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 : 2504845 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 : ['4141163'] with mtr_portfolio_ids : ['29024015'] and first list_photo_ids : [] new path : /proc/2504845/ 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 , BFBFBFBFBFBFBFBFBFBFBFBFBFBFBFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 15 ; length of list_pids : 15 ; length of list_args : 15 time to download the photos : 2.8210136890411377 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 Sat Nov 29 14:10:31 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 : 10998 max_wait_temp : 1 max_wait : 0 gpu_flag : 0 2025-11-29 14:10:35.169647: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2025-11-29 14:10:35.202490: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493010000 Hz 2025-11-29 14:10:35.204536: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7fcd74000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-11-29 14:10:35.204582: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-11-29 14:10:35.209547: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-11-29 14:10:35.549481: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x20ec8590 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-11-29 14:10:35.549527: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-11-29 14:10:35.551336: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-11-29 14:10:35.553193: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-11-29 14:10:35.576301: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-11-29 14:10:35.594653: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-11-29 14:10:35.598296: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-11-29 14:10:35.629113: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-11-29 14:10:35.634003: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-11-29 14:10:35.687565: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-11-29 14:10:35.689324: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-11-29 14:10:35.689713: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-11-29 14:10:35.691413: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-11-29 14:10:35.691434: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-11-29 14:10:35.691444: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-11-29 14:10:35.693743: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 10193 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:41:00.0, compute capability: 7.5) WARNING:tensorflow:From /home/admin/workarea/git/Velours/python/mtr/mask_rcnn/mask_detection.py:69: The name tf.keras.backend.set_session is deprecated. Please use tf.compat.v1.keras.backend.set_session instead. 2025-11-29 14:10:36.059734: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-11-29 14:10:36.059844: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-11-29 14:10:36.059860: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-11-29 14:10:36.059874: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-11-29 14:10:36.059888: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-11-29 14:10:36.059901: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-11-29 14:10:36.059914: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-11-29 14:10:36.059928: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-11-29 14:10:36.061095: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-11-29 14:10:36.062297: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-11-29 14:10:36.062324: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-11-29 14:10:36.062338: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-11-29 14:10:36.062351: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-11-29 14:10:36.062364: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-11-29 14:10:36.062376: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-11-29 14:10:36.062389: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-11-29 14:10:36.062401: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-11-29 14:10:36.063552: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-11-29 14:10:36.063589: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-11-29 14:10:36.063597: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-11-29 14:10:36.063604: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-11-29 14:10:36.064806: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 10193 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:41:00.0, compute capability: 7.5) Using TensorFlow backend. WARNING:tensorflow:From /home/admin/workarea/install/Mask_RCNN/model.py:396: calling crop_and_resize_v1 (from tensorflow.python.ops.image_ops_impl) with box_ind is deprecated and will be removed in a future version. Instructions for updating: box_ind is deprecated, use box_indices instead WARNING:tensorflow:From /home/admin/workarea/install/Mask_RCNN/model.py:703: to_int32 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.cast` instead. WARNING:tensorflow:From /home/admin/workarea/install/Mask_RCNN/model.py:729: to_float (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.cast` instead. Inside mask_sub_process Inside mask_detect About to load cache.load_thcl_param To do loadFromThcl(), then load ParamDescType : thcl2847 thcls : [{'id': 2847, 'mtr_user_id': 31, 'name': 'learn_RUBBIA_REFUS_AMIENS_23', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'photo_desc_type': 5275, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'}] thcl {'id': 2847, 'mtr_user_id': 31, 'name': 'learn_RUBBIA_REFUS_AMIENS_23', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'photo_desc_type': 5275, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'} Update svm_hashtag_type_desc : 5275 FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (5275, 'learn_RUBBIA_REFUS_AMIENS_23', 16384, 25088, 'learn_RUBBIA_REFUS_AMIENS_23', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 1, datetime.datetime(2021, 4, 23, 14, 19, 39), datetime.datetime(2021, 4, 23, 14, 19, 39)) {'thcl': {'id': 2847, 'mtr_user_id': 31, 'name': 'learn_RUBBIA_REFUS_AMIENS_23', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'photo_desc_type': 5275, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'}, 'list_hashtags': ['background', 'papier', 'carton', 'metal', 'pet_clair', 'autre', 'pehd', 'pet_fonce', 'environnement'], 'list_hashtags_csv': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'svm_hashtag_type_desc': 5275, 'photo_desc_type': 5275, 'pb_hashtag_id_or_classifier': 0} list_class_names : ['background', 'papier', 'carton', 'metal', 'pet_clair', 'autre', 'pehd', 'pet_fonce', 'environnement'] Configurations: BACKBONE resnet101 BACKBONE_SHAPES [[160 160] [ 80 80] [ 40 40] [ 20 20] [ 10 10]] BACKBONE_STRIDES [4, 8, 16, 32, 64] BATCH_SIZE 1 BBOX_STD_DEV [0.1 0.1 0.2 0.2] DETECTION_MAX_INSTANCES 100 DETECTION_MIN_CONFIDENCE 0.3 DETECTION_NMS_THRESHOLD 0.3 GPU_COUNT 1 IMAGES_PER_GPU 1 IMAGE_MAX_DIM 640 IMAGE_MIN_DIM 640 IMAGE_PADDING True IMAGE_SHAPE [640 640 3] LEARNING_MOMENTUM 0.9 LEARNING_RATE 0.001 LOSS_WEIGHTS {'rpn_class_loss': 1.0, 'rpn_bbox_loss': 1.0, 'mrcnn_class_loss': 1.0, 'mrcnn_bbox_loss': 1.0, 'mrcnn_mask_loss': 1.0} MASK_POOL_SIZE 14 MASK_SHAPE [28, 28] MAX_GT_INSTANCES 100 MEAN_PIXEL [123.7 116.8 103.9] MINI_MASK_SHAPE (56, 56) NAME learn_RUBBIA_REFUS_AMIENS_23 NUM_CLASSES 9 POOL_SIZE 7 POST_NMS_ROIS_INFERENCE 1000 POST_NMS_ROIS_TRAINING 2000 ROI_POSITIVE_RATIO 0.33 RPN_ANCHOR_RATIOS [0.5, 1, 2] RPN_ANCHOR_SCALES (16, 32, 64, 128, 256) RPN_ANCHOR_STRIDE 1 RPN_BBOX_STD_DEV [0.1 0.1 0.2 0.2] RPN_NMS_THRESHOLD 0.7 RPN_TRAIN_ANCHORS_PER_IMAGE 256 STEPS_PER_EPOCH 1000 TRAIN_ROIS_PER_IMAGE 200 USE_MINI_MASK True USE_RPN_ROIS True VALIDATION_STEPS 50 WEIGHT_DECAY 0.0001 model_param file didn't exist model_name : learn_RUBBIA_REFUS_AMIENS_23 model_type : mask_rcnn list file need : ['mask_model.h5'] file exist in s3 : ['mask_model.h5'] file manque in s3 : [] 2025-11-29 14:10:48.915699: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-11-29 14:10:49.153108: 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 : 15 NEW PHOTO Processing 1 images image shape: (2160, 3840, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 3840.00000 nb d'objets trouves : 32 NEW PHOTO Processing 1 images image shape: (2160, 3840, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 3840.00000 nb d'objets trouves : 17 NEW PHOTO Processing 1 images image shape: (2160, 3840, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 3840.00000 nb d'objets trouves : 16 NEW PHOTO Processing 1 images image shape: (2160, 3840, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 3840.00000 nb d'objets trouves : 9 NEW PHOTO Processing 1 images image shape: (2160, 3840, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 3840.00000 nb d'objets trouves : 15 NEW PHOTO Processing 1 images image shape: (2160, 3840, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 3840.00000 nb d'objets trouves : 30 NEW PHOTO Processing 1 images image shape: (2160, 3840, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 3840.00000 nb d'objets trouves : 19 NEW PHOTO Processing 1 images image shape: (2160, 3840, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 3840.00000 nb d'objets trouves : 12 NEW PHOTO Processing 1 images image shape: (2160, 3840, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 3840.00000 nb d'objets trouves : 9 NEW PHOTO Processing 1 images image shape: (2160, 3840, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 3840.00000 nb d'objets trouves : 13 NEW PHOTO Processing 1 images image shape: (2160, 3840, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 3840.00000 nb d'objets trouves : 21 NEW PHOTO Processing 1 images image shape: (2160, 3840, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 3840.00000 nb d'objets trouves : 9 NEW PHOTO Processing 1 images image shape: (2160, 3840, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 3840.00000 nb d'objets trouves : 14 NEW PHOTO Processing 1 images image shape: (2160, 3840, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 3840.00000 nb d'objets trouves : 11 NEW PHOTO Processing 1 images image shape: (2160, 3840, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 3840.00000 nb d'objets trouves : 16 Detection mask done ! Trying to reset tf kernel 2505451 begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 5706 tf kernel not reseted sub process len(results) : 15 len(list_Values) 0 None max_time_sub_proc : 3600 parent process len(results) : 15 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 : 10998 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'] DEBUG bbox = [2064, 798, 2160, 1044] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0007073879241943359 nb_pixel_total : 15419 time to create 1 rle with old method : 0.021849870681762695 length of segment : 88 DEBUG bbox = [342, 1734, 960, 2622] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.009381532669067383 nb_pixel_total : 240216 time to create 1 rle with new method : 0.04677271842956543 length of segment : 639 DEBUG bbox = [2088, 1686, 2154, 1944] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.00032401084899902344 nb_pixel_total : 12462 time to create 1 rle with old method : 0.018084287643432617 length of segment : 66 DEBUG bbox = [810, 570, 1062, 960] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0013675689697265625 nb_pixel_total : 46343 time to create 1 rle with old method : 0.06290984153747559 length of segment : 258 DEBUG bbox = [6, 522, 318, 774] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.001371145248413086 nb_pixel_total : 51694 time to create 1 rle with old method : 0.06895184516906738 length of segment : 295 DEBUG bbox = [1104, 2436, 1512, 2880] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0023746490478515625 nb_pixel_total : 83118 time to create 1 rle with old method : 0.1117098331451416 length of segment : 410 DEBUG bbox = [618, 984, 834, 1152] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0006766319274902344 nb_pixel_total : 24869 time to create 1 rle with old method : 0.03760123252868652 length of segment : 212 DEBUG bbox = [12, 2352, 276, 2874] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0021314620971679688 nb_pixel_total : 87314 time to create 1 rle with old method : 0.1284008026123047 length of segment : 289 DEBUG bbox = [414, 1512, 534, 1614] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.00041103363037109375 nb_pixel_total : 8330 time to create 1 rle with old method : 0.012918233871459961 length of segment : 131 DEBUG bbox = [648, 1506, 1032, 2064] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.004067897796630859 nb_pixel_total : 108528 time to create 1 rle with old method : 0.15868663787841797 length of segment : 443 DEBUG bbox = [1794, 2316, 2118, 2622] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0014774799346923828 nb_pixel_total : 71570 time to create 1 rle with old method : 0.10080671310424805 length of segment : 324 DEBUG bbox = [1782, 1770, 2022, 2046] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0008492469787597656 nb_pixel_total : 35903 time to create 1 rle with old method : 0.05288839340209961 length of segment : 226 DEBUG bbox = [1122, 288, 1500, 534] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0010988712310791016 nb_pixel_total : 34555 time to create 1 rle with old method : 0.05006003379821777 length of segment : 313 DEBUG bbox = [210, 1848, 438, 1998] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0005464553833007812 nb_pixel_total : 25592 time to create 1 rle with old method : 0.03716731071472168 length of segment : 226 DEBUG bbox = [228, 1422, 660, 1650] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0013003349304199219 nb_pixel_total : 59683 time to create 1 rle with old method : 0.07782602310180664 length of segment : 524 DEBUG bbox = [132, 840, 306, 1098] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0005462169647216797 nb_pixel_total : 23651 time to create 1 rle with old method : 0.03272891044616699 length of segment : 144 DEBUG bbox = [732, 1554, 858, 1710] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0002942085266113281 nb_pixel_total : 13402 time to create 1 rle with old method : 0.0185086727142334 length of segment : 113 DEBUG bbox = [762, 150, 1044, 330] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0007047653198242188 nb_pixel_total : 26693 time to create 1 rle with old method : 0.035083770751953125 length of segment : 219 DEBUG bbox = [234, 630, 636, 864] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0011551380157470703 nb_pixel_total : 54415 time to create 1 rle with old method : 0.06420540809631348 length of segment : 363 DEBUG bbox = [90, 252, 852, 612] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.002713441848754883 nb_pixel_total : 154624 time to create 1 rle with new method : 0.010616540908813477 length of segment : 736 DEBUG bbox = [1092, 1860, 1344, 1956] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0003075599670410156 nb_pixel_total : 14132 time to create 1 rle with old method : 0.016048192977905273 length of segment : 226 DEBUG bbox = [1470, 1236, 1944, 1890] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0028209686279296875 nb_pixel_total : 142121 time to create 1 rle with old method : 0.15860986709594727 length of segment : 418 DEBUG bbox = [1410, 2316, 1734, 2562] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0007627010345458984 nb_pixel_total : 43802 time to create 1 rle with old method : 0.05227208137512207 length of segment : 297 DEBUG bbox = [1812, 1392, 1974, 1584] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.00029921531677246094 nb_pixel_total : 10762 time to create 1 rle with old method : 0.012818098068237305 length of segment : 142 DEBUG bbox = [72, 1614, 324, 1848] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0005452632904052734 nb_pixel_total : 39295 time to create 1 rle with old method : 0.04412484169006348 length of segment : 248 DEBUG bbox = [1662, 1830, 1764, 1944] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.00017261505126953125 nb_pixel_total : 8057 time to create 1 rle with old method : 0.00986933708190918 length of segment : 96 DEBUG bbox = [156, 402, 402, 540] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.00036597251892089844 nb_pixel_total : 20727 time to create 1 rle with old method : 0.0250551700592041 length of segment : 224 DEBUG bbox = [336, 840, 588, 1068] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0008161067962646484 nb_pixel_total : 31021 time to create 1 rle with old method : 0.04020500183105469 length of segment : 272 DEBUG bbox = [918, 114, 1068, 270] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0002799034118652344 nb_pixel_total : 16310 time to create 1 rle with old method : 0.01864790916442871 length of segment : 140 DEBUG bbox = [468, 480, 618, 660] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0003037452697753906 nb_pixel_total : 16351 time to create 1 rle with old method : 0.018393278121948242 length of segment : 201 DEBUG bbox = [822, 1098, 1026, 1290] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.00045228004455566406 nb_pixel_total : 29185 time to create 1 rle with old method : 0.03231382369995117 length of segment : 200 DEBUG bbox = [1128, 3090, 1542, 3300] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0009560585021972656 nb_pixel_total : 61890 time to create 1 rle with old method : 0.07444214820861816 length of segment : 374 DEBUG bbox = [36, 1722, 390, 2088] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0014846324920654297 nb_pixel_total : 92563 time to create 1 rle with old method : 0.10690760612487793 length of segment : 352 DEBUG bbox = [2034, 828, 2154, 1032] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0003781318664550781 nb_pixel_total : 13315 time to create 1 rle with old method : 0.015674829483032227 length of segment : 127 DEBUG bbox = [186, 864, 456, 1080] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0007965564727783203 nb_pixel_total : 31407 time to create 1 rle with old method : 0.04317593574523926 length of segment : 258 DEBUG bbox = [468, 1512, 654, 1794] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0013186931610107422 nb_pixel_total : 34621 time to create 1 rle with old method : 0.039992570877075195 length of segment : 170 DEBUG bbox = [1836, 1182, 2136, 1464] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0010988712310791016 nb_pixel_total : 54481 time to create 1 rle with old method : 0.05985379219055176 length of segment : 295 DEBUG bbox = [474, 2130, 684, 2304] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0009920597076416016 nb_pixel_total : 17949 time to create 1 rle with old method : 0.020978927612304688 length of segment : 198 DEBUG bbox = [2010, 984, 2142, 1224] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0003883838653564453 nb_pixel_total : 24722 time to create 1 rle with old method : 0.028368711471557617 length of segment : 128 DEBUG bbox = [864, 2310, 1080, 2526] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0005829334259033203 nb_pixel_total : 25077 time to create 1 rle with old method : 0.027770280838012695 length of segment : 187 DEBUG bbox = [990, 1098, 1278, 1374] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0008685588836669922 nb_pixel_total : 29263 time to create 1 rle with old method : 0.032679080963134766 length of segment : 227 DEBUG bbox = [1260, 960, 1476, 1122] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0004909038543701172 nb_pixel_total : 22198 time to create 1 rle with old method : 0.024296998977661133 length of segment : 205 DEBUG bbox = [432, 222, 660, 444] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0012235641479492188 nb_pixel_total : 32748 time to create 1 rle with old method : 0.036280155181884766 length of segment : 193 DEBUG bbox = [954, 696, 1134, 858] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0004220008850097656 nb_pixel_total : 21200 time to create 1 rle with old method : 0.02421283721923828 length of segment : 177 DEBUG bbox = [1134, 2124, 1290, 2316] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.000453948974609375 nb_pixel_total : 20240 time to create 1 rle with old method : 0.024622678756713867 length of segment : 155 DEBUG bbox = [1098, 1518, 1296, 1818] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0006115436553955078 nb_pixel_total : 23568 time to create 1 rle with old method : 0.027831077575683594 length of segment : 179 DEBUG bbox = [1926, 2334, 2136, 2526] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0004150867462158203 nb_pixel_total : 20594 time to create 1 rle with old method : 0.022946834564208984 length of segment : 209 DEBUG bbox = [1470, 2202, 1626, 2418] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.00033783912658691406 nb_pixel_total : 18292 time to create 1 rle with old method : 0.020253658294677734 length of segment : 141 DEBUG bbox = [1656, 1860, 1812, 1950] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.00019598007202148438 nb_pixel_total : 9666 time to create 1 rle with old method : 0.01094818115234375 length of segment : 134 DEBUG bbox = [132, 222, 480, 498] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0009276866912841797 nb_pixel_total : 53039 time to create 1 rle with old method : 0.05852150917053223 length of segment : 293 DEBUG bbox = [1800, 1848, 2028, 2076] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0005061626434326172 nb_pixel_total : 24200 time to create 1 rle with old method : 0.02736973762512207 length of segment : 203 DEBUG bbox = [1716, 2052, 1914, 2262] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.00039315223693847656 nb_pixel_total : 22298 time to create 1 rle with old method : 0.025253772735595703 length of segment : 184 DEBUG bbox = [258, 498, 492, 720] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0005502700805664062 nb_pixel_total : 33281 time to create 1 rle with old method : 0.036699533462524414 length of segment : 225 DEBUG bbox = [1638, 480, 2136, 888] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0018508434295654297 nb_pixel_total : 108823 time to create 1 rle with old method : 0.11866497993469238 length of segment : 483 DEBUG bbox = [138, 2712, 582, 3066] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.001634836196899414 nb_pixel_total : 103351 time to create 1 rle with old method : 0.11751079559326172 length of segment : 445 DEBUG bbox = [1674, 1728, 1830, 1878] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.00026726722717285156 nb_pixel_total : 13273 time to create 1 rle with old method : 0.01489567756652832 length of segment : 215 DEBUG bbox = [1218, 1740, 1590, 1890] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0006284713745117188 nb_pixel_total : 34660 time to create 1 rle with old method : 0.037464141845703125 length of segment : 348 DEBUG bbox = [60, 2964, 282, 3054] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0002422332763671875 nb_pixel_total : 12418 time to create 1 rle with old method : 0.013461589813232422 length of segment : 206 DEBUG bbox = [2052, 1806, 2160, 1998] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.00020813941955566406 nb_pixel_total : 12486 time to create 1 rle with old method : 0.014072895050048828 length of segment : 104 DEBUG bbox = [1032, 1842, 1434, 2388] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.001829385757446289 nb_pixel_total : 143458 time to create 1 rle with old method : 0.1554419994354248 length of segment : 398 DEBUG bbox = [504, 1728, 822, 1914] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0006172657012939453 nb_pixel_total : 42392 time to create 1 rle with old method : 0.04634666442871094 length of segment : 294 DEBUG bbox = [270, 540, 474, 780] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0004572868347167969 nb_pixel_total : 27549 time to create 1 rle with old method : 0.029924392700195312 length of segment : 204 DEBUG bbox = [1362, 276, 1716, 534] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0006597042083740234 nb_pixel_total : 26059 time to create 1 rle with old method : 0.029028892517089844 length of segment : 345 DEBUG bbox = [366, 2520, 540, 2808] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.000461578369140625 nb_pixel_total : 33013 time to create 1 rle with old method : 0.036012887954711914 length of segment : 167 DEBUG bbox = [312, 2664, 534, 2862] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0007219314575195312 nb_pixel_total : 27328 time to create 1 rle with old method : 0.029999256134033203 length of segment : 225 DEBUG bbox = [1506, 798, 2160, 1728] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.019930601119995117 nb_pixel_total : 392036 time to create 1 rle with new method : 0.022806406021118164 length of segment : 583 DEBUG bbox = [1632, 2220, 2004, 2526] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0015480518341064453 nb_pixel_total : 67607 time to create 1 rle with old method : 0.08959460258483887 length of segment : 370 DEBUG bbox = [30, 2052, 366, 2496] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0018935203552246094 nb_pixel_total : 84136 time to create 1 rle with old method : 0.09617900848388672 length of segment : 295 DEBUG bbox = [1398, 2094, 1926, 2538] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.002791881561279297 nb_pixel_total : 116264 time to create 1 rle with old method : 0.13643574714660645 length of segment : 464 DEBUG bbox = [444, 1626, 720, 1968] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.001115560531616211 nb_pixel_total : 31986 time to create 1 rle with old method : 0.03654789924621582 length of segment : 254 DEBUG bbox = [1842, 1278, 2046, 1614] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0008707046508789062 nb_pixel_total : 30660 time to create 1 rle with old method : 0.041199445724487305 length of segment : 200 DEBUG bbox = [1584, 1572, 1860, 1788] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0009827613830566406 nb_pixel_total : 36786 time to create 1 rle with old method : 0.043234825134277344 length of segment : 246 DEBUG bbox = [156, 2292, 360, 2442] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0006124973297119141 nb_pixel_total : 24388 time to create 1 rle with old method : 0.028683900833129883 length of segment : 195 DEBUG bbox = [2040, 516, 2148, 684] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.00039124488830566406 nb_pixel_total : 12856 time to create 1 rle with old method : 0.015474081039428711 length of segment : 103 DEBUG bbox = [36, 3210, 384, 3360] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0010044574737548828 nb_pixel_total : 33755 time to create 1 rle with old method : 0.049283504486083984 length of segment : 314 DEBUG bbox = [948, 618, 1476, 1014] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.004022121429443359 nb_pixel_total : 138075 time to create 1 rle with old method : 0.16897368431091309 length of segment : 561 DEBUG bbox = [18, 1986, 138, 2184] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0004417896270751953 nb_pixel_total : 12696 time to create 1 rle with old method : 0.015137910842895508 length of segment : 107 DEBUG bbox = [1512, 1698, 1674, 1908] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0006191730499267578 nb_pixel_total : 19334 time to create 1 rle with old method : 0.023087501525878906 length of segment : 142 DEBUG bbox = [1326, 954, 1512, 1320] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0009007453918457031 nb_pixel_total : 38758 time to create 1 rle with old method : 0.04576253890991211 length of segment : 157 DEBUG bbox = [1518, 462, 2058, 870] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.003387928009033203 nb_pixel_total : 141714 time to create 1 rle with old method : 0.19075918197631836 length of segment : 611 DEBUG bbox = [1764, 828, 1926, 984] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0003185272216796875 nb_pixel_total : 10746 time to create 1 rle with old method : 0.013180017471313477 length of segment : 114 DEBUG bbox = [1596, 1458, 1770, 1644] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0006334781646728516 nb_pixel_total : 17776 time to create 1 rle with old method : 0.021193504333496094 length of segment : 154 DEBUG bbox = [1542, 840, 1788, 936] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.00032401084899902344 nb_pixel_total : 14728 time to create 1 rle with old method : 0.017169713973999023 length of segment : 222 DEBUG bbox = [978, 1356, 1188, 1698] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.00113677978515625 nb_pixel_total : 42930 time to create 1 rle with old method : 0.050873756408691406 length of segment : 178 DEBUG bbox = [42, 2556, 456, 3318] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.002905607223510742 nb_pixel_total : 125414 time to create 1 rle with old method : 0.14705491065979004 length of segment : 342 DEBUG bbox = [1716, 2016, 1968, 2196] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.000732421875 nb_pixel_total : 26953 time to create 1 rle with old method : 0.03176474571228027 length of segment : 245 DEBUG bbox = [210, 3288, 420, 3432] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0003604888916015625 nb_pixel_total : 21772 time to create 1 rle with old method : 0.02825164794921875 length of segment : 209 DEBUG bbox = [1860, 456, 2094, 600] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0005817413330078125 nb_pixel_total : 19168 time to create 1 rle with old method : 0.02254509925842285 length of segment : 231 DEBUG bbox = [918, 54, 1320, 636] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0030672550201416016 nb_pixel_total : 142272 time to create 1 rle with old method : 0.16471314430236816 length of segment : 373 DEBUG bbox = [354, 738, 672, 1086] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0019826889038085938 nb_pixel_total : 68201 time to create 1 rle with old method : 0.09027242660522461 length of segment : 314 DEBUG bbox = [636, 2952, 834, 3096] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0005464553833007812 nb_pixel_total : 17826 time to create 1 rle with old method : 0.020993709564208984 length of segment : 184 DEBUG bbox = [576, 3174, 936, 3288] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0007195472717285156 nb_pixel_total : 24380 time to create 1 rle with old method : 0.028537511825561523 length of segment : 346 DEBUG bbox = [444, 324, 810, 744] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0019600391387939453 nb_pixel_total : 105266 time to create 1 rle with old method : 0.12612557411193848 length of segment : 341 DEBUG bbox = [90, 1062, 300, 1344] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0009341239929199219 nb_pixel_total : 33592 time to create 1 rle with old method : 0.04004263877868652 length of segment : 200 DEBUG bbox = [330, 1686, 666, 2046] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0016694068908691406 nb_pixel_total : 62877 time to create 1 rle with old method : 0.07440638542175293 length of segment : 305 DEBUG bbox = [60, 1152, 510, 1590] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0027320384979248047 nb_pixel_total : 129610 time to create 1 rle with old method : 0.15220999717712402 length of segment : 487 DEBUG bbox = [1794, 1386, 2082, 1836] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0016841888427734375 nb_pixel_total : 86058 time to create 1 rle with old method : 0.10092997550964355 length of segment : 264 DEBUG bbox = [816, 2352, 1086, 2670] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.001102447509765625 nb_pixel_total : 34425 time to create 1 rle with old method : 0.041114091873168945 length of segment : 232 DEBUG bbox = [1446, 1386, 1842, 1986] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0023093223571777344 nb_pixel_total : 76721 time to create 1 rle with old method : 0.0873408317565918 length of segment : 400 DEBUG bbox = [360, 1530, 576, 1752] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0008690357208251953 nb_pixel_total : 32030 time to create 1 rle with old method : 0.03708767890930176 length of segment : 199 DEBUG bbox = [966, 1572, 1392, 1836] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0016891956329345703 nb_pixel_total : 77928 time to create 1 rle with old method : 0.08952045440673828 length of segment : 407 DEBUG bbox = [786, 786, 996, 1020] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0006234645843505859 nb_pixel_total : 30605 time to create 1 rle with old method : 0.03570723533630371 length of segment : 177 DEBUG bbox = [534, 1254, 918, 1542] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0017406940460205078 nb_pixel_total : 38207 time to create 1 rle with old method : 0.0447392463684082 length of segment : 355 DEBUG bbox = [252, 1746, 492, 1872] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0006489753723144531 nb_pixel_total : 19338 time to create 1 rle with old method : 0.022739887237548828 length of segment : 232 DEBUG bbox = [1452, 2220, 1650, 2466] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0007979869842529297 nb_pixel_total : 27034 time to create 1 rle with old method : 0.03162956237792969 length of segment : 169 DEBUG bbox = [1266, 1140, 1488, 1536] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.001132965087890625 nb_pixel_total : 49050 time to create 1 rle with old method : 0.05673694610595703 length of segment : 225 DEBUG bbox = [102, 546, 462, 756] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.00092315673828125 nb_pixel_total : 36552 time to create 1 rle with old method : 0.04199552536010742 length of segment : 328 DEBUG bbox = [288, 252, 690, 636] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.002134084701538086 nb_pixel_total : 80110 time to create 1 rle with old method : 0.09223437309265137 length of segment : 393 DEBUG bbox = [864, 2688, 1026, 2838] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0005083084106445312 nb_pixel_total : 11588 time to create 1 rle with old method : 0.013683795928955078 length of segment : 133 DEBUG bbox = [294, 720, 858, 1320] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0040891170501708984 nb_pixel_total : 163140 time to create 1 rle with new method : 0.009957075119018555 length of segment : 659 DEBUG bbox = [912, 2334, 1482, 2676] DEBUG masks shape = (2160, 3840) time for calcul the mask position with numpy : 0.0025076866149902344 nb_pixel_total : 103621 time to create 1 rle with old method : 0.11671686172485352 length of segment : 677 time spent for convertir_results : 10.274353742599487 Inside saveOutput : final : False verbose : 0 eke 12-6-18 : saveMask need to be cleaned for new output ! Number saved : None batch 1 Loaded 111 chid ids of type : 3594 Number RLEs to save : 30228 save missing photos in datou_result : time spend for datou_step_exec : 74.64047026634216 time spend to save output : 1.8464789390563965 total time spend for step 1 : 76.48694920539856 step2:crop_condition Sat Nov 29 14:11:47 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 : 15 ! batch 1 Loaded 111 chid ids of type : 3594 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ begin to crop the class : papier param for this class : {'min_score': 0.7} filtre for class : papier hashtag_id of this class : 492668766 we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! 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 : 51 About to insert : list_path_to_insert length 51 new photo from crops ! About to upload 51 photos upload in portfolio : 3736932 init cache_photo without model_param we have 51 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1764421921_2504845 INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396887253_319c20b3f68ed3ac5c5d57322f12f3b6_rle_crop_4051472263_0.png', 0, 833, 581, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396887253_319c20b3f68ed3ac5c5d57322f12f3b6_rle_crop_4051472265_0.png', 0, 333, 231, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396887253_319c20b3f68ed3ac5c5d57322f12f3b6_rle_crop_4051472266_0.png', 0, 247, 293, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396887253_319c20b3f68ed3ac5c5d57322f12f3b6_rle_crop_4051472271_0.png', 0, 536, 329, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396887216_13442020c36ad543571c40c26406f573_rle_crop_4051472274_0.png', 0, 227, 313, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396887216_13442020c36ad543571c40c26406f573_rle_crop_4051472276_0.png', 0, 218, 399, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886679_01a7e52f3f2dc1e8d8565ba7aef84c92_rle_crop_4051472280_0.png', 0, 206, 362, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886679_01a7e52f3f2dc1e8d8565ba7aef84c92_rle_crop_4051472281_0.png', 0, 354, 731, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886679_01a7e52f3f2dc1e8d8565ba7aef84c92_rle_crop_4051472282_0.png', 0, 92, 226, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886679_01a7e52f3f2dc1e8d8565ba7aef84c92_rle_crop_4051472284_0.png', 0, 235, 285, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886679_01a7e52f3f2dc1e8d8565ba7aef84c92_rle_crop_4051472285_0.png', 0, 189, 142, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886506_e6e2a9fdf17083ebf64c5988daf9afdd_rle_crop_4051472295_0.png', 0, 179, 115, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886506_e6e2a9fdf17083ebf64c5988daf9afdd_rle_crop_4051472296_0.png', 0, 205, 256, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886506_e6e2a9fdf17083ebf64c5988daf9afdd_rle_crop_4051472298_0.png', 0, 254, 295, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886506_e6e2a9fdf17083ebf64c5988daf9afdd_rle_crop_4051472299_0.png', 0, 165, 198, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886506_e6e2a9fdf17083ebf64c5988daf9afdd_rle_crop_4051472302_0.png', 0, 225, 227, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886506_e6e2a9fdf17083ebf64c5988daf9afdd_rle_crop_4051472303_0.png', 0, 160, 196, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886496_cf2c7cb169eb3bda3db7e1165b9c81f1_rle_crop_4051472307_0.png', 0, 275, 179, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886496_cf2c7cb169eb3bda3db7e1165b9c81f1_rle_crop_4051472308_0.png', 0, 189, 203, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886496_cf2c7cb169eb3bda3db7e1165b9c81f1_rle_crop_4051472309_0.png', 0, 188, 141, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886496_cf2c7cb169eb3bda3db7e1165b9c81f1_rle_crop_4051472310_0.png', 0, 87, 134, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886496_cf2c7cb169eb3bda3db7e1165b9c81f1_rle_crop_4051472312_0.png', 0, 211, 203, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886496_cf2c7cb169eb3bda3db7e1165b9c81f1_rle_crop_4051472313_0.png', 0, 193, 168, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886496_cf2c7cb169eb3bda3db7e1165b9c81f1_rle_crop_4051472316_0.png', 0, 340, 423, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886496_cf2c7cb169eb3bda3db7e1165b9c81f1_rle_crop_4051472317_0.png', 0, 142, 127, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886493_1aa2f7624d70d7916919ec5d6246b3b3_rle_crop_4051472320_0.png', 0, 179, 102, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886455_bcc7e3d5e222518fb3c15b6accbafae3_rle_crop_4051472331_0.png', 0, 273, 220, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886455_bcc7e3d5e222518fb3c15b6accbafae3_rle_crop_4051472332_0.png', 0, 289, 187, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886455_bcc7e3d5e222518fb3c15b6accbafae3_rle_crop_4051472333_0.png', 0, 198, 235, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886451_3f43b3b48fcbaca48248f71e2fe9ae79_rle_crop_4051472334_0.png', 0, 149, 192, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886451_3f43b3b48fcbaca48248f71e2fe9ae79_rle_crop_4051472335_0.png', 0, 164, 102, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886451_3f43b3b48fcbaca48248f71e2fe9ae79_rle_crop_4051472339_0.png', 0, 208, 124, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886451_3f43b3b48fcbaca48248f71e2fe9ae79_rle_crop_4051472342_0.png', 0, 151, 113, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886451_3f43b3b48fcbaca48248f71e2fe9ae79_rle_crop_4051472343_0.png', 0, 169, 152, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886451_3f43b3b48fcbaca48248f71e2fe9ae79_rle_crop_4051472344_0.png', 0, 82, 220, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886449_365bbd2b9360cdb47ef87e4e66c16da5_rle_crop_4051472346_0.png', 0, 682, 291, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886449_365bbd2b9360cdb47ef87e4e66c16da5_rle_crop_4051472347_0.png', 0, 179, 245, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886447_18b717fe2f2f229dcdc404ac9fb0b385_rle_crop_4051472350_0.png', 0, 564, 373, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886447_18b717fe2f2f229dcdc404ac9fb0b385_rle_crop_4051472353_0.png', 0, 103, 345, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886447_18b717fe2f2f229dcdc404ac9fb0b385_rle_crop_4051472354_0.png', 0, 381, 341, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886447_18b717fe2f2f229dcdc404ac9fb0b385_rle_crop_4051472355_0.png', 0, 263, 175, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886444_710ef9ec690bc2cdfd5945207d5bd3b9_rle_crop_4051472357_0.png', 0, 403, 438, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886444_710ef9ec690bc2cdfd5945207d5bd3b9_rle_crop_4051472358_0.png', 0, 399, 262, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886444_710ef9ec690bc2cdfd5945207d5bd3b9_rle_crop_4051472360_0.png', 0, 563, 277, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886437_b0138e5dcaed7ea8004e9600a670911d_rle_crop_4051472361_0.png', 0, 218, 199, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886437_b0138e5dcaed7ea8004e9600a670911d_rle_crop_4051472364_0.png', 0, 271, 355, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886437_b0138e5dcaed7ea8004e9600a670911d_rle_crop_4051472365_0.png', 0, 124, 232, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886437_b0138e5dcaed7ea8004e9600a670911d_rle_crop_4051472367_0.png', 0, 358, 194, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886437_b0138e5dcaed7ea8004e9600a670911d_rle_crop_4051472368_0.png', 0, 180, 328, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886437_b0138e5dcaed7ea8004e9600a670911d_rle_crop_4051472371_0.png', 0, 566, 503, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421931), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886437_b0138e5dcaed7ea8004e9600a670911d_rle_crop_4051472372_0.png', 0, 281, 529, 0, 1764421931,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 51 photos in the portfolio 3736932 time of upload the photos Elapsed time : 11.740746974945068 we have finished the crop for the class : papier begin to crop the class : carton param for this class : {'min_score': 0.7} filtre for class : carton hashtag_id of this class : 492774966 we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! 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 : 19 About to insert : list_path_to_insert length 19 new photo from crops ! About to upload 19 photos upload in portfolio : 3736932 init cache_photo without model_param we have 19 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1764421937_2504845 INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421941), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396887253_319c20b3f68ed3ac5c5d57322f12f3b6_rle_crop_4051472264_0.png', 0, 244, 66, 0, 1764421941,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421941), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396887253_319c20b3f68ed3ac5c5d57322f12f3b6_rle_crop_4051472268_0.png', 0, 163, 212, 0, 1764421941,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421941), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396887216_13442020c36ad543571c40c26406f573_rle_crop_4051472277_0.png', 0, 224, 132, 0, 1764421941,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421941), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886679_01a7e52f3f2dc1e8d8565ba7aef84c92_rle_crop_4051472279_0.png', 0, 159, 218, 0, 1764421941,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421941), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886621_7783b24967ef9c8af3dbf2a21075d826_rle_crop_4051472286_0.png', 0, 214, 242, 0, 1764421941,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421941), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886621_7783b24967ef9c8af3dbf2a21075d826_rle_crop_4051472288_0.png', 0, 119, 224, 0, 1764421941,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421941), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886562_8154b66f5fb7cec60058db0a52cc232f_rle_crop_4051472289_0.png', 0, 210, 237, 0, 1764421941,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421941), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886562_8154b66f5fb7cec60058db0a52cc232f_rle_crop_4051472291_0.png', 0, 163, 138, 0, 1764421941,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421941), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886506_e6e2a9fdf17083ebf64c5988daf9afdd_rle_crop_4051472297_0.png', 0, 247, 168, 0, 1764421941,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421941), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886506_e6e2a9fdf17083ebf64c5988daf9afdd_rle_crop_4051472301_0.png', 0, 184, 187, 0, 1764421941,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421941), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886493_1aa2f7624d70d7916919ec5d6246b3b3_rle_crop_4051472319_0.png', 0, 79, 205, 0, 1764421941,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421941), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886493_1aa2f7624d70d7916919ec5d6246b3b3_rle_crop_4051472323_0.png', 0, 235, 167, 0, 1764421941,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421941), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886493_1aa2f7624d70d7916919ec5d6246b3b3_rle_crop_4051472325_0.png', 0, 284, 164, 0, 1764421941,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421941), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886458_d3691afd5540ab54c783df5d05669d24_rle_crop_4051472326_0.png', 0, 184, 213, 0, 1764421941,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421941), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886447_18b717fe2f2f229dcdc404ac9fb0b385_rle_crop_4051472352_0.png', 0, 133, 184, 0, 1764421941,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421941), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886444_710ef9ec690bc2cdfd5945207d5bd3b9_rle_crop_4051472359_0.png', 0, 255, 232, 0, 1764421941,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421941), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886437_b0138e5dcaed7ea8004e9600a670911d_rle_crop_4051472363_0.png', 0, 221, 177, 0, 1764421941,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421941), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886437_b0138e5dcaed7ea8004e9600a670911d_rle_crop_4051472369_0.png', 0, 330, 393, 0, 1764421941,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421941), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886437_b0138e5dcaed7ea8004e9600a670911d_rle_crop_4051472370_0.png', 0, 138, 132, 0, 1764421941,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 19 photos in the portfolio 3736932 time of upload the photos Elapsed time : 5.01481032371521 we have finished the crop for the class : carton begin to crop the class : metal param for this class : {'min_score': 0.7} filtre for class : metal hashtag_id of this class : 492628673 we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! map_result returned by crop_photo_return_map_crop : length : 7 About to insert : list_path_to_insert length 7 new photo from crops ! About to upload 7 photos upload in portfolio : 3736932 init cache_photo without model_param we have 7 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1764421945_2504845 INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421946), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396887253_319c20b3f68ed3ac5c5d57322f12f3b6_rle_crop_4051472262_0.png', 0, 225, 88, 0, 1764421946,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421946), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396887253_319c20b3f68ed3ac5c5d57322f12f3b6_rle_crop_4051472270_0.png', 0, 91, 118, 0, 1764421946,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421946), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886679_01a7e52f3f2dc1e8d8565ba7aef84c92_rle_crop_4051472278_0.png', 0, 141, 113, 0, 1764421946,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421946), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886562_8154b66f5fb7cec60058db0a52cc232f_rle_crop_4051472290_0.png', 0, 144, 138, 0, 1764421946,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421946), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886562_8154b66f5fb7cec60058db0a52cc232f_rle_crop_4051472292_0.png', 0, 171, 198, 0, 1764421946,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421946), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886506_e6e2a9fdf17083ebf64c5988daf9afdd_rle_crop_4051472306_0.png', 0, 171, 155, 0, 1764421946,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421946), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886451_3f43b3b48fcbaca48248f71e2fe9ae79_rle_crop_4051472345_0.png', 0, 331, 161, 0, 1764421946,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 7 photos in the portfolio 3736932 time of upload the photos Elapsed time : 1.7102782726287842 we have finished the crop for the class : metal begin to crop the class : pet_clair param for this class : {'min_score': 0.7} filtre for class : pet_clair hashtag_id of this class : 2107755846 we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! 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 : 28 About to insert : list_path_to_insert length 28 new photo from crops ! About to upload 28 photos upload in portfolio : 3736932 init cache_photo without model_param we have 28 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1764421958_2504845 INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421964), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396887253_319c20b3f68ed3ac5c5d57322f12f3b6_rle_crop_4051472267_0.png', 0, 385, 358, 0, 1764421964,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421964), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396887253_319c20b3f68ed3ac5c5d57322f12f3b6_rle_crop_4051472269_0.png', 0, 457, 246, 0, 1764421964,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421964), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396887216_13442020c36ad543571c40c26406f573_rle_crop_4051472272_0.png', 0, 292, 324, 0, 1764421964,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421964), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396887216_13442020c36ad543571c40c26406f573_rle_crop_4051472275_0.png', 0, 148, 225, 0, 1764421964,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421964), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886562_8154b66f5fb7cec60058db0a52cc232f_rle_crop_4051472293_0.png', 0, 197, 370, 0, 1764421964,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421964), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886562_8154b66f5fb7cec60058db0a52cc232f_rle_crop_4051472294_0.png', 0, 363, 350, 0, 1764421964,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421964), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886506_e6e2a9fdf17083ebf64c5988daf9afdd_rle_crop_4051472300_0.png', 0, 236, 124, 0, 1764421964,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421964), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886506_e6e2a9fdf17083ebf64c5988daf9afdd_rle_crop_4051472304_0.png', 0, 211, 193, 0, 1764421964,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421964), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886496_cf2c7cb169eb3bda3db7e1165b9c81f1_rle_crop_4051472311_0.png', 0, 260, 283, 0, 1764421964,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421964), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886496_cf2c7cb169eb3bda3db7e1165b9c81f1_rle_crop_4051472314_0.png', 0, 190, 222, 0, 1764421964,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421964), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886496_cf2c7cb169eb3bda3db7e1165b9c81f1_rle_crop_4051472315_0.png', 0, 360, 459, 0, 1764421964,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421964), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886493_1aa2f7624d70d7916919ec5d6246b3b3_rle_crop_4051472321_0.png', 0, 496, 377, 0, 1764421964,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421964), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886493_1aa2f7624d70d7916919ec5d6246b3b3_rle_crop_4051472322_0.png', 0, 164, 294, 0, 1764421964,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421964), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886493_1aa2f7624d70d7916919ec5d6246b3b3_rle_crop_4051472324_0.png', 0, 213, 317, 0, 1764421964,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421964), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886458_d3691afd5540ab54c783df5d05669d24_rle_crop_4051472327_0.png', 0, 849, 582, 0, 1764421964,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421964), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886458_d3691afd5540ab54c783df5d05669d24_rle_crop_4051472328_0.png', 0, 266, 360, 0, 1764421964,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421964), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886455_bcc7e3d5e222518fb3c15b6accbafae3_rle_crop_4051472329_0.png', 0, 426, 258, 0, 1764421964,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421964), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886455_bcc7e3d5e222518fb3c15b6accbafae3_rle_crop_4051472330_0.png', 0, 405, 464, 0, 1764421964,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421964), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886451_3f43b3b48fcbaca48248f71e2fe9ae79_rle_crop_4051472336_0.png', 0, 137, 310, 0, 1764421964,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421964), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886451_3f43b3b48fcbaca48248f71e2fe9ae79_rle_crop_4051472337_0.png', 0, 357, 495, 0, 1764421964,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421964), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886451_3f43b3b48fcbaca48248f71e2fe9ae79_rle_crop_4051472338_0.png', 0, 182, 97, 0, 1764421964,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421964), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886451_3f43b3b48fcbaca48248f71e2fe9ae79_rle_crop_4051472340_0.png', 0, 347, 148, 0, 1764421964,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421964), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886451_3f43b3b48fcbaca48248f71e2fe9ae79_rle_crop_4051472341_0.png', 0, 378, 502, 0, 1764421964,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421964), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886449_365bbd2b9360cdb47ef87e4e66c16da5_rle_crop_4051472348_0.png', 0, 130, 209, 0, 1764421964,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421964), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886449_365bbd2b9360cdb47ef87e4e66c16da5_rle_crop_4051472349_0.png', 0, 108, 231, 0, 1764421964,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421964), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886447_18b717fe2f2f229dcdc404ac9fb0b385_rle_crop_4051472351_0.png', 0, 295, 314, 0, 1764421964,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421964), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886447_18b717fe2f2f229dcdc404ac9fb0b385_rle_crop_4051472356_0.png', 0, 338, 303, 0, 1764421964,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421964), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886437_b0138e5dcaed7ea8004e9600a670911d_rle_crop_4051472362_0.png', 0, 251, 395, 0, 1764421964,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 28 photos in the portfolio 3736932 time of upload the photos Elapsed time : 6.905304431915283 we have finished the crop for the class : pet_clair begin to crop the class : autre param for this class : {'min_score': 0.7} filtre for class : autre hashtag_id of this class : 494826614 we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! map_result returned by crop_photo_return_map_crop : length : 4 About to insert : list_path_to_insert length 4 new photo from crops ! About to upload 4 photos upload in portfolio : 3736932 init cache_photo without model_param we have 4 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1764421968_2504845 INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421969), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886621_7783b24967ef9c8af3dbf2a21075d826_rle_crop_4051472287_0.png', 0, 108, 95, 0, 1764421969,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421969), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886506_e6e2a9fdf17083ebf64c5988daf9afdd_rle_crop_4051472305_0.png', 0, 156, 177, 0, 1764421969,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421969), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886496_cf2c7cb169eb3bda3db7e1165b9c81f1_rle_crop_4051472318_0.png', 0, 136, 348, 0, 1764421969,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421969), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886437_b0138e5dcaed7ea8004e9600a670911d_rle_crop_4051472366_0.png', 0, 237, 168, 0, 1764421969,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 4 photos in the portfolio 3736932 time of upload the photos Elapsed time : 1.3740510940551758 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 ! we have both polygon and rles Next one ! map_result returned by crop_photo_return_map_crop : length : 2 About to insert : list_path_to_insert length 2 new photo from crops ! About to upload 2 photos upload in portfolio : 3736932 init cache_photo without model_param we have 2 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1764421972_2504845 INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421972), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396887216_13442020c36ad543571c40c26406f573_rle_crop_4051472273_0.png', 0, 244, 222, 0, 1764421972,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1764421972), 0.0, 0.0, 14, '', 0, 0, '1764421828_2504845_1396886679_01a7e52f3f2dc1e8d8565ba7aef84c92_rle_crop_4051472283_0.png', 0, 551, 391, 0, 1764421972,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 2 photos in the portfolio 3736932 time of upload the photos Elapsed time : 0.9306752681732178 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 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 [1396887253, 1396887216, 1396886679, 1396886621, 1396886562, 1396886506, 1396886496, 1396886493, 1396886458, 1396886455, 1396886451, 1396886449, 1396886447, 1396886444, 1396886437] Looping around the photos to save general results len do output : 111 /1396897937Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897938Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897939Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897940Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897941Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897942Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897943Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897944Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897945Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897946Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897947Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897948Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897949Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897950Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897951Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897952Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897953Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897954Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897955Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897956Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897957Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897958Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897959Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897960Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897961Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897962Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897963Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897964Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897965Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897966Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897967Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897968Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897969Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897970Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897971Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897972Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897973Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897974Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897975Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897977Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897978Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897979Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897980Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897981Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897982Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897983Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897984Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897985Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897986Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897987Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897988Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897992Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897993Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897994Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897995Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897996Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897997Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897998Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396897999Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396898000Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396898001Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396898002Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396898003Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396898004Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396898005Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396898006Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396898007Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396898008Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396898009Didn't retrieve data .Didn't retrieve 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/1396898078Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396898079Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396898080Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1396898081Didn'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, '4141163') ('3318', '29024015', '1396887253', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396887216', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886679', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886621', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886562', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886506', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886496', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886493', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886458', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886455', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886451', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886449', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886447', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886444', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886437', None, None, None, None, None, '4141163') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 348 time used for this insertion : 0.04150962829589844 save_final save missing photos in datou_result : time spend for datou_step_exec : 64.85182666778564 time spend to save output : 0.04534173011779785 total time spend for step 2 : 64.89716839790344 step3:rle_unique_nms_with_priority Sat Nov 29 14:12:52 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 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 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 111 chid ids of type : 3594 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++nb_obj : 10 nb_hashtags : 4 time to prepare the origin masks : 3.7198100090026855 time for calcul the mask position with numpy : 0.6014702320098877 nb_pixel_total : 7617007 time to create 1 rle with new method : 0.7245035171508789 time for calcul the mask position with numpy : 0.024512290954589844 nb_pixel_total : 107628 time to create 1 rle with old method : 0.13036251068115234 time for calcul the mask position with numpy : 0.027040719985961914 nb_pixel_total : 8330 time to create 1 rle with old method : 0.013892412185668945 time for calcul the mask position with numpy : 0.030218839645385742 nb_pixel_total : 87314 time to create 1 rle with old method : 0.09610772132873535 time for calcul the mask position with numpy : 0.025331497192382812 nb_pixel_total : 24869 time to create 1 rle with old method : 0.041179656982421875 time for calcul the mask position with numpy : 0.02836751937866211 nb_pixel_total : 83118 time to create 1 rle with old method : 0.09971022605895996 time for calcul the mask position with numpy : 0.027350187301635742 nb_pixel_total : 51694 time to create 1 rle with old method : 0.06223773956298828 time for calcul the mask position with numpy : 0.027554035186767578 nb_pixel_total : 46343 time to create 1 rle with old method : 0.058150291442871094 time for calcul the mask position with numpy : 0.026456594467163086 nb_pixel_total : 12462 time to create 1 rle with old method : 0.015360832214355469 time for calcul the mask position with numpy : 0.030254364013671875 nb_pixel_total : 240216 time to create 1 rle with new method : 0.6122674942016602 time for calcul the mask position with numpy : 0.024294376373291016 nb_pixel_total : 15419 time to create 1 rle with old method : 0.01709437370300293 create new chi : 2.803523302078247 time to delete rle : 0.021722078323364258 batch 1 Loaded 21 chid ids of type : 3594 ++++++++++++Number RLEs to save : 7735 TO DO : save crop sub photo not yet done ! save time : 0.49460864067077637 nb_obj : 6 nb_hashtags : 4 time to prepare the origin masks : 2.4100894927978516 time for calcul the mask position with numpy : 0.3514101505279541 nb_pixel_total : 8043446 time to create 1 rle with new method : 0.763390302658081 time for calcul the mask position with numpy : 0.024959325790405273 nb_pixel_total : 23651 time to create 1 rle with old method : 0.0280001163482666 time for calcul the mask position with numpy : 0.023967981338500977 nb_pixel_total : 59683 time to create 1 rle with old method : 0.0680382251739502 time for calcul the mask position with numpy : 0.02535557746887207 nb_pixel_total : 25592 time to create 1 rle with old method : 0.03217768669128418 time for calcul the mask position with numpy : 0.024843215942382812 nb_pixel_total : 34555 time to create 1 rle with old method : 0.03825807571411133 time for calcul the mask position with numpy : 0.023082494735717773 nb_pixel_total : 35903 time to create 1 rle with old method : 0.039055585861206055 time for calcul the mask position with numpy : 0.024143457412719727 nb_pixel_total : 71570 time to create 1 rle with old method : 0.07927584648132324 create new chi : 1.5883893966674805 time to delete rle : 0.0006651878356933594 batch 1 Loaded 13 chid ids of type : 3594 ++++++++Number RLEs to save : 5674 TO DO : save crop sub photo not yet done ! save time : 0.3815581798553467 nb_obj : 8 nb_hashtags : 4 time to prepare the origin masks : 3.2097275257110596 time for calcul the mask position with numpy : 0.3908722400665283 nb_pixel_total : 7838662 time to create 1 rle with new method : 0.9560062885284424 time for calcul the mask position with numpy : 0.023395299911499023 nb_pixel_total : 6549 time to create 1 rle with old method : 0.007579326629638672 time for calcul the mask position with numpy : 0.03999686241149902 nb_pixel_total : 43802 time to create 1 rle with old method : 0.04824090003967285 time for calcul the mask position with numpy : 0.039249420166015625 nb_pixel_total : 142121 time to create 1 rle with old method : 0.1600806713104248 time for calcul the mask position with numpy : 0.02693915367126465 nb_pixel_total : 14132 time to create 1 rle with old method : 0.016541242599487305 time for calcul the mask position with numpy : 0.02515864372253418 nb_pixel_total : 154624 time to create 1 rle with new method : 0.6896426677703857 time for calcul the mask position with numpy : 0.025066614151000977 nb_pixel_total : 54415 time to create 1 rle with old method : 0.060425758361816406 time for calcul the mask position with numpy : 0.02352285385131836 nb_pixel_total : 26693 time to create 1 rle with old method : 0.029097318649291992 time for calcul the mask position with numpy : 0.023128986358642578 nb_pixel_total : 13402 time to create 1 rle with old method : 0.014947891235351562 create new chi : 2.6674938201904297 time to delete rle : 0.0010457038879394531 batch 1 Loaded 17 chid ids of type : 3594 ++++++++Number RLEs to save : 7101 TO DO : save crop sub photo not yet done ! save time : 0.4845600128173828 nb_obj : 3 nb_hashtags : 2 time to prepare the origin masks : 1.4471280574798584 time for calcul the mask position with numpy : 0.5240249633789062 nb_pixel_total : 8226321 time to create 1 rle with new method : 0.72515869140625 time for calcul the mask position with numpy : 0.022516489028930664 nb_pixel_total : 20727 time to create 1 rle with old method : 0.022273778915405273 time for calcul the mask position with numpy : 0.029155492782592773 nb_pixel_total : 8057 time to create 1 rle with old method : 0.008787393569946289 time for calcul the mask position with numpy : 0.03809952735900879 nb_pixel_total : 39295 time to create 1 rle with old method : 0.042294979095458984 create new chi : 1.4512882232666016 time to delete rle : 0.0005404949188232422 batch 1 Loaded 7 chid ids of type : 3594 +++Number RLEs to save : 3296 TO DO : save crop sub photo not yet done ! save time : 0.24449729919433594 nb_obj : 6 nb_hashtags : 3 time to prepare the origin masks : 2.0580074787139893 time for calcul the mask position with numpy : 0.46887755393981934 nb_pixel_total : 8047080 time to create 1 rle with new method : 0.6823036670684814 time for calcul the mask position with numpy : 0.022897958755493164 nb_pixel_total : 92563 time to create 1 rle with old method : 0.10452699661254883 time for calcul the mask position with numpy : 0.022965669631958008 nb_pixel_total : 61890 time to create 1 rle with old method : 0.0699307918548584 time for calcul the mask position with numpy : 0.023593664169311523 nb_pixel_total : 29185 time to create 1 rle with old method : 0.03225302696228027 time for calcul the mask position with numpy : 0.022951126098632812 nb_pixel_total : 16351 time to create 1 rle with old method : 0.01779317855834961 time for calcul the mask position with numpy : 0.024096250534057617 nb_pixel_total : 16310 time to create 1 rle with old method : 0.018163204193115234 time for calcul the mask position with numpy : 0.02397942543029785 nb_pixel_total : 31021 time to create 1 rle with old method : 0.034284114837646484 create new chi : 1.608306646347046 time to delete rle : 0.0008521080017089844 batch 1 Loaded 13 chid ids of type : 3594 +++++++Number RLEs to save : 5238 TO DO : save crop sub photo not yet done ! save time : 0.36200928688049316 nb_obj : 12 nb_hashtags : 5 time to prepare the origin masks : 4.047535181045532 time for calcul the mask position with numpy : 0.6024489402770996 nb_pixel_total : 7967179 time to create 1 rle with new method : 1.471635103225708 time for calcul the mask position with numpy : 0.040596961975097656 nb_pixel_total : 20240 time to create 1 rle with old method : 0.02269434928894043 time for calcul the mask position with numpy : 0.04001212120056152 nb_pixel_total : 21200 time to create 1 rle with old method : 0.024170637130737305 time for calcul the mask position with numpy : 0.023964405059814453 nb_pixel_total : 32748 time to create 1 rle with old method : 0.035552024841308594 time for calcul the mask position with numpy : 0.09966707229614258 nb_pixel_total : 22198 time to create 1 rle with old method : 0.025269746780395508 time for calcul the mask position with numpy : 0.024809598922729492 nb_pixel_total : 29263 time to create 1 rle with old method : 0.0327146053314209 time for calcul the mask position with numpy : 0.023120880126953125 nb_pixel_total : 25077 time to create 1 rle with old method : 0.026839017868041992 time for calcul the mask position with numpy : 0.023898839950561523 nb_pixel_total : 24722 time to create 1 rle with old method : 0.027207374572753906 time for calcul the mask position with numpy : 0.023814678192138672 nb_pixel_total : 17949 time to create 1 rle with old method : 0.020338773727416992 time for calcul the mask position with numpy : 0.025197744369506836 nb_pixel_total : 54481 time to create 1 rle with old method : 0.06121516227722168 time for calcul the mask position with numpy : 0.02329540252685547 nb_pixel_total : 34621 time to create 1 rle with old method : 0.03905487060546875 time for calcul the mask position with numpy : 0.024383068084716797 nb_pixel_total : 31407 time to create 1 rle with old method : 0.0352325439453125 time for calcul the mask position with numpy : 0.02524566650390625 nb_pixel_total : 13315 time to create 1 rle with old method : 0.01710963249206543 create new chi : 2.882335662841797 time to delete rle : 0.001383066177368164 batch 1 Loaded 25 chid ids of type : 3594 +++++++++++++Number RLEs to save : 6800 TO DO : save crop sub photo not yet done ! save time : 0.4577150344848633 nb_obj : 12 nb_hashtags : 3 time to prepare the origin masks : 4.058966159820557 time for calcul the mask position with numpy : 0.4606757164001465 nb_pixel_total : 7829355 time to create 1 rle with new method : 0.6701610088348389 time for calcul the mask position with numpy : 0.025788545608520508 nb_pixel_total : 34660 time to create 1 rle with old method : 0.0394902229309082 time for calcul the mask position with numpy : 0.024824142456054688 nb_pixel_total : 13273 time to create 1 rle with old method : 0.015343666076660156 time for calcul the mask position with numpy : 0.02638411521911621 nb_pixel_total : 103351 time to create 1 rle with old method : 0.11666393280029297 time for calcul the mask position with numpy : 0.024860382080078125 nb_pixel_total : 108823 time to create 1 rle with old method : 0.12035918235778809 time for calcul the mask position with numpy : 0.023267269134521484 nb_pixel_total : 33281 time to create 1 rle with old method : 0.037870168685913086 time for calcul the mask position with numpy : 0.023597240447998047 nb_pixel_total : 22298 time to create 1 rle with old method : 0.025081396102905273 time for calcul the mask position with numpy : 0.023755311965942383 nb_pixel_total : 24200 time to create 1 rle with old method : 0.026542186737060547 time for calcul the mask position with numpy : 0.022644996643066406 nb_pixel_total : 53039 time to create 1 rle with old method : 0.05666971206665039 time for calcul the mask position with numpy : 0.02428579330444336 nb_pixel_total : 9666 time to create 1 rle with old method : 0.01066732406616211 time for calcul the mask position with numpy : 0.02463698387145996 nb_pixel_total : 18292 time to create 1 rle with old method : 0.02020716667175293 time for calcul the mask position with numpy : 0.024082660675048828 nb_pixel_total : 20594 time to create 1 rle with old method : 0.02221846580505371 time for calcul the mask position with numpy : 0.023993253707885742 nb_pixel_total : 23568 time to create 1 rle with old method : 0.026647567749023438 create new chi : 1.9857220649719238 time to delete rle : 0.0012097358703613281 batch 1 Loaded 25 chid ids of type : 3594 ++++++++++++Number RLEs to save : 8278 TO DO : save crop sub photo not yet done ! save time : 0.488267183303833 nb_obj : 7 nb_hashtags : 3 time to prepare the origin masks : 3.0705204010009766 time for calcul the mask position with numpy : 0.5176694393157959 nb_pixel_total : 7997025 time to create 1 rle with new method : 0.8593127727508545 time for calcul the mask position with numpy : 0.02529621124267578 nb_pixel_total : 33013 time to create 1 rle with old method : 0.03894948959350586 time for calcul the mask position with numpy : 0.02424454689025879 nb_pixel_total : 26059 time to create 1 rle with old method : 0.03050684928894043 time for calcul the mask position with numpy : 0.024982929229736328 nb_pixel_total : 27549 time to create 1 rle with old method : 0.032578229904174805 time for calcul the mask position with numpy : 0.026515483856201172 nb_pixel_total : 42392 time to create 1 rle with old method : 0.05186605453491211 time for calcul the mask position with numpy : 0.03976869583129883 nb_pixel_total : 143458 time to create 1 rle with old method : 0.1634206771850586 time for calcul the mask position with numpy : 0.03672385215759277 nb_pixel_total : 12486 time to create 1 rle with old method : 0.014033317565917969 time for calcul the mask position with numpy : 0.024530410766601562 nb_pixel_total : 12418 time to create 1 rle with old method : 0.014313936233520508 create new chi : 1.967456579208374 time to delete rle : 0.0007922649383544922 batch 1 Loaded 15 chid ids of type : 3594 ++++++++Number RLEs to save : 5596 TO DO : save crop sub photo not yet done ! save time : 0.37801098823547363 nb_obj : 3 nb_hashtags : 2 time to prepare the origin masks : 1.390437126159668 time for calcul the mask position with numpy : 0.5280869007110596 nb_pixel_total : 7807429 time to create 1 rle with new method : 0.7457704544067383 time for calcul the mask position with numpy : 0.02459120750427246 nb_pixel_total : 67607 time to create 1 rle with old method : 0.07702803611755371 time for calcul the mask position with numpy : 0.026189804077148438 nb_pixel_total : 392036 time to create 1 rle with new method : 0.6329007148742676 time for calcul the mask position with numpy : 0.025728702545166016 nb_pixel_total : 27328 time to create 1 rle with old method : 0.0315089225769043 create new chi : 2.161353826522827 time to delete rle : 0.0007417201995849609 batch 1 Loaded 7 chid ids of type : 3594 ++++Number RLEs to save : 4516 TO DO : save crop sub photo not yet done ! save time : 0.3278374671936035 nb_obj : 5 nb_hashtags : 2 time to prepare the origin masks : 2.180388927459717 time for calcul the mask position with numpy : 0.3539426326751709 nb_pixel_total : 7994568 time to create 1 rle with new method : 0.6658782958984375 time for calcul the mask position with numpy : 0.026897430419921875 nb_pixel_total : 36786 time to create 1 rle with old method : 0.04329276084899902 time for calcul the mask position with numpy : 0.02704787254333496 nb_pixel_total : 30660 time to create 1 rle with old method : 0.03566575050354004 time for calcul the mask position with numpy : 0.025646686553955078 nb_pixel_total : 31986 time to create 1 rle with old method : 0.03682136535644531 time for calcul the mask position with numpy : 0.025008678436279297 nb_pixel_total : 116264 time to create 1 rle with old method : 0.14595723152160645 time for calcul the mask position with numpy : 0.026033878326416016 nb_pixel_total : 84136 time to create 1 rle with old method : 0.09512996673583984 create new chi : 1.5521481037139893 time to delete rle : 0.0006814002990722656 batch 1 Loaded 11 chid ids of type : 3594 ++++++++Number RLEs to save : 5078 TO DO : save crop sub photo not yet done ! save time : 0.372391939163208 nb_obj : 12 nb_hashtags : 3 time to prepare the origin masks : 4.68137264251709 time for calcul the mask position with numpy : 0.411069393157959 nb_pixel_total : 7786644 time to create 1 rle with new method : 0.7412793636322021 time for calcul the mask position with numpy : 0.023604393005371094 nb_pixel_total : 42930 time to create 1 rle with old method : 0.04668545722961426 time for calcul the mask position with numpy : 0.02254652976989746 nb_pixel_total : 14728 time to create 1 rle with old method : 0.0163266658782959 time for calcul the mask position with numpy : 0.024191617965698242 nb_pixel_total : 17776 time to create 1 rle with old method : 0.019388914108276367 time for calcul the mask position with numpy : 0.024285316467285156 nb_pixel_total : 10746 time to create 1 rle with old method : 0.01152658462524414 time for calcul the mask position with numpy : 0.024248600006103516 nb_pixel_total : 141714 time to create 1 rle with old method : 0.1530623435974121 time for calcul the mask position with numpy : 0.024366140365600586 nb_pixel_total : 38758 time to create 1 rle with old method : 0.04290437698364258 time for calcul the mask position with numpy : 0.023537158966064453 nb_pixel_total : 19334 time to create 1 rle with old method : 0.021188974380493164 time for calcul the mask position with numpy : 0.02378988265991211 nb_pixel_total : 12696 time to create 1 rle with old method : 0.014703750610351562 time for calcul the mask position with numpy : 0.024971485137939453 nb_pixel_total : 138075 time to create 1 rle with old method : 0.15076780319213867 time for calcul the mask position with numpy : 0.023350238800048828 nb_pixel_total : 33755 time to create 1 rle with old method : 0.035645484924316406 time for calcul the mask position with numpy : 0.023222923278808594 nb_pixel_total : 12856 time to create 1 rle with old method : 0.013858556747436523 time for calcul the mask position with numpy : 0.02295398712158203 nb_pixel_total : 24388 time to create 1 rle with old method : 0.0261843204498291 create new chi : 2.0312206745147705 time to delete rle : 0.001207590103149414 batch 1 Loaded 25 chid ids of type : 3594 +++++++++++++Number RLEs to save : 7876 TO DO : save crop sub photo not yet done ! save time : 0.5167632102966309 nb_obj : 4 nb_hashtags : 2 time to prepare the origin masks : 1.4306347370147705 time for calcul the mask position with numpy : 0.5169274806976318 nb_pixel_total : 8101093 time to create 1 rle with new method : 0.721259355545044 time for calcul the mask position with numpy : 0.023478984832763672 nb_pixel_total : 19168 time to create 1 rle with old method : 0.021292924880981445 time for calcul the mask position with numpy : 0.025286436080932617 nb_pixel_total : 21772 time to create 1 rle with old method : 0.024289846420288086 time for calcul the mask position with numpy : 0.027115583419799805 nb_pixel_total : 26953 time to create 1 rle with old method : 0.0301513671875 time for calcul the mask position with numpy : 0.02940511703491211 nb_pixel_total : 125414 time to create 1 rle with old method : 0.1358504295349121 create new chi : 1.5975596904754639 time to delete rle : 0.0006563663482666016 batch 1 Loaded 9 chid ids of type : 3594 ++++++Number RLEs to save : 4214 TO DO : save crop sub photo not yet done ! save time : 0.29727697372436523 nb_obj : 7 nb_hashtags : 3 time to prepare the origin masks : 2.568746566772461 time for calcul the mask position with numpy : 0.5676255226135254 nb_pixel_total : 7839986 time to create 1 rle with new method : 0.6083486080169678 time for calcul the mask position with numpy : 0.033550262451171875 nb_pixel_total : 62877 time to create 1 rle with old method : 0.09419012069702148 time for calcul the mask position with numpy : 0.02628350257873535 nb_pixel_total : 33592 time to create 1 rle with old method : 0.03937959671020508 time for calcul the mask position with numpy : 0.03061389923095703 nb_pixel_total : 105266 time to create 1 rle with old method : 0.1449429988861084 time for calcul the mask position with numpy : 0.025274038314819336 nb_pixel_total : 24380 time to create 1 rle with old method : 0.038439035415649414 time for calcul the mask position with numpy : 0.027615785598754883 nb_pixel_total : 17826 time to create 1 rle with old method : 0.025211811065673828 time for calcul the mask position with numpy : 0.026595354080200195 nb_pixel_total : 68201 time to create 1 rle with old method : 0.07676982879638672 time for calcul the mask position with numpy : 0.025781631469726562 nb_pixel_total : 142272 time to create 1 rle with old method : 0.16164231300354004 create new chi : 2.0059258937835693 time to delete rle : 0.0009577274322509766 batch 1 Loaded 15 chid ids of type : 3594 +++++++Number RLEs to save : 6286 TO DO : save crop sub photo not yet done ! save time : 0.41683483123779297 nb_obj : 4 nb_hashtags : 2 time to prepare the origin masks : 1.9639387130737305 time for calcul the mask position with numpy : 0.5440590381622314 nb_pixel_total : 7967586 time to create 1 rle with new method : 0.716841459274292 time for calcul the mask position with numpy : 0.02445197105407715 nb_pixel_total : 76721 time to create 1 rle with old method : 0.0906381607055664 time for calcul the mask position with numpy : 0.0243680477142334 nb_pixel_total : 34425 time to create 1 rle with old method : 0.039602041244506836 time for calcul the mask position with numpy : 0.024579286575317383 nb_pixel_total : 86058 time to create 1 rle with old method : 0.0963280200958252 time for calcul the mask position with numpy : 0.0258181095123291 nb_pixel_total : 129610 time to create 1 rle with old method : 0.14641284942626953 create new chi : 1.7761404514312744 time to delete rle : 0.0006687641143798828 batch 1 Loaded 9 chid ids of type : 3594 ++++++++Number RLEs to save : 4926 TO DO : save crop sub photo not yet done ! save time : 0.3452625274658203 nb_obj : 12 nb_hashtags : 4 time to prepare the origin masks : 3.9565446376800537 time for calcul the mask position with numpy : 0.4983077049255371 nb_pixel_total : 7625197 time to create 1 rle with new method : 0.6629476547241211 time for calcul the mask position with numpy : 0.023517847061157227 nb_pixel_total : 103621 time to create 1 rle with old method : 0.11391472816467285 time for calcul the mask position with numpy : 0.02366805076599121 nb_pixel_total : 163140 time to create 1 rle with new method : 0.5995378494262695 time for calcul the mask position with numpy : 0.023067712783813477 nb_pixel_total : 11588 time to create 1 rle with old method : 0.012769937515258789 time for calcul the mask position with numpy : 0.024266481399536133 nb_pixel_total : 80110 time to create 1 rle with old method : 0.08700442314147949 time for calcul the mask position with numpy : 0.023891210556030273 nb_pixel_total : 36552 time to create 1 rle with old method : 0.04187893867492676 time for calcul the mask position with numpy : 0.025161027908325195 nb_pixel_total : 49050 time to create 1 rle with old method : 0.05377769470214844 time for calcul the mask position with numpy : 0.024309158325195312 nb_pixel_total : 27034 time to create 1 rle with old method : 0.030269384384155273 time for calcul the mask position with numpy : 0.024168729782104492 nb_pixel_total : 19338 time to create 1 rle with old method : 0.021042585372924805 time for calcul the mask position with numpy : 0.023773908615112305 nb_pixel_total : 38207 time to create 1 rle with old method : 0.04190778732299805 time for calcul the mask position with numpy : 0.023951053619384766 nb_pixel_total : 30605 time to create 1 rle with old method : 0.03471207618713379 time for calcul the mask position with numpy : 0.024423837661743164 nb_pixel_total : 77928 time to create 1 rle with old method : 0.08482551574707031 time for calcul the mask position with numpy : 0.02440333366394043 nb_pixel_total : 32030 time to create 1 rle with old method : 0.03498506546020508 create new chi : 2.673452615737915 time to delete rle : 0.0014469623565673828 batch 1 Loaded 25 chid ids of type : 3594 +++++++++++++Number RLEs to save : 10068 TO DO : save crop sub photo not yet done ! save time : 0.6130108833312988 map_output_result : {1396887253: (0.0, 'Should be the crop_list due to order', 0), 1396887216: (0.0, 'Should be the crop_list due to order', 0), 1396886679: (0.0, 'Should be the crop_list due to order', 0), 1396886621: (0.0, 'Should be the crop_list due to order', 0), 1396886562: (0.0, 'Should be the crop_list due to order', 0), 1396886506: (0.0, 'Should be the crop_list due to order', 0), 1396886496: (0.0, 'Should be the crop_list due to order', 0), 1396886493: (0.0, 'Should be the crop_list due to order', 0), 1396886458: (0.0, 'Should be the crop_list due to order', 0), 1396886455: (0.0, 'Should be the crop_list due to order', 0), 1396886451: (0.0, 'Should be the crop_list due to order', 0), 1396886449: (0.0, 'Should be the crop_list due to order', 0), 1396886447: (0.0, 'Should be the crop_list due to order', 0), 1396886444: (0.0, 'Should be the crop_list due to order', 0), 1396886437: (0.0, 'Should be the crop_list due to order', 0)} End step rle-unique-nms Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : rle_unique_nms_with_priority we use saveGeneral [1396887253, 1396887216, 1396886679, 1396886621, 1396886562, 1396886506, 1396886496, 1396886493, 1396886458, 1396886455, 1396886451, 1396886449, 1396886447, 1396886444, 1396886437] Looping around the photos to save general results len do output : 15 /1396887253.Didn't retrieve data . /1396887216.Didn't retrieve data . /1396886679.Didn't retrieve data . /1396886621.Didn't retrieve data . /1396886562.Didn't retrieve data . /1396886506.Didn't retrieve data . /1396886496.Didn't retrieve data . /1396886493.Didn't retrieve data . /1396886458.Didn't retrieve data . /1396886455.Didn't retrieve data . /1396886451.Didn't retrieve data . /1396886449.Didn't retrieve data . /1396886447.Didn't retrieve data . /1396886444.Didn't retrieve data . /1396886437.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, '4141163') ('3318', '29024015', '1396887253', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396887216', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886679', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886621', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886562', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886506', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886496', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886493', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886458', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886455', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886451', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886449', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886447', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886444', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886437', None, None, None, None, None, '4141163') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 45 time used for this insertion : 0.015314102172851562 save_final save missing photos in datou_result : time spend for datou_step_exec : 80.89739727973938 time spend to save output : 0.015866756439208984 total time spend for step 3 : 80.91326403617859 step4:ventilate_hashtags_in_portfolio Sat Nov 29 14:14:13 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed 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 : 29024015 get user id for portfolio 29024015 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`=29024015 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('autre','metal','carton','pet_clair','background','papier','environnement','pehd','flou','pet_fonce','mal_croppe')) AND mptpi.`min_score`=0.5 To do To do SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=29024015 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('autre','metal','carton','pet_clair','background','papier','environnement','pehd','flou','pet_fonce','mal_croppe')) AND mptpi.`min_score`=0.5 To do Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") To do ! Use context local managing function ! SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=29024015 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('autre','metal','carton','pet_clair','background','papier','environnement','pehd','flou','pet_fonce','mal_croppe')) AND mptpi.`min_score`=0.5 To do lien utilise dans velours : https://marlene.fotonower.com/velours/29024205,29024206,29024207,29024208,29024209,29024210,29024211,29024212,29024213,29024214,29024215?tags=autre,metal,carton,pet_clair,background,papier,environnement,pehd,flou,pet_fonce,mal_croppe Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : ventilate_hashtags_in_portfolio we use saveGeneral [1396887253, 1396887216, 1396886679, 1396886621, 1396886562, 1396886506, 1396886496, 1396886493, 1396886458, 1396886455, 1396886451, 1396886449, 1396886447, 1396886444, 1396886437] Looping around the photos to save general results len do output : 1 /29024015. 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, '4141163') ('3318', '29024015', '1396887253', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396887216', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886679', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886621', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886562', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886506', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886496', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886493', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886458', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886455', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886451', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886449', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886447', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886444', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886437', None, None, None, None, None, '4141163') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 16 time used for this insertion : 0.018893718719482422 save_final save missing photos in datou_result : time spend for datou_step_exec : 1.9191620349884033 time spend to save output : 0.019237041473388672 total time spend for step 4 : 1.938399076461792 step5:final Sat Nov 29 14:14:15 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! complete output_args for input 2 VR 22-3-18 : For now we do not clean correctly the datou structure Beginning of datou step final ! Catched exception ! Connect or reconnect ! Inside saveOutput : final : False verbose : 0 original output for save of step final : {1396887253: ('0.04603444894547325',), 1396887216: ('0.04603444894547325',), 1396886679: ('0.04603444894547325',), 1396886621: ('0.04603444894547325',), 1396886562: ('0.04603444894547325',), 1396886506: ('0.04603444894547325',), 1396886496: ('0.04603444894547325',), 1396886493: ('0.04603444894547325',), 1396886458: ('0.04603444894547325',), 1396886455: ('0.04603444894547325',), 1396886451: ('0.04603444894547325',), 1396886449: ('0.04603444894547325',), 1396886447: ('0.04603444894547325',), 1396886444: ('0.04603444894547325',), 1396886437: ('0.04603444894547325',)} new output for save of step final : {1396887253: ('0.04603444894547325',), 1396887216: ('0.04603444894547325',), 1396886679: ('0.04603444894547325',), 1396886621: ('0.04603444894547325',), 1396886562: ('0.04603444894547325',), 1396886506: ('0.04603444894547325',), 1396886496: ('0.04603444894547325',), 1396886493: ('0.04603444894547325',), 1396886458: ('0.04603444894547325',), 1396886455: ('0.04603444894547325',), 1396886451: ('0.04603444894547325',), 1396886449: ('0.04603444894547325',), 1396886447: ('0.04603444894547325',), 1396886444: ('0.04603444894547325',), 1396886437: ('0.04603444894547325',)} [1396887253, 1396887216, 1396886679, 1396886621, 1396886562, 1396886506, 1396886496, 1396886493, 1396886458, 1396886455, 1396886451, 1396886449, 1396886447, 1396886444, 1396886437] Looping around the photos to save general results len do output : 15 /1396887253.Didn't retrieve data . /1396887216.Didn't retrieve data . /1396886679.Didn't retrieve data . /1396886621.Didn't retrieve data . /1396886562.Didn't retrieve data . /1396886506.Didn't retrieve data . /1396886496.Didn't retrieve data . /1396886493.Didn't retrieve data . /1396886458.Didn't retrieve data . /1396886455.Didn't retrieve data . /1396886451.Didn't retrieve data . /1396886449.Didn't retrieve data . /1396886447.Didn't retrieve data . /1396886444.Didn't retrieve data . /1396886437.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, '4141163') ('3318', '29024015', '1396887253', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396887216', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886679', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886621', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886562', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886506', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886496', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886493', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886458', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886455', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886451', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886449', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886447', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886444', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886437', None, None, None, None, None, '4141163') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 45 time used for this insertion : 0.015175104141235352 save_final save missing photos in datou_result : time spend for datou_step_exec : 0.13473844528198242 time spend to save output : 0.015881061553955078 total time spend for step 5 : 0.1506195068359375 step6:blur_detection Sat Nov 29 14:14:15 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure inside step blur_detection methode: ratio et variance treat image : temp/1764421828_2504845_1396887253_319c20b3f68ed3ac5c5d57322f12f3b6.jpg resize: (2160, 3840) 1396887253 -5.818487897657034 treat image : temp/1764421828_2504845_1396887216_13442020c36ad543571c40c26406f573.jpg resize: (2160, 3840) 1396887216 -6.919446934874534 treat image : temp/1764421828_2504845_1396886679_01a7e52f3f2dc1e8d8565ba7aef84c92.jpg resize: (2160, 3840) 1396886679 -6.9939303929112615 treat image : temp/1764421828_2504845_1396886621_7783b24967ef9c8af3dbf2a21075d826.jpg resize: (2160, 3840) 1396886621 -7.095942490910917 treat image : temp/1764421828_2504845_1396886562_8154b66f5fb7cec60058db0a52cc232f.jpg resize: (2160, 3840) 1396886562 -6.947285982391521 treat image : temp/1764421828_2504845_1396886506_e6e2a9fdf17083ebf64c5988daf9afdd.jpg resize: (2160, 3840) 1396886506 -6.884254278386091 treat image : temp/1764421828_2504845_1396886496_cf2c7cb169eb3bda3db7e1165b9c81f1.jpg resize: (2160, 3840) 1396886496 -7.123377591643139 treat image : temp/1764421828_2504845_1396886493_1aa2f7624d70d7916919ec5d6246b3b3.jpg resize: (2160, 3840) 1396886493 -7.0088459803364955 treat image : temp/1764421828_2504845_1396886458_d3691afd5540ab54c783df5d05669d24.jpg resize: (2160, 3840) 1396886458 -6.839374115329482 treat image : temp/1764421828_2504845_1396886455_bcc7e3d5e222518fb3c15b6accbafae3.jpg resize: (2160, 3840) 1396886455 -7.0895550400148615 treat image : temp/1764421828_2504845_1396886451_3f43b3b48fcbaca48248f71e2fe9ae79.jpg resize: (2160, 3840) 1396886451 -6.886880168660634 treat image : temp/1764421828_2504845_1396886449_365bbd2b9360cdb47ef87e4e66c16da5.jpg resize: (2160, 3840) 1396886449 -6.915233965526227 treat image : temp/1764421828_2504845_1396886447_18b717fe2f2f229dcdc404ac9fb0b385.jpg resize: (2160, 3840) 1396886447 -7.021417979429109 treat image : temp/1764421828_2504845_1396886444_710ef9ec690bc2cdfd5945207d5bd3b9.jpg resize: (2160, 3840) 1396886444 -7.049691330577292 treat image : temp/1764421828_2504845_1396886437_b0138e5dcaed7ea8004e9600a670911d.jpg resize: (2160, 3840) 1396886437 -6.459001224770574 treat image : temp/1764421828_2504845_1396887253_319c20b3f68ed3ac5c5d57322f12f3b6_rle_crop_4051472263_0.png resize: (581, 833) 1396897937 -4.956997387949899 treat image : temp/1764421828_2504845_1396887253_319c20b3f68ed3ac5c5d57322f12f3b6_rle_crop_4051472265_0.png resize: (231, 333) 1396897938 -4.5764498199586905 treat image : temp/1764421828_2504845_1396887253_319c20b3f68ed3ac5c5d57322f12f3b6_rle_crop_4051472266_0.png resize: (293, 247) 1396897939 -4.188719684866163 treat image : temp/1764421828_2504845_1396887253_319c20b3f68ed3ac5c5d57322f12f3b6_rle_crop_4051472271_0.png resize: (329, 536) 1396897940 -4.308999101414288 treat image : temp/1764421828_2504845_1396887216_13442020c36ad543571c40c26406f573_rle_crop_4051472274_0.png resize: (313, 227) 1396897941 -4.678271200083876 treat image : temp/1764421828_2504845_1396887216_13442020c36ad543571c40c26406f573_rle_crop_4051472276_0.png resize: (399, 218) 1396897942 -3.4642063723429057 treat image : temp/1764421828_2504845_1396886679_01a7e52f3f2dc1e8d8565ba7aef84c92_rle_crop_4051472280_0.png resize: (362, 206) 1396897943 -5.637170935451182 treat image : temp/1764421828_2504845_1396886679_01a7e52f3f2dc1e8d8565ba7aef84c92_rle_crop_4051472281_0.png resize: (731, 354) 1396897944 -5.384810654838955 treat image : temp/1764421828_2504845_1396886679_01a7e52f3f2dc1e8d8565ba7aef84c92_rle_crop_4051472282_0.png resize: (226, 92) 1396897945 -4.9013648273842305 treat image : temp/1764421828_2504845_1396886679_01a7e52f3f2dc1e8d8565ba7aef84c92_rle_crop_4051472284_0.png resize: (285, 235) 1396897946 -4.001765791434588 treat image : temp/1764421828_2504845_1396886679_01a7e52f3f2dc1e8d8565ba7aef84c92_rle_crop_4051472285_0.png resize: (142, 189) 1396897947 -3.443435243215828 treat image : temp/1764421828_2504845_1396886506_e6e2a9fdf17083ebf64c5988daf9afdd_rle_crop_4051472295_0.png resize: (115, 179) 1396897948 -4.218734743752659 treat image : temp/1764421828_2504845_1396886506_e6e2a9fdf17083ebf64c5988daf9afdd_rle_crop_4051472296_0.png resize: (256, 205) 1396897949 -2.115039436290382 treat image : temp/1764421828_2504845_1396886506_e6e2a9fdf17083ebf64c5988daf9afdd_rle_crop_4051472298_0.png resize: (295, 254) 1396897950 -4.503814441137033 treat image : temp/1764421828_2504845_1396886506_e6e2a9fdf17083ebf64c5988daf9afdd_rle_crop_4051472299_0.png resize: (198, 165) 1396897951 -3.7634094449729574 treat image : temp/1764421828_2504845_1396886506_e6e2a9fdf17083ebf64c5988daf9afdd_rle_crop_4051472302_0.png resize: (227, 225) 1396897952 -4.278521704908281 treat image : temp/1764421828_2504845_1396886506_e6e2a9fdf17083ebf64c5988daf9afdd_rle_crop_4051472303_0.png resize: (196, 160) 1396897953 -3.927530368725739 treat image : temp/1764421828_2504845_1396886496_cf2c7cb169eb3bda3db7e1165b9c81f1_rle_crop_4051472307_0.png resize: (179, 275) 1396897954 -3.8150059833708694 treat image : temp/1764421828_2504845_1396886496_cf2c7cb169eb3bda3db7e1165b9c81f1_rle_crop_4051472308_0.png resize: (203, 189) 1396897955 -4.1726282524975735 treat image : temp/1764421828_2504845_1396886496_cf2c7cb169eb3bda3db7e1165b9c81f1_rle_crop_4051472309_0.png resize: (141, 188) 1396897956 -3.9055884316078213 treat image : temp/1764421828_2504845_1396886496_cf2c7cb169eb3bda3db7e1165b9c81f1_rle_crop_4051472310_0.png resize: (134, 87) 1396897957 -2.8892504170743836 treat image : temp/1764421828_2504845_1396886496_cf2c7cb169eb3bda3db7e1165b9c81f1_rle_crop_4051472312_0.png resize: (203, 211) 1396897958 -4.231477373464259 treat image : temp/1764421828_2504845_1396886496_cf2c7cb169eb3bda3db7e1165b9c81f1_rle_crop_4051472313_0.png resize: (168, 193) 1396897959 -5.486314196091695 treat image : temp/1764421828_2504845_1396886496_cf2c7cb169eb3bda3db7e1165b9c81f1_rle_crop_4051472316_0.png resize: (423, 340) 1396897960 -4.498041797535902 treat image : temp/1764421828_2504845_1396886496_cf2c7cb169eb3bda3db7e1165b9c81f1_rle_crop_4051472317_0.png resize: (127, 142) 1396897961 -4.585677477261104 treat image : temp/1764421828_2504845_1396886493_1aa2f7624d70d7916919ec5d6246b3b3_rle_crop_4051472320_0.png resize: (102, 179) 1396897962 -4.977232104251224 treat image : temp/1764421828_2504845_1396886455_bcc7e3d5e222518fb3c15b6accbafae3_rle_crop_4051472331_0.png resize: (220, 273) 1396897963 -3.8441679252934744 treat image : temp/1764421828_2504845_1396886455_bcc7e3d5e222518fb3c15b6accbafae3_rle_crop_4051472332_0.png resize: (187, 289) 1396897964 -4.030746915079584 treat image : temp/1764421828_2504845_1396886455_bcc7e3d5e222518fb3c15b6accbafae3_rle_crop_4051472333_0.png resize: (235, 198) 1396897965 -4.610419795181718 treat image : temp/1764421828_2504845_1396886451_3f43b3b48fcbaca48248f71e2fe9ae79_rle_crop_4051472334_0.png resize: (192, 149) 1396897966 -3.7990480650056755 treat image : temp/1764421828_2504845_1396886451_3f43b3b48fcbaca48248f71e2fe9ae79_rle_crop_4051472335_0.png resize: (102, 164) 1396897967 -4.360976812170705 treat image : temp/1764421828_2504845_1396886451_3f43b3b48fcbaca48248f71e2fe9ae79_rle_crop_4051472339_0.png resize: (124, 208) 1396897968 -5.170304939510481 treat image : temp/1764421828_2504845_1396886451_3f43b3b48fcbaca48248f71e2fe9ae79_rle_crop_4051472342_0.png resize: (113, 151) 1396897969 -3.662725890370205 treat image : temp/1764421828_2504845_1396886451_3f43b3b48fcbaca48248f71e2fe9ae79_rle_crop_4051472343_0.png resize: (152, 169) 1396897970 -5.01262432410518 treat image : temp/1764421828_2504845_1396886451_3f43b3b48fcbaca48248f71e2fe9ae79_rle_crop_4051472344_0.png resize: (220, 82) 1396897971 -4.095754511424011 treat image : temp/1764421828_2504845_1396886449_365bbd2b9360cdb47ef87e4e66c16da5_rle_crop_4051472346_0.png resize: (291, 682) 1396897972 -4.602338058881547 treat image : temp/1764421828_2504845_1396886449_365bbd2b9360cdb47ef87e4e66c16da5_rle_crop_4051472347_0.png resize: (245, 179) 1396897973 -4.369213351457304 treat image : temp/1764421828_2504845_1396886447_18b717fe2f2f229dcdc404ac9fb0b385_rle_crop_4051472350_0.png resize: (373, 564) 1396897974 -5.40458194431075 treat image : temp/1764421828_2504845_1396886447_18b717fe2f2f229dcdc404ac9fb0b385_rle_crop_4051472353_0.png resize: (345, 103) 1396897975 -4.377093656542585 treat image : temp/1764421828_2504845_1396886447_18b717fe2f2f229dcdc404ac9fb0b385_rle_crop_4051472354_0.png resize: (341, 381) 1396897977 -3.400977027030429 treat image : temp/1764421828_2504845_1396886447_18b717fe2f2f229dcdc404ac9fb0b385_rle_crop_4051472355_0.png resize: (175, 263) 1396897978 -3.3908459705962533 treat image : temp/1764421828_2504845_1396886444_710ef9ec690bc2cdfd5945207d5bd3b9_rle_crop_4051472357_0.png resize: (438, 403) 1396897979 -4.789415813113758 treat image : temp/1764421828_2504845_1396886444_710ef9ec690bc2cdfd5945207d5bd3b9_rle_crop_4051472358_0.png resize: (262, 399) 1396897980 -4.8622770415283165 treat image : temp/1764421828_2504845_1396886444_710ef9ec690bc2cdfd5945207d5bd3b9_rle_crop_4051472360_0.png resize: (277, 563) 1396897981 -5.142704192599324 treat image : temp/1764421828_2504845_1396886437_b0138e5dcaed7ea8004e9600a670911d_rle_crop_4051472361_0.png resize: (199, 218) 1396897982 -3.792865397620416 treat image : temp/1764421828_2504845_1396886437_b0138e5dcaed7ea8004e9600a670911d_rle_crop_4051472364_0.png resize: (355, 271) 1396897983 -3.9733485914767415 treat image : temp/1764421828_2504845_1396886437_b0138e5dcaed7ea8004e9600a670911d_rle_crop_4051472365_0.png resize: (232, 124) 1396897984 -3.9912697074759005 treat image : temp/1764421828_2504845_1396886437_b0138e5dcaed7ea8004e9600a670911d_rle_crop_4051472367_0.png resize: (194, 358) 1396897985 -5.367226645872826 treat image : temp/1764421828_2504845_1396886437_b0138e5dcaed7ea8004e9600a670911d_rle_crop_4051472368_0.png resize: (328, 180) 1396897986 -4.21951046655466 treat image : temp/1764421828_2504845_1396886437_b0138e5dcaed7ea8004e9600a670911d_rle_crop_4051472371_0.png resize: (503, 566) 1396897987 -4.581372733975712 treat image : temp/1764421828_2504845_1396886437_b0138e5dcaed7ea8004e9600a670911d_rle_crop_4051472372_0.png resize: (529, 281) 1396897988 -3.702507513820085 treat image : temp/1764421828_2504845_1396887253_319c20b3f68ed3ac5c5d57322f12f3b6_rle_crop_4051472264_0.png resize: (66, 244) 1396897992 -4.667040111515625 treat image : temp/1764421828_2504845_1396887253_319c20b3f68ed3ac5c5d57322f12f3b6_rle_crop_4051472268_0.png resize: (212, 163) 1396897993 -3.886275465702189 treat image : temp/1764421828_2504845_1396887216_13442020c36ad543571c40c26406f573_rle_crop_4051472277_0.png resize: (132, 224) 1396897994 -2.5280807158392156 treat image : temp/1764421828_2504845_1396886679_01a7e52f3f2dc1e8d8565ba7aef84c92_rle_crop_4051472279_0.png resize: (218, 159) 1396897995 -5.533089799949123 treat image : temp/1764421828_2504845_1396886621_7783b24967ef9c8af3dbf2a21075d826_rle_crop_4051472286_0.png resize: (242, 214) 1396897996 -2.8143031968357834 treat image : temp/1764421828_2504845_1396886621_7783b24967ef9c8af3dbf2a21075d826_rle_crop_4051472288_0.png resize: (224, 119) 1396897997 -4.029006706898573 treat image : temp/1764421828_2504845_1396886562_8154b66f5fb7cec60058db0a52cc232f_rle_crop_4051472289_0.png resize: (237, 210) 1396897998 -2.751182124533207 treat image : temp/1764421828_2504845_1396886562_8154b66f5fb7cec60058db0a52cc232f_rle_crop_4051472291_0.png resize: (138, 163) 1396897999 -3.7282851223224163 treat image : temp/1764421828_2504845_1396886506_e6e2a9fdf17083ebf64c5988daf9afdd_rle_crop_4051472297_0.png resize: (168, 247) 1396898000 -4.380638887960525 treat image : temp/1764421828_2504845_1396886506_e6e2a9fdf17083ebf64c5988daf9afdd_rle_crop_4051472301_0.png resize: (187, 184) 1396898001 -4.771131059091712 treat image : temp/1764421828_2504845_1396886493_1aa2f7624d70d7916919ec5d6246b3b3_rle_crop_4051472319_0.png resize: (205, 79) 1396898002 -2.4036619215841832 treat image : temp/1764421828_2504845_1396886493_1aa2f7624d70d7916919ec5d6246b3b3_rle_crop_4051472323_0.png resize: (167, 235) 1396898003 -4.444864072157875 treat image : temp/1764421828_2504845_1396886493_1aa2f7624d70d7916919ec5d6246b3b3_rle_crop_4051472325_0.png resize: (164, 284) 1396898004 -3.7888904241227164 treat image : temp/1764421828_2504845_1396886458_d3691afd5540ab54c783df5d05669d24_rle_crop_4051472326_0.png resize: (213, 184) 1396898005 -3.937893236048907 treat image : temp/1764421828_2504845_1396886447_18b717fe2f2f229dcdc404ac9fb0b385_rle_crop_4051472352_0.png resize: (184, 133) 1396898006 -2.61413866423812 treat image : temp/1764421828_2504845_1396886444_710ef9ec690bc2cdfd5945207d5bd3b9_rle_crop_4051472359_0.png resize: (232, 255) 1396898007 -4.458056878185507 treat image : temp/1764421828_2504845_1396886437_b0138e5dcaed7ea8004e9600a670911d_rle_crop_4051472363_0.png resize: (177, 221) 1396898008 -2.7812248649159206 treat image : temp/1764421828_2504845_1396886437_b0138e5dcaed7ea8004e9600a670911d_rle_crop_4051472369_0.png resize: (393, 330) 1396898009 -4.154759610462084 treat image : temp/1764421828_2504845_1396886437_b0138e5dcaed7ea8004e9600a670911d_rle_crop_4051472370_0.png resize: (132, 138) 1396898010 -2.17946000947462 treat image : temp/1764421828_2504845_1396887253_319c20b3f68ed3ac5c5d57322f12f3b6_rle_crop_4051472262_0.png resize: (88, 225) 1396898013 -5.401126354595879 treat image : temp/1764421828_2504845_1396887253_319c20b3f68ed3ac5c5d57322f12f3b6_rle_crop_4051472270_0.png resize: (118, 91) 1396898014 -3.7778001166956106 treat image : temp/1764421828_2504845_1396886679_01a7e52f3f2dc1e8d8565ba7aef84c92_rle_crop_4051472278_0.png resize: (113, 141) 1396898015 -4.578117711153709 treat image : temp/1764421828_2504845_1396886562_8154b66f5fb7cec60058db0a52cc232f_rle_crop_4051472290_0.png resize: (138, 144) 1396898016 -4.8541161571681695 treat image : temp/1764421828_2504845_1396886562_8154b66f5fb7cec60058db0a52cc232f_rle_crop_4051472292_0.png resize: (198, 171) 1396898017 -4.477465083875247 treat image : temp/1764421828_2504845_1396886506_e6e2a9fdf17083ebf64c5988daf9afdd_rle_crop_4051472306_0.png resize: (155, 171) 1396898018 -4.849288612470445 treat image : temp/1764421828_2504845_1396886451_3f43b3b48fcbaca48248f71e2fe9ae79_rle_crop_4051472345_0.png resize: (161, 331) 1396898019 -4.246366644889898 treat image : temp/1764421828_2504845_1396887253_319c20b3f68ed3ac5c5d57322f12f3b6_rle_crop_4051472267_0.png resize: (358, 385) 1396898044 -5.0833852629169565 treat image : temp/1764421828_2504845_1396887253_319c20b3f68ed3ac5c5d57322f12f3b6_rle_crop_4051472269_0.png resize: (246, 457) 1396898045 -5.918108367567742 treat image : temp/1764421828_2504845_1396887216_13442020c36ad543571c40c26406f573_rle_crop_4051472272_0.png resize: (324, 292) 1396898046 -6.3559756432364924 treat image : temp/1764421828_2504845_1396887216_13442020c36ad543571c40c26406f573_rle_crop_4051472275_0.png resize: (225, 148) 1396898047 -4.460475668761502 treat image : temp/1764421828_2504845_1396886562_8154b66f5fb7cec60058db0a52cc232f_rle_crop_4051472293_0.png resize: (370, 197) 1396898048 -4.164631587078447 treat image : temp/1764421828_2504845_1396886562_8154b66f5fb7cec60058db0a52cc232f_rle_crop_4051472294_0.png resize: (350, 363) 1396898049 -4.807764858935789 treat image : temp/1764421828_2504845_1396886506_e6e2a9fdf17083ebf64c5988daf9afdd_rle_crop_4051472300_0.png resize: (124, 236) 1396898050 -5.375763440166645 treat image : temp/1764421828_2504845_1396886506_e6e2a9fdf17083ebf64c5988daf9afdd_rle_crop_4051472304_0.png resize: (193, 211) 1396898051 -5.21587203106507 treat image : temp/1764421828_2504845_1396886496_cf2c7cb169eb3bda3db7e1165b9c81f1_rle_crop_4051472311_0.png resize: (283, 260) 1396898052 -5.169270304325162 treat image : temp/1764421828_2504845_1396886496_cf2c7cb169eb3bda3db7e1165b9c81f1_rle_crop_4051472314_0.png resize: (222, 190) 1396898053 -4.8725646223458705 treat image : temp/1764421828_2504845_1396886496_cf2c7cb169eb3bda3db7e1165b9c81f1_rle_crop_4051472315_0.png resize: (459, 360) 1396898054 -5.18061894808145 treat image : temp/1764421828_2504845_1396886493_1aa2f7624d70d7916919ec5d6246b3b3_rle_crop_4051472321_0.png resize: (377, 496) 1396898055 -6.011360913217858 treat image : temp/1764421828_2504845_1396886493_1aa2f7624d70d7916919ec5d6246b3b3_rle_crop_4051472322_0.png resize: (294, 164) 1396898056 -4.3912754754396985 treat image : temp/1764421828_2504845_1396886493_1aa2f7624d70d7916919ec5d6246b3b3_rle_crop_4051472324_0.png resize: (317, 213) 1396898057 -5.4330979414945695 treat image : temp/1764421828_2504845_1396886458_d3691afd5540ab54c783df5d05669d24_rle_crop_4051472327_0.png resize: (582, 849) 1396898058 -4.664058338190972 treat image : temp/1764421828_2504845_1396886458_d3691afd5540ab54c783df5d05669d24_rle_crop_4051472328_0.png resize: (360, 266) 1396898059 -4.670962480208251 treat image : temp/1764421828_2504845_1396886455_bcc7e3d5e222518fb3c15b6accbafae3_rle_crop_4051472329_0.png resize: (258, 426) 1396898060 -3.628955469808761 treat image : temp/1764421828_2504845_1396886455_bcc7e3d5e222518fb3c15b6accbafae3_rle_crop_4051472330_0.png resize: (464, 405) 1396898061 -5.763750983355054 treat image : temp/1764421828_2504845_1396886451_3f43b3b48fcbaca48248f71e2fe9ae79_rle_crop_4051472336_0.png resize: (310, 137) 1396898062 -4.278063743748637 treat image : temp/1764421828_2504845_1396886451_3f43b3b48fcbaca48248f71e2fe9ae79_rle_crop_4051472337_0.png resize: (495, 357) 1396898063 -5.034170591785096 treat image : temp/1764421828_2504845_1396886451_3f43b3b48fcbaca48248f71e2fe9ae79_rle_crop_4051472338_0.png resize: (97, 182) 1396898064 -4.147403460753474 treat image : temp/1764421828_2504845_1396886451_3f43b3b48fcbaca48248f71e2fe9ae79_rle_crop_4051472340_0.png resize: (148, 347) 1396898065 -4.7659607920628755 treat image : temp/1764421828_2504845_1396886451_3f43b3b48fcbaca48248f71e2fe9ae79_rle_crop_4051472341_0.png resize: (502, 378) 1396898066 -5.865187833931481 treat image : temp/1764421828_2504845_1396886449_365bbd2b9360cdb47ef87e4e66c16da5_rle_crop_4051472348_0.png resize: (209, 130) 1396898067 -4.447609794427711 treat image : temp/1764421828_2504845_1396886449_365bbd2b9360cdb47ef87e4e66c16da5_rle_crop_4051472349_0.png resize: (231, 108) 1396898068 -4.261305144115584 treat image : temp/1764421828_2504845_1396886447_18b717fe2f2f229dcdc404ac9fb0b385_rle_crop_4051472351_0.png resize: (314, 295) 1396898069 -5.210923200675628 treat image : temp/1764421828_2504845_1396886447_18b717fe2f2f229dcdc404ac9fb0b385_rle_crop_4051472356_0.png resize: (303, 338) 1396898070 -4.457318334248909 treat image : temp/1764421828_2504845_1396886437_b0138e5dcaed7ea8004e9600a670911d_rle_crop_4051472362_0.png resize: (395, 251) 1396898071 -5.820458640676761 treat image : temp/1764421828_2504845_1396886621_7783b24967ef9c8af3dbf2a21075d826_rle_crop_4051472287_0.png resize: (95, 108) 1396898076 -5.121964939218695 treat image : temp/1764421828_2504845_1396886506_e6e2a9fdf17083ebf64c5988daf9afdd_rle_crop_4051472305_0.png resize: (177, 156) 1396898077 -4.484980781577464 treat image : temp/1764421828_2504845_1396886496_cf2c7cb169eb3bda3db7e1165b9c81f1_rle_crop_4051472318_0.png resize: (348, 136) 1396898078 -4.831800749992903 treat image : temp/1764421828_2504845_1396886437_b0138e5dcaed7ea8004e9600a670911d_rle_crop_4051472366_0.png resize: (168, 237) 1396898079 -2.8711573254250697 treat image : temp/1764421828_2504845_1396887216_13442020c36ad543571c40c26406f573_rle_crop_4051472273_0.png resize: (222, 244) 1396898080 -5.932371525864961 treat image : temp/1764421828_2504845_1396886679_01a7e52f3f2dc1e8d8565ba7aef84c92_rle_crop_4051472283_0.png resize: (391, 551) 1396898081 -6.333505591170303 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 : 126 time used for this insertion : 0.01982712745666504 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 126 time used for this insertion : 0.03374505043029785 save missing photos in datou_result : time spend for datou_step_exec : 55.78041672706604 time spend to save output : 0.06014275550842285 total time spend for step 6 : 55.84055948257446 step7:brightness Sat Nov 29 14:15:11 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/1764421828_2504845_1396887253_319c20b3f68ed3ac5c5d57322f12f3b6.jpg treat image : temp/1764421828_2504845_1396887216_13442020c36ad543571c40c26406f573.jpg treat image : temp/1764421828_2504845_1396886679_01a7e52f3f2dc1e8d8565ba7aef84c92.jpg treat image : temp/1764421828_2504845_1396886621_7783b24967ef9c8af3dbf2a21075d826.jpg treat image : temp/1764421828_2504845_1396886562_8154b66f5fb7cec60058db0a52cc232f.jpg treat image : temp/1764421828_2504845_1396886506_e6e2a9fdf17083ebf64c5988daf9afdd.jpg treat image : temp/1764421828_2504845_1396886496_cf2c7cb169eb3bda3db7e1165b9c81f1.jpg treat image : temp/1764421828_2504845_1396886493_1aa2f7624d70d7916919ec5d6246b3b3.jpg treat image : temp/1764421828_2504845_1396886458_d3691afd5540ab54c783df5d05669d24.jpg treat image : temp/1764421828_2504845_1396886455_bcc7e3d5e222518fb3c15b6accbafae3.jpg treat image : 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photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 126 time used for this insertion : 0.034789085388183594 save missing photos in datou_result : time spend for datou_step_exec : 14.175102472305298 time spend to save output : 0.061269283294677734 total time spend for step 7 : 14.236371755599976 step8:velours_tree Sat Nov 29 14:15:25 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 : 0.11956477165222168 time spend to save output : 4.220008850097656e-05 total time spend for step 8 : 0.11960697174072266 step9:send_mail_cod Sat Nov 29 14:15:26 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_P29024015_29-11-2025_14_15_26.pdf 29024205 change filename to text .change filename to text .change filename to text .change filename to text .imagette290242051764422126 29024206 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 .imagette290242061764422126 29024207 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 .imagette290242071764422127 29024208 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 .imagette290242081764422129 29024209 imagette290242091764422131 29024210 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 .imagette290242101764422131 29024212 imagette290242121764422133 29024213 imagette290242131764422133 29024214 change filename to text .change filename to text .imagette290242141764422133 29024215 imagette290242151764422133 SELECT h.hashtag,pcr.value FROM MTRUser.portfolio_carac_ratio pcr, MTRBack.hashtags h where pcr.portfolio_id=29024015 and hashtag_type = 3594 and pcr.hashtag_id = h.hashtag_id; velour_link : https://marlene.fotonower.com/velours/29024205,29024206,29024207,29024208,29024209,29024210,29024211,29024212,29024213,29024214,29024215?tags=autre,metal,carton,pet_clair,background,papier,environnement,pehd,flou,pet_fonce,mal_croppe your option no_mail is active, we will not send the real mail to your client args[1396887253] : ((1396887253, -5.818487897657034, 492609224), (1396887253, -0.8415793457877763, 501862349), '0.04603444894547325') We are sending mail with results at report@fotonower.com args[1396887216] : ((1396887216, -6.919446934874534, 492609224), (1396887216, -0.19990167413392715, 496442774), '0.04603444894547325') We are sending mail with results at report@fotonower.com args[1396886679] : ((1396886679, -6.9939303929112615, 492609224), (1396886679, -0.23788600483064792, 496442774), '0.04603444894547325') We are sending mail with results at report@fotonower.com args[1396886621] : ((1396886621, -7.095942490910917, 492609224), (1396886621, -0.28569311251745627, 496442774), '0.04603444894547325') We are sending mail with results at report@fotonower.com args[1396886562] : ((1396886562, -6.947285982391521, 492609224), (1396886562, -0.21742786545142895, 496442774), '0.04603444894547325') We are sending mail with results at report@fotonower.com args[1396886506] : ((1396886506, -6.884254278386091, 492609224), (1396886506, -0.26009265461948355, 496442774), '0.04603444894547325') We are sending mail with results at report@fotonower.com args[1396886496] : ((1396886496, -7.123377591643139, 492609224), (1396886496, -0.08055411709093198, 496442774), '0.04603444894547325') We are sending mail with results at report@fotonower.com args[1396886493] : ((1396886493, -7.0088459803364955, 492609224), (1396886493, -0.210953355850521, 496442774), '0.04603444894547325') We are sending mail with results at report@fotonower.com args[1396886458] : ((1396886458, -6.839374115329482, 492609224), (1396886458, -0.2541653301589996, 496442774), '0.04603444894547325') We are sending mail with results at report@fotonower.com args[1396886455] : ((1396886455, -7.0895550400148615, 492609224), (1396886455, -0.03914515702323878, 2107752395), '0.04603444894547325') We are sending mail with results at report@fotonower.com args[1396886451] : ((1396886451, -6.886880168660634, 492609224), (1396886451, -0.20802329608588221, 496442774), '0.04603444894547325') We are sending mail with results at report@fotonower.com args[1396886449] : ((1396886449, -6.915233965526227, 492609224), (1396886449, -0.173180098136914, 496442774), '0.04603444894547325') We are sending mail with results at report@fotonower.com args[1396886447] : ((1396886447, -7.021417979429109, 492609224), (1396886447, -0.16103492831346536, 496442774), '0.04603444894547325') We are sending mail with results at report@fotonower.com args[1396886444] : ((1396886444, -7.049691330577292, 492609224), (1396886444, -0.11452073494950324, 496442774), '0.04603444894547325') We are sending mail with results at report@fotonower.com args[1396886437] : ((1396886437, -6.459001224770574, 492609224), (1396886437, -0.28848459009992533, 496442774), '0.04603444894547325') We are sending mail with results at report@fotonower.com refus_total : 0.04603444894547325 2022-04-13 10:29:59 0 SELECT ph.photo_id,ph.url,ph.username,ph.uploaded_at,ph.text FROM MTRBack.photos_view ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=29024015 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_P29024015_29-11-2025_14_15_26.pdf results_Auto_P29024015_29-11-2025_14_15_26.pdf uploaded to url https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P29024015_29-11-2025_14_15_26.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','29024015','results_Auto_P29024015_29-11-2025_14_15_26.pdf','https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P29024015_29-11-2025_14_15_26.pdf','pdf','','0.96','0.04603444894547325') Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : send_mail_cod we use saveGeneral [1396887253, 1396887216, 1396886679, 1396886621, 1396886562, 1396886506, 1396886496, 1396886493, 1396886458, 1396886455, 1396886451, 1396886449, 1396886447, 1396886444, 1396886437] 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, '4141163') ('3318', '29024015', '1396887253', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396887216', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886679', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886621', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886562', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886506', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886496', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886493', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886458', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886455', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886451', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886449', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886447', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886444', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886437', None, None, None, None, None, '4141163') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 15 time used for this insertion : 0.01469874382019043 save_final save missing photos in datou_result : time spend for datou_step_exec : 10.702754020690918 time spend to save output : 0.01495361328125 total time spend for step 9 : 10.717707633972168 step10:split_time_score Sat Nov 29 14:15:36 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! complete output_args for input 1 VR 22-3-18 : For now we do not clean correctly the datou structure begin split time score Catched exception ! Connect or reconnect ! TODO : Insert select and so on Begin split_port_in_batch_balle thcls : [{'id': 861, 'mtr_user_id': 31, 'name': 'Rungis_class_dechets_1212', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'Rungis_Aluminium,Rungis_Carton,Rungis_Papier,Rungis_Plastique_clair,Rungis_Plastique_dur,Rungis_Plastique_fonce,Rungis_Tapis_vide,Rungis_Tetrapak', 'svm_portfolios_learning': '1160730,571842,571844,571839,571933,571840,571841,572307', 'photo_hashtag_type': 999, 'photo_desc_type': 3963, 'type_classification': 'caffe', 'hashtag_id_list': '2107751280,2107750907,2107750908,2107750909,2107750910,2107750911,2107750912,2107750913'}] thcls : [{'id': 758, 'mtr_user_id': 31, 'name': 'Rungis_amount_dechets_fall_2018_v2', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': '05102018_Papier_non_papier_dense,05102018_Papier_non_papier_peu_dense,05102018_Papier_non_papier_presque_vide,05102018_Papier_non_papier_tres_dense,05102018_Papier_non_papier_tres_peu_dense', 'svm_portfolios_learning': '1108385,1108386,1108388,1108384,1108387', 'photo_hashtag_type': 856, 'photo_desc_type': 3853, 'type_classification': 'caffe', 'hashtag_id_list': '2107751013,2107751014,2107751015,2107751016,2107751017'}] (('13', 15),) ERROR counted https://github.com/fotonower/Velours/issues/663#issuecomment-421136223 {} 29112025 29024015 Nombre de photos uploadées : 15 / 23040 (0%) 29112025 29024015 Nombre de photos taguées (types de déchets): 0 / 15 (0%) 29112025 29024015 Nombre de photos taguées (volume) : 0 / 15 (0%) elapsed_time : load_data_split_time_score 1.430511474609375e-06 elapsed_time : order_list_meta_photo_and_scores 5.0067901611328125e-06 ??????????????? elapsed_time : fill_and_build_computed_from_old_data 0.0009207725524902344 Catched exception ! Connect or reconnect ! Catched exception ! Connect or reconnect ! elapsed_time : insert_dashboard_record_day_entry 0.24168014526367188 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 : 0.027000801897083117 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P29019879_29-11-2025_08_12_11.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 29019879 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11449 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11452 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 11452 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11453 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11453 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11478 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11478 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11455 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11455 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11458 send_mail_cod have less inputs used (3) than in the step definition (5) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 11449 doesn't seem to be define in the database( WARNING : type of input 2 of step 11452 doesn't seem to be define in the database( WARNING : output 1 of step 11449 have datatype=2 whereas input 1 of step 11453 have datatype=7 WARNING : type of output 2 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11454 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11456 doesn't seem to be define in the database( WARNING : type of output 1 of step 11456 doesn't seem to be define in the database( WARNING : type of input 3 of step 11455 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11456 have datatype=10 whereas input 3 of step 11458 have datatype=6 WARNING : type of input 5 of step 11458 doesn't seem to be define in the database( WARNING : output 0 of step 11477 have datatype=11 whereas input 5 of step 11458 have datatype=None WARNING : output 0 of step 11456 have datatype=10 whereas input 0 of step 11477 have datatype=18 WARNING : type of input 2 of step 11478 doesn't seem to be define in the database( WARNING : output 1 of step 11454 have datatype=7 whereas input 2 of step 11478 have datatype=None WARNING : type of output 3 of step 11478 doesn't seem to be define in the database( WARNING : type of input 2 of step 11456 doesn't seem to be define in the database( WARNING : output 0 of step 11453 have datatype=1 whereas input 0 of step 11454 have datatype=2 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=29019879 AND mptpi.`type`=3726 To do Qualite : 0.02362773099029956 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P29021689_29-11-2025_09_41_19.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 29021689 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11449 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11452 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 11452 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11453 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11453 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11478 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11478 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11455 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11455 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11458 send_mail_cod have less inputs used (3) than in the step definition (5) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 11449 doesn't seem to be define in the database( WARNING : type of input 2 of step 11452 doesn't seem to be define in the database( WARNING : output 1 of step 11449 have datatype=2 whereas input 1 of step 11453 have datatype=7 WARNING : type of output 2 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11454 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11456 doesn't seem to be define in the database( WARNING : type of output 1 of step 11456 doesn't seem to be define in the database( WARNING : type of input 3 of step 11455 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11456 have datatype=10 whereas input 3 of step 11458 have datatype=6 WARNING : type of input 5 of step 11458 doesn't seem to be define in the database( WARNING : output 0 of step 11477 have datatype=11 whereas input 5 of step 11458 have datatype=None WARNING : output 0 of step 11456 have datatype=10 whereas input 0 of step 11477 have datatype=18 WARNING : type of input 2 of step 11478 doesn't seem to be define in the database( WARNING : output 1 of step 11454 have datatype=7 whereas input 2 of step 11478 have datatype=None WARNING : type of output 3 of step 11478 doesn't seem to be define in the database( WARNING : type of input 2 of step 11456 doesn't seem to be define in the database( WARNING : output 0 of step 11453 have datatype=1 whereas input 0 of step 11454 have datatype=2 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=29021689 AND mptpi.`type`=3726 To do Qualite : 0.006393380076347374 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P29021691_29-11-2025_09_39_18.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 29021691 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11449 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11452 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 11452 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11453 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11453 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11478 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11478 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11455 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11455 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11458 send_mail_cod have less inputs used (3) than in the step definition (5) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 11449 doesn't seem to be define in the database( WARNING : type of input 2 of step 11452 doesn't seem to be define in the database( WARNING : output 1 of step 11449 have datatype=2 whereas input 1 of step 11453 have datatype=7 WARNING : type of output 2 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11454 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11456 doesn't seem to be define in the database( WARNING : type of output 1 of step 11456 doesn't seem to be define in the database( WARNING : type of input 3 of step 11455 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11456 have datatype=10 whereas input 3 of step 11458 have datatype=6 WARNING : type of input 5 of step 11458 doesn't seem to be define in the database( WARNING : output 0 of step 11477 have datatype=11 whereas input 5 of step 11458 have datatype=None WARNING : output 0 of step 11456 have datatype=10 whereas input 0 of step 11477 have datatype=18 WARNING : type of input 2 of step 11478 doesn't seem to be define in the database( WARNING : output 1 of step 11454 have datatype=7 whereas input 2 of step 11478 have datatype=None WARNING : type of output 3 of step 11478 doesn't seem to be define in the database( WARNING : type of input 2 of step 11456 doesn't seem to be define in the database( WARNING : output 0 of step 11453 have datatype=1 whereas input 0 of step 11454 have datatype=2 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=29021691 AND mptpi.`type`=3726 To do Qualite : 0.08066464605610273 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P29023311_29-11-2025_12_35_27.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 29023311 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11449 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11452 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 11452 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11453 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11453 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11478 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11478 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11455 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11455 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11458 send_mail_cod have less inputs used (3) than in the step definition (5) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 11449 doesn't seem to be define in the database( WARNING : type of input 2 of step 11452 doesn't seem to be define in the database( WARNING : output 1 of step 11449 have datatype=2 whereas input 1 of step 11453 have datatype=7 WARNING : type of output 2 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11454 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11456 doesn't seem to be define in the database( WARNING : type of output 1 of step 11456 doesn't seem to be define in the database( WARNING : type of input 3 of step 11455 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11456 have datatype=10 whereas input 3 of step 11458 have datatype=6 WARNING : type of input 5 of step 11458 doesn't seem to be define in the database( WARNING : output 0 of step 11477 have datatype=11 whereas input 5 of step 11458 have datatype=None WARNING : output 0 of step 11456 have datatype=10 whereas input 0 of step 11477 have datatype=18 WARNING : type of input 2 of step 11478 doesn't seem to be define in the database( WARNING : output 1 of step 11454 have datatype=7 whereas input 2 of step 11478 have datatype=None WARNING : type of output 3 of step 11478 doesn't seem to be define in the database( WARNING : type of input 2 of step 11456 doesn't seem to be define in the database( WARNING : output 0 of step 11453 have datatype=1 whereas input 0 of step 11454 have datatype=2 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=29023311 AND mptpi.`type`=3726 To do Qualite : 0.04603444894547325 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P29024015_29-11-2025_14_15_26.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 29024015 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`=29024015 AND mptpi.`type`=3594 To do Qualite : 0.03066874466514039 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P29024017_29-11-2025_14_11_19.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 29024017 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11449 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11452 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 11452 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11453 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11453 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11478 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11478 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11455 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11455 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11458 send_mail_cod have less inputs used (3) than in the step definition (5) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 11449 doesn't seem to be define in the database( WARNING : type of input 2 of step 11452 doesn't seem to be define in the database( WARNING : output 1 of step 11449 have datatype=2 whereas input 1 of step 11453 have datatype=7 WARNING : type of output 2 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11454 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11456 doesn't seem to be define in the database( WARNING : type of output 1 of step 11456 doesn't seem to be define in the database( WARNING : type of input 3 of step 11455 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11456 have datatype=10 whereas input 3 of step 11458 have datatype=6 WARNING : type of input 5 of step 11458 doesn't seem to be define in the database( WARNING : output 0 of step 11477 have datatype=11 whereas input 5 of step 11458 have datatype=None WARNING : output 0 of step 11456 have datatype=10 whereas input 0 of step 11477 have datatype=18 WARNING : type of input 2 of step 11478 doesn't seem to be define in the database( WARNING : output 1 of step 11454 have datatype=7 whereas input 2 of step 11478 have datatype=None WARNING : type of output 3 of step 11478 doesn't seem to be define in the database( WARNING : type of input 2 of step 11456 doesn't seem to be define in the database( WARNING : output 0 of step 11453 have datatype=1 whereas input 0 of step 11454 have datatype=2 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=29024017 AND mptpi.`type`=3726 To do NUMBER BATCH : 0 # DISPLAY ALL COLLECTED DATA : {'29112025': {'nb_upload': 15, '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 [1396887253, 1396887216, 1396886679, 1396886621, 1396886562, 1396886506, 1396886496, 1396886493, 1396886458, 1396886455, 1396886451, 1396886449, 1396886447, 1396886444, 1396886437] Looping around the photos to save general results len do output : 1 /29024015Didn'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, '4141163') ('3318', '29024015', '1396887253', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396887216', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886679', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886621', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886562', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886506', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886496', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886493', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886458', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886455', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886451', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886449', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886447', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886444', None, None, None, None, None, '4141163') ('3318', None, None, None, None, None, None, None, '4141163') ('3318', '29024015', '1396886437', None, None, None, None, None, '4141163') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 16 time used for this insertion : 0.01663827896118164 save_final save missing photos in datou_result : time spend for datou_step_exec : 0.8756005764007568 time spend to save output : 0.016849994659423828 total time spend for step 10 : 0.8924505710601807 caffe_path_current : About to save ! 2 After save, about to update current ! ret : 2 len(input) + len(total_photo_id_missing) : 15 set_done_treatment 149.23user 120.45system 5:12.72elapsed 86%CPU (0avgtext+0avgdata 5302156maxresident)k 2167200inputs+145856outputs (7717major+13493501minor)pagefaults 0swaps