406d4cb83c59ec7e3044fb7b2_rle_crop_3970397026_0.png resize: (644, 395) 1385516342 -0.9792862287328933 treat image : temp/1758565831_1294870_1385498166_449b191406d4cb83c59ec7e3044fb7b2_rle_crop_3970397027_0.png resize: (597, 487) 1385516343 -2.860312661336186 treat image : temp/1758565831_1294870_1385498166_449b191406d4cb83c59ec7e3044fb7b2_rle_crop_3970397028_0.png resize: (321, 299) 1385516344 -3.4570930610552284 treat image : temp/1758565831_1294870_1385498166_449b191406d4cb83c59ec7e3044fb7b2_rle_crop_3970397029_0.png resize: (274, 114) 1385516345 -3.937851042971323 treat image : temp/1758565831_1294870_1385498166_449b191406d4cb83c59ec7e3044fb7b2_rle_crop_3970397030_0.png resize: (357, 401) 1385516346 0.0645512041412796 treat image : temp/1758565831_1294870_1385498166_449b191406d4cb83c59ec7e3044fb7b2_rle_crop_3970397032_0.png resize: (411, 468) 1385516347 -5.344390795711046 treat image : temp/1758565831_1294870_1385498129_c35ede04bf510c2c5a7a14b52a3f74af_rle_crop_3970397036_0.png resize: (293, 152) 1385516348 -5.144823390459825 treat image : temp/1758565831_1294870_1385498129_c35ede04bf510c2c5a7a14b52a3f74af_rle_crop_3970397038_0.png resize: (165, 249) 1385516349 -4.20616961544811 treat image : temp/1758565831_1294870_1385498129_c35ede04bf510c2c5a7a14b52a3f74af_rle_crop_3970397039_0.png resize: (138, 344) 1385516350 -4.692294415010518 treat image : temp/1758565831_1294870_1385497572_cd9602d63d509537cfaeee1e881caf71_rle_crop_3970397040_0.png resize: (649, 332) 1385516351 -4.351198293375633 treat image : temp/1758565831_1294870_1385497572_cd9602d63d509537cfaeee1e881caf71_rle_crop_3970397042_0.png resize: (124, 111) 1385516352 -4.725624946831795 treat image : temp/1758565831_1294870_1385497572_cd9602d63d509537cfaeee1e881caf71_rle_crop_3970397045_0.png resize: (779, 671) 1385516353 -5.5464802913094875 treat image : temp/1758565831_1294870_1385497572_cd9602d63d509537cfaeee1e881caf71_rle_crop_3970397047_0.png resize: (431, 364) 1385516354 -5.962857224364662 treat image : temp/1758565831_1294870_1385497002_da7abe3161609374ac21bb437b6f632c_rle_crop_3970397049_0.png resize: (226, 159) 1385516355 -2.0389755210880507 treat image : temp/1758565831_1294870_1385497002_da7abe3161609374ac21bb437b6f632c_rle_crop_3970397050_0.png resize: (340, 138) 1385516356 -4.558833553258352 treat image : temp/1758565831_1294870_1385497002_da7abe3161609374ac21bb437b6f632c_rle_crop_3970397051_0.png resize: (294, 359) 1385516357 -4.8688403413646215 treat image : temp/1758565831_1294870_1385498393_14b4a76598c5c914b3a229a0deaf11bf_rle_crop_3970396995_0.png resize: (964, 900) 1385516364 -1.124220314797395 treat image : temp/1758565831_1294870_1385498393_14b4a76598c5c914b3a229a0deaf11bf_rle_crop_3970396998_0.png resize: (313, 169) 1385516365 -3.9462655113953744 treat image : temp/1758565831_1294870_1385498354_4b2cb45e317aec22a205de6cfe447d75_rle_crop_3970397007_0.png resize: (346, 182) 1385516366 -4.518958474348615 treat image : temp/1758565831_1294870_1385498302_6ca63f9ba3850789623dc1b63874ded1_rle_crop_3970397008_0.png resize: (295, 131) 1385516367 -4.266998846364105 treat image : temp/1758565831_1294870_1385498302_6ca63f9ba3850789623dc1b63874ded1_rle_crop_3970397013_0.png resize: (154, 212) 1385516368 -3.2246255462240083 treat image : temp/1758565831_1294870_1385498233_d02a9b0ec881cbb3df2384cf369db5f3_rle_crop_3970397021_0.png resize: (482, 201) 1385516369 -4.256617865725528 treat image : temp/1758565831_1294870_1385497572_cd9602d63d509537cfaeee1e881caf71_rle_crop_3970397043_0.png resize: (343, 241) 1385516370 -4.04330940537466 treat image : temp/1758565831_1294870_1385497572_cd9602d63d509537cfaeee1e881caf71_rle_crop_3970397046_0.png resize: (300, 179) 1385516371 -3.891653804281676 treat image : temp/1758565831_1294870_1385498674_4cde8b585aedbb155c4a7d6cb0d4e5b4_rle_crop_3970396978_0.png resize: (130, 143) 1385516375 -4.468433457774284 treat image : temp/1758565831_1294870_1385498630_7932360890dcce05b4a444784f63705b_rle_crop_3970396992_0.png resize: (105, 120) 1385516376 -4.332248394686379 treat image : temp/1758565831_1294870_1385498354_4b2cb45e317aec22a205de6cfe447d75_rle_crop_3970397004_0.png resize: (105, 136) 1385516377 -3.9076018603171114 treat image : temp/1758565831_1294870_1385498354_4b2cb45e317aec22a205de6cfe447d75_rle_crop_3970397006_0.png resize: (161, 186) 1385516378 -2.8879627907823346 treat image : 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list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 84 time used for this insertion : 0.020151615142822266 save missing photos in datou_result : time spend for datou_step_exec : 42.59810400009155 time spend to save output : 0.043573617935180664 total time spend for step 6 : 42.64167761802673 step7:brightness Mon Sep 22 20:34:45 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! 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temp/1758565831_1294870_1385498302_6ca63f9ba3850789623dc1b63874ded1_rle_crop_3970397016_0.png treat image : temp/1758565831_1294870_1385497572_cd9602d63d509537cfaeee1e881caf71_rle_crop_3970397044_0.png 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 : 84 time used for this insertion : 0.016394376754760742 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 84 time used for this insertion : 0.015674114227294922 save missing photos in datou_result : time spend for datou_step_exec : 10.426004409790039 time spend to save output : 0.03677988052368164 total time spend for step 7 : 10.46278429031372 step8:velours_tree Mon Sep 22 20:34:55 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 : 0.1771683692932129 time spend to save output : 3.743171691894531e-05 total time spend for step 8 : 0.17720580101013184 step9:send_mail_cod Mon Sep 22 20:34:55 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 complete output_args for input 1 Inconsistent number of input and output, step which parrallelize and manage error in input by avoiding sending an output for this data can't be used in tree dependencies of input and output complete output_args for input 2 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/workarea/git/Velours/python in order to get the selector url, please entre the license of selector results_Auto_P27102182_22-09-2025_20_34_55.pdf 27104580 change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .imagette271045801758566095 27104581 change filename to text .imagette271045811758566096 27104582 imagette271045821758566096 27104583 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 .imagette271045831758566096 27104584 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 .imagette271045841758566098 27104585 imagette271045851758566099 27104586 imagette271045861758566099 27104587 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 .imagette271045871758566099 27104589 imagette271045891758566100 27104590 change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .imagette271045901758566100 SELECT h.hashtag,pcr.value FROM MTRUser.portfolio_carac_ratio pcr, MTRBack.hashtags h where pcr.portfolio_id=27102182 and hashtag_type = 3594 and pcr.hashtag_id = h.hashtag_id; velour_link : https://marlene.fotonower.com/velours/27104580,27104581,27104582,27104583,27104584,27104585,27104586,27104587,27104588,27104589,27104590?tags=metal,pet_fonce,mal_croppe,papier,pet_clair,background,pehd,carton,environnement,flou,autre args[1385498674] : ((1385498674, -6.808443283744036, 492609224), (1385498674, 0.17242037994901652, 2107752395), '0.06238037712191356') We are sending mail with results at report@fotonower.com args[1385498630] : ((1385498630, -6.997757233757742, 492609224), (1385498630, 0.31091839484095807, 2107752395), '0.06238037712191356') We are sending mail with results at report@fotonower.com args[1385498393] : ((1385498393, -7.126142208402309, 492609224), (1385498393, 0.38864306331235227, 2107752395), '0.06238037712191356') We are sending mail with results at report@fotonower.com args[1385498354] : ((1385498354, -7.070694936651752, 492609224), (1385498354, 0.40404987702390266, 2107752395), '0.06238037712191356') We are sending mail with results at report@fotonower.com args[1385498302] : ((1385498302, -6.915374994596135, 492609224), (1385498302, 0.4577014240391334, 2107752395), '0.06238037712191356') We are sending mail with results at report@fotonower.com args[1385498233] : ((1385498233, -6.962635822528561, 492609224), (1385498233, 0.2763526672368367, 2107752395), '0.06238037712191356') We are sending mail with results at report@fotonower.com args[1385498166] : ((1385498166, -7.086447753429027, 492609224), (1385498166, 0.5256292847072552, 2107752395), '0.06238037712191356') We are sending mail with results at report@fotonower.com args[1385498129] : ((1385498129, -6.908581274439847, 492609224), (1385498129, 0.31669876555034104, 2107752395), '0.06238037712191356') We are sending mail with results at report@fotonower.com args[1385497572] : ((1385497572, -7.054283639909519, 492609224), (1385497572, 0.335755007494905, 2107752395), '0.06238037712191356') We are sending mail with results at report@fotonower.com args[1385497002] : ((1385497002, -7.059090112033004, 492609224), (1385497002, 0.4140131191524972, 2107752395), '0.06238037712191356') We are sending mail with results at report@fotonower.com refus_total : 0.06238037712191356 2022-04-13 10:29:59 0 SELECT ph.photo_id,ph.url,ph.username,ph.uploaded_at,ph.text FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=27102182 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_P27102182_22-09-2025_20_34_55.pdf results_Auto_P27102182_22-09-2025_20_34_55.pdf uploaded to url https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27102182_22-09-2025_20_34_55.pdf start insert file to database insert into MTRUser.mtr_files (mtd_id,mtr_portfolio_id,text,url,format,tags,file_size,value) values ('3318','27102182','results_Auto_P27102182_22-09-2025_20_34_55.pdf','https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27102182_22-09-2025_20_34_55.pdf','pdf','','0.83','0.06238037712191356') message_in_mail: Bonjour,
Veuillez trouver ci dessous les résultats du service carac on demand pour le portfolio: https://www.fotonower.com/view/27102182

https://www.fotonower.com/image?json=false&list_photos_id=1385498674
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1385498630
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1385498393
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1385498354
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1385498302
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1385498233
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1385498166
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1385498129
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1385497572
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1385497002
Bravo, la photo est bien prise.

Dans ces conditions,le taux de refus est: 6.24%
Veuillez trouver les photos des contaminants.

exemples de contaminants: metal: https://www.fotonower.com/view/27104580?limit=200
exemples de contaminants: pet_fonce: https://www.fotonower.com/view/27104581?limit=200
exemples de contaminants: papier: https://www.fotonower.com/view/27104583?limit=200
exemples de contaminants: pet_clair: https://www.fotonower.com/view/27104584?limit=200
exemples de contaminants: carton: https://www.fotonower.com/view/27104587?limit=200
exemples de contaminants: autre: https://www.fotonower.com/view/27104590?limit=200
Veuillez trouver le rapport en pdf:https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27102182_22-09-2025_20_34_55.pdf.

Lien vers velours :https://marlene.fotonower.com/velours/27104580,27104581,27104582,27104583,27104584,27104585,27104586,27104587,27104588,27104589,27104590?tags=metal,pet_fonce,mal_croppe,papier,pet_clair,background,pehd,carton,environnement,flou,autre.


L'équipe Fotonower 202 b'' Server: nginx Date: Mon, 22 Sep 2025 18:35:04 GMT Content-Length: 0 Connection: close X-Message-Id: mKB3ayqmQsuc9W7RE9Jeyw Access-Control-Allow-Origin: https://sendgrid.api-docs.io Access-Control-Allow-Methods: POST Access-Control-Allow-Headers: Authorization, Content-Type, On-behalf-of, x-sg-elas-acl Access-Control-Max-Age: 600 X-No-CORS-Reason: https://sendgrid.com/docs/Classroom/Basics/API/cors.html Strict-Transport-Security: max-age=31536000; includeSubDomains Content-Security-Policy: frame-ancestors 'none' Cache-Control: no-cache X-Content-Type-Options: no-sniff Referrer-Policy: strict-origin-when-cross-origin Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : send_mail_cod we use saveGeneral [1385498674, 1385498630, 1385498393, 1385498354, 1385498302, 1385498233, 1385498166, 1385498129, 1385497572, 1385497002] 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 ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498674', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498630', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498393', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498354', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498302', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498233', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498166', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498129', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385497572', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385497002', None, None, None, None, None, '3759738') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 10 time used for this insertion : 0.013995647430419922 save_final save missing photos in datou_result : time spend for datou_step_exec : 8.916130781173706 time spend to save output : 0.014227628707885742 total time spend for step 9 : 8.930358409881592 step10:split_time_score Mon Sep 22 20:35:04 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'}] (('18', 10),) ERROR counted https://github.com/fotonower/Velours/issues/663#issuecomment-421136223 {} 22092025 27102182 Nombre de photos uploadées : 10 / 23040 (0%) 22092025 27102182 Nombre de photos taguées (types de déchets): 0 / 10 (0%) 22092025 27102182 Nombre de photos taguées (volume) : 0 / 10 (0%) elapsed_time : load_data_split_time_score 1.430511474609375e-06 elapsed_time : order_list_meta_photo_and_scores 3.814697265625e-06 ?????????? elapsed_time : fill_and_build_computed_from_old_data 0.00043082237243652344 Catched exception ! Connect or reconnect ! Catched exception ! Connect or reconnect ! elapsed_time : insert_dashboard_record_day_entry 0.20993924140930176 We will return after consolidate but for now we need the day, how to get it, for now depending on the previous heavy steps Qualite : 0.02982813745395805 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27086905_22-09-2025_12_58_13.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27086905 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11449 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11452 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 11452 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11453 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 11453 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11478 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11478 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11455 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11455 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11458 send_mail_cod have less inputs used (3) than in the step definition (5) : maybe we manage optionnal inputs ! Number of inputs / outputs for each 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 11449 doesn't seem to be define in the database( WARNING : type of input 2 of step 11452 doesn't seem to be define in the database( WARNING : output 1 of step 11449 have datatype=2 whereas input 1 of step 11453 have datatype=7 WARNING : type of output 2 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11454 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11456 doesn't seem to be define in the database( WARNING : type of output 1 of step 11456 doesn't seem to be define in the database( WARNING : type of input 3 of step 11455 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11456 have datatype=10 whereas input 3 of step 11458 have datatype=6 WARNING : type of input 5 of step 11458 doesn't seem to be define in the database( WARNING : output 0 of step 11477 have datatype=11 whereas input 5 of step 11458 have datatype=None WARNING : output 0 of step 11456 have datatype=10 whereas input 0 of step 11477 have datatype=18 WARNING : type of input 2 of step 11478 doesn't seem to be define in the database( WARNING : output 1 of step 11454 have datatype=7 whereas input 2 of step 11478 have datatype=None WARNING : type of output 3 of step 11478 doesn't seem to be define in the database( WARNING : type of input 2 of step 11456 doesn't seem to be define in the database( WARNING : output 0 of step 11453 have datatype=1 whereas input 0 of step 11454 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`=27086905 AND mptpi.`type`=3726 To do Qualite : 0.11243366005979938 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27086938_22-09-2025_11_13_59.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27086938 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of 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 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=27086938 AND mptpi.`type`=3594 To do Qualite : 0.11947100871606124 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27089617_22-09-2025_12_52_21.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27089617 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11449 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11452 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 11452 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11453 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 11453 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11478 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11478 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11455 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11455 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11458 send_mail_cod have less inputs used (3) than in the step definition (5) : maybe we manage optionnal inputs ! Number of inputs / outputs for each 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 11449 doesn't seem to be define in the database( WARNING : type of input 2 of step 11452 doesn't seem to be define in the database( WARNING : output 1 of step 11449 have datatype=2 whereas input 1 of step 11453 have datatype=7 WARNING : type of output 2 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11454 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11456 doesn't seem to be define in the database( WARNING : type of output 1 of step 11456 doesn't seem to be define in the database( WARNING : type of input 3 of step 11455 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11456 have datatype=10 whereas input 3 of step 11458 have datatype=6 WARNING : type of input 5 of step 11458 doesn't seem to be define in the database( WARNING : output 0 of step 11477 have datatype=11 whereas input 5 of step 11458 have datatype=None WARNING : output 0 of step 11456 have datatype=10 whereas input 0 of step 11477 have datatype=18 WARNING : type of input 2 of step 11478 doesn't seem to be define in the database( WARNING : output 1 of step 11454 have datatype=7 whereas input 2 of step 11478 have datatype=None WARNING : type of output 3 of step 11478 doesn't seem to be define in the database( WARNING : type of input 2 of step 11456 doesn't seem to be define in the database( WARNING : output 0 of step 11453 have datatype=1 whereas input 0 of step 11454 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`=27089617 AND mptpi.`type`=3726 To do Qualite : 0.02269504496430703 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27089621_22-09-2025_12_43_15.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27089621 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11449 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11452 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 11452 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11453 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 11453 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11478 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11478 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11455 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11455 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11458 send_mail_cod have less inputs used (3) than in the step definition (5) : maybe we manage optionnal inputs ! Number of inputs / outputs for each 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 11449 doesn't seem to be define in the database( WARNING : type of input 2 of step 11452 doesn't seem to be define in the database( WARNING : output 1 of step 11449 have datatype=2 whereas input 1 of step 11453 have datatype=7 WARNING : type of output 2 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11454 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11456 doesn't seem to be define in the database( WARNING : type of output 1 of step 11456 doesn't seem to be define in the database( WARNING : type of input 3 of step 11455 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11456 have datatype=10 whereas input 3 of step 11458 have datatype=6 WARNING : type of input 5 of step 11458 doesn't seem to be define in the database( WARNING : output 0 of step 11477 have datatype=11 whereas input 5 of step 11458 have datatype=None WARNING : output 0 of step 11456 have datatype=10 whereas input 0 of step 11477 have datatype=18 WARNING : type of input 2 of step 11478 doesn't seem to be define in the database( WARNING : output 1 of step 11454 have datatype=7 whereas input 2 of step 11478 have datatype=None WARNING : type of output 3 of step 11478 doesn't seem to be define in the database( WARNING : type of input 2 of step 11456 doesn't seem to be define in the database( WARNING : output 0 of step 11453 have datatype=1 whereas input 0 of step 11454 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`=27089621 AND mptpi.`type`=3726 To do Qualite : 0.1000206431112826 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27093812_22-09-2025_15_41_17.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27093812 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of 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 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=27093812 AND mptpi.`type`=3594 To do Qualite : 0.027299443121552608 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27093816_22-09-2025_15_32_47.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27093816 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11449 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11452 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 11452 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11453 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 11453 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11478 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11478 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11455 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11455 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11458 send_mail_cod have less inputs used (3) than in the step definition (5) : maybe we manage optionnal inputs ! Number of inputs / outputs for each 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 11449 doesn't seem to be define in the database( WARNING : type of input 2 of step 11452 doesn't seem to be define in the database( WARNING : output 1 of step 11449 have datatype=2 whereas input 1 of step 11453 have datatype=7 WARNING : type of output 2 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11454 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11456 doesn't seem to be define in the database( WARNING : type of output 1 of step 11456 doesn't seem to be define in the database( WARNING : type of input 3 of step 11455 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11456 have datatype=10 whereas input 3 of step 11458 have datatype=6 WARNING : type of input 5 of step 11458 doesn't seem to be define in the database( WARNING : output 0 of step 11477 have datatype=11 whereas input 5 of step 11458 have datatype=None WARNING : output 0 of step 11456 have datatype=10 whereas input 0 of step 11477 have datatype=18 WARNING : type of input 2 of step 11478 doesn't seem to be define in the database( WARNING : output 1 of step 11454 have datatype=7 whereas input 2 of step 11478 have datatype=None WARNING : type of output 3 of step 11478 doesn't seem to be define in the database( WARNING : type of input 2 of step 11456 doesn't seem to be define in the database( WARNING : output 0 of step 11453 have datatype=1 whereas input 0 of step 11454 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`=27093816 AND mptpi.`type`=3726 To do Qualite : 0.02045358725039373 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27097587_22-09-2025_18_03_03.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27097587 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11449 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11452 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 11452 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11453 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 11453 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11478 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11478 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11455 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11455 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11458 send_mail_cod have less inputs used (3) than in the step definition (5) : maybe we manage optionnal inputs ! Number of inputs / outputs for each 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 11449 doesn't seem to be define in the database( WARNING : type of input 2 of step 11452 doesn't seem to be define in the database( WARNING : output 1 of step 11449 have datatype=2 whereas input 1 of step 11453 have datatype=7 WARNING : type of output 2 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11454 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11456 doesn't seem to be define in the database( WARNING : type of output 1 of step 11456 doesn't seem to be define in the database( WARNING : type of input 3 of step 11455 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11456 have datatype=10 whereas input 3 of step 11458 have datatype=6 WARNING : type of input 5 of step 11458 doesn't seem to be define in the database( WARNING : output 0 of step 11477 have datatype=11 whereas input 5 of step 11458 have datatype=None WARNING : output 0 of step 11456 have datatype=10 whereas input 0 of step 11477 have datatype=18 WARNING : type of input 2 of step 11478 doesn't seem to be define in the database( WARNING : output 1 of step 11454 have datatype=7 whereas input 2 of step 11478 have datatype=None WARNING : type of output 3 of step 11478 doesn't seem to be define in the database( WARNING : type of input 2 of step 11456 doesn't seem to be define in the database( WARNING : output 0 of step 11453 have datatype=1 whereas input 0 of step 11454 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`=27097587 AND mptpi.`type`=3726 To do Qualite : 0.06225843139146092 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27097608_22-09-2025_16_56_00.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27097608 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of 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 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=27097608 AND mptpi.`type`=3594 To do Qualite : 0.06238037712191356 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27102182_22-09-2025_20_34_55.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27102182 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of 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 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=27102182 AND mptpi.`type`=3594 To do Qualite : 0.06653096064814816 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27102185_22-09-2025_19_13_22.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27102185 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of 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 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=27102185 AND mptpi.`type`=3594 To do Qualite : 0.0320062679907934 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27103128_22-09-2025_19_43_19.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27103128 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11449 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11452 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 11452 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11453 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 11453 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11478 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11478 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11455 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11455 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11458 send_mail_cod have less inputs used (3) than in the step definition (5) : maybe we manage optionnal inputs ! Number of inputs / outputs for each 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 11449 doesn't seem to be define in the database( WARNING : type of input 2 of step 11452 doesn't seem to be define in the database( WARNING : output 1 of step 11449 have datatype=2 whereas input 1 of step 11453 have datatype=7 WARNING : type of output 2 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11454 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11456 doesn't seem to be define in the database( WARNING : type of output 1 of step 11456 doesn't seem to be define in the database( WARNING : type of input 3 of step 11455 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11456 have datatype=10 whereas input 3 of step 11458 have datatype=6 WARNING : type of input 5 of step 11458 doesn't seem to be define in the database( WARNING : output 0 of step 11477 have datatype=11 whereas input 5 of step 11458 have datatype=None WARNING : output 0 of step 11456 have datatype=10 whereas input 0 of step 11477 have datatype=18 WARNING : type of input 2 of step 11478 doesn't seem to be define in the database( WARNING : output 1 of step 11454 have datatype=7 whereas input 2 of step 11478 have datatype=None WARNING : type of output 3 of step 11478 doesn't seem to be define in the database( WARNING : type of input 2 of step 11456 doesn't seem to be define in the database( WARNING : output 0 of step 11453 have datatype=1 whereas input 0 of step 11454 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`=27103128 AND mptpi.`type`=3726 To do NUMBER BATCH : 0 # DISPLAY ALL COLLECTED DATA : {'22092025': {'nb_upload': 10, '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 [1385498674, 1385498630, 1385498393, 1385498354, 1385498302, 1385498233, 1385498166, 1385498129, 1385497572, 1385497002] Looping around the photos to save general results len do output : 1 /27102182Didn'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 ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498674', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498630', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498393', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498354', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498302', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498233', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498166', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385498129', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385497572', None, None, None, None, None, '3759738') ('3318', None, None, None, None, None, None, None, '3759738') ('3318', '27102182', '1385497002', None, None, None, None, None, '3759738') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 11 time used for this insertion : 0.019468307495117188 save_final save missing photos in datou_result : time spend for datou_step_exec : 1.090688705444336 time spend to save output : 0.01973724365234375 total time spend for step 10 : 1.1104259490966797 caffe_path_current : About to save ! 2 After save, about to update current ! ret : 2 len(input) + len(total_photo_id_missing) : 10 set_done_treatment 122.50user 119.97system 4:40.02elapsed 86%CPU (0avgtext+0avgdata 3231744maxresident)k 1253424inputs+123504outputs (30254major+10923424minor)pagefaults 0swaps