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 : 1277193 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 : ['4076212'] with mtr_portfolio_ids : ['28699660'] and first list_photo_ids : [] new path : /proc/1277193/ Inside batchDatouExec : verbose : 0 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! List Step Type Loaded in datou : mask_detect, crop_condition, rle_unique_nms_with_priority, ventilate_hashtags_in_portfolio, final, blur_detection, brightness, velours_tree, send_mail_cod, split_time_score over limit max, limiting to limit_max 40 list_input_json : [] origin We have 1 , BFBFBFBFBFBFBFBFBFBFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 10 ; length of list_pids : 10 ; length of list_args : 10 time to download the photos : 1.4171841144561768 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 Wed Nov 19 10:00:30 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Beginning of datou step mask_detect ! save_polygon : True begin detect begin to check gpu status inside check gpu memory l 3637 free memory gpu now : 10998 max_wait_temp : 1 max_wait : 0 gpu_flag : 0 2025-11-19 10:00:32.839702: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2025-11-19 10:00:32.866495: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493010000 Hz 2025-11-19 10:00:32.868746: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7fadc4000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-11-19 10:00:32.868793: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-11-19 10:00:32.872359: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-11-19 10:00:33.163370: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x2cc372f0 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-11-19 10:00:33.163415: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-11-19 10:00:33.164843: 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 2025-11-19 10:00:33.165230: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-11-19 10:00:33.168134: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-11-19 10:00:33.170729: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-11-19 10:00:33.171196: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-11-19 10:00:33.173789: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-11-19 10:00:33.175047: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-11-19 10:00:33.179990: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-11-19 10:00:33.181724: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-11-19 10:00:33.181796: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-11-19 10:00:33.182772: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-11-19 10:00:33.182793: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-11-19 10:00:33.182804: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-11-19 10:00:33.184360: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 10193 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:41:00.0, compute capability: 7.5) WARNING:tensorflow:From /home/admin/workarea/git/Velours/python/mtr/mask_rcnn/mask_detection.py:69: The name tf.keras.backend.set_session is deprecated. Please use tf.compat.v1.keras.backend.set_session instead. 2025-11-19 10:00:33.425458: 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 2025-11-19 10:00:33.425550: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-11-19 10:00:33.425577: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-11-19 10:00:33.425602: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-11-19 10:00:33.425626: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-11-19 10:00:33.425650: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-11-19 10:00:33.425674: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-11-19 10:00:33.425698: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-11-19 10:00:33.427857: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-11-19 10:00:33.429026: 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 2025-11-19 10:00:33.429052: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-11-19 10:00:33.429066: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-11-19 10:00:33.429078: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-11-19 10:00:33.429090: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-11-19 10:00:33.429103: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-11-19 10:00:33.429115: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-11-19 10:00:33.429127: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-11-19 10:00:33.430315: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-11-19 10:00:33.430340: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-11-19 10:00:33.430347: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-11-19 10:00:33.430354: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-11-19 10:00:33.431897: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 10193 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:41:00.0, compute capability: 7.5) Using TensorFlow backend. WARNING:tensorflow:From /home/admin/workarea/install/Mask_RCNN/model.py:396: calling crop_and_resize_v1 (from tensorflow.python.ops.image_ops_impl) with box_ind is deprecated and will be removed in a future version. Instructions for updating: box_ind is deprecated, use box_indices instead WARNING:tensorflow:From /home/admin/workarea/install/Mask_RCNN/model.py:703: to_int32 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.cast` instead. WARNING:tensorflow:From /home/admin/workarea/install/Mask_RCNN/model.py:729: to_float (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.cast` instead. Inside mask_sub_process Inside mask_detect About to load cache.load_thcl_param To do loadFromThcl(), then load ParamDescType : thcl2847 thcls : [{'id': 2847, 'mtr_user_id': 31, 'name': 'learn_RUBBIA_REFUS_AMIENS_23', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'photo_desc_type': 5275, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'}] thcl {'id': 2847, 'mtr_user_id': 31, 'name': 'learn_RUBBIA_REFUS_AMIENS_23', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'photo_desc_type': 5275, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'} Update svm_hashtag_type_desc : 5275 FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (5275, 'learn_RUBBIA_REFUS_AMIENS_23', 16384, 25088, 'learn_RUBBIA_REFUS_AMIENS_23', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 1, datetime.datetime(2021, 4, 23, 14, 19, 39), datetime.datetime(2021, 4, 23, 14, 19, 39)) {'thcl': {'id': 2847, 'mtr_user_id': 31, 'name': 'learn_RUBBIA_REFUS_AMIENS_23', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'photo_desc_type': 5275, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'}, 'list_hashtags': ['background', 'papier', 'carton', 'metal', 'pet_clair', 'autre', 'pehd', 'pet_fonce', 'environnement'], 'list_hashtags_csv': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'svm_hashtag_type_desc': 5275, 'photo_desc_type': 5275, 'pb_hashtag_id_or_classifier': 0} list_class_names : ['background', 'papier', 'carton', 'metal', 'pet_clair', 'autre', 'pehd', 'pet_fonce', 'environnement'] Configurations: BACKBONE resnet101 BACKBONE_SHAPES [[160 160] [ 80 80] [ 40 40] [ 20 20] [ 10 10]] BACKBONE_STRIDES [4, 8, 16, 32, 64] BATCH_SIZE 1 BBOX_STD_DEV [0.1 0.1 0.2 0.2] DETECTION_MAX_INSTANCES 100 DETECTION_MIN_CONFIDENCE 0.3 DETECTION_NMS_THRESHOLD 0.3 GPU_COUNT 1 IMAGES_PER_GPU 1 IMAGE_MAX_DIM 640 IMAGE_MIN_DIM 640 IMAGE_PADDING True IMAGE_SHAPE [640 640 3] LEARNING_MOMENTUM 0.9 LEARNING_RATE 0.001 LOSS_WEIGHTS {'rpn_class_loss': 1.0, 'rpn_bbox_loss': 1.0, 'mrcnn_class_loss': 1.0, 'mrcnn_bbox_loss': 1.0, 'mrcnn_mask_loss': 1.0} MASK_POOL_SIZE 14 MASK_SHAPE [28, 28] MAX_GT_INSTANCES 100 MEAN_PIXEL [123.7 116.8 103.9] MINI_MASK_SHAPE (56, 56) NAME learn_RUBBIA_REFUS_AMIENS_23 NUM_CLASSES 9 POOL_SIZE 7 POST_NMS_ROIS_INFERENCE 1000 POST_NMS_ROIS_TRAINING 2000 ROI_POSITIVE_RATIO 0.33 RPN_ANCHOR_RATIOS [0.5, 1, 2] RPN_ANCHOR_SCALES (16, 32, 64, 128, 256) RPN_ANCHOR_STRIDE 1 RPN_BBOX_STD_DEV [0.1 0.1 0.2 0.2] RPN_NMS_THRESHOLD 0.7 RPN_TRAIN_ANCHORS_PER_IMAGE 256 STEPS_PER_EPOCH 1000 TRAIN_ROIS_PER_IMAGE 200 USE_MINI_MASK True USE_RPN_ROIS True VALIDATION_STEPS 50 WEIGHT_DECAY 0.0001 model_param file didn't exist model_name : learn_RUBBIA_REFUS_AMIENS_23 model_type : mask_rcnn list file need : ['mask_model.h5'] file exist in s3 : ['mask_model.h5'] file manque in s3 : [] 2025-11-19 10:00:40.928859: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-11-19 10:00:41.086340: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 local folder : /data/models_weight/learn_RUBBIA_REFUS_AMIENS_23 /data/models_weight/learn_RUBBIA_REFUS_AMIENS_23/mask_model.h5 size_local : 256009536 size in s3 : 256009536 create time local : 2021-08-09 09:43:22 create time in s3 : 2021-08-06 18:54:04 mask_model.h5 already exist and didn't need to update list_images length : 10 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 45.00000 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: 37.00000 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: 37.00000 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: 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 : 2 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 48.00000 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: 51.00000 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: 58.00000 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: 42.00000 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: 54.00000 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 : 3 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 14.00000 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 1277667 begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 5163 tf kernel not reseted sub process len(results) : 10 len(list_Values) 0 None max_time_sub_proc : 3600 parent process len(results) : 10 len(list_Values) 0 process is alive finish correctly or not : True after detect begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 10196 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 : 0.0020275115966796875 nb_pixel_total : 113715 time to create 1 rle with old method : 0.12532639503479004 length of segment : 525 time for calcul the mask position with numpy : 0.00011372566223144531 nb_pixel_total : 3328 time to create 1 rle with old method : 0.004053354263305664 length of segment : 71 time for calcul the mask position with numpy : 0.00011229515075683594 nb_pixel_total : 3302 time to create 1 rle with old method : 0.005944252014160156 length of segment : 53 time for calcul the mask position with numpy : 0.00017547607421875 nb_pixel_total : 8469 time to create 1 rle with old method : 0.009849071502685547 length of segment : 154 time for calcul the mask position with numpy : 0.00016736984252929688 nb_pixel_total : 5480 time to create 1 rle with old method : 0.006316423416137695 length of segment : 167 time for calcul the mask position with numpy : 0.0027239322662353516 nb_pixel_total : 44702 time to create 1 rle with old method : 0.051223039627075195 length of segment : 749 time for calcul the mask position with numpy : 0.00017499923706054688 nb_pixel_total : 6329 time to create 1 rle with old method : 0.007404327392578125 length of segment : 169 time for calcul the mask position with numpy : 0.0008256435394287109 nb_pixel_total : 37612 time to create 1 rle with old method : 0.041235923767089844 length of segment : 387 time for calcul the mask position with numpy : 0.0012943744659423828 nb_pixel_total : 93836 time to create 1 rle with old method : 0.10259485244750977 length of segment : 513 time for calcul the mask position with numpy : 0.00700688362121582 nb_pixel_total : 525954 time to create 1 rle with new method : 0.03518199920654297 length of segment : 1265 time for calcul the mask position with numpy : 0.012858152389526367 nb_pixel_total : 1027615 time to create 1 rle with new method : 0.22304129600524902 length of segment : 1159 time for calcul the mask position with numpy : 0.0018513202667236328 nb_pixel_total : 107385 time to create 1 rle with old method : 0.1209115982055664 length of segment : 481 time for calcul the mask position with numpy : 0.000553131103515625 nb_pixel_total : 24731 time to create 1 rle with old method : 0.04135584831237793 length of segment : 221 time for calcul the mask position with numpy : 0.0001442432403564453 nb_pixel_total : 5618 time to create 1 rle with old method : 0.006692409515380859 length of segment : 82 time spent for convertir_results : 1.9524736404418945 Inside saveOutput : final : False verbose : 0 eke 12-6-18 : saveMask need to be cleaned for new output ! Number saved : None batch 1 Loaded 14 chid ids of type : 3594 Number RLEs to save : 5996 save missing photos in datou_result : time spend for datou_step_exec : 21.90053367614746 time spend to save output : 0.41066741943359375 total time spend for step 1 : 22.311201095581055 step2:crop_condition Wed Nov 19 10:00:52 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure Loading chi in step crop with photo_hashtag_type : 3594 Loading chi in step crop for list_pids : 10 ! batch 1 Loaded 14 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 ! map_result returned by crop_photo_return_map_crop : length : 3 About to insert : list_path_to_insert length 3 new photo from crops ! About to upload 3 photos upload in portfolio : 3736932 init cache_photo without model_param we have 3 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1763542853_1277193 INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1763542853), 0.0, 0.0, 14, '', 0, 0, '1763542828_1277193_1395152830_cb3afddd249d32a6823743988e939d14_rle_crop_4038539445_0.png', 0, 84, 151, 0, 1763542853,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1763542853), 0.0, 0.0, 14, '', 0, 0, '1763542828_1277193_1395152830_cb3afddd249d32a6823743988e939d14_rle_crop_4038539444_0.png', 0, 91, 153, 0, 1763542853,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1763542853), 0.0, 0.0, 14, '', 0, 0, '1763542828_1277193_1395152822_dc306ea5918ee8697abb90e990ff1d99_rle_crop_4038539447_0.png', 0, 90, 169, 0, 1763542853,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 3 photos in the portfolio 3736932 time of upload the photos Elapsed time : 1.0859832763671875 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 begin to crop the class : metal param for this class : {'min_score': 0.7} filtre for class : metal hashtag_id of this class : 492628673 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 ! map_result returned by crop_photo_return_map_crop : length : 8 About to insert : list_path_to_insert length 8 new photo from crops ! About to upload 8 photos upload in portfolio : 3736932 init cache_photo without model_param we have 8 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1763542862_1277193 INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1763542863), 0.0, 0.0, 14, '', 0, 0, '1763542828_1277193_1395152876_5aaa01b4aed06f93a4a9d8713442cdd6_rle_crop_4038539441_0.png', 0, 360, 520, 0, 1763542863,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1763542863), 0.0, 0.0, 14, '', 0, 0, '1763542828_1277193_1395152871_55efb1e8637ec62a2cef646fe0e65478_rle_crop_4038539442_0.png', 0, 67, 70, 0, 1763542863,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1763542863), 0.0, 0.0, 14, '', 0, 0, '1763542828_1277193_1395152830_cb3afddd249d32a6823743988e939d14_rle_crop_4038539443_0.png', 0, 74, 53, 0, 1763542863,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1763542863), 0.0, 0.0, 14, '', 0, 0, '1763542828_1277193_1395152819_33459654f7c8d8f70a0e616157d454c9_rle_crop_4038539450_0.png', 0, 823, 968, 0, 1763542863,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1763542863), 0.0, 0.0, 14, '', 0, 0, '1763542828_1277193_1395152819_33459654f7c8d8f70a0e616157d454c9_rle_crop_4038539449_0.png', 0, 316, 510, 0, 1763542863,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1763542863), 0.0, 0.0, 14, '', 0, 0, '1763542828_1277193_1395152816_181b34e36097737104eeaf7d73a13bf2_rle_crop_4038539451_0.png', 0, 1349, 965, 0, 1763542863,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1763542863), 0.0, 0.0, 14, '', 0, 0, '1763542828_1277193_1395152752_5d39f766bf0a51061fcfa9a760ea01d0_rle_crop_4038539454_0.png', 0, 82, 82, 0, 1763542863,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1763542863), 0.0, 0.0, 14, '', 0, 0, '1763542828_1277193_1395152752_5d39f766bf0a51061fcfa9a760ea01d0_rle_crop_4038539452_0.png', 0, 320, 478, 0, 1763542863,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 8 photos in the portfolio 3736932 time of upload the photos Elapsed time : 2.159287214279175 we have finished the crop for the class : pet_clair begin to crop the class : autre param for this class : {'min_score': 0.7} filtre for class : autre hashtag_id of this class : 494826614 we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! map_result returned by crop_photo_return_map_crop : length : 3 About to insert : list_path_to_insert length 3 new photo from crops ! About to upload 3 photos upload in portfolio : 3736932 init cache_photo without model_param we have 3 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1763542867_1277193 INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1763542868), 0.0, 0.0, 14, '', 0, 0, '1763542828_1277193_1395152826_acf826edfa448e6b69c723162bf4813f_rle_crop_4038539446_0.png', 0, 773, 549, 0, 1763542868,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1763542868), 0.0, 0.0, 14, '', 0, 0, '1763542828_1277193_1395152819_33459654f7c8d8f70a0e616157d454c9_rle_crop_4038539448_0.png', 0, 165, 375, 0, 1763542868,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1763542868), 0.0, 0.0, 14, '', 0, 0, '1763542828_1277193_1395152752_5d39f766bf0a51061fcfa9a760ea01d0_rle_crop_4038539453_0.png', 0, 191, 219, 0, 1763542868,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 3 photos in the portfolio 3736932 time of upload the photos Elapsed time : 3.6969704627990723 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 Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : crop_condition we use saveGeneral [1395152876, 1395152873, 1395152871, 1395152838, 1395152830, 1395152826, 1395152822, 1395152819, 1395152816, 1395152752] Looping around the photos to save general results len do output : 14 /1395172007Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1395172009Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1395172010Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1395172087Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1395172088Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1395172089Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1395172091Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1395172092Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1395172093Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1395172094Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1395172096Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1395172132Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1395172133Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1395172135Didn'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, '4076212') ('3318', '28699660', '1395152876', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152873', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152871', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152838', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152830', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152826', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152822', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152819', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152816', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152752', None, None, None, None, None, '4076212') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 52 time used for this insertion : 0.019969940185546875 save_final save missing photos in datou_result : time spend for datou_step_exec : 15.834425210952759 time spend to save output : 0.020676136016845703 total time spend for step 2 : 15.855101346969604 step3:rle_unique_nms_with_priority Wed Nov 19 10:01:08 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array VR 22-3-18 : For now we do not clean correctly the datou structure Begin step rle-unique-nms batch 1 Loaded 14 chid ids of type : 3594 ++++++++++++++++++++++++nb_obj : 1 nb_hashtags : 1 time to prepare the origin masks : 0.0974125862121582 time for calcul the mask position with numpy : 0.16856098175048828 nb_pixel_total : 1959885 time to create 1 rle with new method : 0.17158246040344238 time for calcul the mask position with numpy : 0.006633758544921875 nb_pixel_total : 113715 time to create 1 rle with old method : 0.12089180946350098 create new chi : 0.47771620750427246 time to delete rle : 0.029284954071044922 batch 1 Loaded 3 chid ids of type : 3594 +Number RLEs to save : 2130 TO DO : save crop sub photo not yet done ! save time : 0.173065185546875 No data in photo_id : 1395152873 nb_obj : 1 nb_hashtags : 1 time to prepare the origin masks : 0.12452149391174316 time for calcul the mask position with numpy : 0.1585853099822998 nb_pixel_total : 2070272 time to create 1 rle with new method : 0.1697711944580078 time for calcul the mask position with numpy : 0.006241321563720703 nb_pixel_total : 3328 time to create 1 rle with old method : 0.0036237239837646484 create new chi : 0.34740734100341797 time to delete rle : 0.0002446174621582031 batch 1 Loaded 3 chid ids of type : 3594 +Number RLEs to save : 1222 TO DO : save crop sub photo not yet done ! save time : 0.12026238441467285 No data in photo_id : 1395152838 nb_obj : 3 nb_hashtags : 2 time to prepare the origin masks : 0.16916513442993164 time for calcul the mask position with numpy : 0.08819937705993652 nb_pixel_total : 2056349 time to create 1 rle with new method : 0.20058941841125488 time for calcul the mask position with numpy : 0.0060045719146728516 nb_pixel_total : 5480 time to create 1 rle with old method : 0.005822181701660156 time for calcul the mask position with numpy : 0.006170749664306641 nb_pixel_total : 8469 time to create 1 rle with old method : 0.00913691520690918 time for calcul the mask position with numpy : 0.006212711334228516 nb_pixel_total : 3302 time to create 1 rle with old method : 0.003568887710571289 create new chi : 0.33566904067993164 time to delete rle : 0.00030159950256347656 batch 1 Loaded 7 chid ids of type : 3594 ++++Number RLEs to save : 1828 TO DO : save crop sub photo not yet done ! save time : 0.1637859344482422 nb_obj : 1 nb_hashtags : 1 time to prepare the origin masks : 0.03589963912963867 time for calcul the mask position with numpy : 0.019158363342285156 nb_pixel_total : 2028898 time to create 1 rle with new method : 0.06921243667602539 time for calcul the mask position with numpy : 0.0063762664794921875 nb_pixel_total : 44702 time to create 1 rle with old method : 0.04889035224914551 create new chi : 0.1508331298828125 time to delete rle : 0.000354766845703125 batch 1 Loaded 3 chid ids of type : 3594 +++++++++Number RLEs to save : 2578 TO DO : save crop sub photo not yet done ! save time : 0.20734715461730957 nb_obj : 1 nb_hashtags : 1 time to prepare the origin masks : 0.03396916389465332 time for calcul the mask position with numpy : 0.020702838897705078 nb_pixel_total : 2067271 time to create 1 rle with new method : 0.21478748321533203 time for calcul the mask position with numpy : 0.006352424621582031 nb_pixel_total : 6329 time to create 1 rle with old method : 0.006779193878173828 create new chi : 0.26045989990234375 time to delete rle : 0.0002875328063964844 batch 1 Loaded 3 chid ids of type : 3594 +Number RLEs to save : 1418 TO DO : save crop sub photo not yet done ! save time : 0.12004518508911133 nb_obj : 3 nb_hashtags : 2 time to prepare the origin masks : 0.16524243354797363 time for calcul the mask position with numpy : 0.03892850875854492 nb_pixel_total : 1416198 time to create 1 rle with new method : 0.1569812297821045 time for calcul the mask position with numpy : 0.009131431579589844 nb_pixel_total : 525954 time to create 1 rle with new method : 0.17368721961975098 time for calcul the mask position with numpy : 0.007846355438232422 nb_pixel_total : 93836 time to create 1 rle with old method : 0.10274505615234375 time for calcul the mask position with numpy : 0.0060918331146240234 nb_pixel_total : 37612 time to create 1 rle with old method : 0.039559125900268555 create new chi : 0.5506336688995361 time to delete rle : 0.0005905628204345703 batch 1 Loaded 7 chid ids of type : 3594 +++Number RLEs to save : 5410 TO DO : save crop sub photo not yet done ! save time : 0.35181641578674316 nb_obj : 1 nb_hashtags : 1 time to prepare the origin masks : 0.03507518768310547 time for calcul the mask position with numpy : 0.012618541717529297 nb_pixel_total : 1045985 time to create 1 rle with new method : 0.18824481964111328 time for calcul the mask position with numpy : 0.012755632400512695 nb_pixel_total : 1027615 time to create 1 rle with new method : 0.06288623809814453 create new chi : 0.28317952156066895 time to delete rle : 0.0003266334533691406 batch 1 Loaded 3 chid ids of type : 3594 ++Number RLEs to save : 3398 TO DO : save crop sub photo not yet done ! save time : 0.23468565940856934 nb_obj : 3 nb_hashtags : 2 time to prepare the origin masks : 0.2522714138031006 time for calcul the mask position with numpy : 0.11786103248596191 nb_pixel_total : 1935866 time to create 1 rle with new method : 0.10385012626647949 time for calcul the mask position with numpy : 0.005908012390136719 nb_pixel_total : 5618 time to create 1 rle with old method : 0.0061719417572021484 time for calcul the mask position with numpy : 0.006001710891723633 nb_pixel_total : 24731 time to create 1 rle with old method : 0.025792360305786133 time for calcul the mask position with numpy : 0.006283998489379883 nb_pixel_total : 107385 time to create 1 rle with old method : 0.14208698272705078 create new chi : 0.4243030548095703 time to delete rle : 0.00042510032653808594 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 : 0.20718169212341309 map_output_result : {1395152876: (0.0, 'Should be the crop_list due to order', 0), 1395152873: (0.0, 'Should be the crop_list due to order', 0.0), 1395152871: (0.0, 'Should be the crop_list due to order', 0), 1395152838: (0.0, 'Should be the crop_list due to order', 0.0), 1395152830: (0.0, 'Should be the crop_list due to order', 0), 1395152826: (0.0, 'Should be the crop_list due to order', 0), 1395152822: (0.0, 'Should be the crop_list due to order', 0), 1395152819: (0.0, 'Should be the crop_list due to order', 0), 1395152816: (0.0, 'Should be the crop_list due to order', 0), 1395152752: (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 [1395152876, 1395152873, 1395152871, 1395152838, 1395152830, 1395152826, 1395152822, 1395152819, 1395152816, 1395152752] Looping around the photos to save general results len do output : 10 /1395152876.Didn't retrieve data . /1395152873.Didn't retrieve data . /1395152871.Didn't retrieve data . /1395152838.Didn't retrieve data . /1395152830.Didn't retrieve data . /1395152826.Didn't retrieve data . /1395152822.Didn't retrieve data . /1395152819.Didn't retrieve data . /1395152816.Didn't retrieve data . /1395152752.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, '4076212') ('3318', '28699660', '1395152876', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152873', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152871', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152838', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152830', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152826', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152822', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152819', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152816', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152752', None, None, None, None, None, '4076212') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 30 time used for this insertion : 0.015289783477783203 save_final save missing photos in datou_result : time spend for datou_step_exec : 5.6491782665252686 time spend to save output : 0.01565408706665039 total time spend for step 3 : 5.664832353591919 step4:ventilate_hashtags_in_portfolio Wed Nov 19 10:01:14 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! 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 : 28699660 get user id for portfolio 28699660 SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=28699660 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('pehd','pet_clair','environnement','autre','background','pet_fonce','carton','flou','metal','papier','mal_croppe')) AND mptpi.`min_score`=0.5 To do To do SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=28699660 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('pehd','pet_clair','environnement','autre','background','pet_fonce','carton','flou','metal','papier','mal_croppe')) AND mptpi.`min_score`=0.5 To do Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") To do ! Use context local managing function ! SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=28699660 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('pehd','pet_clair','environnement','autre','background','pet_fonce','carton','flou','metal','papier','mal_croppe')) AND mptpi.`min_score`=0.5 To do lien utilise dans velours : https://marlene.fotonower.com/velours/28701236,28701237,28701238,28701239,28701240,28701241,28701242,28701243,28701244,28701245,28701246?tags=pehd,pet_clair,environnement,autre,background,pet_fonce,carton,flou,metal,papier,mal_croppe Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : ventilate_hashtags_in_portfolio we use saveGeneral [1395152876, 1395152873, 1395152871, 1395152838, 1395152830, 1395152826, 1395152822, 1395152819, 1395152816, 1395152752] Looping around the photos to save general results len do output : 1 /28699660. 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, '4076212') ('3318', '28699660', '1395152876', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152873', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152871', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152838', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152830', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152826', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152822', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152819', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152816', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152752', None, None, None, None, None, '4076212') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 11 time used for this insertion : 0.01642775535583496 save_final save missing photos in datou_result : time spend for datou_step_exec : 1.6594264507293701 time spend to save output : 0.01673746109008789 total time spend for step 4 : 1.676163911819458 step5:final Wed Nov 19 10:01:15 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 : {1395152876: ('0.09684008487654322',), 1395152873: ('0.09684008487654322',), 1395152871: ('0.09684008487654322',), 1395152838: ('0.09684008487654322',), 1395152830: ('0.09684008487654322',), 1395152826: ('0.09684008487654322',), 1395152822: ('0.09684008487654322',), 1395152819: ('0.09684008487654322',), 1395152816: ('0.09684008487654322',), 1395152752: ('0.09684008487654322',)} new output for save of step final : {1395152876: ('0.09684008487654322',), 1395152873: ('0.09684008487654322',), 1395152871: ('0.09684008487654322',), 1395152838: ('0.09684008487654322',), 1395152830: ('0.09684008487654322',), 1395152826: ('0.09684008487654322',), 1395152822: ('0.09684008487654322',), 1395152819: ('0.09684008487654322',), 1395152816: ('0.09684008487654322',), 1395152752: ('0.09684008487654322',)} [1395152876, 1395152873, 1395152871, 1395152838, 1395152830, 1395152826, 1395152822, 1395152819, 1395152816, 1395152752] Looping around the photos to save general results len do output : 10 /1395152876.Didn't retrieve data . /1395152873.Didn't retrieve data . /1395152871.Didn't retrieve data . /1395152838.Didn't retrieve data . /1395152830.Didn't retrieve data . /1395152826.Didn't retrieve data . /1395152822.Didn't retrieve data . /1395152819.Didn't retrieve data . /1395152816.Didn't retrieve data . /1395152752.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, '4076212') ('3318', '28699660', '1395152876', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152873', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152871', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152838', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152830', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152826', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152822', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152819', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152816', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152752', None, None, None, None, None, '4076212') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 30 time used for this insertion : 0.012867450714111328 save_final save missing photos in datou_result : time spend for datou_step_exec : 0.11210060119628906 time spend to save output : 0.013395071029663086 total time spend for step 5 : 0.12549567222595215 step6:blur_detection Wed Nov 19 10:01:15 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/1763542828_1277193_1395152876_5aaa01b4aed06f93a4a9d8713442cdd6.jpg resize: (1080, 1920) 1395152876 -3.9171452320765523 treat image : temp/1763542828_1277193_1395152873_afebaccbc9bcf99db7c2ade373abc3c1.jpg resize: (1080, 1920) 1395152873 -1.9920809780022355 treat image : temp/1763542828_1277193_1395152871_55efb1e8637ec62a2cef646fe0e65478.jpg resize: (1080, 1920) 1395152871 -0.4157715457820401 treat image : temp/1763542828_1277193_1395152838_d9de6a17b98f19d56d04da49999038df.jpg resize: (1080, 1920) 1395152838 -0.030837103937727508 treat image : temp/1763542828_1277193_1395152830_cb3afddd249d32a6823743988e939d14.jpg resize: (1080, 1920) 1395152830 1.4653362356690112 treat image : temp/1763542828_1277193_1395152826_acf826edfa448e6b69c723162bf4813f.jpg resize: (1080, 1920) 1395152826 -0.4835336616912432 treat image : temp/1763542828_1277193_1395152822_dc306ea5918ee8697abb90e990ff1d99.jpg resize: (1080, 1920) 1395152822 1.0358681497685227 treat image : temp/1763542828_1277193_1395152819_33459654f7c8d8f70a0e616157d454c9.jpg resize: (1080, 1920) 1395152819 -4.631443294923833 treat image : temp/1763542828_1277193_1395152816_181b34e36097737104eeaf7d73a13bf2.jpg resize: (1080, 1920) 1395152816 2.958220884512948 treat image : temp/1763542828_1277193_1395152752_5d39f766bf0a51061fcfa9a760ea01d0.jpg resize: (1080, 1920) 1395152752 -1.1504118925365179 treat image : temp/1763542828_1277193_1395152830_cb3afddd249d32a6823743988e939d14_rle_crop_4038539445_0.png resize: (151, 84) 1395172007 -2.4960329719831784 treat image : temp/1763542828_1277193_1395152830_cb3afddd249d32a6823743988e939d14_rle_crop_4038539444_0.png resize: (153, 91) 1395172009 -1.87254430007646 treat image : temp/1763542828_1277193_1395152822_dc306ea5918ee8697abb90e990ff1d99_rle_crop_4038539447_0.png resize: (169, 90) 1395172010 -2.310036861902551 treat image : temp/1763542828_1277193_1395152876_5aaa01b4aed06f93a4a9d8713442cdd6_rle_crop_4038539441_0.png resize: (520, 360) 1395172087 0.05874219406809564 treat image : temp/1763542828_1277193_1395152871_55efb1e8637ec62a2cef646fe0e65478_rle_crop_4038539442_0.png resize: (70, 67) 1395172088 -1.1214274397576232 treat image : temp/1763542828_1277193_1395152830_cb3afddd249d32a6823743988e939d14_rle_crop_4038539443_0.png resize: (53, 74) 1395172089 0.6029425235943572 treat image : temp/1763542828_1277193_1395152819_33459654f7c8d8f70a0e616157d454c9_rle_crop_4038539450_0.png resize: (968, 823) 1395172091 -0.28166783190933525 treat image : temp/1763542828_1277193_1395152819_33459654f7c8d8f70a0e616157d454c9_rle_crop_4038539449_0.png resize: (510, 316) 1395172092 0.2839137471929997 treat image : temp/1763542828_1277193_1395152816_181b34e36097737104eeaf7d73a13bf2_rle_crop_4038539451_0.png resize: (965, 1349) 1395172093 0.4683461324608877 treat image : temp/1763542828_1277193_1395152752_5d39f766bf0a51061fcfa9a760ea01d0_rle_crop_4038539454_0.png resize: (82, 82) 1395172094 -2.4001537122077687 treat image : temp/1763542828_1277193_1395152752_5d39f766bf0a51061fcfa9a760ea01d0_rle_crop_4038539452_0.png resize: (478, 320) 1395172096 0.32304655119464293 treat image : temp/1763542828_1277193_1395152826_acf826edfa448e6b69c723162bf4813f_rle_crop_4038539446_0.png resize: (549, 773) 1395172132 1.2220633161776784 treat image : temp/1763542828_1277193_1395152819_33459654f7c8d8f70a0e616157d454c9_rle_crop_4038539448_0.png resize: (375, 165) 1395172133 -1.2616448690543365 treat image : temp/1763542828_1277193_1395152752_5d39f766bf0a51061fcfa9a760ea01d0_rle_crop_4038539453_0.png resize: (219, 191) 1395172135 -1.112710417895587 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 : 24 time used for this insertion : 0.01641368865966797 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 24 time used for this insertion : 0.01473689079284668 save missing photos in datou_result : time spend for datou_step_exec : 9.01028037071228 time spend to save output : 0.03574514389038086 total time spend for step 6 : 9.046025514602661 step7:brightness Wed Nov 19 10:01:24 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/1763542828_1277193_1395152876_5aaa01b4aed06f93a4a9d8713442cdd6.jpg treat image : temp/1763542828_1277193_1395152873_afebaccbc9bcf99db7c2ade373abc3c1.jpg treat image : temp/1763542828_1277193_1395152871_55efb1e8637ec62a2cef646fe0e65478.jpg treat image : temp/1763542828_1277193_1395152838_d9de6a17b98f19d56d04da49999038df.jpg treat image : temp/1763542828_1277193_1395152830_cb3afddd249d32a6823743988e939d14.jpg treat image : temp/1763542828_1277193_1395152826_acf826edfa448e6b69c723162bf4813f.jpg treat image : temp/1763542828_1277193_1395152822_dc306ea5918ee8697abb90e990ff1d99.jpg treat image : temp/1763542828_1277193_1395152819_33459654f7c8d8f70a0e616157d454c9.jpg treat image : temp/1763542828_1277193_1395152816_181b34e36097737104eeaf7d73a13bf2.jpg treat image : temp/1763542828_1277193_1395152752_5d39f766bf0a51061fcfa9a760ea01d0.jpg treat image : temp/1763542828_1277193_1395152830_cb3afddd249d32a6823743988e939d14_rle_crop_4038539445_0.png treat image : temp/1763542828_1277193_1395152830_cb3afddd249d32a6823743988e939d14_rle_crop_4038539444_0.png treat image : temp/1763542828_1277193_1395152822_dc306ea5918ee8697abb90e990ff1d99_rle_crop_4038539447_0.png treat image : temp/1763542828_1277193_1395152876_5aaa01b4aed06f93a4a9d8713442cdd6_rle_crop_4038539441_0.png treat image : temp/1763542828_1277193_1395152871_55efb1e8637ec62a2cef646fe0e65478_rle_crop_4038539442_0.png treat image : temp/1763542828_1277193_1395152830_cb3afddd249d32a6823743988e939d14_rle_crop_4038539443_0.png treat image : temp/1763542828_1277193_1395152819_33459654f7c8d8f70a0e616157d454c9_rle_crop_4038539450_0.png treat image : temp/1763542828_1277193_1395152819_33459654f7c8d8f70a0e616157d454c9_rle_crop_4038539449_0.png treat image : temp/1763542828_1277193_1395152816_181b34e36097737104eeaf7d73a13bf2_rle_crop_4038539451_0.png treat image : temp/1763542828_1277193_1395152752_5d39f766bf0a51061fcfa9a760ea01d0_rle_crop_4038539454_0.png treat image : temp/1763542828_1277193_1395152752_5d39f766bf0a51061fcfa9a760ea01d0_rle_crop_4038539452_0.png treat image : temp/1763542828_1277193_1395152826_acf826edfa448e6b69c723162bf4813f_rle_crop_4038539446_0.png treat image : temp/1763542828_1277193_1395152819_33459654f7c8d8f70a0e616157d454c9_rle_crop_4038539448_0.png treat image : temp/1763542828_1277193_1395152752_5d39f766bf0a51061fcfa9a760ea01d0_rle_crop_4038539453_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 : 24 time used for this insertion : 0.016996145248413086 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 24 time used for this insertion : 0.015329122543334961 save missing photos in datou_result : time spend for datou_step_exec : 2.6639628410339355 time spend to save output : 0.03678274154663086 total time spend for step 7 : 2.7007455825805664 step8:velours_tree Wed Nov 19 10:01:27 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 : 0.13956880569458008 time spend to save output : 4.1961669921875e-05 total time spend for step 8 : 0.13961076736450195 step9:send_mail_cod Wed Nov 19 10:01:27 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_P28699660_19-11-2025_10_01_27.pdf 28701236 imagette287012361763542887 28701237 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 .imagette287012371763542887 28701239 change filename to text .change filename to text .change filename to text .imagette287012391763542888 28701240 imagette287012401763542888 28701241 imagette287012411763542888 28701242 imagette287012421763542888 28701243 imagette287012431763542888 28701244 imagette287012441763542888 28701245 change filename to text .change filename to text .change filename to text .imagette287012451763542888 28701246 imagette287012461763542889 SELECT h.hashtag,pcr.value FROM MTRUser.portfolio_carac_ratio pcr, MTRBack.hashtags h where pcr.portfolio_id=28699660 and hashtag_type = 3594 and pcr.hashtag_id = h.hashtag_id; velour_link : https://marlene.fotonower.com/velours/28701236,28701237,28701238,28701239,28701240,28701241,28701242,28701243,28701244,28701245,28701246?tags=pehd,pet_clair,environnement,autre,background,pet_fonce,carton,flou,metal,papier,mal_croppe args[1395152876] : ((1395152876, -3.9171452320765523, 492609224), (1395152876, 0.5494425058433103, 2107752395), '0.09684008487654322') We are sending mail with results at report@fotonower.com args[1395152873] : ((1395152873, -1.9920809780022355, 492688767), (1395152873, 0.4449251694180103, 2107752395), '0.09684008487654322') We are sending mail with results at report@fotonower.com args[1395152871] : ((1395152871, -0.4157715457820401, 492688767), (1395152871, 0.5213095864185577, 2107752395), '0.09684008487654322') We are sending mail with results at report@fotonower.com args[1395152838] : ((1395152838, -0.030837103937727508, 492688767), (1395152838, 0.4971580103000609, 2107752395), '0.09684008487654322') We are sending mail with results at report@fotonower.com args[1395152830] : ((1395152830, 1.4653362356690112, 492688767), (1395152830, 0.7279987119625849, 2107752395), '0.09684008487654322') We are sending mail with results at report@fotonower.com args[1395152826] : ((1395152826, -0.4835336616912432, 492688767), (1395152826, 0.9236210123316323, 2107752395), '0.09684008487654322') We are sending mail with results at report@fotonower.com args[1395152822] : ((1395152822, 1.0358681497685227, 492688767), (1395152822, 0.8008651904220492, 2107752395), '0.09684008487654322') We are sending mail with results at report@fotonower.com args[1395152819] : ((1395152819, -4.631443294923833, 492609224), (1395152819, 0.5761759777292857, 2107752395), '0.09684008487654322') We are sending mail with results at report@fotonower.com args[1395152816] : ((1395152816, 2.958220884512948, 492688767), (1395152816, 1.2030482205215713, 2107752395), '0.09684008487654322') We are sending mail with results at report@fotonower.com args[1395152752] : ((1395152752, -1.1504118925365179, 492688767), (1395152752, 0.6053220198532719, 2107752395), '0.09684008487654322') We are sending mail with results at report@fotonower.com refus_total : 0.09684008487654322 2022-04-13 10:29:59 0 SELECT ph.photo_id,ph.url,ph.username,ph.uploaded_at,ph.text FROM MTRBack.photos_view ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=28699660 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_P28699660_19-11-2025_10_01_27.pdf results_Auto_P28699660_19-11-2025_10_01_27.pdf uploaded to url https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P28699660_19-11-2025_10_01_27.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','28699660','results_Auto_P28699660_19-11-2025_10_01_27.pdf','https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P28699660_19-11-2025_10_01_27.pdf','pdf','','0.31','0.09684008487654322') message_in_mail: Bonjour,
Veuillez trouver ci dessous les résultats du service carac on demand pour le portfolio: https://www.fotonower.com/view/28699660

https://www.fotonower.com/image?json=false&list_photos_id=1395152876
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1395152873
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1395152871
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1395152838
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1395152830
La photo est trop floue, merci de reprendre une photo.(avec le score = 1.4653362356690112)
https://www.fotonower.com/image?json=false&list_photos_id=1395152826
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1395152822
La photo est trop floue, merci de reprendre une photo.(avec le score = 1.0358681497685227)
https://www.fotonower.com/image?json=false&list_photos_id=1395152819
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1395152816
La photo est trop floue, merci de reprendre une photo.(avec le score = 2.958220884512948)
https://www.fotonower.com/image?json=false&list_photos_id=1395152752
Bravo, la photo est bien prise.

Dans ces conditions,le taux de refus est: 9.68%
Veuillez trouver les photos des contaminants.

exemples de contaminants: pet_clair: https://www.fotonower.com/view/28701237?limit=200
exemples de contaminants: autre: https://www.fotonower.com/view/28701239?limit=200
exemples de contaminants: papier: https://www.fotonower.com/view/28701245?limit=200
Veuillez trouver le rapport en pdf:https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P28699660_19-11-2025_10_01_27.pdf.

Lien vers velours :https://marlene.fotonower.com/velours/28701236,28701237,28701238,28701239,28701240,28701241,28701242,28701243,28701244,28701245,28701246?tags=pehd,pet_clair,environnement,autre,background,pet_fonce,carton,flou,metal,papier,mal_croppe.


L'équipe Fotonower 202 b'' Date: Wed, 19 Nov 2025 09:01:31 GMT Content-Length: 0 Connection: close Server: nginx X-Message-Id: f4WXsHNNRuSw7CjTpQKyEw 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 [1395152876, 1395152873, 1395152871, 1395152838, 1395152830, 1395152826, 1395152822, 1395152819, 1395152816, 1395152752] 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, '4076212') ('3318', '28699660', '1395152876', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152873', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152871', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152838', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152830', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152826', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152822', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152819', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152816', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152752', None, None, None, None, None, '4076212') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 10 time used for this insertion : 0.015776634216308594 save_final save missing photos in datou_result : time spend for datou_step_exec : 3.2646732330322266 time spend to save output : 0.01602315902709961 total time spend for step 9 : 3.280696392059326 step10:split_time_score Wed Nov 19 10:01:31 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'}] (('06', 10),) ERROR counted https://github.com/fotonower/Velours/issues/663#issuecomment-421136223 {} 19112025 28699660 Nombre de photos uploadées : 10 / 23040 (0%) 19112025 28699660 Nombre de photos taguées (types de déchets): 0 / 10 (0%) 19112025 28699660 Nombre de photos taguées (volume) : 0 / 10 (0%) elapsed_time : load_data_split_time_score 1.6689300537109375e-06 elapsed_time : order_list_meta_photo_and_scores 5.245208740234375e-06 ?????????? elapsed_time : fill_and_build_computed_from_old_data 0.0005273818969726562 Catched exception ! Connect or reconnect ! Catched exception ! Connect or reconnect ! elapsed_time : insert_dashboard_record_day_entry 0.22881150245666504 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 : 0.09684008487654322 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P28699660_19-11-2025_10_01_27.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 28699660 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number 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`=28699660 AND mptpi.`type`=3594 To do Qualite : 0.13480699159807957 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P28699663_19-11-2025_09_31_42.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 28699663 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number 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`=28699663 AND mptpi.`type`=3594 To do Qualite : 0.05604196807484568 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P28699667_19-11-2025_09_21_10.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 28699667 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number 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`=28699667 AND mptpi.`type`=3594 To do Qualite : 0.11329287765775035 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P28699668_19-11-2025_09_11_56.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 28699668 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number 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`=28699668 AND mptpi.`type`=3594 To do Qualite : 0.04295608281893003 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P28700487_19-11-2025_09_51_41.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 28700487 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number 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`=28700487 AND mptpi.`type`=3594 To do find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 28700488 order by id desc limit 1 NUMBER BATCH : 0 # DISPLAY ALL COLLECTED DATA : {'19112025': {'nb_upload': 10, 'nb_taggue_class': 0, 'nb_taggue_densite': 0}} Inside saveOutput : final : True verbose : 0 saveOutput not yet implemented for datou_step.type : split_time_score we use saveGeneral [1395152876, 1395152873, 1395152871, 1395152838, 1395152830, 1395152826, 1395152822, 1395152819, 1395152816, 1395152752] Looping around the photos to save general results len do output : 1 /28699660Didn'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, '4076212') ('3318', '28699660', '1395152876', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152873', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152871', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152838', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152830', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152826', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152822', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152819', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152816', None, None, None, None, None, '4076212') ('3318', None, None, None, None, None, None, None, '4076212') ('3318', '28699660', '1395152752', None, None, None, None, None, '4076212') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 11 time used for this insertion : 0.01563572883605957 save_final save missing photos in datou_result : time spend for datou_step_exec : 1.923670768737793 time spend to save output : 0.0158388614654541 total time spend for step 10 : 1.939509630203247 caffe_path_current : About to save ! 2 After save, about to update current ! ret : 2 len(input) + len(total_photo_id_missing) : 10 set_done_treatment 37.22user 16.58system 1:07.64elapsed 79%CPU (0avgtext+0avgdata 2686048maxresident)k 800inputs+21824outputs (15major+1318147minor)pagefaults 0swaps