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 : 2816304 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 : ['3534279'] with mtr_portfolio_ids : ['25980071'] and first list_photo_ids : [] new path : /proc/2816304/ 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 , WARNING: data may be incomplete, need to offset and complete ! BFBFBFBFBFBFBFBFBFBFBFBFBFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 13 ; length of list_pids : 13 ; length of list_args : 13 time to download the photos : 1.8180475234985352 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 Thu Aug 14 14:40:29 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 : 10619 max_wait_temp : 1 max_wait : 0 gpu_flag : 0 2025-08-14 14:40:32.022633: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2025-08-14 14:40:32.048570: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3492910000 Hz 2025-08-14 14:40:32.050762: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7fcbb0000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-08-14 14:40:32.050820: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-08-14 14:40:32.054651: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-08-14 14:40:32.210506: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x2cf41c60 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-08-14 14:40:32.210569: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-08-14 14:40:32.211965: 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 2025-08-14 14:40:32.212398: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-08-14 14:40:32.215375: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-08-14 14:40:32.218242: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-08-14 14:40:32.218714: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-08-14 14:40:32.221823: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-08-14 14:40:32.222883: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-08-14 14:40:32.227387: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-08-14 14:40:32.228926: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-08-14 14:40:32.228998: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-08-14 14:40:32.229775: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-08-14 14:40:32.229791: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-08-14 14:40:32.229817: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-08-14 14:40:32.231185: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 9836 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. 2025-08-14 14:40:32.484674: 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 2025-08-14 14:40:32.484793: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-08-14 14:40:32.484815: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-08-14 14:40:32.484834: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-08-14 14:40:32.484852: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-08-14 14:40:32.484870: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-08-14 14:40:32.484888: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-08-14 14:40:32.484906: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-08-14 14:40:32.486444: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-08-14 14:40:32.487827: 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 2025-08-14 14:40:32.487869: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-08-14 14:40:32.487891: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-08-14 14:40:32.487911: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-08-14 14:40:32.487930: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-08-14 14:40:32.487950: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-08-14 14:40:32.487969: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-08-14 14:40:32.487989: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-08-14 14:40:32.489545: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-08-14 14:40:32.489585: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-08-14 14:40:32.489596: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-08-14 14:40:32.489606: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-08-14 14:40:32.490919: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 9836 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 : [] 2025-08-14 14:40:39.448369: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-08-14 14:40:39.619900: 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 : 13 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 28.00000 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: 1920.00000 nb d'objets trouves : 6 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 29.00000 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: 1920.00000 nb d'objets trouves : 1 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 28.00000 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: 1920.00000 nb d'objets trouves : 7 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 21.00000 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: 1920.00000 nb d'objets trouves : 5 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 27.00000 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: 1920.00000 nb d'objets trouves : 6 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 24.00000 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: 1920.00000 nb d'objets trouves : 5 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 33.00000 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: 1920.00000 nb d'objets trouves : 4 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 20.00000 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: 1920.00000 nb d'objets trouves : 9 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 27.00000 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: 1920.00000 nb d'objets trouves : 2 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 21.00000 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: 1920.00000 nb d'objets trouves : 10 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 23.00000 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: 1920.00000 nb d'objets trouves : 7 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 23.00000 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: 1920.00000 nb d'objets trouves : 7 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 26.00000 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: 1920.00000 nb d'objets trouves : 9 Detection mask done ! Trying to reset tf kernel 2816929 begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 1944 tf kernel not reseted sub process len(results) : 13 len(list_Values) 0 None max_time_sub_proc : 3600 parent process len(results) : 13 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 : 6839 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 : 0.0017309188842773438 nb_pixel_total : 74681 time to create 1 rle with old method : 0.08518576622009277 length of segment : 302 time for calcul the mask position with numpy : 0.00018668174743652344 nb_pixel_total : 9644 time to create 1 rle with old method : 0.01177668571472168 length of segment : 115 time for calcul the mask position with numpy : 0.01394510269165039 nb_pixel_total : 767440 time to create 1 rle with new method : 0.026057958602905273 length of segment : 992 time for calcul the mask position with numpy : 0.00025725364685058594 nb_pixel_total : 11313 time to create 1 rle with old method : 0.013080596923828125 length of segment : 181 time for calcul the mask position with numpy : 0.00014209747314453125 nb_pixel_total : 7667 time to create 1 rle with old method : 0.009059429168701172 length of segment : 148 time for calcul the mask position with numpy : 0.0016407966613769531 nb_pixel_total : 109142 time to create 1 rle with old method : 0.1259174346923828 length of segment : 546 time for calcul the mask position with numpy : 0.00010037422180175781 nb_pixel_total : 3592 time to create 1 rle with old method : 0.0043680667877197266 length of segment : 63 time for calcul the mask position with numpy : 0.011542320251464844 nb_pixel_total : 733443 time to create 1 rle with new method : 0.020563602447509766 length of segment : 953 time for calcul the mask position with numpy : 0.0015494823455810547 nb_pixel_total : 99677 time to create 1 rle with old method : 0.11206674575805664 length of segment : 504 time for calcul the mask position with numpy : 0.00024008750915527344 nb_pixel_total : 10531 time to create 1 rle with old method : 0.011195659637451172 length of segment : 179 time for calcul the mask position with numpy : 0.0016238689422607422 nb_pixel_total : 114934 time to create 1 rle with old method : 0.12404608726501465 length of segment : 544 time for calcul the mask position with numpy : 0.014396429061889648 nb_pixel_total : 692465 time to create 1 rle with new method : 0.025953292846679688 length of segment : 976 time for calcul the mask position with numpy : 0.0001456737518310547 nb_pixel_total : 4878 time to create 1 rle with old method : 0.005298614501953125 length of segment : 123 time for calcul the mask position with numpy : 0.0004551410675048828 nb_pixel_total : 33941 time to create 1 rle with old method : 0.03632497787475586 length of segment : 189 time for calcul the mask position with numpy : 0.00036716461181640625 nb_pixel_total : 22494 time to create 1 rle with old method : 0.023976564407348633 length of segment : 196 time for calcul the mask position with numpy : 0.00010013580322265625 nb_pixel_total : 4174 time to create 1 rle with old method : 0.004423379898071289 length of segment : 125 time for calcul the mask position with numpy : 0.00011754035949707031 nb_pixel_total : 7922 time to create 1 rle with old method : 0.008626222610473633 length of segment : 111 time for calcul the mask position with numpy : 0.00023603439331054688 nb_pixel_total : 4433 time to create 1 rle with old method : 0.0049707889556884766 length of segment : 84 time for calcul the mask position with numpy : 0.0004792213439941406 nb_pixel_total : 13929 time to create 1 rle with old method : 0.015154361724853516 length of segment : 188 time for calcul the mask position with numpy : 0.00014472007751464844 nb_pixel_total : 3853 time to create 1 rle with old method : 0.004249095916748047 length of segment : 51 time for calcul the mask position with numpy : 0.00020456314086914062 nb_pixel_total : 5196 time to create 1 rle with old method : 0.0056383609771728516 length of segment : 82 time for calcul the mask position with numpy : 0.002698659896850586 nb_pixel_total : 114719 time to create 1 rle with old method : 0.11951303482055664 length of segment : 567 time for calcul the mask position with numpy : 0.0005891323089599609 nb_pixel_total : 18998 time to create 1 rle with old method : 0.020380496978759766 length of segment : 195 time for calcul the mask position with numpy : 0.00017786026000976562 nb_pixel_total : 10005 time to create 1 rle with old method : 0.010701179504394531 length of segment : 144 time for calcul the mask position with numpy : 0.0025565624237060547 nb_pixel_total : 109067 time to create 1 rle with old method : 0.11458206176757812 length of segment : 519 time for calcul the mask position with numpy : 0.0003604888916015625 nb_pixel_total : 12066 time to create 1 rle with old method : 0.013175725936889648 length of segment : 184 time for calcul the mask position with numpy : 0.0002295970916748047 nb_pixel_total : 4274 time to create 1 rle with old method : 0.004853963851928711 length of segment : 81 time spent for convertir_results : 2.263416290283203 Inside saveOutput : final : False verbose : 0 eke 12-6-18 : saveMask need to be cleaned for new output ! Number saved : None batch 1 Loaded 27 chid ids of type : 3594 Number RLEs to save : 8342 save missing photos in datou_result : time spend for datou_step_exec : 22.400913953781128 time spend to save output : 0.48406362533569336 total time spend for step 1 : 22.88497757911682 step2:crop_condition Thu Aug 14 14:40:52 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 : 13 ! batch 1 Loaded 27 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 ! map_result returned by crop_photo_return_map_crop : length : 9 About to insert : list_path_to_insert length 9 new photo from crops ! About to upload 9 photos upload in portfolio : 3736932 init cache_photo without model_param we have 9 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1755175253_2816304 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 9 photos in the portfolio 3736932 time of upload the photos Elapsed time : 2.6422507762908936 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 ! map_result returned by crop_photo_return_map_crop : length : 5 About to insert : list_path_to_insert length 5 new photo from crops ! About to upload 5 photos upload in portfolio : 3736932 init cache_photo without model_param we have 5 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1755175259_2816304 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 5 photos in the portfolio 3736932 time of upload the photos Elapsed time : 1.496962070465088 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 ! 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/1755175260_2816304 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 : 0.5928816795349121 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 ! map_result returned by crop_photo_return_map_crop : length : 10 About to insert : list_path_to_insert length 10 new photo from crops ! About to upload 10 photos upload in portfolio : 3736932 init cache_photo without model_param we have 10 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1755175270_2816304 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 10 photos in the portfolio 3736932 time of upload the photos Elapsed time : 2.698530673980713 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 ! map_result returned by crop_photo_return_map_crop : length : 2 About to insert : list_path_to_insert length 2 new photo from crops ! About to upload 2 photos upload in portfolio : 3736932 init cache_photo without model_param we have 2 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1755175273_2816304 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 2 photos in the portfolio 3736932 time of upload the photos Elapsed time : 0.8756799697875977 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 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 [1376966924, 1376966922, 1376966916, 1376966904, 1376966898, 1376966895, 1376966698, 1376966669, 1376966642, 1376966610, 1376966600, 1376966598, 1376966271] Looping around the photos to save general results len do output : 27 /1377024456Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1377024457Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1377024458Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1377024459Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1377024460Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1377024461Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1377024462Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1377024463Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1377024464Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1377024468Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1377024469Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1377024470Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1377024472Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1377024473Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1377024480Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1377024556Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1377024557Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1377024558Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1377024560Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1377024561Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1377024562Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1377024563Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1377024565Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1377024566Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1377024567Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1377024577Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1377024578Didn'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, '3534279') ('3318', None, '1376966924', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966922', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966916', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966904', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966898', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966895', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966698', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966669', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966642', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966610', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966600', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966598', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966271', None, None, None, None, None, '3534279') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 94 time used for this insertion : 0.018786191940307617 save_final save missing photos in datou_result : time spend for datou_step_exec : 21.43744421005249 time spend to save output : 0.020231962203979492 total time spend for step 2 : 21.45767617225647 step3:rle_unique_nms_with_priority Thu Aug 14 14:41:13 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec 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 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 27 chid ids of type : 3594 ++++++++++++++++++++++++++++nb_obj : 2 nb_hashtags : 1 time to prepare the origin masks : 0.21535611152648926 time for calcul the mask position with numpy : 0.1045076847076416 nb_pixel_total : 1989275 time to create 1 rle with new method : 0.11639714241027832 time for calcul the mask position with numpy : 0.006474018096923828 nb_pixel_total : 9644 time to create 1 rle with old method : 0.010945558547973633 time for calcul the mask position with numpy : 0.006734609603881836 nb_pixel_total : 74681 time to create 1 rle with old method : 0.08314871788024902 create new chi : 0.3379323482513428 time to delete rle : 0.022743940353393555 batch 1 Loaded 5 chid ids of type : 3594 ++Number RLEs to save : 1914 TO DO : save crop sub photo not yet done ! save time : 0.1418612003326416 nb_obj : 1 nb_hashtags : 1 time to prepare the origin masks : 0.12889885902404785 time for calcul the mask position with numpy : 0.06359481811523438 nb_pixel_total : 1306160 time to create 1 rle with new method : 0.08184432983398438 time for calcul the mask position with numpy : 0.011703252792358398 nb_pixel_total : 767440 time to create 1 rle with new method : 0.11737489700317383 create new chi : 0.2812631130218506 time to delete rle : 0.00033593177795410156 batch 1 Loaded 3 chid ids of type : 3594 +Number RLEs to save : 3064 TO DO : save crop sub photo not yet done ! save time : 0.21501564979553223 nb_obj : 5 nb_hashtags : 3 time to prepare the origin masks : 0.29129910469055176 time for calcul the mask position with numpy : 0.16664481163024902 nb_pixel_total : 1209407 time to create 1 rle with new method : 0.11211562156677246 time for calcul the mask position with numpy : 0.012202024459838867 nb_pixel_total : 732479 time to create 1 rle with new method : 0.12948870658874512 time for calcul the mask position with numpy : 0.006781578063964844 nb_pixel_total : 3592 time to create 1 rle with old method : 0.00406193733215332 time for calcul the mask position with numpy : 0.007248640060424805 nb_pixel_total : 109142 time to create 1 rle with old method : 0.12124514579772949 time for calcul the mask position with numpy : 0.0064127445220947266 nb_pixel_total : 7667 time to create 1 rle with old method : 0.008487701416015625 time for calcul the mask position with numpy : 0.0064525604248046875 nb_pixel_total : 11313 time to create 1 rle with old method : 0.01267099380493164 create new chi : 0.6084659099578857 time to delete rle : 0.0006954669952392578 batch 1 Loaded 11 chid ids of type : 3594 +++++Number RLEs to save : 4729 TO DO : save crop sub photo not yet done ! save time : 0.2853074073791504 nb_obj : 1 nb_hashtags : 1 time to prepare the origin masks : 0.04676079750061035 time for calcul the mask position with numpy : 0.02304220199584961 nb_pixel_total : 1973923 time to create 1 rle with new method : 0.0364224910736084 time for calcul the mask position with numpy : 0.00928187370300293 nb_pixel_total : 99677 time to create 1 rle with old method : 0.11371898651123047 create new chi : 0.19152545928955078 time to delete rle : 0.0003542900085449219 batch 1 Loaded 3 chid ids of type : 3594 +Number RLEs to save : 2088 TO DO : save crop sub photo not yet done ! save time : 0.154876708984375 No data in photo_id : 1376966898 No data in photo_id : 1376966895 nb_obj : 1 nb_hashtags : 1 time to prepare the origin masks : 0.04012608528137207 time for calcul the mask position with numpy : 0.021425485610961914 nb_pixel_total : 2063069 time to create 1 rle with new method : 0.09273838996887207 time for calcul the mask position with numpy : 0.006548166275024414 nb_pixel_total : 10531 time to create 1 rle with old method : 0.011789560317993164 create new chi : 0.1464228630065918 time to delete rle : 0.0003097057342529297 batch 1 Loaded 3 chid ids of type : 3594 +Number RLEs to save : 1438 TO DO : save crop sub photo not yet done ! save time : 0.11085271835327148 nb_obj : 4 nb_hashtags : 3 time to prepare the origin masks : 0.32716894149780273 time for calcul the mask position with numpy : 0.0492405891418457 nb_pixel_total : 1227396 time to create 1 rle with new method : 0.08503437042236328 time for calcul the mask position with numpy : 0.0066645145416259766 nb_pixel_total : 33941 time to create 1 rle with old method : 0.04033994674682617 time for calcul the mask position with numpy : 0.006635904312133789 nb_pixel_total : 4864 time to create 1 rle with old method : 0.00603938102722168 time for calcul the mask position with numpy : 0.011758804321289062 nb_pixel_total : 692465 time to create 1 rle with new method : 0.09864020347595215 time for calcul the mask position with numpy : 0.0070781707763671875 nb_pixel_total : 114934 time to create 1 rle with old method : 0.13176584243774414 create new chi : 0.4580512046813965 time to delete rle : 0.0006837844848632812 batch 1 Loaded 9 chid ids of type : 3594 ++++Number RLEs to save : 4734 TO DO : save crop sub photo not yet done ! save time : 0.2804272174835205 No data in photo_id : 1376966642 nb_obj : 3 nb_hashtags : 3 time to prepare the origin masks : 0.055715322494506836 time for calcul the mask position with numpy : 0.12761998176574707 nb_pixel_total : 2039010 time to create 1 rle with new method : 0.08284687995910645 time for calcul the mask position with numpy : 0.0067555904388427734 nb_pixel_total : 7922 time to create 1 rle with old method : 0.009149789810180664 time for calcul the mask position with numpy : 0.0064122676849365234 nb_pixel_total : 4174 time to create 1 rle with old method : 0.004830598831176758 time for calcul the mask position with numpy : 0.007037639617919922 nb_pixel_total : 22494 time to create 1 rle with old method : 0.025819063186645508 create new chi : 0.2798745632171631 time to delete rle : 0.0004794597625732422 batch 1 Loaded 7 chid ids of type : 3594 ++++Number RLEs to save : 1944 TO DO : save crop sub photo not yet done ! save time : 0.1332683563232422 nb_obj : 3 nb_hashtags : 2 time to prepare the origin masks : 0.06295013427734375 time for calcul the mask position with numpy : 0.0727224349975586 nb_pixel_total : 2051385 time to create 1 rle with new method : 0.12056112289428711 time for calcul the mask position with numpy : 0.006511211395263672 nb_pixel_total : 3853 time to create 1 rle with old method : 0.004340410232543945 time for calcul the mask position with numpy : 0.006532430648803711 nb_pixel_total : 13929 time to create 1 rle with old method : 0.015596151351928711 time for calcul the mask position with numpy : 0.006441593170166016 nb_pixel_total : 4433 time to create 1 rle with old method : 0.0049626827239990234 create new chi : 0.24115419387817383 time to delete rle : 0.0003135204315185547 batch 1 Loaded 7 chid ids of type : 3594 +++Number RLEs to save : 1726 TO DO : save crop sub photo not yet done ! save time : 0.13876795768737793 nb_obj : 4 nb_hashtags : 3 time to prepare the origin masks : 0.25693464279174805 time for calcul the mask position with numpy : 0.05611014366149902 nb_pixel_total : 1931879 time to create 1 rle with new method : 0.050153493881225586 time for calcul the mask position with numpy : 0.0065271854400634766 nb_pixel_total : 2808 time to create 1 rle with old method : 0.0033261775970458984 time for calcul the mask position with numpy : 0.006413459777832031 nb_pixel_total : 18998 time to create 1 rle with old method : 0.021811485290527344 time for calcul the mask position with numpy : 0.006974935531616211 nb_pixel_total : 114719 time to create 1 rle with old method : 0.13002920150756836 time for calcul the mask position with numpy : 0.006406307220458984 nb_pixel_total : 5196 time to create 1 rle with old method : 0.005923032760620117 create new chi : 0.3007206916809082 time to delete rle : 0.0005474090576171875 batch 1 Loaded 9 chid ids of type : 3594 ++++Number RLEs to save : 2949 TO DO : save crop sub photo not yet done ! save time : 0.19759654998779297 nb_obj : 3 nb_hashtags : 2 time to prepare the origin masks : 0.0529017448425293 time for calcul the mask position with numpy : 0.02239847183227539 nb_pixel_total : 1948193 time to create 1 rle with new method : 0.0777437686920166 time for calcul the mask position with numpy : 0.0063970088958740234 nb_pixel_total : 4274 time to create 1 rle with old method : 0.004931926727294922 time for calcul the mask position with numpy : 0.006811857223510742 nb_pixel_total : 12066 time to create 1 rle with old method : 0.013623714447021484 time for calcul the mask position with numpy : 0.007615089416503906 nb_pixel_total : 109067 time to create 1 rle with old method : 0.1255505084991455 create new chi : 0.27044200897216797 time to delete rle : 0.0004324913024902344 batch 1 Loaded 7 chid ids of type : 3594 +++Number RLEs to save : 2648 TO DO : save crop sub photo not yet done ! save time : 0.18567538261413574 map_output_result : {1376966924: (0.0, 'Should be the crop_list due to order', 0), 1376966922: (0.0, 'Should be the crop_list due to order', 0), 1376966916: (0.0, 'Should be the crop_list due to order', 0), 1376966904: (0.0, 'Should be the crop_list due to order', 0), 1376966898: (0.0, 'Should be the crop_list due to order', 0.0), 1376966895: (0.0, 'Should be the crop_list due to order', 0.0), 1376966698: (0.0, 'Should be the crop_list due to order', 0), 1376966669: (0.0, 'Should be the crop_list due to order', 0), 1376966642: (0.0, 'Should be the crop_list due to order', 0.0), 1376966610: (0.0, 'Should be the crop_list due to order', 0), 1376966600: (0.0, 'Should be the crop_list due to order', 0), 1376966598: (0.0, 'Should be the crop_list due to order', 0), 1376966271: (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 [1376966924, 1376966922, 1376966916, 1376966904, 1376966898, 1376966895, 1376966698, 1376966669, 1376966642, 1376966610, 1376966600, 1376966598, 1376966271] Looping around the photos to save general results len do output : 13 /1376966924.Didn't retrieve data . /1376966922.Didn't retrieve data . /1376966916.Didn't retrieve data . /1376966904.Didn't retrieve data . /1376966898.Didn't retrieve data . /1376966895.Didn't retrieve data . /1376966698.Didn't retrieve data . /1376966669.Didn't retrieve data . /1376966642.Didn't retrieve data . /1376966610.Didn't retrieve data . /1376966600.Didn't retrieve data . /1376966598.Didn't retrieve data . /1376966271.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, '3534279') ('3318', None, '1376966924', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966922', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966916', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966904', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966898', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966895', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966698', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966669', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966642', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966610', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966600', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966598', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966271', None, None, None, None, None, '3534279') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 39 time used for this insertion : 0.01362919807434082 save_final save missing photos in datou_result : time spend for datou_step_exec : 6.8259336948394775 time spend to save output : 0.01414942741394043 total time spend for step 3 : 6.840083122253418 step4:ventilate_hashtags_in_portfolio Thu Aug 14 14:41:20 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 : 25980071 get user id for portfolio 25980071 SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=25980071 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('carton','metal','flou','pet_fonce','environnement','pehd','autre','mal_croppe','pet_clair','papier','background')) AND mptpi.`min_score`=0.5 To do 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`=25980071 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('carton','metal','flou','pet_fonce','environnement','pehd','autre','mal_croppe','pet_clair','papier','background')) AND mptpi.`min_score`=0.5 To do lien utilise dans velours : https://www.fotonower.com/velours/25984950,25984951,25984953,25984954,25984955,25984956,25984957,25984958,25984959,25984960,25984961?tags=papier,flou,environnement,autre,pet_fonce,metal,pehd,background,carton,pet_clair,mal_croppe Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : ventilate_hashtags_in_portfolio we use saveGeneral [1376966924, 1376966922, 1376966916, 1376966904, 1376966898, 1376966895, 1376966698, 1376966669, 1376966642, 1376966610, 1376966600, 1376966598, 1376966271] Looping around the photos to save general results len do output : 1 /25980071. 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, '3534279') ('3318', None, '1376966924', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966922', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966916', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966904', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966898', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966895', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966698', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966669', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966642', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966610', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966600', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966598', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966271', None, None, None, None, None, '3534279') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 14 time used for this insertion : 0.014245748519897461 save_final save missing photos in datou_result : time spend for datou_step_exec : 0.44482874870300293 time spend to save output : 0.01455378532409668 total time spend for step 4 : 0.4593825340270996 step5:final Thu Aug 14 14:41:20 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 : {1376966924: ('0.1299853049295365',), 1376966922: ('0.1299853049295365',), 1376966916: ('0.1299853049295365',), 1376966904: ('0.1299853049295365',), 1376966898: ('0.1299853049295365',), 1376966895: ('0.1299853049295365',), 1376966698: ('0.1299853049295365',), 1376966669: ('0.1299853049295365',), 1376966642: ('0.1299853049295365',), 1376966610: ('0.1299853049295365',), 1376966600: ('0.1299853049295365',), 1376966598: ('0.1299853049295365',), 1376966271: ('0.1299853049295365',)} new output for save of step final : {1376966924: ('0.1299853049295365',), 1376966922: ('0.1299853049295365',), 1376966916: ('0.1299853049295365',), 1376966904: ('0.1299853049295365',), 1376966898: ('0.1299853049295365',), 1376966895: ('0.1299853049295365',), 1376966698: ('0.1299853049295365',), 1376966669: ('0.1299853049295365',), 1376966642: ('0.1299853049295365',), 1376966610: ('0.1299853049295365',), 1376966600: ('0.1299853049295365',), 1376966598: ('0.1299853049295365',), 1376966271: ('0.1299853049295365',)} [1376966924, 1376966922, 1376966916, 1376966904, 1376966898, 1376966895, 1376966698, 1376966669, 1376966642, 1376966610, 1376966600, 1376966598, 1376966271] Looping around the photos to save general results len do output : 13 /1376966924.Didn't retrieve data . /1376966922.Didn't retrieve data . /1376966916.Didn't retrieve data . /1376966904.Didn't retrieve data . /1376966898.Didn't retrieve data . /1376966895.Didn't retrieve data . /1376966698.Didn't retrieve data . /1376966669.Didn't retrieve data . /1376966642.Didn't retrieve data . /1376966610.Didn't retrieve data . /1376966600.Didn't retrieve data . /1376966598.Didn't retrieve data . /1376966271.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, '3534279') ('3318', None, '1376966924', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966922', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966916', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966904', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966898', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966895', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966698', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966669', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966642', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966610', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966600', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966598', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966271', None, None, None, None, None, '3534279') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 39 time used for this insertion : 0.01306295394897461 save_final save missing photos in datou_result : time spend for datou_step_exec : 0.1256716251373291 time spend to save output : 0.013654232025146484 total time spend for step 5 : 0.13932585716247559 step6:blur_detection Thu Aug 14 14:41:21 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed 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/1755175227_2816304_1376966924_8122c62de7c6ce084332ec2fefd08810.jpg resize: (1080, 1920) 1376966924 -2.2786649330955004 treat image : temp/1755175227_2816304_1376966922_af3783843c57ec4f3cc0c8de70b61314.jpg resize: (1080, 1920) 1376966922 -1.3214862309127375 treat image : temp/1755175227_2816304_1376966916_3a20a406afc85287a66037b05bc3c8c0.jpg resize: (1080, 1920) 1376966916 -2.341219175716967 treat image : temp/1755175227_2816304_1376966904_790ac4c4c53ac5c857f84941d20e9a82.jpg resize: (1080, 1920) 1376966904 -2.4412063080888196 treat image : temp/1755175227_2816304_1376966898_03d9014efa8df01316b6b03c7140ca45.jpg resize: (1080, 1920) 1376966898 -0.7401667131219918 treat image : temp/1755175227_2816304_1376966895_922528d45f3cbfe8a7d313942c914917.jpg resize: (1080, 1920) 1376966895 -1.5180834765032907 treat image : temp/1755175227_2816304_1376966698_323b157b19ba1620213d8b00fe16ac03.jpg resize: (1080, 1920) 1376966698 -2.7071609532816083 treat image : temp/1755175227_2816304_1376966669_b24c3fa1a46aece77d5996a6748aebe1.jpg resize: (1080, 1920) 1376966669 -3.038396940057085 treat image : temp/1755175227_2816304_1376966642_a8ccb0d7698d749ca9d20819517e2806.jpg resize: (1080, 1920) 1376966642 -2.3862427856389012 treat image : temp/1755175227_2816304_1376966610_e930dea93cf088319fca146608527294.jpg resize: (1080, 1920) 1376966610 -1.4543192458932628 treat image : temp/1755175227_2816304_1376966600_f1f986cba33264efec1e608884801b8c.jpg resize: (1080, 1920) 1376966600 -2.717755213691077 treat image : temp/1755175227_2816304_1376966598_c349c47fded426b9b425f6d9d8ffe184.jpg resize: (1080, 1920) 1376966598 -2.9634385941960453 treat image : temp/1755175227_2816304_1376966271_9b36dceda8427fd6ef218f6cd1934ec9.jpg resize: (1080, 1920) 1376966271 -2.1382479495097884 treat image : temp/1755175227_2816304_1376966916_3a20a406afc85287a66037b05bc3c8c0_rle_crop_3914828390_0.png resize: (181, 113) 1377024456 -0.6024688671551954 treat image : temp/1755175227_2816304_1376966698_323b157b19ba1620213d8b00fe16ac03_rle_crop_3914828396_0.png resize: (178, 109) 1377024457 -0.7634350133344062 treat image : temp/1755175227_2816304_1376966669_b24c3fa1a46aece77d5996a6748aebe1_rle_crop_3914828399_0.png resize: (123, 83) 1377024458 -2.0142145041785624 treat image : temp/1755175227_2816304_1376966610_e930dea93cf088319fca146608527294_rle_crop_3914828403_0.png resize: (111, 97) 1377024459 -0.8756684397459235 treat image : temp/1755175227_2816304_1376966600_f1f986cba33264efec1e608884801b8c_rle_crop_3914828405_0.png resize: (174, 128) 1377024460 -1.8633662951012506 treat image : temp/1755175227_2816304_1376966600_f1f986cba33264efec1e608884801b8c_rle_crop_3914828404_0.png resize: (84, 86) 1377024461 -1.8281274285067404 treat image : temp/1755175227_2816304_1376966598_c349c47fded426b9b425f6d9d8ffe184_rle_crop_3914828407_0.png resize: (81, 85) 1377024462 -0.8264017523833354 treat image : temp/1755175227_2816304_1376966271_9b36dceda8427fd6ef218f6cd1934ec9_rle_crop_3914828412_0.png resize: (184, 120) 1377024463 -0.6270806964790778 treat image : temp/1755175227_2816304_1376966271_9b36dceda8427fd6ef218f6cd1934ec9_rle_crop_3914828413_0.png resize: (80, 98) 1377024464 -2.501146736114214 treat image : temp/1755175227_2816304_1376966669_b24c3fa1a46aece77d5996a6748aebe1_rle_crop_3914828398_0.png resize: (975, 989) 1377024468 -0.06063862849368341 treat image : temp/1755175227_2816304_1376966669_b24c3fa1a46aece77d5996a6748aebe1_rle_crop_3914828400_0.png resize: (185, 257) 1377024469 -0.7914375575878313 treat image : temp/1755175227_2816304_1376966610_e930dea93cf088319fca146608527294_rle_crop_3914828401_0.png resize: (173, 186) 1377024470 -1.6277945723590368 treat image : temp/1755175227_2816304_1376966598_c349c47fded426b9b425f6d9d8ffe184_rle_crop_3914828410_0.png resize: (134, 113) 1377024472 -1.9213665851192232 treat image : temp/1755175227_2816304_1376966598_c349c47fded426b9b425f6d9d8ffe184_rle_crop_3914828409_0.png resize: (163, 176) 1377024473 -1.6498821786564695 treat image : temp/1755175227_2816304_1376966600_f1f986cba33264efec1e608884801b8c_rle_crop_3914828406_0.png resize: (51, 112) 1377024480 -4.345854677608984 treat image : temp/1755175227_2816304_1376966924_8122c62de7c6ce084332ec2fefd08810_rle_crop_3914828388_0.png resize: (115, 107) 1377024556 -4.007609708912158 treat image : temp/1755175227_2816304_1376966924_8122c62de7c6ce084332ec2fefd08810_rle_crop_3914828387_0.png resize: (298, 333) 1377024557 0.32769666002409786 treat image : temp/1755175227_2816304_1376966922_af3783843c57ec4f3cc0c8de70b61314_rle_crop_3914828389_0.png resize: (991, 1069) 1377024558 0.14443368585725952 treat image : temp/1755175227_2816304_1376966916_3a20a406afc85287a66037b05bc3c8c0_rle_crop_3914828394_0.png resize: (950, 1023) 1377024560 0.16334409614708495 treat image : temp/1755175227_2816304_1376966916_3a20a406afc85287a66037b05bc3c8c0_rle_crop_3914828391_0.png resize: (148, 64) 1377024561 -1.0645422314446122 treat image : temp/1755175227_2816304_1376966916_3a20a406afc85287a66037b05bc3c8c0_rle_crop_3914828392_0.png resize: (529, 354) 1377024562 -0.1914006624555495 treat image : temp/1755175227_2816304_1376966904_790ac4c4c53ac5c857f84941d20e9a82_rle_crop_3914828395_0.png resize: (494, 352) 1377024563 -0.37708199774751955 treat image : temp/1755175227_2816304_1376966669_b24c3fa1a46aece77d5996a6748aebe1_rle_crop_3914828397_0.png resize: (542, 354) 1377024565 0.319213481923752 treat image : temp/1755175227_2816304_1376966598_c349c47fded426b9b425f6d9d8ffe184_rle_crop_3914828408_0.png resize: (560, 359) 1377024566 -0.1347533856222714 treat image : temp/1755175227_2816304_1376966271_9b36dceda8427fd6ef218f6cd1934ec9_rle_crop_3914828411_0.png resize: (518, 363) 1377024567 0.21494737468164443 treat image : temp/1755175227_2816304_1376966916_3a20a406afc85287a66037b05bc3c8c0_rle_crop_3914828393_0.png resize: (61, 71) 1377024577 3.7109128645702687 treat image : temp/1755175227_2816304_1376966610_e930dea93cf088319fca146608527294_rle_crop_3914828402_0.png resize: (119, 49) 1377024578 -1.9398180923167232 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 : 40 time used for this insertion : 0.013006925582885742 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 40 time used for this insertion : 0.0145721435546875 save missing photos in datou_result : time spend for datou_step_exec : 12.16762638092041 time spend to save output : 0.032514333724975586 total time spend for step 6 : 12.200140714645386 step7:brightness Thu Aug 14 14:41:33 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 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 calcul brightness treat image : temp/1755175227_2816304_1376966924_8122c62de7c6ce084332ec2fefd08810.jpg treat image : temp/1755175227_2816304_1376966922_af3783843c57ec4f3cc0c8de70b61314.jpg treat image : temp/1755175227_2816304_1376966916_3a20a406afc85287a66037b05bc3c8c0.jpg treat image : temp/1755175227_2816304_1376966904_790ac4c4c53ac5c857f84941d20e9a82.jpg treat image : temp/1755175227_2816304_1376966898_03d9014efa8df01316b6b03c7140ca45.jpg treat image : temp/1755175227_2816304_1376966895_922528d45f3cbfe8a7d313942c914917.jpg treat image : temp/1755175227_2816304_1376966698_323b157b19ba1620213d8b00fe16ac03.jpg treat image : temp/1755175227_2816304_1376966669_b24c3fa1a46aece77d5996a6748aebe1.jpg treat image : temp/1755175227_2816304_1376966642_a8ccb0d7698d749ca9d20819517e2806.jpg treat image : temp/1755175227_2816304_1376966610_e930dea93cf088319fca146608527294.jpg treat image : temp/1755175227_2816304_1376966600_f1f986cba33264efec1e608884801b8c.jpg treat image : temp/1755175227_2816304_1376966598_c349c47fded426b9b425f6d9d8ffe184.jpg treat image : temp/1755175227_2816304_1376966271_9b36dceda8427fd6ef218f6cd1934ec9.jpg treat image : temp/1755175227_2816304_1376966916_3a20a406afc85287a66037b05bc3c8c0_rle_crop_3914828390_0.png treat image : temp/1755175227_2816304_1376966698_323b157b19ba1620213d8b00fe16ac03_rle_crop_3914828396_0.png treat image : temp/1755175227_2816304_1376966669_b24c3fa1a46aece77d5996a6748aebe1_rle_crop_3914828399_0.png treat image : temp/1755175227_2816304_1376966610_e930dea93cf088319fca146608527294_rle_crop_3914828403_0.png treat image : temp/1755175227_2816304_1376966600_f1f986cba33264efec1e608884801b8c_rle_crop_3914828405_0.png treat image : temp/1755175227_2816304_1376966600_f1f986cba33264efec1e608884801b8c_rle_crop_3914828404_0.png treat image : temp/1755175227_2816304_1376966598_c349c47fded426b9b425f6d9d8ffe184_rle_crop_3914828407_0.png treat image : temp/1755175227_2816304_1376966271_9b36dceda8427fd6ef218f6cd1934ec9_rle_crop_3914828412_0.png treat image : temp/1755175227_2816304_1376966271_9b36dceda8427fd6ef218f6cd1934ec9_rle_crop_3914828413_0.png treat image : temp/1755175227_2816304_1376966669_b24c3fa1a46aece77d5996a6748aebe1_rle_crop_3914828398_0.png treat image : temp/1755175227_2816304_1376966669_b24c3fa1a46aece77d5996a6748aebe1_rle_crop_3914828400_0.png treat image : temp/1755175227_2816304_1376966610_e930dea93cf088319fca146608527294_rle_crop_3914828401_0.png treat image : temp/1755175227_2816304_1376966598_c349c47fded426b9b425f6d9d8ffe184_rle_crop_3914828410_0.png treat image : temp/1755175227_2816304_1376966598_c349c47fded426b9b425f6d9d8ffe184_rle_crop_3914828409_0.png treat image : temp/1755175227_2816304_1376966600_f1f986cba33264efec1e608884801b8c_rle_crop_3914828406_0.png treat image : temp/1755175227_2816304_1376966924_8122c62de7c6ce084332ec2fefd08810_rle_crop_3914828388_0.png treat image : temp/1755175227_2816304_1376966924_8122c62de7c6ce084332ec2fefd08810_rle_crop_3914828387_0.png treat image : temp/1755175227_2816304_1376966922_af3783843c57ec4f3cc0c8de70b61314_rle_crop_3914828389_0.png treat image : temp/1755175227_2816304_1376966916_3a20a406afc85287a66037b05bc3c8c0_rle_crop_3914828394_0.png treat image : temp/1755175227_2816304_1376966916_3a20a406afc85287a66037b05bc3c8c0_rle_crop_3914828391_0.png treat image : temp/1755175227_2816304_1376966916_3a20a406afc85287a66037b05bc3c8c0_rle_crop_3914828392_0.png treat image : temp/1755175227_2816304_1376966904_790ac4c4c53ac5c857f84941d20e9a82_rle_crop_3914828395_0.png treat image : temp/1755175227_2816304_1376966669_b24c3fa1a46aece77d5996a6748aebe1_rle_crop_3914828397_0.png treat image : temp/1755175227_2816304_1376966598_c349c47fded426b9b425f6d9d8ffe184_rle_crop_3914828408_0.png treat image : temp/1755175227_2816304_1376966271_9b36dceda8427fd6ef218f6cd1934ec9_rle_crop_3914828411_0.png treat image : temp/1755175227_2816304_1376966916_3a20a406afc85287a66037b05bc3c8c0_rle_crop_3914828393_0.png treat image : temp/1755175227_2816304_1376966610_e930dea93cf088319fca146608527294_rle_crop_3914828402_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 : 40 time used for this insertion : 0.0145111083984375 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 40 time used for this insertion : 0.013291358947753906 save missing photos in datou_result : time spend for datou_step_exec : 3.7059786319732666 time spend to save output : 0.03250694274902344 total time spend for step 7 : 3.73848557472229 step8:velours_tree Thu Aug 14 14:41:37 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 VR 22-3-18 : For now we do not clean correctly the datou structure 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 : 0.1352825164794922 time spend to save output : 4.8160552978515625e-05 total time spend for step 8 : 0.1353306770324707 step9:send_mail_cod Thu Aug 14 14:41:37 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 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_P25980071_14-08-2025_14_41_37.pdf 25984950 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 .imagette259849501755175297 25984951 imagette259849511755175298 25984954 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 .imagette259849541755175298 25984955 imagette259849551755175298 25984956 change filename to text .change filename to text .change filename to text .change filename to text .imagette259849561755175298 25984957 imagette259849571755175299 25984958 imagette259849581755175299 25984959 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 .imagette259849591755175299 25984960 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 .imagette259849601755175300 25984961 imagette259849611755175301 SELECT h.hashtag,pcr.value FROM MTRUser.portfolio_carac_ratio pcr, MTRBack.hashtags h where pcr.portfolio_id=25980071 and hashtag_type = 3594 and pcr.hashtag_id = h.hashtag_id; velour_link : https://www.fotonower.com/velours/25984950,25984951,25984953,25984954,25984955,25984956,25984957,25984958,25984959,25984960,25984961?tags=papier,flou,environnement,autre,pet_fonce,metal,pehd,background,carton,pet_clair,mal_croppe args[1376966924] : ((1376966924, -2.2786649330955004, 492609224), (1376966924, 0.5938323046217746, 2107752395), '0.1299853049295365') We are sending mail with results at report@fotonower.com args[1376966922] : ((1376966922, -1.3214862309127375, 492688767), (1376966922, 0.4953488960946095, 2107752395), '0.1299853049295365') We are sending mail with results at report@fotonower.com args[1376966916] : ((1376966916, -2.341219175716967, 492609224), (1376966916, 0.5422945081881259, 2107752395), '0.1299853049295365') We are sending mail with results at report@fotonower.com args[1376966904] : ((1376966904, -2.4412063080888196, 492609224), (1376966904, 0.600468498281568, 2107752395), '0.1299853049295365') We are sending mail with results at report@fotonower.com args[1376966898] : ((1376966898, -0.7401667131219918, 492688767), (1376966898, 0.6328010709760563, 2107752395), '0.1299853049295365') We are sending mail with results at report@fotonower.com args[1376966895] : ((1376966895, -1.5180834765032907, 492688767), (1376966895, 0.511035931244829, 2107752395), '0.1299853049295365') We are sending mail with results at report@fotonower.com args[1376966698] : ((1376966698, -2.7071609532816083, 492609224), (1376966698, 0.6145496492767827, 2107752395), '0.1299853049295365') We are sending mail with results at report@fotonower.com args[1376966669] : ((1376966669, -3.038396940057085, 492609224), (1376966669, 0.3956873145480157, 2107752395), '0.1299853049295365') We are sending mail with results at report@fotonower.com args[1376966642] : ((1376966642, -2.3862427856389012, 492609224), (1376966642, 0.6079463596449737, 2107752395), '0.1299853049295365') We are sending mail with results at report@fotonower.com args[1376966610] : ((1376966610, -1.4543192458932628, 492688767), (1376966610, 0.3390298625649692, 2107752395), '0.1299853049295365') We are sending mail with results at report@fotonower.com args[1376966600] : ((1376966600, -2.717755213691077, 492609224), (1376966600, 0.36169308455814103, 2107752395), '0.1299853049295365') We are sending mail with results at report@fotonower.com args[1376966598] : ((1376966598, -2.9634385941960453, 492609224), (1376966598, 0.37665212699111916, 2107752395), '0.1299853049295365') We are sending mail with results at report@fotonower.com args[1376966271] : ((1376966271, -2.1382479495097884, 492609224), (1376966271, 0.654835645213997, 2107752395), '0.1299853049295365') We are sending mail with results at report@fotonower.com refus_total : 0.1299853049295365 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=25980071 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_P25980071_14-08-2025_14_41_37.pdf results_Auto_P25980071_14-08-2025_14_41_37.pdf uploaded to url https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P25980071_14-08-2025_14_41_37.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','25980071','results_Auto_P25980071_14-08-2025_14_41_37.pdf','https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P25980071_14-08-2025_14_41_37.pdf','pdf','','0.88','0.1299853049295365') message_in_mail: Bonjour,
Veuillez trouver ci dessous les résultats du service carac on demand pour le portfolio: https://www.fotonower.com/view/25980071

https://www.fotonower.com/image?json=false&list_photos_id=1376966924
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1376966922
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1376966916
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1376966904
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1376966898
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1376966895
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1376966698
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1376966669
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1376966642
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1376966610
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1376966600
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1376966598
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1376966271
Bravo, la photo est bien prise.

Dans ces conditions,le taux de refus est: 13.00%
Veuillez trouver les photos des contaminants.

exemples de contaminants: papier: https://www.fotonower.com/view/25984950?limit=200
exemples de contaminants: autre: https://www.fotonower.com/view/25984954?limit=200
exemples de contaminants: metal: https://www.fotonower.com/view/25984956?limit=200
exemples de contaminants: carton: https://www.fotonower.com/view/25984959?limit=200
exemples de contaminants: pet_clair: https://www.fotonower.com/view/25984960?limit=200
Veuillez trouver le rapport en pdf:https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P25980071_14-08-2025_14_41_37.pdf.

Lien vers velours :https://www.fotonower.com/velours/25984950,25984951,25984953,25984954,25984955,25984956,25984957,25984958,25984959,25984960,25984961?tags=papier,flou,environnement,autre,pet_fonce,metal,pehd,background,carton,pet_clair,mal_croppe.


L'équipe Fotonower 202 b'' Server: nginx Date: Thu, 14 Aug 2025 12:41:44 GMT Content-Length: 0 Connection: close X-Message-Id: 8ZoY0VUiS9Kc6BIySb_gLg 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 [1376966924, 1376966922, 1376966916, 1376966904, 1376966898, 1376966895, 1376966698, 1376966669, 1376966642, 1376966610, 1376966600, 1376966598, 1376966271] 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, '3534279') ('3318', None, '1376966924', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966922', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966916', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966904', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966898', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966895', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966698', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966669', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966642', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966610', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966600', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966598', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966271', None, None, None, None, None, '3534279') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 13 time used for this insertion : 0.016522645950317383 save_final save missing photos in datou_result : time spend for datou_step_exec : 7.228953123092651 time spend to save output : 0.016805410385131836 total time spend for step 9 : 7.245758533477783 step10:split_time_score Thu Aug 14 14:41:44 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed 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'}] (('09', 53),) ERROR counted https://github.com/fotonower/Velours/issues/663#issuecomment-421136223 {} 14082025 25980071 Nombre de photos uploadées : 53 / 23040 (0%) 14082025 25980071 Nombre de photos taguées (types de déchets): 0 / 53 (0%) 14082025 25980071 Nombre de photos taguées (volume) : 0 / 53 (0%) elapsed_time : load_data_split_time_score 1.430511474609375e-06 elapsed_time : order_list_meta_photo_and_scores 5.0067901611328125e-06 ????????????????????????????????????????????????????? elapsed_time : fill_and_build_computed_from_old_data 0.0022542476654052734 Catched exception ! Connect or reconnect ! Catched exception ! Connect or reconnect ! elapsed_time : insert_dashboard_record_day_entry 0.2691023349761963 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 : 0.1280742026748971 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P25974582_14-08-2025_10_11_57.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 25974582 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number 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`=25974582 AND mptpi.`type`=3594 To do Qualite : 0.015116423932613166 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P25974586_14-08-2025_10_01_29.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 25974586 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number 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`=25974586 AND mptpi.`type`=3594 To do Qualite : 0.1361061197916667 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P25980071_14-08-2025_14_41_37.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 25980071 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number 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`=25980071 AND mptpi.`type`=3594 To do Qualite : 0.12013578869047618 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P25980101_14-08-2025_13_01_43.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 25980101 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number 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`=25980101 AND mptpi.`type`=3594 To do Qualite : 0.1582214988425926 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P25980105_14-08-2025_12_51_32.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 25980105 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number 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`=25980105 AND mptpi.`type`=3594 To do Qualite : 0.16527360973324515 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P25980109_14-08-2025_12_41_51.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 25980109 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number 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`=25980109 AND mptpi.`type`=3594 To do Qualite : 0.03430676118827159 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P25983542_14-08-2025_14_21_54.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 25983542 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number 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`=25983542 AND mptpi.`type`=3594 To do Qualite : 0.08205182613168727 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P25983560_14-08-2025_14_11_41.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 25983560 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number 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`=25983560 AND mptpi.`type`=3594 To do NUMBER BATCH : 0 # DISPLAY ALL COLLECTED DATA : {'14082025': {'nb_upload': 53, '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 [1376966924, 1376966922, 1376966916, 1376966904, 1376966898, 1376966895, 1376966698, 1376966669, 1376966642, 1376966610, 1376966600, 1376966598, 1376966271] Looping around the photos to save general results len do output : 1 /25980071Didn'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, '3534279') ('3318', None, '1376966924', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966922', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966916', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966904', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966898', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966895', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966698', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966669', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966642', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966610', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966600', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966598', None, None, None, None, None, '3534279') ('3318', None, None, None, None, None, None, None, '3534279') ('3318', None, '1376966271', None, None, None, None, None, '3534279') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 14 time used for this insertion : 0.015119791030883789 save_final save missing photos in datou_result : time spend for datou_step_exec : 0.9305295944213867 time spend to save output : 0.015295743942260742 total time spend for step 10 : 0.9458253383636475 caffe_path_current : About to save ! 2 After save, about to update current ! ret : 2 len(input) + len(total_photo_id_missing) : 13 set_done_treatment 49.44user 16.80system 1:20.00elapsed 82%CPU (0avgtext+0avgdata 2820212maxresident)k 64648inputs+41344outputs (16major+1423140minor)pagefaults 0swaps