import MySQLdb succeeded Import error (python version) ['/Users/moilerat/Documents/Fotonower/install/caffe/distribute/python', '/home/admin/workarea/git/Velours/python/prod', '/home/admin/workarea/install/caffe_cuda8_python3/python', '/home/admin/workarea/install/darknet', '/home/admin/workarea/git/Velours/python', '/home/admin/workarea/install/caffe_frcnn_python3/py-faster-rcnn/caffe-fast-rcnn/python', '/home/admin/mtr/.credentials', '/home/admin/workarea/install/caffe/python', '/home/admin/workarea/install/caffe_frcnn/py-faster-rcnn/tools', '/home/admin/workarea/git/fotonowerpip', '/home/admin/workarea/install/segment-anything', '/home/admin/workarea/git/pyfvs', '/usr/lib/python38.zip', '/usr/lib/python3.8', '/usr/lib/python3.8/lib-dynload', '/home/admin/.local/lib/python3.8/site-packages', '/usr/local/lib/python3.8/dist-packages', '/usr/lib/python3/dist-packages'] process id : 526287 load datou : 3318 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! Unexpected type for variable list_input_json ERROR or WARNING : can't parse json string Expecting value: line 1 column 1 (char 0) Tried to parse : chemin de la photo was removed should we ? (photo_id, hashtag_id, score_max) was removed should we ? [(photo_id, hashtag_id, hashtag_type, x0, x1, y0, y1, score, seg_temp, polygons), ...] was removed should we ? chemin de la photo was removed should we ? [ (photo_id_loc, hashtag_id, hashtag_type, x0, x1, y0, y1, score, None), ...] was removed should we ? chemin de la photo was removed should we ? id de la photo (peut être local ou global) was removed should we ? chemin de la photo was removed should we ? (x0, y0, x1, y1) was removed should we ? chemin de la photo was removed should we ? donnée sous forme de texte was removed should we ? [ (photo_id, photo_id_loc, hashtag_type, x0, x1, y0, y1, score), ...] was removed should we ? None was removed should we ? donnée sous forme de texte was removed should we ? (photo_id, hashtag_id, score_max) was removed should we ? id de la photo (peut être local ou global) was removed should we ? donnée sous forme de texte was removed should we ? donnée sous forme de texte was removed should we ? donnée sous forme de texte was removed should we ? chemin de la photo was removed should we ? (photo_id, hashtag_id, score_max) was removed should we ? chemin de la photo was removed should we ? (photo_id, hashtag_id, score_max) was removed should we ? None was removed should we ? donnée sous forme de nombre was removed should we ? (photo_id, hashtag_id, score_max) was removed should we ? (photo_id, hashtag_id, score_max) was removed should we ? (photo_id, hashtag_id, score_max) was removed should we ? (photo_id, hashtag_id, score_max) was removed should we ? (photo_id, hashtag_id, score_max) was removed should we ? donnée sous forme de texte was removed should we ? None was removed should we ? donnée sous forme de texte was removed should we ? [ptf_id0,ptf_id1...] was removed should we ? FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (5275, 'learn_RUBBIA_REFUS_AMIENS_23', 16384, 25088, 'learn_RUBBIA_REFUS_AMIENS_23', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 1, datetime.datetime(2021, 4, 23, 14, 19, 39), datetime.datetime(2021, 4, 23, 14, 19, 39)) load thcls load THCL from format json or kwargs add thcl : 2847 in CacheModelConfig load pdts add pdt : 5275 in CacheModelConfig Running datou job : batch_current TODO datou_current to load to do maybe to take outside batchDatouExec updating current state to 1 list_input_json: [] Current got : datou_id : 3318, datou_cur_ids : ['2733670'] with mtr_portfolio_ids : ['22153590'] and first list_photo_ids : [] new path : /proc/526287/ Inside batchDatouExec : verbose : 0 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! List Step Type Loaded in datou : mask_detect, crop_condition, rle_unique_nms_with_priority, ventilate_hashtags_in_portfolio, final, blur_detection, brightness, velours_tree, send_mail_cod, split_time_score over limit max, limiting to limit_max 40 list_input_json : [] origin We have 2 , BFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 25 ; length of list_pids : 25 ; length of list_args : 25 time to download the photos : 6.19327187538147 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : 0 number of steps : 10 step1:mask_detect Wed Apr 9 10:40:35 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 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 : 10661 max_wait_temp : 1 max_wait : 0 gpu_flag : 0 2025-04-09 10:40:37.696955: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2025-04-09 10:40:37.723374: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493065000 Hz 2025-04-09 10:40:37.725556: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f4388000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-04-09 10:40:37.725604: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-04-09 10:40:37.729515: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-04-09 10:40:37.873828: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x1e644550 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-04-09 10:40:37.873872: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-04-09 10:40:37.875150: 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 2025-04-09 10:40:37.875527: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-04-09 10:40:37.879192: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-04-09 10:40:37.881826: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-04-09 10:40:37.882332: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-04-09 10:40:37.885221: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-04-09 10:40:37.886509: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-04-09 10:40:37.890878: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-04-09 10:40:37.892380: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-04-09 10:40:37.892449: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-04-09 10:40:37.893222: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-04-09 10:40:37.893237: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-04-09 10:40:37.893245: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-04-09 10:40:37.894631: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 9879 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. 2025-04-09 10:40:38.191271: 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 2025-04-09 10:40:38.191380: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-04-09 10:40:38.191407: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-04-09 10:40:38.191433: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-04-09 10:40:38.191459: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-04-09 10:40:38.191482: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-04-09 10:40:38.191505: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-04-09 10:40:38.191529: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-04-09 10:40:38.192964: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-04-09 10:40:38.194213: 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 2025-04-09 10:40:38.194262: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-04-09 10:40:38.194280: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-04-09 10:40:38.194296: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-04-09 10:40:38.194313: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-04-09 10:40:38.194329: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-04-09 10:40:38.194345: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-04-09 10:40:38.194362: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-04-09 10:40:38.195673: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-04-09 10:40:38.195703: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-04-09 10:40:38.195711: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-04-09 10:40:38.195719: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-04-09 10:40:38.196974: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 9879 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:41:00.0, compute capability: 7.5) Using TensorFlow backend. WARNING:tensorflow:From /home/admin/workarea/install/Mask_RCNN/model.py:396: calling crop_and_resize_v1 (from tensorflow.python.ops.image_ops_impl) with box_ind is deprecated and will be removed in a future version. Instructions for updating: box_ind is deprecated, use box_indices instead WARNING:tensorflow:From /home/admin/workarea/install/Mask_RCNN/model.py:703: to_int32 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.cast` instead. WARNING:tensorflow:From /home/admin/workarea/install/Mask_RCNN/model.py:729: to_float (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.cast` instead. Inside mask_sub_process Inside mask_detect About to load cache.load_thcl_param To do loadFromThcl(), then load ParamDescType : thcl2847 thcls : [{'id': 2847, 'mtr_user_id': 31, 'name': 'learn_RUBBIA_REFUS_AMIENS_23', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'photo_desc_type': 5275, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'}] thcl {'id': 2847, 'mtr_user_id': 31, 'name': 'learn_RUBBIA_REFUS_AMIENS_23', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'photo_desc_type': 5275, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'} Update svm_hashtag_type_desc : 5275 FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (5275, 'learn_RUBBIA_REFUS_AMIENS_23', 16384, 25088, 'learn_RUBBIA_REFUS_AMIENS_23', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 1, datetime.datetime(2021, 4, 23, 14, 19, 39), datetime.datetime(2021, 4, 23, 14, 19, 39)) {'thcl': {'id': 2847, 'mtr_user_id': 31, 'name': 'learn_RUBBIA_REFUS_AMIENS_23', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'photo_desc_type': 5275, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'}, 'list_hashtags': ['background', 'papier', 'carton', 'metal', 'pet_clair', 'autre', 'pehd', 'pet_fonce', 'environnement'], 'list_hashtags_csv': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'svm_hashtag_type_desc': 5275, 'photo_desc_type': 5275, 'pb_hashtag_id_or_classifier': 0} list_class_names : ['background', 'papier', 'carton', 'metal', 'pet_clair', 'autre', 'pehd', 'pet_fonce', 'environnement'] Configurations: BACKBONE resnet101 BACKBONE_SHAPES [[160 160] [ 80 80] [ 40 40] [ 20 20] [ 10 10]] BACKBONE_STRIDES [4, 8, 16, 32, 64] BATCH_SIZE 1 BBOX_STD_DEV [0.1 0.1 0.2 0.2] DETECTION_MAX_INSTANCES 100 DETECTION_MIN_CONFIDENCE 0.3 DETECTION_NMS_THRESHOLD 0.3 GPU_COUNT 1 IMAGES_PER_GPU 1 IMAGE_MAX_DIM 640 IMAGE_MIN_DIM 640 IMAGE_PADDING True IMAGE_SHAPE [640 640 3] LEARNING_MOMENTUM 0.9 LEARNING_RATE 0.001 LOSS_WEIGHTS {'rpn_class_loss': 1.0, 'rpn_bbox_loss': 1.0, 'mrcnn_class_loss': 1.0, 'mrcnn_bbox_loss': 1.0, 'mrcnn_mask_loss': 1.0} MASK_POOL_SIZE 14 MASK_SHAPE [28, 28] MAX_GT_INSTANCES 100 MEAN_PIXEL [123.7 116.8 103.9] MINI_MASK_SHAPE (56, 56) NAME learn_RUBBIA_REFUS_AMIENS_23 NUM_CLASSES 9 POOL_SIZE 7 POST_NMS_ROIS_INFERENCE 1000 POST_NMS_ROIS_TRAINING 2000 ROI_POSITIVE_RATIO 0.33 RPN_ANCHOR_RATIOS [0.5, 1, 2] RPN_ANCHOR_SCALES (16, 32, 64, 128, 256) RPN_ANCHOR_STRIDE 1 RPN_BBOX_STD_DEV [0.1 0.1 0.2 0.2] RPN_NMS_THRESHOLD 0.7 RPN_TRAIN_ANCHORS_PER_IMAGE 256 STEPS_PER_EPOCH 1000 TRAIN_ROIS_PER_IMAGE 200 USE_MINI_MASK True USE_RPN_ROIS True VALIDATION_STEPS 50 WEIGHT_DECAY 0.0001 model_param file didn't exist model_name : learn_RUBBIA_REFUS_AMIENS_23 model_type : mask_rcnn list file need : ['mask_model.h5'] file exist in s3 : ['mask_model.h5'] file manque in s3 : [] 2025-04-09 10:40:51.680532: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-04-09 10:40:51.900716: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 local folder : /data/models_weight/learn_RUBBIA_REFUS_AMIENS_23 /data/models_weight/learn_RUBBIA_REFUS_AMIENS_23/mask_model.h5 size_local : 256009536 size in s3 : 256009536 create time local : 2021-08-09 09:43:22 create time in s3 : 2021-08-06 18:54:04 mask_model.h5 already exist and didn't need to update list_images length : 25 NEW PHOTO Processing 1 images image shape: (2160, 3264, 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: 3264.00000 nb d'objets trouves : 78 NEW PHOTO Processing 1 images image shape: (2160, 3264, 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: 3264.00000 nb d'objets trouves : 74 NEW PHOTO Processing 1 images image shape: (2160, 3264, 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: 3264.00000 nb d'objets trouves : 66 NEW PHOTO Processing 1 images image shape: (2160, 3264, 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: 3264.00000 nb d'objets trouves : 95 NEW PHOTO Processing 1 images image shape: (2160, 3264, 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: 3264.00000 nb d'objets trouves : 88 NEW PHOTO Processing 1 images image shape: (2160, 3264, 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: 3264.00000 nb d'objets trouves : 78 NEW PHOTO Processing 1 images image shape: (2160, 3264, 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: 3264.00000 nb d'objets trouves : 100 NEW PHOTO Processing 1 images image shape: (2160, 3264, 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: 3264.00000 nb d'objets trouves : 54 NEW PHOTO Processing 1 images image shape: (2160, 3264, 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: 3264.00000 nb d'objets trouves : 93 NEW PHOTO Processing 1 images image shape: (2160, 3264, 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: 3264.00000 nb d'objets trouves : 83 NEW PHOTO Processing 1 images image shape: (2160, 3264, 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: 3264.00000 nb d'objets trouves : 87 NEW PHOTO Processing 1 images image shape: (2160, 3264, 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: 3264.00000 nb d'objets trouves : 38 NEW PHOTO Processing 1 images image shape: (2160, 3264, 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: 3264.00000 nb d'objets trouves : 23 NEW PHOTO Processing 1 images image shape: (2160, 3264, 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: 3264.00000 nb d'objets trouves : 99 NEW PHOTO Processing 1 images image shape: (2160, 3264, 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: 3264.00000 nb d'objets trouves : 63 NEW PHOTO Processing 1 images image shape: (2160, 3264, 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: 3264.00000 nb d'objets trouves : 63 NEW PHOTO Processing 1 images image shape: (2160, 3264, 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: 3264.00000 nb d'objets trouves : 50 NEW PHOTO Processing 1 images image shape: (2160, 3264, 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: 3264.00000 nb d'objets trouves : 35 NEW PHOTO Processing 1 images image shape: (2160, 3264, 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: 3264.00000 nb d'objets trouves : 19 NEW PHOTO Processing 1 images image shape: (2160, 3264, 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: 3264.00000 nb d'objets trouves : 100 NEW PHOTO Processing 1 images image shape: (2160, 3264, 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: 3264.00000 nb d'objets trouves : 100 NEW PHOTO Processing 1 images image shape: (2160, 3264, 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: 3264.00000 nb d'objets trouves : 77 NEW PHOTO Processing 1 images image shape: (2160, 3264, 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: 3264.00000 nb d'objets trouves : 72 NEW PHOTO Processing 1 images image shape: (2160, 3264, 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: 3264.00000 nb d'objets trouves : 76 NEW PHOTO Processing 1 images image shape: (2160, 3264, 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: 3264.00000 nb d'objets trouves : 67 Detection mask done ! Trying to reset tf kernel 527041 begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 1748 tf kernel not reseted sub process len(results) : 25 len(list_Values) 0 None max_time_sub_proc : 3600 parent process len(results) : 25 len(list_Values) 0 process is alive process is alive process is alive 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 : 10814 list_Values should be empty [] To do loadFromThcl(), then load ParamDescType : thcl2847 Catched exception ! Connect or reconnect ! thcls : [{'id': 2847, 'mtr_user_id': 31, 'name': 'learn_RUBBIA_REFUS_AMIENS_23', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'photo_desc_type': 5275, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'}] thcl {'id': 2847, 'mtr_user_id': 31, 'name': 'learn_RUBBIA_REFUS_AMIENS_23', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'photo_desc_type': 5275, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'} Update svm_hashtag_type_desc : 5275 ['background', 'papier', 'carton', 'metal', 'pet_clair', 'autre', 'pehd', 'pet_fonce', 'environnement'] time for calcul the mask position with numpy : 0.137770414352417 nb_pixel_total : 32411 time to create 1 rle with old method : 0.040640830993652344 length of segment : 289 time for calcul the mask position with numpy : 0.17508649826049805 nb_pixel_total : 31154 time to create 1 rle with old method : 0.03817486763000488 length of segment : 382 time for calcul the mask position with numpy : 0.09047460556030273 nb_pixel_total : 42040 time to create 1 rle with old method : 0.04843497276306152 length of segment : 154 time for calcul the mask position with numpy : 0.042099952697753906 nb_pixel_total : 12430 time to create 1 rle with old method : 0.020054340362548828 length of segment : 138 time for calcul the mask position with numpy : 0.07562494277954102 nb_pixel_total : 14286 time to create 1 rle with old method : 0.020888566970825195 length of segment : 209 time for calcul the mask position with numpy : 0.13112616539001465 nb_pixel_total : 47665 time to create 1 rle with old method : 0.05256342887878418 length of segment : 238 time for calcul the mask position with numpy : 0.16640400886535645 nb_pixel_total : 55474 time to create 1 rle with old method : 0.06508040428161621 length of segment : 448 time for calcul the mask position with numpy : 0.04888582229614258 nb_pixel_total : 20308 time to create 1 rle with old method : 0.027277469635009766 length of segment : 140 time for calcul the mask position with numpy : 0.019068479537963867 nb_pixel_total : 4528 time to create 1 rle with old method : 0.008934259414672852 length of segment : 60 time for calcul the mask position with numpy : 0.05260825157165527 nb_pixel_total : 17908 time to create 1 rle with old method : 0.025023460388183594 length of segment : 202 time for calcul the mask position with numpy : 0.036338090896606445 nb_pixel_total : 17895 time to create 1 rle with old method : 0.021721363067626953 length of segment : 139 time for calcul the mask position with numpy : 0.07875204086303711 nb_pixel_total : 14618 time to create 1 rle with old method : 0.019108295440673828 length of segment : 292 time for calcul the mask position with numpy : 0.1432359218597412 nb_pixel_total : 41225 time to create 1 rle with old method : 0.0446317195892334 length of segment : 524 time for calcul the mask position with numpy : 0.13375425338745117 nb_pixel_total : 54463 time to create 1 rle with old method : 0.0641181468963623 length of segment : 253 time for calcul the mask position with numpy : 0.1050872802734375 nb_pixel_total : 60538 time to create 1 rle with old method : 0.07074975967407227 length of segment : 433 time for calcul the mask position with numpy : 0.040160417556762695 nb_pixel_total : 10300 time to create 1 rle with old method : 0.016057252883911133 length of segment : 126 time for calcul the mask position with numpy : 0.020295143127441406 nb_pixel_total : 5202 time to create 1 rle with old method : 0.010424613952636719 length of segment : 86 time for calcul the mask position with numpy : 0.004323482513427734 nb_pixel_total : 3028 time to create 1 rle with old method : 0.004567623138427734 length of segment : 48 time for calcul the mask position with numpy : 0.0427091121673584 nb_pixel_total : 49745 time to create 1 rle with old method : 0.058974266052246094 length of segment : 251 time for calcul the mask position with numpy : 0.06549215316772461 nb_pixel_total : 16730 time to create 1 rle with old method : 0.02371358871459961 length of segment : 206 time for calcul the mask position with numpy : 0.03930473327636719 nb_pixel_total : 39485 time to create 1 rle with old method : 0.046709537506103516 length of segment : 255 time for calcul the mask position with numpy : 0.15413999557495117 nb_pixel_total : 59890 time to create 1 rle with old method : 0.06954813003540039 length of segment : 374 time for calcul the mask position with numpy : 0.03966879844665527 nb_pixel_total : 9106 time to create 1 rle with old method : 0.015244245529174805 length of segment : 184 time for calcul the mask position with numpy : 0.08063364028930664 nb_pixel_total : 39586 time to create 1 rle with old method : 0.057138681411743164 length of segment : 213 time for calcul the mask position with numpy : 0.08193564414978027 nb_pixel_total : 47473 time to create 1 rle with old method : 0.06267619132995605 length of segment : 327 time for calcul the mask position with numpy : 0.06766939163208008 nb_pixel_total : 24576 time to create 1 rle with old method : 0.03413200378417969 length of segment : 165 time for calcul the mask position with numpy : 0.07352590560913086 nb_pixel_total : 23136 time to create 1 rle with old method : 0.03425240516662598 length of segment : 139 time for calcul the mask position with numpy : 0.162933349609375 nb_pixel_total : 53554 time to create 1 rle with old method : 0.07577323913574219 length of segment : 360 time for calcul the mask position with numpy : 0.12469768524169922 nb_pixel_total : 86312 time to create 1 rle with old method : 0.13617420196533203 length of segment : 492 time for calcul the mask position with numpy : 0.030264854431152344 nb_pixel_total : 10611 time to create 1 rle with old method : 0.019706249237060547 length of segment : 147 time for calcul the mask position with numpy : 0.013179302215576172 nb_pixel_total : 11546 time to create 1 rle with old method : 0.02073049545288086 length of segment : 117 time for calcul the mask position with numpy : 0.03786492347717285 nb_pixel_total : 9927 time to create 1 rle with old method : 0.01578545570373535 length of segment : 103 time for calcul the mask position with numpy : 0.05884265899658203 nb_pixel_total : 17892 time to create 1 rle with old method : 0.0234222412109375 length of segment : 189 time for calcul the mask position with numpy : 0.05444979667663574 nb_pixel_total : 29862 time to create 1 rle with old method : 0.04392218589782715 length of segment : 281 time for calcul the mask position with numpy : 0.07704830169677734 nb_pixel_total : 32658 time to create 1 rle with old method : 0.04651284217834473 length of segment : 270 time for calcul the mask position with numpy : 0.0077228546142578125 nb_pixel_total : 2281 time to create 1 rle with old method : 0.003598928451538086 length of segment : 50 time for calcul the mask position with numpy : 0.05802488327026367 nb_pixel_total : 27393 time to create 1 rle with old method : 0.041993141174316406 length of segment : 127 time for calcul the mask position with numpy : 0.022388219833374023 nb_pixel_total : 14197 time to create 1 rle with old method : 0.017937421798706055 length of segment : 162 time for calcul the mask position with numpy : 0.06451201438903809 nb_pixel_total : 34768 time to create 1 rle with old method : 0.05050492286682129 length of segment : 194 time for calcul the mask position with numpy : 0.03208041191101074 nb_pixel_total : 21963 time to create 1 rle with old method : 0.032286882400512695 length of segment : 104 time for calcul the mask position with numpy : 0.0379796028137207 nb_pixel_total : 8168 time to create 1 rle with old method : 0.014806985855102539 length of segment : 104 time for calcul the mask position with numpy : 0.13037753105163574 nb_pixel_total : 46766 time to create 1 rle with old method : 0.0640707015991211 length of segment : 203 time for calcul the mask position with numpy : 0.11038565635681152 nb_pixel_total : 31327 time to create 1 rle with old method : 0.04398012161254883 length of segment : 249 time for calcul the mask position with numpy : 0.097076416015625 nb_pixel_total : 19256 time to create 1 rle with old method : 0.027310609817504883 length of segment : 331 time for calcul the mask position with numpy : 0.29850196838378906 nb_pixel_total : 112685 time to create 1 rle with old method : 0.13695335388183594 length of segment : 464 time for calcul the mask position with numpy : 0.08482694625854492 nb_pixel_total : 41982 time to create 1 rle with old method : 0.05936884880065918 length of segment : 291 time for calcul the mask position with numpy : 0.17293953895568848 nb_pixel_total : 58946 time to create 1 rle with old method : 0.0695343017578125 length of segment : 330 time for calcul the mask position with numpy : 0.05928850173950195 nb_pixel_total : 16369 time to create 1 rle with old method : 0.02283167839050293 length of segment : 198 time for calcul the mask position with numpy : 0.04015398025512695 nb_pixel_total : 10729 time to create 1 rle with old method : 0.01765727996826172 length of segment : 120 time for calcul the mask position with numpy : 0.04346442222595215 nb_pixel_total : 19539 time to create 1 rle with old method : 0.03232836723327637 length of segment : 148 time for calcul the mask position with numpy : 0.007402896881103516 nb_pixel_total : 14442 time to create 1 rle with old method : 0.021772146224975586 length of segment : 198 time for calcul the mask position with numpy : 0.03926348686218262 nb_pixel_total : 21487 time to create 1 rle with old method : 0.028880596160888672 length of segment : 142 time for calcul the mask position with numpy : 0.07228803634643555 nb_pixel_total : 35052 time to create 1 rle with old method : 0.04407000541687012 length of segment : 206 time for calcul the mask position with numpy : 0.06662654876708984 nb_pixel_total : 20699 time to create 1 rle with old method : 0.025022029876708984 length of segment : 125 time for calcul the mask position with numpy : 0.12068390846252441 nb_pixel_total : 57645 time to create 1 rle with old method : 0.07233190536499023 length of segment : 231 time for calcul the mask position with numpy : 0.04429912567138672 nb_pixel_total : 49413 time to create 1 rle with old method : 0.057712554931640625 length of segment : 390 time for calcul the mask position with numpy : 0.06327342987060547 nb_pixel_total : 30977 time to create 1 rle with old method : 0.03858184814453125 length of segment : 152 time for calcul the mask position with numpy : 0.039994239807128906 nb_pixel_total : 9558 time to create 1 rle with old method : 0.015248537063598633 length of segment : 157 time for calcul the mask position with numpy : 0.46065521240234375 nb_pixel_total : 178941 time to create 1 rle with new method : 0.01928091049194336 length of segment : 465 time for calcul the mask position with numpy : 0.07470941543579102 nb_pixel_total : 28138 time to create 1 rle with old method : 0.03667330741882324 length of segment : 242 time for calcul the mask position with numpy : 0.04271888732910156 nb_pixel_total : 23160 time to create 1 rle with old method : 0.030075550079345703 length of segment : 198 time for calcul the mask position with numpy : 0.021567344665527344 nb_pixel_total : 15481 time to create 1 rle with old method : 0.020550251007080078 length of segment : 173 time for calcul the mask position with numpy : 0.08006954193115234 nb_pixel_total : 31720 time to create 1 rle with old method : 0.043370723724365234 length of segment : 234 time for calcul the mask position with numpy : 0.016688823699951172 nb_pixel_total : 5504 time to create 1 rle with old method : 0.007966279983520508 length of segment : 84 time for calcul the mask position with numpy : 0.006720542907714844 nb_pixel_total : 8496 time to create 1 rle with old method : 0.014231443405151367 length of segment : 158 time for calcul the mask position with numpy : 0.1551342010498047 nb_pixel_total : 134295 time to create 1 rle with old method : 0.1548175811767578 length of segment : 706 time for calcul the mask position with numpy : 0.050203800201416016 nb_pixel_total : 16151 time to create 1 rle with old method : 0.02063894271850586 length of segment : 182 time for calcul the mask position with numpy : 0.05006909370422363 nb_pixel_total : 20050 time to create 1 rle with old method : 0.027255535125732422 length of segment : 157 time for calcul the mask position with numpy : 0.0719308853149414 nb_pixel_total : 30761 time to create 1 rle with old method : 0.0353693962097168 length of segment : 366 time for calcul the mask position with numpy : 0.10051536560058594 nb_pixel_total : 70166 time to create 1 rle with old method : 0.08240413665771484 length of segment : 391 time for calcul the mask position with numpy : 0.023921966552734375 nb_pixel_total : 11397 time to create 1 rle with old method : 0.016429901123046875 length of segment : 107 time for calcul the mask position with numpy : 0.0004062652587890625 nb_pixel_total : 19606 time to create 1 rle with old method : 0.022108793258666992 length of segment : 190 time for calcul the mask position with numpy : 0.04906749725341797 nb_pixel_total : 44514 time to create 1 rle with old method : 0.05591535568237305 length of segment : 234 time for calcul the mask position with numpy : 0.0229494571685791 nb_pixel_total : 22206 time to create 1 rle with old method : 0.02907395362854004 length of segment : 169 time for calcul the mask position with numpy : 0.07571625709533691 nb_pixel_total : 24492 time to create 1 rle with old method : 0.029313325881958008 length of segment : 243 time for calcul the mask position with numpy : 0.08836030960083008 nb_pixel_total : 51353 time to create 1 rle with old method : 0.060921669006347656 length of segment : 271 time for calcul the mask position with numpy : 0.035089969635009766 nb_pixel_total : 13181 time to create 1 rle with old method : 0.02244424819946289 length of segment : 100 time for calcul the mask position with numpy : 0.041169166564941406 nb_pixel_total : 18411 time to create 1 rle with old method : 0.023229598999023438 length of segment : 136 time for calcul the mask position with numpy : 0.02569580078125 nb_pixel_total : 6364 time to create 1 rle with old method : 0.006752729415893555 length of segment : 112 time for calcul the mask position with numpy : 0.024060487747192383 nb_pixel_total : 6863 time to create 1 rle with old method : 0.007359504699707031 length of segment : 95 time for calcul the mask position with numpy : 0.11087250709533691 nb_pixel_total : 65810 time to create 1 rle with old method : 0.07498383522033691 length of segment : 287 time for calcul the mask position with numpy : 0.038475751876831055 nb_pixel_total : 14211 time to create 1 rle with old method : 0.01909160614013672 length of segment : 138 time for calcul the mask position with numpy : 0.03831148147583008 nb_pixel_total : 25951 time to create 1 rle with old method : 0.031087160110473633 length of segment : 142 time for calcul the mask position with numpy : 0.03212165832519531 nb_pixel_total : 11103 time to create 1 rle with old method : 0.0180819034576416 length of segment : 179 time for calcul the mask position with numpy : 0.22620582580566406 nb_pixel_total : 172068 time to create 1 rle with new method : 0.011176347732543945 length of segment : 415 time for calcul the mask position with numpy : 0.04278850555419922 nb_pixel_total : 17970 time to create 1 rle with old method : 0.022275447845458984 length of segment : 152 time for calcul the mask position with numpy : 0.05872988700866699 nb_pixel_total : 16506 time to create 1 rle with old method : 0.021251916885375977 length of segment : 154 time for calcul the mask position with numpy : 0.02530050277709961 nb_pixel_total : 9550 time to create 1 rle with old method : 0.01802206039428711 length of segment : 112 time for calcul the mask position with numpy : 0.1149284839630127 nb_pixel_total : 54693 time to create 1 rle with old method : 0.06924629211425781 length of segment : 370 time for calcul the mask position with numpy : 0.1287670135498047 nb_pixel_total : 138004 time to create 1 rle with old method : 0.15743637084960938 length of segment : 429 time for calcul the mask position with numpy : 0.09003138542175293 nb_pixel_total : 62500 time to create 1 rle with old method : 0.07136201858520508 length of segment : 302 time for calcul the mask position with numpy : 0.048761606216430664 nb_pixel_total : 10062 time to create 1 rle with old method : 0.017997264862060547 length of segment : 176 time for calcul the mask position with numpy : 0.038846492767333984 nb_pixel_total : 21575 time to create 1 rle with old method : 0.027861356735229492 length of segment : 365 time for calcul the mask position with numpy : 0.059861183166503906 nb_pixel_total : 19605 time to create 1 rle with old method : 0.02691817283630371 length of segment : 183 time for calcul the mask position with numpy : 0.11003470420837402 nb_pixel_total : 46727 time to create 1 rle with old method : 0.05570077896118164 length of segment : 424 time for calcul the mask position with numpy : 0.04278564453125 nb_pixel_total : 32811 time to create 1 rle with old method : 0.041741371154785156 length of segment : 195 time for calcul the mask position with numpy : 0.024034976959228516 nb_pixel_total : 20575 time to create 1 rle with old method : 0.02759408950805664 length of segment : 164 time for calcul the mask position with numpy : 0.04646801948547363 nb_pixel_total : 18674 time to create 1 rle with old method : 0.023697614669799805 length of segment : 174 time for calcul the mask position with numpy : 0.026592493057250977 nb_pixel_total : 24010 time to create 1 rle with old method : 0.029803991317749023 length of segment : 245 time for calcul the mask position with numpy : 0.03349876403808594 nb_pixel_total : 14129 time to create 1 rle with old method : 0.020399808883666992 length of segment : 116 time for calcul the mask position with numpy : 0.05385851860046387 nb_pixel_total : 18543 time to create 1 rle with old method : 0.024219989776611328 length of segment : 157 time for calcul the mask position with numpy : 0.07290434837341309 nb_pixel_total : 37262 time to create 1 rle with old method : 0.04233741760253906 length of segment : 265 time for calcul the mask position with numpy : 0.32694220542907715 nb_pixel_total : 274003 time to create 1 rle with new method : 0.02113628387451172 length of segment : 475 time for calcul the mask position with numpy : 0.021004676818847656 nb_pixel_total : 7704 time to create 1 rle with old method : 0.013236761093139648 length of segment : 103 time for calcul the mask position with numpy : 0.06822466850280762 nb_pixel_total : 58018 time to create 1 rle with old method : 0.07141971588134766 length of segment : 216 time for calcul the mask position with numpy : 0.03154921531677246 nb_pixel_total : 18520 time to create 1 rle with old method : 0.02409958839416504 length of segment : 138 time for calcul the mask position with numpy : 0.04867219924926758 nb_pixel_total : 34045 time to create 1 rle with old method : 0.04018044471740723 length of segment : 217 time for calcul the mask position with numpy : 0.05375790596008301 nb_pixel_total : 17625 time to create 1 rle with old method : 0.02398228645324707 length of segment : 220 time for calcul the mask position with numpy : 0.019273757934570312 nb_pixel_total : 8386 time to create 1 rle with old method : 0.012578248977661133 length of segment : 121 time for calcul the mask position with numpy : 0.016180992126464844 nb_pixel_total : 4925 time to create 1 rle with old method : 0.0072019100189208984 length of segment : 87 time for calcul the mask position with numpy : 0.03929495811462402 nb_pixel_total : 10021 time to create 1 rle with old method : 0.014022350311279297 length of segment : 145 time for calcul the mask position with numpy : 0.015416383743286133 nb_pixel_total : 5811 time to create 1 rle with old method : 0.008581876754760742 length of segment : 83 time for calcul the mask position with numpy : 0.03512907028198242 nb_pixel_total : 22963 time to create 1 rle with old method : 0.030750751495361328 length of segment : 148 time for calcul the mask position with numpy : 0.03488564491271973 nb_pixel_total : 22514 time to create 1 rle with old method : 0.028679609298706055 length of segment : 184 time for calcul the mask position with numpy : 0.12858104705810547 nb_pixel_total : 28599 time to create 1 rle with old method : 0.036658525466918945 length of segment : 249 time for calcul the mask position with numpy : 0.18499231338500977 nb_pixel_total : 40137 time to create 1 rle with old method : 0.05536985397338867 length of segment : 313 time for calcul the mask position with numpy : 0.04745960235595703 nb_pixel_total : 10823 time to create 1 rle with old method : 0.020555973052978516 length of segment : 135 time for calcul the mask position with numpy : 0.19413995742797852 nb_pixel_total : 66667 time to create 1 rle with old method : 0.07833194732666016 length of segment : 364 time for calcul the mask position with numpy : 0.2568700313568115 nb_pixel_total : 52594 time to create 1 rle with old method : 0.06160569190979004 length of segment : 381 time for calcul the mask position with numpy : 0.053572654724121094 nb_pixel_total : 13782 time to create 1 rle with old method : 0.023101329803466797 length of segment : 114 time for calcul the mask position with numpy : 0.08181476593017578 nb_pixel_total : 21873 time to create 1 rle with old method : 0.03054642677307129 length of segment : 210 time for calcul the mask position with numpy : 0.029866933822631836 nb_pixel_total : 6078 time to create 1 rle with old method : 0.010417938232421875 length of segment : 124 time for calcul the mask position with numpy : 0.05390620231628418 nb_pixel_total : 18499 time to create 1 rle with old method : 0.025562763214111328 length of segment : 202 time for calcul the mask position with numpy : 0.20986127853393555 nb_pixel_total : 94440 time to create 1 rle with old method : 0.12791728973388672 length of segment : 376 time for calcul the mask position with numpy : 0.11380219459533691 nb_pixel_total : 19279 time to create 1 rle with old method : 0.025243282318115234 length of segment : 180 time for calcul the mask position with numpy : 0.05838656425476074 nb_pixel_total : 10253 time to create 1 rle with old method : 0.01707148551940918 length of segment : 126 time for calcul the mask position with numpy : 0.023476839065551758 nb_pixel_total : 6054 time to create 1 rle with old method : 0.011793375015258789 length of segment : 76 time for calcul the mask position with numpy : 0.07509636878967285 nb_pixel_total : 38777 time to create 1 rle with old method : 0.04877781867980957 length of segment : 350 time for calcul the mask position with numpy : 0.5807039737701416 nb_pixel_total : 205379 time to create 1 rle with new method : 0.021713733673095703 length of segment : 672 time for calcul the mask position with numpy : 0.09791326522827148 nb_pixel_total : 21105 time to create 1 rle with old method : 0.028842687606811523 length of segment : 202 time for calcul the mask position with numpy : 0.002353191375732422 nb_pixel_total : 30726 time to create 1 rle with old method : 0.0324094295501709 length of segment : 330 time for calcul the mask position with numpy : 0.08658838272094727 nb_pixel_total : 31413 time to create 1 rle with old method : 0.039017438888549805 length of segment : 191 time for calcul the mask position with numpy : 0.050775766372680664 nb_pixel_total : 10554 time to create 1 rle with old method : 0.016139507293701172 length of segment : 149 time for calcul the mask position with numpy : 0.020029783248901367 nb_pixel_total : 11003 time to create 1 rle with old method : 0.01680445671081543 length of segment : 112 time for calcul the mask position with numpy : 0.017712116241455078 nb_pixel_total : 37424 time to create 1 rle with old method : 0.04362750053405762 length of segment : 301 time for calcul the mask position with numpy : 0.548907995223999 nb_pixel_total : 250827 time to create 1 rle with new method : 0.02001786231994629 length of segment : 952 time for calcul the mask position with numpy : 0.045026302337646484 nb_pixel_total : 17353 time to create 1 rle with old method : 0.028055906295776367 length of segment : 144 time for calcul the mask position with numpy : 0.17419123649597168 nb_pixel_total : 35881 time to create 1 rle with old method : 0.04435610771179199 length of segment : 302 time for calcul the mask position with numpy : 0.03204822540283203 nb_pixel_total : 3223 time to create 1 rle with old method : 0.0064127445220947266 length of segment : 186 time for calcul the mask position with numpy : 0.049479007720947266 nb_pixel_total : 8636 time to create 1 rle with old method : 0.013475894927978516 length of segment : 207 time for calcul the mask position with numpy : 0.011043548583984375 nb_pixel_total : 11487 time to create 1 rle with old method : 0.01822495460510254 length of segment : 133 time for calcul the mask position with numpy : 0.04675173759460449 nb_pixel_total : 16954 time to create 1 rle with old method : 0.02834939956665039 length of segment : 127 time for calcul the mask position with numpy : 0.08771204948425293 nb_pixel_total : 46148 time to create 1 rle with old method : 0.06256747245788574 length of segment : 379 time for calcul the mask position with numpy : 0.03394174575805664 nb_pixel_total : 4478 time to create 1 rle with old method : 0.00870203971862793 length of segment : 151 time for calcul the mask position with numpy : 0.09145593643188477 nb_pixel_total : 50272 time to create 1 rle with old method : 0.07039475440979004 length of segment : 387 time for calcul the mask position with numpy : 0.0235598087310791 nb_pixel_total : 6783 time to create 1 rle with old method : 0.010927438735961914 length of segment : 96 time for calcul the mask position with numpy : 0.043550729751586914 nb_pixel_total : 15914 time to create 1 rle with old method : 0.021231412887573242 length of segment : 127 time for calcul the mask position with numpy : 0.07563543319702148 nb_pixel_total : 25144 time to create 1 rle with old method : 0.03374218940734863 length of segment : 201 time for calcul the mask position with numpy : 0.03537464141845703 nb_pixel_total : 11571 time to create 1 rle with old method : 0.017972946166992188 length of segment : 113 time for calcul the mask position with numpy : 0.09370541572570801 nb_pixel_total : 36974 time to create 1 rle with old method : 0.05807161331176758 length of segment : 357 time for calcul the mask position with numpy : 0.06672787666320801 nb_pixel_total : 19532 time to create 1 rle with old method : 0.02678513526916504 length of segment : 214 time for calcul the mask position with numpy : 0.02983999252319336 nb_pixel_total : 8378 time to create 1 rle with old method : 0.013727903366088867 length of segment : 96 time for calcul the mask position with numpy : 0.006113767623901367 nb_pixel_total : 9669 time to create 1 rle with old method : 0.013355255126953125 length of segment : 169 time for calcul the mask position with numpy : 0.028176546096801758 nb_pixel_total : 7886 time to create 1 rle with old method : 0.01266169548034668 length of segment : 104 time for calcul the mask position with numpy : 0.05992484092712402 nb_pixel_total : 26107 time to create 1 rle with old method : 0.03541207313537598 length of segment : 245 time for calcul the mask position with numpy : 0.1661078929901123 nb_pixel_total : 47101 time to create 1 rle with old method : 0.06152510643005371 length of segment : 335 time for calcul the mask position with numpy : 0.0009703636169433594 nb_pixel_total : 39387 time to create 1 rle with old method : 0.04462456703186035 length of segment : 304 time for calcul the mask position with numpy : 0.019575834274291992 nb_pixel_total : 22022 time to create 1 rle with old method : 0.02935051918029785 length of segment : 165 time for calcul the mask position with numpy : 0.3062005043029785 nb_pixel_total : 193594 time to create 1 rle with new method : 0.03443741798400879 length of segment : 972 time for calcul the mask position with numpy : 0.0005681514739990234 nb_pixel_total : 18992 time to create 1 rle with old method : 0.02237987518310547 length of segment : 198 time for calcul the mask position with numpy : 0.14946675300598145 nb_pixel_total : 68824 time to create 1 rle with old method : 0.07866740226745605 length of segment : 271 time for calcul the mask position with numpy : 0.029744863510131836 nb_pixel_total : 8515 time to create 1 rle with old method : 0.012309551239013672 length of segment : 148 time for calcul the mask position with numpy : 0.025880098342895508 nb_pixel_total : 6229 time to create 1 rle with old method : 0.014174938201904297 length of segment : 107 time for calcul the mask position with numpy : 0.017151355743408203 nb_pixel_total : 8632 time to create 1 rle with old method : 0.013534069061279297 length of segment : 62 time for calcul the mask position with numpy : 0.11222338676452637 nb_pixel_total : 35919 time to create 1 rle with old method : 0.042781829833984375 length of segment : 231 time for calcul the mask position with numpy : 0.06879925727844238 nb_pixel_total : 25049 time to create 1 rle with old method : 0.030108213424682617 length of segment : 181 time for calcul the mask position with numpy : 0.049996137619018555 nb_pixel_total : 12727 time to create 1 rle with old method : 0.01923227310180664 length of segment : 130 time for calcul the mask position with numpy : 0.11148858070373535 nb_pixel_total : 45828 time to create 1 rle with old method : 0.06507420539855957 length of segment : 352 time for calcul the mask position with numpy : 0.04552745819091797 nb_pixel_total : 11300 time to create 1 rle with old method : 0.01986217498779297 length of segment : 209 time for calcul the mask position with numpy : 0.1670513153076172 nb_pixel_total : 42271 time to create 1 rle with old method : 0.060623884201049805 length of segment : 341 time for calcul the mask position with numpy : 0.13863039016723633 nb_pixel_total : 34856 time to create 1 rle with old method : 0.06575536727905273 length of segment : 291 time for calcul the mask position with numpy : 0.0681467056274414 nb_pixel_total : 17774 time to create 1 rle with old method : 0.02830052375793457 length of segment : 149 time for calcul the mask position with numpy : 0.06377410888671875 nb_pixel_total : 14418 time to create 1 rle with old method : 0.02288365364074707 length of segment : 166 time for calcul the mask position with numpy : 0.08943748474121094 nb_pixel_total : 22646 time to create 1 rle with old method : 0.03148007392883301 length of segment : 173 time for calcul the mask position with numpy : 0.10825610160827637 nb_pixel_total : 26642 time to create 1 rle with old method : 0.03849911689758301 length of segment : 241 time for calcul the mask position with numpy : 0.06963801383972168 nb_pixel_total : 14266 time to create 1 rle with old method : 0.024088144302368164 length of segment : 185 time for calcul the mask position with numpy : 0.04229474067687988 nb_pixel_total : 10738 time to create 1 rle with old method : 0.019488811492919922 length of segment : 135 time for calcul the mask position with numpy : 0.07814168930053711 nb_pixel_total : 23191 time to create 1 rle with old method : 0.03429388999938965 length of segment : 195 time for calcul the mask position with numpy : 0.09790587425231934 nb_pixel_total : 27880 time to create 1 rle with old method : 0.03381228446960449 length of segment : 250 time for calcul the mask position with numpy : 0.16168904304504395 nb_pixel_total : 49457 time to create 1 rle with old method : 0.05808424949645996 length of segment : 405 time for calcul the mask position with numpy : 0.10245060920715332 nb_pixel_total : 64526 time to create 1 rle with old method : 0.07355308532714844 length of segment : 221 time for calcul the mask position with numpy : 0.06031656265258789 nb_pixel_total : 36315 time to create 1 rle with old method : 0.04363560676574707 length of segment : 208 time for calcul the mask position with numpy : 0.05529665946960449 nb_pixel_total : 30503 time to create 1 rle with old method : 0.04309797286987305 length of segment : 238 time for calcul the mask position with numpy : 0.04194188117980957 nb_pixel_total : 16293 time to create 1 rle with old method : 0.022465229034423828 length of segment : 142 time for calcul the mask position with numpy : 0.08125090599060059 nb_pixel_total : 26146 time to create 1 rle with old method : 0.033780574798583984 length of segment : 313 time for calcul the mask position with numpy : 0.014288187026977539 nb_pixel_total : 11524 time to create 1 rle with old method : 0.017337322235107422 length of segment : 112 time for calcul the mask position with numpy : 0.0002200603485107422 nb_pixel_total : 9712 time to create 1 rle with old method : 0.011518239974975586 length of segment : 109 time for calcul the mask position with numpy : 0.024828672409057617 nb_pixel_total : 8704 time to create 1 rle with old method : 0.014450788497924805 length of segment : 115 time for calcul the mask position with numpy : 0.03970980644226074 nb_pixel_total : 10059 time to create 1 rle with old method : 0.016321897506713867 length of segment : 90 time for calcul the mask position with numpy : 0.02978801727294922 nb_pixel_total : 9271 time to create 1 rle with old method : 0.014689922332763672 length of segment : 187 time for calcul the mask position with numpy : 0.1405324935913086 nb_pixel_total : 48374 time to create 1 rle with old method : 0.05901813507080078 length of segment : 224 time for calcul the mask position with numpy : 0.09926223754882812 nb_pixel_total : 40252 time to create 1 rle with old method : 0.04602169990539551 length of segment : 289 time for calcul the mask position with numpy : 0.012939929962158203 nb_pixel_total : 6712 time to create 1 rle with old method : 0.012402534484863281 length of segment : 93 time for calcul the mask position with numpy : 0.057192325592041016 nb_pixel_total : 15128 time to create 1 rle with old method : 0.026108980178833008 length of segment : 253 time for calcul the mask position with numpy : 0.01340031623840332 nb_pixel_total : 6492 time to create 1 rle with old method : 0.011857748031616211 length of segment : 98 time for calcul the mask position with numpy : 0.09254097938537598 nb_pixel_total : 29065 time to create 1 rle with old method : 0.034525156021118164 length of segment : 244 time for calcul the mask position with numpy : 0.04413795471191406 nb_pixel_total : 38622 time to create 1 rle with old method : 0.044382572174072266 length of segment : 296 time for calcul the mask position with numpy : 0.0932917594909668 nb_pixel_total : 16797 time to create 1 rle with old method : 0.0248873233795166 length of segment : 264 time for calcul the mask position with numpy : 0.09769201278686523 nb_pixel_total : 29131 time to create 1 rle with old method : 0.038069725036621094 length of segment : 253 time for calcul the mask position with numpy : 0.05434918403625488 nb_pixel_total : 19881 time to create 1 rle with old method : 0.027517318725585938 length of segment : 272 time for calcul the mask position with numpy : 0.01563882827758789 nb_pixel_total : 28973 time to create 1 rle with old method : 0.03562808036804199 length of segment : 179 time for calcul the mask position with numpy : 0.011840105056762695 nb_pixel_total : 5280 time to create 1 rle with old method : 0.010624408721923828 length of segment : 48 time for calcul the mask position with numpy : 0.030907392501831055 nb_pixel_total : 27732 time to create 1 rle with old method : 0.03414487838745117 length of segment : 238 time for calcul the mask position with numpy : 0.0527796745300293 nb_pixel_total : 15480 time to create 1 rle with old method : 0.019695520401000977 length of segment : 172 time for calcul the mask position with numpy : 0.2984588146209717 nb_pixel_total : 115073 time to create 1 rle with old method : 0.13835620880126953 length of segment : 457 time for calcul the mask position with numpy : 0.0825812816619873 nb_pixel_total : 17670 time to create 1 rle with old method : 0.05061697959899902 length of segment : 149 time for calcul the mask position with numpy : 0.10340380668640137 nb_pixel_total : 59227 time to create 1 rle with old method : 0.07210516929626465 length of segment : 205 time for calcul the mask position with numpy : 0.2227926254272461 nb_pixel_total : 108564 time to create 1 rle with old method : 0.12839078903198242 length of segment : 315 time for calcul the mask position with numpy : 0.11552810668945312 nb_pixel_total : 25960 time to create 1 rle with old method : 0.03422951698303223 length of segment : 256 time for calcul the mask position with numpy : 0.23171591758728027 nb_pixel_total : 66348 time to create 1 rle with old method : 0.07839822769165039 length of segment : 509 time for calcul the mask position with numpy : 0.10242629051208496 nb_pixel_total : 26152 time to create 1 rle with old method : 0.03265976905822754 length of segment : 223 time for calcul the mask position with numpy : 0.07822489738464355 nb_pixel_total : 27586 time to create 1 rle with old method : 0.03447389602661133 length of segment : 244 time for calcul the mask position with numpy : 0.054647207260131836 nb_pixel_total : 17287 time to create 1 rle with old method : 0.02325296401977539 length of segment : 188 time for calcul the mask position with numpy : 0.020832061767578125 nb_pixel_total : 17953 time to create 1 rle with old method : 0.026334762573242188 length of segment : 111 time for calcul the mask position with numpy : 0.07989978790283203 nb_pixel_total : 28946 time to create 1 rle with old method : 0.03653693199157715 length of segment : 285 time for calcul the mask position with numpy : 0.028179645538330078 nb_pixel_total : 9179 time to create 1 rle with old method : 0.015674114227294922 length of segment : 97 time for calcul the mask position with numpy : 0.08739614486694336 nb_pixel_total : 66969 time to create 1 rle with old method : 0.07749629020690918 length of segment : 333 time for calcul the mask position with numpy : 0.06992244720458984 nb_pixel_total : 16375 time to create 1 rle with old method : 0.023120880126953125 length of segment : 281 time for calcul the mask position with numpy : 0.10482549667358398 nb_pixel_total : 35180 time to create 1 rle with old method : 0.043250083923339844 length of segment : 269 time for calcul the mask position with numpy : 0.00045561790466308594 nb_pixel_total : 21036 time to create 1 rle with old method : 0.023679733276367188 length of segment : 211 time for calcul the mask position with numpy : 0.04601931571960449 nb_pixel_total : 23945 time to create 1 rle with old method : 0.03247332572937012 length of segment : 195 time for calcul the mask position with numpy : 0.02225017547607422 nb_pixel_total : 8491 time to create 1 rle with old method : 0.014545917510986328 length of segment : 73 time for calcul the mask position with numpy : 0.03194785118103027 nb_pixel_total : 16167 time to create 1 rle with old method : 0.02251744270324707 length of segment : 152 time for calcul the mask position with numpy : 0.05011868476867676 nb_pixel_total : 17532 time to create 1 rle with old method : 0.0235292911529541 length of segment : 118 time for calcul the mask position with numpy : 0.03686881065368652 nb_pixel_total : 43271 time to create 1 rle with old method : 0.050871849060058594 length of segment : 239 time for calcul the mask position with numpy : 0.16290068626403809 nb_pixel_total : 70665 time to create 1 rle with old method : 0.10320258140563965 length of segment : 437 time for calcul the mask position with numpy : 0.012753009796142578 nb_pixel_total : 14139 time to create 1 rle with old method : 0.016286849975585938 length of segment : 133 time for calcul the mask position with numpy : 0.1156301498413086 nb_pixel_total : 57689 time to create 1 rle with old method : 0.06562972068786621 length of segment : 246 time for calcul the mask position with numpy : 0.07563567161560059 nb_pixel_total : 31583 time to create 1 rle with old method : 0.0390017032623291 length of segment : 255 time for calcul the mask position with numpy : 0.2641901969909668 nb_pixel_total : 126392 time to create 1 rle with old method : 0.14615750312805176 length of segment : 430 time for calcul the mask position with numpy : 0.15938901901245117 nb_pixel_total : 81711 time to create 1 rle with old method : 0.09666180610656738 length of segment : 295 time for calcul the mask position with numpy : 0.008780479431152344 nb_pixel_total : 8848 time to create 1 rle with old method : 0.015383005142211914 length of segment : 143 time for calcul the mask position with numpy : 0.06452393531799316 nb_pixel_total : 21163 time to create 1 rle with old method : 0.03025984764099121 length of segment : 147 time for calcul the mask position with numpy : 0.0009169578552246094 nb_pixel_total : 17285 time to create 1 rle with old method : 0.020244121551513672 length of segment : 100 time for calcul the mask position with numpy : 0.0269467830657959 nb_pixel_total : 18587 time to create 1 rle with old method : 0.02664470672607422 length of segment : 103 time for calcul the mask position with numpy : 0.054738521575927734 nb_pixel_total : 36941 time to create 1 rle with old method : 0.04409193992614746 length of segment : 448 time for calcul the mask position with numpy : 0.002905607223510742 nb_pixel_total : 7348 time to create 1 rle with old method : 0.010520458221435547 length of segment : 159 time for calcul the mask position with numpy : 0.004700422286987305 nb_pixel_total : 16235 time to create 1 rle with old method : 0.0220029354095459 length of segment : 162 time for calcul the mask position with numpy : 0.06496691703796387 nb_pixel_total : 32090 time to create 1 rle with old method : 0.04007720947265625 length of segment : 237 time for calcul the mask position with numpy : 0.002406597137451172 nb_pixel_total : 13758 time to create 1 rle with old method : 0.016022205352783203 length of segment : 136 time for calcul the mask position with numpy : 0.025445938110351562 nb_pixel_total : 15084 time to create 1 rle with old method : 0.02441573143005371 length of segment : 219 time for calcul the mask position with numpy : 0.09118986129760742 nb_pixel_total : 44744 time to create 1 rle with old method : 0.05411505699157715 length of segment : 191 time for calcul the mask position with numpy : 0.1851215362548828 nb_pixel_total : 44302 time to create 1 rle with old method : 0.05289816856384277 length of segment : 350 time for calcul the mask position with numpy : 0.12568283081054688 nb_pixel_total : 48605 time to create 1 rle with old method : 0.06826043128967285 length of segment : 249 time for calcul the mask position with numpy : 0.13058900833129883 nb_pixel_total : 35293 time to create 1 rle with old method : 0.05993509292602539 length of segment : 319 time for calcul the mask position with numpy : 0.16148829460144043 nb_pixel_total : 53127 time to create 1 rle with old method : 0.06316828727722168 length of segment : 351 time for calcul the mask position with numpy : 0.14072346687316895 nb_pixel_total : 41740 time to create 1 rle with old method : 0.055472373962402344 length of segment : 209 time for calcul the mask position with numpy : 0.08621358871459961 nb_pixel_total : 24848 time to create 1 rle with old method : 0.03226828575134277 length of segment : 336 time for calcul the mask position with numpy : 0.163100004196167 nb_pixel_total : 48705 time to create 1 rle with old method : 0.07506155967712402 length of segment : 364 time for calcul the mask position with numpy : 0.024964094161987305 nb_pixel_total : 12053 time to create 1 rle with old method : 0.01922607421875 length of segment : 129 time for calcul the mask position with numpy : 0.05489516258239746 nb_pixel_total : 19887 time to create 1 rle with old method : 0.030634164810180664 length of segment : 275 time for calcul the mask position with numpy : 0.09088611602783203 nb_pixel_total : 15771 time to create 1 rle with old method : 0.0322566032409668 length of segment : 346 time for calcul the mask position with numpy : 0.05960893630981445 nb_pixel_total : 9592 time to create 1 rle with old method : 0.017481088638305664 length of segment : 138 time for calcul the mask position with numpy : 0.06118655204772949 nb_pixel_total : 11071 time to create 1 rle with old method : 0.017153501510620117 length of segment : 99 time for calcul the mask position with numpy : 0.044030189514160156 nb_pixel_total : 15216 time to create 1 rle with old method : 0.02078557014465332 length of segment : 134 time for calcul the mask position with numpy : 0.05623197555541992 nb_pixel_total : 23992 time to create 1 rle with old method : 0.03309154510498047 length of segment : 359 time for calcul the mask position with numpy : 0.16933774948120117 nb_pixel_total : 44343 time to create 1 rle with old method : 0.05460643768310547 length of segment : 330 time for calcul the mask position with numpy : 0.021831274032592773 nb_pixel_total : 6956 time to create 1 rle with old method : 0.010720014572143555 length of segment : 102 time for calcul the mask position with numpy : 0.03851580619812012 nb_pixel_total : 5199 time to create 1 rle with old method : 0.009734153747558594 length of segment : 127 time for calcul the mask position with numpy : 0.07941746711730957 nb_pixel_total : 27875 time to create 1 rle with old method : 0.0356447696685791 length of segment : 206 time for calcul the mask position with numpy : 0.07855343818664551 nb_pixel_total : 20177 time to create 1 rle with old method : 0.026934385299682617 length of segment : 192 time for calcul the mask position with numpy : 0.03248262405395508 nb_pixel_total : 11102 time to create 1 rle with old method : 0.016432762145996094 length of segment : 168 time for calcul the mask position with numpy : 0.07445883750915527 nb_pixel_total : 14396 time to create 1 rle with old method : 0.019120454788208008 length of segment : 176 time for calcul the mask position with numpy : 0.0783085823059082 nb_pixel_total : 21285 time to create 1 rle with old method : 0.02859973907470703 length of segment : 198 time for calcul the mask position with numpy : 0.04059028625488281 nb_pixel_total : 10569 time to create 1 rle with old method : 0.017174482345581055 length of segment : 117 time for calcul the mask position with numpy : 0.11166834831237793 nb_pixel_total : 44815 time to create 1 rle with old method : 0.05504608154296875 length of segment : 226 time for calcul the mask position with numpy : 0.07417702674865723 nb_pixel_total : 18578 time to create 1 rle with old method : 0.02720165252685547 length of segment : 187 time for calcul the mask position with numpy : 0.11794471740722656 nb_pixel_total : 49156 time to create 1 rle with old method : 0.060271501541137695 length of segment : 269 time for calcul the mask position with numpy : 0.06653976440429688 nb_pixel_total : 20281 time to create 1 rle with old method : 0.027274608612060547 length of segment : 208 time for calcul the mask position with numpy : 0.02803206443786621 nb_pixel_total : 15683 time to create 1 rle with old method : 0.02312326431274414 length of segment : 157 time for calcul the mask position with numpy : 0.030668258666992188 nb_pixel_total : 13080 time to create 1 rle with old method : 0.019823789596557617 length of segment : 186 time for calcul the mask position with numpy : 0.02130746841430664 nb_pixel_total : 9099 time to create 1 rle with old method : 0.013418197631835938 length of segment : 136 time for calcul the mask position with numpy : 0.06452155113220215 nb_pixel_total : 25167 time to create 1 rle with old method : 0.03195333480834961 length of segment : 202 time for calcul the mask position with numpy : 0.16214871406555176 nb_pixel_total : 75621 time to create 1 rle with old method : 0.09075093269348145 length of segment : 717 time for calcul the mask position with numpy : 0.0004067420959472656 nb_pixel_total : 17885 time to create 1 rle with old method : 0.020702123641967773 length of segment : 226 time for calcul the mask position with numpy : 0.021166563034057617 nb_pixel_total : 15746 time to create 1 rle with old method : 0.02374887466430664 length of segment : 120 time for calcul the mask position with numpy : 0.06392765045166016 nb_pixel_total : 38645 time to create 1 rle with old method : 0.04894256591796875 length of segment : 484 time for calcul the mask position with numpy : 0.4169468879699707 nb_pixel_total : 269879 time to create 1 rle with new method : 0.01990056037902832 length of segment : 498 time for calcul the mask position with numpy : 0.05358481407165527 nb_pixel_total : 25493 time to create 1 rle with old method : 0.034192562103271484 length of segment : 158 time for calcul the mask position with numpy : 0.20268964767456055 nb_pixel_total : 59884 time to create 1 rle with old method : 0.07414865493774414 length of segment : 383 time for calcul the mask position with numpy : 0.16600537300109863 nb_pixel_total : 107128 time to create 1 rle with old method : 0.12368941307067871 length of segment : 433 time for calcul the mask position with numpy : 0.03343462944030762 nb_pixel_total : 16368 time to create 1 rle with old method : 0.024648189544677734 length of segment : 176 time for calcul the mask position with numpy : 0.0419001579284668 nb_pixel_total : 27397 time to create 1 rle with old method : 0.0352785587310791 length of segment : 171 time for calcul the mask position with numpy : 0.008669376373291016 nb_pixel_total : 18467 time to create 1 rle with old method : 0.027523040771484375 length of segment : 132 time for calcul the mask position with numpy : 0.020167827606201172 nb_pixel_total : 6092 time to create 1 rle with old method : 0.010453224182128906 length of segment : 104 time for calcul the mask position with numpy : 0.07883167266845703 nb_pixel_total : 21936 time to create 1 rle with old method : 0.028888940811157227 length of segment : 226 time for calcul the mask position with numpy : 0.011335134506225586 nb_pixel_total : 12518 time to create 1 rle with old method : 0.017377138137817383 length of segment : 147 time for calcul the mask position with numpy : 0.010376691818237305 nb_pixel_total : 22147 time to create 1 rle with old method : 0.03000354766845703 length of segment : 332 time for calcul the mask position with numpy : 0.0001919269561767578 nb_pixel_total : 7331 time to create 1 rle with old method : 0.00869131088256836 length of segment : 161 time for calcul the mask position with numpy : 0.10826516151428223 nb_pixel_total : 61572 time to create 1 rle with old method : 0.07361555099487305 length of segment : 294 time for calcul the mask position with numpy : 0.010506153106689453 nb_pixel_total : 5899 time to create 1 rle with old method : 0.008586883544921875 length of segment : 75 time for calcul the mask position with numpy : 0.034145355224609375 nb_pixel_total : 30220 time to create 1 rle with old method : 0.040590763092041016 length of segment : 344 time for calcul the mask position with numpy : 0.012386322021484375 nb_pixel_total : 3370 time to create 1 rle with old method : 0.00496220588684082 length of segment : 53 time for calcul the mask position with numpy : 0.057167768478393555 nb_pixel_total : 19851 time to create 1 rle with old method : 0.026232481002807617 length of segment : 187 time for calcul the mask position with numpy : 0.00029587745666503906 nb_pixel_total : 11748 time to create 1 rle with old method : 0.014013051986694336 length of segment : 107 time for calcul the mask position with numpy : 0.016779661178588867 nb_pixel_total : 22736 time to create 1 rle with old method : 0.029165029525756836 length of segment : 162 time for calcul the mask position with numpy : 0.130845308303833 nb_pixel_total : 111715 time to create 1 rle with old method : 0.12326645851135254 length of segment : 348 time for calcul the mask position with numpy : 0.020079374313354492 nb_pixel_total : 12916 time to create 1 rle with old method : 0.019292593002319336 length of segment : 150 time for calcul the mask position with numpy : 0.08852791786193848 nb_pixel_total : 24590 time to create 1 rle with old method : 0.04037761688232422 length of segment : 306 time for calcul the mask position with numpy : 0.010980367660522461 nb_pixel_total : 4521 time to create 1 rle with old method : 0.008211135864257812 length of segment : 61 time for calcul the mask position with numpy : 0.012358903884887695 nb_pixel_total : 11513 time to create 1 rle with old method : 0.014160633087158203 length of segment : 159 time for calcul the mask position with numpy : 0.009631156921386719 nb_pixel_total : 27396 time to create 1 rle with old method : 0.035711050033569336 length of segment : 189 time for calcul the mask position with numpy : 0.024108409881591797 nb_pixel_total : 19540 time to create 1 rle with old method : 0.024889469146728516 length of segment : 186 time for calcul the mask position with numpy : 0.0069732666015625 nb_pixel_total : 23190 time to create 1 rle with old method : 0.03551506996154785 length of segment : 241 time for calcul the mask position with numpy : 0.24410748481750488 nb_pixel_total : 186833 time to create 1 rle with new method : 0.013501405715942383 length of segment : 433 time for calcul the mask position with numpy : 0.2238011360168457 nb_pixel_total : 144232 time to create 1 rle with old method : 0.18844866752624512 length of segment : 463 time for calcul the mask position with numpy : 0.3788759708404541 nb_pixel_total : 166494 time to create 1 rle with new method : 0.024437904357910156 length of segment : 632 time for calcul the mask position with numpy : 0.06327176094055176 nb_pixel_total : 33184 time to create 1 rle with old method : 0.053104400634765625 length of segment : 201 time for calcul the mask position with numpy : 0.05839943885803223 nb_pixel_total : 24246 time to create 1 rle with old method : 0.032085418701171875 length of segment : 304 time for calcul the mask position with numpy : 0.10557270050048828 nb_pixel_total : 30533 time to create 1 rle with old method : 0.03858494758605957 length of segment : 329 time for calcul the mask position with numpy : 0.044461965560913086 nb_pixel_total : 27954 time to create 1 rle with old method : 0.0370786190032959 length of segment : 105 time for calcul the mask position with numpy : 0.19492769241333008 nb_pixel_total : 119901 time to create 1 rle with old method : 0.1533510684967041 length of segment : 414 time for calcul the mask position with numpy : 0.0837864875793457 nb_pixel_total : 84463 time to create 1 rle with old method : 0.0991063117980957 length of segment : 475 time for calcul the mask position with numpy : 0.018115520477294922 nb_pixel_total : 37320 time to create 1 rle with old method : 0.044672250747680664 length of segment : 229 time for calcul the mask position with numpy : 0.018223047256469727 nb_pixel_total : 10885 time to create 1 rle with old method : 0.01635003089904785 length of segment : 118 time for calcul the mask position with numpy : 0.3505239486694336 nb_pixel_total : 207710 time to create 1 rle with new method : 0.01976776123046875 length of segment : 789 time for calcul the mask position with numpy : 0.04282188415527344 nb_pixel_total : 10647 time to create 1 rle with old method : 0.0170133113861084 length of segment : 170 time for calcul the mask position with numpy : 0.02523183822631836 nb_pixel_total : 37495 time to create 1 rle with old method : 0.05000424385070801 length of segment : 134 time for calcul the mask position with numpy : 0.2401430606842041 nb_pixel_total : 202129 time to create 1 rle with new method : 0.018045425415039062 length of segment : 891 time for calcul the mask position with numpy : 0.029364585876464844 nb_pixel_total : 11008 time to create 1 rle with old method : 0.018877506256103516 length of segment : 126 time for calcul the mask position with numpy : 0.06015729904174805 nb_pixel_total : 89676 time to create 1 rle with old method : 0.10188174247741699 length of segment : 191 time for calcul the mask position with numpy : 0.04262280464172363 nb_pixel_total : 46062 time to create 1 rle with old method : 0.05704641342163086 length of segment : 286 time for calcul the mask position with numpy : 0.007079601287841797 nb_pixel_total : 28918 time to create 1 rle with old method : 0.04309439659118652 length of segment : 169 time for calcul the mask position with numpy : 0.042412519454956055 nb_pixel_total : 26542 time to create 1 rle with old method : 0.03281593322753906 length of segment : 240 time for calcul the mask position with numpy : 0.001756429672241211 nb_pixel_total : 51939 time to create 1 rle with old method : 0.05942654609680176 length of segment : 363 time for calcul the mask position with numpy : 0.1374666690826416 nb_pixel_total : 117254 time to create 1 rle with old method : 0.15422511100769043 length of segment : 377 time for calcul the mask position with numpy : 0.047551870346069336 nb_pixel_total : 40555 time to create 1 rle with old method : 0.055059194564819336 length of segment : 296 time for calcul the mask position with numpy : 0.011181116104125977 nb_pixel_total : 13159 time to create 1 rle with old method : 0.018584251403808594 length of segment : 115 time for calcul the mask position with numpy : 0.03130531311035156 nb_pixel_total : 18985 time to create 1 rle with old method : 0.025899410247802734 length of segment : 243 time for calcul the mask position with numpy : 0.010116815567016602 nb_pixel_total : 59441 time to create 1 rle with old method : 0.07778024673461914 length of segment : 276 time for calcul the mask position with numpy : 0.02220773696899414 nb_pixel_total : 29103 time to create 1 rle with old method : 0.03803586959838867 length of segment : 170 time for calcul the mask position with numpy : 0.023186683654785156 nb_pixel_total : 22458 time to create 1 rle with old method : 0.028968095779418945 length of segment : 111 time for calcul the mask position with numpy : 0.00028586387634277344 nb_pixel_total : 9065 time to create 1 rle with old method : 0.01088714599609375 length of segment : 109 time for calcul the mask position with numpy : 0.027618885040283203 nb_pixel_total : 51295 time to create 1 rle with old method : 0.0625917911529541 length of segment : 386 time for calcul the mask position with numpy : 0.04338502883911133 nb_pixel_total : 11722 time to create 1 rle with old method : 0.017882823944091797 length of segment : 141 time for calcul the mask position with numpy : 0.07782125473022461 nb_pixel_total : 47165 time to create 1 rle with old method : 0.07162070274353027 length of segment : 243 time for calcul the mask position with numpy : 0.058989763259887695 nb_pixel_total : 26850 time to create 1 rle with old method : 0.03431057929992676 length of segment : 184 time for calcul the mask position with numpy : 0.1515514850616455 nb_pixel_total : 53635 time to create 1 rle with old method : 0.0907900333404541 length of segment : 359 time for calcul the mask position with numpy : 0.10288739204406738 nb_pixel_total : 52510 time to create 1 rle with old method : 0.06395220756530762 length of segment : 215 time for calcul the mask position with numpy : 0.09089946746826172 nb_pixel_total : 25151 time to create 1 rle with old method : 0.03121638298034668 length of segment : 225 time for calcul the mask position with numpy : 0.1809706687927246 nb_pixel_total : 61617 time to create 1 rle with old method : 0.07364344596862793 length of segment : 423 time for calcul the mask position with numpy : 0.04973459243774414 nb_pixel_total : 25523 time to create 1 rle with old method : 0.03236818313598633 length of segment : 171 time for calcul the mask position with numpy : 0.029176712036132812 nb_pixel_total : 6003 time to create 1 rle with old method : 0.010125875473022461 length of segment : 95 time for calcul the mask position with numpy : 0.06893610954284668 nb_pixel_total : 27776 time to create 1 rle with old method : 0.03714418411254883 length of segment : 187 time for calcul the mask position with numpy : 0.10793328285217285 nb_pixel_total : 48993 time to create 1 rle with old method : 0.06207871437072754 length of segment : 219 time for calcul the mask position with numpy : 0.0829458236694336 nb_pixel_total : 20271 time to create 1 rle with old method : 0.028786182403564453 length of segment : 268 time for calcul the mask position with numpy : 0.021551847457885742 nb_pixel_total : 17216 time to create 1 rle with old method : 0.022242307662963867 length of segment : 108 time for calcul the mask position with numpy : 0.003880023956298828 nb_pixel_total : 19970 time to create 1 rle with old method : 0.021695613861083984 length of segment : 200 time for calcul the mask position with numpy : 0.10791015625 nb_pixel_total : 36041 time to create 1 rle with old method : 0.044599294662475586 length of segment : 330 time for calcul the mask position with numpy : 0.059012413024902344 nb_pixel_total : 30283 time to create 1 rle with old method : 0.04248762130737305 length of segment : 250 time for calcul the mask position with numpy : 0.017035961151123047 nb_pixel_total : 15477 time to create 1 rle with old method : 0.024133920669555664 length of segment : 170 time for calcul the mask position with numpy : 0.04312849044799805 nb_pixel_total : 15582 time to create 1 rle with old method : 0.0220797061920166 length of segment : 146 time for calcul the mask position with numpy : 0.11127209663391113 nb_pixel_total : 81404 time to create 1 rle with old method : 0.09407615661621094 length of segment : 321 time for calcul the mask position with numpy : 0.054937124252319336 nb_pixel_total : 25889 time to create 1 rle with old method : 0.03450727462768555 length of segment : 157 time for calcul the mask position with numpy : 0.047676801681518555 nb_pixel_total : 27323 time to create 1 rle with old method : 0.032633066177368164 length of segment : 164 time for calcul the mask position with numpy : 0.016814708709716797 nb_pixel_total : 4370 time to create 1 rle with old method : 0.008654117584228516 length of segment : 56 time for calcul the mask position with numpy : 0.09263372421264648 nb_pixel_total : 46566 time to create 1 rle with old method : 0.05642843246459961 length of segment : 360 time for calcul the mask position with numpy : 0.0808563232421875 nb_pixel_total : 37771 time to create 1 rle with old method : 0.046602725982666016 length of segment : 222 time for calcul the mask position with numpy : 0.007614850997924805 nb_pixel_total : 7735 time to create 1 rle with old method : 0.010201454162597656 length of segment : 108 time for calcul the mask position with numpy : 0.07069540023803711 nb_pixel_total : 46738 time to create 1 rle with old method : 0.06777644157409668 length of segment : 216 time for calcul the mask position with numpy : 0.029007673263549805 nb_pixel_total : 33958 time to create 1 rle with old method : 0.04156684875488281 length of segment : 230 time for calcul the mask position with numpy : 0.0266110897064209 nb_pixel_total : 21815 time to create 1 rle with old method : 0.026643991470336914 length of segment : 183 time for calcul the mask position with numpy : 0.021305561065673828 nb_pixel_total : 3983 time to create 1 rle with old method : 0.007925033569335938 length of segment : 89 time for calcul the mask position with numpy : 0.05658721923828125 nb_pixel_total : 31935 time to create 1 rle with old method : 0.041815757751464844 length of segment : 260 time for calcul the mask position with numpy : 0.016152143478393555 nb_pixel_total : 6453 time to create 1 rle with old method : 0.007459163665771484 length of segment : 75 time for calcul the mask position with numpy : 0.09667110443115234 nb_pixel_total : 53394 time to create 1 rle with old method : 0.06632137298583984 length of segment : 247 time for calcul the mask position with numpy : 0.010901451110839844 nb_pixel_total : 2391 time to create 1 rle with old method : 0.0027472972869873047 length of segment : 64 time for calcul the mask position with numpy : 0.06925463676452637 nb_pixel_total : 32493 time to create 1 rle with old method : 0.04160666465759277 length of segment : 314 time for calcul the mask position with numpy : 0.018464326858520508 nb_pixel_total : 12587 time to create 1 rle with old method : 0.020232677459716797 length of segment : 148 time for calcul the mask position with numpy : 0.08843564987182617 nb_pixel_total : 76203 time to create 1 rle with old method : 0.0991673469543457 length of segment : 170 time for calcul the mask position with numpy : 0.05819845199584961 nb_pixel_total : 25013 time to create 1 rle with old method : 0.030993938446044922 length of segment : 286 time for calcul the mask position with numpy : 0.051876068115234375 nb_pixel_total : 20170 time to create 1 rle with old method : 0.02920222282409668 length of segment : 145 time for calcul the mask position with numpy : 0.04679274559020996 nb_pixel_total : 19150 time to create 1 rle with old method : 0.0249783992767334 length of segment : 144 time for calcul the mask position with numpy : 0.04239177703857422 nb_pixel_total : 21514 time to create 1 rle with old method : 0.02810215950012207 length of segment : 155 time for calcul the mask position with numpy : 0.04989981651306152 nb_pixel_total : 42318 time to create 1 rle with old method : 0.051030874252319336 length of segment : 210 time for calcul the mask position with numpy : 0.010863065719604492 nb_pixel_total : 9632 time to create 1 rle with old method : 0.014597892761230469 length of segment : 119 time for calcul the mask position with numpy : 0.06672835350036621 nb_pixel_total : 23007 time to create 1 rle with old method : 0.029631614685058594 length of segment : 187 time for calcul the mask position with numpy : 0.02596449851989746 nb_pixel_total : 9011 time to create 1 rle with old method : 0.016593456268310547 length of segment : 105 time for calcul the mask position with numpy : 0.017049551010131836 nb_pixel_total : 14694 time to create 1 rle with old method : 0.020888090133666992 length of segment : 147 time for calcul the mask position with numpy : 0.024248838424682617 nb_pixel_total : 15792 time to create 1 rle with old method : 0.020856142044067383 length of segment : 149 time for calcul the mask position with numpy : 0.13626956939697266 nb_pixel_total : 97308 time to create 1 rle with old method : 0.11589264869689941 length of segment : 261 time for calcul the mask position with numpy : 0.0423586368560791 nb_pixel_total : 10838 time to create 1 rle with old method : 0.01647043228149414 length of segment : 141 time for calcul the mask position with numpy : 0.10530352592468262 nb_pixel_total : 25185 time to create 1 rle with old method : 0.03259730339050293 length of segment : 296 time for calcul the mask position with numpy : 0.11599111557006836 nb_pixel_total : 20505 time to create 1 rle with old method : 0.025455236434936523 length of segment : 200 time for calcul the mask position with numpy : 0.08530187606811523 nb_pixel_total : 28543 time to create 1 rle with old method : 0.03684806823730469 length of segment : 180 time for calcul the mask position with numpy : 0.054489850997924805 nb_pixel_total : 38982 time to create 1 rle with old method : 0.05432868003845215 length of segment : 108 time for calcul the mask position with numpy : 0.03242897987365723 nb_pixel_total : 8110 time to create 1 rle with old method : 0.009315252304077148 length of segment : 97 time for calcul the mask position with numpy : 0.04024672508239746 nb_pixel_total : 9389 time to create 1 rle with old method : 0.010296344757080078 length of segment : 171 time for calcul the mask position with numpy : 0.0699319839477539 nb_pixel_total : 12015 time to create 1 rle with old method : 0.018910884857177734 length of segment : 233 time for calcul the mask position with numpy : 0.026041746139526367 nb_pixel_total : 5498 time to create 1 rle with old method : 0.010108470916748047 length of segment : 95 time for calcul the mask position with numpy : 0.1257777214050293 nb_pixel_total : 31899 time to create 1 rle with old method : 0.039642333984375 length of segment : 271 time for calcul the mask position with numpy : 0.035336971282958984 nb_pixel_total : 9445 time to create 1 rle with old method : 0.014087438583374023 length of segment : 121 time for calcul the mask position with numpy : 0.11208295822143555 nb_pixel_total : 35732 time to create 1 rle with old method : 0.04247450828552246 length of segment : 263 time for calcul the mask position with numpy : 0.044736385345458984 nb_pixel_total : 33341 time to create 1 rle with old method : 0.043825387954711914 length of segment : 178 time for calcul the mask position with numpy : 0.03011608123779297 nb_pixel_total : 6775 time to create 1 rle with old method : 0.012403011322021484 length of segment : 102 time for calcul the mask position with numpy : 0.48313140869140625 nb_pixel_total : 418173 time to create 1 rle with new method : 0.0358736515045166 length of segment : 1005 time for calcul the mask position with numpy : 0.07877588272094727 nb_pixel_total : 30774 time to create 1 rle with old method : 0.0388026237487793 length of segment : 180 time for calcul the mask position with numpy : 0.003509998321533203 nb_pixel_total : 20537 time to create 1 rle with old method : 0.025704622268676758 length of segment : 197 time for calcul the mask position with numpy : 0.07096028327941895 nb_pixel_total : 25900 time to create 1 rle with old method : 0.03772425651550293 length of segment : 198 time for calcul the mask position with numpy : 0.12295651435852051 nb_pixel_total : 45260 time to create 1 rle with old method : 0.05060601234436035 length of segment : 272 time for calcul the mask position with numpy : 0.09813809394836426 nb_pixel_total : 58951 time to create 1 rle with old method : 0.07161307334899902 length of segment : 444 time for calcul the mask position with numpy : 0.0049228668212890625 nb_pixel_total : 16146 time to create 1 rle with old method : 0.02083563804626465 length of segment : 171 time for calcul the mask position with numpy : 0.1572432518005371 nb_pixel_total : 62190 time to create 1 rle with old method : 0.07356739044189453 length of segment : 445 time for calcul the mask position with numpy : 0.03293156623840332 nb_pixel_total : 25922 time to create 1 rle with old method : 0.032480478286743164 length of segment : 182 time for calcul the mask position with numpy : 0.05567216873168945 nb_pixel_total : 45730 time to create 1 rle with old method : 0.058535099029541016 length of segment : 264 time for calcul the mask position with numpy : 0.03493952751159668 nb_pixel_total : 16771 time to create 1 rle with old method : 0.023536205291748047 length of segment : 151 time for calcul the mask position with numpy : 0.07071423530578613 nb_pixel_total : 27436 time to create 1 rle with old method : 0.033392906188964844 length of segment : 216 time for calcul the mask position with numpy : 0.33534979820251465 nb_pixel_total : 228186 time to create 1 rle with new method : 0.022211074829101562 length of segment : 712 time for calcul the mask position with numpy : 0.017747163772583008 nb_pixel_total : 4466 time to create 1 rle with old method : 0.00971364974975586 length of segment : 79 time for calcul the mask position with numpy : 0.05534982681274414 nb_pixel_total : 20645 time to create 1 rle with old method : 0.030248403549194336 length of segment : 155 time for calcul the mask position with numpy : 0.11733484268188477 nb_pixel_total : 98602 time to create 1 rle with old method : 0.1134943962097168 length of segment : 368 time for calcul the mask position with numpy : 0.024484872817993164 nb_pixel_total : 9542 time to create 1 rle with old method : 0.01724553108215332 length of segment : 126 time for calcul the mask position with numpy : 0.007809638977050781 nb_pixel_total : 4106 time to create 1 rle with old method : 0.007094383239746094 length of segment : 85 time for calcul the mask position with numpy : 0.035631656646728516 nb_pixel_total : 10358 time to create 1 rle with old method : 0.016542434692382812 length of segment : 162 time for calcul the mask position with numpy : 0.17163848876953125 nb_pixel_total : 60326 time to create 1 rle with old method : 0.07043313980102539 length of segment : 718 time for calcul the mask position with numpy : 0.002593517303466797 nb_pixel_total : 6874 time to create 1 rle with old method : 0.007995367050170898 length of segment : 114 time for calcul the mask position with numpy : 9.965896606445312e-05 nb_pixel_total : 2606 time to create 1 rle with old method : 0.003156900405883789 length of segment : 52 time for calcul the mask position with numpy : 0.1092386245727539 nb_pixel_total : 6993 time to create 1 rle with old method : 0.011992216110229492 length of segment : 92 time for calcul the mask position with numpy : 0.0003619194030761719 nb_pixel_total : 13998 time to create 1 rle with old method : 0.015918731689453125 length of segment : 172 time for calcul the mask position with numpy : 0.337597131729126 nb_pixel_total : 284110 time to create 1 rle with new method : 0.021878957748413086 length of segment : 842 time for calcul the mask position with numpy : 0.0631248950958252 nb_pixel_total : 44292 time to create 1 rle with old method : 0.05520486831665039 length of segment : 313 time for calcul the mask position with numpy : 0.0006184577941894531 nb_pixel_total : 21191 time to create 1 rle with old method : 0.024581193923950195 length of segment : 259 time for calcul the mask position with numpy : 0.02605462074279785 nb_pixel_total : 16770 time to create 1 rle with old method : 0.024329662322998047 length of segment : 248 time for calcul the mask position with numpy : 0.05360984802246094 nb_pixel_total : 44029 time to create 1 rle with old method : 0.052037954330444336 length of segment : 256 time for calcul the mask position with numpy : 0.050499677658081055 nb_pixel_total : 37060 time to create 1 rle with old method : 0.04430437088012695 length of segment : 310 time for calcul the mask position with numpy : 0.046125173568725586 nb_pixel_total : 21231 time to create 1 rle with old method : 0.03237771987915039 length of segment : 158 time for calcul the mask position with numpy : 0.044869184494018555 nb_pixel_total : 11862 time to create 1 rle with old method : 0.013132572174072266 length of segment : 124 time for calcul the mask position with numpy : 0.06759333610534668 nb_pixel_total : 12346 time to create 1 rle with old method : 0.01575493812561035 length of segment : 291 time for calcul the mask position with numpy : 0.12501168251037598 nb_pixel_total : 79558 time to create 1 rle with old method : 0.09260964393615723 length of segment : 475 time for calcul the mask position with numpy : 0.08147478103637695 nb_pixel_total : 19657 time to create 1 rle with old method : 0.025249719619750977 length of segment : 183 time for calcul the mask position with numpy : 0.041990041732788086 nb_pixel_total : 28322 time to create 1 rle with old method : 0.03373074531555176 length of segment : 174 time for calcul the mask position with numpy : 0.07432055473327637 nb_pixel_total : 22334 time to create 1 rle with old method : 0.029584646224975586 length of segment : 202 time for calcul the mask position with numpy : 0.0260009765625 nb_pixel_total : 7523 time to create 1 rle with old method : 0.013891220092773438 length of segment : 103 time for calcul the mask position with numpy : 0.03936338424682617 nb_pixel_total : 10804 time to create 1 rle with old method : 0.017864465713500977 length of segment : 128 time for calcul the mask position with numpy : 0.08817315101623535 nb_pixel_total : 16329 time to create 1 rle with old method : 0.03151726722717285 length of segment : 151 time for calcul the mask position with numpy : 0.05287599563598633 nb_pixel_total : 36912 time to create 1 rle with old method : 0.049551963806152344 length of segment : 102 time for calcul the mask position with numpy : 0.11382532119750977 nb_pixel_total : 29799 time to create 1 rle with old method : 0.03911733627319336 length of segment : 267 time for calcul the mask position with numpy : 0.11009359359741211 nb_pixel_total : 40943 time to create 1 rle with old method : 0.04717135429382324 length of segment : 297 time for calcul the mask position with numpy : 0.046003103256225586 nb_pixel_total : 16261 time to create 1 rle with old method : 0.021396636962890625 length of segment : 199 time for calcul the mask position with numpy : 0.4029576778411865 nb_pixel_total : 230337 time to create 1 rle with new method : 0.01825737953186035 length of segment : 694 time for calcul the mask position with numpy : 0.06675028800964355 nb_pixel_total : 24036 time to create 1 rle with old method : 0.03147315979003906 length of segment : 310 time for calcul the mask position with numpy : 0.08523416519165039 nb_pixel_total : 24366 time to create 1 rle with old method : 0.02704167366027832 length of segment : 235 time for calcul the mask position with numpy : 0.0033555030822753906 nb_pixel_total : 12878 time to create 1 rle with old method : 0.01900625228881836 length of segment : 218 time for calcul the mask position with numpy : 0.07933735847473145 nb_pixel_total : 23161 time to create 1 rle with old method : 0.03199410438537598 length of segment : 575 time for calcul the mask position with numpy : 0.10459709167480469 nb_pixel_total : 52560 time to create 1 rle with old method : 0.06210947036743164 length of segment : 269 time for calcul the mask position with numpy : 0.15171480178833008 nb_pixel_total : 95348 time to create 1 rle with old method : 0.10840344429016113 length of segment : 427 time for calcul the mask position with numpy : 0.03893923759460449 nb_pixel_total : 8465 time to create 1 rle with old method : 0.014611005783081055 length of segment : 108 time for calcul the mask position with numpy : 0.01750493049621582 nb_pixel_total : 14680 time to create 1 rle with old method : 0.021094560623168945 length of segment : 199 time for calcul the mask position with numpy : 0.059319496154785156 nb_pixel_total : 15564 time to create 1 rle with old method : 0.02187967300415039 length of segment : 258 time for calcul the mask position with numpy : 0.06448078155517578 nb_pixel_total : 23201 time to create 1 rle with old method : 0.0319972038269043 length of segment : 233 time for calcul the mask position with numpy : 0.035759687423706055 nb_pixel_total : 10821 time to create 1 rle with old method : 0.016165971755981445 length of segment : 192 time for calcul the mask position with numpy : 0.08975744247436523 nb_pixel_total : 42585 time to create 1 rle with old method : 0.052995920181274414 length of segment : 235 time for calcul the mask position with numpy : 0.07497668266296387 nb_pixel_total : 25642 time to create 1 rle with old method : 0.032620906829833984 length of segment : 183 time for calcul the mask position with numpy : 0.0842897891998291 nb_pixel_total : 28075 time to create 1 rle with old method : 0.03697991371154785 length of segment : 380 time for calcul the mask position with numpy : 0.08580136299133301 nb_pixel_total : 35165 time to create 1 rle with old method : 0.04303312301635742 length of segment : 313 time for calcul the mask position with numpy : 0.09654402732849121 nb_pixel_total : 23483 time to create 1 rle with old method : 0.030832767486572266 length of segment : 208 time for calcul the mask position with numpy : 0.041477203369140625 nb_pixel_total : 18874 time to create 1 rle with old method : 0.023557186126708984 length of segment : 144 time for calcul the mask position with numpy : 0.032671213150024414 nb_pixel_total : 33738 time to create 1 rle with old method : 0.04225921630859375 length of segment : 235 time for calcul the mask position with numpy : 0.010026216506958008 nb_pixel_total : 31998 time to create 1 rle with old method : 0.04390263557434082 length of segment : 288 time for calcul the mask position with numpy : 0.041754722595214844 nb_pixel_total : 18371 time to create 1 rle with old method : 0.027085065841674805 length of segment : 175 time for calcul the mask position with numpy : 0.035598039627075195 nb_pixel_total : 9338 time to create 1 rle with old method : 0.015567541122436523 length of segment : 149 time for calcul the mask position with numpy : 0.001936197280883789 nb_pixel_total : 8889 time to create 1 rle with old method : 0.010329723358154297 length of segment : 77 time for calcul the mask position with numpy : 0.02101755142211914 nb_pixel_total : 8596 time to create 1 rle with old method : 0.013222694396972656 length of segment : 72 time for calcul the mask position with numpy : 0.03754281997680664 nb_pixel_total : 11779 time to create 1 rle with old method : 0.017236948013305664 length of segment : 266 time for calcul the mask position with numpy : 0.04637765884399414 nb_pixel_total : 21776 time to create 1 rle with old method : 0.026343584060668945 length of segment : 195 time for calcul the mask position with numpy : 0.028621673583984375 nb_pixel_total : 11005 time to create 1 rle with old method : 0.017914772033691406 length of segment : 188 time for calcul the mask position with numpy : 0.028651952743530273 nb_pixel_total : 6843 time to create 1 rle with old method : 0.010659456253051758 length of segment : 98 time for calcul the mask position with numpy : 0.029102802276611328 nb_pixel_total : 46621 time to create 1 rle with old method : 0.07363367080688477 length of segment : 177 time for calcul the mask position with numpy : 0.0073299407958984375 nb_pixel_total : 10804 time to create 1 rle with old method : 0.015009403228759766 length of segment : 104 time for calcul the mask position with numpy : 0.06958460807800293 nb_pixel_total : 48148 time to create 1 rle with old method : 0.05798172950744629 length of segment : 276 time for calcul the mask position with numpy : 0.01455831527709961 nb_pixel_total : 7091 time to create 1 rle with old method : 0.012306451797485352 length of segment : 112 time for calcul the mask position with numpy : 0.05554556846618652 nb_pixel_total : 27290 time to create 1 rle with old method : 0.040732383728027344 length of segment : 264 time for calcul the mask position with numpy : 0.01957559585571289 nb_pixel_total : 11199 time to create 1 rle with old method : 0.017905235290527344 length of segment : 105 time for calcul the mask position with numpy : 0.03034210205078125 nb_pixel_total : 16288 time to create 1 rle with old method : 0.022620677947998047 length of segment : 204 time for calcul the mask position with numpy : 0.05713605880737305 nb_pixel_total : 36265 time to create 1 rle with old method : 0.042534589767456055 length of segment : 239 time for calcul the mask position with numpy : 0.044799089431762695 nb_pixel_total : 22377 time to create 1 rle with old method : 0.03128170967102051 length of segment : 245 time for calcul the mask position with numpy : 0.06993842124938965 nb_pixel_total : 31034 time to create 1 rle with old method : 0.04255509376525879 length of segment : 358 time for calcul the mask position with numpy : 0.03185629844665527 nb_pixel_total : 19374 time to create 1 rle with old method : 0.0256655216217041 length of segment : 133 time for calcul the mask position with numpy : 0.009433984756469727 nb_pixel_total : 16313 time to create 1 rle with old method : 0.024224281311035156 length of segment : 131 time for calcul the mask position with numpy : 0.05309319496154785 nb_pixel_total : 59411 time to create 1 rle with old method : 0.07067489624023438 length of segment : 403 time for calcul the mask position with numpy : 0.04169130325317383 nb_pixel_total : 20069 time to create 1 rle with old method : 0.03765606880187988 length of segment : 182 time for calcul the mask position with numpy : 0.03584432601928711 nb_pixel_total : 18796 time to create 1 rle with old method : 0.03365039825439453 length of segment : 210 time for calcul the mask position with numpy : 0.034475088119506836 nb_pixel_total : 19739 time to create 1 rle with old method : 0.026790380477905273 length of segment : 364 time for calcul the mask position with numpy : 0.07503461837768555 nb_pixel_total : 26223 time to create 1 rle with old method : 0.03710055351257324 length of segment : 280 time for calcul the mask position with numpy : 0.01952362060546875 nb_pixel_total : 14236 time to create 1 rle with old method : 0.02094411849975586 length of segment : 212 time for calcul the mask position with numpy : 0.030912160873413086 nb_pixel_total : 47708 time to create 1 rle with old method : 0.07728362083435059 length of segment : 274 time for calcul the mask position with numpy : 0.013969898223876953 nb_pixel_total : 5593 time to create 1 rle with old method : 0.006242513656616211 length of segment : 118 time for calcul the mask position with numpy : 0.04377174377441406 nb_pixel_total : 44227 time to create 1 rle with old method : 0.05343770980834961 length of segment : 325 time for calcul the mask position with numpy : 0.007323026657104492 nb_pixel_total : 9520 time to create 1 rle with old method : 0.013803243637084961 length of segment : 85 time for calcul the mask position with numpy : 0.0006380081176757812 nb_pixel_total : 17107 time to create 1 rle with old method : 0.0188448429107666 length of segment : 173 time for calcul the mask position with numpy : 0.0016357898712158203 nb_pixel_total : 12493 time to create 1 rle with old method : 0.014290094375610352 length of segment : 118 time for calcul the mask position with numpy : 0.0011663436889648438 nb_pixel_total : 26850 time to create 1 rle with old method : 0.0305328369140625 length of segment : 132 time for calcul the mask position with numpy : 0.012739181518554688 nb_pixel_total : 17328 time to create 1 rle with old method : 0.02411365509033203 length of segment : 179 time for calcul the mask position with numpy : 0.005122661590576172 nb_pixel_total : 93543 time to create 1 rle with old method : 0.10306978225708008 length of segment : 737 time for calcul the mask position with numpy : 0.001817464828491211 nb_pixel_total : 7661 time to create 1 rle with old method : 0.00860905647277832 length of segment : 125 time for calcul the mask position with numpy : 0.009327411651611328 nb_pixel_total : 18002 time to create 1 rle with old method : 0.025406599044799805 length of segment : 134 time for calcul the mask position with numpy : 0.0021982192993164062 nb_pixel_total : 9534 time to create 1 rle with old method : 0.011035442352294922 length of segment : 93 time for calcul the mask position with numpy : 0.00095367431640625 nb_pixel_total : 5598 time to create 1 rle with old method : 0.006204366683959961 length of segment : 91 time for calcul the mask position with numpy : 0.007443428039550781 nb_pixel_total : 11223 time to create 1 rle with old method : 0.016382455825805664 length of segment : 89 time for calcul the mask position with numpy : 0.006797075271606445 nb_pixel_total : 46695 time to create 1 rle with old method : 0.05968070030212402 length of segment : 329 time for calcul the mask position with numpy : 0.028934717178344727 nb_pixel_total : 218819 time to create 1 rle with new method : 0.01452183723449707 length of segment : 714 time for calcul the mask position with numpy : 0.002349853515625 nb_pixel_total : 104804 time to create 1 rle with old method : 0.11153531074523926 length of segment : 617 time for calcul the mask position with numpy : 0.0008370876312255859 nb_pixel_total : 2465 time to create 1 rle with old method : 0.0032231807708740234 length of segment : 87 time for calcul the mask position with numpy : 0.0020427703857421875 nb_pixel_total : 9375 time to create 1 rle with old method : 0.010410308837890625 length of segment : 152 time for calcul the mask position with numpy : 0.0004055500030517578 nb_pixel_total : 12805 time to create 1 rle with old method : 0.01423335075378418 length of segment : 137 time for calcul the mask position with numpy : 0.002576589584350586 nb_pixel_total : 73737 time to create 1 rle with old method : 0.07767558097839355 length of segment : 408 time for calcul the mask position with numpy : 0.0020494461059570312 nb_pixel_total : 20817 time to create 1 rle with old method : 0.02351069450378418 length of segment : 196 time for calcul the mask position with numpy : 0.03854823112487793 nb_pixel_total : 223003 time to create 1 rle with new method : 0.01911330223083496 length of segment : 847 time for calcul the mask position with numpy : 0.002798795700073242 nb_pixel_total : 30486 time to create 1 rle with old method : 0.033745765686035156 length of segment : 280 time for calcul the mask position with numpy : 0.005022287368774414 nb_pixel_total : 48664 time to create 1 rle with old method : 0.05633139610290527 length of segment : 143 time for calcul the mask position with numpy : 0.0022683143615722656 nb_pixel_total : 9639 time to create 1 rle with old method : 0.011056661605834961 length of segment : 80 time for calcul the mask position with numpy : 0.0012326240539550781 nb_pixel_total : 6635 time to create 1 rle with old method : 0.0076482295989990234 length of segment : 82 time for calcul the mask position with numpy : 0.004278659820556641 nb_pixel_total : 34865 time to create 1 rle with old method : 0.040041208267211914 length of segment : 298 time for calcul the mask position with numpy : 0.0027627944946289062 nb_pixel_total : 31522 time to create 1 rle with old method : 0.03572440147399902 length of segment : 151 time for calcul the mask position with numpy : 0.003812551498413086 nb_pixel_total : 34861 time to create 1 rle with old method : 0.038249969482421875 length of segment : 249 time for calcul the mask position with numpy : 0.004264116287231445 nb_pixel_total : 23948 time to create 1 rle with old method : 0.028452157974243164 length of segment : 267 time for calcul the mask position with numpy : 0.007890701293945312 nb_pixel_total : 36775 time to create 1 rle with old method : 0.04358029365539551 length of segment : 302 time for calcul the mask position with numpy : 0.0055234432220458984 nb_pixel_total : 19708 time to create 1 rle with old method : 0.024994611740112305 length of segment : 179 time for calcul the mask position with numpy : 0.0010006427764892578 nb_pixel_total : 8867 time to create 1 rle with old method : 0.010088205337524414 length of segment : 99 time for calcul the mask position with numpy : 0.004128217697143555 nb_pixel_total : 48073 time to create 1 rle with old method : 0.05229830741882324 length of segment : 249 time for calcul the mask position with numpy : 0.008548259735107422 nb_pixel_total : 54470 time to create 1 rle with old method : 0.060593366622924805 length of segment : 257 time for calcul the mask position with numpy : 0.0035524368286132812 nb_pixel_total : 21280 time to create 1 rle with old method : 0.024234294891357422 length of segment : 216 time for calcul the mask position with numpy : 0.00553584098815918 nb_pixel_total : 44975 time to create 1 rle with old method : 0.05307412147521973 length of segment : 262 time for calcul the mask position with numpy : 0.0008535385131835938 nb_pixel_total : 8274 time to create 1 rle with old method : 0.009462594985961914 length of segment : 112 time for calcul the mask position with numpy : 0.0012345314025878906 nb_pixel_total : 12415 time to create 1 rle with old method : 0.013901472091674805 length of segment : 105 time for calcul the mask position with numpy : 0.0009160041809082031 nb_pixel_total : 6868 time to create 1 rle with old method : 0.008101701736450195 length of segment : 92 time for calcul the mask position with numpy : 0.0009326934814453125 nb_pixel_total : 4062 time to create 1 rle with old method : 0.004743337631225586 length of segment : 84 time for calcul the mask position with numpy : 0.0034978389739990234 nb_pixel_total : 23417 time to create 1 rle with old method : 0.026267290115356445 length of segment : 345 time for calcul the mask position with numpy : 0.005795478820800781 nb_pixel_total : 43291 time to create 1 rle with old method : 0.050527095794677734 length of segment : 210 time for calcul the mask position with numpy : 0.004213571548461914 nb_pixel_total : 16434 time to create 1 rle with old method : 0.021297454833984375 length of segment : 157 time for calcul the mask position with numpy : 0.000993967056274414 nb_pixel_total : 6930 time to create 1 rle with old method : 0.008094072341918945 length of segment : 83 time for calcul the mask position with numpy : 0.00043272972106933594 nb_pixel_total : 13112 time to create 1 rle with old method : 0.015316963195800781 length of segment : 155 time for calcul the mask position with numpy : 0.008970022201538086 nb_pixel_total : 38738 time to create 1 rle with old method : 0.05383610725402832 length of segment : 341 time for calcul the mask position with numpy : 0.003103494644165039 nb_pixel_total : 12682 time to create 1 rle with old method : 0.023719072341918945 length of segment : 225 time for calcul the mask position with numpy : 0.002315521240234375 nb_pixel_total : 11304 time to create 1 rle with old method : 0.013191461563110352 length of segment : 161 time for calcul the mask position with numpy : 0.0009717941284179688 nb_pixel_total : 8989 time to create 1 rle with old method : 0.010700225830078125 length of segment : 125 time for calcul the mask position with numpy : 0.0013508796691894531 nb_pixel_total : 8087 time to create 1 rle with old method : 0.00939321517944336 length of segment : 162 time for calcul the mask position with numpy : 0.003825664520263672 nb_pixel_total : 34335 time to create 1 rle with old method : 0.039331912994384766 length of segment : 219 time for calcul the mask position with numpy : 0.003293752670288086 nb_pixel_total : 13138 time to create 1 rle with old method : 0.017067909240722656 length of segment : 226 time for calcul the mask position with numpy : 0.0015132427215576172 nb_pixel_total : 14342 time to create 1 rle with old method : 0.015791654586791992 length of segment : 147 time for calcul the mask position with numpy : 0.001413583755493164 nb_pixel_total : 11501 time to create 1 rle with old method : 0.012986183166503906 length of segment : 162 time for calcul the mask position with numpy : 0.0028574466705322266 nb_pixel_total : 30704 time to create 1 rle with old method : 0.03413510322570801 length of segment : 233 time for calcul the mask position with numpy : 0.00039315223693847656 nb_pixel_total : 17303 time to create 1 rle with old method : 0.019272804260253906 length of segment : 133 time for calcul the mask position with numpy : 0.0031044483184814453 nb_pixel_total : 31888 time to create 1 rle with old method : 0.035318851470947266 length of segment : 158 time for calcul the mask position with numpy : 0.00030112266540527344 nb_pixel_total : 10197 time to create 1 rle with old method : 0.011407852172851562 length of segment : 126 time for calcul the mask position with numpy : 0.004664421081542969 nb_pixel_total : 32372 time to create 1 rle with old method : 0.03699660301208496 length of segment : 206 time for calcul the mask position with numpy : 0.0003757476806640625 nb_pixel_total : 13741 time to create 1 rle with old method : 0.014894962310791016 length of segment : 138 time for calcul the mask position with numpy : 0.005886554718017578 nb_pixel_total : 13390 time to create 1 rle with old method : 0.017901897430419922 length of segment : 129 time for calcul the mask position with numpy : 0.014786720275878906 nb_pixel_total : 179103 time to create 1 rle with new method : 0.011721134185791016 length of segment : 590 time for calcul the mask position with numpy : 0.007046937942504883 nb_pixel_total : 29737 time to create 1 rle with old method : 0.035166263580322266 length of segment : 213 time for calcul the mask position with numpy : 0.0013234615325927734 nb_pixel_total : 8838 time to create 1 rle with old method : 0.009421825408935547 length of segment : 151 time for calcul the mask position with numpy : 0.006170034408569336 nb_pixel_total : 82764 time to create 1 rle with old method : 0.08812665939331055 length of segment : 257 time for calcul the mask position with numpy : 0.016005277633666992 nb_pixel_total : 101505 time to create 1 rle with old method : 0.1128854751586914 length of segment : 220 time for calcul the mask position with numpy : 0.013373613357543945 nb_pixel_total : 32191 time to create 1 rle with old method : 0.03997349739074707 length of segment : 185 time for calcul the mask position with numpy : 0.007076263427734375 nb_pixel_total : 75733 time to create 1 rle with old method : 0.08598542213439941 length of segment : 420 time for calcul the mask position with numpy : 0.00422978401184082 nb_pixel_total : 38279 time to create 1 rle with old method : 0.04281759262084961 length of segment : 329 time for calcul the mask position with numpy : 0.009537935256958008 nb_pixel_total : 49922 time to create 1 rle with old method : 0.05875968933105469 length of segment : 289 time for calcul the mask position with numpy : 0.0025725364685058594 nb_pixel_total : 26105 time to create 1 rle with old method : 0.030187368392944336 length of segment : 395 time for calcul the mask position with numpy : 0.0003268718719482422 nb_pixel_total : 3596 time to create 1 rle with old method : 0.004439830780029297 length of segment : 57 time for calcul the mask position with numpy : 0.011406421661376953 nb_pixel_total : 27374 time to create 1 rle with old method : 0.03465723991394043 length of segment : 286 time for calcul the mask position with numpy : 0.00664830207824707 nb_pixel_total : 60761 time to create 1 rle with old method : 0.07001328468322754 length of segment : 302 time for calcul the mask position with numpy : 0.0012285709381103516 nb_pixel_total : 23085 time to create 1 rle with old method : 0.025977611541748047 length of segment : 252 time for calcul the mask position with numpy : 0.01665496826171875 nb_pixel_total : 11459 time to create 1 rle with old method : 0.01785731315612793 length of segment : 127 time for calcul the mask position with numpy : 0.0019431114196777344 nb_pixel_total : 21187 time to create 1 rle with old method : 0.02438831329345703 length of segment : 189 time for calcul the mask position with numpy : 0.003350973129272461 nb_pixel_total : 5222 time to create 1 rle with old method : 0.007630109786987305 length of segment : 170 time for calcul the mask position with numpy : 0.010311126708984375 nb_pixel_total : 41386 time to create 1 rle with old method : 0.04943966865539551 length of segment : 191 time for calcul the mask position with numpy : 0.007028818130493164 nb_pixel_total : 43298 time to create 1 rle with old method : 0.05104255676269531 length of segment : 623 time for calcul the mask position with numpy : 0.05031609535217285 nb_pixel_total : 36158 time to create 1 rle with old method : 0.04538679122924805 length of segment : 292 time for calcul the mask position with numpy : 0.0019443035125732422 nb_pixel_total : 35157 time to create 1 rle with old method : 0.0400233268737793 length of segment : 248 time for calcul the mask position with numpy : 0.005397796630859375 nb_pixel_total : 46011 time to create 1 rle with old method : 0.05506753921508789 length of segment : 289 time for calcul the mask position with numpy : 0.000152587890625 nb_pixel_total : 4369 time to create 1 rle with old method : 0.0054187774658203125 length of segment : 70 time for calcul the mask position with numpy : 0.013516664505004883 nb_pixel_total : 56455 time to create 1 rle with old method : 0.0669865608215332 length of segment : 330 time for calcul the mask position with numpy : 0.006739377975463867 nb_pixel_total : 127864 time to create 1 rle with old method : 0.1672649383544922 length of segment : 432 time for calcul the mask position with numpy : 0.002285003662109375 nb_pixel_total : 33537 time to create 1 rle with old method : 0.052588701248168945 length of segment : 187 time for calcul the mask position with numpy : 0.003390073776245117 nb_pixel_total : 37585 time to create 1 rle with old method : 0.0424199104309082 length of segment : 260 time for calcul the mask position with numpy : 0.0018987655639648438 nb_pixel_total : 24915 time to create 1 rle with old method : 0.028822660446166992 length of segment : 144 time for calcul the mask position with numpy : 0.002781391143798828 nb_pixel_total : 24778 time to create 1 rle with old method : 0.028800487518310547 length of segment : 179 time for calcul the mask position with numpy : 0.0005497932434082031 nb_pixel_total : 14423 time to create 1 rle with old method : 0.016866207122802734 length of segment : 117 time for calcul the mask position with numpy : 0.005202054977416992 nb_pixel_total : 31526 time to create 1 rle with old method : 0.03986787796020508 length of segment : 452 time for calcul the mask position with numpy : 0.0004911422729492188 nb_pixel_total : 5455 time to create 1 rle with old method : 0.00663447380065918 length of segment : 98 time for calcul the mask position with numpy : 0.02916693687438965 nb_pixel_total : 197020 time to create 1 rle with new method : 0.01295614242553711 length of segment : 646 time for calcul the mask position with numpy : 0.010423898696899414 nb_pixel_total : 78694 time to create 1 rle with old method : 0.09113335609436035 length of segment : 494 time for calcul the mask position with numpy : 0.013541460037231445 nb_pixel_total : 24047 time to create 1 rle with old method : 0.03352689743041992 length of segment : 305 time for calcul the mask position with numpy : 0.04496455192565918 nb_pixel_total : 115451 time to create 1 rle with old method : 0.13364243507385254 length of segment : 601 time for calcul the mask position with numpy : 0.029060840606689453 nb_pixel_total : 24750 time to create 1 rle with old method : 0.03430366516113281 length of segment : 163 time for calcul the mask position with numpy : 0.016962051391601562 nb_pixel_total : 226922 time to create 1 rle with new method : 0.011632919311523438 length of segment : 300 time for calcul the mask position with numpy : 0.002644062042236328 nb_pixel_total : 21072 time to create 1 rle with old method : 0.024256467819213867 length of segment : 173 time for calcul the mask position with numpy : 0.004113674163818359 nb_pixel_total : 96917 time to create 1 rle with old method : 0.11950063705444336 length of segment : 315 time for calcul the mask position with numpy : 0.009968996047973633 nb_pixel_total : 64732 time to create 1 rle with old method : 0.07348370552062988 length of segment : 498 time for calcul the mask position with numpy : 0.018078327178955078 nb_pixel_total : 107969 time to create 1 rle with old method : 0.12333536148071289 length of segment : 556 time for calcul the mask position with numpy : 0.0009775161743164062 nb_pixel_total : 9916 time to create 1 rle with old method : 0.011814355850219727 length of segment : 307 time for calcul the mask position with numpy : 0.0005180835723876953 nb_pixel_total : 27906 time to create 1 rle with old method : 0.03278827667236328 length of segment : 197 time for calcul the mask position with numpy : 0.019690275192260742 nb_pixel_total : 10089 time to create 1 rle with old method : 0.01624298095703125 length of segment : 126 time for calcul the mask position with numpy : 0.0004971027374267578 nb_pixel_total : 8615 time to create 1 rle with old method : 0.010546684265136719 length of segment : 86 time for calcul the mask position with numpy : 0.0020439624786376953 nb_pixel_total : 116198 time to create 1 rle with old method : 0.1302196979522705 length of segment : 395 time for calcul the mask position with numpy : 0.0012965202331542969 nb_pixel_total : 17307 time to create 1 rle with old method : 0.01990485191345215 length of segment : 129 time for calcul the mask position with numpy : 0.00030875205993652344 nb_pixel_total : 14483 time to create 1 rle with old method : 0.016627788543701172 length of segment : 163 time for calcul the mask position with numpy : 0.013712882995605469 nb_pixel_total : 6147 time to create 1 rle with old method : 0.009909629821777344 length of segment : 183 time for calcul the mask position with numpy : 0.011987447738647461 nb_pixel_total : 9373 time to create 1 rle with old method : 0.012705802917480469 length of segment : 99 time for calcul the mask position with numpy : 0.015014171600341797 nb_pixel_total : 118217 time to create 1 rle with old method : 0.13608717918395996 length of segment : 653 time for calcul the mask position with numpy : 0.0008668899536132812 nb_pixel_total : 34977 time to create 1 rle with old method : 0.03959155082702637 length of segment : 312 time for calcul the mask position with numpy : 0.007751941680908203 nb_pixel_total : 31235 time to create 1 rle with old method : 0.03894972801208496 length of segment : 257 time for calcul the mask position with numpy : 0.0058939456939697266 nb_pixel_total : 46770 time to create 1 rle with old method : 0.05512499809265137 length of segment : 326 time for calcul the mask position with numpy : 0.016642332077026367 nb_pixel_total : 11335 time to create 1 rle with old method : 0.016198158264160156 length of segment : 158 time for calcul the mask position with numpy : 0.013540506362915039 nb_pixel_total : 17167 time to create 1 rle with old method : 0.022475719451904297 length of segment : 181 time for calcul the mask position with numpy : 0.0014903545379638672 nb_pixel_total : 27427 time to create 1 rle with old method : 0.032105445861816406 length of segment : 189 time for calcul the mask position with numpy : 0.003159046173095703 nb_pixel_total : 39812 time to create 1 rle with old method : 0.05485033988952637 length of segment : 239 time for calcul the mask position with numpy : 0.0025556087493896484 nb_pixel_total : 29707 time to create 1 rle with old method : 0.036675214767456055 length of segment : 208 time for calcul the mask position with numpy : 0.0003173351287841797 nb_pixel_total : 5499 time to create 1 rle with old method : 0.006361484527587891 length of segment : 96 time for calcul the mask position with numpy : 0.026836872100830078 nb_pixel_total : 30435 time to create 1 rle with old method : 0.037107229232788086 length of segment : 237 time for calcul the mask position with numpy : 0.040976762771606445 nb_pixel_total : 119000 time to create 1 rle with old method : 0.15166664123535156 length of segment : 312 time for calcul the mask position with numpy : 0.03491950035095215 nb_pixel_total : 17278 time to create 1 rle with old method : 0.01969313621520996 length of segment : 171 time for calcul the mask position with numpy : 0.021671295166015625 nb_pixel_total : 12038 time to create 1 rle with old method : 0.014019489288330078 length of segment : 115 time for calcul the mask position with numpy : 0.015166997909545898 nb_pixel_total : 11858 time to create 1 rle with old method : 0.014575958251953125 length of segment : 135 time for calcul the mask position with numpy : 0.010860919952392578 nb_pixel_total : 7178 time to create 1 rle with old method : 0.013332605361938477 length of segment : 84 time for calcul the mask position with numpy : 0.0006699562072753906 nb_pixel_total : 12683 time to create 1 rle with old method : 0.014871358871459961 length of segment : 130 time for calcul the mask position with numpy : 0.0682070255279541 nb_pixel_total : 19425 time to create 1 rle with old method : 0.02672123908996582 length of segment : 244 time for calcul the mask position with numpy : 0.0480351448059082 nb_pixel_total : 28657 time to create 1 rle with old method : 0.03239727020263672 length of segment : 224 time for calcul the mask position with numpy : 0.01668548583984375 nb_pixel_total : 12201 time to create 1 rle with old method : 0.019001483917236328 length of segment : 76 time for calcul the mask position with numpy : 0.0009627342224121094 nb_pixel_total : 26480 time to create 1 rle with old method : 0.031159162521362305 length of segment : 153 time for calcul the mask position with numpy : 0.00036644935607910156 nb_pixel_total : 13930 time to create 1 rle with old method : 0.016074419021606445 length of segment : 121 time for calcul the mask position with numpy : 0.010507822036743164 nb_pixel_total : 10652 time to create 1 rle with old method : 0.015131473541259766 length of segment : 119 time for calcul the mask position with numpy : 0.03245258331298828 nb_pixel_total : 13418 time to create 1 rle with old method : 0.020914554595947266 length of segment : 188 time for calcul the mask position with numpy : 0.03478193283081055 nb_pixel_total : 10708 time to create 1 rle with old method : 0.017264842987060547 length of segment : 104 time for calcul the mask position with numpy : 0.055054426193237305 nb_pixel_total : 36238 time to create 1 rle with old method : 0.048600196838378906 length of segment : 197 time for calcul the mask position with numpy : 0.06307578086853027 nb_pixel_total : 56794 time to create 1 rle with old method : 0.06542396545410156 length of segment : 280 time for calcul the mask position with numpy : 0.01033926010131836 nb_pixel_total : 22706 time to create 1 rle with old method : 0.02852654457092285 length of segment : 155 time for calcul the mask position with numpy : 0.2947995662689209 nb_pixel_total : 309985 time to create 1 rle with new method : 0.02124810218811035 length of segment : 675 time for calcul the mask position with numpy : 0.00047326087951660156 nb_pixel_total : 7951 time to create 1 rle with old method : 0.009410858154296875 length of segment : 134 time for calcul the mask position with numpy : 0.010806798934936523 nb_pixel_total : 33130 time to create 1 rle with old method : 0.04006528854370117 length of segment : 261 time for calcul the mask position with numpy : 0.0026102066040039062 nb_pixel_total : 8160 time to create 1 rle with old method : 0.01486968994140625 length of segment : 108 time for calcul the mask position with numpy : 0.0014030933380126953 nb_pixel_total : 35606 time to create 1 rle with old method : 0.039546966552734375 length of segment : 182 time for calcul the mask position with numpy : 0.055389404296875 nb_pixel_total : 88773 time to create 1 rle with old method : 0.10043931007385254 length of segment : 397 time for calcul the mask position with numpy : 0.005567312240600586 nb_pixel_total : 14148 time to create 1 rle with old method : 0.025256872177124023 length of segment : 176 time for calcul the mask position with numpy : 0.02393364906311035 nb_pixel_total : 36753 time to create 1 rle with old method : 0.04757237434387207 length of segment : 172 time for calcul the mask position with numpy : 0.028345584869384766 nb_pixel_total : 100968 time to create 1 rle with old method : 0.11588263511657715 length of segment : 427 time for calcul the mask position with numpy : 0.0008437633514404297 nb_pixel_total : 19102 time to create 1 rle with old method : 0.020902156829833984 length of segment : 126 time for calcul the mask position with numpy : 0.021202564239501953 nb_pixel_total : 331114 time to create 1 rle with new method : 0.022250890731811523 length of segment : 737 time for calcul the mask position with numpy : 0.002622365951538086 nb_pixel_total : 16157 time to create 1 rle with old method : 0.02648162841796875 length of segment : 189 time for calcul the mask position with numpy : 0.004862785339355469 nb_pixel_total : 47446 time to create 1 rle with old method : 0.06105947494506836 length of segment : 506 time for calcul the mask position with numpy : 0.0014264583587646484 nb_pixel_total : 36045 time to create 1 rle with old method : 0.04101252555847168 length of segment : 237 time for calcul the mask position with numpy : 0.00032806396484375 nb_pixel_total : 9049 time to create 1 rle with old method : 0.010610580444335938 length of segment : 105 time for calcul the mask position with numpy : 0.004163265228271484 nb_pixel_total : 52393 time to create 1 rle with old method : 0.05728626251220703 length of segment : 277 time for calcul the mask position with numpy : 0.00040721893310546875 nb_pixel_total : 9139 time to create 1 rle with old method : 0.010328292846679688 length of segment : 110 time for calcul the mask position with numpy : 0.0011060237884521484 nb_pixel_total : 25152 time to create 1 rle with old method : 0.0276639461517334 length of segment : 278 time for calcul the mask position with numpy : 0.001682281494140625 nb_pixel_total : 51740 time to create 1 rle with old method : 0.05569601058959961 length of segment : 442 time for calcul the mask position with numpy : 0.012157440185546875 nb_pixel_total : 32619 time to create 1 rle with old method : 0.05189228057861328 length of segment : 256 time for calcul the mask position with numpy : 0.05994391441345215 nb_pixel_total : 582399 time to create 1 rle with new method : 0.03434324264526367 length of segment : 982 time for calcul the mask position with numpy : 0.0002970695495605469 nb_pixel_total : 8372 time to create 1 rle with old method : 0.009891986846923828 length of segment : 108 time for calcul the mask position with numpy : 0.00028777122497558594 nb_pixel_total : 7014 time to create 1 rle with old method : 0.008498430252075195 length of segment : 90 time for calcul the mask position with numpy : 0.0007386207580566406 nb_pixel_total : 14563 time to create 1 rle with old method : 0.017017602920532227 length of segment : 140 time for calcul the mask position with numpy : 0.00022649765014648438 nb_pixel_total : 4466 time to create 1 rle with old method : 0.005384922027587891 length of segment : 82 time for calcul the mask position with numpy : 0.004504203796386719 nb_pixel_total : 56839 time to create 1 rle with old method : 0.06951737403869629 length of segment : 358 time for calcul the mask position with numpy : 0.0005476474761962891 nb_pixel_total : 21558 time to create 1 rle with old method : 0.024704694747924805 length of segment : 166 time for calcul the mask position with numpy : 0.0026361942291259766 nb_pixel_total : 110397 time to create 1 rle with old method : 0.14981889724731445 length of segment : 435 time for calcul the mask position with numpy : 0.006627321243286133 nb_pixel_total : 90453 time to create 1 rle with old method : 0.10387754440307617 length of segment : 424 time for calcul the mask position with numpy : 0.0011343955993652344 nb_pixel_total : 13770 time to create 1 rle with old method : 0.016210317611694336 length of segment : 143 time for calcul the mask position with numpy : 0.0016169548034667969 nb_pixel_total : 20919 time to create 1 rle with old method : 0.024262666702270508 length of segment : 192 time for calcul the mask position with numpy : 0.0024650096893310547 nb_pixel_total : 32963 time to create 1 rle with old method : 0.03707456588745117 length of segment : 244 time for calcul the mask position with numpy : 0.0013720989227294922 nb_pixel_total : 12778 time to create 1 rle with old method : 0.022702455520629883 length of segment : 115 time for calcul the mask position with numpy : 0.0012865066528320312 nb_pixel_total : 13450 time to create 1 rle with old method : 0.016639232635498047 length of segment : 124 time for calcul the mask position with numpy : 0.0074214935302734375 nb_pixel_total : 146596 time to create 1 rle with old method : 0.16201066970825195 length of segment : 602 time for calcul the mask position with numpy : 0.00031447410583496094 nb_pixel_total : 4796 time to create 1 rle with old method : 0.005601644515991211 length of segment : 85 time for calcul the mask position with numpy : 0.0012764930725097656 nb_pixel_total : 15206 time to create 1 rle with old method : 0.017707347869873047 length of segment : 305 time for calcul the mask position with numpy : 0.003536224365234375 nb_pixel_total : 44775 time to create 1 rle with old method : 0.05138421058654785 length of segment : 211 time for calcul the mask position with numpy : 0.00040912628173828125 nb_pixel_total : 4820 time to create 1 rle with old method : 0.005818843841552734 length of segment : 80 time for calcul the mask position with numpy : 0.0069653987884521484 nb_pixel_total : 90690 time to create 1 rle with old method : 0.10177445411682129 length of segment : 392 time for calcul the mask position with numpy : 0.0021119117736816406 nb_pixel_total : 32941 time to create 1 rle with old method : 0.036881446838378906 length of segment : 288 time for calcul the mask position with numpy : 0.002938508987426758 nb_pixel_total : 47970 time to create 1 rle with old method : 0.05552315711975098 length of segment : 275 time for calcul the mask position with numpy : 0.0015902519226074219 nb_pixel_total : 16056 time to create 1 rle with old method : 0.019012928009033203 length of segment : 159 time for calcul the mask position with numpy : 0.000789642333984375 nb_pixel_total : 15579 time to create 1 rle with old method : 0.018511056900024414 length of segment : 212 time for calcul the mask position with numpy : 0.0073091983795166016 nb_pixel_total : 111342 time to create 1 rle with old method : 0.12184858322143555 length of segment : 711 time for calcul the mask position with numpy : 0.0038263797760009766 nb_pixel_total : 67174 time to create 1 rle with old method : 0.07558608055114746 length of segment : 300 time for calcul the mask position with numpy : 0.004575014114379883 nb_pixel_total : 24877 time to create 1 rle with old method : 0.028511762619018555 length of segment : 418 time for calcul the mask position with numpy : 0.0041027069091796875 nb_pixel_total : 33120 time to create 1 rle with old method : 0.05413246154785156 length of segment : 333 time for calcul the mask position with numpy : 0.0006108283996582031 nb_pixel_total : 9958 time to create 1 rle with old method : 0.011447668075561523 length of segment : 150 time for calcul the mask position with numpy : 0.0019652843475341797 nb_pixel_total : 28584 time to create 1 rle with old method : 0.03241157531738281 length of segment : 176 time for calcul the mask position with numpy : 0.0006928443908691406 nb_pixel_total : 3540 time to create 1 rle with old method : 0.0045452117919921875 length of segment : 189 time for calcul the mask position with numpy : 0.0019021034240722656 nb_pixel_total : 27567 time to create 1 rle with old method : 0.031504154205322266 length of segment : 246 time for calcul the mask position with numpy : 0.0008723735809326172 nb_pixel_total : 14475 time to create 1 rle with old method : 0.016700267791748047 length of segment : 175 time for calcul the mask position with numpy : 0.0011031627655029297 nb_pixel_total : 19487 time to create 1 rle with old method : 0.031708717346191406 length of segment : 148 time for calcul the mask position with numpy : 0.002100706100463867 nb_pixel_total : 29726 time to create 1 rle with old method : 0.03555631637573242 length of segment : 582 time for calcul the mask position with numpy : 0.001444101333618164 nb_pixel_total : 14994 time to create 1 rle with old method : 0.02243494987487793 length of segment : 119 time for calcul the mask position with numpy : 0.0012903213500976562 nb_pixel_total : 15062 time to create 1 rle with old method : 0.018106460571289062 length of segment : 128 time for calcul the mask position with numpy : 0.0017228126525878906 nb_pixel_total : 32812 time to create 1 rle with old method : 0.038021087646484375 length of segment : 219 time for calcul the mask position with numpy : 0.002003908157348633 nb_pixel_total : 22494 time to create 1 rle with old method : 0.024680614471435547 length of segment : 292 time for calcul the mask position with numpy : 0.0007255077362060547 nb_pixel_total : 10053 time to create 1 rle with old method : 0.011563301086425781 length of segment : 158 time for calcul the mask position with numpy : 0.005999088287353516 nb_pixel_total : 92312 time to create 1 rle with old method : 0.1040494441986084 length of segment : 328 time for calcul the mask position with numpy : 0.0009415149688720703 nb_pixel_total : 22425 time to create 1 rle with old method : 0.025302410125732422 length of segment : 199 time for calcul the mask position with numpy : 0.0010759830474853516 nb_pixel_total : 15621 time to create 1 rle with old method : 0.018436431884765625 length of segment : 142 time for calcul the mask position with numpy : 0.004601716995239258 nb_pixel_total : 68539 time to create 1 rle with old method : 0.07927227020263672 length of segment : 643 time for calcul the mask position with numpy : 0.0006794929504394531 nb_pixel_total : 14134 time to create 1 rle with old method : 0.0160825252532959 length of segment : 161 time for calcul the mask position with numpy : 0.008207559585571289 nb_pixel_total : 91064 time to create 1 rle with old method : 0.10215520858764648 length of segment : 679 time for calcul the mask position with numpy : 0.0008287429809570312 nb_pixel_total : 8536 time to create 1 rle with old method : 0.01419210433959961 length of segment : 79 time for calcul the mask position with numpy : 0.003290891647338867 nb_pixel_total : 22027 time to create 1 rle with old method : 0.031490325927734375 length of segment : 478 time for calcul the mask position with numpy : 0.0033969879150390625 nb_pixel_total : 44484 time to create 1 rle with old method : 0.049652099609375 length of segment : 312 time for calcul the mask position with numpy : 0.0016536712646484375 nb_pixel_total : 18153 time to create 1 rle with old method : 0.0213470458984375 length of segment : 395 time for calcul the mask position with numpy : 0.0002961158752441406 nb_pixel_total : 10615 time to create 1 rle with old method : 0.01197671890258789 length of segment : 116 time for calcul the mask position with numpy : 0.001218557357788086 nb_pixel_total : 21267 time to create 1 rle with old method : 0.024371623992919922 length of segment : 230 time for calcul the mask position with numpy : 0.0027475357055664062 nb_pixel_total : 43485 time to create 1 rle with old method : 0.04922604560852051 length of segment : 204 time for calcul the mask position with numpy : 0.0007889270782470703 nb_pixel_total : 12081 time to create 1 rle with old method : 0.014083147048950195 length of segment : 102 time for calcul the mask position with numpy : 0.0023746490478515625 nb_pixel_total : 31784 time to create 1 rle with old method : 0.03407883644104004 length of segment : 211 time for calcul the mask position with numpy : 0.0014734268188476562 nb_pixel_total : 25760 time to create 1 rle with old method : 0.028029441833496094 length of segment : 213 time for calcul the mask position with numpy : 0.0009038448333740234 nb_pixel_total : 16087 time to create 1 rle with old method : 0.01856374740600586 length of segment : 133 time for calcul the mask position with numpy : 0.0013580322265625 nb_pixel_total : 18585 time to create 1 rle with old method : 0.021100759506225586 length of segment : 178 time for calcul the mask position with numpy : 0.0011446475982666016 nb_pixel_total : 18204 time to create 1 rle with old method : 0.020583152770996094 length of segment : 267 time for calcul the mask position with numpy : 0.0012958049774169922 nb_pixel_total : 23938 time to create 1 rle with old method : 0.026249170303344727 length of segment : 238 time for calcul the mask position with numpy : 0.002057313919067383 nb_pixel_total : 32854 time to create 1 rle with old method : 0.03698992729187012 length of segment : 219 time for calcul the mask position with numpy : 0.0012946128845214844 nb_pixel_total : 29002 time to create 1 rle with old method : 0.046587467193603516 length of segment : 185 time for calcul the mask position with numpy : 0.0005435943603515625 nb_pixel_total : 18582 time to create 1 rle with old method : 0.023398399353027344 length of segment : 219 time for calcul the mask position with numpy : 0.00031638145446777344 nb_pixel_total : 7814 time to create 1 rle with old method : 0.009139537811279297 length of segment : 125 time for calcul the mask position with numpy : 0.0015246868133544922 nb_pixel_total : 60078 time to create 1 rle with old method : 0.06612420082092285 length of segment : 265 time for calcul the mask position with numpy : 0.0034666061401367188 nb_pixel_total : 56528 time to create 1 rle with old method : 0.06393861770629883 length of segment : 229 time for calcul the mask position with numpy : 0.0009696483612060547 nb_pixel_total : 10959 time to create 1 rle with old method : 0.01272726058959961 length of segment : 216 time for calcul the mask position with numpy : 0.0018181800842285156 nb_pixel_total : 25822 time to create 1 rle with old method : 0.028844833374023438 length of segment : 190 time for calcul the mask position with numpy : 0.002012491226196289 nb_pixel_total : 18298 time to create 1 rle with old method : 0.020958900451660156 length of segment : 219 time for calcul the mask position with numpy : 0.0013666152954101562 nb_pixel_total : 12233 time to create 1 rle with old method : 0.014325618743896484 length of segment : 166 time for calcul the mask position with numpy : 0.0028989315032958984 nb_pixel_total : 34358 time to create 1 rle with old method : 0.038387298583984375 length of segment : 192 time for calcul the mask position with numpy : 0.0023298263549804688 nb_pixel_total : 20846 time to create 1 rle with old method : 0.03442692756652832 length of segment : 320 time for calcul the mask position with numpy : 0.0010156631469726562 nb_pixel_total : 9976 time to create 1 rle with old method : 0.01674675941467285 length of segment : 262 time for calcul the mask position with numpy : 0.001987457275390625 nb_pixel_total : 27026 time to create 1 rle with old method : 0.03125905990600586 length of segment : 329 time for calcul the mask position with numpy : 0.00042510032653808594 nb_pixel_total : 5460 time to create 1 rle with old method : 0.0066378116607666016 length of segment : 56 time for calcul the mask position with numpy : 0.0010848045349121094 nb_pixel_total : 13791 time to create 1 rle with old method : 0.016041278839111328 length of segment : 306 time for calcul the mask position with numpy : 0.002051115036010742 nb_pixel_total : 25042 time to create 1 rle with old method : 0.028989553451538086 length of segment : 236 time for calcul the mask position with numpy : 0.0006566047668457031 nb_pixel_total : 10287 time to create 1 rle with old method : 0.012022256851196289 length of segment : 167 time for calcul the mask position with numpy : 0.00019168853759765625 nb_pixel_total : 5144 time to create 1 rle with old method : 0.006182193756103516 length of segment : 74 time for calcul the mask position with numpy : 0.002604246139526367 nb_pixel_total : 38597 time to create 1 rle with old method : 0.04528617858886719 length of segment : 343 time for calcul the mask position with numpy : 0.0005261898040771484 nb_pixel_total : 6964 time to create 1 rle with old method : 0.00816202163696289 length of segment : 96 time for calcul the mask position with numpy : 0.0011706352233886719 nb_pixel_total : 11871 time to create 1 rle with old method : 0.013997793197631836 length of segment : 136 time for calcul the mask position with numpy : 0.007063150405883789 nb_pixel_total : 69950 time to create 1 rle with old method : 0.07839345932006836 length of segment : 391 time for calcul the mask position with numpy : 0.0014531612396240234 nb_pixel_total : 20240 time to create 1 rle with old method : 0.023337364196777344 length of segment : 156 time for calcul the mask position with numpy : 0.010080575942993164 nb_pixel_total : 92846 time to create 1 rle with old method : 0.10212111473083496 length of segment : 367 time for calcul the mask position with numpy : 0.002260923385620117 nb_pixel_total : 23279 time to create 1 rle with old method : 0.02544569969177246 length of segment : 255 time for calcul the mask position with numpy : 0.004504203796386719 nb_pixel_total : 58962 time to create 1 rle with old method : 0.0635221004486084 length of segment : 331 time for calcul the mask position with numpy : 0.0011773109436035156 nb_pixel_total : 17096 time to create 1 rle with old method : 0.018500804901123047 length of segment : 163 time for calcul the mask position with numpy : 0.0004620552062988281 nb_pixel_total : 10885 time to create 1 rle with old method : 0.01238250732421875 length of segment : 141 time for calcul the mask position with numpy : 0.0005152225494384766 nb_pixel_total : 5281 time to create 1 rle with old method : 0.006146430969238281 length of segment : 105 time for calcul the mask position with numpy : 0.0018157958984375 nb_pixel_total : 18800 time to create 1 rle with old method : 0.02241349220275879 length of segment : 102 time for calcul the mask position with numpy : 0.0011076927185058594 nb_pixel_total : 17642 time to create 1 rle with old method : 0.020302772521972656 length of segment : 189 time for calcul the mask position with numpy : 0.0013082027435302734 nb_pixel_total : 18319 time to create 1 rle with old method : 0.02086663246154785 length of segment : 208 time for calcul the mask position with numpy : 0.001096487045288086 nb_pixel_total : 12863 time to create 1 rle with old method : 0.016797780990600586 length of segment : 112 time for calcul the mask position with numpy : 0.00305938720703125 nb_pixel_total : 24549 time to create 1 rle with old method : 0.04202890396118164 length of segment : 223 time for calcul the mask position with numpy : 0.0009963512420654297 nb_pixel_total : 11175 time to create 1 rle with old method : 0.013126134872436523 length of segment : 147 time for calcul the mask position with numpy : 0.0017375946044921875 nb_pixel_total : 19945 time to create 1 rle with old method : 0.02354264259338379 length of segment : 168 time for calcul the mask position with numpy : 0.004523277282714844 nb_pixel_total : 51340 time to create 1 rle with old method : 0.05910468101501465 length of segment : 432 time for calcul the mask position with numpy : 0.0013322830200195312 nb_pixel_total : 11157 time to create 1 rle with old method : 0.012667417526245117 length of segment : 178 time for calcul the mask position with numpy : 0.0061647891998291016 nb_pixel_total : 89960 time to create 1 rle with old method : 0.10193967819213867 length of segment : 459 time for calcul the mask position with numpy : 0.003185272216796875 nb_pixel_total : 53324 time to create 1 rle with old method : 0.05972743034362793 length of segment : 382 time for calcul the mask position with numpy : 0.0001590251922607422 nb_pixel_total : 1936 time to create 1 rle with old method : 0.0022215843200683594 length of segment : 48 time for calcul the mask position with numpy : 0.009247303009033203 nb_pixel_total : 121067 time to create 1 rle with old method : 0.13625454902648926 length of segment : 725 time for calcul the mask position with numpy : 0.0020051002502441406 nb_pixel_total : 38423 time to create 1 rle with old method : 0.04347848892211914 length of segment : 223 time for calcul the mask position with numpy : 0.001405477523803711 nb_pixel_total : 19412 time to create 1 rle with old method : 0.02154064178466797 length of segment : 185 time for calcul the mask position with numpy : 0.0027768611907958984 nb_pixel_total : 24972 time to create 1 rle with old method : 0.02689647674560547 length of segment : 225 time for calcul the mask position with numpy : 0.0008053779602050781 nb_pixel_total : 10862 time to create 1 rle with old method : 0.011777877807617188 length of segment : 112 time for calcul the mask position with numpy : 0.0009706020355224609 nb_pixel_total : 13260 time to create 1 rle with old method : 0.014657974243164062 length of segment : 122 time for calcul the mask position with numpy : 0.0008060932159423828 nb_pixel_total : 22319 time to create 1 rle with old method : 0.024912118911743164 length of segment : 182 time for calcul the mask position with numpy : 0.013613224029541016 nb_pixel_total : 176688 time to create 1 rle with new method : 0.018908977508544922 length of segment : 625 time for calcul the mask position with numpy : 0.0008399486541748047 nb_pixel_total : 12038 time to create 1 rle with old method : 0.014352560043334961 length of segment : 94 time for calcul the mask position with numpy : 0.0003209114074707031 nb_pixel_total : 2759 time to create 1 rle with old method : 0.0033431053161621094 length of segment : 60 time for calcul the mask position with numpy : 0.0012319087982177734 nb_pixel_total : 12425 time to create 1 rle with old method : 0.014364242553710938 length of segment : 145 time for calcul the mask position with numpy : 0.0007274150848388672 nb_pixel_total : 8012 time to create 1 rle with old method : 0.009173393249511719 length of segment : 94 time for calcul the mask position with numpy : 0.0005180835723876953 nb_pixel_total : 8680 time to create 1 rle with old method : 0.010040760040283203 length of segment : 153 time for calcul the mask position with numpy : 0.002540111541748047 nb_pixel_total : 25978 time to create 1 rle with old method : 0.029412269592285156 length of segment : 284 time for calcul the mask position with numpy : 0.007416248321533203 nb_pixel_total : 137378 time to create 1 rle with old method : 0.14921975135803223 length of segment : 625 time for calcul the mask position with numpy : 0.0007381439208984375 nb_pixel_total : 9850 time to create 1 rle with old method : 0.011156320571899414 length of segment : 102 time for calcul the mask position with numpy : 0.001577615737915039 nb_pixel_total : 17653 time to create 1 rle with old method : 0.019518613815307617 length of segment : 174 time for calcul the mask position with numpy : 0.0014476776123046875 nb_pixel_total : 27185 time to create 1 rle with old method : 0.029039621353149414 length of segment : 170 time for calcul the mask position with numpy : 0.0050318241119384766 nb_pixel_total : 76992 time to create 1 rle with old method : 0.0861964225769043 length of segment : 278 time for calcul the mask position with numpy : 0.0015799999237060547 nb_pixel_total : 22532 time to create 1 rle with old method : 0.027270793914794922 length of segment : 210 time for calcul the mask position with numpy : 0.0003414154052734375 nb_pixel_total : 7242 time to create 1 rle with old method : 0.008504629135131836 length of segment : 79 time for calcul the mask position with numpy : 0.0009427070617675781 nb_pixel_total : 12928 time to create 1 rle with old method : 0.015330076217651367 length of segment : 135 time for calcul the mask position with numpy : 0.0010151863098144531 nb_pixel_total : 11079 time to create 1 rle with old method : 0.018532991409301758 length of segment : 168 time for calcul the mask position with numpy : 0.001985788345336914 nb_pixel_total : 27219 time to create 1 rle with old method : 0.031493425369262695 length of segment : 215 time for calcul the mask position with numpy : 0.0012624263763427734 nb_pixel_total : 13194 time to create 1 rle with old method : 0.021829843521118164 length of segment : 191 time for calcul the mask position with numpy : 0.001010894775390625 nb_pixel_total : 17385 time to create 1 rle with old method : 0.02014780044555664 length of segment : 157 time for calcul the mask position with numpy : 0.00491023063659668 nb_pixel_total : 56714 time to create 1 rle with old method : 0.07470107078552246 length of segment : 209 time for calcul the mask position with numpy : 0.0011096000671386719 nb_pixel_total : 18576 time to create 1 rle with old method : 0.021976232528686523 length of segment : 161 time for calcul the mask position with numpy : 0.0004372596740722656 nb_pixel_total : 5895 time to create 1 rle with old method : 0.00703883171081543 length of segment : 81 time for calcul the mask position with numpy : 0.0005676746368408203 nb_pixel_total : 7696 time to create 1 rle with old method : 0.008831262588500977 length of segment : 110 time for calcul the mask position with numpy : 0.00014829635620117188 nb_pixel_total : 3226 time to create 1 rle with old method : 0.003932952880859375 length of segment : 97 time for calcul the mask position with numpy : 0.0015497207641601562 nb_pixel_total : 22585 time to create 1 rle with old method : 0.025246143341064453 length of segment : 241 time for calcul the mask position with numpy : 0.0008714199066162109 nb_pixel_total : 15764 time to create 1 rle with old method : 0.01793384552001953 length of segment : 135 time for calcul the mask position with numpy : 0.0009968280792236328 nb_pixel_total : 17769 time to create 1 rle with old method : 0.02021479606628418 length of segment : 186 time for calcul the mask position with numpy : 0.0019683837890625 nb_pixel_total : 27248 time to create 1 rle with old method : 0.034253597259521484 length of segment : 199 time for calcul the mask position with numpy : 0.00036716461181640625 nb_pixel_total : 9082 time to create 1 rle with old method : 0.010487556457519531 length of segment : 104 time for calcul the mask position with numpy : 0.00048804283142089844 nb_pixel_total : 9510 time to create 1 rle with old method : 0.011278629302978516 length of segment : 133 time for calcul the mask position with numpy : 0.0054721832275390625 nb_pixel_total : 90063 time to create 1 rle with old method : 0.12546300888061523 length of segment : 437 time for calcul the mask position with numpy : 0.0003829002380371094 nb_pixel_total : 7333 time to create 1 rle with old method : 0.008388996124267578 length of segment : 129 time for calcul the mask position with numpy : 0.0007622241973876953 nb_pixel_total : 15873 time to create 1 rle with old method : 0.01769089698791504 length of segment : 143 time for calcul the mask position with numpy : 0.0009822845458984375 nb_pixel_total : 14002 time to create 1 rle with old method : 0.015106678009033203 length of segment : 200 time for calcul the mask position with numpy : 0.001413106918334961 nb_pixel_total : 25389 time to create 1 rle with old method : 0.029982805252075195 length of segment : 148 time for calcul the mask position with numpy : 0.0031621456146240234 nb_pixel_total : 42229 time to create 1 rle with old method : 0.05166459083557129 length of segment : 399 time for calcul the mask position with numpy : 0.0007536411285400391 nb_pixel_total : 8713 time to create 1 rle with old method : 0.010388851165771484 length of segment : 109 time for calcul the mask position with numpy : 0.017641067504882812 nb_pixel_total : 261327 time to create 1 rle with new method : 0.0202944278717041 length of segment : 661 time for calcul the mask position with numpy : 0.002248525619506836 nb_pixel_total : 44817 time to create 1 rle with old method : 0.05289292335510254 length of segment : 213 time for calcul the mask position with numpy : 0.0014681816101074219 nb_pixel_total : 16238 time to create 1 rle with old method : 0.019730567932128906 length of segment : 236 time for calcul the mask position with numpy : 0.0015206336975097656 nb_pixel_total : 19936 time to create 1 rle with old method : 0.02466130256652832 length of segment : 217 time for calcul the mask position with numpy : 0.00432276725769043 nb_pixel_total : 71307 time to create 1 rle with old method : 0.08245325088500977 length of segment : 460 time for calcul the mask position with numpy : 0.0015001296997070312 nb_pixel_total : 25768 time to create 1 rle with old method : 0.029290199279785156 length of segment : 251 time for calcul the mask position with numpy : 0.00159454345703125 nb_pixel_total : 24566 time to create 1 rle with old method : 0.028097152709960938 length of segment : 216 time for calcul the mask position with numpy : 0.0015451908111572266 nb_pixel_total : 22916 time to create 1 rle with old method : 0.02606368064880371 length of segment : 351 time for calcul the mask position with numpy : 0.0008516311645507812 nb_pixel_total : 17273 time to create 1 rle with old method : 0.019795656204223633 length of segment : 141 time for calcul the mask position with numpy : 0.0006210803985595703 nb_pixel_total : 9634 time to create 1 rle with old method : 0.010869979858398438 length of segment : 148 time for calcul the mask position with numpy : 0.001611471176147461 nb_pixel_total : 26702 time to create 1 rle with old method : 0.03443288803100586 length of segment : 184 time for calcul the mask position with numpy : 0.0035660266876220703 nb_pixel_total : 60013 time to create 1 rle with old method : 0.06970024108886719 length of segment : 352 time for calcul the mask position with numpy : 0.0009551048278808594 nb_pixel_total : 18169 time to create 1 rle with old method : 0.021298885345458984 length of segment : 178 time for calcul the mask position with numpy : 0.0015676021575927734 nb_pixel_total : 22490 time to create 1 rle with old method : 0.025833845138549805 length of segment : 290 time for calcul the mask position with numpy : 0.0007700920104980469 nb_pixel_total : 12904 time to create 1 rle with old method : 0.015044450759887695 length of segment : 159 time for calcul the mask position with numpy : 0.001207113265991211 nb_pixel_total : 17847 time to create 1 rle with old method : 0.022443056106567383 length of segment : 148 time for calcul the mask position with numpy : 0.0017549991607666016 nb_pixel_total : 27431 time to create 1 rle with old method : 0.033149003982543945 length of segment : 169 time for calcul the mask position with numpy : 0.001104116439819336 nb_pixel_total : 18543 time to create 1 rle with old method : 0.021164655685424805 length of segment : 155 time for calcul the mask position with numpy : 0.00164794921875 nb_pixel_total : 22464 time to create 1 rle with old method : 0.02604389190673828 length of segment : 254 time for calcul the mask position with numpy : 0.0012271404266357422 nb_pixel_total : 27799 time to create 1 rle with old method : 0.030780792236328125 length of segment : 183 time for calcul the mask position with numpy : 0.0004067420959472656 nb_pixel_total : 5453 time to create 1 rle with old method : 0.006496429443359375 length of segment : 85 time for calcul the mask position with numpy : 0.0013537406921386719 nb_pixel_total : 22206 time to create 1 rle with old method : 0.025586366653442383 length of segment : 234 time for calcul the mask position with numpy : 0.0020570755004882812 nb_pixel_total : 34603 time to create 1 rle with old method : 0.03934168815612793 length of segment : 437 time for calcul the mask position with numpy : 0.0008158683776855469 nb_pixel_total : 16584 time to create 1 rle with old method : 0.019353866577148438 length of segment : 142 time for calcul the mask position with numpy : 0.0007832050323486328 nb_pixel_total : 11591 time to create 1 rle with old method : 0.01343536376953125 length of segment : 129 time for calcul the mask position with numpy : 0.0028285980224609375 nb_pixel_total : 36238 time to create 1 rle with old method : 0.04137992858886719 length of segment : 285 time for calcul the mask position with numpy : 0.001203775405883789 nb_pixel_total : 18105 time to create 1 rle with old method : 0.021232128143310547 length of segment : 190 time for calcul the mask position with numpy : 0.0005824565887451172 nb_pixel_total : 8670 time to create 1 rle with old method : 0.010271787643432617 length of segment : 105 time for calcul the mask position with numpy : 0.00469517707824707 nb_pixel_total : 93324 time to create 1 rle with old method : 0.11267495155334473 length of segment : 363 time for calcul the mask position with numpy : 0.0010979175567626953 nb_pixel_total : 15938 time to create 1 rle with old method : 0.019056320190429688 length of segment : 149 time for calcul the mask position with numpy : 0.0023255348205566406 nb_pixel_total : 25615 time to create 1 rle with old method : 0.034587860107421875 length of segment : 172 time for calcul the mask position with numpy : 0.0015604496002197266 nb_pixel_total : 31410 time to create 1 rle with old method : 0.03500199317932129 length of segment : 188 time for calcul the mask position with numpy : 0.0060062408447265625 nb_pixel_total : 70711 time to create 1 rle with old method : 0.08020353317260742 length of segment : 360 time for calcul the mask position with numpy : 0.0009357929229736328 nb_pixel_total : 18444 time to create 1 rle with old method : 0.02028036117553711 length of segment : 207 time for calcul the mask position with numpy : 0.0017066001892089844 nb_pixel_total : 33776 time to create 1 rle with old method : 0.03878593444824219 length of segment : 315 time for calcul the mask position with numpy : 0.0012433528900146484 nb_pixel_total : 19812 time to create 1 rle with old method : 0.022475481033325195 length of segment : 145 time for calcul the mask position with numpy : 0.0006082057952880859 nb_pixel_total : 6206 time to create 1 rle with old method : 0.007474184036254883 length of segment : 189 time for calcul the mask position with numpy : 0.0005269050598144531 nb_pixel_total : 9490 time to create 1 rle with old method : 0.010790348052978516 length of segment : 131 time for calcul the mask position with numpy : 0.0002799034118652344 nb_pixel_total : 6368 time to create 1 rle with old method : 0.007407665252685547 length of segment : 107 time for calcul the mask position with numpy : 0.002295970916748047 nb_pixel_total : 26223 time to create 1 rle with old method : 0.04260849952697754 length of segment : 286 time for calcul the mask position with numpy : 0.0004813671112060547 nb_pixel_total : 8196 time to create 1 rle with old method : 0.009390592575073242 length of segment : 101 time for calcul the mask position with numpy : 0.0008127689361572266 nb_pixel_total : 12571 time to create 1 rle with old method : 0.015235662460327148 length of segment : 104 time for calcul the mask position with numpy : 0.0003724098205566406 nb_pixel_total : 6552 time to create 1 rle with old method : 0.010249137878417969 length of segment : 90 time for calcul the mask position with numpy : 0.003751516342163086 nb_pixel_total : 32256 time to create 1 rle with old method : 0.037404537200927734 length of segment : 334 time for calcul the mask position with numpy : 0.0042095184326171875 nb_pixel_total : 99087 time to create 1 rle with old method : 0.1122283935546875 length of segment : 406 time for calcul the mask position with numpy : 0.0003142356872558594 nb_pixel_total : 5967 time to create 1 rle with old method : 0.007109642028808594 length of segment : 119 time for calcul the mask position with numpy : 0.0012242794036865234 nb_pixel_total : 20685 time to create 1 rle with old method : 0.024337291717529297 length of segment : 155 time for calcul the mask position with numpy : 0.002583026885986328 nb_pixel_total : 37274 time to create 1 rle with old method : 0.05124378204345703 length of segment : 243 time for calcul the mask position with numpy : 0.0008003711700439453 nb_pixel_total : 14965 time to create 1 rle with old method : 0.017609357833862305 length of segment : 112 time for calcul the mask position with numpy : 0.003155946731567383 nb_pixel_total : 52127 time to create 1 rle with old method : 0.05872988700866699 length of segment : 404 time for calcul the mask position with numpy : 0.0010302066802978516 nb_pixel_total : 26117 time to create 1 rle with old method : 0.029547929763793945 length of segment : 216 time for calcul the mask position with numpy : 0.0009572505950927734 nb_pixel_total : 16862 time to create 1 rle with old method : 0.019724607467651367 length of segment : 197 time for calcul the mask position with numpy : 8.869171142578125e-05 nb_pixel_total : 1725 time to create 1 rle with old method : 0.0021772384643554688 length of segment : 60 time for calcul the mask position with numpy : 0.0007886886596679688 nb_pixel_total : 24694 time to create 1 rle with old method : 0.027452945709228516 length of segment : 279 time for calcul the mask position with numpy : 0.0011050701141357422 nb_pixel_total : 35894 time to create 1 rle with old method : 0.04128694534301758 length of segment : 265 time for calcul the mask position with numpy : 0.0007834434509277344 nb_pixel_total : 10004 time to create 1 rle with old method : 0.012578010559082031 length of segment : 131 time for calcul the mask position with numpy : 0.0007874965667724609 nb_pixel_total : 10148 time to create 1 rle with old method : 0.011925220489501953 length of segment : 149 time for calcul the mask position with numpy : 0.005997657775878906 nb_pixel_total : 92411 time to create 1 rle with old method : 0.12123870849609375 length of segment : 271 time for calcul the mask position with numpy : 0.0004074573516845703 nb_pixel_total : 4348 time to create 1 rle with old method : 0.007359504699707031 length of segment : 93 time for calcul the mask position with numpy : 0.002271413803100586 nb_pixel_total : 22818 time to create 1 rle with old method : 0.036400556564331055 length of segment : 209 time for calcul the mask position with numpy : 0.002008676528930664 nb_pixel_total : 27046 time to create 1 rle with old method : 0.034549713134765625 length of segment : 228 time for calcul the mask position with numpy : 0.0015578269958496094 nb_pixel_total : 21269 time to create 1 rle with old method : 0.026210546493530273 length of segment : 169 time for calcul the mask position with numpy : 0.0006401538848876953 nb_pixel_total : 12384 time to create 1 rle with old method : 0.014982938766479492 length of segment : 95 time for calcul the mask position with numpy : 0.009736776351928711 nb_pixel_total : 128125 time to create 1 rle with old method : 0.14915156364440918 length of segment : 702 time for calcul the mask position with numpy : 0.0006797313690185547 nb_pixel_total : 10754 time to create 1 rle with old method : 0.012798547744750977 length of segment : 135 time for calcul the mask position with numpy : 0.002009153366088867 nb_pixel_total : 35535 time to create 1 rle with old method : 0.040520429611206055 length of segment : 261 time for calcul the mask position with numpy : 0.004210948944091797 nb_pixel_total : 56053 time to create 1 rle with old method : 0.06360197067260742 length of segment : 416 time for calcul the mask position with numpy : 0.004715442657470703 nb_pixel_total : 66707 time to create 1 rle with old method : 0.07893252372741699 length of segment : 284 time for calcul the mask position with numpy : 0.0009329319000244141 nb_pixel_total : 14428 time to create 1 rle with old method : 0.01684880256652832 length of segment : 139 time for calcul the mask position with numpy : 0.0008108615875244141 nb_pixel_total : 10859 time to create 1 rle with old method : 0.012867450714111328 length of segment : 144 time for calcul the mask position with numpy : 0.003242015838623047 nb_pixel_total : 57281 time to create 1 rle with old method : 0.06725835800170898 length of segment : 272 time for calcul the mask position with numpy : 0.002292633056640625 nb_pixel_total : 37302 time to create 1 rle with old method : 0.04277682304382324 length of segment : 196 time for calcul the mask position with numpy : 0.0004649162292480469 nb_pixel_total : 6843 time to create 1 rle with old method : 0.00824117660522461 length of segment : 72 time for calcul the mask position with numpy : 0.0012972354888916016 nb_pixel_total : 24713 time to create 1 rle with old method : 0.028702259063720703 length of segment : 201 time for calcul the mask position with numpy : 0.0013375282287597656 nb_pixel_total : 16126 time to create 1 rle with old method : 0.01894664764404297 length of segment : 152 time for calcul the mask position with numpy : 0.010431766510009766 nb_pixel_total : 127230 time to create 1 rle with old method : 0.15147876739501953 length of segment : 560 time for calcul the mask position with numpy : 0.0005605220794677734 nb_pixel_total : 15619 time to create 1 rle with old method : 0.018386363983154297 length of segment : 186 time for calcul the mask position with numpy : 0.002776622772216797 nb_pixel_total : 43326 time to create 1 rle with old method : 0.05118060111999512 length of segment : 240 time for calcul the mask position with numpy : 0.0021848678588867188 nb_pixel_total : 18307 time to create 1 rle with old method : 0.02831864356994629 length of segment : 257 time for calcul the mask position with numpy : 0.0016219615936279297 nb_pixel_total : 25158 time to create 1 rle with old method : 0.02918553352355957 length of segment : 283 time for calcul the mask position with numpy : 0.0025780200958251953 nb_pixel_total : 65084 time to create 1 rle with old method : 0.07557225227355957 length of segment : 396 time for calcul the mask position with numpy : 0.0006544589996337891 nb_pixel_total : 7068 time to create 1 rle with old method : 0.017846345901489258 length of segment : 115 time for calcul the mask position with numpy : 0.00035691261291503906 nb_pixel_total : 13798 time to create 1 rle with old method : 0.019568443298339844 length of segment : 137 time for calcul the mask position with numpy : 0.0002942085266113281 nb_pixel_total : 7416 time to create 1 rle with old method : 0.010370016098022461 length of segment : 83 time for calcul the mask position with numpy : 0.0019114017486572266 nb_pixel_total : 37210 time to create 1 rle with old method : 0.08243465423583984 length of segment : 245 time for calcul the mask position with numpy : 0.011848688125610352 nb_pixel_total : 118622 time to create 1 rle with old method : 0.21330738067626953 length of segment : 509 time for calcul the mask position with numpy : 0.0010347366333007812 nb_pixel_total : 19608 time to create 1 rle with old method : 0.024819135665893555 length of segment : 157 time for calcul the mask position with numpy : 0.0009450912475585938 nb_pixel_total : 14115 time to create 1 rle with old method : 0.017343521118164062 length of segment : 129 time for calcul the mask position with numpy : 0.001004934310913086 nb_pixel_total : 14327 time to create 1 rle with old method : 0.017161130905151367 length of segment : 155 time for calcul the mask position with numpy : 0.0016484260559082031 nb_pixel_total : 16123 time to create 1 rle with old method : 0.019429445266723633 length of segment : 150 time for calcul the mask position with numpy : 0.008682727813720703 nb_pixel_total : 147634 time to create 1 rle with old method : 0.17230796813964844 length of segment : 755 time for calcul the mask position with numpy : 0.0015685558319091797 nb_pixel_total : 18650 time to create 1 rle with old method : 0.021601438522338867 length of segment : 194 time for calcul the mask position with numpy : 0.0013148784637451172 nb_pixel_total : 20625 time to create 1 rle with old method : 0.026025056838989258 length of segment : 159 time for calcul the mask position with numpy : 0.00455164909362793 nb_pixel_total : 78483 time to create 1 rle with old method : 0.0987389087677002 length of segment : 217 time for calcul the mask position with numpy : 0.0011394023895263672 nb_pixel_total : 17621 time to create 1 rle with old method : 0.02099776268005371 length of segment : 233 time for calcul the mask position with numpy : 0.0010466575622558594 nb_pixel_total : 16407 time to create 1 rle with old method : 0.01962447166442871 length of segment : 91 time for calcul the mask position with numpy : 0.0009171962738037109 nb_pixel_total : 17559 time to create 1 rle with old method : 0.020628929138183594 length of segment : 123 time for calcul the mask position with numpy : 0.0008947849273681641 nb_pixel_total : 15749 time to create 1 rle with old method : 0.020282506942749023 length of segment : 176 time for calcul the mask position with numpy : 0.0011851787567138672 nb_pixel_total : 19330 time to create 1 rle with old method : 0.022264480590820312 length of segment : 146 time for calcul the mask position with numpy : 0.0009465217590332031 nb_pixel_total : 18144 time to create 1 rle with old method : 0.025708675384521484 length of segment : 138 time for calcul the mask position with numpy : 0.0007319450378417969 nb_pixel_total : 26463 time to create 1 rle with old method : 0.0327911376953125 length of segment : 184 time for calcul the mask position with numpy : 0.0004911422729492188 nb_pixel_total : 16275 time to create 1 rle with old method : 0.020406246185302734 length of segment : 208 time for calcul the mask position with numpy : 0.0016317367553710938 nb_pixel_total : 23356 time to create 1 rle with old method : 0.028490304946899414 length of segment : 233 time for calcul the mask position with numpy : 0.0010738372802734375 nb_pixel_total : 24066 time to create 1 rle with old method : 0.0281522274017334 length of segment : 148 time for calcul the mask position with numpy : 0.0024216175079345703 nb_pixel_total : 35067 time to create 1 rle with old method : 0.04120469093322754 length of segment : 192 time for calcul the mask position with numpy : 0.0020842552185058594 nb_pixel_total : 31874 time to create 1 rle with old method : 0.0370936393737793 length of segment : 163 time for calcul the mask position with numpy : 0.0013332366943359375 nb_pixel_total : 22914 time to create 1 rle with old method : 0.026246070861816406 length of segment : 213 time for calcul the mask position with numpy : 0.0024831295013427734 nb_pixel_total : 44979 time to create 1 rle with old method : 0.0513913631439209 length of segment : 366 time for calcul the mask position with numpy : 0.0006361007690429688 nb_pixel_total : 10928 time to create 1 rle with old method : 0.012943744659423828 length of segment : 123 time for calcul the mask position with numpy : 0.0026617050170898438 nb_pixel_total : 41003 time to create 1 rle with old method : 0.04667329788208008 length of segment : 294 time for calcul the mask position with numpy : 0.011819839477539062 nb_pixel_total : 184939 time to create 1 rle with new method : 0.02162337303161621 length of segment : 592 time for calcul the mask position with numpy : 0.001001596450805664 nb_pixel_total : 14555 time to create 1 rle with old method : 0.017050743103027344 length of segment : 142 time for calcul the mask position with numpy : 0.0011036396026611328 nb_pixel_total : 16921 time to create 1 rle with old method : 0.01953744888305664 length of segment : 230 time for calcul the mask position with numpy : 0.0022683143615722656 nb_pixel_total : 23713 time to create 1 rle with old method : 0.02753591537475586 length of segment : 418 time for calcul the mask position with numpy : 0.0025949478149414062 nb_pixel_total : 37119 time to create 1 rle with old method : 0.04246687889099121 length of segment : 268 time for calcul the mask position with numpy : 0.0010192394256591797 nb_pixel_total : 18883 time to create 1 rle with old method : 0.02193474769592285 length of segment : 168 time for calcul the mask position with numpy : 0.0010943412780761719 nb_pixel_total : 29590 time to create 1 rle with old method : 0.045684099197387695 length of segment : 189 time for calcul the mask position with numpy : 0.0007364749908447266 nb_pixel_total : 9151 time to create 1 rle with old method : 0.012346744537353516 length of segment : 117 time for calcul the mask position with numpy : 0.001013040542602539 nb_pixel_total : 16510 time to create 1 rle with old method : 0.018873214721679688 length of segment : 189 time for calcul the mask position with numpy : 0.0028066635131835938 nb_pixel_total : 45552 time to create 1 rle with old method : 0.05207681655883789 length of segment : 224 time for calcul the mask position with numpy : 0.0014083385467529297 nb_pixel_total : 23053 time to create 1 rle with old method : 0.027165889739990234 length of segment : 153 time for calcul the mask position with numpy : 0.0043222904205322266 nb_pixel_total : 59952 time to create 1 rle with old method : 0.0684654712677002 length of segment : 428 time for calcul the mask position with numpy : 0.0008924007415771484 nb_pixel_total : 11884 time to create 1 rle with old method : 0.014210700988769531 length of segment : 175 time for calcul the mask position with numpy : 0.0010690689086914062 nb_pixel_total : 14163 time to create 1 rle with old method : 0.01669788360595703 length of segment : 154 time for calcul the mask position with numpy : 0.0008897781372070312 nb_pixel_total : 15262 time to create 1 rle with old method : 0.020906925201416016 length of segment : 190 time for calcul the mask position with numpy : 0.006917476654052734 nb_pixel_total : 127793 time to create 1 rle with old method : 0.1434483528137207 length of segment : 744 time for calcul the mask position with numpy : 0.0023725032806396484 nb_pixel_total : 43946 time to create 1 rle with old method : 0.052109479904174805 length of segment : 300 time for calcul the mask position with numpy : 0.0009477138519287109 nb_pixel_total : 12032 time to create 1 rle with old method : 0.014191150665283203 length of segment : 134 time for calcul the mask position with numpy : 0.0009119510650634766 nb_pixel_total : 12934 time to create 1 rle with old method : 0.0148468017578125 length of segment : 191 time for calcul the mask position with numpy : 0.0006783008575439453 nb_pixel_total : 7970 time to create 1 rle with old method : 0.00935983657836914 length of segment : 141 time for calcul the mask position with numpy : 0.003897428512573242 nb_pixel_total : 47665 time to create 1 rle with old method : 0.054976463317871094 length of segment : 306 time for calcul the mask position with numpy : 0.0006544589996337891 nb_pixel_total : 17755 time to create 1 rle with old method : 0.020485401153564453 length of segment : 261 time for calcul the mask position with numpy : 0.0012731552124023438 nb_pixel_total : 30846 time to create 1 rle with old method : 0.03575468063354492 length of segment : 285 time for calcul the mask position with numpy : 0.004424095153808594 nb_pixel_total : 40433 time to create 1 rle with old method : 0.046721696853637695 length of segment : 369 time for calcul the mask position with numpy : 0.0009729862213134766 nb_pixel_total : 18324 time to create 1 rle with old method : 0.0217134952545166 length of segment : 162 time spent for convertir_results : 101.61206603050232 Inside saveOutput : final : False verbose : 0 eke 12-6-18 : saveMask need to be cleaned for new output ! Number saved : None batch 1 Loaded 928 chid ids of type : 3594 Number RLEs to save : 216272 save missing photos in datou_result : time spend for datou_step_exec : 477.5353412628174 time spend to save output : 15.597266674041748 total time spend for step 1 : 493.13260793685913 step2:crop_condition Wed Apr 9 10:48:48 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure Loading chi in step crop with photo_hashtag_type : 3594 Loading chi in step crop for list_pids : 25 ! batch 1 Loaded 928 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ begin to crop the class : papier param for this class : {'min_score': 0.7} filtre for class : papier hashtag_id of this class : 492668766 we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! 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we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! 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we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! map_result returned by crop_photo_return_map_crop : length : 737 About to insert : list_path_to_insert length 737 new photo from crops ! About to upload 737 photos upload in portfolio : 3736932 init cache_photo without model_param we have 737 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1744188655_526287 we have uploaded 737 photos in the portfolio 3736932 time of upload the photos Elapsed time : 234.5691273212433 we have finished the crop for the class : papier begin to crop the class : carton param for this class : {'min_score': 0.7} filtre for class : carton hashtag_id of this class : 492774966 we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! map_result returned by crop_photo_return_map_crop : length : 104 About to insert : list_path_to_insert length 104 new photo from crops ! About to upload 104 photos upload in portfolio : 3736932 init cache_photo without model_param we have 104 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1744188915_526287 we have uploaded 104 photos in the portfolio 3736932 time of upload the photos Elapsed time : 26.17016100883484 we have finished the crop for the class : carton begin to crop the class : metal param for this class : {'min_score': 0.7} filtre for class : metal hashtag_id of this class : 492628673 we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! map_result returned by crop_photo_return_map_crop : length : 8 About to insert : list_path_to_insert length 8 new photo from crops ! About to upload 8 photos upload in portfolio : 3736932 init cache_photo without model_param we have 8 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1744188946_526287 we have uploaded 8 photos in the portfolio 3736932 time of upload the photos Elapsed time : 2.3317298889160156 we have finished the crop for the class : metal begin to crop the class : pet_clair param for this class : {'min_score': 0.7} filtre for class : pet_clair hashtag_id of this class : 2107755846 we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! map_result returned by crop_photo_return_map_crop : length : 57 About to insert : list_path_to_insert length 57 new photo from crops ! About to upload 57 photos upload in portfolio : 3736932 init cache_photo without model_param we have 57 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1744188972_526287 we have uploaded 57 photos in the portfolio 3736932 time of upload the photos Elapsed time : 16.98612952232361 we have finished the crop for the class : pet_clair begin to crop the class : autre param for this class : {'min_score': 0.7} filtre for class : autre hashtag_id of this class : 494826614 we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! map_result returned by crop_photo_return_map_crop : length : 10 About to insert : list_path_to_insert length 10 new photo from crops ! About to upload 10 photos upload in portfolio : 3736932 init cache_photo without model_param we have 10 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1744188996_526287 we have uploaded 10 photos in the portfolio 3736932 time of upload the photos Elapsed time : 3.7686378955841064 we have finished the crop for the class : autre begin to crop the class : pehd param for this class : {'min_score': 0.7} filtre for class : pehd hashtag_id of this class : 628944319 we have both polygon and rles Next one ! we have both polygon and rles Next one ! map_result returned by crop_photo_return_map_crop : length : 2 About to insert : list_path_to_insert length 2 new photo from crops ! About to upload 2 photos upload in portfolio : 3736932 init cache_photo without model_param we have 2 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1744189006_526287 we have uploaded 2 photos in the portfolio 3736932 time of upload the photos Elapsed time : 1.0214629173278809 we have finished the crop for the class : pehd begin to crop the class : pet_fonce param for this class : {'min_score': 0.7} filtre for class : pet_fonce hashtag_id of this class : 2107755900 we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! map_result returned by crop_photo_return_map_crop : length : 10 About to insert : list_path_to_insert length 10 new photo from crops ! About to upload 10 photos upload in portfolio : 3736932 init cache_photo without model_param we have 10 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1744189013_526287 we have uploaded 10 photos in the portfolio 3736932 time of upload the photos Elapsed time : 2.0155508518218994 we have finished the crop for the class : pet_fonce delete rles from all chi we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : crop_condition we use saveGeneral [1350354385, 1350354381, 1350354376, 1350354266, 1350354238, 1350354210, 1350354154, 1350354109, 1350353822, 1350353790, 1350353758, 1350353647, 1350349657, 1350349467, 1350349447, 1350349396, 1350349356, 1350349053, 1350348979, 1350348961, 1350348647, 1350348639, 1350348634, 1350348627, 1350348620] Looping around the photos to save general results len do output : 928 /1350731041Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731042Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731043Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731045Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731046Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731047Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731048Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731049Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731050Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731051Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731052Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731053Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731054Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731055Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731056Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731057Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731059Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731060Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731061Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731062Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731065Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731066Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731067Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731068Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731069Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731070Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731071Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731072Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731073Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731074Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731075Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731076Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731077Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731078Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731079Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731080Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731081Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731082Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731083Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731084Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731085Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731086Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731087Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731088Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731089Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731090Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731091Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731092Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731093Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731094Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731095Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731096Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731097Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731098Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731099Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731100Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731101Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731102Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731103Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731104Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731105Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731106Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731107Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731108Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731109Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731110Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731111Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731112Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731113Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731114Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731115Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731116Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731117Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731118Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731119Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731120Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731121Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731122Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731123Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731124Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731125Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731126Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731127Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731128Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731130Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731131Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731132Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731133Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731134Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731136Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731137Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731138Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731139Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731140Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731141Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731142Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731143Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731144Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731145Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731146Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731147Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731148Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731149Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731150Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731151Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731152Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731153Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731154Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731155Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731156Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731157Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731158Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731159Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731160Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731161Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731162Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731163Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731164Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731165Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731167Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731168Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731169Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731170Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731171Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731172Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731173Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731174Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731175Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731176Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731177Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731178Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731179Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731180Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731181Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731182Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731183Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731184Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731185Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731186Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731187Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731188Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731189Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731190Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731191Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731192Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731193Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731194Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731195Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731196Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731197Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731198Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731199Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731201Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731202Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731203Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731204Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731205Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731206Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731207Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731208Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731209Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731210Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731211Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731213Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731214Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731215Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731216Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731217Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731218Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731219Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731220Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731221Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731222Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731223Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731224Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731225Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731226Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731227Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731228Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731229Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731230Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731231Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731233Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731234Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731235Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731237Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731238Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731239Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731241Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731242Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731243Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731245Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731246Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350731247Didn't retrieve data .Didn't retrieve 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retrieve data . /1350732402Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350732403Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350732404Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350732406Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350732407Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350732408Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350732410Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350732411Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350732412Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350732414Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350732416Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350732417Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350732418Didn't retrieve data .Didn't retrieve 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retrieve data .Didn't retrieve data .Didn't retrieve data . /1350732567Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350732569Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350732570Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350732571Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . before output type Here is an output not treated by saveGeneral : Here is an output not treated by saveGeneral : Here is an output not treated by saveGeneral : Managing all output in save final without adding information in the mtr_datou_result ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354385', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354381', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354376', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354266', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354238', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354210', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354154', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354109', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350353822', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350353790', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350353758', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350353647', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350349657', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350349467', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350349447', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350349396', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350349356', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350349053', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350348979', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350348961', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350348647', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350348639', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350348634', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350348627', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350348620', None, None, None, None, None, '2733670') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 2809 time used for this insertion : 4.303147315979004 save_final save missing photos in datou_result : time spend for datou_step_exec : 487.618524312973 time spend to save output : 4.493755578994751 total time spend for step 2 : 492.1122798919678 step3:rle_unique_nms_with_priority Wed Apr 9 10:57:00 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array VR 22-3-18 : For now we do not clean correctly the datou structure Begin step rle-unique-nms batch 1 Loaded 928 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++nb_obj : 40 nb_hashtags : 4 time to prepare the origin masks : 3.859795331954956 time for calcul the mask position with numpy : 1.8251328468322754 nb_pixel_total : 5903161 time to create 1 rle with new method : 1.443570852279663 time for calcul the mask position with numpy : 0.029078245162963867 nb_pixel_total : 12430 time to create 1 rle with old method : 0.013932466506958008 time for calcul the mask position with numpy : 0.029234647750854492 nb_pixel_total : 27393 time to create 1 rle with old method : 0.0314946174621582 time for calcul the mask position with numpy : 0.029299259185791016 nb_pixel_total : 23136 time to create 1 rle with old method : 0.0265805721282959 time for calcul the mask position with numpy : 0.03147459030151367 nb_pixel_total : 17908 time to create 1 rle with old method : 0.0228426456451416 time for calcul the mask position with numpy : 0.029816389083862305 nb_pixel_total : 39586 time to create 1 rle with old method : 0.04524850845336914 time for calcul the mask position with numpy : 0.029446840286254883 nb_pixel_total : 14618 time to create 1 rle with old method : 0.01676654815673828 time for calcul the mask position with numpy : 0.029175281524658203 nb_pixel_total : 14286 time to create 1 rle with old method : 0.016253948211669922 time for calcul the mask position with numpy : 0.029845237731933594 nb_pixel_total : 32658 time to create 1 rle with old method : 0.03766465187072754 time for calcul the mask position with numpy : 0.030605554580688477 nb_pixel_total : 9927 time to create 1 rle with old method : 0.011428594589233398 time for calcul the mask position with numpy : 0.029303550720214844 nb_pixel_total : 21963 time to create 1 rle with old method : 0.025008440017700195 time for calcul the mask position with numpy : 0.02950310707092285 nb_pixel_total : 32411 time to create 1 rle with old method : 0.0369718074798584 time for calcul the mask position with numpy : 0.029994487762451172 nb_pixel_total : 41225 time to create 1 rle with old method : 0.04675102233886719 time for calcul the mask position with numpy : 0.029478788375854492 nb_pixel_total : 34768 time to create 1 rle with old method : 0.04530811309814453 time for calcul the mask position with numpy : 0.029707670211791992 nb_pixel_total : 9106 time to create 1 rle with old method : 0.01064443588256836 time for calcul the mask position with numpy : 0.030157089233398438 nb_pixel_total : 10611 time to create 1 rle with old method : 0.01258540153503418 time for calcul the mask position with numpy : 0.03476762771606445 nb_pixel_total : 53554 time to create 1 rle with old method : 0.06031680107116699 time for calcul the mask position with numpy : 0.029839515686035156 nb_pixel_total : 85227 time to create 1 rle with old method : 0.09804654121398926 time for calcul the mask position with numpy : 0.029567241668701172 nb_pixel_total : 16730 time to create 1 rle with old method : 0.020899534225463867 time for calcul the mask position with numpy : 0.029634475708007812 nb_pixel_total : 31154 time to create 1 rle with old method : 0.03546929359436035 time for calcul the mask position with numpy : 0.028964757919311523 nb_pixel_total : 5202 time to create 1 rle with old method : 0.005937337875366211 time for calcul the mask position with numpy : 0.02961587905883789 nb_pixel_total : 47473 time to create 1 rle with old method : 0.05361032485961914 time for calcul the mask position with numpy : 0.029215335845947266 nb_pixel_total : 54463 time to create 1 rle with old method : 0.07553315162658691 time for calcul the mask position with numpy : 0.03701424598693848 nb_pixel_total : 14197 time to create 1 rle with old method : 0.01605081558227539 time for calcul the mask position with numpy : 0.028837203979492188 nb_pixel_total : 10300 time to create 1 rle with old method : 0.011740446090698242 time for calcul the mask position with numpy : 0.02897191047668457 nb_pixel_total : 17892 time to create 1 rle with old method : 0.02044844627380371 time for calcul the mask position with numpy : 0.028980016708374023 nb_pixel_total : 29862 time to create 1 rle with old method : 0.034073829650878906 time for calcul the mask position with numpy : 0.029205799102783203 nb_pixel_total : 59890 time to create 1 rle with old method : 0.06757760047912598 time for calcul the mask position with numpy : 0.029247760772705078 nb_pixel_total : 24576 time to create 1 rle with old method : 0.028466224670410156 time for calcul the mask position with numpy : 0.029407501220703125 nb_pixel_total : 20308 time to create 1 rle with old method : 0.02311539649963379 time for calcul the mask position with numpy : 0.029505491256713867 nb_pixel_total : 39485 time to create 1 rle with old method : 0.045050859451293945 time for calcul the mask position with numpy : 0.029172420501708984 nb_pixel_total : 11546 time to create 1 rle with old method : 0.013222932815551758 time for calcul the mask position with numpy : 0.02953624725341797 nb_pixel_total : 49745 time to create 1 rle with old method : 0.05714869499206543 time for calcul the mask position with numpy : 0.029502391815185547 nb_pixel_total : 60538 time to create 1 rle with old method : 0.07758665084838867 time for calcul the mask position with numpy : 0.03586292266845703 nb_pixel_total : 47665 time to create 1 rle with old method : 0.05449247360229492 time for calcul the mask position with numpy : 0.029130935668945312 nb_pixel_total : 55474 time to create 1 rle with old method : 0.06318950653076172 time for calcul the mask position with numpy : 0.029217958450317383 nb_pixel_total : 17895 time to create 1 rle with old method : 0.02048659324645996 time for calcul the mask position with numpy : 0.029405593872070312 nb_pixel_total : 42040 time to create 1 rle with old method : 0.048009395599365234 time for calcul the mask position with numpy : 0.02921438217163086 nb_pixel_total : 4528 time to create 1 rle with old method : 0.005234479904174805 time for calcul the mask position with numpy : 0.03102707862854004 nb_pixel_total : 2281 time to create 1 rle with old method : 0.002653837203979492 time for calcul the mask position with numpy : 0.029056072235107422 nb_pixel_total : 3028 time to create 1 rle with old method : 0.003536224365234375 create new chi : 5.847894668579102 time to delete rle : 0.017664194107055664 batch 1 Loaded 81 chid ids of type : 3594 ++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 19822 TO DO : save crop sub photo not yet done ! save time : 2.3933162689208984 nb_obj : 34 nb_hashtags : 5 time to prepare the origin masks : 4.052216529846191 time for calcul the mask position with numpy : 0.6357932090759277 nb_pixel_total : 5798988 time to create 1 rle with new method : 0.6728196144104004 time for calcul the mask position with numpy : 0.029021501541137695 nb_pixel_total : 21487 time to create 1 rle with old method : 0.024328231811523438 time for calcul the mask position with numpy : 0.02902674674987793 nb_pixel_total : 31720 time to create 1 rle with old method : 0.036995887756347656 time for calcul the mask position with numpy : 0.029401779174804688 nb_pixel_total : 19256 time to create 1 rle with old method : 0.022037506103515625 time for calcul the mask position with numpy : 0.02908611297607422 nb_pixel_total : 44514 time to create 1 rle with old method : 0.05048012733459473 time for calcul the mask position with numpy : 0.029002666473388672 nb_pixel_total : 30761 time to create 1 rle with old method : 0.03511238098144531 time for calcul the mask position with numpy : 0.02882218360900879 nb_pixel_total : 8496 time to create 1 rle with old method : 0.0099029541015625 time for calcul the mask position with numpy : 0.02881646156311035 nb_pixel_total : 14442 time to create 1 rle with old method : 0.016535043716430664 time for calcul the mask position with numpy : 0.02891230583190918 nb_pixel_total : 5504 time to create 1 rle with old method : 0.006327390670776367 time for calcul the mask position with numpy : 0.028890132904052734 nb_pixel_total : 19539 time to create 1 rle with old method : 0.02225804328918457 time for calcul the mask position with numpy : 0.028871774673461914 nb_pixel_total : 15481 time to create 1 rle with old method : 0.01752328872680664 time for calcul the mask position with numpy : 0.02903914451599121 nb_pixel_total : 23160 time to create 1 rle with old method : 0.02661442756652832 time for calcul the mask position with numpy : 0.028818368911743164 nb_pixel_total : 16369 time to create 1 rle with old method : 0.01860499382019043 time for calcul the mask position with numpy : 0.02883744239807129 nb_pixel_total : 22206 time to create 1 rle with old method : 0.025180816650390625 time for calcul the mask position with numpy : 0.028942108154296875 nb_pixel_total : 58946 time to create 1 rle with old method : 0.06649494171142578 time for calcul the mask position with numpy : 0.02893209457397461 nb_pixel_total : 20050 time to create 1 rle with old method : 0.022570371627807617 time for calcul the mask position with numpy : 0.029122352600097656 nb_pixel_total : 57645 time to create 1 rle with old method : 0.06520318984985352 time for calcul the mask position with numpy : 0.028911113739013672 nb_pixel_total : 28138 time to create 1 rle with old method : 0.03185582160949707 time for calcul the mask position with numpy : 0.028914928436279297 nb_pixel_total : 46766 time to create 1 rle with old method : 0.05422711372375488 time for calcul the mask position with numpy : 0.02888202667236328 nb_pixel_total : 9558 time to create 1 rle with old method : 0.010890483856201172 time for calcul the mask position with numpy : 0.028792142868041992 nb_pixel_total : 11397 time to create 1 rle with old method : 0.01287841796875 time for calcul the mask position with numpy : 0.028750896453857422 nb_pixel_total : 20699 time to create 1 rle with old method : 0.02371382713317871 time for calcul the mask position with numpy : 0.029073238372802734 nb_pixel_total : 16151 time to create 1 rle with old method : 0.018291711807250977 time for calcul the mask position with numpy : 0.02852940559387207 nb_pixel_total : 31327 time to create 1 rle with old method : 0.03461098670959473 time for calcul the mask position with numpy : 0.031310081481933594 nb_pixel_total : 41982 time to create 1 rle with old method : 0.04753398895263672 time for calcul the mask position with numpy : 0.029357194900512695 nb_pixel_total : 49413 time to create 1 rle with old method : 0.05575156211853027 time for calcul the mask position with numpy : 0.028965473175048828 nb_pixel_total : 19240 time to create 1 rle with old method : 0.02188730239868164 time for calcul the mask position with numpy : 0.0307772159576416 nb_pixel_total : 178941 time to create 1 rle with new method : 0.4692723751068115 time for calcul the mask position with numpy : 0.029825210571289062 nb_pixel_total : 112685 time to create 1 rle with old method : 0.13230204582214355 time for calcul the mask position with numpy : 0.030985593795776367 nb_pixel_total : 134295 time to create 1 rle with old method : 0.1554102897644043 time for calcul the mask position with numpy : 0.028716564178466797 nb_pixel_total : 35052 time to create 1 rle with old method : 0.039476871490478516 time for calcul the mask position with numpy : 0.028701305389404297 nb_pixel_total : 10729 time to create 1 rle with old method : 0.012299537658691406 time for calcul the mask position with numpy : 0.028831958770751953 nb_pixel_total : 56158 time to create 1 rle with old method : 0.06335616111755371 time for calcul the mask position with numpy : 0.029035329818725586 nb_pixel_total : 8168 time to create 1 rle with old method : 0.009248018264770508 time for calcul the mask position with numpy : 0.029048681259155273 nb_pixel_total : 30977 time to create 1 rle with old method : 0.03501248359680176 create new chi : 4.051267385482788 time to delete rle : 0.0024971961975097656 batch 1 Loaded 69 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 18039 TO DO : save crop sub photo not yet done ! save time : 1.4019689559936523 nb_obj : 40 nb_hashtags : 3 time to prepare the origin masks : 4.374399185180664 time for calcul the mask position with numpy : 1.0052714347839355 nb_pixel_total : 5593738 time to create 1 rle with new method : 0.6009631156921387 time for calcul the mask position with numpy : 0.02962207794189453 nb_pixel_total : 9550 time to create 1 rle with old method : 0.01100468635559082 time for calcul the mask position with numpy : 0.031954288482666016 nb_pixel_total : 51353 time to create 1 rle with old method : 0.07617640495300293 time for calcul the mask position with numpy : 0.02951216697692871 nb_pixel_total : 13181 time to create 1 rle with old method : 0.01513361930847168 time for calcul the mask position with numpy : 0.028775930404663086 nb_pixel_total : 17625 time to create 1 rle with old method : 0.02010035514831543 time for calcul the mask position with numpy : 0.02890634536743164 nb_pixel_total : 14129 time to create 1 rle with old method : 0.017090559005737305 time for calcul the mask position with numpy : 0.02896714210510254 nb_pixel_total : 10021 time to create 1 rle with old method : 0.011434316635131836 time for calcul the mask position with numpy : 0.02897167205810547 nb_pixel_total : 16506 time to create 1 rle with old method : 0.018883466720581055 time for calcul the mask position with numpy : 0.02892780303955078 nb_pixel_total : 24492 time to create 1 rle with old method : 0.02763986587524414 time for calcul the mask position with numpy : 0.029397964477539062 nb_pixel_total : 18520 time to create 1 rle with old method : 0.021654367446899414 time for calcul the mask position with numpy : 0.029140949249267578 nb_pixel_total : 18543 time to create 1 rle with old method : 0.020893335342407227 time for calcul the mask position with numpy : 0.028928518295288086 nb_pixel_total : 6863 time to create 1 rle with old method : 0.007814168930053711 time for calcul the mask position with numpy : 0.029117345809936523 nb_pixel_total : 58018 time to create 1 rle with old method : 0.06499123573303223 time for calcul the mask position with numpy : 0.028865337371826172 nb_pixel_total : 22963 time to create 1 rle with old method : 0.026101350784301758 time for calcul the mask position with numpy : 0.029050350189208984 nb_pixel_total : 11103 time to create 1 rle with old method : 0.012774467468261719 time for calcul the mask position with numpy : 0.032117366790771484 nb_pixel_total : 22974 time to create 1 rle with old method : 0.025994062423706055 time for calcul the mask position with numpy : 0.030460119247436523 nb_pixel_total : 4925 time to create 1 rle with old method : 0.005669116973876953 time for calcul the mask position with numpy : 0.029514074325561523 nb_pixel_total : 18411 time to create 1 rle with old method : 0.021010875701904297 time for calcul the mask position with numpy : 0.02910161018371582 nb_pixel_total : 54693 time to create 1 rle with old method : 0.06087064743041992 time for calcul the mask position with numpy : 0.028547286987304688 nb_pixel_total : 6364 time to create 1 rle with old method : 0.007085323333740234 time for calcul the mask position with numpy : 0.028804302215576172 nb_pixel_total : 37262 time to create 1 rle with old method : 0.0422673225402832 time for calcul the mask position with numpy : 0.028884172439575195 nb_pixel_total : 32811 time to create 1 rle with old method : 0.03717470169067383 time for calcul the mask position with numpy : 0.028960227966308594 nb_pixel_total : 14211 time to create 1 rle with old method : 0.01625800132751465 time for calcul the mask position with numpy : 0.028491497039794922 nb_pixel_total : 65810 time to create 1 rle with old method : 0.07299423217773438 time for calcul the mask position with numpy : 0.028600454330444336 nb_pixel_total : 62500 time to create 1 rle with old method : 0.06899785995483398 time for calcul the mask position with numpy : 0.02880239486694336 nb_pixel_total : 25951 time to create 1 rle with old method : 0.02847909927368164 time for calcul the mask position with numpy : 0.02772045135498047 nb_pixel_total : 46727 time to create 1 rle with old method : 0.05160379409790039 time for calcul the mask position with numpy : 0.029891490936279297 nb_pixel_total : 274003 time to create 1 rle with new method : 0.4893341064453125 time for calcul the mask position with numpy : 0.029100418090820312 nb_pixel_total : 20575 time to create 1 rle with old method : 0.023067235946655273 time for calcul the mask position with numpy : 0.02896571159362793 nb_pixel_total : 19605 time to create 1 rle with old method : 0.022134780883789062 time for calcul the mask position with numpy : 0.028972864151000977 nb_pixel_total : 34045 time to create 1 rle with old method : 0.03796529769897461 time for calcul the mask position with numpy : 0.02912449836730957 nb_pixel_total : 18674 time to create 1 rle with old method : 0.02097606658935547 time for calcul the mask position with numpy : 0.028860807418823242 nb_pixel_total : 21575 time to create 1 rle with old method : 0.02467942237854004 time for calcul the mask position with numpy : 0.029931068420410156 nb_pixel_total : 172068 time to create 1 rle with new method : 0.180922269821167 time for calcul the mask position with numpy : 0.02893686294555664 nb_pixel_total : 17970 time to create 1 rle with old method : 0.020872116088867188 time for calcul the mask position with numpy : 0.032558441162109375 nb_pixel_total : 10062 time to create 1 rle with old method : 0.011595964431762695 time for calcul the mask position with numpy : 0.029036283493041992 nb_pixel_total : 8386 time to create 1 rle with old method : 0.009466171264648438 time for calcul the mask position with numpy : 0.028863906860351562 nb_pixel_total : 22514 time to create 1 rle with old method : 0.02565145492553711 time for calcul the mask position with numpy : 0.029349803924560547 nb_pixel_total : 138004 time to create 1 rle with old method : 0.17931246757507324 time for calcul the mask position with numpy : 0.029865026473999023 nb_pixel_total : 5811 time to create 1 rle with old method : 0.00658869743347168 time for calcul the mask position with numpy : 0.028457164764404297 nb_pixel_total : 7704 time to create 1 rle with old method : 0.008786916732788086 create new chi : 4.704713821411133 time to delete rle : 0.003052949905395508 batch 1 Loaded 81 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 18591 TO DO : save crop sub photo not yet done ! save time : 11.777293920516968 nb_obj : 50 nb_hashtags : 4 time to prepare the origin masks : 4.330408096313477 time for calcul the mask position with numpy : 0.29934239387512207 nb_pixel_total : 5379236 time to create 1 rle with new method : 1.0302929878234863 time for calcul the mask position with numpy : 0.031575918197631836 nb_pixel_total : 35881 time to create 1 rle with old method : 0.042539119720458984 time for calcul the mask position with numpy : 0.031064987182617188 nb_pixel_total : 28599 time to create 1 rle with old method : 0.033934593200683594 time for calcul the mask position with numpy : 0.035976409912109375 nb_pixel_total : 250827 time to create 1 rle with new method : 0.358090877532959 time for calcul the mask position with numpy : 0.029581069946289062 nb_pixel_total : 66667 time to create 1 rle with old method : 0.07571840286254883 time for calcul the mask position with numpy : 0.029616832733154297 nb_pixel_total : 8632 time to create 1 rle with old method : 0.015591621398925781 time for calcul the mask position with numpy : 0.038392066955566406 nb_pixel_total : 10554 time to create 1 rle with old method : 0.017633438110351562 time for calcul the mask position with numpy : 0.028813838958740234 nb_pixel_total : 17353 time to create 1 rle with old method : 0.019193172454833984 time for calcul the mask position with numpy : 0.028562068939208984 nb_pixel_total : 6229 time to create 1 rle with old method : 0.007019519805908203 time for calcul the mask position with numpy : 0.02843618392944336 nb_pixel_total : 6783 time to create 1 rle with old method : 0.00776219367980957 time for calcul the mask position with numpy : 0.03157162666320801 nb_pixel_total : 16954 time to create 1 rle with old method : 0.0212709903717041 time for calcul the mask position with numpy : 0.029845476150512695 nb_pixel_total : 7886 time to create 1 rle with old method : 0.008762121200561523 time for calcul the mask position with numpy : 0.028516054153442383 nb_pixel_total : 40137 time to create 1 rle with old method : 0.047368526458740234 time for calcul the mask position with numpy : 0.02877974510192871 nb_pixel_total : 11485 time to create 1 rle with old method : 0.012819051742553711 time for calcul the mask position with numpy : 0.035452842712402344 nb_pixel_total : 19279 time to create 1 rle with old method : 0.02368450164794922 time for calcul the mask position with numpy : 0.03256821632385254 nb_pixel_total : 25144 time to create 1 rle with old method : 0.03247714042663574 time for calcul the mask position with numpy : 0.03315424919128418 nb_pixel_total : 50272 time to create 1 rle with old method : 0.06453537940979004 time for calcul the mask position with numpy : 0.029482364654541016 nb_pixel_total : 38455 time to create 1 rle with old method : 0.048636436462402344 time for calcul the mask position with numpy : 0.037421226501464844 nb_pixel_total : 22022 time to create 1 rle with old method : 0.026811838150024414 time for calcul the mask position with numpy : 0.030135631561279297 nb_pixel_total : 30726 time to create 1 rle with old method : 0.034914255142211914 time for calcul the mask position with numpy : 0.029749393463134766 nb_pixel_total : 4478 time to create 1 rle with old method : 0.005221843719482422 time for calcul the mask position with numpy : 0.03133058547973633 nb_pixel_total : 36974 time to create 1 rle with old method : 0.043729543685913086 time for calcul the mask position with numpy : 0.029079675674438477 nb_pixel_total : 11571 time to create 1 rle with old method : 0.013285160064697266 time for calcul the mask position with numpy : 0.03075432777404785 nb_pixel_total : 10253 time to create 1 rle with old method : 0.01174020767211914 time for calcul the mask position with numpy : 0.029659509658813477 nb_pixel_total : 6054 time to create 1 rle with old method : 0.00707697868347168 time for calcul the mask position with numpy : 0.031473398208618164 nb_pixel_total : 205379 time to create 1 rle with new method : 0.2796323299407959 time for calcul the mask position with numpy : 0.029649972915649414 nb_pixel_total : 46148 time to create 1 rle with old method : 0.05222654342651367 time for calcul the mask position with numpy : 0.02920246124267578 nb_pixel_total : 31413 time to create 1 rle with old method : 0.03576350212097168 time for calcul the mask position with numpy : 0.029102087020874023 nb_pixel_total : 27569 time to create 1 rle with old method : 0.031249523162841797 time for calcul the mask position with numpy : 0.028876543045043945 nb_pixel_total : 8636 time to create 1 rle with old method : 0.009793996810913086 time for calcul the mask position with numpy : 0.030469417572021484 nb_pixel_total : 1125 time to create 1 rle with old method : 0.0017745494842529297 time for calcul the mask position with numpy : 0.02917170524597168 nb_pixel_total : 52594 time to create 1 rle with old method : 0.058650970458984375 time for calcul the mask position with numpy : 0.028529882431030273 nb_pixel_total : 9669 time to create 1 rle with old method : 0.011343240737915039 time for calcul the mask position with numpy : 0.028865575790405273 nb_pixel_total : 8515 time to create 1 rle with old method : 0.009295225143432617 time for calcul the mask position with numpy : 0.03173637390136719 nb_pixel_total : 13782 time to create 1 rle with old method : 0.0160825252532959 time for calcul the mask position with numpy : 0.02975010871887207 nb_pixel_total : 11003 time to create 1 rle with old method : 0.012482643127441406 time for calcul the mask position with numpy : 0.029566526412963867 nb_pixel_total : 15914 time to create 1 rle with old method : 0.02463841438293457 time for calcul the mask position with numpy : 0.03624558448791504 nb_pixel_total : 94440 time to create 1 rle with old method : 0.11895561218261719 time for calcul the mask position with numpy : 0.029038429260253906 nb_pixel_total : 21105 time to create 1 rle with old method : 0.02389693260192871 time for calcul the mask position with numpy : 0.029756784439086914 nb_pixel_total : 10823 time to create 1 rle with old method : 0.012607574462890625 time for calcul the mask position with numpy : 0.02989029884338379 nb_pixel_total : 18499 time to create 1 rle with old method : 0.0211336612701416 time for calcul the mask position with numpy : 0.02968573570251465 nb_pixel_total : 127836 time to create 1 rle with old method : 0.1554872989654541 time for calcul the mask position with numpy : 0.030275821685791016 nb_pixel_total : 2223 time to create 1 rle with old method : 0.0026683807373046875 time for calcul the mask position with numpy : 0.03000330924987793 nb_pixel_total : 6078 time to create 1 rle with old method : 0.007924318313598633 time for calcul the mask position with numpy : 0.03057718276977539 nb_pixel_total : 26107 time to create 1 rle with old method : 0.032567739486694336 time for calcul the mask position with numpy : 0.029616355895996094 nb_pixel_total : 8378 time to create 1 rle with old method : 0.010078907012939453 time for calcul the mask position with numpy : 0.028914213180541992 nb_pixel_total : 21873 time to create 1 rle with old method : 0.026763916015625 time for calcul the mask position with numpy : 0.03029465675354004 nb_pixel_total : 3223 time to create 1 rle with old method : 0.003857851028442383 time for calcul the mask position with numpy : 0.030467510223388672 nb_pixel_total : 47101 time to create 1 rle with old method : 0.058516502380371094 time for calcul the mask position with numpy : 0.031246662139892578 nb_pixel_total : 68824 time to create 1 rle with old method : 0.07751250267028809 time for calcul the mask position with numpy : 0.029482603073120117 nb_pixel_total : 19532 time to create 1 rle with old method : 0.02356886863708496 create new chi : 5.023587942123413 time to delete rle : 0.008823156356811523 batch 1 Loaded 101 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 25294 TO DO : save crop sub photo not yet done ! save time : 1.865077018737793 nb_obj : 40 nb_hashtags : 4 time to prepare the origin masks : 3.655369997024536 time for calcul the mask position with numpy : 0.13997459411621094 nb_pixel_total : 6086856 time to create 1 rle with new method : 0.5329957008361816 time for calcul the mask position with numpy : 0.028928756713867188 nb_pixel_total : 5280 time to create 1 rle with old method : 0.006145477294921875 time for calcul the mask position with numpy : 0.029410362243652344 nb_pixel_total : 64526 time to create 1 rle with old method : 0.07287883758544922 time for calcul the mask position with numpy : 0.028753995895385742 nb_pixel_total : 10738 time to create 1 rle with old method : 0.012198209762573242 time for calcul the mask position with numpy : 0.028799057006835938 nb_pixel_total : 17774 time to create 1 rle with old method : 0.020060300827026367 time for calcul the mask position with numpy : 0.02866363525390625 nb_pixel_total : 10059 time to create 1 rle with old method : 0.011423349380493164 time for calcul the mask position with numpy : 0.02913832664489746 nb_pixel_total : 49457 time to create 1 rle with old method : 0.055866241455078125 time for calcul the mask position with numpy : 0.028687238693237305 nb_pixel_total : 6712 time to create 1 rle with old method : 0.0077745914459228516 time for calcul the mask position with numpy : 0.028671741485595703 nb_pixel_total : 22646 time to create 1 rle with old method : 0.025832414627075195 time for calcul the mask position with numpy : 0.029036760330200195 nb_pixel_total : 11524 time to create 1 rle with old method : 0.013044118881225586 time for calcul the mask position with numpy : 0.032378196716308594 nb_pixel_total : 26642 time to create 1 rle with old method : 0.0504605770111084 time for calcul the mask position with numpy : 0.036237478256225586 nb_pixel_total : 6492 time to create 1 rle with old method : 0.008280277252197266 time for calcul the mask position with numpy : 0.028863191604614258 nb_pixel_total : 19881 time to create 1 rle with old method : 0.02254629135131836 time for calcul the mask position with numpy : 0.029488325119018555 nb_pixel_total : 25683 time to create 1 rle with old method : 0.029899120330810547 time for calcul the mask position with numpy : 0.02928781509399414 nb_pixel_total : 34856 time to create 1 rle with old method : 0.047399282455444336 time for calcul the mask position with numpy : 0.029701709747314453 nb_pixel_total : 26146 time to create 1 rle with old method : 0.029578685760498047 time for calcul the mask position with numpy : 0.030237913131713867 nb_pixel_total : 14418 time to create 1 rle with old method : 0.017954111099243164 time for calcul the mask position with numpy : 0.029526710510253906 nb_pixel_total : 28973 time to create 1 rle with old method : 0.03316545486450195 time for calcul the mask position with numpy : 0.02983832359313965 nb_pixel_total : 27880 time to create 1 rle with old method : 0.03229832649230957 time for calcul the mask position with numpy : 0.02917790412902832 nb_pixel_total : 38622 time to create 1 rle with old method : 0.047113656997680664 time for calcul the mask position with numpy : 0.029521703720092773 nb_pixel_total : 9271 time to create 1 rle with old method : 0.011215448379516602 time for calcul the mask position with numpy : 0.029164791107177734 nb_pixel_total : 30204 time to create 1 rle with old method : 0.034034013748168945 time for calcul the mask position with numpy : 0.028896808624267578 nb_pixel_total : 9510 time to create 1 rle with old method : 0.010864496231079102 time for calcul the mask position with numpy : 0.029503583908081055 nb_pixel_total : 15128 time to create 1 rle with old method : 0.01756882667541504 time for calcul the mask position with numpy : 0.029593706130981445 nb_pixel_total : 42271 time to create 1 rle with old method : 0.05335116386413574 time for calcul the mask position with numpy : 0.03627657890319824 nb_pixel_total : 29131 time to create 1 rle with old method : 0.035057783126831055 time for calcul the mask position with numpy : 0.03103160858154297 nb_pixel_total : 14266 time to create 1 rle with old method : 0.016339778900146484 time for calcul the mask position with numpy : 0.030734777450561523 nb_pixel_total : 36315 time to create 1 rle with old method : 0.04313778877258301 time for calcul the mask position with numpy : 0.03202486038208008 nb_pixel_total : 16293 time to create 1 rle with old method : 0.021800994873046875 time for calcul the mask position with numpy : 0.030580759048461914 nb_pixel_total : 8704 time to create 1 rle with old method : 0.0113372802734375 time for calcul the mask position with numpy : 0.029429912567138672 nb_pixel_total : 40252 time to create 1 rle with old method : 0.04852628707885742 time for calcul the mask position with numpy : 0.029358863830566406 nb_pixel_total : 23191 time to create 1 rle with old method : 0.02681756019592285 time for calcul the mask position with numpy : 0.030358076095581055 nb_pixel_total : 11300 time to create 1 rle with old method : 0.013182640075683594 time for calcul the mask position with numpy : 0.02959609031677246 nb_pixel_total : 16797 time to create 1 rle with old method : 0.019092321395874023 time for calcul the mask position with numpy : 0.02974390983581543 nb_pixel_total : 35919 time to create 1 rle with old method : 0.041116952896118164 time for calcul the mask position with numpy : 0.030002832412719727 nb_pixel_total : 48374 time to create 1 rle with old method : 0.055406808853149414 time for calcul the mask position with numpy : 0.030354022979736328 nb_pixel_total : 12727 time to create 1 rle with old method : 0.014617204666137695 time for calcul the mask position with numpy : 0.029559850692749023 nb_pixel_total : 29065 time to create 1 rle with old method : 0.03314709663391113 time for calcul the mask position with numpy : 0.0296785831451416 nb_pixel_total : 45828 time to create 1 rle with old method : 0.05183863639831543 time for calcul the mask position with numpy : 0.02952861785888672 nb_pixel_total : 25049 time to create 1 rle with old method : 0.028352737426757812 time for calcul the mask position with numpy : 0.029169082641601562 nb_pixel_total : 15480 time to create 1 rle with old method : 0.017598390579223633 create new chi : 3.049609422683716 time to delete rle : 0.002744436264038086 batch 1 Loaded 81 chid ids of type : 3594 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 18620 TO DO : save crop sub photo not yet done ! save time : 1.525374412536621 nb_obj : 39 nb_hashtags : 4 time to prepare the origin masks : 3.9668092727661133 time for calcul the mask position with numpy : 0.20700383186340332 nb_pixel_total : 5635847 time to create 1 rle with new method : 1.098095178604126 time for calcul the mask position with numpy : 0.031267642974853516 nb_pixel_total : 8491 time to create 1 rle with old method : 0.009830236434936523 time for calcul the mask position with numpy : 0.029125690460205078 nb_pixel_total : 81711 time to create 1 rle with old method : 0.11377716064453125 time for calcul the mask position with numpy : 0.03252577781677246 nb_pixel_total : 16167 time to create 1 rle with old method : 0.018490076065063477 time for calcul the mask position with numpy : 0.02922797203063965 nb_pixel_total : 13888 time to create 1 rle with old method : 0.015828847885131836 time for calcul the mask position with numpy : 0.02936840057373047 nb_pixel_total : 66348 time to create 1 rle with old method : 0.07471466064453125 time for calcul the mask position with numpy : 0.028929471969604492 nb_pixel_total : 8848 time to create 1 rle with old method : 0.010264396667480469 time for calcul the mask position with numpy : 0.031066179275512695 nb_pixel_total : 59227 time to create 1 rle with old method : 0.07594537734985352 time for calcul the mask position with numpy : 0.030885696411132812 nb_pixel_total : 23945 time to create 1 rle with old method : 0.029088735580444336 time for calcul the mask position with numpy : 0.03028583526611328 nb_pixel_total : 13758 time to create 1 rle with old method : 0.015573978424072266 time for calcul the mask position with numpy : 0.02918720245361328 nb_pixel_total : 17670 time to create 1 rle with old method : 0.020156145095825195 time for calcul the mask position with numpy : 0.03140854835510254 nb_pixel_total : 29505 time to create 1 rle with old method : 0.033188819885253906 time for calcul the mask position with numpy : 0.029263973236083984 nb_pixel_total : 18587 time to create 1 rle with old method : 0.021058082580566406 time for calcul the mask position with numpy : 0.029225587844848633 nb_pixel_total : 7348 time to create 1 rle with old method : 0.00852203369140625 time for calcul the mask position with numpy : 0.029126644134521484 nb_pixel_total : 31583 time to create 1 rle with old method : 0.03605532646179199 time for calcul the mask position with numpy : 0.0289461612701416 nb_pixel_total : 26152 time to create 1 rle with old method : 0.029955625534057617 time for calcul the mask position with numpy : 0.029195547103881836 nb_pixel_total : 32090 time to create 1 rle with old method : 0.03643798828125 time for calcul the mask position with numpy : 0.029019594192504883 nb_pixel_total : 27586 time to create 1 rle with old method : 0.03140068054199219 time for calcul the mask position with numpy : 0.02894759178161621 nb_pixel_total : 35180 time to create 1 rle with old method : 0.039858341217041016 time for calcul the mask position with numpy : 0.03098773956298828 nb_pixel_total : 17287 time to create 1 rle with old method : 0.01954793930053711 time for calcul the mask position with numpy : 0.02952265739440918 nb_pixel_total : 126392 time to create 1 rle with old method : 0.14237666130065918 time for calcul the mask position with numpy : 0.030554771423339844 nb_pixel_total : 28946 time to create 1 rle with old method : 0.036161184310913086 time for calcul the mask position with numpy : 0.030730485916137695 nb_pixel_total : 21163 time to create 1 rle with old method : 0.0284268856048584 time for calcul the mask position with numpy : 0.03012847900390625 nb_pixel_total : 44191 time to create 1 rle with old method : 0.05275106430053711 time for calcul the mask position with numpy : 0.03009629249572754 nb_pixel_total : 44744 time to create 1 rle with old method : 0.05021023750305176 time for calcul the mask position with numpy : 0.02919292449951172 nb_pixel_total : 70665 time to create 1 rle with old method : 0.0801401138305664 time for calcul the mask position with numpy : 0.029137849807739258 nb_pixel_total : 16375 time to create 1 rle with old method : 0.01866292953491211 time for calcul the mask position with numpy : 0.0289459228515625 nb_pixel_total : 25960 time to create 1 rle with old method : 0.02929830551147461 time for calcul the mask position with numpy : 0.02897930145263672 nb_pixel_total : 15084 time to create 1 rle with old method : 0.017398595809936523 time for calcul the mask position with numpy : 0.029680490493774414 nb_pixel_total : 66969 time to create 1 rle with old method : 0.0770721435546875 time for calcul the mask position with numpy : 0.030312538146972656 nb_pixel_total : 115073 time to create 1 rle with old method : 0.1292743682861328 time for calcul the mask position with numpy : 0.029143095016479492 nb_pixel_total : 17602 time to create 1 rle with old method : 0.02011895179748535 time for calcul the mask position with numpy : 0.029323577880859375 nb_pixel_total : 15435 time to create 1 rle with old method : 0.017960309982299805 time for calcul the mask position with numpy : 0.029174327850341797 nb_pixel_total : 9179 time to create 1 rle with old method : 0.010680198669433594 time for calcul the mask position with numpy : 0.029353857040405273 nb_pixel_total : 16235 time to create 1 rle with old method : 0.018413066864013672 time for calcul the mask position with numpy : 0.030200481414794922 nb_pixel_total : 108564 time to create 1 rle with old method : 0.12505602836608887 time for calcul the mask position with numpy : 0.029659032821655273 nb_pixel_total : 43271 time to create 1 rle with old method : 0.04875636100769043 time for calcul the mask position with numpy : 0.029750823974609375 nb_pixel_total : 57689 time to create 1 rle with old method : 0.065582275390625 time for calcul the mask position with numpy : 0.029361963272094727 nb_pixel_total : 17532 time to create 1 rle with old method : 0.019809246063232422 time for calcul the mask position with numpy : 0.030258655548095703 nb_pixel_total : 17953 time to create 1 rle with old method : 0.02045583724975586 create new chi : 4.145175933837891 time to delete rle : 0.0032050609588623047 batch 1 Loaded 79 chid ids of type : 3594 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 19988 TO DO : save crop sub photo not yet done ! save time : 3.2976577281951904 nb_obj : 61 nb_hashtags : 3 time to prepare the origin masks : 4.486180305480957 time for calcul the mask position with numpy : 0.6052122116088867 nb_pixel_total : 5256125 time to create 1 rle with new method : 0.6787307262420654 time for calcul the mask position with numpy : 0.02933955192565918 nb_pixel_total : 21936 time to create 1 rle with old method : 0.024599313735961914 time for calcul the mask position with numpy : 0.028886795043945312 nb_pixel_total : 20281 time to create 1 rle with old method : 0.022960662841796875 time for calcul the mask position with numpy : 0.02928781509399414 nb_pixel_total : 16368 time to create 1 rle with old method : 0.018620014190673828 time for calcul the mask position with numpy : 0.029526948928833008 nb_pixel_total : 59884 time to create 1 rle with old method : 0.06672310829162598 time for calcul the mask position with numpy : 0.029150009155273438 nb_pixel_total : 10569 time to create 1 rle with old method : 0.012020349502563477 time for calcul the mask position with numpy : 0.028967857360839844 nb_pixel_total : 14396 time to create 1 rle with old method : 0.016566038131713867 time for calcul the mask position with numpy : 0.029146194458007812 nb_pixel_total : 24848 time to create 1 rle with old method : 0.028369426727294922 time for calcul the mask position with numpy : 0.029084205627441406 nb_pixel_total : 18375 time to create 1 rle with old method : 0.02075362205505371 time for calcul the mask position with numpy : 0.02899789810180664 nb_pixel_total : 49156 time to create 1 rle with old method : 0.0635223388671875 time for calcul the mask position with numpy : 0.06556177139282227 nb_pixel_total : 21285 time to create 1 rle with old method : 0.06012439727783203 time for calcul the mask position with numpy : 0.041867971420288086 nb_pixel_total : 9099 time to create 1 rle with old method : 0.010382413864135742 time for calcul the mask position with numpy : 0.029253005981445312 nb_pixel_total : 5199 time to create 1 rle with old method : 0.0060329437255859375 time for calcul the mask position with numpy : 0.0293428897857666 nb_pixel_total : 20177 time to create 1 rle with old method : 0.022964000701904297 time for calcul the mask position with numpy : 0.028989791870117188 nb_pixel_total : 4521 time to create 1 rle with old method : 0.005213737487792969 time for calcul the mask position with numpy : 0.028838396072387695 nb_pixel_total : 23992 time to create 1 rle with old method : 0.026975154876708984 time for calcul the mask position with numpy : 0.02922844886779785 nb_pixel_total : 44815 time to create 1 rle with old method : 0.052155494689941406 time for calcul the mask position with numpy : 0.028871774673461914 nb_pixel_total : 15771 time to create 1 rle with old method : 0.017922163009643555 time for calcul the mask position with numpy : 0.0315701961517334 nb_pixel_total : 30220 time to create 1 rle with old method : 0.03574490547180176 time for calcul the mask position with numpy : 0.030388355255126953 nb_pixel_total : 3370 time to create 1 rle with old method : 0.0039594173431396484 time for calcul the mask position with numpy : 0.029361486434936523 nb_pixel_total : 18467 time to create 1 rle with old method : 0.021024465560913086 time for calcul the mask position with numpy : 0.02917194366455078 nb_pixel_total : 48605 time to create 1 rle with old method : 0.0544734001159668 time for calcul the mask position with numpy : 0.028693675994873047 nb_pixel_total : 35293 time to create 1 rle with old method : 0.04067850112915039 time for calcul the mask position with numpy : 0.028728246688842773 nb_pixel_total : 15683 time to create 1 rle with old method : 0.017921924591064453 time for calcul the mask position with numpy : 0.02881479263305664 nb_pixel_total : 38645 time to create 1 rle with old method : 0.04410815238952637 time for calcul the mask position with numpy : 0.030918121337890625 nb_pixel_total : 9592 time to create 1 rle with old method : 0.015299320220947266 time for calcul the mask position with numpy : 0.03544759750366211 nb_pixel_total : 25493 time to create 1 rle with old method : 0.03493142127990723 time for calcul the mask position with numpy : 0.03471851348876953 nb_pixel_total : 27875 time to create 1 rle with old method : 0.03741645812988281 time for calcul the mask position with numpy : 0.029808998107910156 nb_pixel_total : 53127 time to create 1 rle with old method : 0.06291007995605469 time for calcul the mask position with numpy : 0.03257632255554199 nb_pixel_total : 12916 time to create 1 rle with old method : 0.017149925231933594 time for calcul the mask position with numpy : 0.029964685440063477 nb_pixel_total : 25167 time to create 1 rle with old method : 0.02912163734436035 time for calcul the mask position with numpy : 0.030093669891357422 nb_pixel_total : 12518 time to create 1 rle with old method : 0.015419960021972656 time for calcul the mask position with numpy : 0.031185626983642578 nb_pixel_total : 111715 time to create 1 rle with old method : 0.12703800201416016 time for calcul the mask position with numpy : 0.02925395965576172 nb_pixel_total : 61572 time to create 1 rle with old method : 0.06955814361572266 time for calcul the mask position with numpy : 0.029444217681884766 nb_pixel_total : 22736 time to create 1 rle with old method : 0.02527165412902832 time for calcul the mask position with numpy : 0.030110836029052734 nb_pixel_total : 19851 time to create 1 rle with old method : 0.03749585151672363 time for calcul the mask position with numpy : 0.03498959541320801 nb_pixel_total : 22121 time to create 1 rle with old method : 0.024924278259277344 time for calcul the mask position with numpy : 0.028885841369628906 nb_pixel_total : 5899 time to create 1 rle with old method : 0.006601810455322266 time for calcul the mask position with numpy : 0.029013633728027344 nb_pixel_total : 15216 time to create 1 rle with old method : 0.017249584197998047 time for calcul the mask position with numpy : 0.02959299087524414 nb_pixel_total : 107128 time to create 1 rle with old method : 0.11986398696899414 time for calcul the mask position with numpy : 0.028223037719726562 nb_pixel_total : 15580 time to create 1 rle with old method : 0.017076492309570312 time for calcul the mask position with numpy : 0.028627872467041016 nb_pixel_total : 19540 time to create 1 rle with old method : 0.02223682403564453 time for calcul the mask position with numpy : 0.028805971145629883 nb_pixel_total : 11096 time to create 1 rle with old method : 0.012264251708984375 time for calcul the mask position with numpy : 0.028932571411132812 nb_pixel_total : 42403 time to create 1 rle with old method : 0.04825997352600098 time for calcul the mask position with numpy : 0.029106855392456055 nb_pixel_total : 12053 time to create 1 rle with old method : 0.013761758804321289 time for calcul the mask position with numpy : 0.029026269912719727 nb_pixel_total : 19887 time to create 1 rle with old method : 0.022873401641845703 time for calcul the mask position with numpy : 0.029320240020751953 nb_pixel_total : 48705 time to create 1 rle with old method : 0.05674910545349121 time for calcul the mask position with numpy : 0.029332637786865234 nb_pixel_total : 6956 time to create 1 rle with old method : 0.007984399795532227 time for calcul the mask position with numpy : 0.02929401397705078 nb_pixel_total : 11102 time to create 1 rle with old method : 0.012731552124023438 time for calcul the mask position with numpy : 0.029385805130004883 nb_pixel_total : 6092 time to create 1 rle with old method : 0.0071027278900146484 time for calcul the mask position with numpy : 0.02939629554748535 nb_pixel_total : 13080 time to create 1 rle with old method : 0.014961481094360352 time for calcul the mask position with numpy : 0.028749465942382812 nb_pixel_total : 4016 time to create 1 rle with old method : 0.004492044448852539 time for calcul the mask position with numpy : 0.028656482696533203 nb_pixel_total : 11513 time to create 1 rle with old method : 0.012840509414672852 time for calcul the mask position with numpy : 0.031546592712402344 nb_pixel_total : 269879 time to create 1 rle with new method : 0.39519286155700684 time for calcul the mask position with numpy : 0.030408382415771484 nb_pixel_total : 27397 time to create 1 rle with old method : 0.031008005142211914 time for calcul the mask position with numpy : 0.029490947723388672 nb_pixel_total : 260 time to create 1 rle with old method : 0.00041556358337402344 time for calcul the mask position with numpy : 0.031049013137817383 nb_pixel_total : 44343 time to create 1 rle with old method : 0.05093741416931152 time for calcul the mask position with numpy : 0.030098915100097656 nb_pixel_total : 26784 time to create 1 rle with old method : 0.03106999397277832 time for calcul the mask position with numpy : 0.030237674713134766 nb_pixel_total : 41740 time to create 1 rle with old method : 0.04886484146118164 time for calcul the mask position with numpy : 0.03043651580810547 nb_pixel_total : 22147 time to create 1 rle with old method : 0.027265310287475586 time for calcul the mask position with numpy : 0.030020713806152344 nb_pixel_total : 11071 time to create 1 rle with old method : 0.012715339660644531 time for calcul the mask position with numpy : 0.02991628646850586 nb_pixel_total : 24590 time to create 1 rle with old method : 0.028428316116333008 create new chi : 5.422231435775757 time to delete rle : 0.004522562026977539 batch 1 Loaded 123 chid ids of type : 3594 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 28476 TO DO : save crop sub photo not yet done ! save time : 3.266864776611328 nb_obj : 30 nb_hashtags : 5 time to prepare the origin masks : 4.520457983016968 time for calcul the mask position with numpy : 0.2317183017730713 nb_pixel_total : 5169029 time to create 1 rle with new method : 1.06247878074646 time for calcul the mask position with numpy : 0.029512882232666016 nb_pixel_total : 89676 time to create 1 rle with old method : 0.10034322738647461 time for calcul the mask position with numpy : 0.02958083152770996 nb_pixel_total : 18985 time to create 1 rle with old method : 0.021785736083984375 time for calcul the mask position with numpy : 0.028952836990356445 nb_pixel_total : 10647 time to create 1 rle with old method : 0.012146949768066406 time for calcul the mask position with numpy : 0.028881549835205078 nb_pixel_total : 11008 time to create 1 rle with old method : 0.012563943862915039 time for calcul the mask position with numpy : 0.02887582778930664 nb_pixel_total : 24246 time to create 1 rle with old method : 0.027524948120117188 time for calcul the mask position with numpy : 0.02886509895324707 nb_pixel_total : 40555 time to create 1 rle with old method : 0.07332515716552734 time for calcul the mask position with numpy : 0.035265445709228516 nb_pixel_total : 84463 time to create 1 rle with old method : 0.10829329490661621 time for calcul the mask position with numpy : 0.02918100357055664 nb_pixel_total : 33184 time to create 1 rle with old method : 0.03754997253417969 time for calcul the mask position with numpy : 0.028724193572998047 nb_pixel_total : 27046 time to create 1 rle with old method : 0.030580520629882812 time for calcul the mask position with numpy : 0.028699159622192383 nb_pixel_total : 10885 time to create 1 rle with old method : 0.012633085250854492 time for calcul the mask position with numpy : 0.029659271240234375 nb_pixel_total : 119901 time to create 1 rle with old method : 0.14025044441223145 time for calcul the mask position with numpy : 0.02923727035522461 nb_pixel_total : 166494 time to create 1 rle with new method : 0.8905465602874756 time for calcul the mask position with numpy : 0.029167652130126953 nb_pixel_total : 37320 time to create 1 rle with old method : 0.04284858703613281 time for calcul the mask position with numpy : 0.028886079788208008 nb_pixel_total : 29103 time to create 1 rle with old method : 0.03308558464050293 time for calcul the mask position with numpy : 0.029448747634887695 nb_pixel_total : 43922 time to create 1 rle with old method : 0.06635046005249023 time for calcul the mask position with numpy : 0.034243106842041016 nb_pixel_total : 117254 time to create 1 rle with old method : 0.12612390518188477 time for calcul the mask position with numpy : 0.028594970703125 nb_pixel_total : 46062 time to create 1 rle with old method : 0.05150008201599121 time for calcul the mask position with numpy : 0.027890443801879883 nb_pixel_total : 30533 time to create 1 rle with old method : 0.03386497497558594 time for calcul the mask position with numpy : 0.02937626838684082 nb_pixel_total : 207710 time to create 1 rle with new method : 0.6798098087310791 time for calcul the mask position with numpy : 0.03058910369873047 nb_pixel_total : 13159 time to create 1 rle with old method : 0.015095710754394531 time for calcul the mask position with numpy : 0.029506206512451172 nb_pixel_total : 26542 time to create 1 rle with old method : 0.030219078063964844 time for calcul the mask position with numpy : 0.029471158981323242 nb_pixel_total : 186833 time to create 1 rle with new method : 0.5500662326812744 time for calcul the mask position with numpy : 0.031640052795410156 nb_pixel_total : 59441 time to create 1 rle with old method : 0.08472347259521484 time for calcul the mask position with numpy : 0.030989408493041992 nb_pixel_total : 22458 time to create 1 rle with old method : 0.03414463996887207 time for calcul the mask position with numpy : 0.034058332443237305 nb_pixel_total : 202129 time to create 1 rle with new method : 0.6171152591705322 time for calcul the mask position with numpy : 0.028824567794799805 nb_pixel_total : 2916 time to create 1 rle with old method : 0.0036449432373046875 time for calcul the mask position with numpy : 0.02902984619140625 nb_pixel_total : 37495 time to create 1 rle with old method : 0.04245734214782715 time for calcul the mask position with numpy : 0.029350757598876953 nb_pixel_total : 144232 time to create 1 rle with old method : 0.16287946701049805 time for calcul the mask position with numpy : 0.028949737548828125 nb_pixel_total : 9058 time to create 1 rle with old method : 0.010274171829223633 time for calcul the mask position with numpy : 0.02896428108215332 nb_pixel_total : 27954 time to create 1 rle with old method : 0.03750419616699219 create new chi : 6.3959033489227295 time to delete rle : 0.003941774368286133 batch 1 Loaded 61 chid ids of type : 3594 ++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 19755 TO DO : save crop sub photo not yet done ! save time : 1.4165153503417969 nb_obj : 47 nb_hashtags : 4 time to prepare the origin masks : 4.086534023284912 time for calcul the mask position with numpy : 0.35002708435058594 nb_pixel_total : 5671063 time to create 1 rle with new method : 0.6885695457458496 time for calcul the mask position with numpy : 0.029036283493041992 nb_pixel_total : 20170 time to create 1 rle with old method : 0.02283000946044922 time for calcul the mask position with numpy : 0.02877187728881836 nb_pixel_total : 19150 time to create 1 rle with old method : 0.021706342697143555 time for calcul the mask position with numpy : 0.029029369354248047 nb_pixel_total : 42318 time to create 1 rle with old method : 0.04764580726623535 time for calcul the mask position with numpy : 0.02915215492248535 nb_pixel_total : 9632 time to create 1 rle with old method : 0.011013269424438477 time for calcul the mask position with numpy : 0.028850793838500977 nb_pixel_total : 15792 time to create 1 rle with old method : 0.0177764892578125 time for calcul the mask position with numpy : 0.035924673080444336 nb_pixel_total : 25013 time to create 1 rle with old method : 0.03940176963806152 time for calcul the mask position with numpy : 0.033315181732177734 nb_pixel_total : 53394 time to create 1 rle with old method : 0.06055760383605957 time for calcul the mask position with numpy : 0.02933526039123535 nb_pixel_total : 26850 time to create 1 rle with old method : 0.030428171157836914 time for calcul the mask position with numpy : 0.029222726821899414 nb_pixel_total : 6003 time to create 1 rle with old method : 0.006907463073730469 time for calcul the mask position with numpy : 0.02906322479248047 nb_pixel_total : 27323 time to create 1 rle with old method : 0.031126737594604492 time for calcul the mask position with numpy : 0.029240131378173828 nb_pixel_total : 17216 time to create 1 rle with old method : 0.019611597061157227 time for calcul the mask position with numpy : 0.028987407684326172 nb_pixel_total : 3983 time to create 1 rle with old method : 0.004582405090332031 time for calcul the mask position with numpy : 0.029152631759643555 nb_pixel_total : 12587 time to create 1 rle with old method : 0.014371395111083984 time for calcul the mask position with numpy : 0.029054880142211914 nb_pixel_total : 25523 time to create 1 rle with old method : 0.028881549835205078 time for calcul the mask position with numpy : 0.02913522720336914 nb_pixel_total : 21514 time to create 1 rle with old method : 0.02440953254699707 time for calcul the mask position with numpy : 0.029642581939697266 nb_pixel_total : 47165 time to create 1 rle with old method : 0.05337238311767578 time for calcul the mask position with numpy : 0.028886079788208008 nb_pixel_total : 19458 time to create 1 rle with old method : 0.022086620330810547 time for calcul the mask position with numpy : 0.02893853187561035 nb_pixel_total : 20271 time to create 1 rle with old method : 0.0228426456451416 time for calcul the mask position with numpy : 0.028977155685424805 nb_pixel_total : 37771 time to create 1 rle with old method : 0.04284930229187012 time for calcul the mask position with numpy : 0.029024600982666016 nb_pixel_total : 9011 time to create 1 rle with old method : 0.010339021682739258 time for calcul the mask position with numpy : 0.029373884201049805 nb_pixel_total : 81404 time to create 1 rle with old method : 0.09123563766479492 time for calcul the mask position with numpy : 0.029010534286499023 nb_pixel_total : 11722 time to create 1 rle with old method : 0.013195037841796875 time for calcul the mask position with numpy : 0.029201984405517578 nb_pixel_total : 33958 time to create 1 rle with old method : 0.0385594367980957 time for calcul the mask position with numpy : 0.029168128967285156 nb_pixel_total : 52510 time to create 1 rle with old method : 0.05922222137451172 time for calcul the mask position with numpy : 0.030521631240844727 nb_pixel_total : 15582 time to create 1 rle with old method : 0.017637968063354492 time for calcul the mask position with numpy : 0.031941890716552734 nb_pixel_total : 6453 time to create 1 rle with old method : 0.00833749771118164 time for calcul the mask position with numpy : 0.02898383140563965 nb_pixel_total : 25151 time to create 1 rle with old method : 0.031688690185546875 time for calcul the mask position with numpy : 0.03139472007751465 nb_pixel_total : 4370 time to create 1 rle with old method : 0.004994392395019531 time for calcul the mask position with numpy : 0.03160405158996582 nb_pixel_total : 48993 time to create 1 rle with old method : 0.05508685111999512 time for calcul the mask position with numpy : 0.029463768005371094 nb_pixel_total : 29664 time to create 1 rle with old method : 0.03913235664367676 time for calcul the mask position with numpy : 0.030994176864624023 nb_pixel_total : 97308 time to create 1 rle with old method : 0.12243080139160156 time for calcul the mask position with numpy : 0.029950857162475586 nb_pixel_total : 36041 time to create 1 rle with old method : 0.04185914993286133 time for calcul the mask position with numpy : 0.029323577880859375 nb_pixel_total : 2391 time to create 1 rle with old method : 0.002807140350341797 time for calcul the mask position with numpy : 0.02901601791381836 nb_pixel_total : 7735 time to create 1 rle with old method : 0.00891566276550293 time for calcul the mask position with numpy : 0.030594587326049805 nb_pixel_total : 23007 time to create 1 rle with old method : 0.03777599334716797 time for calcul the mask position with numpy : 0.0330352783203125 nb_pixel_total : 25889 time to create 1 rle with old method : 0.02959585189819336 time for calcul the mask position with numpy : 0.02904677391052246 nb_pixel_total : 27776 time to create 1 rle with old method : 0.0317683219909668 time for calcul the mask position with numpy : 0.029090166091918945 nb_pixel_total : 32493 time to create 1 rle with old method : 0.03660869598388672 time for calcul the mask position with numpy : 0.029421567916870117 nb_pixel_total : 31935 time to create 1 rle with old method : 0.03568243980407715 time for calcul the mask position with numpy : 0.028909921646118164 nb_pixel_total : 14694 time to create 1 rle with old method : 0.016677141189575195 time for calcul the mask position with numpy : 0.029111623764038086 nb_pixel_total : 61617 time to create 1 rle with old method : 0.06871604919433594 time for calcul the mask position with numpy : 0.029008150100708008 nb_pixel_total : 46738 time to create 1 rle with old method : 0.0534367561340332 time for calcul the mask position with numpy : 0.031013011932373047 nb_pixel_total : 53635 time to create 1 rle with old method : 0.06018781661987305 time for calcul the mask position with numpy : 0.03013467788696289 nb_pixel_total : 15032 time to create 1 rle with old method : 0.0178830623626709 time for calcul the mask position with numpy : 0.03082108497619629 nb_pixel_total : 46566 time to create 1 rle with old method : 0.07554435729980469 time for calcul the mask position with numpy : 0.030303955078125 nb_pixel_total : 76203 time to create 1 rle with old method : 0.08617687225341797 time for calcul the mask position with numpy : 0.02955484390258789 nb_pixel_total : 10166 time to create 1 rle with old method : 0.011752843856811523 create new chi : 4.103962182998657 time to delete rle : 0.0034894943237304688 batch 1 Loaded 95 chid ids of type : 3594 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 20307 TO DO : save crop sub photo not yet done ! save time : 1.36090087890625 nb_obj : 45 nb_hashtags : 5 time to prepare the origin masks : 4.44634485244751 time for calcul the mask position with numpy : 0.4101986885070801 nb_pixel_total : 5107037 time to create 1 rle with new method : 0.9142260551452637 time for calcul the mask position with numpy : 0.02890181541442871 nb_pixel_total : 4466 time to create 1 rle with old method : 0.005146026611328125 time for calcul the mask position with numpy : 0.0292203426361084 nb_pixel_total : 6775 time to create 1 rle with old method : 0.008068084716796875 time for calcul the mask position with numpy : 0.02943897247314453 nb_pixel_total : 6874 time to create 1 rle with old method : 0.007780790328979492 time for calcul the mask position with numpy : 0.030744552612304688 nb_pixel_total : 277117 time to create 1 rle with new method : 0.655858039855957 time for calcul the mask position with numpy : 0.029909610748291016 nb_pixel_total : 45730 time to create 1 rle with old method : 0.05107617378234863 time for calcul the mask position with numpy : 0.028860092163085938 nb_pixel_total : 6993 time to create 1 rle with old method : 0.007970333099365234 time for calcul the mask position with numpy : 0.029473543167114258 nb_pixel_total : 10838 time to create 1 rle with old method : 0.012282609939575195 time for calcul the mask position with numpy : 0.028865814208984375 nb_pixel_total : 9542 time to create 1 rle with old method : 0.010815858840942383 time for calcul the mask position with numpy : 0.029393911361694336 nb_pixel_total : 16770 time to create 1 rle with old method : 0.02094864845275879 time for calcul the mask position with numpy : 0.02942204475402832 nb_pixel_total : 45260 time to create 1 rle with old method : 0.05127835273742676 time for calcul the mask position with numpy : 0.03066873550415039 nb_pixel_total : 30774 time to create 1 rle with old method : 0.03514671325683594 time for calcul the mask position with numpy : 0.029317617416381836 nb_pixel_total : 98602 time to create 1 rle with old method : 0.11046218872070312 time for calcul the mask position with numpy : 0.028934240341186523 nb_pixel_total : 28543 time to create 1 rle with old method : 0.03220486640930176 time for calcul the mask position with numpy : 0.028973102569580078 nb_pixel_total : 9389 time to create 1 rle with old method : 0.010618925094604492 time for calcul the mask position with numpy : 0.029192447662353516 nb_pixel_total : 35732 time to create 1 rle with old method : 0.042023420333862305 time for calcul the mask position with numpy : 0.029233217239379883 nb_pixel_total : 44292 time to create 1 rle with old method : 0.05279278755187988 time for calcul the mask position with numpy : 0.03176450729370117 nb_pixel_total : 27436 time to create 1 rle with old method : 0.03239274024963379 time for calcul the mask position with numpy : 0.029546499252319336 nb_pixel_total : 10358 time to create 1 rle with old method : 0.012777090072631836 time for calcul the mask position with numpy : 0.029339313507080078 nb_pixel_total : 4106 time to create 1 rle with old method : 0.004796504974365234 time for calcul the mask position with numpy : 0.032668113708496094 nb_pixel_total : 228186 time to create 1 rle with new method : 0.6924493312835693 time for calcul the mask position with numpy : 0.029985427856445312 nb_pixel_total : 62190 time to create 1 rle with old method : 0.07085180282592773 time for calcul the mask position with numpy : 0.030756235122680664 nb_pixel_total : 44029 time to create 1 rle with old method : 0.05002236366271973 time for calcul the mask position with numpy : 0.028923749923706055 nb_pixel_total : 31899 time to create 1 rle with old method : 0.03679656982421875 time for calcul the mask position with numpy : 0.029827356338500977 nb_pixel_total : 58951 time to create 1 rle with old method : 0.06591582298278809 time for calcul the mask position with numpy : 0.028908967971801758 nb_pixel_total : 25185 time to create 1 rle with old method : 0.029831886291503906 time for calcul the mask position with numpy : 0.028939247131347656 nb_pixel_total : 21231 time to create 1 rle with old method : 0.02381134033203125 time for calcul the mask position with numpy : 0.029195070266723633 nb_pixel_total : 20645 time to create 1 rle with old method : 0.023326635360717773 time for calcul the mask position with numpy : 0.03201580047607422 nb_pixel_total : 396069 time to create 1 rle with new method : 0.5799736976623535 time for calcul the mask position with numpy : 0.02901601791381836 nb_pixel_total : 36867 time to create 1 rle with old method : 0.04323625564575195 time for calcul the mask position with numpy : 0.029202699661254883 nb_pixel_total : 60326 time to create 1 rle with old method : 0.06856584548950195 time for calcul the mask position with numpy : 0.028983116149902344 nb_pixel_total : 25922 time to create 1 rle with old method : 0.02934408187866211 time for calcul the mask position with numpy : 0.029505252838134766 nb_pixel_total : 16146 time to create 1 rle with old method : 0.01850295066833496 time for calcul the mask position with numpy : 0.02939462661743164 nb_pixel_total : 20505 time to create 1 rle with old method : 0.023576736450195312 time for calcul the mask position with numpy : 0.031171321868896484 nb_pixel_total : 5498 time to create 1 rle with old method : 0.009088277816772461 time for calcul the mask position with numpy : 0.03324556350708008 nb_pixel_total : 25900 time to create 1 rle with old method : 0.033060312271118164 time for calcul the mask position with numpy : 0.02916860580444336 nb_pixel_total : 8110 time to create 1 rle with old method : 0.009383678436279297 time for calcul the mask position with numpy : 0.030974864959716797 nb_pixel_total : 12015 time to create 1 rle with old method : 0.01386260986328125 time for calcul the mask position with numpy : 0.02922344207763672 nb_pixel_total : 11116 time to create 1 rle with old method : 0.013002395629882812 time for calcul the mask position with numpy : 0.02923750877380371 nb_pixel_total : 19735 time to create 1 rle with old method : 0.022413253784179688 time for calcul the mask position with numpy : 0.029093265533447266 nb_pixel_total : 24086 time to create 1 rle with old method : 0.02772688865661621 time for calcul the mask position with numpy : 0.028799057006835938 nb_pixel_total : 675 time to create 1 rle with old method : 0.0008611679077148438 time for calcul the mask position with numpy : 0.02893996238708496 nb_pixel_total : 16771 time to create 1 rle with old method : 0.018828392028808594 time for calcul the mask position with numpy : 0.029296875 nb_pixel_total : 9445 time to create 1 rle with old method : 0.010976314544677734 time for calcul the mask position with numpy : 0.03230619430541992 nb_pixel_total : 38982 time to create 1 rle with old method : 0.04446244239807129 time for calcul the mask position with numpy : 0.029133081436157227 nb_pixel_total : 3122 time to create 1 rle with old method : 0.0037026405334472656 create new chi : 5.893822193145752 time to delete rle : 0.005944490432739258 batch 1 Loaded 91 chid ids of type : 3594 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 24259 TO DO : save crop sub photo not yet done ! save time : 2.535245418548584 nb_obj : 43 nb_hashtags : 5 time to prepare the origin masks : 4.016367435455322 time for calcul the mask position with numpy : 0.4362070560455322 nb_pixel_total : 5789210 time to create 1 rle with new method : 0.779979944229126 time for calcul the mask position with numpy : 0.028795242309570312 nb_pixel_total : 7523 time to create 1 rle with old method : 0.008610248565673828 time for calcul the mask position with numpy : 0.028649091720581055 nb_pixel_total : 18874 time to create 1 rle with old method : 0.021260738372802734 time for calcul the mask position with numpy : 0.028532981872558594 nb_pixel_total : 8465 time to create 1 rle with old method : 0.009617328643798828 time for calcul the mask position with numpy : 0.02861809730529785 nb_pixel_total : 11862 time to create 1 rle with old method : 0.01346731185913086 time for calcul the mask position with numpy : 0.02888774871826172 nb_pixel_total : 24366 time to create 1 rle with old method : 0.027590513229370117 time for calcul the mask position with numpy : 0.028662919998168945 nb_pixel_total : 18371 time to create 1 rle with old method : 0.020939350128173828 time for calcul the mask position with numpy : 0.029191255569458008 nb_pixel_total : 52560 time to create 1 rle with old method : 0.05955910682678223 time for calcul the mask position with numpy : 0.029180288314819336 nb_pixel_total : 28322 time to create 1 rle with old method : 0.03357744216918945 time for calcul the mask position with numpy : 0.028302907943725586 nb_pixel_total : 79558 time to create 1 rle with old method : 0.08980607986450195 time for calcul the mask position with numpy : 0.0286562442779541 nb_pixel_total : 12270 time to create 1 rle with old method : 0.014101743698120117 time for calcul the mask position with numpy : 0.028875350952148438 nb_pixel_total : 11005 time to create 1 rle with old method : 0.012667655944824219 time for calcul the mask position with numpy : 0.02873992919921875 nb_pixel_total : 21776 time to create 1 rle with old method : 0.02468585968017578 time for calcul the mask position with numpy : 0.028607845306396484 nb_pixel_total : 8596 time to create 1 rle with old method : 0.009863853454589844 time for calcul the mask position with numpy : 0.028775453567504883 nb_pixel_total : 31987 time to create 1 rle with old method : 0.03639554977416992 time for calcul the mask position with numpy : 0.028600215911865234 nb_pixel_total : 9338 time to create 1 rle with old method : 0.010591983795166016 time for calcul the mask position with numpy : 0.02889275550842285 nb_pixel_total : 28075 time to create 1 rle with old method : 0.03197216987609863 time for calcul the mask position with numpy : 0.028604984283447266 nb_pixel_total : 10821 time to create 1 rle with old method : 0.012404680252075195 time for calcul the mask position with numpy : 0.0284423828125 nb_pixel_total : 95348 time to create 1 rle with old method : 0.10801911354064941 time for calcul the mask position with numpy : 0.02881598472595215 nb_pixel_total : 46621 time to create 1 rle with old method : 0.05595064163208008 time for calcul the mask position with numpy : 0.030571460723876953 nb_pixel_total : 230337 time to create 1 rle with new method : 0.5213785171508789 time for calcul the mask position with numpy : 0.029417991638183594 nb_pixel_total : 16261 time to create 1 rle with old method : 0.018813133239746094 time for calcul the mask position with numpy : 0.029669523239135742 nb_pixel_total : 23161 time to create 1 rle with old method : 0.028671741485595703 time for calcul the mask position with numpy : 0.029245376586914062 nb_pixel_total : 15564 time to create 1 rle with old method : 0.017659902572631836 time for calcul the mask position with numpy : 0.02933049201965332 nb_pixel_total : 11779 time to create 1 rle with old method : 0.013559341430664062 time for calcul the mask position with numpy : 0.029366254806518555 nb_pixel_total : 33738 time to create 1 rle with old method : 0.038088321685791016 time for calcul the mask position with numpy : 0.0296022891998291 nb_pixel_total : 35165 time to create 1 rle with old method : 0.03955483436584473 time for calcul the mask position with numpy : 0.028856754302978516 nb_pixel_total : 29799 time to create 1 rle with old method : 0.03413796424865723 time for calcul the mask position with numpy : 0.028879880905151367 nb_pixel_total : 23483 time to create 1 rle with old method : 0.026648521423339844 time for calcul the mask position with numpy : 0.02937602996826172 nb_pixel_total : 23201 time to create 1 rle with old method : 0.03717803955078125 time for calcul the mask position with numpy : 0.03286099433898926 nb_pixel_total : 8889 time to create 1 rle with old method : 0.012124300003051758 time for calcul the mask position with numpy : 0.02805924415588379 nb_pixel_total : 10804 time to create 1 rle with old method : 0.012432575225830078 time for calcul the mask position with numpy : 0.029007673263549805 nb_pixel_total : 16329 time to create 1 rle with old method : 0.01857614517211914 time for calcul the mask position with numpy : 0.028942584991455078 nb_pixel_total : 25642 time to create 1 rle with old method : 0.028966426849365234 time for calcul the mask position with numpy : 0.029106855392456055 nb_pixel_total : 42585 time to create 1 rle with old method : 0.046019792556762695 time for calcul the mask position with numpy : 0.028713226318359375 nb_pixel_total : 24036 time to create 1 rle with old method : 0.03893136978149414 time for calcul the mask position with numpy : 0.03314518928527832 nb_pixel_total : 19657 time to create 1 rle with old method : 0.024002790451049805 time for calcul the mask position with numpy : 0.028985261917114258 nb_pixel_total : 14680 time to create 1 rle with old method : 0.01646590232849121 time for calcul the mask position with numpy : 0.02942347526550293 nb_pixel_total : 40943 time to create 1 rle with old method : 0.04991269111633301 time for calcul the mask position with numpy : 0.028989553451538086 nb_pixel_total : 12346 time to create 1 rle with old method : 0.01357412338256836 time for calcul the mask position with numpy : 0.0291595458984375 nb_pixel_total : 22334 time to create 1 rle with old method : 0.02494215965270996 time for calcul the mask position with numpy : 0.028653621673583984 nb_pixel_total : 10804 time to create 1 rle with old method : 0.012256383895874023 time for calcul the mask position with numpy : 0.02940058708190918 nb_pixel_total : 6843 time to create 1 rle with old method : 0.00788736343383789 time for calcul the mask position with numpy : 0.030004501342773438 nb_pixel_total : 36912 time to create 1 rle with old method : 0.041336774826049805 create new chi : 4.249719619750977 time to delete rle : 0.004387855529785156 batch 1 Loaded 87 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 21844 TO DO : save crop sub photo not yet done ! save time : 1.4298911094665527 nb_obj : 20 nb_hashtags : 2 time to prepare the origin masks : 5.947896718978882 time for calcul the mask position with numpy : 0.5267701148986816 nb_pixel_total : 6562203 time to create 1 rle with new method : 0.9270625114440918 time for calcul the mask position with numpy : 0.0222780704498291 nb_pixel_total : 9520 time to create 1 rle with old method : 0.011063575744628906 time for calcul the mask position with numpy : 0.020678997039794922 nb_pixel_total : 44227 time to create 1 rle with old method : 0.05646109580993652 time for calcul the mask position with numpy : 0.021817445755004883 nb_pixel_total : 5593 time to create 1 rle with old method : 0.0064389705657958984 time for calcul the mask position with numpy : 0.021683692932128906 nb_pixel_total : 34844 time to create 1 rle with old method : 0.03924870491027832 time for calcul the mask position with numpy : 0.023717403411865234 nb_pixel_total : 14236 time to create 1 rle with old method : 0.016527175903320312 time for calcul the mask position with numpy : 0.021386146545410156 nb_pixel_total : 26223 time to create 1 rle with old method : 0.03213953971862793 time for calcul the mask position with numpy : 0.027454614639282227 nb_pixel_total : 19739 time to create 1 rle with old method : 0.022669076919555664 time for calcul the mask position with numpy : 0.022118330001831055 nb_pixel_total : 18796 time to create 1 rle with old method : 0.02092719078063965 time for calcul the mask position with numpy : 0.021401405334472656 nb_pixel_total : 20069 time to create 1 rle with old method : 0.022211074829101562 time for calcul the mask position with numpy : 0.020848989486694336 nb_pixel_total : 59411 time to create 1 rle with old method : 0.06536293029785156 time for calcul the mask position with numpy : 0.020374536514282227 nb_pixel_total : 16313 time to create 1 rle with old method : 0.0185394287109375 time for calcul the mask position with numpy : 0.021129608154296875 nb_pixel_total : 19374 time to create 1 rle with old method : 0.021152257919311523 time for calcul the mask position with numpy : 0.021643877029418945 nb_pixel_total : 31034 time to create 1 rle with old method : 0.03457808494567871 time for calcul the mask position with numpy : 0.02120232582092285 nb_pixel_total : 22377 time to create 1 rle with old method : 0.024470090866088867 time for calcul the mask position with numpy : 0.0214996337890625 nb_pixel_total : 36265 time to create 1 rle with old method : 0.05621337890625 time for calcul the mask position with numpy : 0.024281024932861328 nb_pixel_total : 16288 time to create 1 rle with old method : 0.019280195236206055 time for calcul the mask position with numpy : 0.021535634994506836 nb_pixel_total : 11199 time to create 1 rle with old method : 0.012848377227783203 time for calcul the mask position with numpy : 0.023083209991455078 nb_pixel_total : 27290 time to create 1 rle with old method : 0.031063556671142578 time for calcul the mask position with numpy : 0.02223682403564453 nb_pixel_total : 7091 time to create 1 rle with old method : 0.008127450942993164 time for calcul the mask position with numpy : 0.022800683975219727 nb_pixel_total : 48148 time to create 1 rle with old method : 0.05519270896911621 create new chi : 2.516010046005249 time to delete rle : 0.0019497871398925781 batch 1 Loaded 41 chid ids of type : 3594 ++++++++++++++++++++++++++++Number RLEs to save : 11005 TO DO : save crop sub photo not yet done ! save time : 0.8017585277557373 nb_obj : 17 nb_hashtags : 3 time to prepare the origin masks : 9.025418996810913 time for calcul the mask position with numpy : 0.5130808353424072 nb_pixel_total : 6454189 time to create 1 rle with new method : 0.678015947341919 time for calcul the mask position with numpy : 0.026334047317504883 nb_pixel_total : 73737 time to create 1 rle with old method : 0.0799093246459961 time for calcul the mask position with numpy : 0.03298211097717285 nb_pixel_total : 12805 time to create 1 rle with old method : 0.014130830764770508 time for calcul the mask position with numpy : 0.0327606201171875 nb_pixel_total : 9375 time to create 1 rle with old method : 0.010043859481811523 time for calcul the mask position with numpy : 0.033483028411865234 nb_pixel_total : 2465 time to create 1 rle with old method : 0.0028841495513916016 time for calcul the mask position with numpy : 0.03444361686706543 nb_pixel_total : 12816 time to create 1 rle with old method : 0.014693260192871094 time for calcul the mask position with numpy : 0.03598594665527344 nb_pixel_total : 218819 time to create 1 rle with new method : 0.7923295497894287 time for calcul the mask position with numpy : 0.03778791427612305 nb_pixel_total : 46695 time to create 1 rle with old method : 0.06033921241760254 time for calcul the mask position with numpy : 0.03428459167480469 nb_pixel_total : 11223 time to create 1 rle with old method : 0.01341867446899414 time for calcul the mask position with numpy : 0.034330129623413086 nb_pixel_total : 5598 time to create 1 rle with old method : 0.006277799606323242 time for calcul the mask position with numpy : 0.03293585777282715 nb_pixel_total : 9534 time to create 1 rle with old method : 0.010534048080444336 time for calcul the mask position with numpy : 0.03409719467163086 nb_pixel_total : 18002 time to create 1 rle with old method : 0.020630359649658203 time for calcul the mask position with numpy : 0.028454303741455078 nb_pixel_total : 7661 time to create 1 rle with old method : 0.00864720344543457 time for calcul the mask position with numpy : 0.021529436111450195 nb_pixel_total : 93543 time to create 1 rle with old method : 0.10524249076843262 time for calcul the mask position with numpy : 0.02184605598449707 nb_pixel_total : 17328 time to create 1 rle with old method : 0.019133567810058594 time for calcul the mask position with numpy : 0.02237558364868164 nb_pixel_total : 26850 time to create 1 rle with old method : 0.04606056213378906 time for calcul the mask position with numpy : 0.022548913955688477 nb_pixel_total : 12493 time to create 1 rle with old method : 0.015574932098388672 time for calcul the mask position with numpy : 0.023912906646728516 nb_pixel_total : 17107 time to create 1 rle with old method : 0.0206143856048584 create new chi : 2.9988584518432617 time to delete rle : 0.00274658203125 batch 1 Loaded 35 chid ids of type : 3594 +++++++++++++++++++++Number RLEs to save : 10354 TO DO : save crop sub photo not yet done ! save time : 1.7444679737091064 nb_obj : 41 nb_hashtags : 4 time to prepare the origin masks : 3.6659204959869385 time for calcul the mask position with numpy : 0.5326528549194336 nb_pixel_total : 5956115 time to create 1 rle with new method : 0.6585326194763184 time for calcul the mask position with numpy : 0.030318021774291992 nb_pixel_total : 8274 time to create 1 rle with old method : 0.009396076202392578 time for calcul the mask position with numpy : 0.028665542602539062 nb_pixel_total : 31522 time to create 1 rle with old method : 0.0352320671081543 time for calcul the mask position with numpy : 0.02860856056213379 nb_pixel_total : 8087 time to create 1 rle with old method : 0.00920414924621582 time for calcul the mask position with numpy : 0.028563261032104492 nb_pixel_total : 23948 time to create 1 rle with old method : 0.026966094970703125 time for calcul the mask position with numpy : 0.03228116035461426 nb_pixel_total : 30486 time to create 1 rle with old method : 0.034375667572021484 time for calcul the mask position with numpy : 0.028995752334594727 nb_pixel_total : 21280 time to create 1 rle with old method : 0.023894548416137695 time for calcul the mask position with numpy : 0.028882741928100586 nb_pixel_total : 8867 time to create 1 rle with old method : 0.009999752044677734 time for calcul the mask position with numpy : 0.028012514114379883 nb_pixel_total : 11501 time to create 1 rle with old method : 0.012543678283691406 time for calcul the mask position with numpy : 0.02837538719177246 nb_pixel_total : 31888 time to create 1 rle with old method : 0.03524518013000488 time for calcul the mask position with numpy : 0.028104782104492188 nb_pixel_total : 4062 time to create 1 rle with old method : 0.0045070648193359375 time for calcul the mask position with numpy : 0.028173208236694336 nb_pixel_total : 223003 time to create 1 rle with new method : 0.20212626457214355 time for calcul the mask position with numpy : 0.02728891372680664 nb_pixel_total : 11304 time to create 1 rle with old method : 0.012465953826904297 time for calcul the mask position with numpy : 0.02745366096496582 nb_pixel_total : 43291 time to create 1 rle with old method : 0.046975135803222656 time for calcul the mask position with numpy : 0.027306556701660156 nb_pixel_total : 32372 time to create 1 rle with old method : 0.03484988212585449 time for calcul the mask position with numpy : 0.026906490325927734 nb_pixel_total : 54470 time to create 1 rle with old method : 0.058038949966430664 time for calcul the mask position with numpy : 0.027177095413208008 nb_pixel_total : 27 time to create 1 rle with old method : 5.9604644775390625e-05 time for calcul the mask position with numpy : 0.027588844299316406 nb_pixel_total : 44975 time to create 1 rle with old method : 0.04898571968078613 time for calcul the mask position with numpy : 0.027536869049072266 nb_pixel_total : 34865 time to create 1 rle with old method : 0.03655505180358887 time for calcul the mask position with numpy : 0.026813983917236328 nb_pixel_total : 13138 time to create 1 rle with old method : 0.014321565628051758 time for calcul the mask position with numpy : 0.02767634391784668 nb_pixel_total : 13112 time to create 1 rle with old method : 0.014462709426879883 time for calcul the mask position with numpy : 0.02790999412536621 nb_pixel_total : 1962 time to create 1 rle with old method : 0.002338886260986328 time for calcul the mask position with numpy : 0.028498172760009766 nb_pixel_total : 36775 time to create 1 rle with old method : 0.04081130027770996 time for calcul the mask position with numpy : 0.0268404483795166 nb_pixel_total : 12682 time to create 1 rle with old method : 0.014069557189941406 time for calcul the mask position with numpy : 0.02684497833251953 nb_pixel_total : 16434 time to create 1 rle with old method : 0.018283843994140625 time for calcul the mask position with numpy : 0.027478456497192383 nb_pixel_total : 19708 time to create 1 rle with old method : 0.021713972091674805 time for calcul the mask position with numpy : 0.027945756912231445 nb_pixel_total : 38738 time to create 1 rle with old method : 0.041777610778808594 time for calcul the mask position with numpy : 0.02668595314025879 nb_pixel_total : 8989 time to create 1 rle with old method : 0.009491443634033203 time for calcul the mask position with numpy : 0.027195215225219727 nb_pixel_total : 34861 time to create 1 rle with old method : 0.03708171844482422 time for calcul the mask position with numpy : 0.027666330337524414 nb_pixel_total : 23417 time to create 1 rle with old method : 0.025532007217407227 time for calcul the mask position with numpy : 0.026520490646362305 nb_pixel_total : 10665 time to create 1 rle with old method : 0.011335372924804688 time for calcul the mask position with numpy : 0.02676558494567871 nb_pixel_total : 6930 time to create 1 rle with old method : 0.00761866569519043 time for calcul the mask position with numpy : 0.027637243270874023 nb_pixel_total : 12415 time to create 1 rle with old method : 0.013170719146728516 time for calcul the mask position with numpy : 0.02756047248840332 nb_pixel_total : 48073 time to create 1 rle with old method : 0.05212545394897461 time for calcul the mask position with numpy : 0.027113676071166992 nb_pixel_total : 34335 time to create 1 rle with old method : 0.03765392303466797 time for calcul the mask position with numpy : 0.02663278579711914 nb_pixel_total : 30704 time to create 1 rle with old method : 0.03375387191772461 time for calcul the mask position with numpy : 0.027526378631591797 nb_pixel_total : 20817 time to create 1 rle with old method : 0.02196335792541504 time for calcul the mask position with numpy : 0.026706457138061523 nb_pixel_total : 6868 time to create 1 rle with old method : 0.007289409637451172 time for calcul the mask position with numpy : 0.026511430740356445 nb_pixel_total : 14342 time to create 1 rle with old method : 0.01580500602722168 time for calcul the mask position with numpy : 0.027011871337890625 nb_pixel_total : 48664 time to create 1 rle with old method : 0.05224871635437012 time for calcul the mask position with numpy : 0.027022600173950195 nb_pixel_total : 9639 time to create 1 rle with old method : 0.010358572006225586 time for calcul the mask position with numpy : 0.027918100357055664 nb_pixel_total : 6635 time to create 1 rle with old method : 0.007590055465698242 create new chi : 3.529369592666626 time to delete rle : 0.0035507678985595703 batch 1 Loaded 83 chid ids of type : 3594 ++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 18102 TO DO : save crop sub photo not yet done ! save time : 1.2068917751312256 nb_obj : 25 nb_hashtags : 4 time to prepare the origin masks : 9.580434322357178 time for calcul the mask position with numpy : 0.7580547332763672 nb_pixel_total : 5999079 time to create 1 rle with new method : 1.2503907680511475 time for calcul the mask position with numpy : 0.038323402404785156 nb_pixel_total : 56455 time to create 1 rle with old method : 0.06124138832092285 time for calcul the mask position with numpy : 0.033376216888427734 nb_pixel_total : 2445 time to create 1 rle with old method : 0.0027997493743896484 time for calcul the mask position with numpy : 0.03248858451843262 nb_pixel_total : 46011 time to create 1 rle with old method : 0.04951977729797363 time for calcul the mask position with numpy : 0.03294539451599121 nb_pixel_total : 35157 time to create 1 rle with old method : 0.03810429573059082 time for calcul the mask position with numpy : 0.03263592720031738 nb_pixel_total : 36158 time to create 1 rle with old method : 0.038802385330200195 time for calcul the mask position with numpy : 0.02017951011657715 nb_pixel_total : 43298 time to create 1 rle with old method : 0.046352386474609375 time for calcul the mask position with numpy : 0.02104806900024414 nb_pixel_total : 41386 time to create 1 rle with old method : 0.044185638427734375 time for calcul the mask position with numpy : 0.021218538284301758 nb_pixel_total : 5222 time to create 1 rle with old method : 0.0058078765869140625 time for calcul the mask position with numpy : 0.020267486572265625 nb_pixel_total : 21187 time to create 1 rle with old method : 0.023080110549926758 time for calcul the mask position with numpy : 0.020920991897583008 nb_pixel_total : 11459 time to create 1 rle with old method : 0.012418031692504883 time for calcul the mask position with numpy : 0.020682573318481445 nb_pixel_total : 23085 time to create 1 rle with old method : 0.025005578994750977 time for calcul the mask position with numpy : 0.020218849182128906 nb_pixel_total : 60761 time to create 1 rle with old method : 0.06502628326416016 time for calcul the mask position with numpy : 0.020017385482788086 nb_pixel_total : 27374 time to create 1 rle with old method : 0.029503822326660156 time for calcul the mask position with numpy : 0.019746780395507812 nb_pixel_total : 3596 time to create 1 rle with old method : 0.0039882659912109375 time for calcul the mask position with numpy : 0.020408153533935547 nb_pixel_total : 26105 time to create 1 rle with old method : 0.029041051864624023 time for calcul the mask position with numpy : 0.022979736328125 nb_pixel_total : 49922 time to create 1 rle with old method : 0.056966304779052734 time for calcul the mask position with numpy : 0.021685361862182617 nb_pixel_total : 38279 time to create 1 rle with old method : 0.04228639602661133 time for calcul the mask position with numpy : 0.02143406867980957 nb_pixel_total : 75733 time to create 1 rle with old method : 0.08078837394714355 time for calcul the mask position with numpy : 0.021550416946411133 nb_pixel_total : 32191 time to create 1 rle with old method : 0.03460407257080078 time for calcul the mask position with numpy : 0.022327899932861328 nb_pixel_total : 101505 time to create 1 rle with old method : 0.10719919204711914 time for calcul the mask position with numpy : 0.02112269401550293 nb_pixel_total : 82764 time to create 1 rle with old method : 0.09529256820678711 time for calcul the mask position with numpy : 0.022749900817871094 nb_pixel_total : 8838 time to create 1 rle with old method : 0.0094451904296875 time for calcul the mask position with numpy : 0.021615266799926758 nb_pixel_total : 29737 time to create 1 rle with old method : 0.034404754638671875 time for calcul the mask position with numpy : 0.021931886672973633 nb_pixel_total : 179103 time to create 1 rle with new method : 0.6420619487762451 time for calcul the mask position with numpy : 0.020961523056030273 nb_pixel_total : 13390 time to create 1 rle with old method : 0.01412820816040039 create new chi : 4.25011134147644 time to delete rle : 0.002475738525390625 batch 1 Loaded 51 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 15310 TO DO : save crop sub photo not yet done ! save time : 1.0521790981292725 nb_obj : 33 nb_hashtags : 3 time to prepare the origin masks : 4.3484885692596436 time for calcul the mask position with numpy : 0.4075968265533447 nb_pixel_total : 5497335 time to create 1 rle with new method : 0.37401318550109863 time for calcul the mask position with numpy : 0.030420303344726562 nb_pixel_total : 21072 time to create 1 rle with old method : 0.033536434173583984 time for calcul the mask position with numpy : 0.03573942184448242 nb_pixel_total : 226922 time to create 1 rle with new method : 0.7854759693145752 time for calcul the mask position with numpy : 0.029554128646850586 nb_pixel_total : 5455 time to create 1 rle with old method : 0.006267070770263672 time for calcul the mask position with numpy : 0.029061317443847656 nb_pixel_total : 9916 time to create 1 rle with old method : 0.011497259140014648 time for calcul the mask position with numpy : 0.029536724090576172 nb_pixel_total : 96917 time to create 1 rle with old method : 0.1081399917602539 time for calcul the mask position with numpy : 0.029120683670043945 nb_pixel_total : 14423 time to create 1 rle with old method : 0.016220569610595703 time for calcul the mask position with numpy : 0.029542207717895508 nb_pixel_total : 37585 time to create 1 rle with old method : 0.04271411895751953 time for calcul the mask position with numpy : 0.029366016387939453 nb_pixel_total : 127864 time to create 1 rle with old method : 0.1424856185913086 time for calcul the mask position with numpy : 0.028604984283447266 nb_pixel_total : 13724 time to create 1 rle with old method : 0.01621699333190918 time for calcul the mask position with numpy : 0.029196500778198242 nb_pixel_total : 33537 time to create 1 rle with old method : 0.03777170181274414 time for calcul the mask position with numpy : 0.029262781143188477 nb_pixel_total : 8615 time to create 1 rle with old method : 0.009839296340942383 time for calcul the mask position with numpy : 0.028702497482299805 nb_pixel_total : 31526 time to create 1 rle with old method : 0.03568434715270996 time for calcul the mask position with numpy : 0.02910757064819336 nb_pixel_total : 52754 time to create 1 rle with old method : 0.05988454818725586 time for calcul the mask position with numpy : 0.029348134994506836 nb_pixel_total : 3826 time to create 1 rle with old method : 0.006697654724121094 time for calcul the mask position with numpy : 0.032587289810180664 nb_pixel_total : 118176 time to create 1 rle with old method : 0.13915252685546875 time for calcul the mask position with numpy : 0.03292703628540039 nb_pixel_total : 24778 time to create 1 rle with old method : 0.028203964233398438 time for calcul the mask position with numpy : 0.030410051345825195 nb_pixel_total : 197020 time to create 1 rle with new method : 0.6732733249664307 time for calcul the mask position with numpy : 0.02956700325012207 nb_pixel_total : 4087 time to create 1 rle with old method : 0.0052106380462646484 time for calcul the mask position with numpy : 0.0298612117767334 nb_pixel_total : 24915 time to create 1 rle with old method : 0.02877950668334961 time for calcul the mask position with numpy : 0.03151822090148926 nb_pixel_total : 46770 time to create 1 rle with old method : 0.05875253677368164 time for calcul the mask position with numpy : 0.03321266174316406 nb_pixel_total : 107969 time to create 1 rle with old method : 0.12406563758850098 time for calcul the mask position with numpy : 0.029732465744018555 nb_pixel_total : 64732 time to create 1 rle with old method : 0.07930254936218262 time for calcul the mask position with numpy : 0.02959442138671875 nb_pixel_total : 17307 time to create 1 rle with old method : 0.022628307342529297 time for calcul the mask position with numpy : 0.030236005783081055 nb_pixel_total : 24047 time to create 1 rle with old method : 0.028208494186401367 time for calcul the mask position with numpy : 0.02957749366760254 nb_pixel_total : 31235 time to create 1 rle with old method : 0.035324811935424805 time for calcul the mask position with numpy : 0.03022146224975586 nb_pixel_total : 115451 time to create 1 rle with old method : 0.13364458084106445 time for calcul the mask position with numpy : 0.02893543243408203 nb_pixel_total : 16210 time to create 1 rle with old method : 0.020351648330688477 time for calcul the mask position with numpy : 0.02917003631591797 nb_pixel_total : 8546 time to create 1 rle with old method : 0.009705543518066406 time for calcul the mask position with numpy : 0.02924942970275879 nb_pixel_total : 17167 time to create 1 rle with old method : 0.019141674041748047 time for calcul the mask position with numpy : 0.029982328414916992 nb_pixel_total : 24750 time to create 1 rle with old method : 0.02927088737487793 time for calcul the mask position with numpy : 0.030550241470336914 nb_pixel_total : 6147 time to create 1 rle with old method : 0.010363578796386719 time for calcul the mask position with numpy : 0.033211708068847656 nb_pixel_total : 10089 time to create 1 rle with old method : 0.01656317710876465 time for calcul the mask position with numpy : 0.030241727828979492 nb_pixel_total : 9373 time to create 1 rle with old method : 0.010863065719604492 create new chi : 4.642654895782471 time to delete rle : 0.0035538673400878906 batch 1 Loaded 67 chid ids of type : 3594 ++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 19819 TO DO : save crop sub photo not yet done ! save time : 1.3958933353424072 nb_obj : 23 nb_hashtags : 4 time to prepare the origin masks : 9.60894250869751 time for calcul the mask position with numpy : 0.820350170135498 nb_pixel_total : 6186345 time to create 1 rle with new method : 0.5842788219451904 time for calcul the mask position with numpy : 0.02220010757446289 nb_pixel_total : 299771 time to create 1 rle with new method : 1.1762628555297852 time for calcul the mask position with numpy : 0.03316855430603027 nb_pixel_total : 22706 time to create 1 rle with old method : 0.024804115295410156 time for calcul the mask position with numpy : 0.03374648094177246 nb_pixel_total : 56794 time to create 1 rle with old method : 0.06421685218811035 time for calcul the mask position with numpy : 0.03221535682678223 nb_pixel_total : 36238 time to create 1 rle with old method : 0.04064059257507324 time for calcul the mask position with numpy : 0.028277873992919922 nb_pixel_total : 10708 time to create 1 rle with old method : 0.01223611831665039 time for calcul the mask position with numpy : 0.026125192642211914 nb_pixel_total : 13418 time to create 1 rle with old method : 0.015268802642822266 time for calcul the mask position with numpy : 0.02266693115234375 nb_pixel_total : 10652 time to create 1 rle with old method : 0.012163400650024414 time for calcul the mask position with numpy : 0.022861957550048828 nb_pixel_total : 13930 time to create 1 rle with old method : 0.015872955322265625 time for calcul the mask position with numpy : 0.023077726364135742 nb_pixel_total : 26480 time to create 1 rle with old method : 0.03055882453918457 time for calcul the mask position with numpy : 0.022197961807250977 nb_pixel_total : 12201 time to create 1 rle with old method : 0.01384115219116211 time for calcul the mask position with numpy : 0.023305892944335938 nb_pixel_total : 28657 time to create 1 rle with old method : 0.03260016441345215 time for calcul the mask position with numpy : 0.02194046974182129 nb_pixel_total : 19425 time to create 1 rle with old method : 0.022400379180908203 time for calcul the mask position with numpy : 0.022359609603881836 nb_pixel_total : 12683 time to create 1 rle with old method : 0.014415740966796875 time for calcul the mask position with numpy : 0.02220439910888672 nb_pixel_total : 7178 time to create 1 rle with old method : 0.008258819580078125 time for calcul the mask position with numpy : 0.024299144744873047 nb_pixel_total : 11858 time to create 1 rle with old method : 0.015052318572998047 time for calcul the mask position with numpy : 0.0250701904296875 nb_pixel_total : 12038 time to create 1 rle with old method : 0.01911163330078125 time for calcul the mask position with numpy : 0.02421879768371582 nb_pixel_total : 17278 time to create 1 rle with old method : 0.021718978881835938 time for calcul the mask position with numpy : 0.02223658561706543 nb_pixel_total : 119000 time to create 1 rle with old method : 0.13359594345092773 time for calcul the mask position with numpy : 0.02304840087890625 nb_pixel_total : 30435 time to create 1 rle with old method : 0.034365177154541016 time for calcul the mask position with numpy : 0.022500991821289062 nb_pixel_total : 5499 time to create 1 rle with old method : 0.006358146667480469 time for calcul the mask position with numpy : 0.02227020263671875 nb_pixel_total : 29707 time to create 1 rle with old method : 0.033679962158203125 time for calcul the mask position with numpy : 0.02237677574157715 nb_pixel_total : 39812 time to create 1 rle with old method : 0.04396367073059082 time for calcul the mask position with numpy : 0.02212691307067871 nb_pixel_total : 27427 time to create 1 rle with old method : 0.03076791763305664 create new chi : 3.8467025756835938 time to delete rle : 0.001668691635131836 batch 1 Loaded 47 chid ids of type : 3594 +++++++++++++++++++++++Number RLEs to save : 11004 TO DO : save crop sub photo not yet done ! save time : 2.1354146003723145 nb_obj : 16 nb_hashtags : 3 time to prepare the origin masks : 9.076529264450073 time for calcul the mask position with numpy : 0.7318694591522217 nb_pixel_total : 6206751 time to create 1 rle with new method : 0.6773102283477783 time for calcul the mask position with numpy : 0.04174232482910156 nb_pixel_total : 9139 time to create 1 rle with old method : 0.010528564453125 time for calcul the mask position with numpy : 0.03544330596923828 nb_pixel_total : 52393 time to create 1 rle with old method : 0.059350013732910156 time for calcul the mask position with numpy : 0.03592348098754883 nb_pixel_total : 9049 time to create 1 rle with old method : 0.010326862335205078 time for calcul the mask position with numpy : 0.03190732002258301 nb_pixel_total : 36045 time to create 1 rle with old method : 0.050214529037475586 time for calcul the mask position with numpy : 0.025228261947631836 nb_pixel_total : 47446 time to create 1 rle with old method : 0.07893943786621094 time for calcul the mask position with numpy : 0.02475714683532715 nb_pixel_total : 16157 time to create 1 rle with old method : 0.026558876037597656 time for calcul the mask position with numpy : 0.025397539138793945 nb_pixel_total : 331114 time to create 1 rle with new method : 1.0875880718231201 time for calcul the mask position with numpy : 0.021677017211914062 nb_pixel_total : 19102 time to create 1 rle with old method : 0.021658897399902344 time for calcul the mask position with numpy : 0.024054527282714844 nb_pixel_total : 98527 time to create 1 rle with old method : 0.1129145622253418 time for calcul the mask position with numpy : 0.023190736770629883 nb_pixel_total : 36753 time to create 1 rle with old method : 0.04285883903503418 time for calcul the mask position with numpy : 0.023082494735717773 nb_pixel_total : 14148 time to create 1 rle with old method : 0.02326488494873047 time for calcul the mask position with numpy : 0.023870468139648438 nb_pixel_total : 88769 time to create 1 rle with old method : 0.10684013366699219 time for calcul the mask position with numpy : 0.021748781204223633 nb_pixel_total : 35606 time to create 1 rle with old method : 0.04076218605041504 time for calcul the mask position with numpy : 0.022748470306396484 nb_pixel_total : 8160 time to create 1 rle with old method : 0.00923919677734375 time for calcul the mask position with numpy : 0.022091388702392578 nb_pixel_total : 33130 time to create 1 rle with old method : 0.03696155548095703 time for calcul the mask position with numpy : 0.024080991744995117 nb_pixel_total : 7951 time to create 1 rle with old method : 0.01311635971069336 create new chi : 3.6339199542999268 time to delete rle : 0.0029425621032714844 batch 1 Loaded 33 chid ids of type : 3594 ++++++++++++++++++Number RLEs to save : 10255 TO DO : save crop sub photo not yet done ! save time : 0.6282384395599365 nb_obj : 11 nb_hashtags : 4 time to prepare the origin masks : 6.56325888633728 time for calcul the mask position with numpy : 0.9860613346099854 nb_pixel_total : 6143808 time to create 1 rle with new method : 0.48084378242492676 time for calcul the mask position with numpy : 0.037047386169433594 nb_pixel_total : 110397 time to create 1 rle with old method : 0.1302809715270996 time for calcul the mask position with numpy : 0.025382518768310547 nb_pixel_total : 21558 time to create 1 rle with old method : 0.02447032928466797 time for calcul the mask position with numpy : 0.02262258529663086 nb_pixel_total : 48152 time to create 1 rle with old method : 0.05970120429992676 time for calcul the mask position with numpy : 0.023899555206298828 nb_pixel_total : 4466 time to create 1 rle with old method : 0.005243539810180664 time for calcul the mask position with numpy : 0.026419639587402344 nb_pixel_total : 14563 time to create 1 rle with old method : 0.016612768173217773 time for calcul the mask position with numpy : 0.024128437042236328 nb_pixel_total : 7014 time to create 1 rle with old method : 0.008044958114624023 time for calcul the mask position with numpy : 0.024957656860351562 nb_pixel_total : 8372 time to create 1 rle with old method : 0.009712457656860352 time for calcul the mask position with numpy : 0.04169940948486328 nb_pixel_total : 582399 time to create 1 rle with new method : 0.5490753650665283 time for calcul the mask position with numpy : 0.036316871643066406 nb_pixel_total : 32619 time to create 1 rle with old method : 0.0402677059173584 time for calcul the mask position with numpy : 0.03549003601074219 nb_pixel_total : 51740 time to create 1 rle with old method : 0.06306838989257812 time for calcul the mask position with numpy : 0.04087066650390625 nb_pixel_total : 25152 time to create 1 rle with old method : 0.04046058654785156 create new chi : 2.8211774826049805 time to delete rle : 0.0018787384033203125 batch 1 Loaded 23 chid ids of type : 3594 ++++++++++++++++++Number RLEs to save : 8598 TO DO : save crop sub photo not yet done ! save time : 0.6540079116821289 nb_obj : 57 nb_hashtags : 5 time to prepare the origin masks : 4.753248691558838 time for calcul the mask position with numpy : 0.5071558952331543 nb_pixel_total : 5308334 time to create 1 rle with new method : 0.7023141384124756 time for calcul the mask position with numpy : 0.0293581485748291 nb_pixel_total : 15206 time to create 1 rle with old method : 0.017858505249023438 time for calcul the mask position with numpy : 0.029722929000854492 nb_pixel_total : 21267 time to create 1 rle with old method : 0.024431705474853516 time for calcul the mask position with numpy : 0.029294967651367188 nb_pixel_total : 19487 time to create 1 rle with old method : 0.022918224334716797 time for calcul the mask position with numpy : 0.03106546401977539 nb_pixel_total : 3540 time to create 1 rle with old method : 0.0043048858642578125 time for calcul the mask position with numpy : 0.03034234046936035 nb_pixel_total : 111342 time to create 1 rle with old method : 0.12439560890197754 time for calcul the mask position with numpy : 0.029729604721069336 nb_pixel_total : 24877 time to create 1 rle with old method : 0.02814650535583496 time for calcul the mask position with numpy : 0.031310319900512695 nb_pixel_total : 18582 time to create 1 rle with old method : 0.021001815795898438 time for calcul the mask position with numpy : 0.02939915657043457 nb_pixel_total : 25760 time to create 1 rle with old method : 0.028917312622070312 time for calcul the mask position with numpy : 0.030194759368896484 nb_pixel_total : 90453 time to create 1 rle with old method : 0.1165323257446289 time for calcul the mask position with numpy : 0.03515267372131348 nb_pixel_total : 7814 time to create 1 rle with old method : 0.009026765823364258 time for calcul the mask position with numpy : 0.030248165130615234 nb_pixel_total : 67174 time to create 1 rle with old method : 0.07634902000427246 time for calcul the mask position with numpy : 0.029566049575805664 nb_pixel_total : 12778 time to create 1 rle with old method : 0.016335487365722656 time for calcul the mask position with numpy : 0.033841609954833984 nb_pixel_total : 22341 time to create 1 rle with old method : 0.026498079299926758 time for calcul the mask position with numpy : 0.030734539031982422 nb_pixel_total : 28584 time to create 1 rle with old method : 0.03236246109008789 time for calcul the mask position with numpy : 0.03020334243774414 nb_pixel_total : 15849 time to create 1 rle with old method : 0.018220186233520508 time for calcul the mask position with numpy : 0.029919147491455078 nb_pixel_total : 16056 time to create 1 rle with old method : 0.018354177474975586 time for calcul the mask position with numpy : 0.03131675720214844 nb_pixel_total : 146596 time to create 1 rle with old method : 0.165785551071167 time for calcul the mask position with numpy : 0.028983592987060547 nb_pixel_total : 9958 time to create 1 rle with old method : 0.011171102523803711 time for calcul the mask position with numpy : 0.030216693878173828 nb_pixel_total : 14994 time to create 1 rle with old method : 0.0170438289642334 time for calcul the mask position with numpy : 0.030670166015625 nb_pixel_total : 44484 time to create 1 rle with old method : 0.05105757713317871 time for calcul the mask position with numpy : 0.029689550399780273 nb_pixel_total : 23938 time to create 1 rle with old method : 0.027318477630615234 time for calcul the mask position with numpy : 0.037809133529663086 nb_pixel_total : 91064 time to create 1 rle with old method : 0.10202383995056152 time for calcul the mask position with numpy : 0.029559850692749023 nb_pixel_total : 14475 time to create 1 rle with old method : 0.017345905303955078 time for calcul the mask position with numpy : 0.029758930206298828 nb_pixel_total : 27567 time to create 1 rle with old method : 0.03147268295288086 time for calcul the mask position with numpy : 0.0312042236328125 nb_pixel_total : 92312 time to create 1 rle with old method : 0.10533380508422852 time for calcul the mask position with numpy : 0.030710697174072266 nb_pixel_total : 2850 time to create 1 rle with old method : 0.003795623779296875 time for calcul the mask position with numpy : 0.0319361686706543 nb_pixel_total : 59698 time to create 1 rle with old method : 0.07166743278503418 time for calcul the mask position with numpy : 0.03203129768371582 nb_pixel_total : 32812 time to create 1 rle with old method : 0.03682589530944824 time for calcul the mask position with numpy : 0.029592275619506836 nb_pixel_total : 90690 time to create 1 rle with old method : 0.1022336483001709 time for calcul the mask position with numpy : 0.02999114990234375 nb_pixel_total : 22494 time to create 1 rle with old method : 0.02793741226196289 time for calcul the mask position with numpy : 0.03278231620788574 nb_pixel_total : 43485 time to create 1 rle with old method : 0.04947090148925781 time for calcul the mask position with numpy : 0.029844045639038086 nb_pixel_total : 32941 time to create 1 rle with old method : 0.04722762107849121 time for calcul the mask position with numpy : 0.03390860557556152 nb_pixel_total : 47970 time to create 1 rle with old method : 0.05936288833618164 time for calcul the mask position with numpy : 0.02991461753845215 nb_pixel_total : 33120 time to create 1 rle with old method : 0.037418365478515625 time for calcul the mask position with numpy : 0.03003382682800293 nb_pixel_total : 32854 time to create 1 rle with old method : 0.03734612464904785 time for calcul the mask position with numpy : 0.03091144561767578 nb_pixel_total : 22425 time to create 1 rle with old method : 0.025682449340820312 time for calcul the mask position with numpy : 0.0297393798828125 nb_pixel_total : 31766 time to create 1 rle with old method : 0.03599143028259277 time for calcul the mask position with numpy : 0.028917551040649414 nb_pixel_total : 15621 time to create 1 rle with old method : 0.0177152156829834 time for calcul the mask position with numpy : 0.029138565063476562 nb_pixel_total : 4796 time to create 1 rle with old method : 0.0054264068603515625 time for calcul the mask position with numpy : 0.029381513595581055 nb_pixel_total : 32963 time to create 1 rle with old method : 0.0377202033996582 time for calcul the mask position with numpy : 0.03028726577758789 nb_pixel_total : 12081 time to create 1 rle with old method : 0.013713598251342773 time for calcul the mask position with numpy : 0.03253316879272461 nb_pixel_total : 18204 time to create 1 rle with old method : 0.021033287048339844 time for calcul the mask position with numpy : 0.029660701751708984 nb_pixel_total : 29002 time to create 1 rle with old method : 0.03300333023071289 time for calcul the mask position with numpy : 0.02950453758239746 nb_pixel_total : 6693 time to create 1 rle with old method : 0.00811457633972168 time for calcul the mask position with numpy : 0.030915021896362305 nb_pixel_total : 10053 time to create 1 rle with old method : 0.014936447143554688 time for calcul the mask position with numpy : 0.03495979309082031 nb_pixel_total : 14134 time to create 1 rle with old method : 0.023094892501831055 time for calcul the mask position with numpy : 0.03401970863342285 nb_pixel_total : 4820 time to create 1 rle with old method : 0.005510807037353516 time for calcul the mask position with numpy : 0.029922008514404297 nb_pixel_total : 13770 time to create 1 rle with old method : 0.016400814056396484 time for calcul the mask position with numpy : 0.03003382682800293 nb_pixel_total : 15510 time to create 1 rle with old method : 0.018079757690429688 time for calcul the mask position with numpy : 0.03076648712158203 nb_pixel_total : 13450 time to create 1 rle with old method : 0.015492677688598633 time for calcul the mask position with numpy : 0.030029773712158203 nb_pixel_total : 15062 time to create 1 rle with old method : 0.017934083938598633 time for calcul the mask position with numpy : 0.030605077743530273 nb_pixel_total : 44775 time to create 1 rle with old method : 0.05941939353942871 time for calcul the mask position with numpy : 0.03389263153076172 nb_pixel_total : 14035 time to create 1 rle with old method : 0.023369312286376953 time for calcul the mask position with numpy : 0.0307619571685791 nb_pixel_total : 20919 time to create 1 rle with old method : 0.023591279983520508 time for calcul the mask position with numpy : 0.03188300132751465 nb_pixel_total : 9294 time to create 1 rle with old method : 0.010675907135009766 time for calcul the mask position with numpy : 0.03036212921142578 nb_pixel_total : 18585 time to create 1 rle with old method : 0.021286964416503906 time for calcul the mask position with numpy : 0.03022003173828125 nb_pixel_total : 8536 time to create 1 rle with old method : 0.009774923324584961 create new chi : 5.070840120315552 time to delete rle : 0.011126518249511719 batch 1 Loaded 115 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 29400 TO DO : save crop sub photo not yet done ! save time : 3.093029499053955 nb_obj : 58 nb_hashtags : 4 time to prepare the origin masks : 4.798532247543335 time for calcul the mask position with numpy : 0.47479748725891113 nb_pixel_total : 5297126 time to create 1 rle with new method : 0.5204336643218994 time for calcul the mask position with numpy : 0.03361821174621582 nb_pixel_total : 58962 time to create 1 rle with old method : 0.0674123764038086 time for calcul the mask position with numpy : 0.03310060501098633 nb_pixel_total : 56528 time to create 1 rle with old method : 0.06384682655334473 time for calcul the mask position with numpy : 0.03081369400024414 nb_pixel_total : 11871 time to create 1 rle with old method : 0.015783309936523438 time for calcul the mask position with numpy : 0.03255438804626465 nb_pixel_total : 11175 time to create 1 rle with old method : 0.013166666030883789 time for calcul the mask position with numpy : 0.03026103973388672 nb_pixel_total : 2759 time to create 1 rle with old method : 0.004632234573364258 time for calcul the mask position with numpy : 0.0338132381439209 nb_pixel_total : 20846 time to create 1 rle with old method : 0.03314518928527832 time for calcul the mask position with numpy : 0.030528545379638672 nb_pixel_total : 12233 time to create 1 rle with old method : 0.014324188232421875 time for calcul the mask position with numpy : 0.03334212303161621 nb_pixel_total : 18298 time to create 1 rle with old method : 0.029683828353881836 time for calcul the mask position with numpy : 0.03391456604003906 nb_pixel_total : 137378 time to create 1 rle with old method : 0.15889596939086914 time for calcul the mask position with numpy : 0.031606197357177734 nb_pixel_total : 19412 time to create 1 rle with old method : 0.022408723831176758 time for calcul the mask position with numpy : 0.030373096466064453 nb_pixel_total : 8012 time to create 1 rle with old method : 0.009191751480102539 time for calcul the mask position with numpy : 0.03036665916442871 nb_pixel_total : 19945 time to create 1 rle with old method : 0.023160457611083984 time for calcul the mask position with numpy : 0.030549049377441406 nb_pixel_total : 12863 time to create 1 rle with old method : 0.015155553817749023 time for calcul the mask position with numpy : 0.03197145462036133 nb_pixel_total : 121067 time to create 1 rle with old method : 0.1377553939819336 time for calcul the mask position with numpy : 0.03017282485961914 nb_pixel_total : 22532 time to create 1 rle with old method : 0.025631427764892578 time for calcul the mask position with numpy : 0.02986431121826172 nb_pixel_total : 13791 time to create 1 rle with old method : 0.016096830368041992 time for calcul the mask position with numpy : 0.03033161163330078 nb_pixel_total : 5281 time to create 1 rle with old method : 0.0063855648040771484 time for calcul the mask position with numpy : 0.033284902572631836 nb_pixel_total : 11157 time to create 1 rle with old method : 0.014301061630249023 time for calcul the mask position with numpy : 0.031507253646850586 nb_pixel_total : 24972 time to create 1 rle with old method : 0.02936267852783203 time for calcul the mask position with numpy : 0.03374218940734863 nb_pixel_total : 12425 time to create 1 rle with old method : 0.014487028121948242 time for calcul the mask position with numpy : 0.033286094665527344 nb_pixel_total : 92846 time to create 1 rle with old method : 0.11003804206848145 time for calcul the mask position with numpy : 0.031181812286376953 nb_pixel_total : 15690 time to create 1 rle with old method : 0.018285512924194336 time for calcul the mask position with numpy : 0.03229641914367676 nb_pixel_total : 34358 time to create 1 rle with old method : 0.04253268241882324 time for calcul the mask position with numpy : 0.03169417381286621 nb_pixel_total : 20240 time to create 1 rle with old method : 0.023834943771362305 time for calcul the mask position with numpy : 0.030948877334594727 nb_pixel_total : 8680 time to create 1 rle with old method : 0.011675357818603516 time for calcul the mask position with numpy : 0.036405086517333984 nb_pixel_total : 176688 time to create 1 rle with new method : 0.5296111106872559 time for calcul the mask position with numpy : 0.03586697578430176 nb_pixel_total : 23279 time to create 1 rle with old method : 0.028171300888061523 time for calcul the mask position with numpy : 0.0364382266998291 nb_pixel_total : 10862 time to create 1 rle with old method : 0.012776851654052734 time for calcul the mask position with numpy : 0.03235912322998047 nb_pixel_total : 25042 time to create 1 rle with old method : 0.029012441635131836 time for calcul the mask position with numpy : 0.03161215782165527 nb_pixel_total : 17096 time to create 1 rle with old method : 0.023255109786987305 time for calcul the mask position with numpy : 0.03524947166442871 nb_pixel_total : 51340 time to create 1 rle with old method : 0.06834983825683594 time for calcul the mask position with numpy : 0.03220057487487793 nb_pixel_total : 20400 time to create 1 rle with old method : 0.02405834197998047 time for calcul the mask position with numpy : 0.03128552436828613 nb_pixel_total : 53324 time to create 1 rle with old method : 0.06148076057434082 time for calcul the mask position with numpy : 0.030366182327270508 nb_pixel_total : 24549 time to create 1 rle with old method : 0.02835845947265625 time for calcul the mask position with numpy : 0.030437469482421875 nb_pixel_total : 38423 time to create 1 rle with old method : 0.044000864028930664 time for calcul the mask position with numpy : 0.031248807907104492 nb_pixel_total : 69950 time to create 1 rle with old method : 0.07959532737731934 time for calcul the mask position with numpy : 0.030690908432006836 nb_pixel_total : 76992 time to create 1 rle with old method : 0.08659887313842773 time for calcul the mask position with numpy : 0.03249955177307129 nb_pixel_total : 17642 time to create 1 rle with old method : 0.020256519317626953 time for calcul the mask position with numpy : 0.029755115509033203 nb_pixel_total : 18319 time to create 1 rle with old method : 0.02108025550842285 time for calcul the mask position with numpy : 0.03168678283691406 nb_pixel_total : 25822 time to create 1 rle with old method : 0.038344621658325195 time for calcul the mask position with numpy : 0.03358578681945801 nb_pixel_total : 27026 time to create 1 rle with old method : 0.03699159622192383 time for calcul the mask position with numpy : 0.02942800521850586 nb_pixel_total : 18800 time to create 1 rle with old method : 0.023908138275146484 time for calcul the mask position with numpy : 0.029773950576782227 nb_pixel_total : 9850 time to create 1 rle with old method : 0.01141214370727539 time for calcul the mask position with numpy : 0.03097987174987793 nb_pixel_total : 6964 time to create 1 rle with old method : 0.007986068725585938 time for calcul the mask position with numpy : 0.029608726501464844 nb_pixel_total : 38597 time to create 1 rle with old method : 0.04337358474731445 time for calcul the mask position with numpy : 0.02933979034423828 nb_pixel_total : 5460 time to create 1 rle with old method : 0.006349802017211914 time for calcul the mask position with numpy : 0.030245304107666016 nb_pixel_total : 1936 time to create 1 rle with old method : 0.002284526824951172 time for calcul the mask position with numpy : 0.029462814331054688 nb_pixel_total : 3915 time to create 1 rle with old method : 0.004705667495727539 time for calcul the mask position with numpy : 0.031159400939941406 nb_pixel_total : 89960 time to create 1 rle with old method : 0.10248231887817383 time for calcul the mask position with numpy : 0.029562950134277344 nb_pixel_total : 9871 time to create 1 rle with old method : 0.013900995254516602 time for calcul the mask position with numpy : 0.03110480308532715 nb_pixel_total : 10959 time to create 1 rle with old method : 0.012851953506469727 time for calcul the mask position with numpy : 0.03005504608154297 nb_pixel_total : 10287 time to create 1 rle with old method : 0.012397050857543945 time for calcul the mask position with numpy : 0.03180837631225586 nb_pixel_total : 25978 time to create 1 rle with old method : 0.031154870986938477 time for calcul the mask position with numpy : 0.02950286865234375 nb_pixel_total : 27185 time to create 1 rle with old method : 0.031633853912353516 time for calcul the mask position with numpy : 0.029518842697143555 nb_pixel_total : 12038 time to create 1 rle with old method : 0.01414346694946289 time for calcul the mask position with numpy : 0.029820919036865234 nb_pixel_total : 10737 time to create 1 rle with old method : 0.012481451034545898 time for calcul the mask position with numpy : 0.029409170150756836 nb_pixel_total : 13260 time to create 1 rle with old method : 0.015260934829711914 time for calcul the mask position with numpy : 0.02941107749938965 nb_pixel_total : 7242 time to create 1 rle with old method : 0.0084075927734375 create new chi : 5.306039810180664 time to delete rle : 0.004564523696899414 batch 1 Loaded 117 chid ids of type : 3594 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 27716 TO DO : save crop sub photo not yet done ! save time : 10.009813785552979 nb_obj : 37 nb_hashtags : 5 time to prepare the origin masks : 4.210740089416504 time for calcul the mask position with numpy : 0.6172926425933838 nb_pixel_total : 5952313 time to create 1 rle with new method : 0.8672938346862793 time for calcul the mask position with numpy : 0.02982807159423828 nb_pixel_total : 15764 time to create 1 rle with old method : 0.019441604614257812 time for calcul the mask position with numpy : 0.03220963478088379 nb_pixel_total : 25389 time to create 1 rle with old method : 0.030755043029785156 time for calcul the mask position with numpy : 0.029282331466674805 nb_pixel_total : 22585 time to create 1 rle with old method : 0.025508642196655273 time for calcul the mask position with numpy : 0.029305219650268555 nb_pixel_total : 44817 time to create 1 rle with old method : 0.050400495529174805 time for calcul the mask position with numpy : 0.029427766799926758 nb_pixel_total : 19936 time to create 1 rle with old method : 0.03294253349304199 time for calcul the mask position with numpy : 0.03355908393859863 nb_pixel_total : 27248 time to create 1 rle with old method : 0.03579902648925781 time for calcul the mask position with numpy : 0.02950906753540039 nb_pixel_total : 90063 time to create 1 rle with old method : 0.10148096084594727 time for calcul the mask position with numpy : 0.028946876525878906 nb_pixel_total : 22916 time to create 1 rle with old method : 0.026407480239868164 time for calcul the mask position with numpy : 0.029672861099243164 nb_pixel_total : 17273 time to create 1 rle with old method : 0.0202486515045166 time for calcul the mask position with numpy : 0.030211448669433594 nb_pixel_total : 55401 time to create 1 rle with old method : 0.06316828727722168 time for calcul the mask position with numpy : 0.02916097640991211 nb_pixel_total : 12928 time to create 1 rle with old method : 0.014791011810302734 time for calcul the mask position with numpy : 0.028946399688720703 nb_pixel_total : 17769 time to create 1 rle with old method : 0.020439624786376953 time for calcul the mask position with numpy : 0.029047489166259766 nb_pixel_total : 15873 time to create 1 rle with old method : 0.018053054809570312 time for calcul the mask position with numpy : 0.028800010681152344 nb_pixel_total : 16238 time to create 1 rle with old method : 0.01864337921142578 time for calcul the mask position with numpy : 0.02889227867126465 nb_pixel_total : 22490 time to create 1 rle with old method : 0.025499820709228516 time for calcul the mask position with numpy : 0.03038191795349121 nb_pixel_total : 244515 time to create 1 rle with new method : 0.6666786670684814 time for calcul the mask position with numpy : 0.029422283172607422 nb_pixel_total : 14002 time to create 1 rle with old method : 0.01643657684326172 time for calcul the mask position with numpy : 0.02994990348815918 nb_pixel_total : 24566 time to create 1 rle with old method : 0.03104090690612793 time for calcul the mask position with numpy : 0.03043341636657715 nb_pixel_total : 17385 time to create 1 rle with old method : 0.01987600326538086 time for calcul the mask position with numpy : 0.03518223762512207 nb_pixel_total : 26702 time to create 1 rle with old method : 0.03838753700256348 time for calcul the mask position with numpy : 0.035573720932006836 nb_pixel_total : 8713 time to create 1 rle with old method : 0.011211156845092773 time for calcul the mask position with numpy : 0.030486106872558594 nb_pixel_total : 42229 time to create 1 rle with old method : 0.0483856201171875 time for calcul the mask position with numpy : 0.02967238426208496 nb_pixel_total : 9634 time to create 1 rle with old method : 0.011787891387939453 time for calcul the mask position with numpy : 0.030300378799438477 nb_pixel_total : 9510 time to create 1 rle with old method : 0.011039495468139648 time for calcul the mask position with numpy : 0.034754276275634766 nb_pixel_total : 27219 time to create 1 rle with old method : 0.03264141082763672 time for calcul the mask position with numpy : 0.032434940338134766 nb_pixel_total : 7805 time to create 1 rle with old method : 0.009009599685668945 time for calcul the mask position with numpy : 0.033388376235961914 nb_pixel_total : 11079 time to create 1 rle with old method : 0.013564348220825195 time for calcul the mask position with numpy : 0.03104543685913086 nb_pixel_total : 25768 time to create 1 rle with old method : 0.029377460479736328 time for calcul the mask position with numpy : 0.0327606201171875 nb_pixel_total : 71307 time to create 1 rle with old method : 0.08363795280456543 time for calcul the mask position with numpy : 0.03102564811706543 nb_pixel_total : 18576 time to create 1 rle with old method : 0.02203083038330078 time for calcul the mask position with numpy : 0.030698537826538086 nb_pixel_total : 18169 time to create 1 rle with old method : 0.026588916778564453 time for calcul the mask position with numpy : 0.035195350646972656 nb_pixel_total : 56714 time to create 1 rle with old method : 0.08904910087585449 time for calcul the mask position with numpy : 0.0332033634185791 nb_pixel_total : 7333 time to create 1 rle with old method : 0.008666753768920898 time for calcul the mask position with numpy : 0.02982473373413086 nb_pixel_total : 13194 time to create 1 rle with old method : 0.015371322631835938 time for calcul the mask position with numpy : 0.0321805477142334 nb_pixel_total : 7696 time to create 1 rle with old method : 0.008950471878051758 time for calcul the mask position with numpy : 0.029558420181274414 nb_pixel_total : 5895 time to create 1 rle with old method : 0.006837129592895508 time for calcul the mask position with numpy : 0.030916929244995117 nb_pixel_total : 3226 time to create 1 rle with old method : 0.0038268566131591797 create new chi : 4.400311231613159 time to delete rle : 0.004723787307739258 batch 1 Loaded 75 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 17916 TO DO : save crop sub photo not yet done ! save time : 4.611118793487549 nb_obj : 45 nb_hashtags : 3 time to prepare the origin masks : 4.157990217208862 time for calcul the mask position with numpy : 0.8270766735076904 nb_pixel_total : 5906048 time to create 1 rle with new method : 1.697549819946289 time for calcul the mask position with numpy : 0.029456377029418945 nb_pixel_total : 25615 time to create 1 rle with old method : 0.029375553131103516 time for calcul the mask position with numpy : 0.028560400009155273 nb_pixel_total : 12904 time to create 1 rle with old method : 0.014857769012451172 time for calcul the mask position with numpy : 0.029076576232910156 nb_pixel_total : 18105 time to create 1 rle with old method : 0.020257234573364258 time for calcul the mask position with numpy : 0.028970718383789062 nb_pixel_total : 10004 time to create 1 rle with old method : 0.011343002319335938 time for calcul the mask position with numpy : 0.02983999252319336 nb_pixel_total : 24026 time to create 1 rle with old method : 0.027096033096313477 time for calcul the mask position with numpy : 0.029268264770507812 nb_pixel_total : 22206 time to create 1 rle with old method : 0.02428293228149414 time for calcul the mask position with numpy : 0.028500795364379883 nb_pixel_total : 27431 time to create 1 rle with old method : 0.031102895736694336 time for calcul the mask position with numpy : 0.02952432632446289 nb_pixel_total : 37274 time to create 1 rle with old method : 0.04214668273925781 time for calcul the mask position with numpy : 0.028414011001586914 nb_pixel_total : 36238 time to create 1 rle with old method : 0.041069746017456055 time for calcul the mask position with numpy : 0.029830217361450195 nb_pixel_total : 9490 time to create 1 rle with old method : 0.010314226150512695 time for calcul the mask position with numpy : 0.029169321060180664 nb_pixel_total : 70711 time to create 1 rle with old method : 0.07851433753967285 time for calcul the mask position with numpy : 0.029115915298461914 nb_pixel_total : 26117 time to create 1 rle with old method : 0.02907538414001465 time for calcul the mask position with numpy : 0.02910900115966797 nb_pixel_total : 34603 time to create 1 rle with old method : 0.04044389724731445 time for calcul the mask position with numpy : 0.033347368240356445 nb_pixel_total : 5967 time to create 1 rle with old method : 0.0076601505279541016 time for calcul the mask position with numpy : 0.029454946517944336 nb_pixel_total : 19812 time to create 1 rle with old method : 0.022340059280395508 time for calcul the mask position with numpy : 0.028705358505249023 nb_pixel_total : 33506 time to create 1 rle with old method : 0.0372467041015625 time for calcul the mask position with numpy : 0.028781414031982422 nb_pixel_total : 10148 time to create 1 rle with old method : 0.012671470642089844 time for calcul the mask position with numpy : 0.029196977615356445 nb_pixel_total : 26223 time to create 1 rle with old method : 0.029683828353881836 time for calcul the mask position with numpy : 0.030069828033447266 nb_pixel_total : 20685 time to create 1 rle with old method : 0.023395776748657227 time for calcul the mask position with numpy : 0.029417753219604492 nb_pixel_total : 4348 time to create 1 rle with old method : 0.00504612922668457 time for calcul the mask position with numpy : 0.029252290725708008 nb_pixel_total : 52127 time to create 1 rle with old method : 0.05988192558288574 time for calcul the mask position with numpy : 0.02944493293762207 nb_pixel_total : 33776 time to create 1 rle with old method : 0.03942608833312988 time for calcul the mask position with numpy : 0.02946305274963379 nb_pixel_total : 18444 time to create 1 rle with old method : 0.02115488052368164 time for calcul the mask position with numpy : 0.029210329055786133 nb_pixel_total : 11591 time to create 1 rle with old method : 0.013185739517211914 time for calcul the mask position with numpy : 0.028978586196899414 nb_pixel_total : 4224 time to create 1 rle with old method : 0.00496220588684082 time for calcul the mask position with numpy : 0.030038833618164062 nb_pixel_total : 31355 time to create 1 rle with old method : 0.03595447540283203 time for calcul the mask position with numpy : 0.02955770492553711 nb_pixel_total : 27799 time to create 1 rle with old method : 0.03173255920410156 time for calcul the mask position with numpy : 0.029189109802246094 nb_pixel_total : 14965 time to create 1 rle with old method : 0.017130136489868164 time for calcul the mask position with numpy : 0.0289609432220459 nb_pixel_total : 17847 time to create 1 rle with old method : 0.02031850814819336 time for calcul the mask position with numpy : 0.02907252311706543 nb_pixel_total : 8670 time to create 1 rle with old method : 0.009926557540893555 time for calcul the mask position with numpy : 0.02979254722595215 nb_pixel_total : 92411 time to create 1 rle with old method : 0.10938096046447754 time for calcul the mask position with numpy : 0.029875516891479492 nb_pixel_total : 12571 time to create 1 rle with old method : 0.014763355255126953 time for calcul the mask position with numpy : 0.030948877334594727 nb_pixel_total : 16862 time to create 1 rle with old method : 0.023050546646118164 time for calcul the mask position with numpy : 0.03413724899291992 nb_pixel_total : 6368 time to create 1 rle with old method : 0.007652759552001953 time for calcul the mask position with numpy : 0.030907869338989258 nb_pixel_total : 18543 time to create 1 rle with old method : 0.021185636520385742 time for calcul the mask position with numpy : 0.030080318450927734 nb_pixel_total : 93324 time to create 1 rle with old method : 0.11179661750793457 time for calcul the mask position with numpy : 0.030510663986206055 nb_pixel_total : 5453 time to create 1 rle with old method : 0.0073511600494384766 time for calcul the mask position with numpy : 0.030459880828857422 nb_pixel_total : 6206 time to create 1 rle with old method : 0.008343696594238281 time for calcul the mask position with numpy : 0.03044295310974121 nb_pixel_total : 99087 time to create 1 rle with old method : 0.11565160751342773 time for calcul the mask position with numpy : 0.029294252395629883 nb_pixel_total : 1725 time to create 1 rle with old method : 0.0020568370819091797 time for calcul the mask position with numpy : 0.029242515563964844 nb_pixel_total : 32256 time to create 1 rle with old method : 0.03708338737487793 time for calcul the mask position with numpy : 0.02980804443359375 nb_pixel_total : 22464 time to create 1 rle with old method : 0.026082515716552734 time for calcul the mask position with numpy : 0.0316164493560791 nb_pixel_total : 15938 time to create 1 rle with old method : 0.018398761749267578 time for calcul the mask position with numpy : 0.032011985778808594 nb_pixel_total : 16577 time to create 1 rle with old method : 0.022780656814575195 time for calcul the mask position with numpy : 0.031440019607543945 nb_pixel_total : 8196 time to create 1 rle with old method : 0.01324915885925293 create new chi : 5.240402936935425 time to delete rle : 0.004517078399658203 batch 1 Loaded 91 chid ids of type : 3594 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 19953 TO DO : save crop sub photo not yet done ! save time : 1.5107133388519287 nb_obj : 45 nb_hashtags : 4 time to prepare the origin masks : 4.744138240814209 time for calcul the mask position with numpy : 0.4568610191345215 nb_pixel_total : 5534290 time to create 1 rle with new method : 0.4048731327056885 time for calcul the mask position with numpy : 0.03013777732849121 nb_pixel_total : 78483 time to create 1 rle with old method : 0.08838081359863281 time for calcul the mask position with numpy : 0.03087019920349121 nb_pixel_total : 24713 time to create 1 rle with old method : 0.029721975326538086 time for calcul the mask position with numpy : 0.03211855888366699 nb_pixel_total : 118622 time to create 1 rle with old method : 0.13570880889892578 time for calcul the mask position with numpy : 0.029427528381347656 nb_pixel_total : 10754 time to create 1 rle with old method : 0.012639045715332031 time for calcul the mask position with numpy : 0.029198884963989258 nb_pixel_total : 27046 time to create 1 rle with old method : 0.030368328094482422 time for calcul the mask position with numpy : 0.029659032821655273 nb_pixel_total : 14327 time to create 1 rle with old method : 0.01657271385192871 time for calcul the mask position with numpy : 0.02926325798034668 nb_pixel_total : 22509 time to create 1 rle with old method : 0.02544713020324707 time for calcul the mask position with numpy : 0.02988910675048828 nb_pixel_total : 128125 time to create 1 rle with old method : 0.18207979202270508 time for calcul the mask position with numpy : 0.02965831756591797 nb_pixel_total : 7068 time to create 1 rle with old method : 0.008158683776855469 time for calcul the mask position with numpy : 0.029981613159179688 nb_pixel_total : 14428 time to create 1 rle with old method : 0.016777992248535156 time for calcul the mask position with numpy : 0.029876232147216797 nb_pixel_total : 65084 time to create 1 rle with old method : 0.07337641716003418 time for calcul the mask position with numpy : 0.02996516227722168 nb_pixel_total : 37302 time to create 1 rle with old method : 0.04222750663757324 time for calcul the mask position with numpy : 0.02955770492553711 nb_pixel_total : 18307 time to create 1 rle with old method : 0.02082681655883789 time for calcul the mask position with numpy : 0.02908921241760254 nb_pixel_total : 1090 time to create 1 rle with old method : 0.0013997554779052734 time for calcul the mask position with numpy : 0.028228044509887695 nb_pixel_total : 15749 time to create 1 rle with old method : 0.01780223846435547 time for calcul the mask position with numpy : 0.028276681900024414 nb_pixel_total : 17559 time to create 1 rle with old method : 0.019321680068969727 time for calcul the mask position with numpy : 0.029106616973876953 nb_pixel_total : 20625 time to create 1 rle with old method : 0.022855758666992188 time for calcul the mask position with numpy : 0.02979135513305664 nb_pixel_total : 147537 time to create 1 rle with old method : 0.16243958473205566 time for calcul the mask position with numpy : 0.0286862850189209 nb_pixel_total : 19608 time to create 1 rle with old method : 0.021953105926513672 time for calcul the mask position with numpy : 0.028447866439819336 nb_pixel_total : 22818 time to create 1 rle with old method : 0.025925397872924805 time for calcul the mask position with numpy : 0.029192686080932617 nb_pixel_total : 18650 time to create 1 rle with old method : 0.02090740203857422 time for calcul the mask position with numpy : 0.0297238826751709 nb_pixel_total : 57281 time to create 1 rle with old method : 0.07622122764587402 time for calcul the mask position with numpy : 0.02938079833984375 nb_pixel_total : 16126 time to create 1 rle with old method : 0.01984405517578125 time for calcul the mask position with numpy : 0.029389142990112305 nb_pixel_total : 24066 time to create 1 rle with old method : 0.02855682373046875 time for calcul the mask position with numpy : 0.029878616333007812 nb_pixel_total : 43326 time to create 1 rle with old method : 0.052576541900634766 time for calcul the mask position with numpy : 0.030887126922607422 nb_pixel_total : 14115 time to create 1 rle with old method : 0.01624321937561035 time for calcul the mask position with numpy : 0.03017592430114746 nb_pixel_total : 19330 time to create 1 rle with old method : 0.02203845977783203 time for calcul the mask position with numpy : 0.029813289642333984 nb_pixel_total : 56053 time to create 1 rle with old method : 0.06511759757995605 time for calcul the mask position with numpy : 0.031485557556152344 nb_pixel_total : 7416 time to create 1 rle with old method : 0.008779287338256836 time for calcul the mask position with numpy : 0.0296323299407959 nb_pixel_total : 26463 time to create 1 rle with old method : 0.030519962310791016 time for calcul the mask position with numpy : 0.03176760673522949 nb_pixel_total : 127230 time to create 1 rle with old method : 0.14474797248840332 time for calcul the mask position with numpy : 0.030753374099731445 nb_pixel_total : 66707 time to create 1 rle with old method : 0.09422755241394043 time for calcul the mask position with numpy : 0.029099225997924805 nb_pixel_total : 1374 time to create 1 rle with old method : 0.0017011165618896484 time for calcul the mask position with numpy : 0.02899456024169922 nb_pixel_total : 16123 time to create 1 rle with old method : 0.01850271224975586 time for calcul the mask position with numpy : 0.030386924743652344 nb_pixel_total : 17621 time to create 1 rle with old method : 0.020052433013916016 time for calcul the mask position with numpy : 0.029836177825927734 nb_pixel_total : 35535 time to create 1 rle with old method : 0.04040980339050293 time for calcul the mask position with numpy : 0.02953052520751953 nb_pixel_total : 25158 time to create 1 rle with old method : 0.028521299362182617 time for calcul the mask position with numpy : 0.02945852279663086 nb_pixel_total : 21269 time to create 1 rle with old method : 0.02482318878173828 time for calcul the mask position with numpy : 0.03396034240722656 nb_pixel_total : 8506 time to create 1 rle with old method : 0.013828754425048828 time for calcul the mask position with numpy : 0.03364849090576172 nb_pixel_total : 37210 time to create 1 rle with old method : 0.042433977127075195 time for calcul the mask position with numpy : 0.02930760383605957 nb_pixel_total : 18144 time to create 1 rle with old method : 0.02079296112060547 time for calcul the mask position with numpy : 0.02978825569152832 nb_pixel_total : 10859 time to create 1 rle with old method : 0.014030694961547852 time for calcul the mask position with numpy : 0.03344464302062988 nb_pixel_total : 12384 time to create 1 rle with old method : 0.0156400203704834 time for calcul the mask position with numpy : 0.029806137084960938 nb_pixel_total : 6843 time to create 1 rle with old method : 0.007917404174804688 time for calcul the mask position with numpy : 0.02848339080810547 nb_pixel_total : 16407 time to create 1 rle with old method : 0.01862049102783203 create new chi : 4.050585508346558 time to delete rle : 0.0038421154022216797 batch 1 Loaded 91 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 21996 TO DO : save crop sub photo not yet done ! save time : 2.8240790367126465 nb_obj : 31 nb_hashtags : 4 time to prepare the origin masks : 3.9305591583251953 time for calcul the mask position with numpy : 0.7144455909729004 nb_pixel_total : 5988924 time to create 1 rle with new method : 0.7892718315124512 time for calcul the mask position with numpy : 0.029288530349731445 nb_pixel_total : 14555 time to create 1 rle with old method : 0.016651153564453125 time for calcul the mask position with numpy : 0.02949213981628418 nb_pixel_total : 18883 time to create 1 rle with old method : 0.022757530212402344 time for calcul the mask position with numpy : 0.02954721450805664 nb_pixel_total : 12133 time to create 1 rle with old method : 0.014683723449707031 time for calcul the mask position with numpy : 0.03007197380065918 nb_pixel_total : 44979 time to create 1 rle with old method : 0.05241560935974121 time for calcul the mask position with numpy : 0.029884815216064453 nb_pixel_total : 11884 time to create 1 rle with old method : 0.013814926147460938 time for calcul the mask position with numpy : 0.03110957145690918 nb_pixel_total : 40433 time to create 1 rle with old method : 0.046817779541015625 time for calcul the mask position with numpy : 0.029314279556274414 nb_pixel_total : 45552 time to create 1 rle with old method : 0.05202293395996094 time for calcul the mask position with numpy : 0.029144763946533203 nb_pixel_total : 15262 time to create 1 rle with old method : 0.01743626594543457 time for calcul the mask position with numpy : 0.02923107147216797 nb_pixel_total : 7970 time to create 1 rle with old method : 0.009235620498657227 time for calcul the mask position with numpy : 0.029291868209838867 nb_pixel_total : 23053 time to create 1 rle with old method : 0.02623605728149414 time for calcul the mask position with numpy : 0.02968740463256836 nb_pixel_total : 127793 time to create 1 rle with old method : 0.1446828842163086 time for calcul the mask position with numpy : 0.029509782791137695 nb_pixel_total : 35067 time to create 1 rle with old method : 0.039548397064208984 time for calcul the mask position with numpy : 0.0334622859954834 nb_pixel_total : 12032 time to create 1 rle with old method : 0.01993846893310547 time for calcul the mask position with numpy : 0.03481888771057129 nb_pixel_total : 43946 time to create 1 rle with old method : 0.051030874252319336 time for calcul the mask position with numpy : 0.029913663864135742 nb_pixel_total : 184939 time to create 1 rle with new method : 0.35963988304138184 time for calcul the mask position with numpy : 0.03010082244873047 nb_pixel_total : 23713 time to create 1 rle with old method : 0.028069019317626953 time for calcul the mask position with numpy : 0.0307004451751709 nb_pixel_total : 41003 time to create 1 rle with old method : 0.04935455322265625 time for calcul the mask position with numpy : 0.029622316360473633 nb_pixel_total : 10928 time to create 1 rle with old method : 0.01256251335144043 time for calcul the mask position with numpy : 0.03129267692565918 nb_pixel_total : 22914 time to create 1 rle with old method : 0.028455734252929688 time for calcul the mask position with numpy : 0.031781673431396484 nb_pixel_total : 28818 time to create 1 rle with old method : 0.03261518478393555 time for calcul the mask position with numpy : 0.029384136199951172 nb_pixel_total : 30846 time to create 1 rle with old method : 0.03623056411743164 time for calcul the mask position with numpy : 0.03191018104553223 nb_pixel_total : 37119 time to create 1 rle with old method : 0.04141092300415039 time for calcul the mask position with numpy : 0.029816865921020508 nb_pixel_total : 16510 time to create 1 rle with old method : 0.01854705810546875 time for calcul the mask position with numpy : 0.029311180114746094 nb_pixel_total : 18324 time to create 1 rle with old method : 0.021474361419677734 time for calcul the mask position with numpy : 0.02945423126220703 nb_pixel_total : 12934 time to create 1 rle with old method : 0.014718294143676758 time for calcul the mask position with numpy : 0.030434370040893555 nb_pixel_total : 31874 time to create 1 rle with old method : 0.0364842414855957 time for calcul the mask position with numpy : 0.029967069625854492 nb_pixel_total : 59952 time to create 1 rle with old method : 0.0713193416595459 time for calcul the mask position with numpy : 0.029390335083007812 nb_pixel_total : 16921 time to create 1 rle with old method : 0.01995372772216797 time for calcul the mask position with numpy : 0.029490947723388672 nb_pixel_total : 9151 time to create 1 rle with old method : 0.01056051254272461 time for calcul the mask position with numpy : 0.029764175415039062 nb_pixel_total : 47665 time to create 1 rle with old method : 0.05631613731384277 time for calcul the mask position with numpy : 0.029833555221557617 nb_pixel_total : 14163 time to create 1 rle with old method : 0.022854328155517578 create new chi : 3.8951234817504883 time to delete rle : 0.003911018371582031 batch 1 Loaded 63 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 17684 TO DO : save crop sub photo not yet done ! save time : 3.7530477046966553 map_output_result : {1350354385: (0.0, 'Should be the crop_list due to order', 0), 1350354381: (0.0, 'Should be the crop_list due to order', 0), 1350354376: (0.0, 'Should be the crop_list due to order', 0), 1350354266: (0.0, 'Should be the crop_list due to order', 0), 1350354238: (0.0, 'Should be the crop_list due to order', 0), 1350354210: (0.0, 'Should be the crop_list due to order', 0), 1350354154: (0.0, 'Should be the crop_list due to order', 0), 1350354109: (0.0, 'Should be the crop_list due to order', 0), 1350353822: (0.0, 'Should be the crop_list due to order', 0), 1350353790: (0.0, 'Should be the crop_list due to order', 0), 1350353758: (0.0, 'Should be the crop_list due to order', 0), 1350353647: (0.0, 'Should be the crop_list due to order', 0), 1350349657: (0.0, 'Should be the crop_list due to order', 0), 1350349467: (0.0, 'Should be the crop_list due to order', 0), 1350349447: (0.0, 'Should be the crop_list due to order', 0), 1350349396: (0.0, 'Should be the crop_list due to order', 0), 1350349356: (0.0, 'Should be the crop_list due to order', 0), 1350349053: (0.0, 'Should be the crop_list due to order', 0), 1350348979: (0.0, 'Should be the crop_list due to order', 0), 1350348961: (0.0, 'Should be the crop_list due to order', 0), 1350348647: (0.0, 'Should be the crop_list due to order', 0), 1350348639: (0.0, 'Should be the crop_list due to order', 0), 1350348634: (0.0, 'Should be the crop_list due to order', 0), 1350348627: (0.0, 'Should be the crop_list due to order', 0), 1350348620: (0.0, 'Should be the crop_list due to order', 0)} End step rle-unique-nms Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : rle_unique_nms_with_priority we use saveGeneral [1350354385, 1350354381, 1350354376, 1350354266, 1350354238, 1350354210, 1350354154, 1350354109, 1350353822, 1350353790, 1350353758, 1350353647, 1350349657, 1350349467, 1350349447, 1350349396, 1350349356, 1350349053, 1350348979, 1350348961, 1350348647, 1350348639, 1350348634, 1350348627, 1350348620] Looping around the photos to save general results len do output : 25 /1350354385.Didn't retrieve data . /1350354381.Didn't retrieve data . /1350354376.Didn't retrieve data . /1350354266.Didn't retrieve data . /1350354238.Didn't retrieve data . /1350354210.Didn't retrieve data . /1350354154.Didn't retrieve data . /1350354109.Didn't retrieve data . /1350353822.Didn't retrieve data . /1350353790.Didn't retrieve data . /1350353758.Didn't retrieve data . /1350353647.Didn't retrieve data . /1350349657.Didn't retrieve data . /1350349467.Didn't retrieve data . /1350349447.Didn't retrieve data . /1350349396.Didn't retrieve data . /1350349356.Didn't retrieve data . /1350349053.Didn't retrieve data . /1350348979.Didn't retrieve data . /1350348961.Didn't retrieve data . /1350348647.Didn't retrieve data . /1350348639.Didn't retrieve data . /1350348634.Didn't retrieve data . /1350348627.Didn't retrieve data . /1350348620.Didn't retrieve data . before output type Used above Here is an output not treated by saveGeneral : Managing all output in save final without adding information in the mtr_datou_result ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354385', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354381', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354376', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354266', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354238', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354210', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354154', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354109', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350353822', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350353790', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350353758', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350353647', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350349657', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350349467', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350349447', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350349396', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350349356', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350349053', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350348979', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350348961', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350348647', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350348639', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350348634', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350348627', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350348620', None, None, None, None, None, '2733670') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 75 time used for this insertion : 3.381957769393921 save_final save missing photos in datou_result : time spend for datou_step_exec : 310.77819871902466 time spend to save output : 3.3862738609313965 total time spend for step 3 : 314.16447257995605 step4:ventilate_hashtags_in_portfolio Wed Apr 9 11:02:14 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure beginning of datou step ventilate_hashtags_in_portfolio : To implement ! Iterating over portfolio : 22153590 get user id for portfolio 22153590 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`=22153590 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('papier','autre','pet_clair','mal_croppe','pet_fonce','background','carton','flou','pehd','environnement','metal')) AND mptpi.`min_score`=0.5 To do To do SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=22153590 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('papier','autre','pet_clair','mal_croppe','pet_fonce','background','carton','flou','pehd','environnement','metal')) AND mptpi.`min_score`=0.5 To do Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") To do ! Use context local managing function ! SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=22153590 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('papier','autre','pet_clair','mal_croppe','pet_fonce','background','carton','flou','pehd','environnement','metal')) AND mptpi.`min_score`=0.5 To do lien utilise dans velours : https://www.fotonower.com/velours/22158161,22158162,22158163,22158164,22158165,22158166,22158167,22158168,22158169,22158170,22158171?tags=papier,autre,pet_clair,mal_croppe,pet_fonce,background,carton,flou,pehd,environnement,metal Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : ventilate_hashtags_in_portfolio we use saveGeneral [1350354385, 1350354381, 1350354376, 1350354266, 1350354238, 1350354210, 1350354154, 1350354109, 1350353822, 1350353790, 1350353758, 1350353647, 1350349657, 1350349467, 1350349447, 1350349396, 1350349356, 1350349053, 1350348979, 1350348961, 1350348647, 1350348639, 1350348634, 1350348627, 1350348620] Looping around the photos to save general results len do output : 1 /22153590. before output type Here is an output not treated by saveGeneral : Managing all output in save final without adding information in the mtr_datou_result ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354385', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354381', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354376', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354266', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354238', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354210', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354154', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354109', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350353822', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350353790', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350353758', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350353647', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350349657', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350349467', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350349447', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350349396', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350349356', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350349053', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350348979', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350348961', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350348647', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350348639', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350348634', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350348627', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350348620', None, None, None, None, None, '2733670') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 26 time used for this insertion : 0.07062506675720215 save_final save missing photos in datou_result : time spend for datou_step_exec : 2.141294002532959 time spend to save output : 0.0712728500366211 total time spend for step 4 : 2.21256685256958 step5:final Wed Apr 9 11:02:16 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 : {1350354385: ('0.1808327092411039',), 1350354381: ('0.1808327092411039',), 1350354376: ('0.1808327092411039',), 1350354266: ('0.1808327092411039',), 1350354238: ('0.1808327092411039',), 1350354210: ('0.1808327092411039',), 1350354154: ('0.1808327092411039',), 1350354109: ('0.1808327092411039',), 1350353822: ('0.1808327092411039',), 1350353790: ('0.1808327092411039',), 1350353758: ('0.1808327092411039',), 1350353647: ('0.1808327092411039',), 1350349657: ('0.1808327092411039',), 1350349467: ('0.1808327092411039',), 1350349447: ('0.1808327092411039',), 1350349396: ('0.1808327092411039',), 1350349356: ('0.1808327092411039',), 1350349053: ('0.1808327092411039',), 1350348979: ('0.1808327092411039',), 1350348961: ('0.1808327092411039',), 1350348647: ('0.1808327092411039',), 1350348639: ('0.1808327092411039',), 1350348634: ('0.1808327092411039',), 1350348627: ('0.1808327092411039',), 1350348620: ('0.1808327092411039',)} new output for save of step final : {1350354385: ('0.1808327092411039',), 1350354381: ('0.1808327092411039',), 1350354376: ('0.1808327092411039',), 1350354266: ('0.1808327092411039',), 1350354238: ('0.1808327092411039',), 1350354210: ('0.1808327092411039',), 1350354154: ('0.1808327092411039',), 1350354109: ('0.1808327092411039',), 1350353822: ('0.1808327092411039',), 1350353790: ('0.1808327092411039',), 1350353758: ('0.1808327092411039',), 1350353647: ('0.1808327092411039',), 1350349657: ('0.1808327092411039',), 1350349467: ('0.1808327092411039',), 1350349447: ('0.1808327092411039',), 1350349396: ('0.1808327092411039',), 1350349356: ('0.1808327092411039',), 1350349053: ('0.1808327092411039',), 1350348979: ('0.1808327092411039',), 1350348961: ('0.1808327092411039',), 1350348647: ('0.1808327092411039',), 1350348639: ('0.1808327092411039',), 1350348634: ('0.1808327092411039',), 1350348627: ('0.1808327092411039',), 1350348620: ('0.1808327092411039',)} [1350354385, 1350354381, 1350354376, 1350354266, 1350354238, 1350354210, 1350354154, 1350354109, 1350353822, 1350353790, 1350353758, 1350353647, 1350349657, 1350349467, 1350349447, 1350349396, 1350349356, 1350349053, 1350348979, 1350348961, 1350348647, 1350348639, 1350348634, 1350348627, 1350348620] Looping around the photos to save general results len do output : 25 /1350354385.Didn't retrieve data . /1350354381.Didn't retrieve data . /1350354376.Didn't retrieve data . /1350354266.Didn't retrieve data . /1350354238.Didn't retrieve data . /1350354210.Didn't retrieve data . /1350354154.Didn't retrieve data . /1350354109.Didn't retrieve data . /1350353822.Didn't retrieve data . /1350353790.Didn't retrieve data . /1350353758.Didn't retrieve data . /1350353647.Didn't retrieve data . /1350349657.Didn't retrieve data . /1350349467.Didn't retrieve data . /1350349447.Didn't retrieve data . /1350349396.Didn't retrieve data . /1350349356.Didn't retrieve data . /1350349053.Didn't retrieve data . /1350348979.Didn't retrieve data . /1350348961.Didn't retrieve data . /1350348647.Didn't retrieve data . /1350348639.Didn't retrieve data . /1350348634.Didn't retrieve data . /1350348627.Didn't retrieve data . /1350348620.Didn't retrieve data . before output type Used above Used above Managing all output in save final without adding information in the mtr_datou_result ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354385', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354381', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354376', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354266', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354238', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354210', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354154', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354109', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350353822', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350353790', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350353758', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350353647', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350349657', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350349467', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350349447', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350349396', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350349356', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350349053', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350348979', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350348961', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350348647', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350348639', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350348634', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350348627', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350348620', None, None, None, None, None, '2733670') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 75 time used for this insertion : 0.014827966690063477 save_final save missing photos in datou_result : time spend for datou_step_exec : 0.2286074161529541 time spend to save output : 0.0161130428314209 total time spend for step 5 : 0.244720458984375 step6:blur_detection Wed Apr 9 11:02:16 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure inside step blur_detection methode: ratio et variance treat image : temp/1744188028_526287_1350354385_2cea8ffe0c2c623168982c62e676574a.jpg resize: (2160, 3264) 1350354385 -4.100571456291909 treat image : temp/1744188028_526287_1350354381_af1b28391812fd60847c1f476aed4118.jpg resize: (2160, 3264) 1350354381 -6.959770946997557 treat image : temp/1744188028_526287_1350354376_6870268064e55c268caa5f25f62ec5f0.jpg resize: (2160, 3264) 1350354376 -3.682739609923275 treat image : temp/1744188028_526287_1350354266_d9dba015b83540935f9bdd201b6105d0.jpg resize: (2160, 3264) 1350354266 -4.323971207693347 treat image : temp/1744188028_526287_1350354238_2036eebfe632b29e2a540286eeb6259a.jpg resize: (2160, 3264) 1350354238 -4.350479451574903 treat image : temp/1744188028_526287_1350354210_2aec466957ab6ba300f942803750266a.jpg resize: (2160, 3264) 1350354210 -3.2621304897102537 treat image : temp/1744188028_526287_1350354154_64348d6cae587f265f2dbe8d68e66000.jpg resize: (2160, 3264) 1350354154 -3.8967271387534472 treat image : temp/1744188028_526287_1350354109_33c5649ac7277e0d05064f9032f6c752.jpg resize: (2160, 3264) 1350354109 -4.821390505988285 treat image : temp/1744188028_526287_1350353822_07684af6a1c91a58a696908c81064934.jpg resize: (2160, 3264) 1350353822 -7.189897712199227 treat image : temp/1744188028_526287_1350353790_307b2cff76264ca60f3b152d1eaab2ab.jpg resize: (2160, 3264) 1350353790 -5.430509657505177 treat image : temp/1744188028_526287_1350353758_8d6bb830860c08a08e682e8d2fca0a36.jpg resize: (2160, 3264) 1350353758 -5.346999629610621 treat image : temp/1744188028_526287_1350353647_7855d35abae558d149b4e737bb9c423e.jpg resize: (2160, 3264) 1350353647 -5.508265674681599 treat image : temp/1744188028_526287_1350349657_389428bd1d366284d58cf2726fc328c1.jpg resize: (2160, 3264) 1350349657 -5.003032658520355 treat image : temp/1744188028_526287_1350349467_3ec1503bc5c267fba232df399a8ebc45.jpg resize: (2160, 3264) 1350349467 -5.528169447534381 treat image : temp/1744188028_526287_1350349447_38f1864038ef5bd47b5594f52d132f05.jpg resize: (2160, 3264) 1350349447 -4.955397447482667 treat image : temp/1744188028_526287_1350349396_61dbdea14437975bd6dfbaafa5d3e727.jpg resize: (2160, 3264) 1350349396 -2.178547239931399 treat image : temp/1744188028_526287_1350349356_58e05f478b5fe239d12cb7ad9483b5b5.jpg resize: (2160, 3264) 1350349356 -3.1445010563566376 treat image : temp/1744188028_526287_1350349053_490ca2509fde983ce77e12eef8fc03b8.jpg resize: (2160, 3264) 1350349053 0.22959933100933377 treat image : temp/1744188028_526287_1350348979_1f8179beb63deedc6d2e5eac9441ca93.jpg resize: (2160, 3264) 1350348979 -2.061419198065726 treat image : temp/1744188028_526287_1350348961_a3e0f98b100836b6d26a391eea69a962.jpg resize: (2160, 3264) 1350348961 -5.519550417404214 treat image : temp/1744188028_526287_1350348647_7d059849ee87461751636f02b6f9dbae.jpg resize: (2160, 3264) 1350348647 -3.3549865258295313 treat image : temp/1744188028_526287_1350348639_cd2c5c08c4581b6ae57a567da2f821b6.jpg resize: (2160, 3264) 1350348639 -4.648489467943674 treat image : temp/1744188028_526287_1350348634_18d3f33a2065931b656781f9433f99ab.jpg resize: (2160, 3264) 1350348634 -5.009963121636203 treat image : temp/1744188028_526287_1350348627_3b1dcf9cfbcd71dafa67fc98902e76b2.jpg resize: (2160, 3264) 1350348627 -4.877062475140464 treat image : temp/1744188028_526287_1350348620_087e4540e0b4bd28acf5592deefa8bff.jpg resize: (2160, 3264) 1350348620 -4.773984982268944 treat image : temp/1744188028_526287_1350354385_2cea8ffe0c2c623168982c62e676574a_rle_crop_3751281790_0.png resize: (162, 123) 1350731041 -1.526187525243071 treat image : temp/1744188028_526287_1350354385_2cea8ffe0c2c623168982c62e676574a_rle_crop_3751281767_0.png resize: (355, 504) 1350731042 -1.9221320945431772 treat image : temp/1744188028_526287_1350354385_2cea8ffe0c2c623168982c62e676574a_rle_crop_3751281769_0.png resize: (85, 82) 1350731043 -1.0845006913232074 treat image : temp/1744188028_526287_1350354385_2cea8ffe0c2c623168982c62e676574a_rle_crop_3751281768_0.png resize: (123, 108) 1350731045 -0.6366154616223171 treat image : temp/1744188028_526287_1350354385_2cea8ffe0c2c623168982c62e676574a_rle_crop_3751281762_0.png resize: (194, 122) 1350731046 -0.6464742354152966 treat image : temp/1744188028_526287_1350354385_2cea8ffe0c2c623168982c62e676574a_rle_crop_3751281756_0.png resize: (138, 140) 1350731047 -1.8711195190092813 treat image : temp/1744188028_526287_1350354385_2cea8ffe0c2c623168982c62e676574a_rle_crop_3751281759_0.png resize: (303, 395) 1350731048 -2.7853625093508003 treat image : temp/1744188028_526287_1350354385_2cea8ffe0c2c623168982c62e676574a_rle_crop_3751281764_0.png resize: (292, 86) 1350731049 -1.6072581569708615 treat image : temp/1744188028_526287_1350354385_2cea8ffe0c2c623168982c62e676574a_rle_crop_3751281778_0.png resize: (163, 204) 1350731050 -3.088494960469537 treat image : temp/1744188028_526287_1350354385_2cea8ffe0c2c623168982c62e676574a_rle_crop_3751281786_0.png resize: (281, 171) 1350731051 -2.588779839274167 treat image : temp/1744188028_526287_1350354385_2cea8ffe0c2c623168982c62e676574a_rle_crop_3751281765_0.png resize: (465, 163) 1350731052 -1.2307059126058622 treat image : temp/1744188028_526287_1350354385_2cea8ffe0c2c623168982c62e676574a_rle_crop_3751281755_0.png resize: (146, 372) 1350731053 -1.6571422449907443 treat image : temp/1744188028_526287_1350354385_2cea8ffe0c2c623168982c62e676574a_rle_crop_3751281766_0.png resize: (246, 375) 1350731054 -1.7302073410902834 treat image : temp/1744188028_526287_1350354385_2cea8ffe0c2c623168982c62e676574a_rle_crop_3751281781_0.png resize: (372, 458) 1350731055 -2.2928604016193934 treat image : temp/1744188028_526287_1350354385_2cea8ffe0c2c623168982c62e676574a_rle_crop_3751281757_0.png resize: (209, 138) 1350731056 -1.233787937215996 treat image : temp/1744188028_526287_1350354385_2cea8ffe0c2c623168982c62e676574a_rle_crop_3751281770_0.png resize: (47, 76) 1350731057 3.032229464882682 treat image : temp/1744188028_526287_1350354385_2cea8ffe0c2c623168982c62e676574a_rle_crop_3751281772_0.png resize: (200, 137) 1350731059 -1.4720826243452174 treat image : temp/1744188028_526287_1350354385_2cea8ffe0c2c623168982c62e676574a_rle_crop_3751281754_0.png resize: (382, 283) 1350731060 -1.8791874793049983 treat image : temp/1744188028_526287_1350354385_2cea8ffe0c2c623168982c62e676574a_rle_crop_3751281788_0.png resize: (46, 68) 1350731061 0.3015606688082231 treat image : temp/1744188028_526287_1350354385_2cea8ffe0c2c623168982c62e676574a_rle_crop_3751281774_0.png resize: (309, 415) 1350731062 -3.4445559696766685 treat image : temp/1744188028_526287_1350354385_2cea8ffe0c2c623168982c62e676574a_rle_crop_3751281784_0.png resize: (103, 134) 1350731065 -2.0601764174678086 treat image : temp/1744188028_526287_1350354385_2cea8ffe0c2c623168982c62e676574a_rle_crop_3751281761_0.png resize: (60, 94) 1350731066 0.7932218393666495 treat image : temp/1744188028_526287_1350354385_2cea8ffe0c2c623168982c62e676574a_rle_crop_3751281783_0.png resize: (116, 125) 1350731067 -1.378175019279421 treat image : temp/1744188028_526287_1350354385_2cea8ffe0c2c623168982c62e676574a_rle_crop_3751281775_0.png resize: (173, 93) 1350731068 -1.948106488554888 treat image : temp/1744188028_526287_1350354385_2cea8ffe0c2c623168982c62e676574a_rle_crop_3751281758_0.png resize: (238, 344) 1350731069 -2.399495568756161 treat image : temp/1744188028_526287_1350354385_2cea8ffe0c2c623168982c62e676574a_rle_crop_3751281760_0.png resize: (136, 194) 1350731070 -1.3395914924548626 treat image : temp/1744188028_526287_1350354385_2cea8ffe0c2c623168982c62e676574a_rle_crop_3751281780_0.png resize: (359, 226) 1350731071 -3.951057984017639 treat image : temp/1744188028_526287_1350354385_2cea8ffe0c2c623168982c62e676574a_rle_crop_3751281792_0.png resize: (88, 319) 1350731072 -1.2498978379355112 treat image : temp/1744188028_526287_1350354385_2cea8ffe0c2c623168982c62e676574a_rle_crop_3751281791_0.png resize: (192, 225) 1350731073 -2.441427439509504 treat image : temp/1744188028_526287_1350354385_2cea8ffe0c2c623168982c62e676574a_rle_crop_3751281763_0.png resize: (124, 245) 1350731074 -2.290545916046212 treat image : temp/1744188028_526287_1350354381_af1b28391812fd60847c1f476aed4118_rle_crop_3751281810_0.png resize: (140, 103) 1350731075 -2.2419200386943645 treat image : temp/1744188028_526287_1350354381_af1b28391812fd60847c1f476aed4118_rle_crop_3751281798_0.png resize: (274, 304) 1350731076 -2.0124804628339787 treat image : temp/1744188028_526287_1350354381_af1b28391812fd60847c1f476aed4118_rle_crop_3751281797_0.png resize: (362, 413) 1350731077 -2.69937159968433 treat image : temp/1744188028_526287_1350354381_af1b28391812fd60847c1f476aed4118_rle_crop_3751281821_0.png resize: (218, 278) 1350731078 -3.5130828579853475 treat image : temp/1744188028_526287_1350354381_af1b28391812fd60847c1f476aed4118_rle_crop_3751281809_0.png resize: (145, 286) 1350731079 -1.3233879513848492 treat image : temp/1744188028_526287_1350354381_af1b28391812fd60847c1f476aed4118_rle_crop_3751281808_0.png resize: (323, 242) 1350731080 -4.624833575384256 treat image : temp/1744188028_526287_1350354381_af1b28391812fd60847c1f476aed4118_rle_crop_3751281807_0.png resize: (211, 399) 1350731081 -4.280458533047807 treat image : temp/1744188028_526287_1350354381_af1b28391812fd60847c1f476aed4118_rle_crop_3751281822_0.png resize: (235, 575) 1350731082 -4.831672373477266 treat image : temp/1744188028_526287_1350354381_af1b28391812fd60847c1f476aed4118_rle_crop_3751281793_0.png resize: (98, 139) 1350731083 -2.9947649099605314 treat image : temp/1744188028_526287_1350354381_af1b28391812fd60847c1f476aed4118_rle_crop_3751281795_0.png resize: (184, 280) 1350731084 -2.721481283193498 treat image : temp/1744188028_526287_1350354381_af1b28391812fd60847c1f476aed4118_rle_crop_3751281805_0.png resize: (206, 235) 1350731085 -4.064355474464862 treat image : temp/1744188028_526287_1350354381_af1b28391812fd60847c1f476aed4118_rle_crop_3751281806_0.png resize: (118, 254) 1350731086 -4.031354458859877 treat image : temp/1744188028_526287_1350354381_af1b28391812fd60847c1f476aed4118_rle_crop_3751281801_0.png resize: (119, 160) 1350731087 -3.2666806482603308 treat image : temp/1744188028_526287_1350354381_af1b28391812fd60847c1f476aed4118_rle_crop_3751281802_0.png resize: (148, 186) 1350731088 -3.399121492918699 treat image : temp/1744188028_526287_1350354381_af1b28391812fd60847c1f476aed4118_rle_crop_3751281825_0.png resize: (226, 301) 1350731089 -3.939411155166852 treat image : temp/1744188028_526287_1350354381_af1b28391812fd60847c1f476aed4118_rle_crop_3751281820_0.png resize: (156, 160) 1350731090 -3.2047108133912023 treat image : temp/1744188028_526287_1350354381_af1b28391812fd60847c1f476aed4118_rle_crop_3751281794_0.png resize: (192, 356) 1350731091 -3.6673656463172066 treat image : temp/1744188028_526287_1350354381_af1b28391812fd60847c1f476aed4118_rle_crop_3751281815_0.png resize: (213, 240) 1350731092 -3.35324436529325 treat image : temp/1744188028_526287_1350354381_af1b28391812fd60847c1f476aed4118_rle_crop_3751281799_0.png resize: (315, 316) 1350731093 -4.9010569302141915 treat image : temp/1744188028_526287_1350354381_af1b28391812fd60847c1f476aed4118_rle_crop_3751281816_0.png resize: (71, 114) 1350731094 -3.709180370320913 treat image : temp/1744188028_526287_1350354381_af1b28391812fd60847c1f476aed4118_rle_crop_3751281813_0.png resize: (169, 194) 1350731095 -3.0480331762653785 treat image : temp/1744188028_526287_1350354381_af1b28391812fd60847c1f476aed4118_rle_crop_3751281814_0.png resize: (173, 163) 1350731096 -2.4208765422893745 treat image : temp/1744188028_526287_1350354381_af1b28391812fd60847c1f476aed4118_rle_crop_3751281826_0.png resize: (169, 194) 1350731097 -3.760288904703026 treat image : temp/1744188028_526287_1350354381_af1b28391812fd60847c1f476aed4118_rle_crop_3751281812_0.png resize: (234, 156) 1350731098 -4.680546654117775 treat image : temp/1744188028_526287_1350354381_af1b28391812fd60847c1f476aed4118_rle_crop_3751281817_0.png resize: (158, 81) 1350731099 -3.5332444454781022 treat image : temp/1744188028_526287_1350354381_af1b28391812fd60847c1f476aed4118_rle_crop_3751281796_0.png resize: (331, 224) 1350731100 -3.380558810039049 treat image : 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temp/1744188028_526287_1350348647_7d059849ee87461751636f02b6f9dbae_rle_crop_3751282519_0.png resize: (153, 225) 1350732570 -1.7740796318897147 treat image : temp/1744188028_526287_1350348639_cd2c5c08c4581b6ae57a567da2f821b6_rle_crop_3751282551_0.png resize: (251, 140) 1350732571 -2.105990612117074 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 : 953 time used for this insertion : 0.07137894630432129 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 953 time used for this insertion : 0.1564958095550537 save missing photos in datou_result : time spend for datou_step_exec : 112.06330037117004 time spend to save output : 0.2450118064880371 total time spend for step 6 : 112.30831217765808 step7:brightness Wed Apr 9 11:04:09 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 ! 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temp/1744188028_526287_1350349356_58e05f478b5fe239d12cb7ad9483b5b5_rle_crop_3751282379_0.png treat image : temp/1744188028_526287_1350348961_a3e0f98b100836b6d26a391eea69a962_rle_crop_3751282452_0.png treat image : temp/1744188028_526287_1350348647_7d059849ee87461751636f02b6f9dbae_rle_crop_3751282519_0.png treat image : temp/1744188028_526287_1350348639_cd2c5c08c4581b6ae57a567da2f821b6_rle_crop_3751282551_0.png Inside saveOutput : final : False verbose : 0 begin to insert list_values into class_photo_scores : length of list_valuse in save_photo_hashtag_id_thcl_score : 953 time used for this insertion : 0.07454633712768555 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 953 time used for this insertion : 0.1770796775817871 save missing photos in datou_result : time spend for datou_step_exec : 32.430078744888306 time spend to save output : 0.26068758964538574 total time spend for step 7 : 32.69076633453369 step8:velours_tree Wed Apr 9 11:04:41 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 : 2.2456817626953125 time spend to save output : 5.412101745605469e-05 total time spend for step 8 : 2.2457358837127686 step9:send_mail_cod Wed Apr 9 11:04:44 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 complete output_args for input 1 Inconsistent number of input and output, step which parrallelize and manage error in input by avoiding sending an output for this data can't be used in tree dependencies of input and output complete output_args for input 2 Inconsistent number of input and output, step which parrallelize and manage error in input by avoiding sending an output for this data can't be used in tree dependencies of input and output complete output_args for input 3 We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure dans la step send mail cod work_area: /home/admin/workarea/git/Velours/python in order to get the selector url, please entre the license of selector results_Auto_P22153590_09-04-2025_11_04_44.pdf 22158161 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 .imagette221581611744189484 22158162 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 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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 .imagette221581671744189488 22158168 imagette221581681744189490 22158169 change filename to text .change filename to text .imagette221581691744189490 22158171 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 .imagette221581711744189490 SELECT h.hashtag,pcr.value FROM MTRUser.portfolio_carac_ratio pcr, MTRBack.hashtags h where pcr.portfolio_id=22153590 and hashtag_type = 3594 and pcr.hashtag_id = h.hashtag_id; velour_link : https://www.fotonower.com/velours/22158161,22158162,22158163,22158164,22158165,22158166,22158167,22158168,22158169,22158170,22158171?tags=papier,autre,pet_clair,mal_croppe,pet_fonce,background,carton,flou,pehd,environnement,metal args[1350354385] : ((1350354385, -4.100571456291909, 492609224), (1350354385, 0.050008307542047346, 2107752395), '0.1808327092411039') We are sending mail with results at report@fotonower.com args[1350354381] : ((1350354381, -6.959770946997557, 492609224), (1350354381, -0.1815155097647313, 496442774), '0.1808327092411039') We are sending mail with results at report@fotonower.com args[1350354376] : ((1350354376, -3.682739609923275, 492609224), (1350354376, -0.19468510230679298, 496442774), '0.1808327092411039') We are sending mail with results at report@fotonower.com args[1350354266] : ((1350354266, -4.323971207693347, 492609224), (1350354266, -0.015078481378763286, 2107752395), '0.1808327092411039') We are sending mail with results at report@fotonower.com args[1350354238] : ((1350354238, -4.350479451574903, 492609224), (1350354238, -0.12089515973082375, 496442774), '0.1808327092411039') We are sending mail with results at report@fotonower.com args[1350354210] : ((1350354210, -3.2621304897102537, 492609224), (1350354210, -0.02820959657888806, 2107752395), '0.1808327092411039') We are sending mail with results at report@fotonower.com args[1350354154] : ((1350354154, -3.8967271387534472, 492609224), (1350354154, -0.026074636452133815, 2107752395), '0.1808327092411039') We are sending mail with results at report@fotonower.com args[1350354109] : ((1350354109, -4.821390505988285, 492609224), (1350354109, 0.06166151263482605, 2107752395), '0.1808327092411039') We are sending mail with results at report@fotonower.com args[1350353822] : ((1350353822, -7.189897712199227, 492609224), (1350353822, -0.115878418650977, 496442774), '0.1808327092411039') We are sending mail with results at report@fotonower.com args[1350353790] : ((1350353790, -5.430509657505177, 492609224), (1350353790, 0.14435553215220712, 2107752395), '0.1808327092411039') We are sending mail with results at report@fotonower.com args[1350353758] : ((1350353758, -5.346999629610621, 492609224), (1350353758, -0.01484452567275176, 2107752395), '0.1808327092411039') We are sending mail with results at report@fotonower.com args[1350353647] : ((1350353647, -5.508265674681599, 492609224), (1350353647, 0.09663434911477022, 2107752395), '0.1808327092411039') We are sending mail with results at report@fotonower.com args[1350349657] : ((1350349657, -5.003032658520355, 492609224), (1350349657, 0.23437723506970692, 2107752395), '0.1808327092411039') We are sending mail with results at report@fotonower.com args[1350349467] : ((1350349467, -5.528169447534381, 492609224), (1350349467, 0.05544565194487898, 2107752395), '0.1808327092411039') We are sending mail with results at report@fotonower.com args[1350349447] : ((1350349447, -4.955397447482667, 492609224), (1350349447, 0.029117459167128344, 2107752395), '0.1808327092411039') We are sending mail with results at report@fotonower.com args[1350349396] : ((1350349396, -2.178547239931399, 492609224), (1350349396, -0.15771272099596872, 496442774), '0.1808327092411039') We are sending mail with results at report@fotonower.com args[1350349356] : ((1350349356, -3.1445010563566376, 492609224), (1350349356, -0.1048093087916126, 496442774), '0.1808327092411039') We are sending mail with results at report@fotonower.com args[1350349053] : ((1350349053, 0.22959933100933377, 492688767), (1350349053, -0.01482709142784962, 2107752395), '0.1808327092411039') We are sending mail with results at report@fotonower.com args[1350348979] : ((1350348979, -2.061419198065726, 492609224), (1350348979, 0.09275863609550034, 2107752395), '0.1808327092411039') We are sending mail with results at report@fotonower.com args[1350348961] : ((1350348961, -5.519550417404214, 492609224), (1350348961, -0.05363823047917298, 2107752395), '0.1808327092411039') We are sending mail with results at report@fotonower.com args[1350348647] : ((1350348647, -3.3549865258295313, 492609224), (1350348647, -0.09374181656458347, 496442774), '0.1808327092411039') We are sending mail with results at report@fotonower.com args[1350348639] : ((1350348639, -4.648489467943674, 492609224), (1350348639, -0.08796126989566119, 496442774), '0.1808327092411039') We are sending mail with results at report@fotonower.com args[1350348634] : ((1350348634, -5.009963121636203, 492609224), (1350348634, -0.00889534726240857, 2107752395), '0.1808327092411039') We are sending mail with results at report@fotonower.com args[1350348627] : ((1350348627, -4.877062475140464, 492609224), (1350348627, 0.04190615992699511, 2107752395), '0.1808327092411039') We are sending mail with results at report@fotonower.com args[1350348620] : ((1350348620, -4.773984982268944, 492609224), (1350348620, 0.1827177998363924, 2107752395), '0.1808327092411039') We are sending mail with results at report@fotonower.com refus_total : 0.1808327092411039 2022-04-13 10:29:59 0 SELECT ph.photo_id,ph.url,ph.username,ph.uploaded_at,ph.text FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=22153590 AND mpp.hide_status=0 ORDER BY mpp.order LIMIT 0, 1000 SELECT photo_id, url FROM MTRBack.photos ph WHERE photo_id IN (1350354385,1350348639,1350348647,1350348961,1350354266,1350354238,1350354154,1350354109,1350348620,1350353822,1350353647,1350349657,1350354381,1350354376,1350354210,1350353790,1350353758,1350349467,1350349447,1350349396) Found this number of photos: 20 begin to download photo : 1350354385 begin to download photo : 1350354238 begin to download photo : 1350353647 begin to download photo : 1350353790 download finish for photo 1350353647 begin to download photo : 1350349657 download finish for photo 1350354385 begin to download photo : 1350348639 download finish for photo 1350353790 begin to download photo : 1350353758 download finish for photo 1350349657 begin to download photo : 1350354381 download finish for photo 1350348639 begin to download photo : 1350348647 download finish for photo 1350354238 begin to download photo : 1350354154 download finish for photo 1350348647 begin to download photo : 1350348961 download finish for photo 1350354381 begin to download photo : 1350354376 download finish for photo 1350354154 begin to download photo : 1350354109 download finish for photo 1350353758 begin to download photo : 1350349467 download finish for photo 1350354376 begin to download photo : 1350354210 download finish for photo 1350348961 begin to download photo : 1350354266 download finish for photo 1350354109 begin to download photo : 1350348620 download finish for photo 1350349467 begin to download photo : 1350349447 download finish for photo 1350348620 begin to download photo : 1350353822 download finish for photo 1350349447 begin to download photo : 1350349396 download finish for photo 1350354210 download finish for photo 1350354266 download finish for photo 1350353822 download finish for photo 1350349396 start upload file to ovh https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P22153590_09-04-2025_11_04_44.pdf results_Auto_P22153590_09-04-2025_11_04_44.pdf uploaded to url https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P22153590_09-04-2025_11_04_44.pdf start insert file to database insert into MTRUser.mtr_files (mtd_id,mtr_portfolio_id,text,url,format,tags,file_size,value) values ('3318','22153590','results_Auto_P22153590_09-04-2025_11_04_44.pdf','https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P22153590_09-04-2025_11_04_44.pdf','pdf','','1.12','0.1808327092411039') message_in_mail: Bonjour,
Veuillez trouver ci dessous les résultats du service carac on demand pour le portfolio: https://www.fotonower.com/view/22153590

https://www.fotonower.com/image?json=false&list_photos_id=1350354385
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1350354381
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1350354376
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1350354266
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1350354238
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1350354210
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1350354154
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1350354109
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1350353822
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1350353790
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1350353758
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1350353647
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1350349657
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1350349467
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1350349447
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1350349396
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1350349356
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1350349053
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1350348979
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1350348961
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1350348647
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1350348639
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1350348634
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1350348627
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1350348620
Bravo, la photo est bien prise.

Dans ces conditions,le taux de refus est: 18.08%
Veuillez trouver les photos des contaminants.

exemples de contaminants: papier: https://www.fotonower.com/view/22158161?limit=200
exemples de contaminants: autre: https://www.fotonower.com/view/22158162?limit=200
exemples de contaminants: pet_clair: https://www.fotonower.com/view/22158163?limit=200
exemples de contaminants: pet_fonce: https://www.fotonower.com/view/22158165?limit=200
exemples de contaminants: carton: https://www.fotonower.com/view/22158167?limit=200
exemples de contaminants: pehd: https://www.fotonower.com/view/22158169?limit=200
exemples de contaminants: metal: https://www.fotonower.com/view/22158171?limit=200
Veuillez trouver le rapport en pdf:https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P22153590_09-04-2025_11_04_44.pdf.

Lien vers velours :https://www.fotonower.com/velours/22158161,22158162,22158163,22158164,22158165,22158166,22158167,22158168,22158169,22158170,22158171?tags=papier,autre,pet_clair,mal_croppe,pet_fonce,background,carton,flou,pehd,environnement,metal.


L'équipe Fotonower 202 b'' Server: nginx Date: Wed, 09 Apr 2025 09:04:56 GMT Content-Length: 0 Connection: close X-Message-Id: yfKEhj6xRgWw7Rsz9VEpDg Access-Control-Allow-Origin: https://sendgrid.api-docs.io Access-Control-Allow-Methods: POST Access-Control-Allow-Headers: Authorization, Content-Type, On-behalf-of, x-sg-elas-acl Access-Control-Max-Age: 600 X-No-CORS-Reason: https://sendgrid.com/docs/Classroom/Basics/API/cors.html Strict-Transport-Security: max-age=31536000; includeSubDomains Content-Security-Policy: frame-ancestors 'none' Cache-Control: no-cache X-Content-Type-Options: no-sniff Referrer-Policy: strict-origin-when-cross-origin Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : send_mail_cod we use saveGeneral [1350354385, 1350354381, 1350354376, 1350354266, 1350354238, 1350354210, 1350354154, 1350354109, 1350353822, 1350353790, 1350353758, 1350353647, 1350349657, 1350349467, 1350349447, 1350349396, 1350349356, 1350349053, 1350348979, 1350348961, 1350348647, 1350348639, 1350348634, 1350348627, 1350348620] Looping around the photos to save general results len do output : 0 before output type Used above Managing all output in save final without adding information in the mtr_datou_result ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354385', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354381', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354376', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354266', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354238', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354210', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354154', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354109', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350353822', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350353790', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350353758', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350353647', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350349657', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350349467', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350349447', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350349396', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350349356', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350349053', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350348979', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350348961', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350348647', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350348639', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350348634', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350348627', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350348620', None, None, None, None, None, '2733670') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 25 time used for this insertion : 0.01677727699279785 save_final save missing photos in datou_result : time spend for datou_step_exec : 12.377710580825806 time spend to save output : 0.01723766326904297 total time spend for step 9 : 12.394948244094849 step10:split_time_score Wed Apr 9 11:04:56 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! complete output_args for input 1 VR 22-3-18 : For now we do not clean correctly the datou structure begin split time score Catched exception ! Connect or reconnect ! TODO : Insert select and so on Begin split_port_in_batch_balle thcls : [{'id': 861, 'mtr_user_id': 31, 'name': 'Rungis_class_dechets_1212', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'Rungis_Aluminium,Rungis_Carton,Rungis_Papier,Rungis_Plastique_clair,Rungis_Plastique_dur,Rungis_Plastique_fonce,Rungis_Tapis_vide,Rungis_Tetrapak', 'svm_portfolios_learning': '1160730,571842,571844,571839,571933,571840,571841,572307', 'photo_hashtag_type': 999, 'photo_desc_type': 3963, 'type_classification': 'caffe', 'hashtag_id_list': '2107751280,2107750907,2107750908,2107750909,2107750910,2107750911,2107750912,2107750913'}] thcls : [{'id': 758, 'mtr_user_id': 31, 'name': 'Rungis_amount_dechets_fall_2018_v2', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': '05102018_Papier_non_papier_dense,05102018_Papier_non_papier_peu_dense,05102018_Papier_non_papier_presque_vide,05102018_Papier_non_papier_tres_dense,05102018_Papier_non_papier_tres_peu_dense', 'svm_portfolios_learning': '1108385,1108386,1108388,1108384,1108387', 'photo_hashtag_type': 856, 'photo_desc_type': 3853, 'type_classification': 'caffe', 'hashtag_id_list': '2107751013,2107751014,2107751015,2107751016,2107751017'}] (('16', 25),) ERROR counted https://github.com/fotonower/Velours/issues/663#issuecomment-421136223 {} 07042025 22153590 Nombre de photos uploadées : 25 / 23040 (0%) 07042025 22153590 Nombre de photos taguées (types de déchets): 0 / 25 (0%) 07042025 22153590 Nombre de photos taguées (volume) : 0 / 25 (0%) elapsed_time : load_data_split_time_score 4.0531158447265625e-06 elapsed_time : order_list_meta_photo_and_scores 1.0728836059570312e-05 ????????????????????????? elapsed_time : fill_and_build_computed_from_old_data 0.0012352466583251953 elapsed_time : insert_dashboard_record_day_entry 0.02438807487487793 We will return after consolidate but for now we need the day, how to get it, for now depending on the previous heavy steps find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 22153527 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 22153533 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 22153536 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 22153537 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 22153567 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 22153572 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 22153573 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 22153575 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 22153579 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 22153585 order by id desc limit 1 Qualite : 0.1808327092411039 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P22153590_09-04-2025_11_04_44.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 22153590 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=22153590 AND mptpi.`type`=3594 To do Qualite : 0.2245747095134351 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P22153594_09-04-2025_10_39_29.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 22153594 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=22153594 AND mptpi.`type`=3594 To do Qualite : 0.18817508340141612 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P22153599_09-04-2025_10_31_18.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 22153599 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=22153599 AND mptpi.`type`=3594 To do find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 22153631 order by id desc limit 1 Qualite : 0.2387647538497724 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P22153644_09-04-2025_10_11_42.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 22153644 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=22153644 AND mptpi.`type`=3594 To do Qualite : 0.20050398026424382 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P22153647_09-04-2025_10_19_51.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 22153647 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=22153647 AND mptpi.`type`=3594 To do Qualite : 0.16284528966389794 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P22153651_09-04-2025_09_56_05.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 22153651 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=22153651 AND mptpi.`type`=3594 To do find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 22153655 order by id desc limit 1 Qualite : 0.13395730297527286 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P22153656_09-04-2025_09_56_03.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 22153656 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11449 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11452 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 11452 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11453 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11453 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11478 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11478 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11455 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11455 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11458 send_mail_cod have less inputs used (3) than in the step definition (5) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 11449 doesn't seem to be define in the database( WARNING : type of input 2 of step 11452 doesn't seem to be define in the database( WARNING : output 1 of step 11449 have datatype=2 whereas input 1 of step 11453 have datatype=7 WARNING : type of output 2 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11454 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11456 doesn't seem to be define in the database( WARNING : type of output 1 of step 11456 doesn't seem to be define in the database( WARNING : type of input 3 of step 11455 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11456 have datatype=10 whereas input 3 of step 11458 have datatype=6 WARNING : type of input 5 of step 11458 doesn't seem to be define in the database( WARNING : output 0 of step 11477 have datatype=11 whereas input 5 of step 11458 have datatype=None WARNING : output 0 of step 11456 have datatype=10 whereas input 0 of step 11477 have datatype=18 WARNING : type of input 2 of step 11478 doesn't seem to be define in the database( WARNING : output 1 of step 11454 have datatype=7 whereas input 2 of step 11478 have datatype=None WARNING : type of output 3 of step 11478 doesn't seem to be define in the database( WARNING : type of input 2 of step 11456 doesn't seem to be define in the database( WARNING : output 0 of step 11453 have datatype=1 whereas input 0 of step 11454 have datatype=2 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=22153656 AND mptpi.`type`=3726 To do NUMBER BATCH : 0 # DISPLAY ALL COLLECTED DATA : {'07042025': {'nb_upload': 25, '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 [1350354385, 1350354381, 1350354376, 1350354266, 1350354238, 1350354210, 1350354154, 1350354109, 1350353822, 1350353790, 1350353758, 1350353647, 1350349657, 1350349467, 1350349447, 1350349396, 1350349356, 1350349053, 1350348979, 1350348961, 1350348647, 1350348639, 1350348634, 1350348627, 1350348620] Looping around the photos to save general results len do output : 1 /22153590Didn't retrieve data . before output type Here is an output not treated by saveGeneral : Managing all output in save final without adding information in the mtr_datou_result ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354385', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354381', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354376', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354266', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354238', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354210', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354154', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350354109', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350353822', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350353790', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350353758', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350353647', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350349657', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350349467', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350349447', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350349396', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350349356', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350349053', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350348979', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350348961', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350348647', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350348639', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350348634', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350348627', None, None, None, None, None, '2733670') ('3318', None, None, None, None, None, None, None, '2733670') ('3318', '22153590', '1350348620', None, None, None, None, None, '2733670') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 26 time used for this insertion : 0.037573814392089844 save_final save missing photos in datou_result : time spend for datou_step_exec : 14.800012588500977 time spend to save output : 0.03791046142578125 total time spend for step 10 : 14.837923049926758 caffe_path_current : About to save ! 2 After save, about to update current ! ret : 2 len(input) + len(total_photo_id_missing) : 25 set_done_treatment 644.84user 355.95system 24:47.83elapsed 67%CPU (0avgtext+0avgdata 10300484maxresident)k 36883208inputs+414672outputs (1058139major+64624169minor)pagefaults 0swaps