python /home/admin/mtr/script_for_cron.py -j default -m 20 -a 'python3 ~/workarea/git/Velours/python/prod/datou.py -j batch_current -a 4741' -s test_cod -M 0 -S 0 -U 100,80,95 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/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', '/home/admin/workarea/git/apy', '/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 : 752055 load datou : 4741 # 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 13156 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 13160 mask_detect have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 13160 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 13158 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 13158 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 13157 crop_condition is not consistent : 4 used against 2 in the step definition ! WARNING : number of outputs for step 13157 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 13161 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 13159 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 13159 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! 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 13156 doesn't seem to be define in the database( WARNING : type of input 2 of step 13157 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 13161 doesn't seem to be define in the database( WARNING : type of input 3 of step 13159 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 13157 doesn't seem to be define in the database( WARNING : output 0 of step 13163 have datatype=6 whereas input 2 of step 13157 have datatype=None WARNING : type of input 2 of step 13157 doesn't seem to be define in the database( WARNING : output 0 of step 13162 have datatype=6 whereas input 2 of step 13157 have datatype=None We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 13161 have datatype=10 whereas input 3 of step 13164 have datatype=6 WARNING : output 0 of step 13161 have datatype=10 whereas input 0 of step 13166 have datatype=18 WARNING : type of input 5 of step 13164 doesn't seem to be define in the database( WARNING : output 0 of step 13166 have datatype=11 whereas input 5 of step 13164 have datatype=None WARNING : type of input 2 of step 13157 doesn't seem to be define in the database( WARNING : output 1 of step 13158 have datatype=7 whereas input 2 of step 13157 have datatype=None WARNING : type of output 3 of step 13157 doesn't seem to be define in the database( WARNING : type of input 3 of step 13161 doesn't seem to be define in the database( WARNING : type of output 2 of step 13160 doesn't seem to be define in the database( WARNING : type of input 1 of step 13163 doesn't seem to be define in the database( WARNING : type of output 2 of step 13160 doesn't seem to be define in the database( WARNING : type of input 1 of step 13162 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 ? 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 ? 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 ? 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 ? [ (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 ? 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 ? 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 : (5732, 'mask_refus_amiens_050123', 16384, 25088, 'mask_refus_amiens_050123', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 3, datetime.datetime(2023, 1, 5, 13, 23, 59), datetime.datetime(2023, 1, 5, 13, 23, 59)) FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (5972, 'learn_entrant_syctomXV_111023', 16384, 25088, 'learn_entrant_syctomXV_111023', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 3, datetime.datetime(2023, 10, 11, 15, 57, 35), datetime.datetime(2023, 10, 11, 15, 57, 35)) load thcls load THCL from format json or kwargs add thcl : 3453 in CacheModelConfig load THCL from format json or kwargs add thcl : 3783 in CacheModelConfig load pdts add pdt : 5732 in CacheModelConfig add pdt : 5972 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 : 4741, datou_cur_ids : ['3953017'] with mtr_portfolio_ids : ['27873696'] and first list_photo_ids : [] new path : /proc/752055/ 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 ! 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 13156 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 13160 mask_detect have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 13160 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 13158 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 13158 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 13157 crop_condition is not consistent : 4 used against 2 in the step definition ! WARNING : number of outputs for step 13157 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 13161 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 13159 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 13159 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! 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 13156 doesn't seem to be define in the database( WARNING : type of input 2 of step 13157 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 13161 doesn't seem to be define in the database( WARNING : type of input 3 of step 13159 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 13157 doesn't seem to be define in the database( WARNING : output 0 of step 13163 have datatype=6 whereas input 2 of step 13157 have datatype=None WARNING : type of input 2 of step 13157 doesn't seem to be define in the database( WARNING : output 0 of step 13162 have datatype=6 whereas input 2 of step 13157 have datatype=None We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 13161 have datatype=10 whereas input 3 of step 13164 have datatype=6 WARNING : output 0 of step 13161 have datatype=10 whereas input 0 of step 13166 have datatype=18 WARNING : type of input 5 of step 13164 doesn't seem to be define in the database( WARNING : output 0 of step 13166 have datatype=11 whereas input 5 of step 13164 have datatype=None WARNING : type of input 2 of step 13157 doesn't seem to be define in the database( WARNING : output 1 of step 13158 have datatype=7 whereas input 2 of step 13157 have datatype=None WARNING : type of output 3 of step 13157 doesn't seem to be define in the database( WARNING : type of input 3 of step 13161 doesn't seem to be define in the database( WARNING : type of output 2 of step 13160 doesn't seem to be define in the database( WARNING : type of input 1 of step 13163 doesn't seem to be define in the database( WARNING : type of output 2 of step 13160 doesn't seem to be define in the database( WARNING : type of input 1 of step 13162 doesn't seem to be define in the database( DataTypes for each output/input checked ! List Step Type Loaded in datou : mask_detect, mask_detect, blur_detection, brightness, rle_unique_nms_with_priority, crop_condition, ventilate_hashtags_in_portfolio, final, velours_tree, send_mail_cod, split_time_score over limit max, limiting to limit_max 30 list_input_json : [] origin We have 1 , BFBFBFBFBFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 5 ; length of list_pids : 5 ; length of list_args : 5 time to download the photos : 1.7130606174468994 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 : 11 step1:mask_detect Fri Oct 17 10:26:20 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec 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 : 5485 max_wait_temp : 1 max_wait : 0 gpu_flag : 0 2025-10-17 10:26:23.415583: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2025-10-17 10:26:23.442521: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493010000 Hz 2025-10-17 10:26:23.444760: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f9838000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-10-17 10:26:23.444819: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-10-17 10:26:23.448944: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-10-17 10:26:23.598940: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x55f6bd0 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-10-17 10:26:23.599037: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-10-17 10:26:23.600681: 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 2025-10-17 10:26:23.601502: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-10-17 10:26:23.604988: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-10-17 10:26:23.607257: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-10-17 10:26:23.608212: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-10-17 10:26:23.610847: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-10-17 10:26:23.612268: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-10-17 10:26:23.616914: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-10-17 10:26:23.618186: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-10-17 10:26:23.618264: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-10-17 10:26:23.618969: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-10-17 10:26:23.618988: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-10-17 10:26:23.618997: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-10-17 10:26:23.620071: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 5013 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. 2025-10-17 10:26:24.129841: 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 2025-10-17 10:26:24.129957: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-10-17 10:26:24.129989: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-10-17 10:26:24.130018: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-10-17 10:26:24.130049: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-10-17 10:26:24.130079: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-10-17 10:26:24.130107: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-10-17 10:26:24.130139: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-10-17 10:26:24.131850: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-10-17 10:26:24.133043: 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 2025-10-17 10:26:24.133078: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-10-17 10:26:24.133094: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-10-17 10:26:24.133119: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-10-17 10:26:24.133135: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-10-17 10:26:24.133149: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-10-17 10:26:24.133162: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-10-17 10:26:24.133177: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-10-17 10:26:24.134180: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-10-17 10:26:24.134215: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-10-17 10:26:24.134224: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-10-17 10:26:24.134232: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-10-17 10:26:24.135260: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 5013 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 : thcl3783 thcls : [{'id': 3783, 'mtr_user_id': 31, 'name': 'learn_entrant_syctomXV_111023', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,sac,textiles,verre,organique,dasri,masque,encombrant,autre_emballage,autre_non_emballage,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 4853, 'photo_desc_type': 5972, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0,0,0'}] thcl {'id': 3783, 'mtr_user_id': 31, 'name': 'learn_entrant_syctomXV_111023', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,sac,textiles,verre,organique,dasri,masque,encombrant,autre_emballage,autre_non_emballage,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 4853, 'photo_desc_type': 5972, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0,0,0'} Update svm_hashtag_type_desc : 5972 FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (5972, 'learn_entrant_syctomXV_111023', 16384, 25088, 'learn_entrant_syctomXV_111023', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 3, datetime.datetime(2023, 10, 11, 15, 57, 35), datetime.datetime(2023, 10, 11, 15, 57, 35)) {'thcl': {'id': 3783, 'mtr_user_id': 31, 'name': 'learn_entrant_syctomXV_111023', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,sac,textiles,verre,organique,dasri,masque,encombrant,autre_emballage,autre_non_emballage,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 4853, 'photo_desc_type': 5972, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0,0,0'}, 'list_hashtags': ['background', 'sac', 'textiles', 'verre', 'organique', 'dasri', 'masque', 'encombrant', 'autre_emballage', 'autre_non_emballage', 'environnement'], 'list_hashtags_csv': 'background,sac,textiles,verre,organique,dasri,masque,encombrant,autre_emballage,autre_non_emballage,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 4853, 'svm_hashtag_type_desc': 5972, 'photo_desc_type': 5972, 'pb_hashtag_id_or_classifier': 0} list_class_names : ['background', 'sac', 'textiles', 'verre', 'organique', 'dasri', 'masque', 'encombrant', 'autre_emballage', 'autre_non_emballage', '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_entrant_syctomXV_111023 NUM_CLASSES 11 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_entrant_syctomXV_111023 model_type : mask_rcnn list file need : ['mask_model.h5'] file exist in s3 : ['mask_model.h5'] file manque in s3 : [] 2025-10-17 10:26:35.278158: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-10-17 10:26:35.475191: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 local folder : /data/models_weight/learn_entrant_syctomXV_111023 /data/models_weight/learn_entrant_syctomXV_111023/mask_model.h5 size_local : 256052544 size in s3 : 256052544 create time local : 2023-10-26 16:36:43 create time in s3 : 2023-10-11 13:57:17 mask_model.h5 already exist and didn't need to update list_images length : 5 NEW PHOTO Processing 1 images image shape: (4160, 3120, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 19) min: 0.00000 max: 4160.00000 nb d'objets trouves : 8 NEW PHOTO Processing 1 images image shape: (4160, 3120, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 150.91250 image_metas shape: (1, 19) min: 0.00000 max: 4160.00000 nb d'objets trouves : 18 NEW PHOTO Processing 1 images image shape: (4160, 3120, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 19) min: 0.00000 max: 4160.00000 nb d'objets trouves : 9 NEW PHOTO Processing 1 images image shape: (4160, 3120, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 19) min: 0.00000 max: 4160.00000 nb d'objets trouves : 9 NEW PHOTO Processing 1 images image shape: (4160, 3120, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 143.35000 image_metas shape: (1, 19) min: 0.00000 max: 4160.00000 nb d'objets trouves : 7 Detection mask done ! Trying to reset tf kernel 752215 begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 5485 tf kernel not reseted sub process len(results) : 5 len(list_Values) 0 None max_time_sub_proc : 3600 parent process len(results) : 5 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 : 10774 list_Values should be empty [] To do loadFromThcl(), then load ParamDescType : thcl3783 Catched exception ! Connect or reconnect ! thcls : [{'id': 3783, 'mtr_user_id': 31, 'name': 'learn_entrant_syctomXV_111023', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,sac,textiles,verre,organique,dasri,masque,encombrant,autre_emballage,autre_non_emballage,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 4853, 'photo_desc_type': 5972, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0,0,0'}] thcl {'id': 3783, 'mtr_user_id': 31, 'name': 'learn_entrant_syctomXV_111023', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,sac,textiles,verre,organique,dasri,masque,encombrant,autre_emballage,autre_non_emballage,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 4853, 'photo_desc_type': 5972, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0,0,0'} Update svm_hashtag_type_desc : 5972 ['background', 'sac', 'textiles', 'verre', 'organique', 'dasri', 'masque', 'encombrant', 'autre_emballage', 'autre_non_emballage', 'environnement'] time for calcul the mask position with numpy : 0.014619588851928711 nb_pixel_total : 419269 time to create 1 rle with new method : 0.028168916702270508 length of segment : 891 time for calcul the mask position with numpy : 0.0008363723754882812 nb_pixel_total : 30965 time to create 1 rle with old method : 0.0367741584777832 length of segment : 251 time for calcul the mask position with numpy : 0.03362441062927246 nb_pixel_total : 1155521 time to create 1 rle with new method : 0.05297112464904785 length of segment : 2155 time for calcul the mask position with numpy : 0.0015594959259033203 nb_pixel_total : 75965 time to create 1 rle with old method : 0.09189796447753906 length of segment : 720 time for calcul the mask position with numpy : 0.00037670135498046875 nb_pixel_total : 4201 time to create 1 rle with old method : 0.008632421493530273 length of segment : 70 time for calcul the mask position with numpy : 0.0034155845642089844 nb_pixel_total : 120852 time to create 1 rle with old method : 0.14603662490844727 length of segment : 512 time for calcul the mask position with numpy : 0.0008416175842285156 nb_pixel_total : 30464 time to create 1 rle with old method : 0.03635120391845703 length of segment : 285 time for calcul the mask position with numpy : 0.0005304813385009766 nb_pixel_total : 22956 time to create 1 rle with old method : 0.03040313720703125 length of segment : 251 time for calcul the mask position with numpy : 0.0012540817260742188 nb_pixel_total : 52442 time to create 1 rle with old method : 0.06114602088928223 length of segment : 373 time for calcul the mask position with numpy : 0.0002276897430419922 nb_pixel_total : 7367 time to create 1 rle with old method : 0.008925676345825195 length of segment : 169 time for calcul the mask position with numpy : 0.0015704631805419922 nb_pixel_total : 28693 time to create 1 rle with old method : 0.039795875549316406 length of segment : 233 time for calcul the mask position with numpy : 0.0012218952178955078 nb_pixel_total : 46297 time to create 1 rle with old method : 0.05695343017578125 length of segment : 395 time for calcul the mask position with numpy : 0.0013775825500488281 nb_pixel_total : 4004 time to create 1 rle with old method : 0.00520634651184082 length of segment : 87 time for calcul the mask position with numpy : 0.002123594284057617 nb_pixel_total : 83650 time to create 1 rle with old method : 0.0977792739868164 length of segment : 328 time for calcul the mask position with numpy : 0.004246711730957031 nb_pixel_total : 68028 time to create 1 rle with old method : 0.07929444313049316 length of segment : 564 time for calcul the mask position with numpy : 0.0016293525695800781 nb_pixel_total : 104811 time to create 1 rle with old method : 0.12383174896240234 length of segment : 445 time for calcul the mask position with numpy : 0.004261016845703125 nb_pixel_total : 238436 time to create 1 rle with new method : 0.008727788925170898 length of segment : 549 time for calcul the mask position with numpy : 0.0031652450561523438 nb_pixel_total : 26818 time to create 1 rle with old method : 0.036604881286621094 length of segment : 326 time for calcul the mask position with numpy : 0.0009889602661132812 nb_pixel_total : 33379 time to create 1 rle with old method : 0.03954458236694336 length of segment : 249 time for calcul the mask position with numpy : 0.0007767677307128906 nb_pixel_total : 23627 time to create 1 rle with old method : 0.03104567527770996 length of segment : 287 time for calcul the mask position with numpy : 0.018461942672729492 nb_pixel_total : 12805 time to create 1 rle with old method : 0.0192563533782959 length of segment : 443 time for calcul the mask position with numpy : 0.00041556358337402344 nb_pixel_total : 13532 time to create 1 rle with old method : 0.01698756217956543 length of segment : 143 time for calcul the mask position with numpy : 0.0006897449493408203 nb_pixel_total : 16389 time to create 1 rle with old method : 0.01986980438232422 length of segment : 164 time for calcul the mask position with numpy : 0.0013709068298339844 nb_pixel_total : 34075 time to create 1 rle with old method : 0.04114079475402832 length of segment : 174 time for calcul the mask position with numpy : 0.0008404254913330078 nb_pixel_total : 45948 time to create 1 rle with old method : 0.05498003959655762 length of segment : 574 time for calcul the mask position with numpy : 0.0004279613494873047 nb_pixel_total : 16305 time to create 1 rle with old method : 0.019786357879638672 length of segment : 130 time for calcul the mask position with numpy : 0.01251840591430664 nb_pixel_total : 860577 time to create 1 rle with new method : 0.028412342071533203 length of segment : 1362 time for calcul the mask position with numpy : 0.0008823871612548828 nb_pixel_total : 63836 time to create 1 rle with old method : 0.07436323165893555 length of segment : 379 time for calcul the mask position with numpy : 0.0003924369812011719 nb_pixel_total : 27562 time to create 1 rle with old method : 0.031552791595458984 length of segment : 275 time for calcul the mask position with numpy : 0.0013353824615478516 nb_pixel_total : 92440 time to create 1 rle with old method : 0.12201571464538574 length of segment : 637 time for calcul the mask position with numpy : 0.0031859874725341797 nb_pixel_total : 177126 time to create 1 rle with new method : 0.009238243103027344 length of segment : 475 time for calcul the mask position with numpy : 0.0002110004425048828 nb_pixel_total : 6617 time to create 1 rle with old method : 0.009481191635131836 length of segment : 67 time for calcul the mask position with numpy : 0.0018563270568847656 nb_pixel_total : 19218 time to create 1 rle with old method : 0.02318716049194336 length of segment : 216 time for calcul the mask position with numpy : 0.0026149749755859375 nb_pixel_total : 168700 time to create 1 rle with new method : 0.006669521331787109 length of segment : 484 time for calcul the mask position with numpy : 0.0030298233032226562 nb_pixel_total : 182879 time to create 1 rle with new method : 0.006448507308959961 length of segment : 482 time for calcul the mask position with numpy : 0.0004172325134277344 nb_pixel_total : 14706 time to create 1 rle with old method : 0.017930030822753906 length of segment : 106 time for calcul the mask position with numpy : 0.0011129379272460938 nb_pixel_total : 45711 time to create 1 rle with old method : 0.05491352081298828 length of segment : 156 time for calcul the mask position with numpy : 0.0009586811065673828 nb_pixel_total : 42479 time to create 1 rle with old method : 0.04958605766296387 length of segment : 207 time for calcul the mask position with numpy : 0.0008587837219238281 nb_pixel_total : 23470 time to create 1 rle with old method : 0.02783799171447754 length of segment : 264 time for calcul the mask position with numpy : 0.026781558990478516 nb_pixel_total : 771605 time to create 1 rle with new method : 0.06875276565551758 length of segment : 902 time for calcul the mask position with numpy : 0.0009975433349609375 nb_pixel_total : 25704 time to create 1 rle with old method : 0.03126263618469238 length of segment : 372 time for calcul the mask position with numpy : 0.0003330707550048828 nb_pixel_total : 16063 time to create 1 rle with old method : 0.019912242889404297 length of segment : 242 time for calcul the mask position with numpy : 0.00015163421630859375 nb_pixel_total : 6970 time to create 1 rle with old method : 0.009049654006958008 length of segment : 48 time for calcul the mask position with numpy : 0.0009188652038574219 nb_pixel_total : 39006 time to create 1 rle with old method : 0.05137038230895996 length of segment : 235 time for calcul the mask position with numpy : 1.3055179119110107 nb_pixel_total : 5680578 time to create 1 rle with new method : 0.4749901294708252 length of segment : 2602 time for calcul the mask position with numpy : 0.16670680046081543 nb_pixel_total : 1949802 time to create 1 rle with new method : 0.2367537021636963 length of segment : 1870 time for calcul the mask position with numpy : 0.046933889389038086 nb_pixel_total : 2502392 time to create 1 rle with new method : 0.5665750503540039 length of segment : 4190 time for calcul the mask position with numpy : 0.02622079849243164 nb_pixel_total : 1984184 time to create 1 rle with new method : 0.1809699535369873 length of segment : 1032 time for calcul the mask position with numpy : 0.025954008102416992 nb_pixel_total : 1533489 time to create 1 rle with new method : 0.2058258056640625 length of segment : 2319 time for calcul the mask position with numpy : 0.23553228378295898 nb_pixel_total : 3341503 time to create 1 rle with new method : 0.43376588821411133 length of segment : 1793 time for calcul the mask position with numpy : 0.14816951751708984 nb_pixel_total : 3793925 time to create 1 rle with new method : 0.35286951065063477 length of segment : 2244 time spent for convertir_results : 15.867489099502563 Inside saveOutput : final : False verbose : 0 eke 12-6-18 : saveMask need to be cleaned for new output ! Number saved : None batch 1 Loaded 51 chid ids of type : 4854 Number RLEs to save : 0 save missing photos in datou_result : time spend for datou_step_exec : 61.32317924499512 time spend to save output : 0.47270679473876953 total time spend for step 1 : 61.79588603973389 step2:mask_detect Fri Oct 17 10:27:22 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 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 mask_detect ! save_polygon : True begin detect begin to check gpu status inside check gpu memory l 3637 free memory gpu now : 10774 max_wait_temp : 1 max_wait : 0 gpu_flag : 0 2025-10-17 10:27:25.093095: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2025-10-17 10:27:25.122622: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493010000 Hz 2025-10-17 10:27:25.124578: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f9838000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-10-17 10:27:25.124629: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-10-17 10:27:25.128607: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-10-17 10:27:25.390170: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x6d8ed50 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-10-17 10:27:25.390228: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-10-17 10:27:25.392020: 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 2025-10-17 10:27:25.397831: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-10-17 10:27:25.402509: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-10-17 10:27:25.405816: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-10-17 10:27:25.406999: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-10-17 10:27:25.411249: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-10-17 10:27:25.412961: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-10-17 10:27:25.420371: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-10-17 10:27:25.422218: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-10-17 10:27:25.422362: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-10-17 10:27:25.423306: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-10-17 10:27:25.423325: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-10-17 10:27:25.423336: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-10-17 10:27:25.425077: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 9985 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. 2025-10-17 10:27:25.662943: 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 2025-10-17 10:27:25.663067: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-10-17 10:27:25.663087: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-10-17 10:27:25.663105: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-10-17 10:27:25.663121: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-10-17 10:27:25.663137: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-10-17 10:27:25.663154: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-10-17 10:27:25.663171: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-10-17 10:27:25.664529: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-10-17 10:27:25.665850: 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 2025-10-17 10:27:25.665909: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-10-17 10:27:25.665927: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-10-17 10:27:25.665943: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-10-17 10:27:25.665959: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-10-17 10:27:25.665975: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-10-17 10:27:25.665990: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-10-17 10:27:25.666006: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-10-17 10:27:25.667347: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-10-17 10:27:25.667383: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-10-17 10:27:25.667392: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-10-17 10:27:25.667400: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-10-17 10:27:25.668782: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 9985 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 : thcl3453 thcls : [{'id': 3453, 'mtr_user_id': 31, 'name': 'mask_refus_amiens_050123', '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': 4485, 'photo_desc_type': 5732, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'}] thcl {'id': 3453, 'mtr_user_id': 31, 'name': 'mask_refus_amiens_050123', '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': 4485, 'photo_desc_type': 5732, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'} Update svm_hashtag_type_desc : 5732 FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (5732, 'mask_refus_amiens_050123', 16384, 25088, 'mask_refus_amiens_050123', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 3, datetime.datetime(2023, 1, 5, 13, 23, 59), datetime.datetime(2023, 1, 5, 13, 23, 59)) {'thcl': {'id': 3453, 'mtr_user_id': 31, 'name': 'mask_refus_amiens_050123', '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': 4485, 'photo_desc_type': 5732, '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': 4485, 'svm_hashtag_type_desc': 5732, 'photo_desc_type': 5732, '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 mask_refus_amiens_050123 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 : mask_refus_amiens_050123 model_type : mask_rcnn list file need : ['mask_model.h5'] file exist in s3 : ['mask_model.h5'] file manque in s3 : [] 2025-10-17 10:27:38.610195: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-10-17 10:27:38.801666: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 local folder : /data/models_weight/mask_refus_amiens_050123 /data/models_weight/mask_refus_amiens_050123/mask_model.h5 size_local : 256009536 size in s3 : 256009536 create time local : 2023-01-05 13:44:07 create time in s3 : 2023-01-05 12:23:52 mask_model.h5 already exist and didn't need to update list_images length : 5 NEW PHOTO Processing 1 images image shape: (4160, 3120, 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: 4160.00000 nb d'objets trouves : 60 NEW PHOTO Processing 1 images image shape: (4160, 3120, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 150.91250 image_metas shape: (1, 17) min: 0.00000 max: 4160.00000 nb d'objets trouves : 45 NEW PHOTO Processing 1 images image shape: (4160, 3120, 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: 4160.00000 nb d'objets trouves : 63 NEW PHOTO Processing 1 images image shape: (4160, 3120, 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: 4160.00000 nb d'objets trouves : 61 NEW PHOTO Processing 1 images image shape: (4160, 3120, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 143.35000 image_metas shape: (1, 17) min: 0.00000 max: 4160.00000 nb d'objets trouves : 7 Detection mask done ! Trying to reset tf kernel 753986 begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 5485 tf kernel not reseted sub process len(results) : 5 len(list_Values) 0 None max_time_sub_proc : 3600 parent process len(results) : 5 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 : 10774 list_Values should be empty [] To do loadFromThcl(), then load ParamDescType : thcl3453 Catched exception ! Connect or reconnect ! thcls : [{'id': 3453, 'mtr_user_id': 31, 'name': 'mask_refus_amiens_050123', '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': 4485, 'photo_desc_type': 5732, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'}] thcl {'id': 3453, 'mtr_user_id': 31, 'name': 'mask_refus_amiens_050123', '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': 4485, 'photo_desc_type': 5732, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'} Update svm_hashtag_type_desc : 5732 ['background', 'papier', 'carton', 'metal', 'pet_clair', 'autre', 'pehd', 'pet_fonce', 'environnement'] time for calcul the mask position with numpy : 0.004564046859741211 nb_pixel_total : 113974 time to create 1 rle with old method : 0.14218783378601074 length of segment : 455 time for calcul the mask position with numpy : 0.00394439697265625 nb_pixel_total : 113343 time to create 1 rle with old method : 0.13442659378051758 length of segment : 556 time for calcul the mask position with numpy : 0.003350496292114258 nb_pixel_total : 171722 time to create 1 rle with new method : 0.013902902603149414 length of segment : 591 time for calcul the mask position with numpy : 0.01587986946105957 nb_pixel_total : 630987 time to create 1 rle with new method : 0.06355619430541992 length of segment : 870 time for calcul the mask position with numpy : 0.005600690841674805 nb_pixel_total : 322083 time to create 1 rle with new method : 0.015479803085327148 length of segment : 713 time for calcul the mask position with numpy : 0.002965688705444336 nb_pixel_total : 153739 time to create 1 rle with new method : 0.007934808731079102 length of segment : 558 time for calcul the mask position with numpy : 0.001493215560913086 nb_pixel_total : 59963 time to create 1 rle with old method : 0.07152533531188965 length of segment : 273 time for calcul the mask position with numpy : 0.008296966552734375 nb_pixel_total : 447091 time to create 1 rle with new method : 0.024323701858520508 length of segment : 797 time for calcul the mask position with numpy : 0.010402202606201172 nb_pixel_total : 550076 time to create 1 rle with new method : 0.02730393409729004 length of segment : 742 time for calcul the mask position with numpy : 0.0017566680908203125 nb_pixel_total : 73901 time to create 1 rle with old method : 0.08805441856384277 length of segment : 271 time for calcul the mask position with numpy : 0.0040225982666015625 nb_pixel_total : 180686 time to create 1 rle with new method : 0.01139211654663086 length of segment : 510 time for calcul the mask position with numpy : 0.00033593177795410156 nb_pixel_total : 11597 time to create 1 rle with old method : 0.013852834701538086 length of segment : 118 time for calcul the mask position with numpy : 0.0012602806091308594 nb_pixel_total : 66020 time to create 1 rle with old method : 0.07808041572570801 length of segment : 391 time for calcul the mask position with numpy : 0.0006890296936035156 nb_pixel_total : 34178 time to create 1 rle with old method : 0.040813446044921875 length of segment : 277 time for calcul the mask position with numpy : 0.0027642250061035156 nb_pixel_total : 162900 time to create 1 rle with new method : 0.007231473922729492 length of segment : 494 time for calcul the mask position with numpy : 0.0007944107055664062 nb_pixel_total : 31132 time to create 1 rle with old method : 0.04418611526489258 length of segment : 214 time for calcul the mask position with numpy : 0.0009107589721679688 nb_pixel_total : 27193 time to create 1 rle with old method : 0.03341054916381836 length of segment : 245 time for calcul the mask position with numpy : 0.0013430118560791016 nb_pixel_total : 63504 time to create 1 rle with old method : 0.07569313049316406 length of segment : 394 time for calcul the mask position with numpy : 0.0006396770477294922 nb_pixel_total : 24964 time to create 1 rle with old method : 0.030309200286865234 length of segment : 192 time for calcul the mask position with numpy : 0.010504961013793945 nb_pixel_total : 372180 time to create 1 rle with new method : 0.03271651268005371 length of segment : 1008 time for calcul the mask position with numpy : 0.00434422492980957 nb_pixel_total : 225028 time to create 1 rle with new method : 0.011193990707397461 length of segment : 696 time for calcul the mask position with numpy : 0.0039479732513427734 nb_pixel_total : 137731 time to create 1 rle with old method : 0.16485905647277832 length of segment : 821 time for calcul the mask position with numpy : 0.030134916305541992 nb_pixel_total : 1658962 time to create 1 rle with new method : 0.10049700736999512 length of segment : 2147 time for calcul the mask position with numpy : 0.004127979278564453 nb_pixel_total : 271075 time to create 1 rle with new method : 0.010165214538574219 length of segment : 533 time for calcul the mask position with numpy : 0.006852626800537109 nb_pixel_total : 332359 time to create 1 rle with new method : 0.01887989044189453 length of segment : 835 time for calcul the mask position with numpy : 0.0009088516235351562 nb_pixel_total : 40951 time to create 1 rle with old method : 0.049355506896972656 length of segment : 206 time for calcul the mask position with numpy : 0.007620096206665039 nb_pixel_total : 406832 time to create 1 rle with new method : 0.02183246612548828 length of segment : 1374 time for calcul the mask position with numpy : 0.0021560192108154297 nb_pixel_total : 44573 time to create 1 rle with old method : 0.06548118591308594 length of segment : 390 time for calcul the mask position with numpy : 0.0005497932434082031 nb_pixel_total : 23807 time to create 1 rle with old method : 0.027454137802124023 length of segment : 150 time for calcul the mask position with numpy : 0.0013616085052490234 nb_pixel_total : 62886 time to create 1 rle with old method : 0.07346439361572266 length of segment : 318 time for calcul the mask position with numpy : 0.00606083869934082 nb_pixel_total : 269868 time to create 1 rle with new method : 0.017848968505859375 length of segment : 737 time for calcul the mask position with numpy : 0.001981019973754883 nb_pixel_total : 107537 time to create 1 rle with old method : 0.12152504920959473 length of segment : 377 time for calcul the mask position with numpy : 0.01932835578918457 nb_pixel_total : 677771 time to create 1 rle with new method : 0.07215142250061035 length of segment : 1375 time for calcul the mask position with numpy : 0.0033142566680908203 nb_pixel_total : 177540 time to create 1 rle with new method : 0.009719371795654297 length of segment : 698 time for calcul the mask position with numpy : 0.0009200572967529297 nb_pixel_total : 43906 time to create 1 rle with old method : 0.04961395263671875 length of segment : 290 time for calcul the mask position with numpy : 0.006714582443237305 nb_pixel_total : 323987 time to create 1 rle with new method : 0.022061824798583984 length of segment : 567 time for calcul the mask position with numpy : 0.007645606994628906 nb_pixel_total : 335707 time to create 1 rle with new method : 0.02515435218811035 length of segment : 1081 time for calcul the mask position with numpy : 0.009219646453857422 nb_pixel_total : 315615 time to create 1 rle with new method : 0.030227184295654297 length of segment : 960 time for calcul the mask position with numpy : 0.0011801719665527344 nb_pixel_total : 47174 time to create 1 rle with old method : 0.057047128677368164 length of segment : 250 time for calcul the mask position with numpy : 0.009169816970825195 nb_pixel_total : 300764 time to create 1 rle with new method : 0.03255295753479004 length of segment : 1041 time for calcul the mask position with numpy : 0.00023818016052246094 nb_pixel_total : 8045 time to create 1 rle with old method : 0.009737730026245117 length of segment : 119 time for calcul the mask position with numpy : 0.010109663009643555 nb_pixel_total : 452495 time to create 1 rle with new method : 0.03206467628479004 length of segment : 841 time for calcul the mask position with numpy : 0.0020978450775146484 nb_pixel_total : 90777 time to create 1 rle with old method : 0.10303759574890137 length of segment : 478 time for calcul the mask position with numpy : 0.004823207855224609 nb_pixel_total : 250774 time to create 1 rle with new method : 0.014181852340698242 length of segment : 662 time for calcul the mask position with numpy : 0.010226726531982422 nb_pixel_total : 307605 time to create 1 rle with new method : 0.03744173049926758 length of segment : 1015 time for calcul the mask position with numpy : 0.0054779052734375 nb_pixel_total : 84437 time to create 1 rle with old method : 0.09490704536437988 length of segment : 562 time for calcul the mask position with numpy : 0.0017826557159423828 nb_pixel_total : 97948 time to create 1 rle with old method : 0.10727095603942871 length of segment : 324 time for calcul the mask position with numpy : 0.0044329166412353516 nb_pixel_total : 192584 time to create 1 rle with new method : 0.01349329948425293 length of segment : 769 time for calcul the mask position with numpy : 0.0071370601654052734 nb_pixel_total : 294005 time to create 1 rle with new method : 0.021500349044799805 length of segment : 861 time for calcul the mask position with numpy : 0.002892017364501953 nb_pixel_total : 6749 time to create 1 rle with old method : 0.007963895797729492 length of segment : 52 time for calcul the mask position with numpy : 0.0015904903411865234 nb_pixel_total : 63279 time to create 1 rle with old method : 0.07045173645019531 length of segment : 452 time for calcul the mask position with numpy : 0.0015707015991210938 nb_pixel_total : 80687 time to create 1 rle with old method : 0.0922846794128418 length of segment : 427 time for calcul the mask position with numpy : 0.013269901275634766 nb_pixel_total : 790774 time to create 1 rle with new method : 0.030469894409179688 length of segment : 1560 time for calcul the mask position with numpy : 0.0034661293029785156 nb_pixel_total : 176543 time to create 1 rle with new method : 0.01045083999633789 length of segment : 647 time for calcul the mask position with numpy : 0.0081024169921875 nb_pixel_total : 416559 time to create 1 rle with new method : 0.020786285400390625 length of segment : 1166 time for calcul the mask position with numpy : 0.014187812805175781 nb_pixel_total : 596176 time to create 1 rle with new method : 0.03410649299621582 length of segment : 1636 time for calcul the mask position with numpy : 0.0005924701690673828 nb_pixel_total : 14904 time to create 1 rle with old method : 0.017420053482055664 length of segment : 284 time for calcul the mask position with numpy : 0.0017178058624267578 nb_pixel_total : 95377 time to create 1 rle with old method : 0.10950803756713867 length of segment : 568 time for calcul the mask position with numpy : 0.006829023361206055 nb_pixel_total : 415050 time to create 1 rle with new method : 0.018496274948120117 length of segment : 1228 time for calcul the mask position with numpy : 0.00713038444519043 nb_pixel_total : 117 time to create 1 rle with old method : 0.00020551681518554688 length of segment : 16 time for calcul the mask position with numpy : 0.024028539657592773 nb_pixel_total : 1559342 time to create 1 rle with new method : 0.07638788223266602 length of segment : 1955 time for calcul the mask position with numpy : 0.0013027191162109375 nb_pixel_total : 68176 time to create 1 rle with old method : 0.07847857475280762 length of segment : 393 time for calcul the mask position with numpy : 0.002680063247680664 nb_pixel_total : 131954 time to create 1 rle with old method : 0.1551671028137207 length of segment : 532 time for calcul the mask position with numpy : 0.0064165592193603516 nb_pixel_total : 341713 time to create 1 rle with new method : 0.01690077781677246 length of segment : 754 time for calcul the mask position with numpy : 0.0016276836395263672 nb_pixel_total : 69064 time to create 1 rle with old method : 0.07977080345153809 length of segment : 266 time for calcul the mask position with numpy : 0.0181734561920166 nb_pixel_total : 1160507 time to create 1 rle with new method : 0.051482439041137695 length of segment : 1015 time for calcul the mask position with numpy : 0.0010597705841064453 nb_pixel_total : 48223 time to create 1 rle with old method : 0.0560002326965332 length of segment : 414 time for calcul the mask position with numpy : 0.014227151870727539 nb_pixel_total : 616089 time to create 1 rle with new method : 0.04755878448486328 length of segment : 1307 time for calcul the mask position with numpy : 0.002103090286254883 nb_pixel_total : 129071 time to create 1 rle with old method : 0.15127062797546387 length of segment : 379 time for calcul the mask position with numpy : 0.0009350776672363281 nb_pixel_total : 56823 time to create 1 rle with old method : 0.0684814453125 length of segment : 258 time for calcul the mask position with numpy : 0.0014889240264892578 nb_pixel_total : 49144 time to create 1 rle with old method : 0.05889248847961426 length of segment : 520 time for calcul the mask position with numpy : 0.0065653324127197266 nb_pixel_total : 423164 time to create 1 rle with new method : 0.01789379119873047 length of segment : 730 time for calcul the mask position with numpy : 0.000591278076171875 nb_pixel_total : 21193 time to create 1 rle with old method : 0.03318929672241211 length of segment : 169 time for calcul the mask position with numpy : 0.009515047073364258 nb_pixel_total : 332212 time to create 1 rle with new method : 0.021947145462036133 length of segment : 879 time for calcul the mask position with numpy : 0.0003974437713623047 nb_pixel_total : 12308 time to create 1 rle with old method : 0.01742386817932129 length of segment : 194 time for calcul the mask position with numpy : 0.0036630630493164062 nb_pixel_total : 177531 time to create 1 rle with new method : 0.009647607803344727 length of segment : 577 time for calcul the mask position with numpy : 0.0026917457580566406 nb_pixel_total : 113906 time to create 1 rle with old method : 0.16382741928100586 length of segment : 420 time for calcul the mask position with numpy : 0.0017702579498291016 nb_pixel_total : 74325 time to create 1 rle with old method : 0.09717178344726562 length of segment : 374 time for calcul the mask position with numpy : 0.0008907318115234375 nb_pixel_total : 40473 time to create 1 rle with old method : 0.05475425720214844 length of segment : 239 time for calcul the mask position with numpy : 0.0004611015319824219 nb_pixel_total : 10263 time to create 1 rle with old method : 0.014618635177612305 length of segment : 169 time for calcul the mask position with numpy : 0.004441499710083008 nb_pixel_total : 176424 time to create 1 rle with new method : 0.011923789978027344 length of segment : 528 time for calcul the mask position with numpy : 0.0016205310821533203 nb_pixel_total : 79142 time to create 1 rle with old method : 0.11094021797180176 length of segment : 190 time for calcul the mask position with numpy : 0.000640869140625 nb_pixel_total : 235 time to create 1 rle with old method : 0.0004801750183105469 length of segment : 24 time for calcul the mask position with numpy : 0.011172771453857422 nb_pixel_total : 488428 time to create 1 rle with new method : 0.03056502342224121 length of segment : 1664 time for calcul the mask position with numpy : 0.030666828155517578 nb_pixel_total : 152417 time to create 1 rle with new method : 0.14879965782165527 length of segment : 1726 time for calcul the mask position with numpy : 0.0010595321655273438 nb_pixel_total : 47621 time to create 1 rle with old method : 0.0663001537322998 length of segment : 225 time for calcul the mask position with numpy : 0.0005106925964355469 nb_pixel_total : 24011 time to create 1 rle with old method : 0.03194451332092285 length of segment : 254 time for calcul the mask position with numpy : 0.0039272308349609375 nb_pixel_total : 106609 time to create 1 rle with old method : 0.14358854293823242 length of segment : 710 time for calcul the mask position with numpy : 0.005326986312866211 nb_pixel_total : 256168 time to create 1 rle with new method : 0.013550281524658203 length of segment : 924 time for calcul the mask position with numpy : 0.03070211410522461 nb_pixel_total : 1188387 time to create 1 rle with new method : 0.09677696228027344 length of segment : 3077 time for calcul the mask position with numpy : 0.0019295215606689453 nb_pixel_total : 111226 time to create 1 rle with old method : 0.12953996658325195 length of segment : 314 time for calcul the mask position with numpy : 0.01898813247680664 nb_pixel_total : 1105346 time to create 1 rle with new method : 0.05120539665222168 length of segment : 1104 time for calcul the mask position with numpy : 0.00971674919128418 nb_pixel_total : 461282 time to create 1 rle with new method : 0.030695676803588867 length of segment : 999 time for calcul the mask position with numpy : 0.006533384323120117 nb_pixel_total : 187670 time to create 1 rle with new method : 0.021529197692871094 length of segment : 876 time for calcul the mask position with numpy : 0.012828826904296875 nb_pixel_total : 637482 time to create 1 rle with new method : 0.03772139549255371 length of segment : 1471 time for calcul the mask position with numpy : 0.001870870590209961 nb_pixel_total : 115525 time to create 1 rle with old method : 0.13360595703125 length of segment : 440 time for calcul the mask position with numpy : 0.00048160552978515625 nb_pixel_total : 18607 time to create 1 rle with old method : 0.022736072540283203 length of segment : 176 time for calcul the mask position with numpy : 0.0009620189666748047 nb_pixel_total : 48647 time to create 1 rle with old method : 0.0587308406829834 length of segment : 314 time for calcul the mask position with numpy : 0.002061605453491211 nb_pixel_total : 73750 time to create 1 rle with old method : 0.0887289047241211 length of segment : 419 time for calcul the mask position with numpy : 0.029326677322387695 nb_pixel_total : 1409351 time to create 1 rle with new method : 0.09122180938720703 length of segment : 2085 time for calcul the mask position with numpy : 0.0037622451782226562 nb_pixel_total : 185381 time to create 1 rle with new method : 0.011329174041748047 length of segment : 632 time for calcul the mask position with numpy : 0.01800060272216797 nb_pixel_total : 1081897 time to create 1 rle with new method : 0.043092966079711914 length of segment : 1081 time for calcul the mask position with numpy : 0.0008907318115234375 nb_pixel_total : 47975 time to create 1 rle with old method : 0.056603193283081055 length of segment : 225 time for calcul the mask position with numpy : 0.028494596481323242 nb_pixel_total : 1410741 time to create 1 rle with new method : 0.09905767440795898 length of segment : 2036 time for calcul the mask position with numpy : 0.008343219757080078 nb_pixel_total : 471637 time to create 1 rle with new method : 0.021219730377197266 length of segment : 1320 time for calcul the mask position with numpy : 0.0033774375915527344 nb_pixel_total : 115542 time to create 1 rle with old method : 0.13454437255859375 length of segment : 791 time for calcul the mask position with numpy : 0.012402772903442383 nb_pixel_total : 489806 time to create 1 rle with new method : 0.032978057861328125 length of segment : 1035 time for calcul the mask position with numpy : 0.0006604194641113281 nb_pixel_total : 29494 time to create 1 rle with old method : 0.034267425537109375 length of segment : 284 time for calcul the mask position with numpy : 0.008988142013549805 nb_pixel_total : 475329 time to create 1 rle with new method : 0.023126602172851562 length of segment : 1121 time for calcul the mask position with numpy : 0.002167940139770508 nb_pixel_total : 104091 time to create 1 rle with old method : 0.1264793872833252 length of segment : 515 time for calcul the mask position with numpy : 0.0072095394134521484 nb_pixel_total : 335100 time to create 1 rle with new method : 0.019973278045654297 length of segment : 509 time for calcul the mask position with numpy : 0.0018379688262939453 nb_pixel_total : 56812 time to create 1 rle with old method : 0.06475663185119629 length of segment : 424 time for calcul the mask position with numpy : 0.017286062240600586 nb_pixel_total : 964060 time to create 1 rle with new method : 0.040911197662353516 length of segment : 1368 time for calcul the mask position with numpy : 0.0016241073608398438 nb_pixel_total : 41963 time to create 1 rle with old method : 0.05094146728515625 length of segment : 377 time for calcul the mask position with numpy : 0.008378028869628906 nb_pixel_total : 354280 time to create 1 rle with new method : 0.031986236572265625 length of segment : 1561 time for calcul the mask position with numpy : 0.004006862640380859 nb_pixel_total : 209161 time to create 1 rle with new method : 0.02724766731262207 length of segment : 720 time for calcul the mask position with numpy : 0.002531766891479492 nb_pixel_total : 81974 time to create 1 rle with old method : 0.09337496757507324 length of segment : 433 time for calcul the mask position with numpy : 0.0022649765014648438 nb_pixel_total : 116018 time to create 1 rle with old method : 0.13460040092468262 length of segment : 335 time for calcul the mask position with numpy : 0.003998756408691406 nb_pixel_total : 193965 time to create 1 rle with new method : 0.011045694351196289 length of segment : 712 time for calcul the mask position with numpy : 0.005944967269897461 nb_pixel_total : 284996 time to create 1 rle with new method : 0.01975226402282715 length of segment : 726 time for calcul the mask position with numpy : 0.0230257511138916 nb_pixel_total : 734490 time to create 1 rle with new method : 0.0587613582611084 length of segment : 1349 time for calcul the mask position with numpy : 0.0037980079650878906 nb_pixel_total : 157770 time to create 1 rle with new method : 0.011348962783813477 length of segment : 664 time for calcul the mask position with numpy : 0.0016524791717529297 nb_pixel_total : 88626 time to create 1 rle with old method : 0.10039758682250977 length of segment : 369 time for calcul the mask position with numpy : 0.0016603469848632812 nb_pixel_total : 73471 time to create 1 rle with old method : 0.08334875106811523 length of segment : 395 time for calcul the mask position with numpy : 0.004408359527587891 nb_pixel_total : 231159 time to create 1 rle with new method : 0.011888980865478516 length of segment : 564 time for calcul the mask position with numpy : 0.0013153553009033203 nb_pixel_total : 55819 time to create 1 rle with old method : 0.06577587127685547 length of segment : 286 time for calcul the mask position with numpy : 0.01339864730834961 nb_pixel_total : 738683 time to create 1 rle with new method : 0.03923654556274414 length of segment : 1346 time for calcul the mask position with numpy : 0.0013370513916015625 nb_pixel_total : 77814 time to create 1 rle with old method : 0.09079504013061523 length of segment : 241 time for calcul the mask position with numpy : 0.016024351119995117 nb_pixel_total : 887466 time to create 1 rle with new method : 0.0384068489074707 length of segment : 1261 time for calcul the mask position with numpy : 0.0003514289855957031 nb_pixel_total : 16932 time to create 1 rle with old method : 0.02105116844177246 length of segment : 86 time for calcul the mask position with numpy : 0.0010035037994384766 nb_pixel_total : 51073 time to create 1 rle with old method : 0.05925583839416504 length of segment : 322 time for calcul the mask position with numpy : 0.0035164356231689453 nb_pixel_total : 178477 time to create 1 rle with new method : 0.009749174118041992 length of segment : 457 time for calcul the mask position with numpy : 0.005795478820800781 nb_pixel_total : 258420 time to create 1 rle with new method : 0.015472412109375 length of segment : 766 time for calcul the mask position with numpy : 0.0004942417144775391 nb_pixel_total : 22425 time to create 1 rle with old method : 0.026595354080200195 length of segment : 161 time for calcul the mask position with numpy : 0.0013194084167480469 nb_pixel_total : 58965 time to create 1 rle with old method : 0.07031559944152832 length of segment : 288 time for calcul the mask position with numpy : 0.0012843608856201172 nb_pixel_total : 67190 time to create 1 rle with old method : 0.07709050178527832 length of segment : 346 time for calcul the mask position with numpy : 0.0005307197570800781 nb_pixel_total : 17898 time to create 1 rle with old method : 0.02157735824584961 length of segment : 149 time for calcul the mask position with numpy : 0.0015711784362792969 nb_pixel_total : 75733 time to create 1 rle with old method : 0.08695769309997559 length of segment : 579 time for calcul the mask position with numpy : 0.001665353775024414 nb_pixel_total : 54817 time to create 1 rle with old method : 0.0658411979675293 length of segment : 377 time for calcul the mask position with numpy : 0.0034723281860351562 nb_pixel_total : 119621 time to create 1 rle with old method : 0.13824248313903809 length of segment : 444 time for calcul the mask position with numpy : 0.009594917297363281 nb_pixel_total : 311467 time to create 1 rle with new method : 0.024400949478149414 length of segment : 879 time for calcul the mask position with numpy : 0.0032806396484375 nb_pixel_total : 141610 time to create 1 rle with old method : 0.19370102882385254 length of segment : 532 time for calcul the mask position with numpy : 0.001268148422241211 nb_pixel_total : 67917 time to create 1 rle with old method : 0.07883238792419434 length of segment : 406 time for calcul the mask position with numpy : 0.006502628326416016 nb_pixel_total : 262396 time to create 1 rle with new method : 0.015779972076416016 length of segment : 775 time for calcul the mask position with numpy : 0.006453275680541992 nb_pixel_total : 341443 time to create 1 rle with new method : 0.018761873245239258 length of segment : 1020 time for calcul the mask position with numpy : 0.0022776126861572266 nb_pixel_total : 138010 time to create 1 rle with old method : 0.1826615333557129 length of segment : 350 time for calcul the mask position with numpy : 0.0024344921112060547 nb_pixel_total : 108921 time to create 1 rle with old method : 0.13299036026000977 length of segment : 769 time for calcul the mask position with numpy : 0.002711057662963867 nb_pixel_total : 167183 time to create 1 rle with new method : 0.006829261779785156 length of segment : 508 time for calcul the mask position with numpy : 0.006949663162231445 nb_pixel_total : 47111 time to create 1 rle with old method : 0.05566763877868652 length of segment : 211 time for calcul the mask position with numpy : 0.0033736228942871094 nb_pixel_total : 155570 time to create 1 rle with new method : 0.008929967880249023 length of segment : 465 time for calcul the mask position with numpy : 0.0013117790222167969 nb_pixel_total : 65077 time to create 1 rle with old method : 0.07564091682434082 length of segment : 335 time for calcul the mask position with numpy : 0.009860992431640625 nb_pixel_total : 540490 time to create 1 rle with new method : 0.026470184326171875 length of segment : 1220 time for calcul the mask position with numpy : 0.001377105712890625 nb_pixel_total : 82373 time to create 1 rle with old method : 0.0960383415222168 length of segment : 423 time for calcul the mask position with numpy : 0.0037496089935302734 nb_pixel_total : 134506 time to create 1 rle with old method : 0.15599727630615234 length of segment : 701 time for calcul the mask position with numpy : 0.0010590553283691406 nb_pixel_total : 57700 time to create 1 rle with old method : 0.07132101058959961 length of segment : 230 time for calcul the mask position with numpy : 0.0022759437561035156 nb_pixel_total : 116214 time to create 1 rle with old method : 0.1330721378326416 length of segment : 570 time for calcul the mask position with numpy : 0.0043714046478271484 nb_pixel_total : 215941 time to create 1 rle with new method : 0.013098955154418945 length of segment : 714 time for calcul the mask position with numpy : 0.0034322738647460938 nb_pixel_total : 168296 time to create 1 rle with new method : 0.010052919387817383 length of segment : 465 time for calcul the mask position with numpy : 0.0011115074157714844 nb_pixel_total : 27520 time to create 1 rle with old method : 0.04617953300476074 length of segment : 225 time for calcul the mask position with numpy : 0.0012085437774658203 nb_pixel_total : 60141 time to create 1 rle with old method : 0.07126688957214355 length of segment : 210 time for calcul the mask position with numpy : 0.0021517276763916016 nb_pixel_total : 133835 time to create 1 rle with old method : 0.15210485458374023 length of segment : 350 time for calcul the mask position with numpy : 0.006082773208618164 nb_pixel_total : 347984 time to create 1 rle with new method : 0.017237186431884766 length of segment : 1455 time for calcul the mask position with numpy : 0.0009222030639648438 nb_pixel_total : 43489 time to create 1 rle with old method : 0.04971480369567871 length of segment : 254 time for calcul the mask position with numpy : 0.0012218952178955078 nb_pixel_total : 61887 time to create 1 rle with old method : 0.07015848159790039 length of segment : 284 time for calcul the mask position with numpy : 0.0010571479797363281 nb_pixel_total : 36671 time to create 1 rle with old method : 0.04175162315368652 length of segment : 316 time for calcul the mask position with numpy : 0.0010929107666015625 nb_pixel_total : 51676 time to create 1 rle with old method : 0.057692766189575195 length of segment : 333 time for calcul the mask position with numpy : 0.001986265182495117 nb_pixel_total : 73460 time to create 1 rle with old method : 0.08731245994567871 length of segment : 308 time for calcul the mask position with numpy : 0.001798868179321289 nb_pixel_total : 90293 time to create 1 rle with old method : 0.10950875282287598 length of segment : 356 time for calcul the mask position with numpy : 0.005214691162109375 nb_pixel_total : 250562 time to create 1 rle with new method : 0.01396489143371582 length of segment : 835 time for calcul the mask position with numpy : 0.0011749267578125 nb_pixel_total : 46153 time to create 1 rle with old method : 0.054703474044799805 length of segment : 262 time for calcul the mask position with numpy : 0.002818584442138672 nb_pixel_total : 96566 time to create 1 rle with old method : 0.11410999298095703 length of segment : 441 time for calcul the mask position with numpy : 0.0004413127899169922 nb_pixel_total : 21520 time to create 1 rle with old method : 0.025812387466430664 length of segment : 186 time for calcul the mask position with numpy : 0.0035750865936279297 nb_pixel_total : 160930 time to create 1 rle with new method : 0.008327722549438477 length of segment : 406 time for calcul the mask position with numpy : 0.023389339447021484 nb_pixel_total : 1307498 time to create 1 rle with new method : 0.06556057929992676 length of segment : 1226 time for calcul the mask position with numpy : 0.00871133804321289 nb_pixel_total : 375902 time to create 1 rle with new method : 0.01866769790649414 length of segment : 1002 time for calcul the mask position with numpy : 0.0024161338806152344 nb_pixel_total : 54501 time to create 1 rle with old method : 0.08555889129638672 length of segment : 321 time for calcul the mask position with numpy : 0.0020248889923095703 nb_pixel_total : 63737 time to create 1 rle with old method : 0.09293246269226074 length of segment : 322 time for calcul the mask position with numpy : 0.001390218734741211 nb_pixel_total : 45546 time to create 1 rle with old method : 0.05379486083984375 length of segment : 284 time for calcul the mask position with numpy : 0.003088712692260742 nb_pixel_total : 121696 time to create 1 rle with old method : 0.14369869232177734 length of segment : 536 time for calcul the mask position with numpy : 0.003897428512573242 nb_pixel_total : 144099 time to create 1 rle with old method : 0.16785097122192383 length of segment : 460 time for calcul the mask position with numpy : 0.0013263225555419922 nb_pixel_total : 44836 time to create 1 rle with old method : 0.0559232234954834 length of segment : 341 time for calcul the mask position with numpy : 0.002388477325439453 nb_pixel_total : 76430 time to create 1 rle with old method : 0.09335660934448242 length of segment : 350 time for calcul the mask position with numpy : 0.0007655620574951172 nb_pixel_total : 22437 time to create 1 rle with old method : 0.0270993709564209 length of segment : 183 time for calcul the mask position with numpy : 0.0009961128234863281 nb_pixel_total : 32068 time to create 1 rle with old method : 0.03875732421875 length of segment : 136 time for calcul the mask position with numpy : 0.003036975860595703 nb_pixel_total : 144236 time to create 1 rle with old method : 0.16777348518371582 length of segment : 420 time for calcul the mask position with numpy : 0.0008103847503662109 nb_pixel_total : 23836 time to create 1 rle with old method : 0.028690814971923828 length of segment : 153 time for calcul the mask position with numpy : 0.009981870651245117 nb_pixel_total : 492919 time to create 1 rle with new method : 0.026885271072387695 length of segment : 746 time for calcul the mask position with numpy : 0.0014841556549072266 nb_pixel_total : 67478 time to create 1 rle with old method : 0.07943391799926758 length of segment : 285 time for calcul the mask position with numpy : 0.0015444755554199219 nb_pixel_total : 56865 time to create 1 rle with old method : 0.06835031509399414 length of segment : 270 time for calcul the mask position with numpy : 0.0027010440826416016 nb_pixel_total : 93052 time to create 1 rle with old method : 0.10893440246582031 length of segment : 664 time for calcul the mask position with numpy : 0.01185750961303711 nb_pixel_total : 565504 time to create 1 rle with new method : 0.0362248420715332 length of segment : 816 time for calcul the mask position with numpy : 0.0018775463104248047 nb_pixel_total : 83563 time to create 1 rle with old method : 0.10238146781921387 length of segment : 385 time for calcul the mask position with numpy : 0.0038836002349853516 nb_pixel_total : 209053 time to create 1 rle with new method : 0.010753393173217773 length of segment : 548 time for calcul the mask position with numpy : 0.025316715240478516 nb_pixel_total : 1151762 time to create 1 rle with new method : 0.07646393775939941 length of segment : 1471 time for calcul the mask position with numpy : 0.005242109298706055 nb_pixel_total : 190229 time to create 1 rle with new method : 0.010871410369873047 length of segment : 466 time for calcul the mask position with numpy : 0.0025191307067871094 nb_pixel_total : 111108 time to create 1 rle with old method : 0.12623882293701172 length of segment : 625 time for calcul the mask position with numpy : 0.0047512054443359375 nb_pixel_total : 291079 time to create 1 rle with new method : 0.01173543930053711 length of segment : 613 time for calcul the mask position with numpy : 0.001352548599243164 nb_pixel_total : 57719 time to create 1 rle with old method : 0.06763911247253418 length of segment : 395 time for calcul the mask position with numpy : 0.002836465835571289 nb_pixel_total : 112635 time to create 1 rle with old method : 0.12987995147705078 length of segment : 631 time for calcul the mask position with numpy : 0.0013663768768310547 nb_pixel_total : 40807 time to create 1 rle with old method : 0.047437191009521484 length of segment : 673 time for calcul the mask position with numpy : 0.0009515285491943359 nb_pixel_total : 38055 time to create 1 rle with old method : 0.04540205001831055 length of segment : 274 time for calcul the mask position with numpy : 0.0020380020141601562 nb_pixel_total : 68561 time to create 1 rle with old method : 0.08144330978393555 length of segment : 549 time for calcul the mask position with numpy : 0.010214805603027344 nb_pixel_total : 515959 time to create 1 rle with new method : 0.02834939956665039 length of segment : 870 time for calcul the mask position with numpy : 0.01389765739440918 nb_pixel_total : 480998 time to create 1 rle with new method : 0.052047014236450195 length of segment : 1481 time for calcul the mask position with numpy : 0.0013332366943359375 nb_pixel_total : 53212 time to create 1 rle with old method : 0.06256484985351562 length of segment : 434 time for calcul the mask position with numpy : 0.000759124755859375 nb_pixel_total : 32290 time to create 1 rle with old method : 0.03840160369873047 length of segment : 247 time for calcul the mask position with numpy : 0.0022640228271484375 nb_pixel_total : 101219 time to create 1 rle with old method : 0.14025378227233887 length of segment : 290 time for calcul the mask position with numpy : 0.015335559844970703 nb_pixel_total : 270525 time to create 1 rle with new method : 0.04547429084777832 length of segment : 581 time for calcul the mask position with numpy : 0.00980234146118164 nb_pixel_total : 493556 time to create 1 rle with new method : 0.027928829193115234 length of segment : 707 time for calcul the mask position with numpy : 0.0006673336029052734 nb_pixel_total : 25333 time to create 1 rle with old method : 0.030571699142456055 length of segment : 184 time for calcul the mask position with numpy : 0.006132602691650391 nb_pixel_total : 174699 time to create 1 rle with new method : 0.01848602294921875 length of segment : 706 time for calcul the mask position with numpy : 0.004006147384643555 nb_pixel_total : 147269 time to create 1 rle with old method : 0.17354774475097656 length of segment : 471 time for calcul the mask position with numpy : 0.0027952194213867188 nb_pixel_total : 125860 time to create 1 rle with old method : 0.1547718048095703 length of segment : 588 time for calcul the mask position with numpy : 0.0009331703186035156 nb_pixel_total : 48129 time to create 1 rle with old method : 0.05976104736328125 length of segment : 338 time for calcul the mask position with numpy : 0.0015411376953125 nb_pixel_total : 67512 time to create 1 rle with old method : 0.08060455322265625 length of segment : 286 time for calcul the mask position with numpy : 0.0024514198303222656 nb_pixel_total : 112031 time to create 1 rle with old method : 0.13584613800048828 length of segment : 454 time for calcul the mask position with numpy : 0.0008320808410644531 nb_pixel_total : 25067 time to create 1 rle with old method : 0.03110980987548828 length of segment : 175 time for calcul the mask position with numpy : 0.003607034683227539 nb_pixel_total : 119659 time to create 1 rle with old method : 0.1466052532196045 length of segment : 308 time for calcul the mask position with numpy : 0.003854036331176758 nb_pixel_total : 166500 time to create 1 rle with new method : 0.011872291564941406 length of segment : 489 time for calcul the mask position with numpy : 0.0058705806732177734 nb_pixel_total : 269412 time to create 1 rle with new method : 0.017878055572509766 length of segment : 924 time for calcul the mask position with numpy : 0.016462087631225586 nb_pixel_total : 931160 time to create 1 rle with new method : 0.04375028610229492 length of segment : 1165 time for calcul the mask position with numpy : 0.009294986724853516 nb_pixel_total : 220455 time to create 1 rle with new method : 0.033631324768066406 length of segment : 576 time for calcul the mask position with numpy : 0.0006897449493408203 nb_pixel_total : 33996 time to create 1 rle with old method : 0.04033303260803223 length of segment : 265 time for calcul the mask position with numpy : 0.0010228157043457031 nb_pixel_total : 30781 time to create 1 rle with old method : 0.036489248275756836 length of segment : 393 time for calcul the mask position with numpy : 0.0022192001342773438 nb_pixel_total : 114280 time to create 1 rle with old method : 0.1327970027923584 length of segment : 632 time for calcul the mask position with numpy : 0.0014014244079589844 nb_pixel_total : 94087 time to create 1 rle with old method : 0.10707616806030273 length of segment : 302 time for calcul the mask position with numpy : 0.002203702926635742 nb_pixel_total : 21038 time to create 1 rle with old method : 0.025874614715576172 length of segment : 354 time for calcul the mask position with numpy : 0.0018498897552490234 nb_pixel_total : 96563 time to create 1 rle with old method : 0.13950824737548828 length of segment : 324 time for calcul the mask position with numpy : 0.0006966590881347656 nb_pixel_total : 33754 time to create 1 rle with old method : 0.03922867774963379 length of segment : 291 time for calcul the mask position with numpy : 0.06719803810119629 nb_pixel_total : 3294542 time to create 1 rle with new method : 0.23794794082641602 length of segment : 7337 time for calcul the mask position with numpy : 0.019118547439575195 nb_pixel_total : 1462874 time to create 1 rle with new method : 0.05656003952026367 length of segment : 848 time for calcul the mask position with numpy : 0.02755260467529297 nb_pixel_total : 2024072 time to create 1 rle with new method : 0.07568120956420898 length of segment : 1416 time for calcul the mask position with numpy : 0.002941608428955078 nb_pixel_total : 186045 time to create 1 rle with new method : 0.006391763687133789 length of segment : 328 time for calcul the mask position with numpy : 0.0006241798400878906 nb_pixel_total : 37664 time to create 1 rle with old method : 0.04642844200134277 length of segment : 166 time for calcul the mask position with numpy : 0.0019230842590332031 nb_pixel_total : 108203 time to create 1 rle with old method : 0.12944459915161133 length of segment : 227 time for calcul the mask position with numpy : 0.001783132553100586 nb_pixel_total : 139432 time to create 1 rle with old method : 0.16456079483032227 length of segment : 476 time spent for convertir_results : 43.830283880233765 Inside saveOutput : final : False verbose : 0 eke 12-6-18 : saveMask need to be cleaned for new output ! Number saved : None batch 1 Loaded 287 chid ids of type : 4854 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 0 save missing photos in datou_result : time spend for datou_step_exec : 131.4357669353485 time spend to save output : 0.430316686630249 total time spend for step 2 : 131.86608362197876 step3:blur_detection Fri Oct 17 10:29:33 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure inside step blur_detection methode: variance laplacian (4160, 3120) 2048.3414622848823 (4160, 3120) 1709.9590986854955 (4160, 3120) 1610.0099019925085 (4160, 3120) 1276.588076740277 (4160, 3120) 202.6232422376391 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 : 5 time used for this insertion : 0.03662872314453125 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 5 time used for this insertion : 0.03615760803222656 save missing photos in datou_result : time spend for datou_step_exec : 1.6906764507293701 time spend to save output : 0.09267592430114746 total time spend for step 3 : 1.7833523750305176 step4:brightness Fri Oct 17 10:29:35 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/1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57.jpg treat image : temp/1760689578_752055_1389772233_5048c8487627fd84ace06f8bef2b5109.jpg treat image : temp/1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f.jpg treat image : temp/1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744.jpg treat image : temp/1760689578_752055_1389772225_d0a8609c6715c5f1a67191409dd5978c.jpg 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 : 5 time used for this insertion : 0.04004263877868652 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 5 time used for this insertion : 0.03600120544433594 save missing photos in datou_result : time spend for datou_step_exec : 7.093175888061523 time spend to save output : 0.09327936172485352 total time spend for step 4 : 7.186455249786377 step5:rle_unique_nms_with_priority Fri Oct 17 10:29:42 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed 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 VR 22-3-18 : For now we do not clean correctly the datou structure Begin step rle-unique-nms batch 1 Loaded 287 chid ids of type : 4854 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++nb_obj : 63 nb_hashtags : 9 time to prepare the origin masks : 55.24987864494324 time for calcul the mask position with numpy : 0.35547900199890137 nb_pixel_total : 2626780 time to create 1 rle with new method : 1.5193431377410889 time for calcul the mask position with numpy : 0.05638480186462402 nb_pixel_total : 72691 time to create 1 rle with old method : 0.08551692962646484 time for calcul the mask position with numpy : 0.05417299270629883 nb_pixel_total : 91698 time to create 1 rle with old method : 0.11775350570678711 time for calcul the mask position with numpy : 0.05987906455993652 nb_pixel_total : 59597 time to create 1 rle with old method : 0.06880664825439453 time for calcul the mask position with numpy : 0.06625175476074219 nb_pixel_total : 445613 time to create 1 rle with new method : 1.3003325462341309 time for calcul the mask position with numpy : 0.05811738967895508 nb_pixel_total : 80402 time to create 1 rle with old method : 0.09517598152160645 time for calcul the mask position with numpy : 0.0597233772277832 nb_pixel_total : 549238 time to create 1 rle with new method : 1.4772753715515137 time for calcul the mask position with numpy : 0.05378556251525879 nb_pixel_total : 44352 time to create 1 rle with old method : 0.0523531436920166 time for calcul the mask position with numpy : 0.05453801155090332 nb_pixel_total : 1938 time to create 1 rle with old method : 0.002674579620361328 time for calcul the mask position with numpy : 0.05653834342956543 nb_pixel_total : 319646 time to create 1 rle with new method : 1.6283612251281738 time for calcul the mask position with numpy : 0.05420541763305664 nb_pixel_total : 26298 time to create 1 rle with old method : 0.04402041435241699 time for calcul the mask position with numpy : 0.06089448928833008 nb_pixel_total : 204398 time to create 1 rle with new method : 1.2563066482543945 time for calcul the mask position with numpy : 0.05564069747924805 nb_pixel_total : 171272 time to create 1 rle with new method : 1.1484322547912598 time for calcul the mask position with numpy : 0.056231021881103516 nb_pixel_total : 321380 time to create 1 rle with new method : 1.1783998012542725 time for calcul the mask position with numpy : 0.055881500244140625 nb_pixel_total : 3125 time to create 1 rle with old method : 0.003850221633911133 time for calcul the mask position with numpy : 0.05413675308227539 nb_pixel_total : 30549 time to create 1 rle with old method : 0.0407259464263916 time for calcul the mask position with numpy : 0.05865073204040527 nb_pixel_total : 43468 time to create 1 rle with old method : 0.06540346145629883 time for calcul the mask position with numpy : 0.06149172782897949 nb_pixel_total : 11563 time to create 1 rle with old method : 0.04550433158874512 time for calcul the mask position with numpy : 0.07022619247436523 nb_pixel_total : 179765 time to create 1 rle with new method : 1.2280423641204834 time for calcul the mask position with numpy : 0.05477428436279297 nb_pixel_total : 63323 time to create 1 rle with old method : 0.07396888732910156 time for calcul the mask position with numpy : 0.055852413177490234 nb_pixel_total : 65535 time to create 1 rle with old method : 0.0759892463684082 time for calcul the mask position with numpy : 0.05568051338195801 nb_pixel_total : 298851 time to create 1 rle with new method : 1.095491886138916 time for calcul the mask position with numpy : 0.05600476264953613 nb_pixel_total : 6733 time to create 1 rle with old method : 0.008318185806274414 time for calcul the mask position with numpy : 0.06351327896118164 nb_pixel_total : 35409 time to create 1 rle with old method : 0.05843830108642578 time for calcul the mask position with numpy : 0.055591583251953125 nb_pixel_total : 62029 time to create 1 rle with old method : 0.08165717124938965 time for calcul the mask position with numpy : 0.057575225830078125 nb_pixel_total : 418016 time to create 1 rle with new method : 0.820540189743042 time for calcul the mask position with numpy : 0.054046630859375 nb_pixel_total : 144 time to create 1 rle with old method : 0.00023603439331054688 time for calcul the mask position with numpy : 0.054320573806762695 nb_pixel_total : 9615 time to create 1 rle with old method : 0.01181483268737793 time for calcul the mask position with numpy : 0.06218600273132324 nb_pixel_total : 8019 time to create 1 rle with old method : 0.012931108474731445 time for calcul the mask position with numpy : 0.057753562927246094 nb_pixel_total : 176199 time to create 1 rle with new method : 1.2328314781188965 time for calcul the mask position with numpy : 0.06264233589172363 nb_pixel_total : 24891 time to create 1 rle with old method : 0.0302884578704834 time for calcul the mask position with numpy : 0.060246944427490234 nb_pixel_total : 39831 time to create 1 rle with old method : 0.056670427322387695 time for calcul the mask position with numpy : 0.05617189407348633 nb_pixel_total : 75529 time to create 1 rle with old method : 0.09426736831665039 time for calcul the mask position with numpy : 0.06112813949584961 nb_pixel_total : 162732 time to create 1 rle with new method : 2.277959108352661 time for calcul the mask position with numpy : 0.18975257873535156 nb_pixel_total : 1155652 time to create 1 rle with new method : 1.615664005279541 time for calcul the mask position with numpy : 0.06577682495117188 nb_pixel_total : 629016 time to create 1 rle with new method : 1.3108994960784912 time for calcul the mask position with numpy : 0.056479692459106445 nb_pixel_total : 65958 time to create 1 rle with old method : 0.07655644416809082 time for calcul the mask position with numpy : 0.055414438247680664 nb_pixel_total : 7386 time to create 1 rle with old method : 0.009021997451782227 time for calcul the mask position with numpy : 0.05484914779663086 nb_pixel_total : 40796 time to create 1 rle with old method : 0.047649383544921875 time for calcul the mask position with numpy : 0.05619192123413086 nb_pixel_total : 23712 time to create 1 rle with old method : 0.029863595962524414 time for calcul the mask position with numpy : 0.058591604232788086 nb_pixel_total : 269281 time to create 1 rle with new method : 0.8004412651062012 time for calcul the mask position with numpy : 0.06751418113708496 nb_pixel_total : 6723 time to create 1 rle with old method : 0.011185407638549805 time for calcul the mask position with numpy : 0.06140851974487305 nb_pixel_total : 49320 time to create 1 rle with old method : 0.058559417724609375 time for calcul the mask position with numpy : 0.05794858932495117 nb_pixel_total : 196636 time to create 1 rle with new method : 0.8323547840118408 time for calcul the mask position with numpy : 0.059464216232299805 nb_pixel_total : 14872 time to create 1 rle with old method : 0.0174710750579834 time for calcul the mask position with numpy : 0.05955386161804199 nb_pixel_total : 31087 time to create 1 rle with old method : 0.036131858825683594 time for calcul the mask position with numpy : 0.11152338981628418 nb_pixel_total : 1619401 time to create 1 rle with new method : 1.041273832321167 time for calcul the mask position with numpy : 0.05891132354736328 nb_pixel_total : 50940 time to create 1 rle with old method : 0.061907052993774414 time for calcul the mask position with numpy : 0.0577998161315918 nb_pixel_total : 163721 time to create 1 rle with new method : 0.8349721431732178 time for calcul the mask position with numpy : 0.05778956413269043 nb_pixel_total : 113804 time to create 1 rle with old method : 0.13530278205871582 time for calcul the mask position with numpy : 0.05929446220397949 nb_pixel_total : 113177 time to create 1 rle with old method : 0.1420574188232422 time for calcul the mask position with numpy : 0.05475974082946777 nb_pixel_total : 6341 time to create 1 rle with old method : 0.008265256881713867 time for calcul the mask position with numpy : 0.05822038650512695 nb_pixel_total : 247318 time to create 1 rle with new method : 1.0841310024261475 time for calcul the mask position with numpy : 0.06056332588195801 nb_pixel_total : 61217 time to create 1 rle with old method : 0.07262825965881348 time for calcul the mask position with numpy : 0.06350421905517578 nb_pixel_total : 371171 time to create 1 rle with new method : 0.7605640888214111 time for calcul the mask position with numpy : 0.05882072448730469 nb_pixel_total : 317646 time to create 1 rle with new method : 0.9984924793243408 time for calcul the mask position with numpy : 0.054782867431640625 nb_pixel_total : 1665 time to create 1 rle with old method : 0.002539396286010742 time for calcul the mask position with numpy : 0.05595517158508301 nb_pixel_total : 137708 time to create 1 rle with old method : 0.16154074668884277 time for calcul the mask position with numpy : 0.05481553077697754 nb_pixel_total : 4591 time to create 1 rle with old method : 0.005824089050292969 time for calcul the mask position with numpy : 0.0556182861328125 nb_pixel_total : 27042 time to create 1 rle with old method : 0.031646728515625 time for calcul the mask position with numpy : 0.055649518966674805 nb_pixel_total : 153507 time to create 1 rle with new method : 1.063805103302002 time for calcul the mask position with numpy : 0.05473637580871582 nb_pixel_total : 27573 time to create 1 rle with old method : 0.032663822174072266 time for calcul the mask position with numpy : 0.05948781967163086 nb_pixel_total : 270826 time to create 1 rle with new method : 0.835991621017456 time for calcul the mask position with numpy : 0.0571134090423584 nb_pixel_total : 70484 time to create 1 rle with old method : 0.08212780952453613 create new chi : 34.75536012649536 time to delete rle : 0.11570477485656738 batch 1 Loaded 64 chid ids of type : 4855 Number RLEs to save : 62880 TO DO : save crop sub photo not yet done ! save time : 5.974905729293823 nb_obj : 60 nb_hashtags : 9 time to prepare the origin masks : 52.98427081108093 time for calcul the mask position with numpy : 0.226851224899292 nb_pixel_total : 2526711 time to create 1 rle with new method : 1.7765543460845947 time for calcul the mask position with numpy : 0.2373652458190918 nb_pixel_total : 1155186 time to create 1 rle with new method : 2.1745903491973877 time for calcul the mask position with numpy : 0.05647706985473633 nb_pixel_total : 73496 time to create 1 rle with old method : 0.09203481674194336 time for calcul the mask position with numpy : 0.05935406684875488 nb_pixel_total : 40517 time to create 1 rle with old method : 0.05055499076843262 time for calcul the mask position with numpy : 0.05958056449890137 nb_pixel_total : 12292 time to create 1 rle with old method : 0.014419078826904297 time for calcul the mask position with numpy : 0.05391883850097656 nb_pixel_total : 2118 time to create 1 rle with old method : 0.0026941299438476562 time for calcul the mask position with numpy : 0.054270267486572266 nb_pixel_total : 4861 time to create 1 rle with old method : 0.006031990051269531 time for calcul the mask position with numpy : 0.06968951225280762 nb_pixel_total : 1310457 time to create 1 rle with new method : 0.7235655784606934 time for calcul the mask position with numpy : 0.05414319038391113 nb_pixel_total : 20973 time to create 1 rle with old method : 0.024906158447265625 time for calcul the mask position with numpy : 0.05503058433532715 nb_pixel_total : 16824 time to create 1 rle with old method : 0.021001100540161133 time for calcul the mask position with numpy : 0.05443620681762695 nb_pixel_total : 26630 time to create 1 rle with old method : 0.0314333438873291 time for calcul the mask position with numpy : 0.06281208992004395 nb_pixel_total : 1103282 time to create 1 rle with new method : 1.329380750656128 time for calcul the mask position with numpy : 0.05427193641662598 nb_pixel_total : 28456 time to create 1 rle with old method : 0.033512115478515625 time for calcul the mask position with numpy : 0.05559849739074707 nb_pixel_total : 178979 time to create 1 rle with new method : 0.9346482753753662 time for calcul the mask position with numpy : 0.05432558059692383 nb_pixel_total : 8109 time to create 1 rle with old method : 0.010833024978637695 time for calcul the mask position with numpy : 0.05404543876647949 nb_pixel_total : 1 time to create 1 rle with old method : 2.47955322265625e-05 time for calcul the mask position with numpy : 0.05576896667480469 nb_pixel_total : 341301 time to create 1 rle with new method : 1.5025794506072998 time for calcul the mask position with numpy : 0.054265499114990234 nb_pixel_total : 23582 time to create 1 rle with old method : 0.027927398681640625 time for calcul the mask position with numpy : 0.05406641960144043 nb_pixel_total : 3015 time to create 1 rle with old method : 0.0036821365356445312 time for calcul the mask position with numpy : 0.055376529693603516 nb_pixel_total : 279988 time to create 1 rle with new method : 1.491502046585083 time for calcul the mask position with numpy : 0.057614803314208984 nb_pixel_total : 67667 time to create 1 rle with old method : 0.07893919944763184 time for calcul the mask position with numpy : 0.05398917198181152 nb_pixel_total : 68085 time to create 1 rle with old method : 0.07951951026916504 time for calcul the mask position with numpy : 0.05426955223083496 nb_pixel_total : 78744 time to create 1 rle with old method : 0.0926814079284668 time for calcul the mask position with numpy : 0.05462360382080078 nb_pixel_total : 41382 time to create 1 rle with old method : 0.04849362373352051 time for calcul the mask position with numpy : 0.05516982078552246 nb_pixel_total : 131777 time to create 1 rle with old method : 0.15872526168823242 time for calcul the mask position with numpy : 0.055753231048583984 nb_pixel_total : 107084 time to create 1 rle with old method : 0.14897489547729492 time for calcul the mask position with numpy : 0.06310486793518066 nb_pixel_total : 68701 time to create 1 rle with old method : 0.13147664070129395 time for calcul the mask position with numpy : 0.06935977935791016 nb_pixel_total : 11870 time to create 1 rle with old method : 0.02358722686767578 time for calcul the mask position with numpy : 0.07086801528930664 nb_pixel_total : 237984 time to create 1 rle with new method : 1.2936208248138428 time for calcul the mask position with numpy : 0.05536937713623047 nb_pixel_total : 154957 time to create 1 rle with new method : 0.9236736297607422 time for calcul the mask position with numpy : 0.05414128303527832 nb_pixel_total : 260 time to create 1 rle with old method : 0.0003864765167236328 time for calcul the mask position with numpy : 0.055908203125 nb_pixel_total : 86580 time to create 1 rle with old method : 0.10107541084289551 time for calcul the mask position with numpy : 0.0614163875579834 nb_pixel_total : 612015 time to create 1 rle with new method : 0.5527834892272949 time for calcul the mask position with numpy : 0.0756382942199707 nb_pixel_total : 1559133 time to create 1 rle with new method : 0.9315085411071777 time for calcul the mask position with numpy : 0.06186985969543457 nb_pixel_total : 109953 time to create 1 rle with old method : 0.13500452041625977 time for calcul the mask position with numpy : 0.0566253662109375 nb_pixel_total : 143370 time to create 1 rle with old method : 0.1698923110961914 time for calcul the mask position with numpy : 0.05536961555480957 nb_pixel_total : 6082 time to create 1 rle with old method : 0.008713006973266602 time for calcul the mask position with numpy : 0.05467367172241211 nb_pixel_total : 52412 time to create 1 rle with old method : 0.060880184173583984 time for calcul the mask position with numpy : 0.0557863712310791 nb_pixel_total : 104640 time to create 1 rle with old method : 0.13315272331237793 time for calcul the mask position with numpy : 0.05734896659851074 nb_pixel_total : 5661 time to create 1 rle with old method : 0.0070874691009521484 time for calcul the mask position with numpy : 0.06393122673034668 nb_pixel_total : 492509 time to create 1 rle with new method : 1.4247372150421143 time for calcul the mask position with numpy : 0.05408763885498047 nb_pixel_total : 20449 time to create 1 rle with old method : 0.024303436279296875 time for calcul the mask position with numpy : 0.05373430252075195 nb_pixel_total : 1755 time to create 1 rle with old method : 0.0023488998413085938 time for calcul the mask position with numpy : 0.05380105972290039 nb_pixel_total : 12102 time to create 1 rle with old method : 0.015282154083251953 time for calcul the mask position with numpy : 0.05442523956298828 nb_pixel_total : 2665 time to create 1 rle with old method : 0.0031964778900146484 time for calcul the mask position with numpy : 0.0537409782409668 nb_pixel_total : 7359 time to create 1 rle with old method : 0.008712530136108398 time for calcul the mask position with numpy : 0.05439925193786621 nb_pixel_total : 49048 time to create 1 rle with old method : 0.05723690986633301 time for calcul the mask position with numpy : 0.05494070053100586 nb_pixel_total : 143284 time to create 1 rle with old method : 0.16449666023254395 time for calcul the mask position with numpy : 0.056887149810791016 nb_pixel_total : 372668 time to create 1 rle with new method : 0.45201587677001953 time for calcul the mask position with numpy : 0.057457685470581055 nb_pixel_total : 31361 time to create 1 rle with old method : 0.03658866882324219 time for calcul the mask position with numpy : 0.054409027099609375 nb_pixel_total : 113655 time to create 1 rle with old method : 0.1407458782196045 time for calcul the mask position with numpy : 0.058826446533203125 nb_pixel_total : 978 time to create 1 rle with old method : 0.0017077922821044922 time for calcul the mask position with numpy : 0.05666542053222656 nb_pixel_total : 48157 time to create 1 rle with old method : 0.05600118637084961 time for calcul the mask position with numpy : 0.054912567138671875 nb_pixel_total : 174590 time to create 1 rle with new method : 0.24550342559814453 time for calcul the mask position with numpy : 0.05361437797546387 nb_pixel_total : 227 time to create 1 rle with old method : 0.00031256675720214844 time for calcul the mask position with numpy : 0.056740522384643555 nb_pixel_total : 422714 time to create 1 rle with new method : 0.7471258640289307 time for calcul the mask position with numpy : 0.055062055587768555 nb_pixel_total : 128848 time to create 1 rle with old method : 0.15064716339111328 time for calcul the mask position with numpy : 0.05408477783203125 nb_pixel_total : 83507 time to create 1 rle with old method : 0.09500932693481445 time for calcul the mask position with numpy : 0.05440521240234375 nb_pixel_total : 56535 time to create 1 rle with old method : 0.06506824493408203 time for calcul the mask position with numpy : 0.05460667610168457 nb_pixel_total : 10212 time to create 1 rle with old method : 0.012205123901367188 time for calcul the mask position with numpy : 0.054050445556640625 nb_pixel_total : 1442 time to create 1 rle with old method : 0.00182342529296875 create new chi : 23.46218180656433 time to delete rle : 0.006444692611694336 batch 1 Loaded 61 chid ids of type : 4855 Number RLEs to save : 55785 TO DO : save crop sub photo not yet done ! save time : 5.339334726333618 nb_obj : 72 nb_hashtags : 10 time to prepare the origin masks : 56.3152859210968 time for calcul the mask position with numpy : 0.08712577819824219 nb_pixel_total : 2959898 time to create 1 rle with new method : 1.0921342372894287 time for calcul the mask position with numpy : 0.05371356010437012 nb_pixel_total : 29456 time to create 1 rle with old method : 0.03347921371459961 time for calcul the mask position with numpy : 0.05295205116271973 nb_pixel_total : 2905 time to create 1 rle with old method : 0.003898143768310547 time for calcul the mask position with numpy : 0.052950143814086914 nb_pixel_total : 58902 time to create 1 rle with old method : 0.06698870658874512 time for calcul the mask position with numpy : 0.05496835708618164 nb_pixel_total : 115718 time to create 1 rle with old method : 0.13799834251403809 time for calcul the mask position with numpy : 0.05126523971557617 nb_pixel_total : 6582 time to create 1 rle with old method : 0.007682085037231445 time for calcul the mask position with numpy : 0.05218362808227539 nb_pixel_total : 56089 time to create 1 rle with old method : 0.06774497032165527 time for calcul the mask position with numpy : 0.052512168884277344 nb_pixel_total : 14610 time to create 1 rle with old method : 0.018979549407958984 time for calcul the mask position with numpy : 0.05536031723022461 nb_pixel_total : 2578 time to create 1 rle with old method : 0.003023386001586914 time for calcul the mask position with numpy : 0.05812573432922363 nb_pixel_total : 458322 time to create 1 rle with new method : 0.6696527004241943 time for calcul the mask position with numpy : 0.052773475646972656 nb_pixel_total : 88353 time to create 1 rle with old method : 0.09658551216125488 time for calcul the mask position with numpy : 0.051425933837890625 nb_pixel_total : 20877 time to create 1 rle with old method : 0.023235321044921875 time for calcul the mask position with numpy : 0.052525997161865234 nb_pixel_total : 115218 time to create 1 rle with old method : 0.1264176368713379 time for calcul the mask position with numpy : 0.05308079719543457 nb_pixel_total : 137855 time to create 1 rle with old method : 0.15703058242797852 time for calcul the mask position with numpy : 0.05469918251037598 nb_pixel_total : 306280 time to create 1 rle with new method : 0.6313004493713379 time for calcul the mask position with numpy : 0.05284595489501953 nb_pixel_total : 119493 time to create 1 rle with old method : 0.13615202903747559 time for calcul the mask position with numpy : 0.05260777473449707 nb_pixel_total : 209170 time to create 1 rle with new method : 0.6902163028717041 time for calcul the mask position with numpy : 0.05216360092163086 nb_pixel_total : 8057 time to create 1 rle with old method : 0.009894132614135742 time for calcul the mask position with numpy : 0.052533626556396484 nb_pixel_total : 15222 time to create 1 rle with old method : 0.017260313034057617 time for calcul the mask position with numpy : 0.0522458553314209 nb_pixel_total : 16612 time to create 1 rle with old method : 0.019268274307250977 time for calcul the mask position with numpy : 0.05241656303405762 nb_pixel_total : 22379 time to create 1 rle with old method : 0.025864839553833008 time for calcul the mask position with numpy : 0.05286049842834473 nb_pixel_total : 14015 time to create 1 rle with old method : 0.01642632484436035 time for calcul the mask position with numpy : 0.05925559997558594 nb_pixel_total : 736456 time to create 1 rle with new method : 0.6679303646087646 time for calcul the mask position with numpy : 0.0537111759185791 nb_pixel_total : 284852 time to create 1 rle with new method : 0.7430753707885742 time for calcul the mask position with numpy : 0.05441880226135254 nb_pixel_total : 56609 time to create 1 rle with old method : 0.06783938407897949 time for calcul the mask position with numpy : 0.05287051200866699 nb_pixel_total : 50952 time to create 1 rle with old method : 0.05628538131713867 time for calcul the mask position with numpy : 0.05351400375366211 nb_pixel_total : 354656 time to create 1 rle with new method : 0.7294838428497314 time for calcul the mask position with numpy : 0.05339384078979492 nb_pixel_total : 69691 time to create 1 rle with old method : 0.07724118232727051 time for calcul the mask position with numpy : 0.052884578704833984 nb_pixel_total : 230919 time to create 1 rle with new method : 0.6029119491577148 time for calcul the mask position with numpy : 0.05171537399291992 nb_pixel_total : 4108 time to create 1 rle with old method : 0.005080461502075195 time for calcul the mask position with numpy : 0.053542375564575195 nb_pixel_total : 176610 time to create 1 rle with new method : 0.5861632823944092 time for calcul the mask position with numpy : 0.05263543128967285 nb_pixel_total : 2967 time to create 1 rle with old method : 0.003926992416381836 time for calcul the mask position with numpy : 0.054817914962768555 nb_pixel_total : 2765 time to create 1 rle with old method : 0.004120349884033203 time for calcul the mask position with numpy : 0.05313682556152344 nb_pixel_total : 30467 time to create 1 rle with old method : 0.034683942794799805 time for calcul the mask position with numpy : 0.07327675819396973 nb_pixel_total : 2848 time to create 1 rle with old method : 0.004001617431640625 time for calcul the mask position with numpy : 0.05341601371765137 nb_pixel_total : 8278 time to create 1 rle with old method : 0.010296106338500977 time for calcul the mask position with numpy : 0.054785728454589844 nb_pixel_total : 46941 time to create 1 rle with old method : 0.05322527885437012 time for calcul the mask position with numpy : 0.053484201431274414 nb_pixel_total : 257128 time to create 1 rle with new method : 0.6397740840911865 time for calcul the mask position with numpy : 0.05232357978820801 nb_pixel_total : 56669 time to create 1 rle with old method : 0.07041025161743164 time for calcul the mask position with numpy : 0.05162382125854492 nb_pixel_total : 36945 time to create 1 rle with old method : 0.041229963302612305 time for calcul the mask position with numpy : 0.05944371223449707 nb_pixel_total : 178106 time to create 1 rle with new method : 0.6602809429168701 time for calcul the mask position with numpy : 0.05220437049865723 nb_pixel_total : 18941 time to create 1 rle with old method : 0.021649837493896484 time for calcul the mask position with numpy : 0.051550865173339844 nb_pixel_total : 63782 time to create 1 rle with old method : 0.07361364364624023 time for calcul the mask position with numpy : 0.05229043960571289 nb_pixel_total : 103912 time to create 1 rle with old method : 0.1197209358215332 time for calcul the mask position with numpy : 0.05217742919921875 nb_pixel_total : 41931 time to create 1 rle with old method : 0.04789400100708008 time for calcul the mask position with numpy : 0.05202507972717285 nb_pixel_total : 51637 time to create 1 rle with old method : 0.05756831169128418 time for calcul the mask position with numpy : 0.053968191146850586 nb_pixel_total : 489392 time to create 1 rle with new method : 0.672713041305542 time for calcul the mask position with numpy : 0.053933143615722656 nb_pixel_total : 3249 time to create 1 rle with old method : 0.003950834274291992 time for calcul the mask position with numpy : 0.06047821044921875 nb_pixel_total : 859712 time to create 1 rle with new method : 0.7135896682739258 time for calcul the mask position with numpy : 0.056839704513549805 nb_pixel_total : 127827 time to create 1 rle with old method : 0.14588260650634766 time for calcul the mask position with numpy : 0.0529634952545166 nb_pixel_total : 25410 time to create 1 rle with old method : 0.02907419204711914 time for calcul the mask position with numpy : 0.053458452224731445 nb_pixel_total : 27444 time to create 1 rle with old method : 0.03431248664855957 time for calcul the mask position with numpy : 0.05455493927001953 nb_pixel_total : 75465 time to create 1 rle with old method : 0.0888361930847168 time for calcul the mask position with numpy : 0.05379056930541992 nb_pixel_total : 4056 time to create 1 rle with old method : 0.005130767822265625 time for calcul the mask position with numpy : 0.05409955978393555 nb_pixel_total : 36640 time to create 1 rle with old method : 0.04514789581298828 time for calcul the mask position with numpy : 0.054802894592285156 nb_pixel_total : 193786 time to create 1 rle with new method : 0.7317590713500977 time for calcul the mask position with numpy : 0.053287506103515625 nb_pixel_total : 43695 time to create 1 rle with old method : 0.05074787139892578 time for calcul the mask position with numpy : 0.061614274978637695 nb_pixel_total : 886860 time to create 1 rle with new method : 0.7448639869689941 time for calcul the mask position with numpy : 0.05616593360900879 nb_pixel_total : 341811 time to create 1 rle with new method : 0.6928870677947998 time for calcul the mask position with numpy : 0.05510425567626953 nb_pixel_total : 104796 time to create 1 rle with old method : 0.12661242485046387 time for calcul the mask position with numpy : 0.05402541160583496 nb_pixel_total : 8112 time to create 1 rle with old method : 0.009822607040405273 time for calcul the mask position with numpy : 0.06360888481140137 nb_pixel_total : 732327 time to create 1 rle with new method : 0.5932683944702148 time for calcul the mask position with numpy : 0.055748701095581055 nb_pixel_total : 474715 time to create 1 rle with new method : 0.6861493587493896 time for calcul the mask position with numpy : 0.05196189880371094 nb_pixel_total : 108612 time to create 1 rle with old method : 0.1239631175994873 time for calcul the mask position with numpy : 0.053598642349243164 nb_pixel_total : 166245 time to create 1 rle with new method : 0.8766875267028809 time for calcul the mask position with numpy : 0.05287957191467285 nb_pixel_total : 29030 time to create 1 rle with old method : 0.034035444259643555 time for calcul the mask position with numpy : 0.05776548385620117 nb_pixel_total : 334044 time to create 1 rle with new method : 0.6612048149108887 time for calcul the mask position with numpy : 0.052308082580566406 nb_pixel_total : 81679 time to create 1 rle with old method : 0.09805464744567871 time for calcul the mask position with numpy : 0.05340409278869629 nb_pixel_total : 90164 time to create 1 rle with old method : 0.10105180740356445 time for calcul the mask position with numpy : 0.05256199836730957 nb_pixel_total : 13396 time to create 1 rle with old method : 0.015044927597045898 time for calcul the mask position with numpy : 0.05169057846069336 nb_pixel_total : 465 time to create 1 rle with old method : 0.0006260871887207031 time for calcul the mask position with numpy : 0.05221152305603027 nb_pixel_total : 22661 time to create 1 rle with old method : 0.025967121124267578 time for calcul the mask position with numpy : 0.052828073501586914 nb_pixel_total : 50846 time to create 1 rle with old method : 0.06110811233520508 create new chi : 21.492818355560303 time to delete rle : 0.005572319030761719 batch 1 Loaded 73 chid ids of type : 4855 Number RLEs to save : 65730 TO DO : save crop sub photo not yet done ! save time : 6.1667869091033936 nb_obj : 69 nb_hashtags : 9 time to prepare the origin masks : 48.29496955871582 time for calcul the mask position with numpy : 0.07974481582641602 nb_pixel_total : 4093381 time to create 1 rle with new method : 0.2621762752532959 time for calcul the mask position with numpy : 0.058992624282836914 nb_pixel_total : 22480 time to create 1 rle with old method : 0.025655746459960938 time for calcul the mask position with numpy : 0.052797794342041016 nb_pixel_total : 6955 time to create 1 rle with old method : 0.007985830307006836 time for calcul the mask position with numpy : 0.05281662940979004 nb_pixel_total : 23396 time to create 1 rle with old method : 0.027695655822753906 time for calcul the mask position with numpy : 0.060239315032958984 nb_pixel_total : 45592 time to create 1 rle with old method : 0.06338024139404297 time for calcul the mask position with numpy : 0.054570913314819336 nb_pixel_total : 17526 time to create 1 rle with old method : 0.02056288719177246 time for calcul the mask position with numpy : 0.05401778221130371 nb_pixel_total : 14583 time to create 1 rle with old method : 0.017053842544555664 time for calcul the mask position with numpy : 0.0580906867980957 nb_pixel_total : 84785 time to create 1 rle with old method : 0.10940074920654297 time for calcul the mask position with numpy : 0.05416989326477051 nb_pixel_total : 45470 time to create 1 rle with old method : 0.053385257720947266 time for calcul the mask position with numpy : 0.05379533767700195 nb_pixel_total : 10002 time to create 1 rle with old method : 0.012305736541748047 time for calcul the mask position with numpy : 0.05456352233886719 nb_pixel_total : 150897 time to create 1 rle with new method : 0.22948002815246582 time for calcul the mask position with numpy : 0.05292320251464844 nb_pixel_total : 83838 time to create 1 rle with old method : 0.09419536590576172 time for calcul the mask position with numpy : 0.05310845375061035 nb_pixel_total : 143490 time to create 1 rle with old method : 0.1611027717590332 time for calcul the mask position with numpy : 0.052054405212402344 nb_pixel_total : 37989 time to create 1 rle with old method : 0.04341554641723633 time for calcul the mask position with numpy : 0.0520632266998291 nb_pixel_total : 41113 time to create 1 rle with old method : 0.06608462333679199 time for calcul the mask position with numpy : 0.055208683013916016 nb_pixel_total : 129289 time to create 1 rle with old method : 0.14528250694274902 time for calcul the mask position with numpy : 0.05257463455200195 nb_pixel_total : 160520 time to create 1 rle with new method : 0.22749733924865723 time for calcul the mask position with numpy : 0.049959421157836914 nb_pixel_total : 4012 time to create 1 rle with old method : 0.004721879959106445 time for calcul the mask position with numpy : 0.05135083198547363 nb_pixel_total : 96364 time to create 1 rle with old method : 0.10562705993652344 time for calcul the mask position with numpy : 0.051130056381225586 nb_pixel_total : 849 time to create 1 rle with old method : 0.0010371208190917969 time for calcul the mask position with numpy : 0.05100679397583008 nb_pixel_total : 9888 time to create 1 rle with old method : 0.011048555374145508 time for calcul the mask position with numpy : 0.050789833068847656 nb_pixel_total : 17623 time to create 1 rle with old method : 0.02001953125 time for calcul the mask position with numpy : 0.05241751670837402 nb_pixel_total : 54478 time to create 1 rle with old method : 0.062280893325805664 time for calcul the mask position with numpy : 0.0548243522644043 nb_pixel_total : 376159 time to create 1 rle with new method : 0.22420358657836914 time for calcul the mask position with numpy : 0.05149197578430176 nb_pixel_total : 188750 time to create 1 rle with new method : 0.2325305938720703 time for calcul the mask position with numpy : 0.05128908157348633 nb_pixel_total : 18431 time to create 1 rle with old method : 0.020901203155517578 time for calcul the mask position with numpy : 0.051328420639038086 nb_pixel_total : 100982 time to create 1 rle with old method : 0.1104276180267334 time for calcul the mask position with numpy : 0.05150294303894043 nb_pixel_total : 23744 time to create 1 rle with old method : 0.031245708465576172 time for calcul the mask position with numpy : 0.06135272979736328 nb_pixel_total : 174648 time to create 1 rle with new method : 0.23041510581970215 time for calcul the mask position with numpy : 0.05164527893066406 nb_pixel_total : 35942 time to create 1 rle with old method : 0.04061293601989746 time for calcul the mask position with numpy : 0.052632808685302734 nb_pixel_total : 57707 time to create 1 rle with old method : 0.06500768661499023 time for calcul the mask position with numpy : 0.052031755447387695 nb_pixel_total : 83479 time to create 1 rle with old method : 0.09176015853881836 time for calcul the mask position with numpy : 0.050901174545288086 nb_pixel_total : 53104 time to create 1 rle with old method : 0.05948495864868164 time for calcul the mask position with numpy : 0.05185532569885254 nb_pixel_total : 76367 time to create 1 rle with old method : 0.08573412895202637 time for calcul the mask position with numpy : 0.05141019821166992 nb_pixel_total : 56760 time to create 1 rle with old method : 0.06491851806640625 time for calcul the mask position with numpy : 0.05166745185852051 nb_pixel_total : 278854 time to create 1 rle with new method : 0.22544288635253906 time for calcul the mask position with numpy : 0.05227851867675781 nb_pixel_total : 112287 time to create 1 rle with old method : 0.12328243255615234 time for calcul the mask position with numpy : 0.05294990539550781 nb_pixel_total : 1465 time to create 1 rle with old method : 0.002263307571411133 time for calcul the mask position with numpy : 0.05440402030944824 nb_pixel_total : 67350 time to create 1 rle with old method : 0.07886576652526855 time for calcul the mask position with numpy : 0.05686831474304199 nb_pixel_total : 63645 time to create 1 rle with old method : 0.0819709300994873 time for calcul the mask position with numpy : 0.058722734451293945 nb_pixel_total : 41245 time to create 1 rle with old method : 0.060210227966308594 time for calcul the mask position with numpy : 0.06624245643615723 nb_pixel_total : 142857 time to create 1 rle with old method : 0.16339945793151855 time for calcul the mask position with numpy : 0.058135986328125 nb_pixel_total : 475628 time to create 1 rle with new method : 0.23369717597961426 time for calcul the mask position with numpy : 0.05990099906921387 nb_pixel_total : 492159 time to create 1 rle with new method : 0.30577802658081055 time for calcul the mask position with numpy : 0.053307294845581055 nb_pixel_total : 14226 time to create 1 rle with old method : 0.017511844635009766 time for calcul the mask position with numpy : 0.052788734436035156 nb_pixel_total : 35655 time to create 1 rle with old method : 0.04097104072570801 time for calcul the mask position with numpy : 0.05394434928894043 nb_pixel_total : 110991 time to create 1 rle with old method : 0.1263432502746582 time for calcul the mask position with numpy : 0.055364131927490234 nb_pixel_total : 250499 time to create 1 rle with new method : 0.22316980361938477 time for calcul the mask position with numpy : 0.05247688293457031 nb_pixel_total : 21490 time to create 1 rle with old method : 0.023959636688232422 time for calcul the mask position with numpy : 0.053450584411621094 nb_pixel_total : 208783 time to create 1 rle with new method : 0.22255587577819824 time for calcul the mask position with numpy : 0.05268049240112305 nb_pixel_total : 114781 time to create 1 rle with old method : 0.13457489013671875 time for calcul the mask position with numpy : 0.05452299118041992 nb_pixel_total : 207387 time to create 1 rle with new method : 0.23483848571777344 time for calcul the mask position with numpy : 0.05755877494812012 nb_pixel_total : 558974 time to create 1 rle with new method : 0.2378840446472168 time for calcul the mask position with numpy : 0.06380057334899902 nb_pixel_total : 1131051 time to create 1 rle with new method : 0.24704265594482422 time for calcul the mask position with numpy : 0.05409407615661621 nb_pixel_total : 3737 time to create 1 rle with old method : 0.0064945220947265625 time for calcul the mask position with numpy : 0.06029558181762695 nb_pixel_total : 2993 time to create 1 rle with old method : 0.004451274871826172 time for calcul the mask position with numpy : 0.05406761169433594 nb_pixel_total : 92788 time to create 1 rle with old method : 0.10617923736572266 time for calcul the mask position with numpy : 0.05461001396179199 nb_pixel_total : 4402 time to create 1 rle with old method : 0.007392168045043945 time for calcul the mask position with numpy : 0.06090545654296875 nb_pixel_total : 102380 time to create 1 rle with old method : 0.11881327629089355 time for calcul the mask position with numpy : 0.052550315856933594 nb_pixel_total : 5877 time to create 1 rle with old method : 0.006775856018066406 time for calcul the mask position with numpy : 0.06080007553100586 nb_pixel_total : 1304228 time to create 1 rle with new method : 0.22699880599975586 time for calcul the mask position with numpy : 0.05248141288757324 nb_pixel_total : 3998 time to create 1 rle with old method : 0.00525665283203125 time for calcul the mask position with numpy : 0.060115814208984375 nb_pixel_total : 93876 time to create 1 rle with old method : 0.11541986465454102 time for calcul the mask position with numpy : 0.05331015586853027 nb_pixel_total : 114668 time to create 1 rle with old method : 0.12987351417541504 time for calcul the mask position with numpy : 0.05366325378417969 nb_pixel_total : 46026 time to create 1 rle with old method : 0.052703857421875 time for calcul the mask position with numpy : 0.053580284118652344 nb_pixel_total : 235585 time to create 1 rle with new method : 0.2245481014251709 time for calcul the mask position with numpy : 0.05332303047180176 nb_pixel_total : 28887 time to create 1 rle with old method : 0.03349494934082031 time for calcul the mask position with numpy : 0.054482460021972656 nb_pixel_total : 44774 time to create 1 rle with old method : 0.051749229431152344 time for calcul the mask position with numpy : 0.05280256271362305 nb_pixel_total : 23863 time to create 1 rle with old method : 0.029254674911499023 time for calcul the mask position with numpy : 0.05275988578796387 nb_pixel_total : 1198 time to create 1 rle with old method : 0.0016176700592041016 create new chi : 11.129979133605957 time to delete rle : 0.005229473114013672 batch 1 Loaded 70 chid ids of type : 4855 Number RLEs to save : 58068 TO DO : save crop sub photo not yet done ! save time : 5.50171422958374 nb_obj : 14 nb_hashtags : 4 time to prepare the origin masks : 19.76034450531006 time for calcul the mask position with numpy : 0.07977867126464844 nb_pixel_total : 1464986 time to create 1 rle with new method : 2.1490275859832764 time for calcul the mask position with numpy : 0.03622269630432129 nb_pixel_total : 9796 time to create 1 rle with old method : 0.013036966323852539 time for calcul the mask position with numpy : 0.03924679756164551 nb_pixel_total : 394441 time to create 1 rle with new method : 0.815237283706665 time for calcul the mask position with numpy : 0.03739142417907715 nb_pixel_total : 6032 time to create 1 rle with old method : 0.00723576545715332 time for calcul the mask position with numpy : 0.04036116600036621 nb_pixel_total : 360703 time to create 1 rle with new method : 0.8726174831390381 time for calcul the mask position with numpy : 0.04520297050476074 nb_pixel_total : 11991 time to create 1 rle with old method : 0.014626502990722656 time for calcul the mask position with numpy : 0.04343676567077637 nb_pixel_total : 311967 time to create 1 rle with new method : 0.8399593830108643 time for calcul the mask position with numpy : 0.0388948917388916 nb_pixel_total : 31805 time to create 1 rle with old method : 0.03562498092651367 time for calcul the mask position with numpy : 0.037572383880615234 nb_pixel_total : 148483 time to create 1 rle with old method : 0.16602110862731934 time for calcul the mask position with numpy : 0.041840553283691406 nb_pixel_total : 129366 time to create 1 rle with old method : 0.1466996669769287 time for calcul the mask position with numpy : 0.03925657272338867 nb_pixel_total : 44499 time to create 1 rle with old method : 0.05033755302429199 time for calcul the mask position with numpy : 0.06944584846496582 nb_pixel_total : 1980855 time to create 1 rle with new method : 0.8304779529571533 time for calcul the mask position with numpy : 0.21405553817749023 nb_pixel_total : 3274517 time to create 1 rle with new method : 0.9087269306182861 time for calcul the mask position with numpy : 0.07395219802856445 nb_pixel_total : 1460306 time to create 1 rle with new method : 1.058462142944336 time for calcul the mask position with numpy : 0.380979061126709 nb_pixel_total : 3349453 time to create 1 rle with new method : 1.571540117263794 create new chi : 11.072936773300171 time to delete rle : 0.0027799606323242188 batch 1 Loaded 15 chid ids of type : 4855 Number RLEs to save : 34323 TO DO : save crop sub photo not yet done ! save time : 3.299673318862915 map_output_result : {1389772234: (0.20237075270332455, 'Should be the crop_list due to order', 0.183169141455011), 1389772233: (0.20237075270332455, 'Should be the crop_list due to order', 0.32418156645332236), 1389772231: (0.20237075270332455, 'Should be the crop_list due to order', 0.24751364759648717), 1389772229: (0.20237075270332455, 'Should be the crop_list due to order', 0.07229330072460859), 1389772225: (0.20237075270332455, 'Should be the crop_list due to order', 0.18469610728719357)} 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 [1389772234, 1389772233, 1389772231, 1389772229, 1389772225] Looping around the photos to save general results len do output : 5 /1389772234.Didn't retrieve data . /1389772233.Didn't retrieve data . /1389772231.Didn't retrieve data . /1389772229.Didn't retrieve data . /1389772225.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 ('4741', None, None, None, None, None, None, None, '3953017') ('4741', '27873696', '1389772234', None, None, None, None, None, '3953017') ('4741', None, None, None, None, None, None, None, '3953017') ('4741', '27873696', '1389772233', None, None, None, None, None, '3953017') ('4741', None, None, None, None, None, None, None, '3953017') ('4741', '27873696', '1389772231', None, None, None, None, None, '3953017') ('4741', None, None, None, None, None, None, None, '3953017') ('4741', '27873696', '1389772229', None, None, None, None, None, '3953017') ('4741', None, None, None, None, None, None, None, '3953017') ('4741', '27873696', '1389772225', None, None, None, None, None, '3953017') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 15 time used for this insertion : 0.03876042366027832 save_final save missing photos in datou_result : time spend for datou_step_exec : 363.4155032634735 time spend to save output : 0.07872653007507324 total time spend for step 5 : 363.4942297935486 step6:crop_condition Fri Oct 17 10:35:46 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed 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 some photos are not treated, begin crop_condition Loading chi in step crop with photo_hashtag_type : 4855 Loading chi in step crop for list_pids : 5 ! batch 1 Loaded 283 chid ids of type : 4855 begin to crop the class : papier param for this class : {'min_score': 0.1} filtre for class : papier hashtag_id of this class : 492668766 Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! map_result returned by crop_photo_return_map_crop : length : 57 About to insert : list_path_to_insert length 57 new photo from crops ! About to upload 57 photos upload in portfolio : 3015255 init cache_photo without model_param we have 57 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1760690229_752055 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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57_rle_crop_4000151477_0.png', 0, 347, 454, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57_rle_crop_4000151483_0.png', 0, 633, 836, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57_rle_crop_4000151470_0.png', 0, 339, 329, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57_rle_crop_4000151461_0.png', 0, 463, 468, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57_rle_crop_4000151471_0.png', 0, 623, 714, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57_rle_crop_4000151474_0.png', 0, 1896, 1509, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57_rle_crop_4000151463_0.png', 0, 1622, 868, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57_rle_crop_4000151448_0.png', 0, 568, 321, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57_rle_crop_4000151444_0.png', 0, 255, 251, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57_rle_crop_4000151485_0.png', 0, 523, 671, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57_rle_crop_4000151478_0.png', 0, 479, 524, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57_rle_crop_4000151464_0.png', 0, 257, 389, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57_rle_crop_4000151449_0.png', 0, 763, 941, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57_rle_crop_4000151440_0.png', 0, 431, 589, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57_rle_crop_4000151433_0.png', 0, 289, 486, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772233_5048c8487627fd84ace06f8bef2b5109_rle_crop_4000155490_0.png', 0, 409, 530, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772233_5048c8487627fd84ace06f8bef2b5109_rle_crop_4000155482_0.png', 0, 790, 756, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772233_5048c8487627fd84ace06f8bef2b5109_rle_crop_4000155499_0.png', 0, 1093, 1918, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772233_5048c8487627fd84ace06f8bef2b5109_rle_crop_4000155519_0.png', 0, 380, 578, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772233_5048c8487627fd84ace06f8bef2b5109_rle_crop_4000155495_0.png', 0, 644, 527, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772233_5048c8487627fd84ace06f8bef2b5109_rle_crop_4000155479_0.png', 0, 615, 612, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772233_5048c8487627fd84ace06f8bef2b5109_rle_crop_4000155521_0.png', 0, 1038, 575, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772233_5048c8487627fd84ace06f8bef2b5109_rle_crop_4000155498_0.png', 0, 1294, 912, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772233_5048c8487627fd84ace06f8bef2b5109_rle_crop_4000155514_0.png', 0, 742, 1145, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772233_5048c8487627fd84ace06f8bef2b5109_rle_crop_4000155522_0.png', 0, 556, 341, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772233_5048c8487627fd84ace06f8bef2b5109_rle_crop_4000155489_0.png', 0, 222, 314, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772233_5048c8487627fd84ace06f8bef2b5109_rle_crop_4000155518_0.png', 0, 178, 409, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155865_0.png', 0, 132, 284, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155890_0.png', 0, 477, 1255, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155921_0.png', 0, 963, 1257, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155891_0.png', 0, 264, 395, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155904_0.png', 0, 634, 456, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155918_0.png', 0, 227, 327, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155930_0.png', 0, 1246, 499, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155922_0.png', 0, 598, 1014, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155886_0.png', 0, 712, 1347, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155910_0.png', 0, 706, 963, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155932_0.png', 0, 642, 385, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155880_0.png', 0, 416, 715, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155873_0.png', 0, 605, 987, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155901_0.png', 0, 524, 760, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155936_0.png', 0, 416, 214, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155876_0.png', 0, 327, 790, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164478_0.png', 0, 552, 950, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164515_0.png', 0, 1646, 1051, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164504_0.png', 0, 597, 485, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164496_0.png', 0, 665, 341, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164507_0.png', 0, 996, 811, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164467_0.png', 0, 584, 355, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164506_0.png', 0, 570, 670, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164508_0.png', 0, 1255, 1370, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164505_0.png', 0, 560, 430, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164520_0.png', 0, 1262, 480, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164497_0.png', 0, 1146, 859, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164502_0.png', 0, 460, 836, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164522_0.png', 0, 249, 322, 0, 1760690251,'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(1760690251), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772225_d0a8609c6715c5f1a67191409dd5978c_rle_crop_4000164943_0.png', 0, 2163, 1394, 0, 1760690251,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 57 photos in the portfolio 3015255 time of upload the photos Elapsed time : 134.3936026096344 we have finished the crop for the class : papier begin to crop the class : carton param for this class : {'min_score': 0.1} filtre for class : carton hashtag_id of this class : 492774966 Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! map_result returned by crop_photo_return_map_crop : length : 47 About to insert : list_path_to_insert length 47 new photo from crops ! About to upload 47 photos upload in portfolio : 3015255 init cache_photo without model_param we have 47 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1760690401_752055 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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57_rle_crop_4000151430_0.png', 0, 403, 318, 0, 1760690410,'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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57_rle_crop_4000151447_0.png', 0, 320, 345, 0, 1760690410,'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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57_rle_crop_4000151434_0.png', 0, 1193, 702, 0, 1760690410,'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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57_rle_crop_4000151429_0.png', 0, 480, 249, 0, 1760690410,'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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57_rle_crop_4000151441_0.png', 0, 775, 633, 0, 1760690410,'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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57_rle_crop_4000151435_0.png', 0, 324, 349, 0, 1760690410,'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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57_rle_crop_4000151432_0.png', 0, 920, 691, 0, 1760690410,'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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57_rle_crop_4000151468_0.png', 0, 728, 635, 0, 1760690410,'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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57_rle_crop_4000151446_0.png', 0, 716, 491, 0, 1760690410,'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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57_rle_crop_4000151476_0.png', 0, 624, 514, 0, 1760690410,'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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57_rle_crop_4000151488_0.png', 0, 410, 550, 0, 1760690410,'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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57_rle_crop_4000151480_0.png', 0, 612, 659, 0, 1760690410,'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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57_rle_crop_4000151437_0.png', 0, 748, 718, 0, 1760690410,'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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57_rle_crop_4000151431_0.png', 0, 497, 213, 0, 1760690410,'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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772233_5048c8487627fd84ace06f8bef2b5109_rle_crop_4000155473_0.png', 0, 1741, 1671, 0, 1760690410,'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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772233_5048c8487627fd84ace06f8bef2b5109_rle_crop_4000155524_0.png', 0, 373, 213, 0, 1760690410,'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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772233_5048c8487627fd84ace06f8bef2b5109_rle_crop_4000155492_0.png', 0, 618, 227, 0, 1760690410,'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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772233_5048c8487627fd84ace06f8bef2b5109_rle_crop_4000155487_0.png', 0, 274, 382, 0, 1760690410,'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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772233_5048c8487627fd84ace06f8bef2b5109_rle_crop_4000155485_0.png', 0, 708, 730, 0, 1760690410,'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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155907_0.png', 0, 263, 515, 0, 1760690410,'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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155919_0.png', 0, 369, 688, 0, 1760690410,'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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155870_0.png', 0, 333, 238, 0, 1760690410,'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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155887_0.png', 0, 576, 715, 0, 1760690410,'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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155874_0.png', 0, 286, 356, 0, 1760690410,'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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155871_0.png', 0, 298, 67, 0, 1760690410,'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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155882_0.png', 0, 259, 132, 0, 1760690410,'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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155868_0.png', 0, 480, 333, 0, 1760690410,'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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155877_0.png', 0, 491, 455, 0, 1760690410,'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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155923_0.png', 0, 591, 520, 0, 1760690410,'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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155925_0.png', 0, 1203, 1206, 0, 1760690410,'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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155931_0.png', 0, 411, 405, 0, 1760690410,'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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155892_0.png', 0, 565, 564, 0, 1760690410,'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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155929_0.png', 0, 345, 268, 0, 1760690410,'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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164511_0.png', 0, 246, 655, 0, 1760690410,'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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164521_0.png', 0, 245, 294, 0, 1760690410,'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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164479_0.png', 0, 683, 431, 0, 1760690410,'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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164498_0.png', 0, 1032, 671, 0, 1760690410,'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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164483_0.png', 0, 579, 622, 0, 1760690410,'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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164473_0.png', 0, 326, 439, 0, 1760690410,'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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164463_0.png', 0, 266, 262, 0, 1760690410,'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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164466_0.png', 0, 710, 393, 0, 1760690410,'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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164494_0.png', 0, 300, 322, 0, 1760690410,'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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164490_0.png', 0, 819, 525, 0, 1760690410,'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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164471_0.png', 0, 582, 405, 0, 1760690410,'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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164518_0.png', 0, 526, 425, 0, 1760690410,'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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164486_0.png', 0, 334, 376, 0, 1760690410,'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(1760690410), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164519_0.png', 0, 287, 250, 0, 1760690410,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 47 photos in the portfolio 3015255 time of upload the photos Elapsed time : 394.30646777153015 we have finished the crop for the class : carton begin to crop the class : metal param for this class : {'min_score': 0.1} filtre for class : metal hashtag_id of this class : 492628673 Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! 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 : 3015255 init cache_photo without model_param we have 19 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1760690805_752055 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(1760690809), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57_rle_crop_4000151467_0.png', 0, 209, 150, 0, 1760690809,'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(1760690809), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57_rle_crop_4000151457_0.png', 0, 458, 647, 0, 1760690809,'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(1760690809), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57_rle_crop_4000151445_0.png', 0, 132, 118, 0, 1760690809,'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(1760690809), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57_rle_crop_4000151466_0.png', 0, 285, 195, 0, 1760690809,'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(1760690809), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772233_5048c8487627fd84ace06f8bef2b5109_rle_crop_4000155469_0.png', 0, 319, 207, 0, 1760690809,'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(1760690809), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772233_5048c8487627fd84ace06f8bef2b5109_rle_crop_4000155500_0.png', 0, 468, 313, 0, 1760690809,'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(1760690809), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155903_0.png', 0, 306, 164, 0, 1760690809,'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(1760690809), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155920_0.png', 0, 277, 356, 0, 1760690809,'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(1760690809), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155867_0.png', 0, 296, 274, 0, 1760690809,'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(1760690809), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155900_0.png', 0, 335, 206, 0, 1760690809,'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(1760690809), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155909_0.png', 0, 231, 332, 0, 1760690809,'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(1760690809), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155884_0.png', 0, 181, 159, 0, 1760690809,'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(1760690809), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155889_0.png', 0, 266, 307, 0, 1760690809,'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(1760690809), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164468_0.png', 0, 202, 245, 0, 1760690809,'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(1760690809), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164485_0.png', 0, 252, 377, 0, 1760690809,'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(1760690809), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164482_0.png', 0, 205, 151, 0, 1760690809,'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(1760690809), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164503_0.png', 0, 161, 186, 0, 1760690809,'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(1760690809), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164493_0.png', 0, 338, 262, 0, 1760690809,'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(1760690809), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164481_0.png', 0, 476, 289, 0, 1760690809,'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 3015255 time of upload the photos Elapsed time : 167.6485824584961 we have finished the crop for the class : metal begin to crop the class : pet_clair param for this class : {'min_score': 0.1} filtre for class : pet_clair hashtag_id of this class : 2107755846 Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! map_result returned by crop_photo_return_map_crop : length : 11 About to insert : list_path_to_insert length 11 new photo from crops ! About to upload 11 photos upload in portfolio : 3015255 init cache_photo without model_param we have 11 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1760690985_752055 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(1760690987), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57_rle_crop_4000151452_0.png', 0, 265, 319, 0, 1760690987,'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(1760690987), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57_rle_crop_4000151491_0.png', 0, 361, 359, 0, 1760690987,'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(1760690987), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57_rle_crop_4000151490_0.png', 0, 665, 532, 0, 1760690987,'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(1760690987), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772233_5048c8487627fd84ace06f8bef2b5109_rle_crop_4000155488_0.png', 0, 554, 185, 0, 1760690987,'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(1760690987), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772233_5048c8487627fd84ace06f8bef2b5109_rle_crop_4000155516_0.png', 0, 435, 420, 0, 1760690987,'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(1760690987), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772233_5048c8487627fd84ace06f8bef2b5109_rle_crop_4000155515_0.png', 0, 308, 190, 0, 1760690987,'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(1760690987), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155914_0.png', 0, 208, 252, 0, 1760690987,'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(1760690987), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155916_0.png', 0, 275, 446, 0, 1760690987,'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(1760690987), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164487_0.png', 0, 156, 429, 0, 1760690987,'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(1760690987), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164488_0.png', 0, 414, 324, 0, 1760690987,'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(1760690987), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164501_0.png', 0, 273, 625, 0, 1760690987,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 11 photos in the portfolio 3015255 time of upload the photos Elapsed time : 140.42767143249512 we have finished the crop for the class : pet_clair begin to crop the class : pehd param for this class : {'min_score': 0.1} filtre for class : pehd hashtag_id of this class : 628944319 map_result returned by crop_photo_return_map_crop : length : 0 About to insert : list_path_to_insert length 0 new photo from crops ! About to upload 0 photos WARNING : list_path_to_insert is empty, cannot upload ! we have finished the crop for the class : pehd begin to crop the class : pet_fonce param for this class : {'min_score': 0.1} filtre for class : pet_fonce hashtag_id of this class : 2107755900 begin to crop the class : sac param for this class : {'min_score': 0.1} filtre for class : sac hashtag_id of this class : 492618350 Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! map_result returned by crop_photo_return_map_crop : length : 9 About to insert : list_path_to_insert length 9 new photo from crops ! About to upload 9 photos upload in portfolio : 3015255 init cache_photo without model_param we have 9 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1760691139_752055 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(1760691142), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57_rle_crop_4000151453_0.png', 0, 1023, 824, 0, 1760691142,'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(1760691142), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57_rle_crop_4000151460_0.png', 0, 235, 503, 0, 1760691142,'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(1760691142), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772233_5048c8487627fd84ace06f8bef2b5109_rle_crop_4000155478_0.png', 0, 389, 229, 0, 1760691142,'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(1760691142), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772233_5048c8487627fd84ace06f8bef2b5109_rle_crop_4000155483_0.png', 0, 103, 282, 0, 1760691142,'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(1760691142), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155912_0.png', 0, 819, 1254, 0, 1760691142,'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(1760691142), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155902_0.png', 0, 257, 573, 0, 1760691142,'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(1760691142), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155906_0.png', 0, 206, 374, 0, 1760691142,'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(1760691142), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164495_0.png', 0, 323, 168, 0, 1760691142,'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(1760691142), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164461_0.png', 0, 205, 103, 0, 1760691142,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 9 photos in the portfolio 3015255 time of upload the photos Elapsed time : 99.10944676399231 we have finished the crop for the class : sac begin to crop the class : textiles param for this class : {'min_score': 0.1} filtre for class : textiles hashtag_id of this class : 494789423 Next one ! map_result returned by crop_photo_return_map_crop : length : 1 About to insert : list_path_to_insert length 1 new photo from crops ! About to upload 1 photos upload in portfolio : 3015255 init cache_photo without model_param we have 1 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1760691245_752055 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(1760691245), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155894_0.png', 0, 692, 479, 0, 1760691245,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 1 photos in the portfolio 3015255 time of upload the photos Elapsed time : 9.316813468933105 we have finished the crop for the class : textiles begin to crop the class : verre param for this class : {'min_score': 0.1} filtre for class : verre hashtag_id of this class : 492631919 begin to crop the class : organique param for this class : {'min_score': 0.1} filtre for class : organique hashtag_id of this class : 530726390 begin to crop the class : dasri param for this class : {'min_score': 0.1} filtre for class : dasri hashtag_id of this class : 1608424396 begin to crop the class : masque param for this class : {'min_score': 0.1} filtre for class : masque hashtag_id of this class : 492626781 begin to crop the class : encombrant param for this class : {'min_score': 0.1} filtre for class : encombrant hashtag_id of this class : 605975549 begin to crop the class : autre param for this class : {'min_score': 0.1} filtre for class : autre hashtag_id of this class : 494826614 Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! map_result returned by crop_photo_return_map_crop : length : 13 About to insert : list_path_to_insert length 13 new photo from crops ! About to upload 13 photos upload in portfolio : 3015255 init cache_photo without model_param we have 13 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1760691276_752055 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(1760691279), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772233_5048c8487627fd84ace06f8bef2b5109_rle_crop_4000155467_0.png', 0, 1840, 902, 0, 1760691279,'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(1760691279), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772233_5048c8487627fd84ace06f8bef2b5109_rle_crop_4000155501_0.png', 0, 560, 649, 0, 1760691279,'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(1760691279), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772233_5048c8487627fd84ace06f8bef2b5109_rle_crop_4000155477_0.png', 0, 1394, 1102, 0, 1760691279,'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(1760691279), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772233_5048c8487627fd84ace06f8bef2b5109_rle_crop_4000155468_0.png', 0, 374, 319, 0, 1760691279,'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(1760691279), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155926_0.png', 0, 661, 1110, 0, 1760691279,'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(1760691279), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155878_0.png', 0, 719, 606, 0, 1760691279,'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(1760691279), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155897_0.png', 0, 239, 308, 0, 1760691279,'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(1760691279), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155879_0.png', 0, 422, 441, 0, 1760691279,'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(1760691279), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155928_0.png', 0, 412, 478, 0, 1760691279,'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(1760691279), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164470_0.png', 0, 496, 437, 0, 1760691279,'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(1760691279), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164523_0.png', 0, 282, 166, 0, 1760691279,'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(1760691279), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164491_0.png', 0, 389, 631, 0, 1760691279,'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(1760691279), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164517_0.png', 0, 357, 298, 0, 1760691279,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 13 photos in the portfolio 3015255 time of upload the photos Elapsed time : 120.39759159088135 we have finished the crop for the class : autre begin to crop the class : autre_emballage param for this class : {'min_score': 0.1} filtre for class : autre_emballage hashtag_id of this class : 2107760328 Next one ! map_result returned by crop_photo_return_map_crop : length : 1 About to insert : list_path_to_insert length 1 new photo from crops ! About to upload 1 photos upload in portfolio : 3015255 init cache_photo without model_param we have 1 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1760691401_752055 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(1760691401), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164500_0.png', 0, 219, 220, 0, 1760691401,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 1 photos in the portfolio 3015255 time of upload the photos Elapsed time : 15.996551275253296 we have finished the crop for the class : autre_emballage begin to crop the class : autre_non_emballage param for this class : {'min_score': 0.1} filtre for class : autre_non_emballage hashtag_id of this class : 2107760329 Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! 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 : 3015255 init cache_photo without model_param we have 7 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1760691429_752055 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(1760691430), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57_rle_crop_4000151443_0.png', 0, 175, 235, 0, 1760691430,'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(1760691430), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57_rle_crop_4000151462_0.png', 0, 694, 2145, 0, 1760691430,'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(1760691430), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772233_5048c8487627fd84ace06f8bef2b5109_rle_crop_4000155523_0.png', 0, 421, 317, 0, 1760691430,'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(1760691430), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772233_5048c8487627fd84ace06f8bef2b5109_rle_crop_4000155503_0.png', 0, 226, 368, 0, 1760691430,'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(1760691430), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772233_5048c8487627fd84ace06f8bef2b5109_rle_crop_4000155494_0.png', 0, 628, 549, 0, 1760691430,'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(1760691430), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772233_5048c8487627fd84ace06f8bef2b5109_rle_crop_4000155511_0.png', 0, 68, 166, 0, 1760691430,'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(1760691430), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772233_5048c8487627fd84ace06f8bef2b5109_rle_crop_4000155504_0.png', 0, 296, 446, 0, 1760691430,'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 3015255 time of upload the photos Elapsed time : 60.77366518974304 we have finished the crop for the class : autre_non_emballage begin to crop the class : environnement param for this class : {'min_score': 0.1} filtre for class : environnement hashtag_id of this class : 493012381 Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! Next one ! map_result returned by crop_photo_return_map_crop : length : 30 About to insert : list_path_to_insert length 30 new photo from crops ! About to upload 30 photos upload in portfolio : 3015255 init cache_photo without model_param we have 30 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1760691550_752055 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(1760691557), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57_rle_crop_4000151472_0.png', 0, 74, 267, 0, 1760691557,'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(1760691557), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57_rle_crop_4000151456_0.png', 0, 104, 120, 0, 1760691557,'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(1760691557), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57_rle_crop_4000151469_0.png', 0, 188, 48, 0, 1760691557,'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(1760691557), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57_rle_crop_4000151482_0.png', 0, 1253, 928, 0, 1760691557,'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(1760691557), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57_rle_crop_4000151473_0.png', 0, 234, 219, 0, 1760691557,'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(1760691557), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772234_aab207b67d90e1aebb38075581c72d57_rle_crop_4000151487_0.png', 0, 277, 222, 0, 1760691557,'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(1760691557), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772233_5048c8487627fd84ace06f8bef2b5109_rle_crop_4000155470_0.png', 0, 107, 174, 0, 1760691557,'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(1760691557), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772233_5048c8487627fd84ace06f8bef2b5109_rle_crop_4000155491_0.png', 0, 675, 383, 0, 1760691557,'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(1760691557), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772233_5048c8487627fd84ace06f8bef2b5109_rle_crop_4000155525_0.png', 0, 138, 154, 0, 1760691557,'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(1760691557), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772233_5048c8487627fd84ace06f8bef2b5109_rle_crop_4000155512_0.png', 0, 217, 546, 0, 1760691557,'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(1760691557), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772233_5048c8487627fd84ace06f8bef2b5109_rle_crop_4000155520_0.png', 0, 30, 24, 0, 1760691557,'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(1760691557), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772233_5048c8487627fd84ace06f8bef2b5109_rle_crop_4000155474_0.png', 0, 227, 130, 0, 1760691557,'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(1760691557), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155888_0.png', 0, 495, 262, 0, 1760691557,'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(1760691557), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155915_0.png', 0, 197, 224, 0, 1760691557,'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(1760691557), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155908_0.png', 0, 301, 292, 0, 1760691557,'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(1760691557), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772231_cd74a8e2b599018bb8e6739d4e07993f_rle_crop_4000155869_0.png', 0, 153, 65, 0, 1760691557,'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(1760691557), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164455_0.png', 0, 3120, 4160, 0, 1760691557,'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(1760691557), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164477_0.png', 0, 398, 285, 0, 1760691557,'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(1760691557), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164457_0.png', 0, 191, 47, 0, 1760691557,'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(1760691557), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164459_0.png', 0, 469, 145, 0, 1760691557,'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(1760691557), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164456_0.png', 0, 172, 179, 0, 1760691557,'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(1760691557), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164460_0.png', 0, 348, 132, 0, 1760691557,'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(1760691557), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164489_0.png', 0, 360, 263, 0, 1760691557,'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(1760691557), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164458_0.png', 0, 221, 176, 0, 1760691557,'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(1760691557), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772229_b32f1ec8cf18ed7603850468f4f4d744_rle_crop_4000164469_0.png', 0, 193, 472, 0, 1760691557,'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(1760691557), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772225_d0a8609c6715c5f1a67191409dd5978c_rle_crop_4000164944_0.png', 0, 2560, 2366, 0, 1760691557,'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(1760691557), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772225_d0a8609c6715c5f1a67191409dd5978c_rle_crop_4000164946_0.png', 0, 2929, 2987, 0, 1760691557,'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(1760691557), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772225_d0a8609c6715c5f1a67191409dd5978c_rle_crop_4000164945_0.png', 0, 2723, 773, 0, 1760691557,'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(1760691557), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772225_d0a8609c6715c5f1a67191409dd5978c_rle_crop_4000164939_0.png', 0, 360, 125, 0, 1760691557,'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(1760691557), 0.0, 0.0, 14, '', 0, 0, '1760689578_752055_1389772225_d0a8609c6715c5f1a67191409dd5978c_rle_crop_4000164941_0.png', 0, 883, 250, 0, 1760691557,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 30 photos in the portfolio 3015255 time of upload the photos Elapsed time : 319.71526050567627 we have finished the crop for the class : environnement delete rles for these photos Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : crop_condition we use saveGeneral [1389772234, 1389772233, 1389772231, 1389772229, 1389772225] Looping around the photos to save general results len do output : 195 /1389782300Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782302Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782306Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782309Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782310Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782314Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782316Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782322Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782325Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782327Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782330Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782334Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782336Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782341Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782343Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782345Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782349Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782353Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782355Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782357Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782359Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782365Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782367Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782370Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782374Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782377Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782380Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782383Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782385Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782388Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782391Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782395Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782398Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782401Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782403Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782406Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782409Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782414Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782416Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782418Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782421Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782423Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782425Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782428Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782431Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782434Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782436Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782438Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782440Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782442Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782446Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782448Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782450Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782453Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782456Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782458Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782460Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782488Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782494Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782501Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782504Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782512Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782517Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782523Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782527Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782531Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782536Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782540Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782544Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782546Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782553Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782556Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782561Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782568Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782575Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782579Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782583Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782587Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782592Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782596Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782602Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782606Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782611Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782616Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782621Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782627Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782631Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782637Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782645Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782649Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782654Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782661Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782669Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782676Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782682Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782689Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782696Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782700Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782708Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782716Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782724Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782729Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782736Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782745Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782763Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782771Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782775Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782783Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782787Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782792Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782804Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782809Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782816Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782827Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782835Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782842Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782852Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782860Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782867Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782874Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782881Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782891Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782896Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782912Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782921Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782932Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782938Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782950Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782956Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782966Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782975Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782981Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782988Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389782994Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783024Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783033Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783040Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783050Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783059Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783066Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783074Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783082Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783089Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783102Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783124Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783130Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783136Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783141Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783151Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783159Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783167Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783174Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783181Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783188Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783196Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783204Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783214Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783229Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783252Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783261Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783272Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783283Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783290Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783299Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783308Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783389Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783398Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783407Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783416Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783424Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783436Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783445Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783451Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783462Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783468Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783476Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783489Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783500Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783509Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783521Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783534Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783543Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783554Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783565Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783579Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783595Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783610Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783620Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783632Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783647Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783658Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783669Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783682Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783694Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1389783705Didn'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 ('4741', None, None, None, None, None, None, None, '3953017') ('4741', '27873696', '1389772234', None, None, None, None, None, '3953017') ('4741', None, None, None, None, None, None, None, '3953017') ('4741', '27873696', '1389772233', None, None, None, None, None, '3953017') ('4741', None, None, None, None, None, None, None, '3953017') ('4741', '27873696', '1389772231', None, None, None, None, None, '3953017') ('4741', None, None, None, None, None, None, None, '3953017') ('4741', '27873696', '1389772229', None, None, None, None, None, '3953017') ('4741', None, None, None, None, None, None, None, '3953017') ('4741', '27873696', '1389772225', None, None, None, None, None, '3953017') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 590 time used for this insertion : 106.76146531105042 save_final save missing photos in datou_result : time spend for datou_step_exec : 1829.2880547046661 time spend to save output : 106.76580619812012 total time spend for step 6 : 1936.0538609027863 step7:ventilate_hashtags_in_portfolio Fri Oct 17 11:08:02 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 : 27873696 get user id for portfolio 27873696 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`=27873696 AND mptpi.`type`=4855 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('papier','carton','metal','pet_clair','pehd','pet_fonce','pet_opaque','barquette_opaque','film_plastique','ela','sac','textiles','verre','organique','dasri','masque','encombrant','autre_emballage','autre_non_emballage','environnement','autre','flux_dev','mal_croppe','flou','film_dev_souple','sac_om_plein')) AND mptpi.`min_score`=0.1 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`=27873696 AND mptpi.`type`=4855 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('papier','carton','metal','pet_clair','pehd','pet_fonce','pet_opaque','barquette_opaque','film_plastique','ela','sac','textiles','verre','organique','dasri','masque','encombrant','autre_emballage','autre_non_emballage','environnement','autre','flux_dev','mal_croppe','flou','film_dev_souple','sac_om_plein')) AND mptpi.`min_score`=0.1 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") 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") 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`=27873696 AND mptpi.`type`=4856 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('papier','carton','metal','pet_clair','pehd','pet_fonce','pet_opaque','barquette_opaque','film_plastique','ela','sac','textiles','verre','organique','dasri','masque','encombrant','autre_emballage','autre_non_emballage','environnement','autre','flux_dev','mal_croppe','flou','film_dev_souple','sac_om_plein')) AND mptpi.`min_score`=0.1 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`=27873696 AND mptpi.`type`=4856 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('papier','carton','metal','pet_clair','pehd','pet_fonce','pet_opaque','barquette_opaque','film_plastique','ela','sac','textiles','verre','organique','dasri','masque','encombrant','autre_emballage','autre_non_emballage','environnement','autre','flux_dev','mal_croppe','flou','film_dev_souple','sac_om_plein')) AND mptpi.`min_score`=0.1 To do lien utilise dans velours : https://marlene.fotonower.com/velours/27876056,27876057,27876058,27876060,27876061,27876069,27876073,27876076,27876079,27876081,27876083,27876087,27876094,27876098,27876101,27876104,27876108,27876111,27876114,27876118?tags=papier,carton,metal,pet_clair,pehd,ela,textiles,verre,organique,dasri,masque,encombrant,autre_non_emballage,environnement,autre,flux_dev,mal_croppe,flou,film_dev_souple,sac_om_plein&datou_id_consolidate=4742&port_consolidate=27873696 Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : ventilate_hashtags_in_portfolio we use saveGeneral [1389772234, 1389772233, 1389772231, 1389772229, 1389772225] Looping around the photos to save general results len do output : 1 /27873696. 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 ('4741', None, None, None, None, None, None, None, '3953017') ('4741', '27873696', '1389772234', None, None, None, None, None, '3953017') ('4741', None, None, None, None, None, None, None, '3953017') ('4741', '27873696', '1389772233', None, None, None, None, None, '3953017') ('4741', None, None, None, None, None, None, None, '3953017') ('4741', '27873696', '1389772231', None, None, None, None, None, '3953017') ('4741', None, None, None, None, None, None, None, '3953017') ('4741', '27873696', '1389772229', None, None, None, None, None, '3953017') ('4741', None, None, None, None, None, None, None, '3953017') ('4741', '27873696', '1389772225', None, None, None, None, None, '3953017') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 6 time used for this insertion : 45.47111773490906 save_final save missing photos in datou_result : time spend for datou_step_exec : 491.7445242404938 time spend to save output : 45.596495151519775 total time spend for step 7 : 537.3410193920135 step8:final Fri Oct 17 11:16:59 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 : {1389772234: ('0.21051313281129763',), 1389772233: ('0.21051313281129763',), 1389772231: ('0.21051313281129763',), 1389772229: ('0.21051313281129763',), 1389772225: ('0.21051313281129763',)} new output for save of step final : {1389772234: ('0.21051313281129763',), 1389772233: ('0.21051313281129763',), 1389772231: ('0.21051313281129763',), 1389772229: ('0.21051313281129763',), 1389772225: ('0.21051313281129763',)} [1389772234, 1389772233, 1389772231, 1389772229, 1389772225] Looping around the photos to save general results len do output : 5 /1389772234.Didn't retrieve data . /1389772233.Didn't retrieve data . /1389772231.Didn't retrieve data . /1389772229.Didn't retrieve data . /1389772225.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 ('4741', None, None, None, None, None, None, None, '3953017') ('4741', '27873696', '1389772234', None, None, None, None, None, '3953017') ('4741', None, None, None, None, None, None, None, '3953017') ('4741', '27873696', '1389772233', None, None, None, None, None, '3953017') ('4741', None, None, None, None, None, None, None, '3953017') ('4741', '27873696', '1389772231', None, None, None, None, None, '3953017') ('4741', None, None, None, None, None, None, None, '3953017') ('4741', '27873696', '1389772229', None, None, None, None, None, '3953017') ('4741', None, None, None, None, None, None, None, '3953017') ('4741', '27873696', '1389772225', None, None, None, None, None, '3953017') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 15 time used for this insertion : 3.0715889930725098 save_final save missing photos in datou_result : time spend for datou_step_exec : 5.46602725982666 time spend to save output : 3.0726706981658936 total time spend for step 8 : 8.538697957992554 step9:velours_tree Fri Oct 17 11:17:08 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 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 : 0.4975712299346924 time spend to save output : 5.793571472167969e-05 total time spend for step 9 : 0.49762916564941406 step10:send_mail_cod Fri Oct 17 11:17:08 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 complete output_args for input 1 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 in order to get the selector url, please entre the license of selector results_Auto_P27873696_17-10-2025_11_17_08.pdf 27875977 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 .imagette278759771760692628 27875983 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 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text .change filename to text .change filename to text .change filename to text .change filename to text .imagette278759901760692635 27875993 imagette278759931760692636 27875996 imagette278759961760692636 27875998 imagette278759981760692636 27875999 imagette278759991760692636 27876000 imagette278760001760692637 27876002 imagette278760021760692637 27876003 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 .imagette278760031760692637 27876004 change filename to text .imagette278760041760692638 27876006 imagette278760061760692638 27876007 imagette278760071760692638 27876011 imagette278760111760692638 27876014 imagette278760141760692638 27876017 imagette278760171760692638 27876020 change filename to text .imagette278760201760692638 27876023 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 .imagette278760231760692638 27876029 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 .imagette278760291760692639 27876032 imagette278760321760692640 27876035 imagette278760351760692640 27876038 imagette278760381760692640 27876041 imagette278760411760692641 27876044 imagette278760441760692641 SELECT h.hashtag,pcr.value FROM MTRUser.portfolio_carac_ratio pcr, MTRBack.hashtags h where pcr.portfolio_id=27873696 and hashtag_type = 4855 and pcr.hashtag_id = h.hashtag_id; velour_link : https://marlene.fotonower.com/velours/27876056,27876057,27876058,27876060,27876061,27876069,27876073,27876076,27876079,27876081,27876083,27876087,27876094,27876098,27876101,27876104,27876108,27876111,27876114,27876118?tags=papier,carton,metal,pet_clair,pehd,ela,textiles,verre,organique,dasri,masque,encombrant,autre_non_emballage,environnement,autre,flux_dev,mal_croppe,flou,film_dev_souple,sac_om_plein&datou_id_consolidate=4742&port_consolidate=27873696 your option no_mail is active, we will not send the real mail to your client args[1389772234] : ((1389772234, 2048.3414622848823, 492609224), (1389772234, -0.39218416250162513, 496442774), '0.21051313281129763') We are sending mail with results at report@fotonower.com,cod@fotonower.com args[1389772233] : ((1389772233, 1709.9590986854955, 2107751945), (1389772233, -0.22709344979543789, 496442774), '0.21051313281129763') We are sending mail with results at report@fotonower.com,cod@fotonower.com args[1389772231] : ((1389772231, 1610.0099019925085, 2107751945), (1389772231, -0.2240523989968024, 496442774), '0.21051313281129763') We are sending mail with results at report@fotonower.com,cod@fotonower.com args[1389772229] : ((1389772229, 1276.588076740277, 2107751945), (1389772229, -0.23162873763040803, 496442774), '0.21051313281129763') We are sending mail with results at report@fotonower.com,cod@fotonower.com args[1389772225] : ((1389772225, 202.6232422376391, 492688767), (1389772225, -0.3582182270203608, 496442774), '0.21051313281129763') We are sending mail with results at report@fotonower.com,cod@fotonower.com refus_total : 0.21051313281129763 2022-04-13 10:29:59 0 start upload file to ovh https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27873696_17-10-2025_11_17_08.pdf results_Auto_P27873696_17-10-2025_11_17_08.pdf uploaded to url https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27873696_17-10-2025_11_17_08.pdf start insert file to database insert into MTRUser.mtr_files (mtd_id,mtr_portfolio_id,text,url,format,tags,file_size,value) values ('4741','27873696','results_Auto_P27873696_17-10-2025_11_17_08.pdf','https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27873696_17-10-2025_11_17_08.pdf','pdf','','2.68','0.21051313281129763') Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : send_mail_cod we use saveGeneral [1389772234, 1389772233, 1389772231, 1389772229, 1389772225] 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 ('4741', None, None, None, None, None, None, None, '3953017') ('4741', '27873696', '1389772234', None, None, None, None, None, '3953017') ('4741', None, None, None, None, None, None, None, '3953017') ('4741', '27873696', '1389772233', None, None, None, None, None, '3953017') ('4741', None, None, None, None, None, None, None, '3953017') ('4741', '27873696', '1389772231', None, None, None, None, None, '3953017') ('4741', None, None, None, None, None, None, None, '3953017') ('4741', '27873696', '1389772229', None, None, None, None, None, '3953017') ('4741', None, None, None, None, None, None, None, '3953017') ('4741', '27873696', '1389772225', None, None, None, None, None, '3953017') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 5 time used for this insertion : 5.0564284324646 save_final save missing photos in datou_result : time spend for datou_step_exec : 19.22802209854126 time spend to save output : 5.056762933731079 total time spend for step 10 : 24.28478503227234 step11:split_time_score Fri Oct 17 11:17:33 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed 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 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 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'}] (('39', 1), ('40', 2), ('41', 2)) ERROR counted https://github.com/fotonower/Velours/issues/663#issuecomment-421136223 {} 08112024 27873696 Nombre de photos uploadées : 5 / 23040 (0%) 08112024 27873696 Nombre de photos taguées (types de déchets): 0 / 5 (0%) 08112024 27873696 Nombre de photos taguées (volume) : 0 / 5 (0%) Catched exception ! (1213, 'Deadlock found when trying to get lock; try restarting transaction') Connect or reconnect ! elapsed_time : load_data_split_time_score 2.6226043701171875e-06 elapsed_time : order_list_meta_photo_and_scores 7.867813110351562e-06 ????? elapsed_time : fill_and_build_computed_from_old_data 0.000370025634765625 Catched exception ! Connect or reconnect ! Catched exception ! Connect or reconnect ! elapsed_time : insert_dashboard_record_day_entry 40.365472078323364 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 : 0.21051313281129763 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27873696_17-10-2025_11_17_08.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27873696 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 13156 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 13160 mask_detect have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 13160 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 13158 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 13158 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 13157 crop_condition is not consistent : 4 used against 2 in the step definition ! WARNING : number of outputs for step 13157 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 13161 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 13159 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 13159 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! 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 13156 doesn't seem to be define in the database( WARNING : type of input 2 of step 13157 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 13161 doesn't seem to be define in the database( WARNING : type of input 3 of step 13159 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 13157 doesn't seem to be define in the database( WARNING : output 0 of step 13163 have datatype=6 whereas input 2 of step 13157 have datatype=None WARNING : type of input 2 of step 13157 doesn't seem to be define in the database( WARNING : output 0 of step 13162 have datatype=6 whereas input 2 of step 13157 have datatype=None We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 13161 have datatype=10 whereas input 3 of step 13164 have datatype=6 WARNING : output 0 of step 13161 have datatype=10 whereas input 0 of step 13166 have datatype=18 WARNING : type of input 5 of step 13164 doesn't seem to be define in the database( WARNING : output 0 of step 13166 have datatype=11 whereas input 5 of step 13164 have datatype=None WARNING : type of input 2 of step 13157 doesn't seem to be define in the database( WARNING : output 1 of step 13158 have datatype=7 whereas input 2 of step 13157 have datatype=None WARNING : type of output 3 of step 13157 doesn't seem to be define in the database( WARNING : type of input 3 of step 13161 doesn't seem to be define in the database( WARNING : type of output 2 of step 13160 doesn't seem to be define in the database( WARNING : type of input 1 of step 13163 doesn't seem to be define in the database( WARNING : type of output 2 of step 13160 doesn't seem to be define in the database( WARNING : type of input 1 of step 13162 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`=27873696 AND mptpi.`type`=4855 To do NUMBER BATCH : 0 # DISPLAY ALL COLLECTED DATA : {'08112024': {'nb_upload': 5, '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 [1389772234, 1389772233, 1389772231, 1389772229, 1389772225] Looping around the photos to save general results len do output : 1 /27873696Didn'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 ('4741', None, None, None, None, None, None, None, '3953017') ('4741', '27873696', '1389772234', None, None, None, None, None, '3953017') ('4741', None, None, None, None, None, None, None, '3953017') ('4741', '27873696', '1389772233', None, None, None, None, None, '3953017') ('4741', None, None, None, None, None, None, None, '3953017') ('4741', '27873696', '1389772231', None, None, None, None, None, '3953017') ('4741', None, None, None, None, None, None, None, '3953017') ('4741', '27873696', '1389772229', None, None, None, None, None, '3953017') ('4741', None, None, None, None, None, None, None, '3953017') ('4741', '27873696', '1389772225', None, None, None, None, None, '3953017') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 6 time used for this insertion : 3.1433095932006836 save_final save missing photos in datou_result : time spend for datou_step_exec : 59.29793953895569 time spend to save output : 3.1435680389404297 total time spend for step 11 : 62.44150757789612 caffe_path_current : About to save ! 2 After save, about to update current ! ret : 2 len(input) + len(total_photo_id_missing) : 5 set_done_treatment 584.76user 236.12system 52:25.33elapsed 26%CPU (0avgtext+0avgdata 7011188maxresident)k 1358408inputs+601464outputs (13923major+42378095minor)pagefaults 0swaps