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 : 2142513 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 : ['3735570'] with mtr_portfolio_ids : ['26946471'] and first list_photo_ids : [] new path : /proc/2142513/ 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 , BFBFBFBFBFBFBFBFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 8 ; length of list_pids : 8 ; length of list_args : 8 time to download the photos : 1.0228822231292725 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 Sep 17 14:30:30 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 : 10365 max_wait_temp : 1 max_wait : 0 gpu_flag : 0 2025-09-17 14:30:35.099724: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2025-09-17 14:30:35.144841: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3492910000 Hz 2025-09-17 14:30:35.147536: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7fb734000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-09-17 14:30:35.147562: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-09-17 14:30:35.152955: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-09-17 14:30:35.306549: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0xdfcb970 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-09-17 14:30:35.306598: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-09-17 14:30:35.308206: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-09-17 14:30:35.309836: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-09-17 14:30:35.346430: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-09-17 14:30:35.368236: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-09-17 14:30:35.372586: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-09-17 14:30:35.409913: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-09-17 14:30:35.415960: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-09-17 14:30:35.483036: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-09-17 14:30:35.485068: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-09-17 14:30:35.485530: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-09-17 14:30:35.487230: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-09-17 14:30:35.487257: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-09-17 14:30:35.487269: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-09-17 14:30:35.489294: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 9600 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:41:00.0, compute capability: 7.5) WARNING:tensorflow:From /home/admin/workarea/git/Velours/python/mtr/mask_rcnn/mask_detection.py:69: The name tf.keras.backend.set_session is deprecated. Please use tf.compat.v1.keras.backend.set_session instead. 2025-09-17 14:30:35.883694: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-09-17 14:30:35.883778: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-09-17 14:30:35.883795: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-09-17 14:30:35.883811: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-09-17 14:30:35.883826: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-09-17 14:30:35.883844: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-09-17 14:30:35.883859: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-09-17 14:30:35.883874: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-09-17 14:30:35.885202: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-09-17 14:30:35.886455: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-09-17 14:30:35.886500: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-09-17 14:30:35.886516: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-09-17 14:30:35.886530: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-09-17 14:30:35.886544: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-09-17 14:30:35.886558: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-09-17 14:30:35.886572: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-09-17 14:30:35.886586: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-09-17 14:30:35.887919: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-09-17 14:30:35.887971: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-09-17 14:30:35.887982: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-09-17 14:30:35.887989: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-09-17 14:30:35.889474: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 9600 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:41:00.0, compute capability: 7.5) Using TensorFlow backend. WARNING:tensorflow:From /home/admin/workarea/install/Mask_RCNN/model.py:396: calling crop_and_resize_v1 (from tensorflow.python.ops.image_ops_impl) with box_ind is deprecated and will be removed in a future version. Instructions for updating: box_ind is deprecated, use box_indices instead WARNING:tensorflow:From /home/admin/workarea/install/Mask_RCNN/model.py:703: to_int32 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.cast` instead. WARNING:tensorflow:From /home/admin/workarea/install/Mask_RCNN/model.py:729: to_float (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.cast` instead. Inside mask_sub_process Inside mask_detect About to load cache.load_thcl_param To do loadFromThcl(), then load ParamDescType : thcl2847 thcls : [{'id': 2847, 'mtr_user_id': 31, 'name': 'learn_RUBBIA_REFUS_AMIENS_23', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'photo_desc_type': 5275, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'}] thcl {'id': 2847, 'mtr_user_id': 31, 'name': 'learn_RUBBIA_REFUS_AMIENS_23', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'photo_desc_type': 5275, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'} Update svm_hashtag_type_desc : 5275 FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (5275, 'learn_RUBBIA_REFUS_AMIENS_23', 16384, 25088, 'learn_RUBBIA_REFUS_AMIENS_23', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 1, datetime.datetime(2021, 4, 23, 14, 19, 39), datetime.datetime(2021, 4, 23, 14, 19, 39)) {'thcl': {'id': 2847, 'mtr_user_id': 31, 'name': 'learn_RUBBIA_REFUS_AMIENS_23', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'photo_desc_type': 5275, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'}, 'list_hashtags': ['background', 'papier', 'carton', 'metal', 'pet_clair', 'autre', 'pehd', 'pet_fonce', 'environnement'], 'list_hashtags_csv': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'svm_hashtag_type_desc': 5275, 'photo_desc_type': 5275, 'pb_hashtag_id_or_classifier': 0} list_class_names : ['background', 'papier', 'carton', 'metal', 'pet_clair', 'autre', 'pehd', 'pet_fonce', 'environnement'] Configurations: BACKBONE resnet101 BACKBONE_SHAPES [[160 160] [ 80 80] [ 40 40] [ 20 20] [ 10 10]] BACKBONE_STRIDES [4, 8, 16, 32, 64] BATCH_SIZE 1 BBOX_STD_DEV [0.1 0.1 0.2 0.2] DETECTION_MAX_INSTANCES 100 DETECTION_MIN_CONFIDENCE 0.3 DETECTION_NMS_THRESHOLD 0.3 GPU_COUNT 1 IMAGES_PER_GPU 1 IMAGE_MAX_DIM 640 IMAGE_MIN_DIM 640 IMAGE_PADDING True IMAGE_SHAPE [640 640 3] LEARNING_MOMENTUM 0.9 LEARNING_RATE 0.001 LOSS_WEIGHTS {'rpn_class_loss': 1.0, 'rpn_bbox_loss': 1.0, 'mrcnn_class_loss': 1.0, 'mrcnn_bbox_loss': 1.0, 'mrcnn_mask_loss': 1.0} MASK_POOL_SIZE 14 MASK_SHAPE [28, 28] MAX_GT_INSTANCES 100 MEAN_PIXEL [123.7 116.8 103.9] MINI_MASK_SHAPE (56, 56) NAME learn_RUBBIA_REFUS_AMIENS_23 NUM_CLASSES 9 POOL_SIZE 7 POST_NMS_ROIS_INFERENCE 1000 POST_NMS_ROIS_TRAINING 2000 ROI_POSITIVE_RATIO 0.33 RPN_ANCHOR_RATIOS [0.5, 1, 2] RPN_ANCHOR_SCALES (16, 32, 64, 128, 256) RPN_ANCHOR_STRIDE 1 RPN_BBOX_STD_DEV [0.1 0.1 0.2 0.2] RPN_NMS_THRESHOLD 0.7 RPN_TRAIN_ANCHORS_PER_IMAGE 256 STEPS_PER_EPOCH 1000 TRAIN_ROIS_PER_IMAGE 200 USE_MINI_MASK True USE_RPN_ROIS True VALIDATION_STEPS 50 WEIGHT_DECAY 0.0001 model_param file didn't exist model_name : learn_RUBBIA_REFUS_AMIENS_23 model_type : mask_rcnn list file need : ['mask_model.h5'] file exist in s3 : ['mask_model.h5'] file manque in s3 : [] 2025-09-17 14:30:44.887144: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-09-17 14:30:45.281777: 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 : 8 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 31.00000 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 : 12 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 30.00000 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 : 16 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 30.00000 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 : 14 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 31.00000 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 : 15 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 33.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 11 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 22.00000 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 : 18 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 30.00000 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 : 15 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 25.00000 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 : 13 Detection mask done ! Trying to reset tf kernel 2142999 begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 498 tf kernel not reseted sub process len(results) : 8 len(list_Values) 0 None max_time_sub_proc : 3600 parent process len(results) : 8 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 : 1299 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 : 0.00036215782165527344 nb_pixel_total : 9696 time to create 1 rle with old method : 0.011610269546508789 length of segment : 91 time for calcul the mask position with numpy : 0.00025200843811035156 nb_pixel_total : 10325 time to create 1 rle with old method : 0.012117385864257812 length of segment : 145 time for calcul the mask position with numpy : 0.00014400482177734375 nb_pixel_total : 7001 time to create 1 rle with old method : 0.008392572402954102 length of segment : 99 time for calcul the mask position with numpy : 0.0022737979888916016 nb_pixel_total : 114121 time to create 1 rle with old method : 0.12376761436462402 length of segment : 529 time for calcul the mask position with numpy : 0.0004858970642089844 nb_pixel_total : 28422 time to create 1 rle with old method : 0.03061699867248535 length of segment : 190 time for calcul the mask position with numpy : 0.0004165172576904297 nb_pixel_total : 15672 time to create 1 rle with old method : 0.019282817840576172 length of segment : 159 time for calcul the mask position with numpy : 0.0002334117889404297 nb_pixel_total : 9235 time to create 1 rle with old method : 0.009982824325561523 length of segment : 180 time for calcul the mask position with numpy : 0.00020241737365722656 nb_pixel_total : 9544 time to create 1 rle with old method : 0.01114344596862793 length of segment : 91 time for calcul the mask position with numpy : 0.0004611015319824219 nb_pixel_total : 23159 time to create 1 rle with old method : 0.026712417602539062 length of segment : 191 time for calcul the mask position with numpy : 0.027719974517822266 nb_pixel_total : 1396766 time to create 1 rle with new method : 0.0671226978302002 length of segment : 1093 time for calcul the mask position with numpy : 0.00021409988403320312 nb_pixel_total : 8023 time to create 1 rle with old method : 0.008783578872680664 length of segment : 118 time for calcul the mask position with numpy : 0.0002951622009277344 nb_pixel_total : 14468 time to create 1 rle with old method : 0.015430927276611328 length of segment : 221 time for calcul the mask position with numpy : 0.0008437633514404297 nb_pixel_total : 53649 time to create 1 rle with old method : 0.05767655372619629 length of segment : 266 time for calcul the mask position with numpy : 0.0003979206085205078 nb_pixel_total : 22743 time to create 1 rle with old method : 0.02461075782775879 length of segment : 166 time for calcul the mask position with numpy : 0.00019502639770507812 nb_pixel_total : 9916 time to create 1 rle with old method : 0.010948419570922852 length of segment : 110 time for calcul the mask position with numpy : 0.001844167709350586 nb_pixel_total : 112201 time to create 1 rle with old method : 0.125380277633667 length of segment : 507 time for calcul the mask position with numpy : 0.0010237693786621094 nb_pixel_total : 33307 time to create 1 rle with old method : 0.037374019622802734 length of segment : 232 time for calcul the mask position with numpy : 0.000324249267578125 nb_pixel_total : 8224 time to create 1 rle with old method : 0.009889364242553711 length of segment : 84 time for calcul the mask position with numpy : 0.00034618377685546875 nb_pixel_total : 9767 time to create 1 rle with old method : 0.011645793914794922 length of segment : 77 time for calcul the mask position with numpy : 0.0003838539123535156 nb_pixel_total : 6795 time to create 1 rle with old method : 0.008187055587768555 length of segment : 107 time for calcul the mask position with numpy : 0.0009791851043701172 nb_pixel_total : 22873 time to create 1 rle with old method : 0.027519941329956055 length of segment : 171 time for calcul the mask position with numpy : 0.01901865005493164 nb_pixel_total : 749123 time to create 1 rle with new method : 0.030541419982910156 length of segment : 963 time for calcul the mask position with numpy : 0.0005671977996826172 nb_pixel_total : 29210 time to create 1 rle with old method : 0.03287148475646973 length of segment : 136 time for calcul the mask position with numpy : 0.0003044605255126953 nb_pixel_total : 8734 time to create 1 rle with old method : 0.010205984115600586 length of segment : 177 time for calcul the mask position with numpy : 0.0004558563232421875 nb_pixel_total : 15147 time to create 1 rle with old method : 0.017345428466796875 length of segment : 154 time for calcul the mask position with numpy : 0.0017266273498535156 nb_pixel_total : 90798 time to create 1 rle with old method : 0.10301637649536133 length of segment : 315 time for calcul the mask position with numpy : 0.00034928321838378906 nb_pixel_total : 17218 time to create 1 rle with old method : 0.019810199737548828 length of segment : 157 time for calcul the mask position with numpy : 0.00013208389282226562 nb_pixel_total : 3888 time to create 1 rle with old method : 0.004685163497924805 length of segment : 109 time for calcul the mask position with numpy : 0.00025725364685058594 nb_pixel_total : 8793 time to create 1 rle with old method : 0.010267019271850586 length of segment : 177 time for calcul the mask position with numpy : 0.011052370071411133 nb_pixel_total : 723362 time to create 1 rle with new method : 0.02406597137451172 length of segment : 1013 time for calcul the mask position with numpy : 0.00025200843811035156 nb_pixel_total : 5264 time to create 1 rle with old method : 0.006209850311279297 length of segment : 75 time for calcul the mask position with numpy : 0.00018405914306640625 nb_pixel_total : 3860 time to create 1 rle with old method : 0.004647016525268555 length of segment : 66 time for calcul the mask position with numpy : 0.00032067298889160156 nb_pixel_total : 12490 time to create 1 rle with old method : 0.014934301376342773 length of segment : 99 time for calcul the mask position with numpy : 0.0005097389221191406 nb_pixel_total : 9034 time to create 1 rle with old method : 0.010719060897827148 length of segment : 183 time for calcul the mask position with numpy : 0.0004630088806152344 nb_pixel_total : 8577 time to create 1 rle with old method : 0.010166406631469727 length of segment : 137 time for calcul the mask position with numpy : 0.00035953521728515625 nb_pixel_total : 6240 time to create 1 rle with old method : 0.0075147151947021484 length of segment : 140 time for calcul the mask position with numpy : 0.0002334117889404297 nb_pixel_total : 4586 time to create 1 rle with old method : 0.0056226253509521484 length of segment : 73 time for calcul the mask position with numpy : 0.0011091232299804688 nb_pixel_total : 42180 time to create 1 rle with old method : 0.05159473419189453 length of segment : 322 time for calcul the mask position with numpy : 0.0006885528564453125 nb_pixel_total : 15151 time to create 1 rle with old method : 0.01754617691040039 length of segment : 176 time spent for convertir_results : 2.6602814197540283 Inside saveOutput : final : False verbose : 0 eke 12-6-18 : saveMask need to be cleaned for new output ! Number saved : None batch 1 Loaded 39 chid ids of type : 3594 Number RLEs to save : 9299 save missing photos in datou_result : time spend for datou_step_exec : 28.847146034240723 time spend to save output : 0.6102442741394043 total time spend for step 1 : 29.457390308380127 step2:crop_condition Wed Sep 17 14:31:00 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! 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 : 8 ! batch 1 Loaded 39 chid ids of type : 3594 ++++++++++++++++++++++++++++++++++++++++++++++ begin to crop the class : papier param for this class : {'min_score': 0.7} filtre for class : papier hashtag_id of this class : 492668766 we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! map_result returned by crop_photo_return_map_crop : length : 10 About to insert : list_path_to_insert length 10 new photo from crops ! About to upload 10 photos upload in portfolio : 3736932 init cache_photo without model_param we have 10 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1758112261_2142513 batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 10 photos in the portfolio 3736932 time of upload the photos Elapsed time : 2.7246830463409424 we have finished the crop for the class : papier begin to crop the class : carton param for this class : {'min_score': 0.7} filtre for class : carton hashtag_id of this class : 492774966 we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! 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/1758112267_2142513 batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 3 photos in the portfolio 3736932 time of upload the photos Elapsed time : 1.035954475402832 we have finished the crop for the class : carton begin to crop the class : metal param for this class : {'min_score': 0.7} filtre for class : metal hashtag_id of this class : 492628673 we have both polygon and rles Next one ! map_result returned by crop_photo_return_map_crop : length : 1 About to insert : list_path_to_insert length 1 new photo from crops ! About to upload 1 photos upload in portfolio : 3736932 init cache_photo without model_param we have 1 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1758112268_2142513 batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 1 photos in the portfolio 3736932 time of upload the photos Elapsed time : 0.5832641124725342 we have finished the crop for the class : metal begin to crop the class : pet_clair param for this class : {'min_score': 0.7} filtre for class : pet_clair hashtag_id of this class : 2107755846 we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! 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 : 22 About to insert : list_path_to_insert length 22 new photo from crops ! About to upload 22 photos upload in portfolio : 3736932 init cache_photo without model_param we have 22 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1758112281_2142513 batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 22 photos in the portfolio 3736932 time of upload the photos Elapsed time : 6.3267598152160645 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 ! map_result returned by crop_photo_return_map_crop : length : 1 About to insert : list_path_to_insert length 1 new photo from crops ! About to upload 1 photos upload in portfolio : 3736932 init cache_photo without model_param we have 1 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1758112288_2142513 batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 1 photos in the portfolio 3736932 time of upload the photos Elapsed time : 0.5824093818664551 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 we have both polygon and rles Next one ! we have both polygon and rles Next one ! map_result returned by crop_photo_return_map_crop : length : 2 About to insert : list_path_to_insert length 2 new photo from crops ! About to upload 2 photos upload in portfolio : 3736932 init cache_photo without model_param we have 2 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1758112289_2142513 batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 2 photos in the portfolio 3736932 time of upload the photos Elapsed time : 0.910327672958374 we have finished the crop for the class : pehd 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 [1384191524, 1384191060, 1384191038, 1384191036, 1384191012, 1384190912, 1384190784, 1384189763] Looping around the photos to save general results len do output : 39 /1384224219Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1384224220Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1384224221Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1384224222Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1384224223Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1384224224Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1384224225Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1384224226Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1384224227Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1384224228Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1384224231Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1384224232Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1384224233Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1384224234Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1384224242Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1384224243Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1384224244Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1384224245Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1384224246Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1384224247Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1384224248Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1384224249Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1384224250Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1384224251Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1384224252Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1384224253Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1384224254Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1384224256Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1384224257Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1384224258Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1384224259Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1384224260Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1384224261Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1384224262Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1384224263Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1384224264Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1384224265Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1384224268Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1384224269Didn'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, '3735570') ('3318', '26946471', '1384191524', None, None, None, None, None, '3735570') ('3318', None, None, None, None, None, None, None, '3735570') ('3318', '26946471', '1384191060', None, None, None, None, None, '3735570') ('3318', None, None, None, None, None, None, None, '3735570') ('3318', '26946471', '1384191038', None, None, None, None, None, '3735570') ('3318', None, None, None, None, None, None, None, '3735570') ('3318', '26946471', '1384191036', None, None, None, None, None, '3735570') ('3318', None, None, None, None, None, None, None, '3735570') ('3318', '26946471', '1384191012', None, None, None, None, None, '3735570') ('3318', None, None, None, None, None, None, None, '3735570') ('3318', '26946471', '1384190912', None, None, None, None, None, '3735570') ('3318', None, None, None, None, None, None, None, '3735570') ('3318', '26946471', '1384190784', None, None, None, None, None, '3735570') ('3318', None, None, None, None, None, None, None, '3735570') ('3318', '26946471', '1384189763', None, None, None, None, None, '3735570') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 125 time used for this insertion : 0.02269124984741211 save_final save missing photos in datou_result : time spend for datou_step_exec : 29.765544891357422 time spend to save output : 0.024083852767944336 total time spend for step 2 : 29.789628744125366 step3:rle_unique_nms_with_priority Wed Sep 17 14:31:29 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec 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 VR 22-3-18 : For now we do not clean correctly the datou structure Begin step rle-unique-nms batch 1 Loaded 39 chid ids of type : 3594 ++++++++++++++++++++++++++++++++++++++++++++++nb_obj : 5 nb_hashtags : 3 time to prepare the origin masks : 0.6243879795074463 time for calcul the mask position with numpy : 0.09475564956665039 nb_pixel_total : 1904035 time to create 1 rle with new method : 0.14004993438720703 time for calcul the mask position with numpy : 0.00850820541381836 nb_pixel_total : 28422 time to create 1 rle with old method : 0.0322260856628418 time for calcul the mask position with numpy : 0.00881648063659668 nb_pixel_total : 114121 time to create 1 rle with old method : 0.1310722827911377 time for calcul the mask position with numpy : 0.00881052017211914 nb_pixel_total : 7001 time to create 1 rle with old method : 0.008977651596069336 time for calcul the mask position with numpy : 0.007700204849243164 nb_pixel_total : 10325 time to create 1 rle with old method : 0.013086795806884766 time for calcul the mask position with numpy : 0.007616996765136719 nb_pixel_total : 9696 time to create 1 rle with old method : 0.010855913162231445 create new chi : 0.48500633239746094 time to delete rle : 0.018961429595947266 batch 1 Loaded 11 chid ids of type : 3594 +++++Number RLEs to save : 3188 TO DO : save crop sub photo not yet done ! save time : 0.23119664192199707 nb_obj : 5 nb_hashtags : 2 time to prepare the origin masks : 0.3901181221008301 time for calcul the mask position with numpy : 0.015489578247070312 nb_pixel_total : 660361 time to create 1 rle with new method : 0.10884428024291992 time for calcul the mask position with numpy : 0.029614925384521484 nb_pixel_total : 1355629 time to create 1 rle with new method : 0.06410741806030273 time for calcul the mask position with numpy : 0.008345842361450195 nb_pixel_total : 23159 time to create 1 rle with old method : 0.03504037857055664 time for calcul the mask position with numpy : 0.010491132736206055 nb_pixel_total : 9544 time to create 1 rle with old method : 0.01507568359375 time for calcul the mask position with numpy : 0.009549140930175781 nb_pixel_total : 9235 time to create 1 rle with old method : 0.014225006103515625 time for calcul the mask position with numpy : 0.008878946304321289 nb_pixel_total : 15672 time to create 1 rle with old method : 0.025608301162719727 create new chi : 0.3463428020477295 time to delete rle : 0.0008840560913085938 batch 1 Loaded 13 chid ids of type : 3594 +++++++Number RLEs to save : 4416 TO DO : save crop sub photo not yet done ! save time : 0.3097717761993408 nb_obj : 4 nb_hashtags : 2 time to prepare the origin masks : 0.10206460952758789 time for calcul the mask position with numpy : 0.05700397491455078 nb_pixel_total : 1875091 time to create 1 rle with new method : 0.11636996269226074 time for calcul the mask position with numpy : 0.008391618728637695 nb_pixel_total : 112201 time to create 1 rle with old method : 0.1275177001953125 time for calcul the mask position with numpy : 0.007831335067749023 nb_pixel_total : 9916 time to create 1 rle with old method : 0.011723041534423828 time for calcul the mask position with numpy : 0.008097648620605469 nb_pixel_total : 22743 time to create 1 rle with old method : 0.02808070182800293 time for calcul the mask position with numpy : 0.008279085159301758 nb_pixel_total : 53649 time to create 1 rle with old method : 0.059496164321899414 create new chi : 0.44818639755249023 time to delete rle : 0.0008766651153564453 batch 1 Loaded 9 chid ids of type : 3594 ++++Number RLEs to save : 3178 TO DO : save crop sub photo not yet done ! save time : 0.23808884620666504 nb_obj : 8 nb_hashtags : 3 time to prepare the origin masks : 0.7899234294891357 time for calcul the mask position with numpy : 0.2618894577026367 nb_pixel_total : 1212192 time to create 1 rle with new method : 0.32466864585876465 time for calcul the mask position with numpy : 0.006720304489135742 nb_pixel_total : 8663 time to create 1 rle with old method : 0.009602069854736328 time for calcul the mask position with numpy : 0.006521940231323242 nb_pixel_total : 29210 time to create 1 rle with old method : 0.03233170509338379 time for calcul the mask position with numpy : 0.012861251831054688 nb_pixel_total : 749123 time to create 1 rle with new method : 0.08621358871459961 time for calcul the mask position with numpy : 0.006717205047607422 nb_pixel_total : 16319 time to create 1 rle with old method : 0.018036365509033203 time for calcul the mask position with numpy : 0.006450176239013672 nb_pixel_total : 6795 time to create 1 rle with old method : 0.0075016021728515625 time for calcul the mask position with numpy : 0.006773948669433594 nb_pixel_total : 9767 time to create 1 rle with old method : 0.010854721069335938 time for calcul the mask position with numpy : 0.006345510482788086 nb_pixel_total : 8224 time to create 1 rle with old method : 0.01588726043701172 time for calcul the mask position with numpy : 0.006758689880371094 nb_pixel_total : 33307 time to create 1 rle with old method : 0.0366518497467041 create new chi : 0.8791470527648926 time to delete rle : 0.0005869865417480469 batch 1 Loaded 17 chid ids of type : 3594 ++++++++++++++Number RLEs to save : 4827 TO DO : save crop sub photo not yet done ! save time : 0.3439323902130127 nb_obj : 2 nb_hashtags : 2 time to prepare the origin masks : 0.06928730010986328 time for calcul the mask position with numpy : 0.03341031074523926 nb_pixel_total : 1967655 time to create 1 rle with new method : 0.04326796531677246 time for calcul the mask position with numpy : 0.008310794830322266 nb_pixel_total : 90798 time to create 1 rle with old method : 0.11620068550109863 time for calcul the mask position with numpy : 0.008172273635864258 nb_pixel_total : 15147 time to create 1 rle with old method : 0.017500877380371094 create new chi : 0.22737574577331543 time to delete rle : 0.0005750656127929688 batch 1 Loaded 5 chid ids of type : 3594 ++Number RLEs to save : 2018 TO DO : save crop sub photo not yet done ! save time : 0.17175078392028809 nb_obj : 4 nb_hashtags : 2 time to prepare the origin masks : 0.11881184577941895 time for calcul the mask position with numpy : 0.07479357719421387 nb_pixel_total : 1321208 time to create 1 rle with new method : 0.6770739555358887 time for calcul the mask position with numpy : 0.01567244529724121 nb_pixel_total : 722493 time to create 1 rle with new method : 0.11010098457336426 time for calcul the mask position with numpy : 0.008116483688354492 nb_pixel_total : 8793 time to create 1 rle with old method : 0.011942863464355469 time for calcul the mask position with numpy : 0.008019208908081055 nb_pixel_total : 3888 time to create 1 rle with old method : 0.005729198455810547 time for calcul the mask position with numpy : 0.0068514347076416016 nb_pixel_total : 17218 time to create 1 rle with old method : 0.01928853988647461 create new chi : 0.9591503143310547 time to delete rle : 0.0010221004486083984 batch 1 Loaded 9 chid ids of type : 3594 ++++Number RLEs to save : 3915 TO DO : save crop sub photo not yet done ! save time : 0.3003413677215576 nb_obj : 6 nb_hashtags : 4 time to prepare the origin masks : 0.5465586185455322 time for calcul the mask position with numpy : 0.08650398254394531 nb_pixel_total : 2028135 time to create 1 rle with new method : 0.15790200233459473 time for calcul the mask position with numpy : 0.0075664520263671875 nb_pixel_total : 6240 time to create 1 rle with old method : 0.007102012634277344 time for calcul the mask position with numpy : 0.007268428802490234 nb_pixel_total : 8577 time to create 1 rle with old method : 0.009692668914794922 time for calcul the mask position with numpy : 0.008254528045654297 nb_pixel_total : 9034 time to create 1 rle with old method : 0.010279417037963867 time for calcul the mask position with numpy : 0.013986825942993164 nb_pixel_total : 12490 time to create 1 rle with old method : 0.014230966567993164 time for calcul the mask position with numpy : 0.014073371887207031 nb_pixel_total : 3860 time to create 1 rle with old method : 0.004461526870727539 time for calcul the mask position with numpy : 0.014475584030151367 nb_pixel_total : 5264 time to create 1 rle with old method : 0.00861048698425293 create new chi : 0.38091349601745605 time to delete rle : 0.0007648468017578125 batch 1 Loaded 13 chid ids of type : 3594 +++++++Number RLEs to save : 2480 TO DO : save crop sub photo not yet done ! save time : 0.19528865814208984 nb_obj : 3 nb_hashtags : 2 time to prepare the origin masks : 0.10951352119445801 time for calcul the mask position with numpy : 0.03475832939147949 nb_pixel_total : 2011683 time to create 1 rle with new method : 0.08307409286499023 time for calcul the mask position with numpy : 0.007609128952026367 nb_pixel_total : 15151 time to create 1 rle with old method : 0.01730656623840332 time for calcul the mask position with numpy : 0.008196115493774414 nb_pixel_total : 42180 time to create 1 rle with old method : 0.0495297908782959 time for calcul the mask position with numpy : 0.008200883865356445 nb_pixel_total : 4586 time to create 1 rle with old method : 0.005589962005615234 create new chi : 0.2149491310119629 time to delete rle : 0.0008554458618164062 batch 1 Loaded 7 chid ids of type : 3594 +++Number RLEs to save : 2222 TO DO : save crop sub photo not yet done ! save time : 0.19142436981201172 map_output_result : {1384191524: (0.0, 'Should be the crop_list due to order', 0), 1384191060: (0.0, 'Should be the crop_list due to order', 0), 1384191038: (0.0, 'Should be the crop_list due to order', 0), 1384191036: (0.0, 'Should be the crop_list due to order', 0), 1384191012: (0.0, 'Should be the crop_list due to order', 0), 1384190912: (0.0, 'Should be the crop_list due to order', 0), 1384190784: (0.0, 'Should be the crop_list due to order', 0), 1384189763: (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 [1384191524, 1384191060, 1384191038, 1384191036, 1384191012, 1384190912, 1384190784, 1384189763] Looping around the photos to save general results len do output : 8 /1384191524.Didn't retrieve data . /1384191060.Didn't retrieve data . /1384191038.Didn't retrieve data . /1384191036.Didn't retrieve data . /1384191012.Didn't retrieve data . /1384190912.Didn't retrieve data . /1384190784.Didn't retrieve data . /1384189763.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, '3735570') ('3318', '26946471', '1384191524', None, None, None, None, None, '3735570') ('3318', None, None, None, None, None, None, None, '3735570') ('3318', '26946471', '1384191060', None, None, None, None, None, '3735570') ('3318', None, None, None, None, None, None, None, '3735570') ('3318', '26946471', '1384191038', None, None, None, None, None, '3735570') ('3318', None, None, None, None, None, None, None, '3735570') ('3318', '26946471', '1384191036', None, None, None, None, None, '3735570') ('3318', None, None, None, None, None, None, None, '3735570') ('3318', '26946471', '1384191012', None, None, None, None, None, '3735570') ('3318', None, None, None, None, None, None, None, '3735570') ('3318', '26946471', '1384190912', None, None, None, None, None, '3735570') ('3318', None, None, None, None, None, None, None, '3735570') ('3318', '26946471', '1384190784', None, None, None, None, None, '3735570') ('3318', None, None, None, None, None, None, None, '3735570') ('3318', '26946471', '1384189763', None, None, None, None, None, '3735570') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 24 time used for this insertion : 0.014885663986206055 save_final save missing photos in datou_result : time spend for datou_step_exec : 9.072598695755005 time spend to save output : 0.015486717224121094 total time spend for step 3 : 9.088085412979126 step4:ventilate_hashtags_in_portfolio Wed Sep 17 14:31:39 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 : 26946471 get user id for portfolio 26946471 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`=26946471 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('carton','pet_fonce','mal_croppe','flou','autre','pehd','metal','background','papier','pet_clair','environnement')) 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`=26946471 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('carton','pet_fonce','mal_croppe','flou','autre','pehd','metal','background','papier','pet_clair','environnement')) 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`=26946471 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('carton','pet_fonce','mal_croppe','flou','autre','pehd','metal','background','papier','pet_clair','environnement')) AND mptpi.`min_score`=0.5 To do lien utilise dans velours : https://marlene.fotonower.com/velours/26949330,26949331,26949334,26949335,26949336,26949337,26949340,26949341,26949342,26949344,26949346?tags=carton,pet_fonce,mal_croppe,flou,autre,pehd,metal,background,papier,pet_clair,environnement Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : ventilate_hashtags_in_portfolio we use saveGeneral [1384191524, 1384191060, 1384191038, 1384191036, 1384191012, 1384190912, 1384190784, 1384189763] Looping around the photos to save general results len do output : 1 /26946471. 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, '3735570') ('3318', '26946471', '1384191524', None, None, None, None, None, '3735570') ('3318', None, None, None, None, None, None, None, '3735570') ('3318', '26946471', '1384191060', None, None, None, None, None, '3735570') ('3318', None, None, None, None, None, None, None, '3735570') ('3318', '26946471', '1384191038', None, None, None, None, None, '3735570') ('3318', None, None, None, None, None, None, None, '3735570') ('3318', '26946471', '1384191036', None, None, None, None, None, '3735570') ('3318', None, None, None, None, None, None, None, '3735570') ('3318', '26946471', '1384191012', None, None, None, None, None, '3735570') ('3318', None, None, None, None, None, None, None, '3735570') ('3318', '26946471', '1384190912', None, None, None, None, None, '3735570') ('3318', None, None, None, None, None, None, None, '3735570') ('3318', '26946471', '1384190784', None, None, None, None, None, '3735570') ('3318', None, None, None, None, None, None, None, '3735570') ('3318', '26946471', '1384189763', None, None, None, None, None, '3735570') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 9 time used for this insertion : 0.013890504837036133 save_final save missing photos in datou_result : time spend for datou_step_exec : 1.71156907081604 time spend to save output : 0.014320135116577148 total time spend for step 4 : 1.7258892059326172 step5:final Wed Sep 17 14:31:40 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 : {1384191524: ('0.21752266589506175',), 1384191060: ('0.21752266589506175',), 1384191038: ('0.21752266589506175',), 1384191036: ('0.21752266589506175',), 1384191012: ('0.21752266589506175',), 1384190912: ('0.21752266589506175',), 1384190784: ('0.21752266589506175',), 1384189763: ('0.21752266589506175',)} new output for save of step final : {1384191524: ('0.21752266589506175',), 1384191060: ('0.21752266589506175',), 1384191038: ('0.21752266589506175',), 1384191036: ('0.21752266589506175',), 1384191012: ('0.21752266589506175',), 1384190912: ('0.21752266589506175',), 1384190784: ('0.21752266589506175',), 1384189763: ('0.21752266589506175',)} [1384191524, 1384191060, 1384191038, 1384191036, 1384191012, 1384190912, 1384190784, 1384189763] Looping around the photos to save general results len do output : 8 /1384191524.Didn't retrieve data . /1384191060.Didn't retrieve data . /1384191038.Didn't retrieve data . /1384191036.Didn't retrieve data . /1384191012.Didn't retrieve data . /1384190912.Didn't retrieve data . /1384190784.Didn't retrieve data . /1384189763.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, '3735570') ('3318', '26946471', '1384191524', None, None, None, None, None, '3735570') ('3318', None, None, None, None, None, None, None, '3735570') ('3318', '26946471', '1384191060', None, None, None, None, None, '3735570') ('3318', None, None, None, None, None, None, None, '3735570') ('3318', '26946471', '1384191038', None, None, None, None, None, '3735570') ('3318', None, None, None, None, None, None, None, '3735570') ('3318', '26946471', '1384191036', None, None, None, None, None, '3735570') ('3318', None, None, None, None, None, None, None, '3735570') ('3318', '26946471', '1384191012', None, None, None, None, None, '3735570') ('3318', None, None, None, None, None, None, None, '3735570') ('3318', '26946471', '1384190912', None, None, None, None, None, '3735570') ('3318', None, None, None, None, None, None, None, '3735570') ('3318', '26946471', '1384190784', None, None, None, None, None, '3735570') ('3318', None, None, None, None, None, None, None, '3735570') ('3318', '26946471', '1384189763', None, None, None, None, None, '3735570') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 24 time used for this insertion : 0.01358652114868164 save_final save missing photos in datou_result : time spend for datou_step_exec : 0.12020182609558105 time spend to save output : 0.014057397842407227 total time spend for step 5 : 0.13425922393798828 step6:blur_detection Wed Sep 17 14:31:40 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/1758112229_2142513_1384191524_c9e95c2620eaeb1772035de1c813b6c6.jpg resize: (1080, 1920) 1384191524 3.7137042856178346 treat image : temp/1758112229_2142513_1384191060_31e732e5f130a973d95641d6845f2434.jpg resize: (1080, 1920) 1384191060 1.409877879161049 treat image : temp/1758112229_2142513_1384191038_ccd42c98652c31598148c07c68731f76.jpg resize: (1080, 1920) 1384191038 -0.05447774986383022 treat image : temp/1758112229_2142513_1384191036_94bde198df001ee0110cc0139438fb6f.jpg resize: (1080, 1920) 1384191036 0.7060412648012938 treat image : temp/1758112229_2142513_1384191012_1ba439d605b21f735844766e0f29f922.jpg resize: (1080, 1920) 1384191012 1.6464080431831747 treat image : temp/1758112229_2142513_1384190912_5c3ebea66d3d205b333a642bb2aee02a.jpg resize: (1080, 1920) 1384190912 0.018974068614121167 treat image : temp/1758112229_2142513_1384190784_20a0cee0a0b1e0b21eaac1af3ad0c674.jpg resize: (1080, 1920) 1384190784 1.4094870989507458 treat image : temp/1758112229_2142513_1384189763_f6a77f6a06de2efd2f0aa6e615daa49f.jpg resize: (1080, 1920) 1384189763 3.5511776660629675 treat image : temp/1758112229_2142513_1384191060_31e732e5f130a973d95641d6845f2434_rle_crop_3961604389_0.png resize: (180, 105) 1384224219 -1.9737163887149622 treat image : temp/1758112229_2142513_1384191060_31e732e5f130a973d95641d6845f2434_rle_crop_3961604394_0.png resize: (206, 123) 1384224220 -0.6518317438537498 treat image : temp/1758112229_2142513_1384191038_ccd42c98652c31598148c07c68731f76_rle_crop_3961604395_0.png resize: (266, 247) 1384224221 0.29826354222087736 treat image : temp/1758112229_2142513_1384191038_ccd42c98652c31598148c07c68731f76_rle_crop_3961604397_0.png resize: (110, 151) 1384224222 -1.5733370203815311 treat image : temp/1758112229_2142513_1384191036_94bde198df001ee0110cc0139438fb6f_rle_crop_3961604406_0.png resize: (177, 102) 1384224223 -1.9917271678911572 treat image : temp/1758112229_2142513_1384190912_5c3ebea66d3d205b333a642bb2aee02a_rle_crop_3961604411_0.png resize: (177, 98) 1384224224 -2.056607779259785 treat image : temp/1758112229_2142513_1384190784_20a0cee0a0b1e0b21eaac1af3ad0c674_rle_crop_3961604416_0.png resize: (183, 101) 1384224225 -1.812779135501075 treat image : temp/1758112229_2142513_1384190784_20a0cee0a0b1e0b21eaac1af3ad0c674_rle_crop_3961604414_0.png resize: (62, 93) 1384224226 0.7621909278794664 treat image : temp/1758112229_2142513_1384190784_20a0cee0a0b1e0b21eaac1af3ad0c674_rle_crop_3961604415_0.png resize: (88, 193) 1384224227 -1.502094311444554 treat image : temp/1758112229_2142513_1384189763_f6a77f6a06de2efd2f0aa6e615daa49f_rle_crop_3961604419_0.png resize: (73, 112) 1384224228 -2.066360443686981 treat image : temp/1758112229_2142513_1384191524_c9e95c2620eaeb1772035de1c813b6c6_rle_crop_3961604384_0.png resize: (141, 105) 1384224231 -1.5572232628913518 treat image : temp/1758112229_2142513_1384191036_94bde198df001ee0110cc0139438fb6f_rle_crop_3961604404_0.png resize: (960, 1055) 1384224232 0.5919242533155264 treat image : temp/1758112229_2142513_1384191036_94bde198df001ee0110cc0139438fb6f_rle_crop_3961604402_0.png resize: (100, 96) 1384224233 -1.3518085566369975 treat image : temp/1758112229_2142513_1384190784_20a0cee0a0b1e0b21eaac1af3ad0c674_rle_crop_3961604413_0.png resize: (75, 92) 1384224234 -1.3478225704103162 treat image : temp/1758112229_2142513_1384191524_c9e95c2620eaeb1772035de1c813b6c6_rle_crop_3961604387_0.png resize: (190, 181) 1384224242 0.4768387397716537 treat image : temp/1758112229_2142513_1384191524_c9e95c2620eaeb1772035de1c813b6c6_rle_crop_3961604383_0.png resize: (89, 158) 1384224243 -0.07963466435816818 treat image : temp/1758112229_2142513_1384191524_c9e95c2620eaeb1772035de1c813b6c6_rle_crop_3961604386_0.png resize: (513, 369) 1384224244 0.13856707246200253 treat image : temp/1758112229_2142513_1384191060_31e732e5f130a973d95641d6845f2434_rle_crop_3961604392_0.png resize: (1007, 1437) 1384224245 0.04525383045678945 treat image : temp/1758112229_2142513_1384191060_31e732e5f130a973d95641d6845f2434_rle_crop_3961604393_0.png resize: (116, 106) 1384224246 -1.0573847026740495 treat image : temp/1758112229_2142513_1384191060_31e732e5f130a973d95641d6845f2434_rle_crop_3961604388_0.png resize: (158, 128) 1384224247 -0.03310326577945454 treat image : temp/1758112229_2142513_1384191060_31e732e5f130a973d95641d6845f2434_rle_crop_3961604391_0.png resize: (163, 217) 1384224248 -1.3633456700078082 treat image : temp/1758112229_2142513_1384191060_31e732e5f130a973d95641d6845f2434_rle_crop_3961604390_0.png resize: (89, 153) 1384224249 0.5005896315826291 treat image : temp/1758112229_2142513_1384191038_ccd42c98652c31598148c07c68731f76_rle_crop_3961604396_0.png resize: (166, 236) 1384224250 -2.2647012110998896 treat image : temp/1758112229_2142513_1384191038_ccd42c98652c31598148c07c68731f76_rle_crop_3961604398_0.png resize: (504, 364) 1384224251 0.11787238806046127 treat image : temp/1758112229_2142513_1384191036_94bde198df001ee0110cc0139438fb6f_rle_crop_3961604405_0.png resize: (133, 284) 1384224252 -0.052447422757896746 treat image : temp/1758112229_2142513_1384191036_94bde198df001ee0110cc0139438fb6f_rle_crop_3961604399_0.png resize: (122, 395) 1384224253 -1.7012846373788062 treat image : temp/1758112229_2142513_1384191036_94bde198df001ee0110cc0139438fb6f_rle_crop_3961604400_0.png resize: (84, 131) 1384224254 -1.2484939577924743 treat image : temp/1758112229_2142513_1384191036_94bde198df001ee0110cc0139438fb6f_rle_crop_3961604403_0.png resize: (164, 181) 1384224256 -2.3071672874855063 treat image : temp/1758112229_2142513_1384191036_94bde198df001ee0110cc0139438fb6f_rle_crop_3961604401_0.png resize: (76, 152) 1384224257 0.41780013726997534 treat image : temp/1758112229_2142513_1384191012_1ba439d605b21f735844766e0f29f922_rle_crop_3961604407_0.png resize: (154, 129) 1384224258 -0.4106501458840646 treat image : temp/1758112229_2142513_1384190912_5c3ebea66d3d205b333a642bb2aee02a_rle_crop_3961604412_0.png resize: (994, 1008) 1384224259 -0.032120341755542674 treat image : temp/1758112229_2142513_1384190912_5c3ebea66d3d205b333a642bb2aee02a_rle_crop_3961604409_0.png resize: (157, 151) 1384224260 1.5013770708942984 treat image : temp/1758112229_2142513_1384190912_5c3ebea66d3d205b333a642bb2aee02a_rle_crop_3961604410_0.png resize: (109, 52) 1384224261 -1.2386367987204734 treat image : temp/1758112229_2142513_1384190784_20a0cee0a0b1e0b21eaac1af3ad0c674_rle_crop_3961604418_0.png resize: (137, 87) 1384224262 -0.5840759731455432 treat image : temp/1758112229_2142513_1384189763_f6a77f6a06de2efd2f0aa6e615daa49f_rle_crop_3961604421_0.png resize: (176, 113) 1384224263 -0.7300769583675674 treat image : temp/1758112229_2142513_1384189763_f6a77f6a06de2efd2f0aa6e615daa49f_rle_crop_3961604420_0.png resize: (322, 184) 1384224264 -0.9927014899670467 treat image : temp/1758112229_2142513_1384191012_1ba439d605b21f735844766e0f29f922_rle_crop_3961604408_0.png resize: (315, 364) 1384224265 0.057969477490730885 treat image : temp/1758112229_2142513_1384191524_c9e95c2620eaeb1772035de1c813b6c6_rle_crop_3961604385_0.png resize: (99, 87) 1384224268 1.1249816574225964 treat image : temp/1758112229_2142513_1384190784_20a0cee0a0b1e0b21eaac1af3ad0c674_rle_crop_3961604417_0.png resize: (137, 100) 1384224269 -1.2887858798456246 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 : 47 time used for this insertion : 0.014614582061767578 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 47 time used for this insertion : 0.013726472854614258 save missing photos in datou_result : time spend for datou_step_exec : 8.830996751785278 time spend to save output : 0.03726768493652344 total time spend for step 6 : 8.868264436721802 step7:brightness Wed Sep 17 14:31:49 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/1758112229_2142513_1384191524_c9e95c2620eaeb1772035de1c813b6c6.jpg treat image : temp/1758112229_2142513_1384191060_31e732e5f130a973d95641d6845f2434.jpg treat image : temp/1758112229_2142513_1384191038_ccd42c98652c31598148c07c68731f76.jpg treat image : temp/1758112229_2142513_1384191036_94bde198df001ee0110cc0139438fb6f.jpg treat image : temp/1758112229_2142513_1384191012_1ba439d605b21f735844766e0f29f922.jpg treat image : temp/1758112229_2142513_1384190912_5c3ebea66d3d205b333a642bb2aee02a.jpg treat image : temp/1758112229_2142513_1384190784_20a0cee0a0b1e0b21eaac1af3ad0c674.jpg treat image : temp/1758112229_2142513_1384189763_f6a77f6a06de2efd2f0aa6e615daa49f.jpg treat image : temp/1758112229_2142513_1384191060_31e732e5f130a973d95641d6845f2434_rle_crop_3961604389_0.png treat image : temp/1758112229_2142513_1384191060_31e732e5f130a973d95641d6845f2434_rle_crop_3961604394_0.png treat image : temp/1758112229_2142513_1384191038_ccd42c98652c31598148c07c68731f76_rle_crop_3961604395_0.png treat image : temp/1758112229_2142513_1384191038_ccd42c98652c31598148c07c68731f76_rle_crop_3961604397_0.png treat image : temp/1758112229_2142513_1384191036_94bde198df001ee0110cc0139438fb6f_rle_crop_3961604406_0.png treat image : temp/1758112229_2142513_1384190912_5c3ebea66d3d205b333a642bb2aee02a_rle_crop_3961604411_0.png treat image : temp/1758112229_2142513_1384190784_20a0cee0a0b1e0b21eaac1af3ad0c674_rle_crop_3961604416_0.png treat image : temp/1758112229_2142513_1384190784_20a0cee0a0b1e0b21eaac1af3ad0c674_rle_crop_3961604414_0.png treat image : temp/1758112229_2142513_1384190784_20a0cee0a0b1e0b21eaac1af3ad0c674_rle_crop_3961604415_0.png treat image : temp/1758112229_2142513_1384189763_f6a77f6a06de2efd2f0aa6e615daa49f_rle_crop_3961604419_0.png treat image : temp/1758112229_2142513_1384191524_c9e95c2620eaeb1772035de1c813b6c6_rle_crop_3961604384_0.png treat image : 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temp/1758112229_2142513_1384190784_20a0cee0a0b1e0b21eaac1af3ad0c674_rle_crop_3961604417_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 : 47 time used for this insertion : 0.01665472984313965 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 47 time used for this insertion : 0.016017913818359375 save missing photos in datou_result : time spend for datou_step_exec : 2.2209010124206543 time spend to save output : 0.037699222564697266 total time spend for step 7 : 2.2586002349853516 step8:velours_tree Wed Sep 17 14:31:51 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 : 0.1303091049194336 time spend to save output : 3.7670135498046875e-05 total time spend for step 8 : 0.13034677505493164 step9:send_mail_cod Wed Sep 17 14:31:52 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed 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_P26946471_17-09-2025_14_31_52.pdf 26949330 change filename to text .change filename to text .change filename to text .imagette269493301758112312 26949331 imagette269493311758112312 26949334 imagette269493341758112312 26949335 imagette269493351758112312 26949336 change filename to text .imagette269493361758112312 26949337 change filename to text .change filename to text .imagette269493371758112312 26949340 change filename to text .imagette269493401758112312 26949341 imagette269493411758112312 26949342 change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .imagette269493421758112312 26949344 change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .imagette269493441758112313 SELECT h.hashtag,pcr.value FROM MTRUser.portfolio_carac_ratio pcr, MTRBack.hashtags h where pcr.portfolio_id=26946471 and hashtag_type = 3594 and pcr.hashtag_id = h.hashtag_id; velour_link : https://marlene.fotonower.com/velours/26949330,26949331,26949334,26949335,26949336,26949337,26949340,26949341,26949342,26949344,26949346?tags=carton,pet_fonce,mal_croppe,flou,autre,pehd,metal,background,papier,pet_clair,environnement args[1384191524] : ((1384191524, 3.7137042856178346, 492688767), (1384191524, 0.3477219528013906, 2107752395), '0.21752266589506175') We are sending mail with results at report@fotonower.com args[1384191060] : ((1384191060, 1.409877879161049, 492688767), (1384191060, 0.4482038397762176, 2107752395), '0.21752266589506175') We are sending mail with results at report@fotonower.com args[1384191038] : ((1384191038, -0.05447774986383022, 492688767), (1384191038, 0.4654509926299391, 2107752395), '0.21752266589506175') We are sending mail with results at report@fotonower.com args[1384191036] : ((1384191036, 0.7060412648012938, 492688767), (1384191036, 0.46795739100798217, 2107752395), '0.21752266589506175') We are sending mail with results at report@fotonower.com args[1384191012] : ((1384191012, 1.6464080431831747, 492688767), (1384191012, 0.8127892370564442, 2107752395), '0.21752266589506175') We are sending mail with results at report@fotonower.com args[1384190912] : ((1384190912, 0.018974068614121167, 492688767), (1384190912, 0.34796022784210917, 2107752395), '0.21752266589506175') We are sending mail with results at report@fotonower.com args[1384190784] : ((1384190784, 1.4094870989507458, 492688767), (1384190784, 0.47581888756761165, 2107752395), '0.21752266589506175') We are sending mail with results at report@fotonower.com args[1384189763] : ((1384189763, 3.5511776660629675, 492688767), (1384189763, 0.42449976207954665, 2107752395), '0.21752266589506175') We are sending mail with results at report@fotonower.com refus_total : 0.21752266589506175 2022-04-13 10:29:59 0 SELECT ph.photo_id,ph.url,ph.username,ph.uploaded_at,ph.text FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=26946471 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_P26946471_17-09-2025_14_31_52.pdf results_Auto_P26946471_17-09-2025_14_31_52.pdf uploaded to url https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P26946471_17-09-2025_14_31_52.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','26946471','results_Auto_P26946471_17-09-2025_14_31_52.pdf','https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P26946471_17-09-2025_14_31_52.pdf','pdf','','0.44','0.21752266589506175') message_in_mail: Bonjour,
Veuillez trouver ci dessous les résultats du service carac on demand pour le portfolio: https://www.fotonower.com/view/26946471

https://www.fotonower.com/image?json=false&list_photos_id=1384191524
La photo est trop floue, merci de reprendre une photo.(avec le score = 3.7137042856178346)
https://www.fotonower.com/image?json=false&list_photos_id=1384191060
La photo est trop floue, merci de reprendre une photo.(avec le score = 1.409877879161049)
https://www.fotonower.com/image?json=false&list_photos_id=1384191038
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1384191036
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1384191012
La photo est trop floue, merci de reprendre une photo.(avec le score = 1.6464080431831747)
https://www.fotonower.com/image?json=false&list_photos_id=1384190912
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1384190784
La photo est trop floue, merci de reprendre une photo.(avec le score = 1.4094870989507458)
https://www.fotonower.com/image?json=false&list_photos_id=1384189763
La photo est trop floue, merci de reprendre une photo.(avec le score = 3.5511776660629675)

Dans ces conditions,le taux de refus est: 21.75%
Veuillez trouver les photos des contaminants.

exemples de contaminants: carton: https://www.fotonower.com/view/26949330?limit=200
exemples de contaminants: autre: https://www.fotonower.com/view/26949336?limit=200
exemples de contaminants: pehd: https://www.fotonower.com/view/26949337?limit=200
exemples de contaminants: metal: https://www.fotonower.com/view/26949340?limit=200
exemples de contaminants: papier: https://www.fotonower.com/view/26949342?limit=200
exemples de contaminants: pet_clair: https://www.fotonower.com/view/26949344?limit=200
Veuillez trouver le rapport en pdf:https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P26946471_17-09-2025_14_31_52.pdf.

Lien vers velours :https://marlene.fotonower.com/velours/26949330,26949331,26949334,26949335,26949336,26949337,26949340,26949341,26949342,26949344,26949346?tags=carton,pet_fonce,mal_croppe,flou,autre,pehd,metal,background,papier,pet_clair,environnement.


L'équipe Fotonower 202 b'' Server: nginx Date: Wed, 17 Sep 2025 12:31:56 GMT Content-Length: 0 Connection: close X-Message-Id: QbnPZbvuR-2G7EdJHalTzw 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 [1384191524, 1384191060, 1384191038, 1384191036, 1384191012, 1384190912, 1384190784, 1384189763] 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, '3735570') ('3318', '26946471', '1384191524', None, None, None, None, None, '3735570') ('3318', None, None, None, None, None, None, None, '3735570') ('3318', '26946471', '1384191060', None, None, None, None, None, '3735570') ('3318', None, None, None, None, None, None, None, '3735570') ('3318', '26946471', '1384191038', None, None, None, None, None, '3735570') ('3318', None, None, None, None, None, None, None, '3735570') ('3318', '26946471', '1384191036', None, None, None, None, None, '3735570') ('3318', None, None, None, None, None, None, None, '3735570') ('3318', '26946471', '1384191012', None, None, None, None, None, '3735570') ('3318', None, None, None, None, None, None, None, '3735570') ('3318', '26946471', '1384190912', None, None, None, None, None, '3735570') ('3318', None, None, None, None, None, None, None, '3735570') ('3318', '26946471', '1384190784', None, None, None, None, None, '3735570') ('3318', None, None, None, None, None, None, None, '3735570') ('3318', '26946471', '1384189763', None, None, None, None, None, '3735570') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 8 time used for this insertion : 0.015954017639160156 save_final save missing photos in datou_result : time spend for datou_step_exec : 4.369905233383179 time spend to save output : 0.01616191864013672 total time spend for step 9 : 4.386067152023315 step10:split_time_score Wed Sep 17 14:31:56 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'}] (('13', 8),) ERROR counted https://github.com/fotonower/Velours/issues/663#issuecomment-421136223 {} 17092025 26946471 Nombre de photos uploadées : 8 / 23040 (0%) 17092025 26946471 Nombre de photos taguées (types de déchets): 0 / 8 (0%) 17092025 26946471 Nombre de photos taguées (volume) : 0 / 8 (0%) elapsed_time : load_data_split_time_score 2.384185791015625e-06 elapsed_time : order_list_meta_photo_and_scores 7.3909759521484375e-06 ???????? elapsed_time : fill_and_build_computed_from_old_data 0.00047969818115234375 Catched exception ! Connect or reconnect ! Catched exception ! Connect or reconnect ! elapsed_time : insert_dashboard_record_day_entry 0.2173168659210205 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 : 0.10858108874133637 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P26931981_17-09-2025_09_30_48.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 26931981 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`=26931981 AND mptpi.`type`=3594 To do Qualite : 0.07002329282407407 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P26931985_17-09-2025_08_51_23.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 26931985 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`=26931985 AND mptpi.`type`=3594 To do Qualite : 0.060776120580808085 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P26931986_17-09-2025_08_41_31.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 26931986 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`=26931986 AND mptpi.`type`=3594 To do Qualite : 0.0977959718714927 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P26945362_17-09-2025_13_11_57.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 26945362 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`=26945362 AND mptpi.`type`=3594 To do Qualite : 0.06575307264109347 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P26941005_17-09-2025_13_02_01.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 26941005 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`=26941005 AND mptpi.`type`=3594 To do Qualite : 0.12312721032664604 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P26941009_17-09-2025_11_41_55.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 26941009 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`=26941009 AND mptpi.`type`=3594 To do Qualite : 0.030984171382030176 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P26944431_17-09-2025_12_41_58.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 26944431 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`=26944431 AND mptpi.`type`=3594 To do Qualite : 0.07949328596536352 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P26946470_17-09-2025_14_02_36.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 26946470 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`=26946470 AND mptpi.`type`=3594 To do Qualite : 0.21752266589506175 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P26946471_17-09-2025_14_31_52.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 26946471 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`=26946471 AND mptpi.`type`=3594 To do NUMBER BATCH : 0 # DISPLAY ALL COLLECTED DATA : {'17092025': {'nb_upload': 8, '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 [1384191524, 1384191060, 1384191038, 1384191036, 1384191012, 1384190912, 1384190784, 1384189763] Looping around the photos to save general results len do output : 1 /26946471Didn'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, '3735570') ('3318', '26946471', '1384191524', None, None, None, None, None, '3735570') ('3318', None, None, None, None, None, None, None, '3735570') ('3318', '26946471', '1384191060', None, None, None, None, None, '3735570') ('3318', None, None, None, None, None, None, None, '3735570') ('3318', '26946471', '1384191038', None, None, None, None, None, '3735570') ('3318', None, None, None, None, None, None, None, '3735570') ('3318', '26946471', '1384191036', None, None, None, None, None, '3735570') ('3318', None, None, None, None, None, None, None, '3735570') ('3318', '26946471', '1384191012', None, None, None, None, None, '3735570') ('3318', None, None, None, None, None, None, None, '3735570') ('3318', '26946471', '1384190912', None, None, None, None, None, '3735570') ('3318', None, None, None, None, None, None, None, '3735570') ('3318', '26946471', '1384190784', None, None, None, None, None, '3735570') ('3318', None, None, None, None, None, None, None, '3735570') ('3318', '26946471', '1384189763', None, None, None, None, None, '3735570') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 9 time used for this insertion : 0.016122102737426758 save_final save missing photos in datou_result : time spend for datou_step_exec : 0.9588491916656494 time spend to save output : 0.01638197898864746 total time spend for step 10 : 0.9752311706542969 caffe_path_current : About to save ! 2 After save, about to update current ! ret : 2 len(input) + len(total_photo_id_missing) : 8 set_done_treatment 48.54user 21.47system 1:32.51elapsed 75%CPU (0avgtext+0avgdata 2923524maxresident)k 2252240inputs+30056outputs (8243major+1717581minor)pagefaults 0swaps