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 : 1198527 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 : ['3759647'] with mtr_portfolio_ids : ['27101376'] and first list_photo_ids : [] new path : /proc/1198527/ 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 , BFBFBFBFBFBFBFBFBFBFBFBFBFBFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 14 ; length of list_pids : 14 ; length of list_args : 14 time to download the photos : 2.1182045936584473 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : 0 number of steps : 10 step1:mask_detect Mon Sep 22 19:30:31 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec 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 : 10586 max_wait_temp : 1 max_wait : 0 gpu_flag : 0 2025-09-22 19:30:34.435165: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2025-09-22 19:30:34.460593: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3492910000 Hz 2025-09-22 19:30:34.462296: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f4f14000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-09-22 19:30:34.462352: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-09-22 19:30:34.465042: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-09-22 19:30:34.619971: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x437bdfd0 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-09-22 19:30:34.620028: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-09-22 19:30:34.621002: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-09-22 19:30:34.621684: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-09-22 19:30:34.624780: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-09-22 19:30:34.627921: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-09-22 19:30:34.628825: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-09-22 19:30:34.637915: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-09-22 19:30:34.639173: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-09-22 19:30:34.649649: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-09-22 19:30:34.651111: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-09-22 19:30:34.651196: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-09-22 19:30:34.651952: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-09-22 19:30:34.651968: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-09-22 19:30:34.651977: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-09-22 19:30:34.653486: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 9805 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:41:00.0, compute capability: 7.5) WARNING:tensorflow:From /home/admin/workarea/git/Velours/python/mtr/mask_rcnn/mask_detection.py:69: The name tf.keras.backend.set_session is deprecated. Please use tf.compat.v1.keras.backend.set_session instead. 2025-09-22 19:30:34.953978: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-09-22 19:30:34.954096: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-09-22 19:30:34.954114: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-09-22 19:30:34.954131: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-09-22 19:30:34.954146: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-09-22 19:30:34.954161: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-09-22 19:30:34.954176: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-09-22 19:30:34.954191: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-09-22 19:30:34.955408: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-09-22 19:30:34.956645: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-09-22 19:30:34.956681: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-09-22 19:30:34.956697: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-09-22 19:30:34.956712: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-09-22 19:30:34.956726: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-09-22 19:30:34.956740: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-09-22 19:30:34.956754: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-09-22 19:30:34.956768: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-09-22 19:30:34.957997: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-09-22 19:30:34.958037: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-09-22 19:30:34.958046: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-09-22 19:30:34.958053: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-09-22 19:30:34.959264: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 9805 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:41:00.0, compute capability: 7.5) Using TensorFlow backend. WARNING:tensorflow:From /home/admin/workarea/install/Mask_RCNN/model.py:396: calling crop_and_resize_v1 (from tensorflow.python.ops.image_ops_impl) with box_ind is deprecated and will be removed in a future version. Instructions for updating: box_ind is deprecated, use box_indices instead WARNING:tensorflow:From /home/admin/workarea/install/Mask_RCNN/model.py:703: to_int32 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.cast` instead. WARNING:tensorflow:From /home/admin/workarea/install/Mask_RCNN/model.py:729: to_float (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.cast` instead. Inside mask_sub_process Inside mask_detect About to load cache.load_thcl_param To do loadFromThcl(), then load ParamDescType : thcl2847 thcls : [{'id': 2847, 'mtr_user_id': 31, 'name': 'learn_RUBBIA_REFUS_AMIENS_23', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'photo_desc_type': 5275, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'}] thcl {'id': 2847, 'mtr_user_id': 31, 'name': 'learn_RUBBIA_REFUS_AMIENS_23', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'photo_desc_type': 5275, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'} Update svm_hashtag_type_desc : 5275 FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (5275, 'learn_RUBBIA_REFUS_AMIENS_23', 16384, 25088, 'learn_RUBBIA_REFUS_AMIENS_23', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 1, datetime.datetime(2021, 4, 23, 14, 19, 39), datetime.datetime(2021, 4, 23, 14, 19, 39)) {'thcl': {'id': 2847, 'mtr_user_id': 31, 'name': 'learn_RUBBIA_REFUS_AMIENS_23', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'photo_desc_type': 5275, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'}, 'list_hashtags': ['background', 'papier', 'carton', 'metal', 'pet_clair', 'autre', 'pehd', 'pet_fonce', 'environnement'], 'list_hashtags_csv': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'svm_hashtag_type_desc': 5275, 'photo_desc_type': 5275, 'pb_hashtag_id_or_classifier': 0} list_class_names : ['background', 'papier', 'carton', 'metal', 'pet_clair', 'autre', 'pehd', 'pet_fonce', 'environnement'] Configurations: BACKBONE resnet101 BACKBONE_SHAPES [[160 160] [ 80 80] [ 40 40] [ 20 20] [ 10 10]] BACKBONE_STRIDES [4, 8, 16, 32, 64] BATCH_SIZE 1 BBOX_STD_DEV [0.1 0.1 0.2 0.2] DETECTION_MAX_INSTANCES 100 DETECTION_MIN_CONFIDENCE 0.3 DETECTION_NMS_THRESHOLD 0.3 GPU_COUNT 1 IMAGES_PER_GPU 1 IMAGE_MAX_DIM 640 IMAGE_MIN_DIM 640 IMAGE_PADDING True IMAGE_SHAPE [640 640 3] LEARNING_MOMENTUM 0.9 LEARNING_RATE 0.001 LOSS_WEIGHTS {'rpn_class_loss': 1.0, 'rpn_bbox_loss': 1.0, 'mrcnn_class_loss': 1.0, 'mrcnn_bbox_loss': 1.0, 'mrcnn_mask_loss': 1.0} MASK_POOL_SIZE 14 MASK_SHAPE [28, 28] MAX_GT_INSTANCES 100 MEAN_PIXEL [123.7 116.8 103.9] MINI_MASK_SHAPE (56, 56) NAME learn_RUBBIA_REFUS_AMIENS_23 NUM_CLASSES 9 POOL_SIZE 7 POST_NMS_ROIS_INFERENCE 1000 POST_NMS_ROIS_TRAINING 2000 ROI_POSITIVE_RATIO 0.33 RPN_ANCHOR_RATIOS [0.5, 1, 2] RPN_ANCHOR_SCALES (16, 32, 64, 128, 256) RPN_ANCHOR_STRIDE 1 RPN_BBOX_STD_DEV [0.1 0.1 0.2 0.2] RPN_NMS_THRESHOLD 0.7 RPN_TRAIN_ANCHORS_PER_IMAGE 256 STEPS_PER_EPOCH 1000 TRAIN_ROIS_PER_IMAGE 200 USE_MINI_MASK True USE_RPN_ROIS True VALIDATION_STEPS 50 WEIGHT_DECAY 0.0001 model_param file didn't exist model_name : learn_RUBBIA_REFUS_AMIENS_23 model_type : mask_rcnn list file need : ['mask_model.h5'] file exist in s3 : ['mask_model.h5'] file manque in s3 : [] 2025-09-22 19:30:42.429616: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-09-22 19:30:42.626532: 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 : 14 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 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 : 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 : 6 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 35.00000 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: 16.00000 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: 7.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 1 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 15 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 37.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 3 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 42.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 2 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 : 4 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 29.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 0 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 23.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 13 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 26.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 7 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 49.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 1 Detection mask done ! Trying to reset tf kernel 1199167 begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 4329 tf kernel not reseted sub process len(results) : 14 len(list_Values) 0 None max_time_sub_proc : 3600 parent process len(results) : 14 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 : 5702 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 : 0.0006976127624511719 nb_pixel_total : 14076 time to create 1 rle with old method : 0.016707658767700195 length of segment : 197 time for calcul the mask position with numpy : 0.00019311904907226562 nb_pixel_total : 3139 time to create 1 rle with old method : 0.0038890838623046875 length of segment : 65 time for calcul the mask position with numpy : 0.0002541542053222656 nb_pixel_total : 3842 time to create 1 rle with old method : 0.004489898681640625 length of segment : 109 time for calcul the mask position with numpy : 0.00014925003051757812 nb_pixel_total : 3325 time to create 1 rle with old method : 0.0039038658142089844 length of segment : 59 time for calcul the mask position with numpy : 0.00038051605224609375 nb_pixel_total : 10282 time to create 1 rle with old method : 0.011649131774902344 length of segment : 139 time for calcul the mask position with numpy : 0.00015497207641601562 nb_pixel_total : 3657 time to create 1 rle with old method : 0.0044329166412353516 length of segment : 57 time for calcul the mask position with numpy : 0.0005042552947998047 nb_pixel_total : 12668 time to create 1 rle with old method : 0.014328718185424805 length of segment : 183 time for calcul the mask position with numpy : 9.059906005859375e-05 nb_pixel_total : 1100 time to create 1 rle with old method : 0.0014758110046386719 length of segment : 33 time for calcul the mask position with numpy : 0.00035190582275390625 nb_pixel_total : 5731 time to create 1 rle with old method : 0.006724834442138672 length of segment : 167 time for calcul the mask position with numpy : 0.0004990100860595703 nb_pixel_total : 15947 time to create 1 rle with old method : 0.018288373947143555 length of segment : 160 time for calcul the mask position with numpy : 0.0002617835998535156 nb_pixel_total : 6124 time to create 1 rle with old method : 0.007407665252685547 length of segment : 81 time for calcul the mask position with numpy : 0.0001392364501953125 nb_pixel_total : 3095 time to create 1 rle with old method : 0.0038285255432128906 length of segment : 54 time for calcul the mask position with numpy : 0.00047397613525390625 nb_pixel_total : 12794 time to create 1 rle with old method : 0.015357017517089844 length of segment : 188 time for calcul the mask position with numpy : 0.00027298927307128906 nb_pixel_total : 6124 time to create 1 rle with old method : 0.007642984390258789 length of segment : 125 time for calcul the mask position with numpy : 0.000247955322265625 nb_pixel_total : 4205 time to create 1 rle with old method : 0.005089998245239258 length of segment : 102 time for calcul the mask position with numpy : 0.0001678466796875 nb_pixel_total : 3747 time to create 1 rle with old method : 0.004546642303466797 length of segment : 79 time for calcul the mask position with numpy : 0.00026488304138183594 nb_pixel_total : 5767 time to create 1 rle with old method : 0.0069732666015625 length of segment : 99 time for calcul the mask position with numpy : 0.0001842975616455078 nb_pixel_total : 7108 time to create 1 rle with old method : 0.008919477462768555 length of segment : 63 time for calcul the mask position with numpy : 0.00011372566223144531 nb_pixel_total : 1498 time to create 1 rle with old method : 0.0017936229705810547 length of segment : 41 time for calcul the mask position with numpy : 0.00013446807861328125 nb_pixel_total : 2626 time to create 1 rle with old method : 0.0033485889434814453 length of segment : 50 time for calcul the mask position with numpy : 0.0004744529724121094 nb_pixel_total : 11716 time to create 1 rle with old method : 0.013355731964111328 length of segment : 184 time for calcul the mask position with numpy : 0.00019168853759765625 nb_pixel_total : 3816 time to create 1 rle with old method : 0.004682302474975586 length of segment : 67 time for calcul the mask position with numpy : 0.0003428459167480469 nb_pixel_total : 13596 time to create 1 rle with old method : 0.018210887908935547 length of segment : 192 time for calcul the mask position with numpy : 0.0001652240753173828 nb_pixel_total : 8355 time to create 1 rle with old method : 0.009947538375854492 length of segment : 123 time for calcul the mask position with numpy : 0.000179290771484375 nb_pixel_total : 7799 time to create 1 rle with old method : 0.0093536376953125 length of segment : 138 time for calcul the mask position with numpy : 0.0002200603485107422 nb_pixel_total : 12244 time to create 1 rle with old method : 0.014666318893432617 length of segment : 188 time for calcul the mask position with numpy : 0.00014925003051757812 nb_pixel_total : 2594 time to create 1 rle with old method : 0.0032956600189208984 length of segment : 57 time for calcul the mask position with numpy : 0.00011301040649414062 nb_pixel_total : 5307 time to create 1 rle with old method : 0.006273031234741211 length of segment : 104 time for calcul the mask position with numpy : 7.939338684082031e-05 nb_pixel_total : 3755 time to create 1 rle with old method : 0.004511594772338867 length of segment : 71 time for calcul the mask position with numpy : 6.604194641113281e-05 nb_pixel_total : 2189 time to create 1 rle with old method : 0.0027120113372802734 length of segment : 56 time for calcul the mask position with numpy : 0.0003161430358886719 nb_pixel_total : 7551 time to create 1 rle with old method : 0.008750677108764648 length of segment : 103 time for calcul the mask position with numpy : 0.0024063587188720703 nb_pixel_total : 119120 time to create 1 rle with old method : 0.13097620010375977 length of segment : 491 time for calcul the mask position with numpy : 7.843971252441406e-05 nb_pixel_total : 2278 time to create 1 rle with old method : 0.0027687549591064453 length of segment : 61 time for calcul the mask position with numpy : 0.0004317760467529297 nb_pixel_total : 13522 time to create 1 rle with old method : 0.016050100326538086 length of segment : 192 time for calcul the mask position with numpy : 0.0003974437713623047 nb_pixel_total : 12349 time to create 1 rle with old method : 0.014234781265258789 length of segment : 187 time for calcul the mask position with numpy : 0.00013947486877441406 nb_pixel_total : 3150 time to create 1 rle with old method : 0.004035234451293945 length of segment : 51 time for calcul the mask position with numpy : 0.00020360946655273438 nb_pixel_total : 4421 time to create 1 rle with old method : 0.005201578140258789 length of segment : 117 time for calcul the mask position with numpy : 0.0002849102020263672 nb_pixel_total : 8923 time to create 1 rle with old method : 0.010503053665161133 length of segment : 150 time for calcul the mask position with numpy : 0.000118255615234375 nb_pixel_total : 1624 time to create 1 rle with old method : 0.0021414756774902344 length of segment : 49 time for calcul the mask position with numpy : 0.00027823448181152344 nb_pixel_total : 8634 time to create 1 rle with old method : 0.009648323059082031 length of segment : 132 time for calcul the mask position with numpy : 0.0001347064971923828 nb_pixel_total : 2346 time to create 1 rle with old method : 0.0031194686889648438 length of segment : 47 time for calcul the mask position with numpy : 0.0003724098205566406 nb_pixel_total : 9602 time to create 1 rle with old method : 0.011314153671264648 length of segment : 142 time for calcul the mask position with numpy : 0.00012040138244628906 nb_pixel_total : 1623 time to create 1 rle with old method : 0.0020689964294433594 length of segment : 46 time for calcul the mask position with numpy : 0.00046563148498535156 nb_pixel_total : 10740 time to create 1 rle with old method : 0.013581514358520508 length of segment : 194 time for calcul the mask position with numpy : 0.00011610984802246094 nb_pixel_total : 2775 time to create 1 rle with old method : 0.0032651424407958984 length of segment : 42 time for calcul the mask position with numpy : 0.0004646778106689453 nb_pixel_total : 13466 time to create 1 rle with old method : 0.015656232833862305 length of segment : 193 time for calcul the mask position with numpy : 0.002360820770263672 nb_pixel_total : 114923 time to create 1 rle with old method : 0.12884020805358887 length of segment : 554 time for calcul the mask position with numpy : 0.0002009868621826172 nb_pixel_total : 6034 time to create 1 rle with old method : 0.0074002742767333984 length of segment : 81 time for calcul the mask position with numpy : 9.107589721679688e-05 nb_pixel_total : 1049 time to create 1 rle with old method : 0.0013492107391357422 length of segment : 32 time for calcul the mask position with numpy : 0.0003161430358886719 nb_pixel_total : 16650 time to create 1 rle with old method : 0.018890380859375 length of segment : 134 time for calcul the mask position with numpy : 0.0002646446228027344 nb_pixel_total : 9918 time to create 1 rle with old method : 0.01149439811706543 length of segment : 117 time spent for convertir_results : 1.8026468753814697 Inside saveOutput : final : False verbose : 0 eke 12-6-18 : saveMask need to be cleaned for new output ! Number saved : None batch 1 Loaded 51 chid ids of type : 3594 Number RLEs to save : 6346 save missing photos in datou_result : time spend for datou_step_exec : 25.26165008544922 time spend to save output : 0.41349101066589355 total time spend for step 1 : 25.675141096115112 step2:crop_condition Mon Sep 22 19:30:57 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 : 14 ! batch 1 Loaded 51 chid ids of type : 3594 ++++++++++++++++++++++++++++++++++++++++++++++++++++ begin to crop the class : papier param for this class : {'min_score': 0.7} filtre for class : papier hashtag_id of this class : 492668766 we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! map_result returned by crop_photo_return_map_crop : length : 37 About to insert : list_path_to_insert length 37 new photo from crops ! About to upload 37 photos upload in portfolio : 3736932 init cache_photo without model_param we have 37 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1758562259_1198527 batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 37 photos in the portfolio 3736932 time of upload the photos Elapsed time : 10.649348020553589 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 ! 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/1758562270_1198527 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 : 0.5996038913726807 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/1758562271_1198527 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 : 0.701519250869751 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 ! map_result returned by crop_photo_return_map_crop : length : 8 About to insert : list_path_to_insert length 8 new photo from crops ! About to upload 8 photos upload in portfolio : 3736932 init cache_photo without model_param we have 8 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1758562273_1198527 batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 8 photos in the portfolio 3736932 time of upload the photos Elapsed time : 3.1438870429992676 we have finished the crop for the class : pet_clair begin to crop the class : autre param for this class : {'min_score': 0.7} filtre for class : autre hashtag_id of this class : 494826614 we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! map_result returned by crop_photo_return_map_crop : length : 3 About to insert : list_path_to_insert length 3 new photo from crops ! About to upload 3 photos upload in portfolio : 3736932 init cache_photo without model_param we have 3 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1758562276_1198527 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 : 0.8086683750152588 we have finished the crop for the class : autre begin to crop the class : pehd param for this class : {'min_score': 0.7} filtre for class : pehd hashtag_id of this class : 628944319 begin to crop the class : pet_fonce param for this class : {'min_score': 0.7} filtre for class : pet_fonce hashtag_id of this class : 2107755900 we have both polygon and rles Next one ! map_result returned by crop_photo_return_map_crop : length : 1 About to insert : list_path_to_insert length 1 new photo from crops ! About to upload 1 photos upload in portfolio : 3736932 init cache_photo without model_param we have 1 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1758562278_1198527 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 : 0.5809454917907715 we have finished the crop for the class : pet_fonce delete rles from all chi we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles 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 [1385493414, 1385493392, 1385493389, 1385493387, 1385493384, 1385493382, 1385493380, 1385493374, 1385493371, 1385493368, 1385493365, 1385493363, 1385493361, 1385493288] Looping around the photos to save general results len do output : 51 /1385508715Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508716Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508717Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508718Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508719Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508720Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508721Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508722Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508723Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508724Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508725Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508726Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508727Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508728Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508729Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508730Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508731Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508732Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508733Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508734Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508735Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508736Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508737Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508738Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508739Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508740Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508741Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508742Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508743Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508744Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508745Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508746Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508747Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508748Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508749Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508750Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508751Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508752Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508753Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508754Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508755Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508756Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508757Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508758Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508759Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508760Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508761Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508763Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508764Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508765Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1385508767Didn'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, '3759647') ('3318', '27101376', '1385493414', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493392', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493389', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493387', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493384', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493382', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493380', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493374', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493371', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493368', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493365', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493363', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493361', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493288', None, None, None, None, None, '3759647') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 167 time used for this insertion : 0.018765926361083984 save_final save missing photos in datou_result : time spend for datou_step_exec : 21.125043153762817 time spend to save output : 0.020468473434448242 total time spend for step 2 : 21.145511627197266 step3:rle_unique_nms_with_priority Mon Sep 22 19:31:18 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array 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 51 chid ids of type : 3594 ++++++++++++++++++++++++++++++++++++++++++++++++++++nb_obj : 6 nb_hashtags : 3 time to prepare the origin masks : 0.8359007835388184 time for calcul the mask position with numpy : 0.26581597328186035 nb_pixel_total : 2035279 time to create 1 rle with new method : 0.26413416862487793 time for calcul the mask position with numpy : 0.007901191711425781 nb_pixel_total : 3657 time to create 1 rle with old method : 0.004237174987792969 time for calcul the mask position with numpy : 0.007988929748535156 nb_pixel_total : 10282 time to create 1 rle with old method : 0.011816263198852539 time for calcul the mask position with numpy : 0.007930278778076172 nb_pixel_total : 3325 time to create 1 rle with old method : 0.004283905029296875 time for calcul the mask position with numpy : 0.008367776870727539 nb_pixel_total : 3842 time to create 1 rle with old method : 0.0057828426361083984 time for calcul the mask position with numpy : 0.00797891616821289 nb_pixel_total : 3139 time to create 1 rle with old method : 0.003699064254760742 time for calcul the mask position with numpy : 0.007900714874267578 nb_pixel_total : 14076 time to create 1 rle with old method : 0.016115188598632812 create new chi : 0.6386134624481201 time to delete rle : 0.018178462982177734 batch 1 Loaded 13 chid ids of type : 3594 ++++++Number RLEs to save : 2332 TO DO : save crop sub photo not yet done ! save time : 0.17372632026672363 nb_obj : 5 nb_hashtags : 2 time to prepare the origin masks : 0.2961618900299072 time for calcul the mask position with numpy : 0.0772092342376709 nb_pixel_total : 2032030 time to create 1 rle with new method : 0.2342841625213623 time for calcul the mask position with numpy : 0.006452798843383789 nb_pixel_total : 6124 time to create 1 rle with old method : 0.006982326507568359 time for calcul the mask position with numpy : 0.007766246795654297 nb_pixel_total : 15947 time to create 1 rle with old method : 0.01826620101928711 time for calcul the mask position with numpy : 0.0077059268951416016 nb_pixel_total : 5731 time to create 1 rle with old method : 0.00669407844543457 time for calcul the mask position with numpy : 0.013121366500854492 nb_pixel_total : 1100 time to create 1 rle with old method : 0.0013172626495361328 time for calcul the mask position with numpy : 0.008449792861938477 nb_pixel_total : 12668 time to create 1 rle with old method : 0.014494180679321289 create new chi : 0.4123802185058594 time to delete rle : 0.0006477832794189453 batch 1 Loaded 11 chid ids of type : 3594 +++++Number RLEs to save : 2328 TO DO : save crop sub photo not yet done ! save time : 0.1756434440612793 nb_obj : 3 nb_hashtags : 2 time to prepare the origin masks : 0.10203361511230469 time for calcul the mask position with numpy : 0.04004311561584473 nb_pixel_total : 2051587 time to create 1 rle with new method : 0.16537046432495117 time for calcul the mask position with numpy : 0.0073986053466796875 nb_pixel_total : 6124 time to create 1 rle with old method : 0.007040500640869141 time for calcul the mask position with numpy : 0.00743556022644043 nb_pixel_total : 12794 time to create 1 rle with old method : 0.01633429527282715 time for calcul the mask position with numpy : 0.007597923278808594 nb_pixel_total : 3095 time to create 1 rle with old method : 0.004266023635864258 create new chi : 0.255887508392334 time to delete rle : 0.0004978179931640625 batch 1 Loaded 7 chid ids of type : 3594 +++Number RLEs to save : 1814 TO DO : save crop sub photo not yet done ! save time : 0.13920187950134277 nb_obj : 5 nb_hashtags : 1 time to prepare the origin masks : 0.12631678581237793 time for calcul the mask position with numpy : 0.16756153106689453 nb_pixel_total : 2051275 time to create 1 rle with new method : 0.10638999938964844 time for calcul the mask position with numpy : 0.008152961730957031 nb_pixel_total : 1498 time to create 1 rle with old method : 0.001905679702758789 time for calcul the mask position with numpy : 0.007913351058959961 nb_pixel_total : 7108 time to create 1 rle with old method : 0.008252620697021484 time for calcul the mask position with numpy : 0.008185148239135742 nb_pixel_total : 5767 time to create 1 rle with old method : 0.007058858871459961 time for calcul the mask position with numpy : 0.007363319396972656 nb_pixel_total : 3747 time to create 1 rle with old method : 0.004428863525390625 time for calcul the mask position with numpy : 0.006542205810546875 nb_pixel_total : 4205 time to create 1 rle with old method : 0.004914045333862305 create new chi : 0.3531227111816406 time to delete rle : 0.00034499168395996094 batch 1 Loaded 11 chid ids of type : 3594 +++++Number RLEs to save : 1848 TO DO : save crop sub photo not yet done ! save time : 0.1568470001220703 nb_obj : 3 nb_hashtags : 2 time to prepare the origin masks : 0.059763193130493164 time for calcul the mask position with numpy : 0.09005117416381836 nb_pixel_total : 2055442 time to create 1 rle with new method : 0.16380572319030762 time for calcul the mask position with numpy : 0.007435798645019531 nb_pixel_total : 3816 time to create 1 rle with old method : 0.004444122314453125 time for calcul the mask position with numpy : 0.008257865905761719 nb_pixel_total : 11716 time to create 1 rle with old method : 0.013805627822875977 time for calcul the mask position with numpy : 0.007004737854003906 nb_pixel_total : 2626 time to create 1 rle with old method : 0.004462003707885742 create new chi : 0.31204843521118164 time to delete rle : 0.0003743171691894531 batch 1 Loaded 7 chid ids of type : 3594 +++Number RLEs to save : 1682 TO DO : save crop sub photo not yet done ! save time : 0.12391972541809082 nb_obj : 1 nb_hashtags : 1 time to prepare the origin masks : 0.04421734809875488 time for calcul the mask position with numpy : 0.027000904083251953 nb_pixel_total : 2060004 time to create 1 rle with new method : 0.1283578872680664 time for calcul the mask position with numpy : 0.006452322006225586 nb_pixel_total : 13596 time to create 1 rle with old method : 0.01660633087158203 create new chi : 0.19156265258789062 time to delete rle : 0.0002875328063964844 batch 1 Loaded 3 chid ids of type : 3594 +Number RLEs to save : 1464 TO DO : save crop sub photo not yet done ! save time : 0.10737037658691406 nb_obj : 10 nb_hashtags : 2 time to prepare the origin masks : 0.7767355442047119 time for calcul the mask position with numpy : 0.0580134391784668 nb_pixel_total : 1902408 time to create 1 rle with new method : 0.19345593452453613 time for calcul the mask position with numpy : 0.0062181949615478516 nb_pixel_total : 2278 time to create 1 rle with old method : 0.002518892288208008 time for calcul the mask position with numpy : 0.0071828365325927734 nb_pixel_total : 119120 time to create 1 rle with old method : 0.1292884349822998 time for calcul the mask position with numpy : 0.006245613098144531 nb_pixel_total : 7551 time to create 1 rle with old method : 0.008454084396362305 time for calcul the mask position with numpy : 0.006313323974609375 nb_pixel_total : 2189 time to create 1 rle with old method : 0.002432107925415039 time for calcul the mask position with numpy : 0.006328105926513672 nb_pixel_total : 3755 time to create 1 rle with old method : 0.004232883453369141 time for calcul the mask position with numpy : 0.005820512771606445 nb_pixel_total : 5307 time to create 1 rle with old method : 0.005793333053588867 time for calcul the mask position with numpy : 0.0059642791748046875 nb_pixel_total : 2594 time to create 1 rle with old method : 0.003010988235473633 time for calcul the mask position with numpy : 0.0067195892333984375 nb_pixel_total : 12244 time to create 1 rle with old method : 0.013785123825073242 time for calcul the mask position with numpy : 0.006533384323120117 nb_pixel_total : 7799 time to create 1 rle with old method : 0.012682199478149414 time for calcul the mask position with numpy : 0.006125688552856445 nb_pixel_total : 8355 time to create 1 rle with old method : 0.009558439254760742 create new chi : 0.5168004035949707 time to delete rle : 0.000568389892578125 batch 1 Loaded 21 chid ids of type : 3594 ++++++++++Number RLEs to save : 3864 TO DO : save crop sub photo not yet done ! save time : 0.24679327011108398 nb_obj : 1 nb_hashtags : 1 time to prepare the origin masks : 0.04728102684020996 time for calcul the mask position with numpy : 0.02132415771484375 nb_pixel_total : 2060078 time to create 1 rle with new method : 0.029769182205200195 time for calcul the mask position with numpy : 0.006366729736328125 nb_pixel_total : 13522 time to create 1 rle with old method : 0.016259193420410156 create new chi : 0.08714723587036133 time to delete rle : 0.00023484230041503906 batch 1 Loaded 3 chid ids of type : 3594 +Number RLEs to save : 1464 TO DO : save crop sub photo not yet done ! save time : 0.11680221557617188 nb_obj : 1 nb_hashtags : 1 time to prepare the origin masks : 0.037191152572631836 time for calcul the mask position with numpy : 0.09739065170288086 nb_pixel_total : 2061251 time to create 1 rle with new method : 0.3646731376647949 time for calcul the mask position with numpy : 0.006433248519897461 nb_pixel_total : 12349 time to create 1 rle with old method : 0.015961885452270508 create new chi : 0.4954679012298584 time to delete rle : 0.00032329559326171875 batch 1 Loaded 3 chid ids of type : 3594 +Number RLEs to save : 1454 TO DO : save crop sub photo not yet done ! save time : 0.12163519859313965 nb_obj : 3 nb_hashtags : 2 time to prepare the origin masks : 0.12747693061828613 time for calcul the mask position with numpy : 0.655346155166626 nb_pixel_total : 2057106 time to create 1 rle with new method : 0.10420703887939453 time for calcul the mask position with numpy : 0.006876707077026367 nb_pixel_total : 8923 time to create 1 rle with old method : 0.010335445404052734 time for calcul the mask position with numpy : 0.008512258529663086 nb_pixel_total : 4421 time to create 1 rle with old method : 0.005166769027709961 time for calcul the mask position with numpy : 0.007868528366088867 nb_pixel_total : 3150 time to create 1 rle with old method : 0.0036859512329101562 create new chi : 0.8146920204162598 time to delete rle : 0.0005354881286621094 batch 1 Loaded 7 chid ids of type : 3594 ++++Number RLEs to save : 1716 TO DO : save crop sub photo not yet done ! save time : 0.15122628211975098 No data in photo_id : 1385493365 nb_obj : 7 nb_hashtags : 2 time to prepare the origin masks : 0.711961030960083 time for calcul the mask position with numpy : 0.08193016052246094 nb_pixel_total : 2036256 time to create 1 rle with new method : 0.29708242416381836 time for calcul the mask position with numpy : 0.010720014572143555 nb_pixel_total : 2775 time to create 1 rle with old method : 0.006609439849853516 time for calcul the mask position with numpy : 0.012526988983154297 nb_pixel_total : 10740 time to create 1 rle with old method : 0.02197718620300293 time for calcul the mask position with numpy : 0.007868766784667969 nb_pixel_total : 1623 time to create 1 rle with old method : 0.002011537551879883 time for calcul the mask position with numpy : 0.00760340690612793 nb_pixel_total : 9602 time to create 1 rle with old method : 0.011039257049560547 time for calcul the mask position with numpy : 0.007683992385864258 nb_pixel_total : 2346 time to create 1 rle with old method : 0.0027680397033691406 time for calcul the mask position with numpy : 0.0076100826263427734 nb_pixel_total : 8634 time to create 1 rle with old method : 0.009905338287353516 time for calcul the mask position with numpy : 0.007807731628417969 nb_pixel_total : 1624 time to create 1 rle with old method : 0.0019490718841552734 create new chi : 0.5133416652679443 time to delete rle : 0.0006287097930908203 batch 1 Loaded 15 chid ids of type : 3594 +++++++Number RLEs to save : 2384 TO DO : save crop sub photo not yet done ! save time : 0.17424345016479492 nb_obj : 6 nb_hashtags : 4 time to prepare the origin masks : 0.2525002956390381 time for calcul the mask position with numpy : 0.11122488975524902 nb_pixel_total : 1911560 time to create 1 rle with new method : 0.13628673553466797 time for calcul the mask position with numpy : 0.008127927780151367 nb_pixel_total : 9918 time to create 1 rle with old method : 0.011934280395507812 time for calcul the mask position with numpy : 0.0087432861328125 nb_pixel_total : 16650 time to create 1 rle with old method : 0.020619630813598633 time for calcul the mask position with numpy : 0.007938861846923828 nb_pixel_total : 1049 time to create 1 rle with old method : 0.0012555122375488281 time for calcul the mask position with numpy : 0.007402658462524414 nb_pixel_total : 6034 time to create 1 rle with old method : 0.006996631622314453 time for calcul the mask position with numpy : 0.008409976959228516 nb_pixel_total : 114923 time to create 1 rle with old method : 0.13317394256591797 time for calcul the mask position with numpy : 0.0074710845947265625 nb_pixel_total : 13466 time to create 1 rle with old method : 0.015590667724609375 create new chi : 0.5036883354187012 time to delete rle : 0.0007381439208984375 batch 1 Loaded 13 chid ids of type : 3594 ++++++Number RLEs to save : 3302 TO DO : save crop sub photo not yet done ! save time : 0.21674752235412598 No data in photo_id : 1385493288 map_output_result : {1385493414: (0.0, 'Should be the crop_list due to order', 0), 1385493392: (0.0, 'Should be the crop_list due to order', 0), 1385493389: (0.0, 'Should be the crop_list due to order', 0), 1385493387: (0.0, 'Should be the crop_list due to order', 0), 1385493384: (0.0, 'Should be the crop_list due to order', 0), 1385493382: (0.0, 'Should be the crop_list due to order', 0), 1385493380: (0.0, 'Should be the crop_list due to order', 0), 1385493374: (0.0, 'Should be the crop_list due to order', 0), 1385493371: (0.0, 'Should be the crop_list due to order', 0), 1385493368: (0.0, 'Should be the crop_list due to order', 0), 1385493365: (0.0, 'Should be the crop_list due to order', 0.0), 1385493363: (0.0, 'Should be the crop_list due to order', 0), 1385493361: (0.0, 'Should be the crop_list due to order', 0), 1385493288: (0.0, 'Should be the crop_list due to order', 0.0)} End step rle-unique-nms Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : rle_unique_nms_with_priority we use saveGeneral [1385493414, 1385493392, 1385493389, 1385493387, 1385493384, 1385493382, 1385493380, 1385493374, 1385493371, 1385493368, 1385493365, 1385493363, 1385493361, 1385493288] Looping around the photos to save general results len do output : 14 /1385493414.Didn't retrieve data . /1385493392.Didn't retrieve data . /1385493389.Didn't retrieve data . /1385493387.Didn't retrieve data . /1385493384.Didn't retrieve data . /1385493382.Didn't retrieve data . /1385493380.Didn't retrieve data . /1385493374.Didn't retrieve data . /1385493371.Didn't retrieve data . /1385493368.Didn't retrieve data . /1385493365.Didn't retrieve data . /1385493363.Didn't retrieve data . /1385493361.Didn't retrieve data . /1385493288.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, '3759647') ('3318', '27101376', '1385493414', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493392', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493389', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493387', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493384', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493382', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493380', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493374', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493371', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493368', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493365', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493363', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493361', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493288', None, None, None, None, None, '3759647') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 42 time used for this insertion : 0.013326406478881836 save_final save missing photos in datou_result : time spend for datou_step_exec : 10.9359712600708 time spend to save output : 0.014027595520019531 total time spend for step 3 : 10.94999885559082 step4:ventilate_hashtags_in_portfolio Mon Sep 22 19:31:29 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 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 : 27101376 get user id for portfolio 27101376 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`=27101376 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('pehd','metal','carton','background','flou','pet_clair','papier','pet_fonce','environnement','mal_croppe','autre')) AND mptpi.`min_score`=0.5 To do To do SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=27101376 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('pehd','metal','carton','background','flou','pet_clair','papier','pet_fonce','environnement','mal_croppe','autre')) AND mptpi.`min_score`=0.5 To do Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") To do ! Use context local managing function ! SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=27101376 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('pehd','metal','carton','background','flou','pet_clair','papier','pet_fonce','environnement','mal_croppe','autre')) AND mptpi.`min_score`=0.5 To do lien utilise dans velours : https://marlene.fotonower.com/velours/27103075,27103076,27103077,27103078,27103079,27103080,27103081,27103082,27103083,27103084,27103085?tags=pehd,metal,carton,background,flou,pet_clair,papier,pet_fonce,environnement,mal_croppe,autre Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : ventilate_hashtags_in_portfolio we use saveGeneral [1385493414, 1385493392, 1385493389, 1385493387, 1385493384, 1385493382, 1385493380, 1385493374, 1385493371, 1385493368, 1385493365, 1385493363, 1385493361, 1385493288] Looping around the photos to save general results len do output : 1 /27101376. 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, '3759647') ('3318', '27101376', '1385493414', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493392', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493389', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493387', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493384', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493382', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493380', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493374', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493371', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493368', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493365', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493363', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493361', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493288', None, None, None, None, None, '3759647') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 15 time used for this insertion : 0.014967918395996094 save_final save missing photos in datou_result : time spend for datou_step_exec : 1.7383842468261719 time spend to save output : 0.01547861099243164 total time spend for step 4 : 1.7538628578186035 step5:final Mon Sep 22 19:31:31 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! 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 : {1385493414: ('0.019597525352733684',), 1385493392: ('0.019597525352733684',), 1385493389: ('0.019597525352733684',), 1385493387: ('0.019597525352733684',), 1385493384: ('0.019597525352733684',), 1385493382: ('0.019597525352733684',), 1385493380: ('0.019597525352733684',), 1385493374: ('0.019597525352733684',), 1385493371: ('0.019597525352733684',), 1385493368: ('0.019597525352733684',), 1385493365: ('0.019597525352733684',), 1385493363: ('0.019597525352733684',), 1385493361: ('0.019597525352733684',), 1385493288: ('0.019597525352733684',)} new output for save of step final : {1385493414: ('0.019597525352733684',), 1385493392: ('0.019597525352733684',), 1385493389: ('0.019597525352733684',), 1385493387: ('0.019597525352733684',), 1385493384: ('0.019597525352733684',), 1385493382: ('0.019597525352733684',), 1385493380: ('0.019597525352733684',), 1385493374: ('0.019597525352733684',), 1385493371: ('0.019597525352733684',), 1385493368: ('0.019597525352733684',), 1385493365: ('0.019597525352733684',), 1385493363: ('0.019597525352733684',), 1385493361: ('0.019597525352733684',), 1385493288: ('0.019597525352733684',)} [1385493414, 1385493392, 1385493389, 1385493387, 1385493384, 1385493382, 1385493380, 1385493374, 1385493371, 1385493368, 1385493365, 1385493363, 1385493361, 1385493288] Looping around the photos to save general results len do output : 14 /1385493414.Didn't retrieve data . /1385493392.Didn't retrieve data . /1385493389.Didn't retrieve data . /1385493387.Didn't retrieve data . /1385493384.Didn't retrieve data . /1385493382.Didn't retrieve data . /1385493380.Didn't retrieve data . /1385493374.Didn't retrieve data . /1385493371.Didn't retrieve data . /1385493368.Didn't retrieve data . /1385493365.Didn't retrieve data . /1385493363.Didn't retrieve data . /1385493361.Didn't retrieve data . /1385493288.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, '3759647') ('3318', '27101376', '1385493414', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493392', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493389', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493387', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493384', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493382', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493380', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493374', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493371', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493368', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493365', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493363', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493361', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493288', None, None, None, None, None, '3759647') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 42 time used for this insertion : 0.013928890228271484 save_final save missing photos in datou_result : time spend for datou_step_exec : 0.16623544692993164 time spend to save output : 0.014809131622314453 total time spend for step 5 : 0.1810445785522461 step6:blur_detection Mon Sep 22 19:31:31 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! 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/1758562229_1198527_1385493414_2cf5f5e1cce3617e965ca5ba40d5fd4f.jpg resize: (1080, 1920) 1385493414 -0.21830604232967496 treat image : temp/1758562229_1198527_1385493392_7a58c4570c0cbbe7fb96a311e2155e01.jpg resize: (1080, 1920) 1385493392 -4.1656524628877625 treat image : temp/1758562229_1198527_1385493389_6cc27c1bd58ee9466e3a6a5bcba58d92.jpg resize: (1080, 1920) 1385493389 -0.14293948534201625 treat image : temp/1758562229_1198527_1385493387_82669b1e2b95d4a2b865c4d055c6a1d7.jpg resize: (1080, 1920) 1385493387 -0.4336149573857401 treat image : temp/1758562229_1198527_1385493384_0800b203d866ebdee93fa488509e0a15.jpg resize: (1080, 1920) 1385493384 -4.3689766950073174 treat image : temp/1758562229_1198527_1385493382_7ac564fa8ca55bb0a588d7d619776547.jpg resize: (1080, 1920) 1385493382 -1.7713379347162475 treat image : temp/1758562229_1198527_1385493380_d3597869a388d24a409d7024246a7145.jpg resize: (1080, 1920) 1385493380 -0.9588840126676682 treat image : temp/1758562229_1198527_1385493374_5a1bfd20d66d98ef495f4254e57a8def.jpg resize: (1080, 1920) 1385493374 0.20051835736715923 treat image : temp/1758562229_1198527_1385493371_712f54a1d9ea5206aaa42c73153d94a6.jpg resize: (1080, 1920) 1385493371 -0.40472937529603353 treat image : temp/1758562229_1198527_1385493368_3baeada51ccb65ef55e8b390acfa52e0.jpg resize: (1080, 1920) 1385493368 0.2557862273142555 treat image : temp/1758562229_1198527_1385493365_7aba007111844fdbb3180d833c8eaba5.jpg resize: (1080, 1920) 1385493365 0.4871868654270025 treat image : temp/1758562229_1198527_1385493363_4aec09ad3be1ddaac8ec1709919b7085.jpg resize: (1080, 1920) 1385493363 -4.418815722879061 treat image : temp/1758562229_1198527_1385493361_5b879e577807d29dd68b7ee815d5022b.jpg resize: (1080, 1920) 1385493361 -4.105101821322119 treat image : temp/1758562229_1198527_1385493288_bad5729ae338f473cb9c7cd075e14bb7.jpg resize: (1080, 1920) 1385493288 1.052830364578977 treat image : temp/1758562229_1198527_1385493414_2cf5f5e1cce3617e965ca5ba40d5fd4f_rle_crop_3970347550_0.png resize: (194, 120) 1385508715 -0.36045728027606294 treat image : temp/1758562229_1198527_1385493414_2cf5f5e1cce3617e965ca5ba40d5fd4f_rle_crop_3970347551_0.png resize: (56, 95) 1385508716 -3.166022267872808 treat image : temp/1758562229_1198527_1385493414_2cf5f5e1cce3617e965ca5ba40d5fd4f_rle_crop_3970347552_0.png resize: (109, 53) 1385508717 -0.19313646496674855 treat image : temp/1758562229_1198527_1385493414_2cf5f5e1cce3617e965ca5ba40d5fd4f_rle_crop_3970347554_0.png resize: (139, 116) 1385508718 -1.3569133845565264 treat image : temp/1758562229_1198527_1385493392_7a58c4570c0cbbe7fb96a311e2155e01_rle_crop_3970347556_0.png resize: (183, 114) 1385508719 -0.5387756527567524 treat image : temp/1758562229_1198527_1385493392_7a58c4570c0cbbe7fb96a311e2155e01_rle_crop_3970347558_0.png resize: (152, 60) 1385508720 -4.361546313799851 treat image : temp/1758562229_1198527_1385493392_7a58c4570c0cbbe7fb96a311e2155e01_rle_crop_3970347559_0.png resize: (127, 176) 1385508721 -2.859505155628956 treat image : temp/1758562229_1198527_1385493392_7a58c4570c0cbbe7fb96a311e2155e01_rle_crop_3970347560_0.png resize: (81, 103) 1385508722 -3.956005370692903 treat image : temp/1758562229_1198527_1385493389_6cc27c1bd58ee9466e3a6a5bcba58d92_rle_crop_3970347562_0.png resize: (188, 112) 1385508723 -0.4242433546799602 treat image : temp/1758562229_1198527_1385493389_6cc27c1bd58ee9466e3a6a5bcba58d92_rle_crop_3970347563_0.png resize: (125, 79) 1385508724 -0.9378973240327111 treat image : temp/1758562229_1198527_1385493387_82669b1e2b95d4a2b865c4d055c6a1d7_rle_crop_3970347564_0.png resize: (102, 83) 1385508725 -0.6229501314670346 treat image : temp/1758562229_1198527_1385493387_82669b1e2b95d4a2b865c4d055c6a1d7_rle_crop_3970347565_0.png resize: (79, 62) 1385508726 0.4427305362735986 treat image : temp/1758562229_1198527_1385493387_82669b1e2b95d4a2b865c4d055c6a1d7_rle_crop_3970347566_0.png resize: (99, 95) 1385508727 -1.395886029995889 treat image : temp/1758562229_1198527_1385493387_82669b1e2b95d4a2b865c4d055c6a1d7_rle_crop_3970347567_0.png resize: (63, 159) 1385508728 -0.9800700105685404 treat image : temp/1758562229_1198527_1385493387_82669b1e2b95d4a2b865c4d055c6a1d7_rle_crop_3970347568_0.png resize: (39, 51) 1385508729 1.2770022769511367 treat image : temp/1758562229_1198527_1385493384_0800b203d866ebdee93fa488509e0a15_rle_crop_3970347569_0.png resize: (49, 64) 1385508730 1.750803947536071 treat image : temp/1758562229_1198527_1385493384_0800b203d866ebdee93fa488509e0a15_rle_crop_3970347570_0.png resize: (183, 105) 1385508731 -0.48190350836316315 treat image : temp/1758562229_1198527_1385493382_7ac564fa8ca55bb0a588d7d619776547_rle_crop_3970347572_0.png resize: (192, 119) 1385508732 -0.38953785154524273 treat image : temp/1758562229_1198527_1385493380_d3597869a388d24a409d7024246a7145_rle_crop_3970347573_0.png resize: (123, 85) 1385508733 1.3481818828246406 treat image : temp/1758562229_1198527_1385493380_d3597869a388d24a409d7024246a7145_rle_crop_3970347574_0.png resize: (134, 112) 1385508734 -0.9243153123002749 treat image : temp/1758562229_1198527_1385493380_d3597869a388d24a409d7024246a7145_rle_crop_3970347575_0.png resize: (183, 108) 1385508735 -0.38407272791220537 treat image : temp/1758562229_1198527_1385493380_d3597869a388d24a409d7024246a7145_rle_crop_3970347577_0.png resize: (103, 78) 1385508736 -0.8371931237560322 treat image : temp/1758562229_1198527_1385493380_d3597869a388d24a409d7024246a7145_rle_crop_3970347578_0.png resize: (71, 59) 1385508737 0.7473312018449388 treat image : temp/1758562229_1198527_1385493380_d3597869a388d24a409d7024246a7145_rle_crop_3970347579_0.png resize: (55, 58) 1385508738 -0.7025171404516205 treat image : temp/1758562229_1198527_1385493380_d3597869a388d24a409d7024246a7145_rle_crop_3970347580_0.png resize: (103, 129) 1385508739 -2.281365722059876 treat image : temp/1758562229_1198527_1385493380_d3597869a388d24a409d7024246a7145_rle_crop_3970347582_0.png resize: (61, 58) 1385508740 -0.13779524141490826 treat image : temp/1758562229_1198527_1385493374_5a1bfd20d66d98ef495f4254e57a8def_rle_crop_3970347583_0.png resize: (188, 132) 1385508741 -0.6055937528468274 treat image : temp/1758562229_1198527_1385493371_712f54a1d9ea5206aaa42c73153d94a6_rle_crop_3970347584_0.png resize: (184, 114) 1385508742 -0.389679320045646 treat image : temp/1758562229_1198527_1385493368_3baeada51ccb65ef55e8b390acfa52e0_rle_crop_3970347586_0.png resize: (117, 61) 1385508743 -2.6059505980488256 treat image : temp/1758562229_1198527_1385493363_4aec09ad3be1ddaac8ec1709919b7085_rle_crop_3970347588_0.png resize: (49, 42) 1385508744 -1.9319495833069187 treat image : temp/1758562229_1198527_1385493363_4aec09ad3be1ddaac8ec1709919b7085_rle_crop_3970347589_0.png resize: (128, 80) 1385508745 -2.010979898766715 treat image : temp/1758562229_1198527_1385493363_4aec09ad3be1ddaac8ec1709919b7085_rle_crop_3970347592_0.png resize: (46, 47) 1385508746 -3.413503613500213 treat image : temp/1758562229_1198527_1385493363_4aec09ad3be1ddaac8ec1709919b7085_rle_crop_3970347593_0.png resize: (194, 91) 1385508747 -0.9177284686854992 treat image : temp/1758562229_1198527_1385493363_4aec09ad3be1ddaac8ec1709919b7085_rle_crop_3970347594_0.png resize: (42, 80) 1385508748 -3.275388411484217 treat image : temp/1758562229_1198527_1385493361_5b879e577807d29dd68b7ee815d5022b_rle_crop_3970347595_0.png resize: (191, 114) 1385508749 -0.6003325589956551 treat image : temp/1758562229_1198527_1385493361_5b879e577807d29dd68b7ee815d5022b_rle_crop_3970347597_0.png resize: (81, 105) 1385508750 -3.6112024988242837 treat image : temp/1758562229_1198527_1385493361_5b879e577807d29dd68b7ee815d5022b_rle_crop_3970347600_0.png resize: (114, 166) 1385508751 -1.337463671960043 treat image : temp/1758562229_1198527_1385493414_2cf5f5e1cce3617e965ca5ba40d5fd4f_rle_crop_3970347553_0.png resize: (59, 76) 1385508752 -0.5282291161302208 treat image : temp/1758562229_1198527_1385493414_2cf5f5e1cce3617e965ca5ba40d5fd4f_rle_crop_3970347555_0.png resize: (52, 93) 1385508753 -3.293333477640996 treat image : temp/1758562229_1198527_1385493389_6cc27c1bd58ee9466e3a6a5bcba58d92_rle_crop_3970347561_0.png resize: (54, 84) 1385508754 -0.3390840256375785 treat image : temp/1758562229_1198527_1385493380_d3597869a388d24a409d7024246a7145_rle_crop_3970347576_0.png resize: (57, 59) 1385508755 -0.6067385161560286 treat image : temp/1758562229_1198527_1385493380_d3597869a388d24a409d7024246a7145_rle_crop_3970347581_0.png resize: (489, 366) 1385508756 0.3460026670778438 treat image : temp/1758562229_1198527_1385493368_3baeada51ccb65ef55e8b390acfa52e0_rle_crop_3970347585_0.png resize: (51, 80) 1385508757 0.7749900769484599 treat image : temp/1758562229_1198527_1385493368_3baeada51ccb65ef55e8b390acfa52e0_rle_crop_3970347587_0.png resize: (130, 112) 1385508758 -0.9077342132800063 treat image : temp/1758562229_1198527_1385493363_4aec09ad3be1ddaac8ec1709919b7085_rle_crop_3970347590_0.png resize: (46, 76) 1385508759 -3.5618657800695317 treat image : temp/1758562229_1198527_1385493363_4aec09ad3be1ddaac8ec1709919b7085_rle_crop_3970347591_0.png resize: (142, 92) 1385508760 -1.6078371910882343 treat image : temp/1758562229_1198527_1385493361_5b879e577807d29dd68b7ee815d5022b_rle_crop_3970347596_0.png resize: (551, 330) 1385508761 0.17134952593479796 treat image : temp/1758562229_1198527_1385493392_7a58c4570c0cbbe7fb96a311e2155e01_rle_crop_3970347557_0.png resize: (33, 43) 1385508763 -2.988045210963507 treat image : temp/1758562229_1198527_1385493384_0800b203d866ebdee93fa488509e0a15_rle_crop_3970347571_0.png resize: (66, 79) 1385508764 -4.798656450412988 treat image : temp/1758562229_1198527_1385493361_5b879e577807d29dd68b7ee815d5022b_rle_crop_3970347598_0.png resize: (32, 46) 1385508765 -3.661257109570835 treat image : temp/1758562229_1198527_1385493361_5b879e577807d29dd68b7ee815d5022b_rle_crop_3970347599_0.png resize: (133, 165) 1385508767 -3.3464483356167594 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 : 65 time used for this insertion : 0.014430999755859375 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 65 time used for this insertion : 0.013924360275268555 save missing photos in datou_result : time spend for datou_step_exec : 11.27411961555481 time spend to save output : 0.0327913761138916 total time spend for step 6 : 11.306910991668701 step7:brightness Mon Sep 22 19:31:42 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/1758562229_1198527_1385493414_2cf5f5e1cce3617e965ca5ba40d5fd4f.jpg treat image : temp/1758562229_1198527_1385493392_7a58c4570c0cbbe7fb96a311e2155e01.jpg treat image : temp/1758562229_1198527_1385493389_6cc27c1bd58ee9466e3a6a5bcba58d92.jpg treat image : temp/1758562229_1198527_1385493387_82669b1e2b95d4a2b865c4d055c6a1d7.jpg treat image : temp/1758562229_1198527_1385493384_0800b203d866ebdee93fa488509e0a15.jpg treat image : temp/1758562229_1198527_1385493382_7ac564fa8ca55bb0a588d7d619776547.jpg treat image : temp/1758562229_1198527_1385493380_d3597869a388d24a409d7024246a7145.jpg treat image : temp/1758562229_1198527_1385493374_5a1bfd20d66d98ef495f4254e57a8def.jpg treat image : temp/1758562229_1198527_1385493371_712f54a1d9ea5206aaa42c73153d94a6.jpg treat image : temp/1758562229_1198527_1385493368_3baeada51ccb65ef55e8b390acfa52e0.jpg treat image : 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temp/1758562229_1198527_1385493363_4aec09ad3be1ddaac8ec1709919b7085_rle_crop_3970347594_0.png treat image : temp/1758562229_1198527_1385493361_5b879e577807d29dd68b7ee815d5022b_rle_crop_3970347595_0.png treat image : temp/1758562229_1198527_1385493361_5b879e577807d29dd68b7ee815d5022b_rle_crop_3970347597_0.png treat image : temp/1758562229_1198527_1385493361_5b879e577807d29dd68b7ee815d5022b_rle_crop_3970347600_0.png treat image : temp/1758562229_1198527_1385493414_2cf5f5e1cce3617e965ca5ba40d5fd4f_rle_crop_3970347553_0.png treat image : temp/1758562229_1198527_1385493414_2cf5f5e1cce3617e965ca5ba40d5fd4f_rle_crop_3970347555_0.png treat image : temp/1758562229_1198527_1385493389_6cc27c1bd58ee9466e3a6a5bcba58d92_rle_crop_3970347561_0.png treat image : temp/1758562229_1198527_1385493380_d3597869a388d24a409d7024246a7145_rle_crop_3970347576_0.png treat image : temp/1758562229_1198527_1385493380_d3597869a388d24a409d7024246a7145_rle_crop_3970347581_0.png treat image : temp/1758562229_1198527_1385493368_3baeada51ccb65ef55e8b390acfa52e0_rle_crop_3970347585_0.png treat image : temp/1758562229_1198527_1385493368_3baeada51ccb65ef55e8b390acfa52e0_rle_crop_3970347587_0.png treat image : temp/1758562229_1198527_1385493363_4aec09ad3be1ddaac8ec1709919b7085_rle_crop_3970347590_0.png treat image : temp/1758562229_1198527_1385493363_4aec09ad3be1ddaac8ec1709919b7085_rle_crop_3970347591_0.png treat image : temp/1758562229_1198527_1385493361_5b879e577807d29dd68b7ee815d5022b_rle_crop_3970347596_0.png treat image : temp/1758562229_1198527_1385493392_7a58c4570c0cbbe7fb96a311e2155e01_rle_crop_3970347557_0.png treat image : temp/1758562229_1198527_1385493384_0800b203d866ebdee93fa488509e0a15_rle_crop_3970347571_0.png treat image : temp/1758562229_1198527_1385493361_5b879e577807d29dd68b7ee815d5022b_rle_crop_3970347598_0.png treat image : temp/1758562229_1198527_1385493361_5b879e577807d29dd68b7ee815d5022b_rle_crop_3970347599_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 : 65 time used for this insertion : 0.015266656875610352 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 65 time used for this insertion : 0.013092994689941406 save missing photos in datou_result : time spend for datou_step_exec : 3.1589231491088867 time spend to save output : 0.033141136169433594 total time spend for step 7 : 3.1920642852783203 step8:velours_tree Mon Sep 22 19:31:45 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed 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 : 0.19206690788269043 time spend to save output : 3.6716461181640625e-05 total time spend for step 8 : 0.19210362434387207 step9:send_mail_cod Mon Sep 22 19:31:46 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_P27101376_22-09-2025_19_31_46.pdf 27103075 imagette271030751758562306 27103076 change filename to text .imagette271030761758562306 27103077 change filename to text .imagette271030771758562306 27103078 imagette271030781758562306 27103079 imagette271030791758562306 27103080 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 .imagette271030801758562306 27103081 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 .imagette271030811758562306 27103082 change filename to text .imagette271030821758562308 27103084 imagette271030841758562308 27103085 change filename to text .change filename to text .change filename to text .imagette271030851758562308 SELECT h.hashtag,pcr.value FROM MTRUser.portfolio_carac_ratio pcr, MTRBack.hashtags h where pcr.portfolio_id=27101376 and hashtag_type = 3594 and pcr.hashtag_id = h.hashtag_id; velour_link : https://marlene.fotonower.com/velours/27103075,27103076,27103077,27103078,27103079,27103080,27103081,27103082,27103083,27103084,27103085?tags=pehd,metal,carton,background,flou,pet_clair,papier,pet_fonce,environnement,mal_croppe,autre args[1385493414] : ((1385493414, -0.21830604232967496, 492688767), (1385493414, 0.09678439878799132, 2107752395), '0.019597525352733684') We are sending mail with results at report@fotonower.com args[1385493392] : ((1385493392, -4.1656524628877625, 492609224), (1385493392, 0.2740506573330215, 2107752395), '0.019597525352733684') We are sending mail with results at report@fotonower.com args[1385493389] : ((1385493389, -0.14293948534201625, 492688767), (1385493389, 0.671836720129217, 2107752395), '0.019597525352733684') We are sending mail with results at report@fotonower.com args[1385493387] : ((1385493387, -0.4336149573857401, 492688767), (1385493387, 0.5053831874748376, 2107752395), '0.019597525352733684') We are sending mail with results at report@fotonower.com args[1385493384] : ((1385493384, -4.3689766950073174, 492609224), (1385493384, 0.34147601796240573, 2107752395), '0.019597525352733684') We are sending mail with results at report@fotonower.com args[1385493382] : ((1385493382, -1.7713379347162475, 492688767), (1385493382, 0.41442101046428315, 2107752395), '0.019597525352733684') We are sending mail with results at report@fotonower.com args[1385493380] : ((1385493380, -0.9588840126676682, 492688767), (1385493380, 0.29681702731906173, 2107752395), '0.019597525352733684') We are sending mail with results at report@fotonower.com args[1385493374] : ((1385493374, 0.20051835736715923, 492688767), (1385493374, 0.7460568886730921, 2107752395), '0.019597525352733684') We are sending mail with results at report@fotonower.com args[1385493371] : ((1385493371, -0.40472937529603353, 492688767), (1385493371, 0.9985656777917244, 2107752395), '0.019597525352733684') We are sending mail with results at report@fotonower.com args[1385493368] : ((1385493368, 0.2557862273142555, 492688767), (1385493368, 0.34734977217681806, 2107752395), '0.019597525352733684') We are sending mail with results at report@fotonower.com args[1385493365] : ((1385493365, 0.4871868654270025, 492688767), (1385493365, 0.5547302326967284, 2107752395), '0.019597525352733684') We are sending mail with results at report@fotonower.com args[1385493363] : ((1385493363, -4.418815722879061, 492609224), (1385493363, 0.4822690509030648, 2107752395), '0.019597525352733684') We are sending mail with results at report@fotonower.com args[1385493361] : ((1385493361, -4.105101821322119, 492609224), (1385493361, 0.3700757405131611, 2107752395), '0.019597525352733684') We are sending mail with results at report@fotonower.com args[1385493288] : ((1385493288, 1.052830364578977, 492688767), (1385493288, 0.8254769388072556, 2107752395), '0.019597525352733684') We are sending mail with results at report@fotonower.com refus_total : 0.019597525352733684 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=27101376 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_P27101376_22-09-2025_19_31_46.pdf results_Auto_P27101376_22-09-2025_19_31_46.pdf uploaded to url https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27101376_22-09-2025_19_31_46.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','27101376','results_Auto_P27101376_22-09-2025_19_31_46.pdf','https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27101376_22-09-2025_19_31_46.pdf','pdf','','0.19','0.019597525352733684') message_in_mail: Bonjour,
Veuillez trouver ci dessous les résultats du service carac on demand pour le portfolio: https://www.fotonower.com/view/27101376

https://www.fotonower.com/image?json=false&list_photos_id=1385493414
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1385493392
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1385493389
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1385493387
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1385493384
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1385493382
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1385493380
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1385493374
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1385493371
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1385493368
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1385493365
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1385493363
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1385493361
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1385493288
La photo est trop floue, merci de reprendre une photo.(avec le score = 1.052830364578977)

Dans ces conditions,le taux de refus est: 1.96%
Veuillez trouver les photos des contaminants.

exemples de contaminants: metal: https://www.fotonower.com/view/27103076?limit=200
exemples de contaminants: carton: https://www.fotonower.com/view/27103077?limit=200
exemples de contaminants: pet_clair: https://www.fotonower.com/view/27103080?limit=200
exemples de contaminants: papier: https://www.fotonower.com/view/27103081?limit=200
exemples de contaminants: pet_fonce: https://www.fotonower.com/view/27103082?limit=200
exemples de contaminants: autre: https://www.fotonower.com/view/27103085?limit=200
Veuillez trouver le rapport en pdf:https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27101376_22-09-2025_19_31_46.pdf.

Lien vers velours :https://marlene.fotonower.com/velours/27103075,27103076,27103077,27103078,27103079,27103080,27103081,27103082,27103083,27103084,27103085?tags=pehd,metal,carton,background,flou,pet_clair,papier,pet_fonce,environnement,mal_croppe,autre.


L'équipe Fotonower 202 b'' Server: nginx Date: Mon, 22 Sep 2025 17:31:50 GMT Content-Length: 0 Connection: close X-Message-Id: -XF_12gORBmmliFgwqjRYA 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 [1385493414, 1385493392, 1385493389, 1385493387, 1385493384, 1385493382, 1385493380, 1385493374, 1385493371, 1385493368, 1385493365, 1385493363, 1385493361, 1385493288] 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, '3759647') ('3318', '27101376', '1385493414', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493392', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493389', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493387', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493384', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493382', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493380', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493374', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493371', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493368', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493365', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493363', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493361', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493288', None, None, None, None, None, '3759647') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 14 time used for this insertion : 0.014859914779663086 save_final save missing photos in datou_result : time spend for datou_step_exec : 4.142756223678589 time spend to save output : 0.015151023864746094 total time spend for step 9 : 4.157907247543335 step10:split_time_score Mon Sep 22 19:31:50 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'}] (('17', 14),) ERROR counted https://github.com/fotonower/Velours/issues/663#issuecomment-421136223 {} 22092025 27101376 Nombre de photos uploadées : 14 / 23040 (0%) 22092025 27101376 Nombre de photos taguées (types de déchets): 0 / 14 (0%) 22092025 27101376 Nombre de photos taguées (volume) : 0 / 14 (0%) elapsed_time : load_data_split_time_score 2.6226043701171875e-06 elapsed_time : order_list_meta_photo_and_scores 5.9604644775390625e-06 ?????????????? elapsed_time : fill_and_build_computed_from_old_data 0.0007007122039794922 Catched exception ! Connect or reconnect ! Catched exception ! Connect or reconnect ! elapsed_time : insert_dashboard_record_day_entry 0.2168436050415039 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 : 0.05209852430555556 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27081911_22-09-2025_09_51_42.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27081911 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`=27081911 AND mptpi.`type`=3594 To do find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27086455 order by id desc limit 1 Qualite : 0.11064838927469141 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27086457_22-09-2025_10_51_50.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27086457 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`=27086457 AND mptpi.`type`=3594 To do Qualite : 0.12047576678240735 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27096228_22-09-2025_17_11_00.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27096228 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`=27096228 AND mptpi.`type`=3594 To do Qualite : 0.07098423032407408 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27096232_22-09-2025_16_31_38.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27096232 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`=27096232 AND mptpi.`type`=3594 To do Qualite : 0.03187968474426807 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27096240_22-09-2025_16_22_15.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27096240 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`=27096240 AND mptpi.`type`=3594 To do Qualite : 0.06591898999183013 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27096242_22-09-2025_16_13_39.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27096242 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`=27096242 AND mptpi.`type`=3594 To do Qualite : 0.09502984610768174 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27099648_22-09-2025_17_52_03.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27099648 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`=27099648 AND mptpi.`type`=3594 To do Qualite : 0.06505486968449932 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27099650_22-09-2025_17_42_44.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27099650 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`=27099650 AND mptpi.`type`=3594 To do Qualite : 0.08340133101851852 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27099651_22-09-2025_17_31_50.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27099651 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`=27099651 AND mptpi.`type`=3594 To do find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27101373 order by id desc limit 1 Qualite : 0.019597525352733684 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27101376_22-09-2025_19_31_46.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27101376 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`=27101376 AND mptpi.`type`=3594 To do Qualite : 0.11757369429976851 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27101379_22-09-2025_19_02_08.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27101379 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`=27101379 AND mptpi.`type`=3594 To do Qualite : 0.09443853684413582 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27101382_22-09-2025_18_51_34.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27101382 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`=27101382 AND mptpi.`type`=3594 To do NUMBER BATCH : 0 # DISPLAY ALL COLLECTED DATA : {'22092025': {'nb_upload': 14, '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 [1385493414, 1385493392, 1385493389, 1385493387, 1385493384, 1385493382, 1385493380, 1385493374, 1385493371, 1385493368, 1385493365, 1385493363, 1385493361, 1385493288] Looping around the photos to save general results len do output : 1 /27101376Didn'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, '3759647') ('3318', '27101376', '1385493414', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493392', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493389', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493387', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493384', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493382', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493380', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493374', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493371', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493368', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493365', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493363', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493361', None, None, None, None, None, '3759647') ('3318', None, None, None, None, None, None, None, '3759647') ('3318', '27101376', '1385493288', None, None, None, None, None, '3759647') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 15 time used for this insertion : 0.013741254806518555 save_final save missing photos in datou_result : time spend for datou_step_exec : 3.0342049598693848 time spend to save output : 0.013959169387817383 total time spend for step 10 : 3.048164129257202 caffe_path_current : About to save ! 2 After save, about to update current ! ret : 2 len(input) + len(total_photo_id_missing) : 14 set_done_treatment 39.60user 22.57system 1:28.26elapsed 70%CPU (0avgtext+0avgdata 2858964maxresident)k 560272inputs+13120outputs (1080major+1727261minor)pagefaults 0swaps