python /home/admin/mtr/script_for_cron.py -j datou_current3 -m 20 -a ' -a 3318 ' -s datou_3318 -M 0 -S 0 -U 95,95,120 import MySQLdb succeeded Import error (python version) ['/Users/moilerat/Documents/Fotonower/install/caffe/distribute/python', '/home/admin/workarea/git/Velours/python/prod', '/home/admin/workarea/install/caffe_cuda8_python3/python', '/home/admin/workarea/install/darknet', '/home/admin/workarea/git/Velours/python', '/home/admin/workarea/install/caffe_frcnn_python3/py-faster-rcnn/caffe-fast-rcnn/python', '/home/admin/mtr/.credentials', '/home/admin/workarea/install/caffe/python', '/home/admin/workarea/install/caffe_frcnn/py-faster-rcnn/tools', '/home/admin/workarea/git/fotonowerpip', '/home/admin/workarea/install/segment-anything', '/home/admin/workarea/git/pyfvs', '/usr/lib/python38.zip', '/usr/lib/python3.8', '/usr/lib/python3.8/lib-dynload', '/home/admin/.local/lib/python3.8/site-packages', '/usr/local/lib/python3.8/dist-packages', '/usr/lib/python3/dist-packages'] process id : 977867 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 : ['2734295'] with mtr_portfolio_ids : ['22161073'] and first list_photo_ids : [] new path : /proc/977867/ Inside batchDatouExec : verbose : 0 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! List Step Type Loaded in datou : mask_detect, crop_condition, rle_unique_nms_with_priority, ventilate_hashtags_in_portfolio, final, blur_detection, brightness, velours_tree, send_mail_cod, split_time_score over limit max, limiting to limit_max 40 list_input_json : [] origin We have 1 , BFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 24 ; length of list_pids : 24 ; length of list_args : 24 time to download the photos : 4.694862604141235 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 12:30:33 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec 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 : 2956 max_wait_temp : 1 max_wait : 0 gpu_flag : 0 2025-04-09 12:30:37.041224: 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 12:30:37.067131: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493065000 Hz 2025-04-09 12:30:37.069578: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f3f04000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-04-09 12:30:37.069643: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-04-09 12:30:37.073561: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-04-09 12:30:37.337641: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x124469b0 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-04-09 12:30:37.337710: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-04-09 12:30:37.338846: 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 12:30:37.339331: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-04-09 12:30:37.342569: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-04-09 12:30:37.345627: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-04-09 12:30:37.346151: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-04-09 12:30:37.349208: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-04-09 12:30:37.350423: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-04-09 12:30:37.355698: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-04-09 12:30:37.356879: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-04-09 12:30:37.356992: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-04-09 12:30:37.357579: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-04-09 12:30:37.357595: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-04-09 12:30:37.357605: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-04-09 12:30:37.358573: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 2504 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 12:30:37.643266: 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 12:30:37.643348: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-04-09 12:30:37.643365: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-04-09 12:30:37.643381: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-04-09 12:30:37.643395: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-04-09 12:30:37.643410: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-04-09 12:30:37.643424: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-04-09 12:30:37.643439: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-04-09 12:30:37.644316: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-04-09 12:30:37.645326: 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 12:30:37.645382: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-04-09 12:30:37.645404: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-04-09 12:30:37.645424: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-04-09 12:30:37.645444: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-04-09 12:30:37.645464: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-04-09 12:30:37.645483: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-04-09 12:30:37.645503: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-04-09 12:30:37.646543: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-04-09 12:30:37.646579: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-04-09 12:30:37.646589: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-04-09 12:30:37.646599: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-04-09 12:30:37.647731: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 2504 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 12:30:48.655610: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-04-09 12:30:48.843958: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-04-09 12:30:50.740623: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.06GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-04-09 12:30:50.740700: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.06GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-04-09 12:30:50.747097: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.06GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-04-09 12:30:50.747119: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.06GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-04-09 12:30:50.798000: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.06GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-04-09 12:30:50.798066: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.06GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-04-09 12:30:50.839779: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.09GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-04-09 12:30:50.839805: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.09GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-04-09 12:30:50.882683: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.15GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-04-09 12:30:50.882722: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.15GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-04-09 12:30:50.884803: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.45G (1553858560 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-09 12:30:50.885372: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.30G (1398472704 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-09 12:30:51.199604: W tensorflow/core/common_runtime/bfc_allocator.cc:311] Garbage collection: deallocate free memory regions (i.e., allocations) so that we can re-allocate a larger region to avoid OOM due to memory fragmentation. If you see this message frequently, you are running near the threshold of the available device memory and re-allocation may incur great performance overhead. You may try smaller batch sizes to observe the performance impact. Set TF_ENABLE_GPU_GARBAGE_COLLECTION=false if you'd like to disable this feature. 2025-04-09 12:30:51.244595: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.95G (2090729472 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-09 12:30:51.245813: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.95G (2090729472 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-09 12:30:51.247379: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.95G (2090729472 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-09 12:30:51.248421: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.95G (2090729472 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-09 12:30:51.258861: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.95G (2090729472 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-09 12:30:51.259499: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.95G (2090729472 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-09 12:30:51.260172: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.95G (2090729472 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-09 12:30:51.260773: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.95G (2090729472 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-09 12:30:51.261401: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.95G (2090729472 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-09 12:30:51.262022: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.95G (2090729472 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-09 12:30:51.276631: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.95G (2090729472 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-09 12:30:51.277197: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.95G (2090729472 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-09 12:30:51.301189: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.95G (2090729472 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-09 12:30:51.301276: W tensorflow/core/kernels/gpu_utils.cc:49] Failed to allocate memory for convolution redzone checking; skipping this check. This is benign and only means that we won't check cudnn for out-of-bounds reads and writes. This message will only be printed once. 2025-04-09 12:30:51.302406: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.95G (2090729472 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-09 12:30:51.303513: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.95G (2090729472 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-09 12:30:51.310580: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.95G (2090729472 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-09 12:30:51.311163: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.95G (2090729472 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-09 12:30:51.319107: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.95G (2090729472 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-09 12:30:51.319713: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.95G (2090729472 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-09 12:30:51.337007: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.95G (2090729472 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-09 12:30:51.337774: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.95G (2090729472 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-09 12:30:51.338572: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.95G (2090729472 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-09 12:30:51.339341: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.95G (2090729472 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-09 12:30:51.343431: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.95G (2090729472 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-09 12:30:51.344035: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.95G (2090729472 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-09 12:30:51.344634: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.95G (2090729472 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-09 12:30:51.345215: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.95G (2090729472 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-09 12:30:51.346187: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.95G (2090729472 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-09 12:30:51.356335: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.95G (2090729472 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-09 12:30:51.356936: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.95G (2090729472 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-09 12:30:51.365948: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.95G (2090729472 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-09 12:30:51.366560: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.95G (2090729472 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-09 12:30:51.367208: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.95G (2090729472 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-09 12:30:51.367811: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.95G (2090729472 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-09 12:30:51.368418: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.95G (2090729472 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-09 12:30:51.368991: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.95G (2090729472 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 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 : 24 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 : 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 : 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 : 73 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 : 70 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 : 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 : 46 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 : 51 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 : 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 : 84 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 : 47 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 : 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 : 94 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 : 73 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 : 12 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 : 47 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 : 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 : 91 Detection mask done ! Trying to reset tf kernel 978435 begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 1984 tf kernel not reseted sub process len(results) : 24 len(list_Values) 0 None max_time_sub_proc : 3600 parent process len(results) : 24 len(list_Values) 0 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 : 3177 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 : 0.05821681022644043 nb_pixel_total : 16032 time to create 1 rle with old method : 0.02299976348876953 length of segment : 141 time for calcul the mask position with numpy : 0.18139028549194336 nb_pixel_total : 77903 time to create 1 rle with old method : 0.08527350425720215 length of segment : 396 time for calcul the mask position with numpy : 0.057317495346069336 nb_pixel_total : 12850 time to create 1 rle with old method : 0.017429113388061523 length of segment : 98 time for calcul the mask position with numpy : 0.06200146675109863 nb_pixel_total : 25031 time to create 1 rle with old method : 0.027234554290771484 length of segment : 185 time for calcul the mask position with numpy : 0.13781118392944336 nb_pixel_total : 43969 time to create 1 rle with old method : 0.050759315490722656 length of segment : 274 time for calcul the mask position with numpy : 0.21483445167541504 nb_pixel_total : 151880 time to create 1 rle with new method : 0.02053546905517578 length of segment : 413 time for calcul the mask position with numpy : 0.14494633674621582 nb_pixel_total : 54258 time to create 1 rle with old method : 0.07828831672668457 length of segment : 385 time for calcul the mask position with numpy : 0.19226288795471191 nb_pixel_total : 21333 time to create 1 rle with old method : 0.029268264770507812 length of segment : 355 time for calcul the mask position with numpy : 0.05001378059387207 nb_pixel_total : 24488 time to create 1 rle with old method : 0.03713107109069824 length of segment : 173 time for calcul the mask position with numpy : 0.14075756072998047 nb_pixel_total : 42605 time to create 1 rle with old method : 0.0626821517944336 length of segment : 398 time for calcul the mask position with numpy : 0.08372926712036133 nb_pixel_total : 33217 time to create 1 rle with old method : 0.04606795310974121 length of segment : 210 time for calcul the mask position with numpy : 0.009397268295288086 nb_pixel_total : 17089 time to create 1 rle with old method : 0.027458667755126953 length of segment : 191 time for calcul the mask position with numpy : 0.027765750885009766 nb_pixel_total : 9563 time to create 1 rle with old method : 0.02391529083251953 length of segment : 162 time for calcul the mask position with numpy : 0.03785061836242676 nb_pixel_total : 15799 time to create 1 rle with old method : 0.02347111701965332 length of segment : 136 time for calcul the mask position with numpy : 0.11710548400878906 nb_pixel_total : 63625 time to create 1 rle with old method : 0.08436226844787598 length of segment : 431 time for calcul the mask position with numpy : 0.03669619560241699 nb_pixel_total : 17800 time to create 1 rle with old method : 0.02414846420288086 length of segment : 141 time for calcul the mask position with numpy : 0.04035043716430664 nb_pixel_total : 10039 time to create 1 rle with old method : 0.013802766799926758 length of segment : 118 time for calcul the mask position with numpy : 0.07094645500183105 nb_pixel_total : 25890 time to create 1 rle with old method : 0.0339665412902832 length of segment : 220 time for calcul the mask position with numpy : 0.03116893768310547 nb_pixel_total : 35263 time to create 1 rle with old method : 0.0670614242553711 length of segment : 281 time for calcul the mask position with numpy : 0.0822913646697998 nb_pixel_total : 38464 time to create 1 rle with old method : 0.05080437660217285 length of segment : 227 time for calcul the mask position with numpy : 0.011185407638549805 nb_pixel_total : 15828 time to create 1 rle with old method : 0.02001953125 length of segment : 117 time for calcul the mask position with numpy : 0.09357905387878418 nb_pixel_total : 44485 time to create 1 rle with old method : 0.059323787689208984 length of segment : 215 time for calcul the mask position with numpy : 0.3540027141571045 nb_pixel_total : 254260 time to create 1 rle with new method : 0.04752492904663086 length of segment : 1243 time for calcul the mask position with numpy : 0.03994464874267578 nb_pixel_total : 6882 time to create 1 rle with old method : 0.0074541568756103516 length of segment : 104 time for calcul the mask position with numpy : 0.02587437629699707 nb_pixel_total : 8052 time to create 1 rle with old method : 0.009109735488891602 length of segment : 56 time for calcul the mask position with numpy : 0.028618335723876953 nb_pixel_total : 13883 time to create 1 rle with old method : 0.014955282211303711 length of segment : 147 time for calcul the mask position with numpy : 0.015529394149780273 nb_pixel_total : 16031 time to create 1 rle with old method : 0.017293930053710938 length of segment : 158 time for calcul the mask position with numpy : 0.06934833526611328 nb_pixel_total : 23851 time to create 1 rle with old method : 0.025562286376953125 length of segment : 220 time for calcul the mask position with numpy : 0.029922962188720703 nb_pixel_total : 14567 time to create 1 rle with old method : 0.016611814498901367 length of segment : 151 time for calcul the mask position with numpy : 0.04754376411437988 nb_pixel_total : 26027 time to create 1 rle with old method : 0.027278423309326172 length of segment : 168 time for calcul the mask position with numpy : 0.06756281852722168 nb_pixel_total : 39188 time to create 1 rle with old method : 0.051796674728393555 length of segment : 379 time for calcul the mask position with numpy : 0.06258988380432129 nb_pixel_total : 29957 time to create 1 rle with old method : 0.037763357162475586 length of segment : 217 time for calcul the mask position with numpy : 0.0463712215423584 nb_pixel_total : 12563 time to create 1 rle with old method : 0.02021336555480957 length of segment : 129 time for calcul the mask position with numpy : 0.015917301177978516 nb_pixel_total : 4376 time to create 1 rle with old method : 0.012337923049926758 length of segment : 98 time for calcul the mask position with numpy : 0.03379416465759277 nb_pixel_total : 9245 time to create 1 rle with old method : 0.01487588882446289 length of segment : 146 time for calcul the mask position with numpy : 0.08648371696472168 nb_pixel_total : 101730 time to create 1 rle with old method : 0.11275339126586914 length of segment : 526 time for calcul the mask position with numpy : 0.014295339584350586 nb_pixel_total : 18012 time to create 1 rle with old method : 0.02536773681640625 length of segment : 124 time for calcul the mask position with numpy : 0.038175106048583984 nb_pixel_total : 19255 time to create 1 rle with old method : 0.03162336349487305 length of segment : 159 time for calcul the mask position with numpy : 0.0033555030822753906 nb_pixel_total : 2999 time to create 1 rle with old method : 0.005180835723876953 length of segment : 61 time for calcul the mask position with numpy : 0.03133201599121094 nb_pixel_total : 7695 time to create 1 rle with old method : 0.009864330291748047 length of segment : 101 time for calcul the mask position with numpy : 0.010941505432128906 nb_pixel_total : 13302 time to create 1 rle with old method : 0.015048742294311523 length of segment : 181 time for calcul the mask position with numpy : 0.012755870819091797 nb_pixel_total : 40226 time to create 1 rle with old method : 0.04469943046569824 length of segment : 271 time for calcul the mask position with numpy : 0.12003636360168457 nb_pixel_total : 41105 time to create 1 rle with old method : 0.05078864097595215 length of segment : 366 time for calcul the mask position with numpy : 0.11439847946166992 nb_pixel_total : 26052 time to create 1 rle with old method : 0.03335762023925781 length of segment : 228 time for calcul the mask position with numpy : 0.06145143508911133 nb_pixel_total : 13976 time to create 1 rle with old method : 0.020804405212402344 length of segment : 142 time for calcul the mask position with numpy : 0.203139066696167 nb_pixel_total : 70454 time to create 1 rle with old method : 0.08697891235351562 length of segment : 435 time for calcul the mask position with numpy : 0.16704916954040527 nb_pixel_total : 186507 time to create 1 rle with new method : 0.016157865524291992 length of segment : 492 time for calcul the mask position with numpy : 0.08846402168273926 nb_pixel_total : 38604 time to create 1 rle with old method : 0.06279897689819336 length of segment : 335 time for calcul the mask position with numpy : 0.04342532157897949 nb_pixel_total : 14868 time to create 1 rle with old method : 0.02487945556640625 length of segment : 154 time for calcul the mask position with numpy : 0.004755735397338867 nb_pixel_total : 15638 time to create 1 rle with old method : 0.017485857009887695 length of segment : 162 time for calcul the mask position with numpy : 0.10022783279418945 nb_pixel_total : 42735 time to create 1 rle with old method : 0.05144524574279785 length of segment : 204 time for calcul the mask position with numpy : 0.038970947265625 nb_pixel_total : 10309 time to create 1 rle with old method : 0.017233610153198242 length of segment : 123 time for calcul the mask position with numpy : 0.13167834281921387 nb_pixel_total : 43408 time to create 1 rle with old method : 0.04987740516662598 length of segment : 183 time for calcul the mask position with numpy : 0.16174888610839844 nb_pixel_total : 127318 time to create 1 rle with old method : 0.14673233032226562 length of segment : 484 time for calcul the mask position with numpy : 0.03964805603027344 nb_pixel_total : 10702 time to create 1 rle with old method : 0.014930248260498047 length of segment : 122 time for calcul the mask position with numpy : 0.02899622917175293 nb_pixel_total : 15214 time to create 1 rle with old method : 0.02232813835144043 length of segment : 132 time for calcul the mask position with numpy : 0.18824076652526855 nb_pixel_total : 102881 time to create 1 rle with old method : 0.12508249282836914 length of segment : 427 time for calcul the mask position with numpy : 0.08443856239318848 nb_pixel_total : 33358 time to create 1 rle with old method : 0.041585683822631836 length of segment : 229 time for calcul the mask position with numpy : 0.04920244216918945 nb_pixel_total : 9017 time to create 1 rle with old method : 0.013830184936523438 length of segment : 197 time for calcul the mask position with numpy : 0.002125263214111328 nb_pixel_total : 9426 time to create 1 rle with old method : 0.011060476303100586 length of segment : 114 time for calcul the mask position with numpy : 0.11981821060180664 nb_pixel_total : 51623 time to create 1 rle with old method : 0.06078362464904785 length of segment : 280 time for calcul the mask position with numpy : 0.020609617233276367 nb_pixel_total : 5705 time to create 1 rle with old method : 0.011242866516113281 length of segment : 80 time for calcul the mask position with numpy : 0.01129007339477539 nb_pixel_total : 38317 time to create 1 rle with old method : 0.047519683837890625 length of segment : 189 time for calcul the mask position with numpy : 0.015842437744140625 nb_pixel_total : 17603 time to create 1 rle with old method : 0.02108597755432129 length of segment : 128 time for calcul the mask position with numpy : 0.09744548797607422 nb_pixel_total : 54262 time to create 1 rle with old method : 0.07712006568908691 length of segment : 196 time for calcul the mask position with numpy : 0.09541988372802734 nb_pixel_total : 40796 time to create 1 rle with old method : 0.053090572357177734 length of segment : 339 time for calcul the mask position with numpy : 0.07004570960998535 nb_pixel_total : 21934 time to create 1 rle with old method : 0.03140878677368164 length of segment : 173 time for calcul the mask position with numpy : 0.03816628456115723 nb_pixel_total : 12397 time to create 1 rle with old method : 0.018498659133911133 length of segment : 171 time for calcul the mask position with numpy : 0.030910491943359375 nb_pixel_total : 20588 time to create 1 rle with old method : 0.045667171478271484 length of segment : 155 time for calcul the mask position with numpy : 0.08785605430603027 nb_pixel_total : 62530 time to create 1 rle with old method : 0.08047127723693848 length of segment : 247 time for calcul the mask position with numpy : 0.021947383880615234 nb_pixel_total : 22870 time to create 1 rle with old method : 0.030689239501953125 length of segment : 168 time for calcul the mask position with numpy : 0.005021810531616211 nb_pixel_total : 22240 time to create 1 rle with old method : 0.02743053436279297 length of segment : 162 time for calcul the mask position with numpy : 0.0820317268371582 nb_pixel_total : 27023 time to create 1 rle with old method : 0.04473066329956055 length of segment : 187 time for calcul the mask position with numpy : 0.017963647842407227 nb_pixel_total : 8344 time to create 1 rle with old method : 0.014549970626831055 length of segment : 189 time for calcul the mask position with numpy : 0.04042172431945801 nb_pixel_total : 13632 time to create 1 rle with old method : 0.021764516830444336 length of segment : 173 time for calcul the mask position with numpy : 0.3731837272644043 nb_pixel_total : 115226 time to create 1 rle with old method : 0.13435840606689453 length of segment : 536 time for calcul the mask position with numpy : 0.06857132911682129 nb_pixel_total : 26872 time to create 1 rle with old method : 0.03488898277282715 length of segment : 217 time for calcul the mask position with numpy : 0.05229592323303223 nb_pixel_total : 15047 time to create 1 rle with old method : 0.02078866958618164 length of segment : 127 time for calcul the mask position with numpy : 0.08368849754333496 nb_pixel_total : 41182 time to create 1 rle with old method : 0.05033063888549805 length of segment : 257 time for calcul the mask position with numpy : 0.09231686592102051 nb_pixel_total : 44526 time to create 1 rle with old method : 0.06400656700134277 length of segment : 339 time for calcul the mask position with numpy : 0.03902029991149902 nb_pixel_total : 15394 time to create 1 rle with old method : 0.01831650733947754 length of segment : 108 time for calcul the mask position with numpy : 0.016952037811279297 nb_pixel_total : 6854 time to create 1 rle with old method : 0.010976314544677734 length of segment : 78 time for calcul the mask position with numpy : 0.1512131690979004 nb_pixel_total : 66586 time to create 1 rle with old method : 0.08523392677307129 length of segment : 332 time for calcul the mask position with numpy : 0.055557966232299805 nb_pixel_total : 19444 time to create 1 rle with old method : 0.024805307388305664 length of segment : 133 time for calcul the mask position with numpy : 0.005280733108520508 nb_pixel_total : 9204 time to create 1 rle with old method : 0.011515140533447266 length of segment : 149 time for calcul the mask position with numpy : 0.07388567924499512 nb_pixel_total : 21738 time to create 1 rle with old method : 0.02806377410888672 length of segment : 208 time for calcul the mask position with numpy : 0.04311251640319824 nb_pixel_total : 22295 time to create 1 rle with old method : 0.029079198837280273 length of segment : 238 time for calcul the mask position with numpy : 0.13541817665100098 nb_pixel_total : 69589 time to create 1 rle with old method : 0.08635234832763672 length of segment : 369 time for calcul the mask position with numpy : 0.023137807846069336 nb_pixel_total : 7408 time to create 1 rle with old method : 0.010741233825683594 length of segment : 100 time for calcul the mask position with numpy : 0.037590980529785156 nb_pixel_total : 9795 time to create 1 rle with old method : 0.016788244247436523 length of segment : 153 time for calcul the mask position with numpy : 0.04069828987121582 nb_pixel_total : 24181 time to create 1 rle with old method : 0.03389430046081543 length of segment : 207 time for calcul the mask position with numpy : 0.03704094886779785 nb_pixel_total : 12286 time to create 1 rle with old method : 0.019257545471191406 length of segment : 94 time for calcul the mask position with numpy : 0.07737445831298828 nb_pixel_total : 21242 time to create 1 rle with old method : 0.03065347671508789 length of segment : 214 time for calcul the mask position with numpy : 0.031479597091674805 nb_pixel_total : 10128 time to create 1 rle with old method : 0.01385641098022461 length of segment : 164 time for calcul the mask position with numpy : 0.12864112854003906 nb_pixel_total : 15846 time to create 1 rle with old method : 0.02296590805053711 length of segment : 149 time for calcul the mask position with numpy : 0.04908442497253418 nb_pixel_total : 12920 time to create 1 rle with old method : 0.02260613441467285 length of segment : 159 time for calcul the mask position with numpy : 0.13161754608154297 nb_pixel_total : 77644 time to create 1 rle with old method : 0.08745408058166504 length of segment : 381 time for calcul the mask position with numpy : 0.06399130821228027 nb_pixel_total : 32077 time to create 1 rle with old method : 0.04101061820983887 length of segment : 215 time for calcul the mask position with numpy : 0.014178991317749023 nb_pixel_total : 5160 time to create 1 rle with old method : 0.007980108261108398 length of segment : 86 time for calcul the mask position with numpy : 0.12645912170410156 nb_pixel_total : 32692 time to create 1 rle with old method : 0.04023456573486328 length of segment : 178 time for calcul the mask position with numpy : 0.020230770111083984 nb_pixel_total : 8667 time to create 1 rle with old method : 0.014877080917358398 length of segment : 121 time for calcul the mask position with numpy : 0.05274796485900879 nb_pixel_total : 10879 time to create 1 rle with old method : 0.017765522003173828 length of segment : 302 time for calcul the mask position with numpy : 0.15732073783874512 nb_pixel_total : 71931 time to create 1 rle with old method : 0.08990621566772461 length of segment : 314 time for calcul the mask position with numpy : 0.045449018478393555 nb_pixel_total : 13875 time to create 1 rle with old method : 0.019857168197631836 length of segment : 163 time for calcul the mask position with numpy : 0.06505823135375977 nb_pixel_total : 36286 time to create 1 rle with old method : 0.04841923713684082 length of segment : 248 time for calcul the mask position with numpy : 0.005133152008056641 nb_pixel_total : 4634 time to create 1 rle with old method : 0.008540153503417969 length of segment : 64 time for calcul the mask position with numpy : 0.10761404037475586 nb_pixel_total : 53088 time to create 1 rle with old method : 0.0638270378112793 length of segment : 378 time for calcul the mask position with numpy : 0.10470271110534668 nb_pixel_total : 26551 time to create 1 rle with old method : 0.035584449768066406 length of segment : 408 time for calcul the mask position with numpy : 0.0022077560424804688 nb_pixel_total : 2658 time to create 1 rle with old method : 0.0030875205993652344 length of segment : 76 time for calcul the mask position with numpy : 0.07456707954406738 nb_pixel_total : 42722 time to create 1 rle with old method : 0.04974365234375 length of segment : 260 time for calcul the mask position with numpy : 0.07488560676574707 nb_pixel_total : 34513 time to create 1 rle with old method : 0.04305553436279297 length of segment : 438 time for calcul the mask position with numpy : 0.23607468605041504 nb_pixel_total : 133886 time to create 1 rle with old method : 0.150665283203125 length of segment : 453 time for calcul the mask position with numpy : 0.05883169174194336 nb_pixel_total : 17448 time to create 1 rle with old method : 0.024983644485473633 length of segment : 174 time for calcul the mask position with numpy : 0.02315235137939453 nb_pixel_total : 14002 time to create 1 rle with old method : 0.018059730529785156 length of segment : 152 time for calcul the mask position with numpy : 0.08616495132446289 nb_pixel_total : 19588 time to create 1 rle with old method : 0.02463507652282715 length of segment : 386 time for calcul the mask position with numpy : 0.06303048133850098 nb_pixel_total : 27311 time to create 1 rle with old method : 0.03350496292114258 length of segment : 207 time for calcul the mask position with numpy : 0.06257057189941406 nb_pixel_total : 18499 time to create 1 rle with old method : 0.024470090866088867 length of segment : 162 time for calcul the mask position with numpy : 0.02798175811767578 nb_pixel_total : 8609 time to create 1 rle with old method : 0.013434648513793945 length of segment : 104 time for calcul the mask position with numpy : 0.15671992301940918 nb_pixel_total : 37342 time to create 1 rle with old method : 0.04490208625793457 length of segment : 237 time for calcul the mask position with numpy : 0.08785247802734375 nb_pixel_total : 23106 time to create 1 rle with old method : 0.03180861473083496 length of segment : 164 time for calcul the mask position with numpy : 0.07028436660766602 nb_pixel_total : 30120 time to create 1 rle with old method : 0.03670048713684082 length of segment : 182 time for calcul the mask position with numpy : 0.026686668395996094 nb_pixel_total : 8745 time to create 1 rle with old method : 0.014757871627807617 length of segment : 105 time for calcul the mask position with numpy : 0.07328987121582031 nb_pixel_total : 25143 time to create 1 rle with old method : 0.031652212142944336 length of segment : 168 time for calcul the mask position with numpy : 0.06178879737854004 nb_pixel_total : 25335 time to create 1 rle with old method : 0.03199052810668945 length of segment : 134 time for calcul the mask position with numpy : 0.12818694114685059 nb_pixel_total : 57357 time to create 1 rle with old method : 0.06712031364440918 length of segment : 333 time for calcul the mask position with numpy : 0.05512571334838867 nb_pixel_total : 8543 time to create 1 rle with old method : 0.013784170150756836 length of segment : 202 time for calcul the mask position with numpy : 0.09747195243835449 nb_pixel_total : 22768 time to create 1 rle with old method : 0.030210494995117188 length of segment : 224 time for calcul the mask position with numpy : 0.06730294227600098 nb_pixel_total : 22139 time to create 1 rle with old method : 0.0314640998840332 length of segment : 215 time for calcul the mask position with numpy : 0.11161184310913086 nb_pixel_total : 59656 time to create 1 rle with old method : 0.06641268730163574 length of segment : 299 time for calcul the mask position with numpy : 0.03190255165100098 nb_pixel_total : 8880 time to create 1 rle with old method : 0.014786958694458008 length of segment : 122 time for calcul the mask position with numpy : 0.08351707458496094 nb_pixel_total : 19910 time to create 1 rle with old method : 0.025999784469604492 length of segment : 210 time for calcul the mask position with numpy : 0.06613898277282715 nb_pixel_total : 28320 time to create 1 rle with old method : 0.03502631187438965 length of segment : 250 time for calcul the mask position with numpy : 0.04652857780456543 nb_pixel_total : 29069 time to create 1 rle with old method : 0.03619718551635742 length of segment : 154 time for calcul the mask position with numpy : 0.05519556999206543 nb_pixel_total : 25303 time to create 1 rle with old method : 0.03430938720703125 length of segment : 140 time for calcul the mask position with numpy : 0.03573775291442871 nb_pixel_total : 17605 time to create 1 rle with old method : 0.02138376235961914 length of segment : 139 time for calcul the mask position with numpy : 0.04873347282409668 nb_pixel_total : 16146 time to create 1 rle with old method : 0.022274255752563477 length of segment : 160 time for calcul the mask position with numpy : 0.0006797313690185547 nb_pixel_total : 13502 time to create 1 rle with old method : 0.014542102813720703 length of segment : 204 time for calcul the mask position with numpy : 0.058843135833740234 nb_pixel_total : 26603 time to create 1 rle with old method : 0.03293776512145996 length of segment : 202 time for calcul the mask position with numpy : 0.08209013938903809 nb_pixel_total : 33900 time to create 1 rle with old method : 0.04166674613952637 length of segment : 192 time for calcul the mask position with numpy : 0.028619766235351562 nb_pixel_total : 10042 time to create 1 rle with old method : 0.01588726043701172 length of segment : 120 time for calcul the mask position with numpy : 0.02115345001220703 nb_pixel_total : 4732 time to create 1 rle with old method : 0.008718252182006836 length of segment : 63 time for calcul the mask position with numpy : 0.10499143600463867 nb_pixel_total : 22627 time to create 1 rle with old method : 0.026484012603759766 length of segment : 329 time for calcul the mask position with numpy : 0.04109477996826172 nb_pixel_total : 10916 time to create 1 rle with old method : 0.01472163200378418 length of segment : 137 time for calcul the mask position with numpy : 0.017183542251586914 nb_pixel_total : 6399 time to create 1 rle with old method : 0.012580394744873047 length of segment : 81 time for calcul the mask position with numpy : 0.013993024826049805 nb_pixel_total : 7486 time to create 1 rle with old method : 0.013438701629638672 length of segment : 76 time for calcul the mask position with numpy : 0.034723520278930664 nb_pixel_total : 12200 time to create 1 rle with old method : 0.018091917037963867 length of segment : 122 time for calcul the mask position with numpy : 0.021284103393554688 nb_pixel_total : 6452 time to create 1 rle with old method : 0.01058053970336914 length of segment : 94 time for calcul the mask position with numpy : 0.02595996856689453 nb_pixel_total : 6433 time to create 1 rle with old method : 0.012053489685058594 length of segment : 90 time for calcul the mask position with numpy : 0.07517337799072266 nb_pixel_total : 22032 time to create 1 rle with old method : 0.028196334838867188 length of segment : 268 time for calcul the mask position with numpy : 0.09367156028747559 nb_pixel_total : 48820 time to create 1 rle with old method : 0.053673744201660156 length of segment : 278 time for calcul the mask position with numpy : 0.17221617698669434 nb_pixel_total : 89845 time to create 1 rle with old method : 0.09899687767028809 length of segment : 495 time for calcul the mask position with numpy : 0.058983564376831055 nb_pixel_total : 11541 time to create 1 rle with old method : 0.0170290470123291 length of segment : 147 time for calcul the mask position with numpy : 0.09387874603271484 nb_pixel_total : 37719 time to create 1 rle with old method : 0.04421496391296387 length of segment : 257 time for calcul the mask position with numpy : 0.04241323471069336 nb_pixel_total : 25009 time to create 1 rle with old method : 0.033638954162597656 length of segment : 187 time for calcul the mask position with numpy : 0.014321565628051758 nb_pixel_total : 9631 time to create 1 rle with old method : 0.015599489212036133 length of segment : 99 time for calcul the mask position with numpy : 0.03947567939758301 nb_pixel_total : 29300 time to create 1 rle with old method : 0.03412604331970215 length of segment : 149 time for calcul the mask position with numpy : 0.008351802825927734 nb_pixel_total : 5400 time to create 1 rle with old method : 0.007872819900512695 length of segment : 115 time for calcul the mask position with numpy : 0.03371930122375488 nb_pixel_total : 10666 time to create 1 rle with old method : 0.0175321102142334 length of segment : 193 time for calcul the mask position with numpy : 0.09926056861877441 nb_pixel_total : 57573 time to create 1 rle with old method : 0.06527876853942871 length of segment : 313 time for calcul the mask position with numpy : 0.07704830169677734 nb_pixel_total : 22690 time to create 1 rle with old method : 0.02876591682434082 length of segment : 275 time for calcul the mask position with numpy : 0.041422128677368164 nb_pixel_total : 12758 time to create 1 rle with old method : 0.020602941513061523 length of segment : 136 time for calcul the mask position with numpy : 0.030899524688720703 nb_pixel_total : 5457 time to create 1 rle with old method : 0.010574102401733398 length of segment : 95 time for calcul the mask position with numpy : 0.10764265060424805 nb_pixel_total : 61314 time to create 1 rle with old method : 0.07060813903808594 length of segment : 359 time for calcul the mask position with numpy : 0.14143109321594238 nb_pixel_total : 115095 time to create 1 rle with old method : 0.13171744346618652 length of segment : 276 time for calcul the mask position with numpy : 0.02381110191345215 nb_pixel_total : 11271 time to create 1 rle with old method : 0.01806807518005371 length of segment : 213 time for calcul the mask position with numpy : 0.03933429718017578 nb_pixel_total : 20033 time to create 1 rle with old method : 0.02569723129272461 length of segment : 156 time for calcul the mask position with numpy : 0.07404565811157227 nb_pixel_total : 20433 time to create 1 rle with old method : 0.0290679931640625 length of segment : 213 time for calcul the mask position with numpy : 0.004492044448852539 nb_pixel_total : 10792 time to create 1 rle with old method : 0.013417959213256836 length of segment : 135 time for calcul the mask position with numpy : 0.06586360931396484 nb_pixel_total : 33867 time to create 1 rle with old method : 0.038530826568603516 length of segment : 249 time for calcul the mask position with numpy : 0.1054694652557373 nb_pixel_total : 52980 time to create 1 rle with old method : 0.062416791915893555 length of segment : 377 time for calcul the mask position with numpy : 0.04714703559875488 nb_pixel_total : 20866 time to create 1 rle with old method : 0.027695417404174805 length of segment : 125 time for calcul the mask position with numpy : 0.05366826057434082 nb_pixel_total : 19528 time to create 1 rle with old method : 0.026394128799438477 length of segment : 159 time for calcul the mask position with numpy : 0.04889178276062012 nb_pixel_total : 31851 time to create 1 rle with old method : 0.038413047790527344 length of segment : 165 time for calcul the mask position with numpy : 0.12423014640808105 nb_pixel_total : 84581 time to create 1 rle with old method : 0.09335875511169434 length of segment : 323 time for calcul the mask position with numpy : 0.03427267074584961 nb_pixel_total : 21718 time to create 1 rle with old method : 0.026464223861694336 length of segment : 156 time for calcul the mask position with numpy : 0.020429611206054688 nb_pixel_total : 6726 time to create 1 rle with old method : 0.009887933731079102 length of segment : 109 time for calcul the mask position with numpy : 0.012357950210571289 nb_pixel_total : 10842 time to create 1 rle with old method : 0.017014026641845703 length of segment : 102 time for calcul the mask position with numpy : 0.08812713623046875 nb_pixel_total : 59268 time to create 1 rle with old method : 0.06673550605773926 length of segment : 329 time for calcul the mask position with numpy : 0.06087899208068848 nb_pixel_total : 19374 time to create 1 rle with old method : 0.026070833206176758 length of segment : 174 time for calcul the mask position with numpy : 0.1341695785522461 nb_pixel_total : 115425 time to create 1 rle with old method : 0.14221501350402832 length of segment : 445 time for calcul the mask position with numpy : 0.09087324142456055 nb_pixel_total : 41234 time to create 1 rle with old method : 0.05739474296569824 length of segment : 338 time for calcul the mask position with numpy : 0.05013871192932129 nb_pixel_total : 34186 time to create 1 rle with old method : 0.04595804214477539 length of segment : 252 time for calcul the mask position with numpy : 0.0200502872467041 nb_pixel_total : 4572 time to create 1 rle with old method : 0.008957862854003906 length of segment : 78 time for calcul the mask position with numpy : 0.015479803085327148 nb_pixel_total : 9533 time to create 1 rle with old method : 0.014383554458618164 length of segment : 102 time for calcul the mask position with numpy : 0.02318596839904785 nb_pixel_total : 9814 time to create 1 rle with old method : 0.016154766082763672 length of segment : 108 time for calcul the mask position with numpy : 0.03643965721130371 nb_pixel_total : 26753 time to create 1 rle with old method : 0.03432106971740723 length of segment : 248 time for calcul the mask position with numpy : 0.06447267532348633 nb_pixel_total : 31073 time to create 1 rle with old method : 0.038808584213256836 length of segment : 366 time for calcul the mask position with numpy : 0.05881166458129883 nb_pixel_total : 20027 time to create 1 rle with old method : 0.026621580123901367 length of segment : 167 time for calcul the mask position with numpy : 0.03860282897949219 nb_pixel_total : 10906 time to create 1 rle with old method : 0.017241477966308594 length of segment : 124 time for calcul the mask position with numpy : 0.0373532772064209 nb_pixel_total : 20397 time to create 1 rle with old method : 0.026685237884521484 length of segment : 142 time for calcul the mask position with numpy : 0.05461764335632324 nb_pixel_total : 23556 time to create 1 rle with old method : 0.030513763427734375 length of segment : 140 time for calcul the mask position with numpy : 0.12136340141296387 nb_pixel_total : 79777 time to create 1 rle with old method : 0.08780455589294434 length of segment : 364 time for calcul the mask position with numpy : 0.05664968490600586 nb_pixel_total : 14459 time to create 1 rle with old method : 0.020211219787597656 length of segment : 235 time for calcul the mask position with numpy : 0.09919285774230957 nb_pixel_total : 27741 time to create 1 rle with old method : 0.03493475914001465 length of segment : 209 time for calcul the mask position with numpy : 0.028331279754638672 nb_pixel_total : 8920 time to create 1 rle with old method : 0.015042304992675781 length of segment : 109 time for calcul the mask position with numpy : 0.05080699920654297 nb_pixel_total : 8187 time to create 1 rle with old method : 0.012026786804199219 length of segment : 228 time for calcul the mask position with numpy : 0.10156536102294922 nb_pixel_total : 44227 time to create 1 rle with old method : 0.04855847358703613 length of segment : 355 time for calcul the mask position with numpy : 0.08105182647705078 nb_pixel_total : 30686 time to create 1 rle with old method : 0.039865970611572266 length of segment : 237 time for calcul the mask position with numpy : 0.027724027633666992 nb_pixel_total : 11481 time to create 1 rle with old method : 0.01495671272277832 length of segment : 92 time for calcul the mask position with numpy : 0.10600662231445312 nb_pixel_total : 55446 time to create 1 rle with old method : 0.06334543228149414 length of segment : 356 time for calcul the mask position with numpy : 0.08407425880432129 nb_pixel_total : 32824 time to create 1 rle with old method : 0.04158425331115723 length of segment : 195 time for calcul the mask position with numpy : 0.020673513412475586 nb_pixel_total : 14271 time to create 1 rle with old method : 0.02039337158203125 length of segment : 159 time for calcul the mask position with numpy : 0.12585163116455078 nb_pixel_total : 51127 time to create 1 rle with old method : 0.06293463706970215 length of segment : 453 time for calcul the mask position with numpy : 0.16112256050109863 nb_pixel_total : 60208 time to create 1 rle with old method : 0.07064628601074219 length of segment : 281 time for calcul the mask position with numpy : 0.03308677673339844 nb_pixel_total : 9169 time to create 1 rle with old method : 0.013693571090698242 length of segment : 151 time for calcul the mask position with numpy : 0.009557723999023438 nb_pixel_total : 13863 time to create 1 rle with old method : 0.019681692123413086 length of segment : 161 time for calcul the mask position with numpy : 0.03553962707519531 nb_pixel_total : 13910 time to create 1 rle with old method : 0.017724275588989258 length of segment : 143 time for calcul the mask position with numpy : 0.10158944129943848 nb_pixel_total : 51247 time to create 1 rle with old method : 0.07137012481689453 length of segment : 343 time for calcul the mask position with numpy : 0.06467461585998535 nb_pixel_total : 18605 time to create 1 rle with old method : 0.028330564498901367 length of segment : 205 time for calcul the mask position with numpy : 0.07342171669006348 nb_pixel_total : 61884 time to create 1 rle with old method : 0.07854700088500977 length of segment : 328 time for calcul the mask position with numpy : 0.062363624572753906 nb_pixel_total : 39665 time to create 1 rle with old method : 0.050112247467041016 length of segment : 284 time for calcul the mask position with numpy : 0.01099705696105957 nb_pixel_total : 4511 time to create 1 rle with old method : 0.008921623229980469 length of segment : 62 time for calcul the mask position with numpy : 0.05463075637817383 nb_pixel_total : 41365 time to create 1 rle with old method : 0.049462318420410156 length of segment : 235 time for calcul the mask position with numpy : 0.06815910339355469 nb_pixel_total : 33516 time to create 1 rle with old method : 0.0383152961730957 length of segment : 297 time for calcul the mask position with numpy : 0.06371474266052246 nb_pixel_total : 13023 time to create 1 rle with old method : 0.019969463348388672 length of segment : 136 time for calcul the mask position with numpy : 0.11251449584960938 nb_pixel_total : 80461 time to create 1 rle with old method : 0.0914914608001709 length of segment : 333 time for calcul the mask position with numpy : 0.05642271041870117 nb_pixel_total : 27043 time to create 1 rle with old method : 0.03396916389465332 length of segment : 156 time for calcul the mask position with numpy : 0.26214027404785156 nb_pixel_total : 98672 time to create 1 rle with old method : 0.10959792137145996 length of segment : 567 time for calcul the mask position with numpy : 0.18129730224609375 nb_pixel_total : 64883 time to create 1 rle with old method : 0.07632112503051758 length of segment : 378 time for calcul the mask position with numpy : 0.21672916412353516 nb_pixel_total : 192852 time to create 1 rle with new method : 0.014306306838989258 length of segment : 592 time for calcul the mask position with numpy : 0.11703300476074219 nb_pixel_total : 39237 time to create 1 rle with old method : 0.04706597328186035 length of segment : 389 time for calcul the mask position with numpy : 0.07303905487060547 nb_pixel_total : 23023 time to create 1 rle with old method : 0.030548810958862305 length of segment : 208 time for calcul the mask position with numpy : 0.07674169540405273 nb_pixel_total : 30748 time to create 1 rle with old method : 0.03637290000915527 length of segment : 169 time for calcul the mask position with numpy : 0.06878280639648438 nb_pixel_total : 34142 time to create 1 rle with old method : 0.041605472564697266 length of segment : 336 time for calcul the mask position with numpy : 0.16398048400878906 nb_pixel_total : 56292 time to create 1 rle with old method : 0.06548929214477539 length of segment : 432 time for calcul the mask position with numpy : 0.055567264556884766 nb_pixel_total : 41604 time to create 1 rle with old method : 0.051563262939453125 length of segment : 259 time for calcul the mask position with numpy : 0.08137130737304688 nb_pixel_total : 27600 time to create 1 rle with old method : 0.035241127014160156 length of segment : 217 time for calcul the mask position with numpy : 0.07680058479309082 nb_pixel_total : 26093 time to create 1 rle with old method : 0.035802602767944336 length of segment : 282 time for calcul the mask position with numpy : 0.08928132057189941 nb_pixel_total : 55035 time to create 1 rle with old method : 0.06456565856933594 length of segment : 397 time for calcul the mask position with numpy : 0.08680224418640137 nb_pixel_total : 36804 time to create 1 rle with old method : 0.045995235443115234 length of segment : 401 time for calcul the mask position with numpy : 0.06812286376953125 nb_pixel_total : 30176 time to create 1 rle with old method : 0.03796029090881348 length of segment : 194 time for calcul the mask position with numpy : 0.018309831619262695 nb_pixel_total : 12996 time to create 1 rle with old method : 0.018833160400390625 length of segment : 145 time for calcul the mask position with numpy : 0.07639431953430176 nb_pixel_total : 21412 time to create 1 rle with old method : 0.03606534004211426 length of segment : 219 time for calcul the mask position with numpy : 0.03434443473815918 nb_pixel_total : 7858 time to create 1 rle with old method : 0.01183009147644043 length of segment : 218 time for calcul the mask position with numpy : 0.10366415977478027 nb_pixel_total : 43912 time to create 1 rle with old method : 0.0527806282043457 length of segment : 406 time for calcul the mask position with numpy : 0.11630034446716309 nb_pixel_total : 84600 time to create 1 rle with old method : 0.09614253044128418 length of segment : 453 time for calcul the mask position with numpy : 0.08761048316955566 nb_pixel_total : 41815 time to create 1 rle with old method : 0.049224853515625 length of segment : 297 time for calcul the mask position with numpy : 0.009051322937011719 nb_pixel_total : 7589 time to create 1 rle with old method : 0.010840177536010742 length of segment : 145 time for calcul the mask position with numpy : 0.045113563537597656 nb_pixel_total : 33913 time to create 1 rle with old method : 0.041538238525390625 length of segment : 412 time for calcul the mask position with numpy : 0.00010967254638671875 nb_pixel_total : 2931 time to create 1 rle with old method : 0.0035858154296875 length of segment : 58 time for calcul the mask position with numpy : 0.050606727600097656 nb_pixel_total : 14201 time to create 1 rle with old method : 0.019193649291992188 length of segment : 146 time for calcul the mask position with numpy : 0.09880924224853516 nb_pixel_total : 33758 time to create 1 rle with old method : 0.04380989074707031 length of segment : 251 time for calcul the mask position with numpy : 0.021030187606811523 nb_pixel_total : 12991 time to create 1 rle with old method : 0.018965721130371094 length of segment : 100 time for calcul the mask position with numpy : 0.04462075233459473 nb_pixel_total : 29164 time to create 1 rle with old method : 0.0386662483215332 length of segment : 157 time for calcul the mask position with numpy : 0.036328792572021484 nb_pixel_total : 23659 time to create 1 rle with old method : 0.03347039222717285 length of segment : 252 time for calcul the mask position with numpy : 0.04103350639343262 nb_pixel_total : 21369 time to create 1 rle with old method : 0.02733755111694336 length of segment : 178 time for calcul the mask position with numpy : 0.13912606239318848 nb_pixel_total : 59780 time to create 1 rle with old method : 0.06879687309265137 length of segment : 373 time for calcul the mask position with numpy : 0.1743922233581543 nb_pixel_total : 110409 time to create 1 rle with old method : 0.12429213523864746 length of segment : 313 time for calcul the mask position with numpy : 0.0936117172241211 nb_pixel_total : 27377 time to create 1 rle with old method : 0.034522056579589844 length of segment : 255 time for calcul the mask position with numpy : 0.09737753868103027 nb_pixel_total : 26487 time to create 1 rle with old method : 0.033110618591308594 length of segment : 235 time for calcul the mask position with numpy : 0.09688377380371094 nb_pixel_total : 30161 time to create 1 rle with old method : 0.03760814666748047 length of segment : 205 time for calcul the mask position with numpy : 0.07562804222106934 nb_pixel_total : 28656 time to create 1 rle with old method : 0.03638029098510742 length of segment : 160 time for calcul the mask position with numpy : 0.08478164672851562 nb_pixel_total : 25605 time to create 1 rle with old method : 0.032709598541259766 length of segment : 276 time for calcul the mask position with numpy : 0.07102799415588379 nb_pixel_total : 25625 time to create 1 rle with old method : 0.032578229904174805 length of segment : 202 time for calcul the mask position with numpy : 0.04943394660949707 nb_pixel_total : 25566 time to create 1 rle with old method : 0.03196310997009277 length of segment : 154 time for calcul the mask position with numpy : 0.08888030052185059 nb_pixel_total : 54887 time to create 1 rle with old method : 0.06074690818786621 length of segment : 298 time for calcul the mask position with numpy : 0.10368227958679199 nb_pixel_total : 44064 time to create 1 rle with old method : 0.05256509780883789 length of segment : 391 time for calcul the mask position with numpy : 0.026110172271728516 nb_pixel_total : 5327 time to create 1 rle with old method : 0.009246110916137695 length of segment : 87 time for calcul the mask position with numpy : 0.05512428283691406 nb_pixel_total : 22701 time to create 1 rle with old method : 0.028902769088745117 length of segment : 293 time for calcul the mask position with numpy : 0.01744675636291504 nb_pixel_total : 4037 time to create 1 rle with old method : 0.008126497268676758 length of segment : 62 time for calcul the mask position with numpy : 0.028430461883544922 nb_pixel_total : 27223 time to create 1 rle with old method : 0.06359243392944336 length of segment : 220 time for calcul the mask position with numpy : 0.16806697845458984 nb_pixel_total : 50502 time to create 1 rle with old method : 0.05920004844665527 length of segment : 416 time for calcul the mask position with numpy : 0.05348682403564453 nb_pixel_total : 18483 time to create 1 rle with old method : 0.02271103858947754 length of segment : 159 time for calcul the mask position with numpy : 0.07993602752685547 nb_pixel_total : 21999 time to create 1 rle with old method : 0.028818130493164062 length of segment : 202 time for calcul the mask position with numpy : 0.05453920364379883 nb_pixel_total : 15990 time to create 1 rle with old method : 0.02287459373474121 length of segment : 150 time for calcul the mask position with numpy : 0.028059005737304688 nb_pixel_total : 6252 time to create 1 rle with old method : 0.011157512664794922 length of segment : 64 time for calcul the mask position with numpy : 0.05439639091491699 nb_pixel_total : 16929 time to create 1 rle with old method : 0.021241426467895508 length of segment : 176 time for calcul the mask position with numpy : 0.17247462272644043 nb_pixel_total : 131268 time to create 1 rle with old method : 0.1627492904663086 length of segment : 542 time for calcul the mask position with numpy : 0.031025171279907227 nb_pixel_total : 14132 time to create 1 rle with old method : 0.016106843948364258 length of segment : 108 time for calcul the mask position with numpy : 0.10004425048828125 nb_pixel_total : 33209 time to create 1 rle with old method : 0.04265141487121582 length of segment : 242 time for calcul the mask position with numpy : 0.08532166481018066 nb_pixel_total : 28336 time to create 1 rle with old method : 0.03559613227844238 length of segment : 247 time for calcul the mask position with numpy : 0.09767913818359375 nb_pixel_total : 44345 time to create 1 rle with old method : 0.05222940444946289 length of segment : 240 time for calcul the mask position with numpy : 0.07453680038452148 nb_pixel_total : 28173 time to create 1 rle with old method : 0.03305864334106445 length of segment : 300 time for calcul the mask position with numpy : 0.16927146911621094 nb_pixel_total : 108448 time to create 1 rle with old method : 0.13117551803588867 length of segment : 371 time for calcul the mask position with numpy : 0.08511948585510254 nb_pixel_total : 57703 time to create 1 rle with old method : 0.06720805168151855 length of segment : 304 time for calcul the mask position with numpy : 0.007596254348754883 nb_pixel_total : 5073 time to create 1 rle with old method : 0.005571126937866211 length of segment : 67 time for calcul the mask position with numpy : 0.07121849060058594 nb_pixel_total : 29800 time to create 1 rle with old method : 0.03723454475402832 length of segment : 169 time for calcul the mask position with numpy : 0.018677711486816406 nb_pixel_total : 8119 time to create 1 rle with old method : 0.012493610382080078 length of segment : 117 time for calcul the mask position with numpy : 0.17454242706298828 nb_pixel_total : 36313 time to create 1 rle with old method : 0.045294761657714844 length of segment : 189 time for calcul the mask position with numpy : 0.12105464935302734 nb_pixel_total : 134437 time to create 1 rle with old method : 0.1507408618927002 length of segment : 378 time for calcul the mask position with numpy : 0.014266252517700195 nb_pixel_total : 6090 time to create 1 rle with old method : 0.009920120239257812 length of segment : 137 time for calcul the mask position with numpy : 0.09516286849975586 nb_pixel_total : 54606 time to create 1 rle with old method : 0.0614924430847168 length of segment : 381 time for calcul the mask position with numpy : 0.047544002532958984 nb_pixel_total : 18257 time to create 1 rle with old method : 0.021745681762695312 length of segment : 165 time for calcul the mask position with numpy : 0.02608323097229004 nb_pixel_total : 16753 time to create 1 rle with old method : 0.025299787521362305 length of segment : 99 time for calcul the mask position with numpy : 0.045320749282836914 nb_pixel_total : 14997 time to create 1 rle with old method : 0.020084857940673828 length of segment : 143 time for calcul the mask position with numpy : 0.02960348129272461 nb_pixel_total : 7223 time to create 1 rle with old method : 0.0112457275390625 length of segment : 140 time for calcul the mask position with numpy : 0.1522672176361084 nb_pixel_total : 51454 time to create 1 rle with old method : 0.05859947204589844 length of segment : 303 time for calcul the mask position with numpy : 0.17569422721862793 nb_pixel_total : 52652 time to create 1 rle with old method : 0.06055903434753418 length of segment : 569 time for calcul the mask position with numpy : 0.0982668399810791 nb_pixel_total : 39413 time to create 1 rle with old method : 0.051328182220458984 length of segment : 250 time for calcul the mask position with numpy : 0.1132667064666748 nb_pixel_total : 52887 time to create 1 rle with old method : 0.05853533744812012 length of segment : 432 time for calcul the mask position with numpy : 0.09246611595153809 nb_pixel_total : 56058 time to create 1 rle with old method : 0.06371665000915527 length of segment : 205 time for calcul the mask position with numpy : 0.10121488571166992 nb_pixel_total : 61212 time to create 1 rle with old method : 0.07400035858154297 length of segment : 269 time for calcul the mask position with numpy : 0.15214133262634277 nb_pixel_total : 84251 time to create 1 rle with old method : 0.0982363224029541 length of segment : 387 time for calcul the mask position with numpy : 0.07836031913757324 nb_pixel_total : 46544 time to create 1 rle with old method : 0.05574321746826172 length of segment : 254 time for calcul the mask position with numpy : 0.022155284881591797 nb_pixel_total : 13288 time to create 1 rle with old method : 0.018219947814941406 length of segment : 110 time for calcul the mask position with numpy : 0.0299685001373291 nb_pixel_total : 16168 time to create 1 rle with old method : 0.02298903465270996 length of segment : 153 time for calcul the mask position with numpy : 0.07012343406677246 nb_pixel_total : 45658 time to create 1 rle with old method : 0.05771350860595703 length of segment : 244 time for calcul the mask position with numpy : 0.1705493927001953 nb_pixel_total : 86668 time to create 1 rle with old method : 0.10163640975952148 length of segment : 489 time for calcul the mask position with numpy : 0.03520774841308594 nb_pixel_total : 32381 time to create 1 rle with old method : 0.039914608001708984 length of segment : 241 time for calcul the mask position with numpy : 0.05125093460083008 nb_pixel_total : 16867 time to create 1 rle with old method : 0.026118040084838867 length of segment : 171 time for calcul the mask position with numpy : 0.1407623291015625 nb_pixel_total : 74236 time to create 1 rle with old method : 0.08437156677246094 length of segment : 658 time for calcul the mask position with numpy : 0.09871339797973633 nb_pixel_total : 63253 time to create 1 rle with old method : 0.07001662254333496 length of segment : 368 time for calcul the mask position with numpy : 0.06359243392944336 nb_pixel_total : 26023 time to create 1 rle with old method : 0.03397774696350098 length of segment : 193 time for calcul the mask position with numpy : 0.36150264739990234 nb_pixel_total : 269519 time to create 1 rle with new method : 0.021192312240600586 length of segment : 576 time for calcul the mask position with numpy : 0.04863119125366211 nb_pixel_total : 31424 time to create 1 rle with old method : 0.03967595100402832 length of segment : 227 time for calcul the mask position with numpy : 0.1546940803527832 nb_pixel_total : 106170 time to create 1 rle with old method : 0.1216270923614502 length of segment : 341 time for calcul the mask position with numpy : 0.11426734924316406 nb_pixel_total : 149070 time to create 1 rle with old method : 0.17110061645507812 length of segment : 565 time for calcul the mask position with numpy : 0.02134418487548828 nb_pixel_total : 17480 time to create 1 rle with old method : 0.02461528778076172 length of segment : 152 time for calcul the mask position with numpy : 0.00145721435546875 nb_pixel_total : 17720 time to create 1 rle with old method : 0.020076751708984375 length of segment : 226 time for calcul the mask position with numpy : 0.021393299102783203 nb_pixel_total : 26958 time to create 1 rle with old method : 0.04132270812988281 length of segment : 172 time for calcul the mask position with numpy : 0.0319516658782959 nb_pixel_total : 12134 time to create 1 rle with old method : 0.017548561096191406 length of segment : 145 time for calcul the mask position with numpy : 0.03737163543701172 nb_pixel_total : 39785 time to create 1 rle with old method : 0.04953289031982422 length of segment : 301 time for calcul the mask position with numpy : 0.02532052993774414 nb_pixel_total : 9742 time to create 1 rle with old method : 0.01521754264831543 length of segment : 151 time for calcul the mask position with numpy : 0.13535213470458984 nb_pixel_total : 74289 time to create 1 rle with old method : 0.08911371231079102 length of segment : 427 time for calcul the mask position with numpy : 0.4656679630279541 nb_pixel_total : 410937 time to create 1 rle with new method : 0.03539872169494629 length of segment : 850 time for calcul the mask position with numpy : 0.049068450927734375 nb_pixel_total : 16934 time to create 1 rle with old method : 0.023699522018432617 length of segment : 207 time for calcul the mask position with numpy : 0.07972931861877441 nb_pixel_total : 98181 time to create 1 rle with old method : 0.13327908515930176 length of segment : 395 time for calcul the mask position with numpy : 0.13331317901611328 nb_pixel_total : 97534 time to create 1 rle with old method : 0.11128997802734375 length of segment : 551 time for calcul the mask position with numpy : 0.07762384414672852 nb_pixel_total : 29740 time to create 1 rle with old method : 0.03914785385131836 length of segment : 272 time for calcul the mask position with numpy : 0.09224104881286621 nb_pixel_total : 59760 time to create 1 rle with old method : 0.07286643981933594 length of segment : 248 time for calcul the mask position with numpy : 0.04036092758178711 nb_pixel_total : 65081 time to create 1 rle with old method : 0.0745382308959961 length of segment : 330 time for calcul the mask position with numpy : 0.014619112014770508 nb_pixel_total : 5703 time to create 1 rle with old method : 0.009725570678710938 length of segment : 60 time for calcul the mask position with numpy : 0.07849764823913574 nb_pixel_total : 26463 time to create 1 rle with old method : 0.03595566749572754 length of segment : 243 time for calcul the mask position with numpy : 0.16812777519226074 nb_pixel_total : 165811 time to create 1 rle with new method : 0.010497808456420898 length of segment : 738 time for calcul the mask position with numpy : 0.05261850357055664 nb_pixel_total : 13683 time to create 1 rle with old method : 0.02174210548400879 length of segment : 154 time for calcul the mask position with numpy : 0.0357208251953125 nb_pixel_total : 16122 time to create 1 rle with old method : 0.02295994758605957 length of segment : 155 time for calcul the mask position with numpy : 0.05403256416320801 nb_pixel_total : 28896 time to create 1 rle with old method : 0.03765416145324707 length of segment : 202 time for calcul the mask position with numpy : 0.18269753456115723 nb_pixel_total : 194303 time to create 1 rle with new method : 0.009968280792236328 length of segment : 507 time for calcul the mask position with numpy : 0.03831839561462402 nb_pixel_total : 20840 time to create 1 rle with old method : 0.028539180755615234 length of segment : 138 time for calcul the mask position with numpy : 0.04994964599609375 nb_pixel_total : 60832 time to create 1 rle with old method : 0.073822021484375 length of segment : 289 time for calcul the mask position with numpy : 0.05785799026489258 nb_pixel_total : 53291 time to create 1 rle with old method : 0.06722688674926758 length of segment : 344 time for calcul the mask position with numpy : 0.1707761287689209 nb_pixel_total : 250511 time to create 1 rle with new method : 0.01536870002746582 length of segment : 564 time for calcul the mask position with numpy : 0.03130149841308594 nb_pixel_total : 65485 time to create 1 rle with old method : 0.07509231567382812 length of segment : 377 time for calcul the mask position with numpy : 0.0555574893951416 nb_pixel_total : 37946 time to create 1 rle with old method : 0.04880332946777344 length of segment : 330 time for calcul the mask position with numpy : 0.025075435638427734 nb_pixel_total : 23464 time to create 1 rle with old method : 0.027456283569335938 length of segment : 194 time for calcul the mask position with numpy : 0.029124975204467773 nb_pixel_total : 29244 time to create 1 rle with old method : 0.03731346130371094 length of segment : 199 time for calcul the mask position with numpy : 0.0341334342956543 nb_pixel_total : 8266 time to create 1 rle with old method : 0.013023853302001953 length of segment : 178 time for calcul the mask position with numpy : 0.19547247886657715 nb_pixel_total : 251128 time to create 1 rle with new method : 0.025966882705688477 length of segment : 617 time for calcul the mask position with numpy : 0.07277846336364746 nb_pixel_total : 61538 time to create 1 rle with old method : 0.07262611389160156 length of segment : 217 time for calcul the mask position with numpy : 0.02839350700378418 nb_pixel_total : 21979 time to create 1 rle with old method : 0.030706405639648438 length of segment : 222 time for calcul the mask position with numpy : 0.042684078216552734 nb_pixel_total : 20860 time to create 1 rle with old method : 0.029795169830322266 length of segment : 174 time for calcul the mask position with numpy : 0.04015183448791504 nb_pixel_total : 14786 time to create 1 rle with old method : 0.02192831039428711 length of segment : 133 time for calcul the mask position with numpy : 0.06514167785644531 nb_pixel_total : 18573 time to create 1 rle with old method : 0.02615642547607422 length of segment : 260 time for calcul the mask position with numpy : 0.16306734085083008 nb_pixel_total : 26907 time to create 1 rle with old method : 0.036713600158691406 length of segment : 218 time for calcul the mask position with numpy : 0.2690160274505615 nb_pixel_total : 123870 time to create 1 rle with old method : 0.14008688926696777 length of segment : 688 time for calcul the mask position with numpy : 0.09013843536376953 nb_pixel_total : 42984 time to create 1 rle with old method : 0.05251264572143555 length of segment : 306 time for calcul the mask position with numpy : 0.07990455627441406 nb_pixel_total : 34984 time to create 1 rle with old method : 0.04700160026550293 length of segment : 225 time for calcul the mask position with numpy : 0.039636850357055664 nb_pixel_total : 20851 time to create 1 rle with old method : 0.029838085174560547 length of segment : 208 time for calcul the mask position with numpy : 0.03322744369506836 nb_pixel_total : 6985 time to create 1 rle with old method : 0.012958765029907227 length of segment : 82 time for calcul the mask position with numpy : 0.17406344413757324 nb_pixel_total : 92996 time to create 1 rle with old method : 0.10860085487365723 length of segment : 372 time for calcul the mask position with numpy : 0.023265361785888672 nb_pixel_total : 5926 time to create 1 rle with old method : 0.011358976364135742 length of segment : 98 time for calcul the mask position with numpy : 0.2021961212158203 nb_pixel_total : 167299 time to create 1 rle with new method : 0.012319803237915039 length of segment : 413 time for calcul the mask position with numpy : 0.05418753623962402 nb_pixel_total : 16605 time to create 1 rle with old method : 0.02339625358581543 length of segment : 164 time for calcul the mask position with numpy : 0.09702181816101074 nb_pixel_total : 25992 time to create 1 rle with old method : 0.03130459785461426 length of segment : 277 time for calcul the mask position with numpy : 0.12894582748413086 nb_pixel_total : 68410 time to create 1 rle with old method : 0.07998991012573242 length of segment : 210 time for calcul the mask position with numpy : 0.08994364738464355 nb_pixel_total : 48320 time to create 1 rle with old method : 0.05760836601257324 length of segment : 256 time for calcul the mask position with numpy : 0.42282557487487793 nb_pixel_total : 247672 time to create 1 rle with new method : 0.0276947021484375 length of segment : 958 time for calcul the mask position with numpy : 0.035962581634521484 nb_pixel_total : 20261 time to create 1 rle with old method : 0.024811506271362305 length of segment : 185 time for calcul the mask position with numpy : 0.021724700927734375 nb_pixel_total : 10453 time to create 1 rle with old method : 0.017081260681152344 length of segment : 146 time for calcul the mask position with numpy : 0.2915232181549072 nb_pixel_total : 204551 time to create 1 rle with new method : 0.020723819732666016 length of segment : 588 time for calcul the mask position with numpy : 0.1517329216003418 nb_pixel_total : 128179 time to create 1 rle with old method : 0.14530515670776367 length of segment : 294 time for calcul the mask position with numpy : 0.05969572067260742 nb_pixel_total : 19639 time to create 1 rle with old method : 0.02699422836303711 length of segment : 182 time for calcul the mask position with numpy : 0.12994647026062012 nb_pixel_total : 100123 time to create 1 rle with old method : 0.12280440330505371 length of segment : 369 time for calcul the mask position with numpy : 0.1333637237548828 nb_pixel_total : 117200 time to create 1 rle with old method : 0.13195562362670898 length of segment : 296 time for calcul the mask position with numpy : 0.0065746307373046875 nb_pixel_total : 118474 time to create 1 rle with old method : 0.1374049186706543 length of segment : 298 time for calcul the mask position with numpy : 0.10356950759887695 nb_pixel_total : 34334 time to create 1 rle with old method : 0.04150199890136719 length of segment : 253 time for calcul the mask position with numpy : 0.0241086483001709 nb_pixel_total : 20680 time to create 1 rle with old method : 0.030363798141479492 length of segment : 94 time for calcul the mask position with numpy : 0.02846693992614746 nb_pixel_total : 21259 time to create 1 rle with old method : 0.02887272834777832 length of segment : 340 time for calcul the mask position with numpy : 0.030709266662597656 nb_pixel_total : 38879 time to create 1 rle with old method : 0.04880046844482422 length of segment : 358 time for calcul the mask position with numpy : 0.010736942291259766 nb_pixel_total : 22990 time to create 1 rle with old method : 0.03407001495361328 length of segment : 272 time for calcul the mask position with numpy : 0.02086806297302246 nb_pixel_total : 26072 time to create 1 rle with old method : 0.033608436584472656 length of segment : 228 time for calcul the mask position with numpy : 0.03969597816467285 nb_pixel_total : 15424 time to create 1 rle with old method : 0.02430129051208496 length of segment : 174 time for calcul the mask position with numpy : 0.0008873939514160156 nb_pixel_total : 35183 time to create 1 rle with old method : 0.04027271270751953 length of segment : 329 time for calcul the mask position with numpy : 0.26439929008483887 nb_pixel_total : 121658 time to create 1 rle with old method : 0.13646721839904785 length of segment : 367 time for calcul the mask position with numpy : 0.11475181579589844 nb_pixel_total : 35219 time to create 1 rle with old method : 0.04428291320800781 length of segment : 193 time for calcul the mask position with numpy : 0.17635512351989746 nb_pixel_total : 67334 time to create 1 rle with old method : 0.07568573951721191 length of segment : 291 time for calcul the mask position with numpy : 0.09109377861022949 nb_pixel_total : 23984 time to create 1 rle with old method : 0.030195951461791992 length of segment : 223 time for calcul the mask position with numpy : 0.06411266326904297 nb_pixel_total : 19691 time to create 1 rle with old method : 0.02850341796875 length of segment : 117 time for calcul the mask position with numpy : 0.0319218635559082 nb_pixel_total : 15538 time to create 1 rle with old method : 0.026670217514038086 length of segment : 93 time for calcul the mask position with numpy : 0.09569787979125977 nb_pixel_total : 41419 time to create 1 rle with old method : 0.05098986625671387 length of segment : 246 time for calcul the mask position with numpy : 0.03636574745178223 nb_pixel_total : 19791 time to create 1 rle with old method : 0.028071165084838867 length of segment : 188 time for calcul the mask position with numpy : 0.12903571128845215 nb_pixel_total : 33001 time to create 1 rle with old method : 0.06427860260009766 length of segment : 371 time for calcul the mask position with numpy : 0.24873113632202148 nb_pixel_total : 117223 time to create 1 rle with old method : 0.14053845405578613 length of segment : 296 time for calcul the mask position with numpy : 0.0401453971862793 nb_pixel_total : 13921 time to create 1 rle with old method : 0.021741151809692383 length of segment : 109 time for calcul the mask position with numpy : 0.12144875526428223 nb_pixel_total : 45324 time to create 1 rle with old method : 0.057561635971069336 length of segment : 302 time for calcul the mask position with numpy : 0.062233686447143555 nb_pixel_total : 16353 time to create 1 rle with old method : 0.022267818450927734 length of segment : 165 time for calcul the mask position with numpy : 0.06821322441101074 nb_pixel_total : 43727 time to create 1 rle with old method : 0.05243253707885742 length of segment : 247 time for calcul the mask position with numpy : 0.20640778541564941 nb_pixel_total : 83200 time to create 1 rle with old method : 0.0948185920715332 length of segment : 441 time for calcul the mask position with numpy : 0.1298973560333252 nb_pixel_total : 33282 time to create 1 rle with old method : 0.044785499572753906 length of segment : 433 time for calcul the mask position with numpy : 0.11763691902160645 nb_pixel_total : 24119 time to create 1 rle with old method : 0.03633713722229004 length of segment : 248 time for calcul the mask position with numpy : 0.16600632667541504 nb_pixel_total : 47220 time to create 1 rle with old method : 0.056592702865600586 length of segment : 388 time for calcul the mask position with numpy : 0.06921505928039551 nb_pixel_total : 24619 time to create 1 rle with old method : 0.030699491500854492 length of segment : 215 time for calcul the mask position with numpy : 0.14331841468811035 nb_pixel_total : 113864 time to create 1 rle with old method : 0.13243961334228516 length of segment : 300 time for calcul the mask position with numpy : 0.016971111297607422 nb_pixel_total : 14570 time to create 1 rle with old method : 0.01938915252685547 length of segment : 243 time for calcul the mask position with numpy : 0.03207254409790039 nb_pixel_total : 26812 time to create 1 rle with old method : 0.03468441963195801 length of segment : 239 time for calcul the mask position with numpy : 0.2828254699707031 nb_pixel_total : 143948 time to create 1 rle with old method : 0.16848278045654297 length of segment : 264 time for calcul the mask position with numpy : 0.13504433631896973 nb_pixel_total : 50653 time to create 1 rle with old method : 0.060894012451171875 length of segment : 332 time for calcul the mask position with numpy : 0.041527509689331055 nb_pixel_total : 40119 time to create 1 rle with old method : 0.04792380332946777 length of segment : 266 time for calcul the mask position with numpy : 0.02401876449584961 nb_pixel_total : 6420 time to create 1 rle with old method : 0.01134943962097168 length of segment : 89 time for calcul the mask position with numpy : 0.10121488571166992 nb_pixel_total : 43101 time to create 1 rle with old method : 0.05418658256530762 length of segment : 307 time for calcul the mask position with numpy : 0.06407999992370605 nb_pixel_total : 16986 time to create 1 rle with old method : 0.02386188507080078 length of segment : 155 time for calcul the mask position with numpy : 0.006155967712402344 nb_pixel_total : 12579 time to create 1 rle with old method : 0.01735544204711914 length of segment : 122 time for calcul the mask position with numpy : 0.093475341796875 nb_pixel_total : 24729 time to create 1 rle with old method : 0.03551912307739258 length of segment : 177 time for calcul the mask position with numpy : 0.1129305362701416 nb_pixel_total : 68823 time to create 1 rle with old method : 0.10372567176818848 length of segment : 257 time for calcul the mask position with numpy : 0.053566694259643555 nb_pixel_total : 11158 time to create 1 rle with old method : 0.01923346519470215 length of segment : 153 time for calcul the mask position with numpy : 0.03854489326477051 nb_pixel_total : 10518 time to create 1 rle with old method : 0.011835336685180664 length of segment : 123 time for calcul the mask position with numpy : 0.0004413127899169922 nb_pixel_total : 14326 time to create 1 rle with old method : 0.016210556030273438 length of segment : 187 time for calcul the mask position with numpy : 0.27771592140197754 nb_pixel_total : 155030 time to create 1 rle with new method : 0.03171896934509277 length of segment : 560 time for calcul the mask position with numpy : 0.0746307373046875 nb_pixel_total : 29780 time to create 1 rle with old method : 0.0387120246887207 length of segment : 212 time for calcul the mask position with numpy : 0.0032892227172851562 nb_pixel_total : 23690 time to create 1 rle with old method : 0.026717662811279297 length of segment : 256 time for calcul the mask position with numpy : 0.06083202362060547 nb_pixel_total : 13343 time to create 1 rle with old method : 0.019699573516845703 length of segment : 128 time for calcul the mask position with numpy : 0.10546660423278809 nb_pixel_total : 29430 time to create 1 rle with old method : 0.05048990249633789 length of segment : 292 time for calcul the mask position with numpy : 0.04162454605102539 nb_pixel_total : 10457 time to create 1 rle with old method : 0.015241384506225586 length of segment : 148 time for calcul the mask position with numpy : 0.23047494888305664 nb_pixel_total : 93942 time to create 1 rle with old method : 0.10990071296691895 length of segment : 335 time for calcul the mask position with numpy : 0.6825306415557861 nb_pixel_total : 215636 time to create 1 rle with new method : 0.023780107498168945 length of segment : 628 time for calcul the mask position with numpy : 0.15068578720092773 nb_pixel_total : 42629 time to create 1 rle with old method : 0.05334281921386719 length of segment : 345 time for calcul the mask position with numpy : 0.198150634765625 nb_pixel_total : 44532 time to create 1 rle with old method : 0.0545964241027832 length of segment : 372 time for calcul the mask position with numpy : 0.03436613082885742 nb_pixel_total : 10523 time to create 1 rle with old method : 0.01745152473449707 length of segment : 139 time for calcul the mask position with numpy : 0.03851628303527832 nb_pixel_total : 17345 time to create 1 rle with old method : 0.023787975311279297 length of segment : 169 time for calcul the mask position with numpy : 0.24483060836791992 nb_pixel_total : 79352 time to create 1 rle with old method : 0.09664559364318848 length of segment : 361 time for calcul the mask position with numpy : 0.182142972946167 nb_pixel_total : 65963 time to create 1 rle with old method : 0.0733499526977539 length of segment : 338 time for calcul the mask position with numpy : 0.11476778984069824 nb_pixel_total : 54630 time to create 1 rle with old method : 0.06353569030761719 length of segment : 301 time for calcul the mask position with numpy : 0.04108786582946777 nb_pixel_total : 10831 time to create 1 rle with old method : 0.01567530632019043 length of segment : 116 time for calcul the mask position with numpy : 0.6506283283233643 nb_pixel_total : 411357 time to create 1 rle with new method : 0.04217410087585449 length of segment : 664 time for calcul the mask position with numpy : 0.019033193588256836 nb_pixel_total : 9324 time to create 1 rle with old method : 0.010241985321044922 length of segment : 119 time for calcul the mask position with numpy : 0.08006834983825684 nb_pixel_total : 34162 time to create 1 rle with old method : 0.043297529220581055 length of segment : 195 time for calcul the mask position with numpy : 0.0713968276977539 nb_pixel_total : 23146 time to create 1 rle with old method : 0.028133153915405273 length of segment : 175 time for calcul the mask position with numpy : 0.017282962799072266 nb_pixel_total : 15651 time to create 1 rle with old method : 0.021889448165893555 length of segment : 189 time for calcul the mask position with numpy : 0.062328338623046875 nb_pixel_total : 25626 time to create 1 rle with old method : 0.03345298767089844 length of segment : 242 time for calcul the mask position with numpy : 0.05007672309875488 nb_pixel_total : 13709 time to create 1 rle with old method : 0.026418685913085938 length of segment : 164 time for calcul the mask position with numpy : 0.08283495903015137 nb_pixel_total : 24327 time to create 1 rle with old method : 0.03230452537536621 length of segment : 178 time for calcul the mask position with numpy : 0.016272544860839844 nb_pixel_total : 5644 time to create 1 rle with old method : 0.00653076171875 length of segment : 76 time for calcul the mask position with numpy : 0.1175386905670166 nb_pixel_total : 46315 time to create 1 rle with old method : 0.05770993232727051 length of segment : 331 time for calcul the mask position with numpy : 0.016016244888305664 nb_pixel_total : 3433 time to create 1 rle with old method : 0.006242513656616211 length of segment : 86 time for calcul the mask position with numpy : 0.3091461658477783 nb_pixel_total : 149351 time to create 1 rle with old method : 0.18606257438659668 length of segment : 570 time for calcul the mask position with numpy : 0.029885053634643555 nb_pixel_total : 8085 time to create 1 rle with old method : 0.014584779739379883 length of segment : 102 time for calcul the mask position with numpy : 0.0707864761352539 nb_pixel_total : 39700 time to create 1 rle with old method : 0.04889726638793945 length of segment : 280 time for calcul the mask position with numpy : 0.0004611015319824219 nb_pixel_total : 9128 time to create 1 rle with old method : 0.010787010192871094 length of segment : 218 time for calcul the mask position with numpy : 0.27992749214172363 nb_pixel_total : 145199 time to create 1 rle with old method : 0.1639852523803711 length of segment : 413 time for calcul the mask position with numpy : 0.06842398643493652 nb_pixel_total : 22676 time to create 1 rle with old method : 0.02849268913269043 length of segment : 308 time for calcul the mask position with numpy : 0.02863287925720215 nb_pixel_total : 36170 time to create 1 rle with old method : 0.043477773666381836 length of segment : 224 time for calcul the mask position with numpy : 0.08623480796813965 nb_pixel_total : 32366 time to create 1 rle with old method : 0.04179239273071289 length of segment : 190 time for calcul the mask position with numpy : 0.04154682159423828 nb_pixel_total : 20214 time to create 1 rle with old method : 0.030258655548095703 length of segment : 178 time for calcul the mask position with numpy : 0.04062509536743164 nb_pixel_total : 36540 time to create 1 rle with old method : 0.04589509963989258 length of segment : 269 time for calcul the mask position with numpy : 0.00029015541076660156 nb_pixel_total : 7928 time to create 1 rle with old method : 0.00881195068359375 length of segment : 175 time for calcul the mask position with numpy : 0.14854216575622559 nb_pixel_total : 80763 time to create 1 rle with old method : 0.09310555458068848 length of segment : 366 time for calcul the mask position with numpy : 0.025085926055908203 nb_pixel_total : 6492 time to create 1 rle with old method : 0.01194000244140625 length of segment : 85 time for calcul the mask position with numpy : 0.01474905014038086 nb_pixel_total : 98913 time to create 1 rle with old method : 0.11163735389709473 length of segment : 426 time for calcul the mask position with numpy : 0.1441652774810791 nb_pixel_total : 118169 time to create 1 rle with old method : 0.13918161392211914 length of segment : 478 time for calcul the mask position with numpy : 0.007545948028564453 nb_pixel_total : 43769 time to create 1 rle with old method : 0.0508122444152832 length of segment : 223 time for calcul the mask position with numpy : 0.009340047836303711 nb_pixel_total : 5735 time to create 1 rle with old method : 0.008775949478149414 length of segment : 48 time for calcul the mask position with numpy : 0.042772531509399414 nb_pixel_total : 23350 time to create 1 rle with old method : 0.030225276947021484 length of segment : 379 time for calcul the mask position with numpy : 0.0057370662689208984 nb_pixel_total : 56211 time to create 1 rle with old method : 0.06711888313293457 length of segment : 253 time for calcul the mask position with numpy : 0.044857025146484375 nb_pixel_total : 13573 time to create 1 rle with old method : 0.018872499465942383 length of segment : 163 time for calcul the mask position with numpy : 0.03337979316711426 nb_pixel_total : 46905 time to create 1 rle with old method : 0.05608558654785156 length of segment : 260 time for calcul the mask position with numpy : 0.0027496814727783203 nb_pixel_total : 23406 time to create 1 rle with old method : 0.03242778778076172 length of segment : 163 time for calcul the mask position with numpy : 0.0008542537689208984 nb_pixel_total : 13859 time to create 1 rle with old method : 0.017216920852661133 length of segment : 197 time for calcul the mask position with numpy : 0.061887502670288086 nb_pixel_total : 83912 time to create 1 rle with old method : 0.09610605239868164 length of segment : 471 time for calcul the mask position with numpy : 0.0164339542388916 nb_pixel_total : 36322 time to create 1 rle with old method : 0.06621789932250977 length of segment : 205 time for calcul the mask position with numpy : 0.025714397430419922 nb_pixel_total : 58111 time to create 1 rle with old method : 0.07139039039611816 length of segment : 468 time for calcul the mask position with numpy : 0.048033714294433594 nb_pixel_total : 48866 time to create 1 rle with old method : 0.05781912803649902 length of segment : 292 time for calcul the mask position with numpy : 0.01668834686279297 nb_pixel_total : 20172 time to create 1 rle with old method : 0.03273320198059082 length of segment : 155 time for calcul the mask position with numpy : 0.09220600128173828 nb_pixel_total : 101468 time to create 1 rle with old method : 0.11502242088317871 length of segment : 754 time for calcul the mask position with numpy : 0.03991508483886719 nb_pixel_total : 61518 time to create 1 rle with old method : 0.0736534595489502 length of segment : 579 time for calcul the mask position with numpy : 0.0006170272827148438 nb_pixel_total : 12933 time to create 1 rle with old method : 0.015005350112915039 length of segment : 144 time for calcul the mask position with numpy : 0.021239042282104492 nb_pixel_total : 29594 time to create 1 rle with old method : 0.0381927490234375 length of segment : 199 time for calcul the mask position with numpy : 0.06201434135437012 nb_pixel_total : 45745 time to create 1 rle with old method : 0.056052207946777344 length of segment : 557 time for calcul the mask position with numpy : 0.0007970333099365234 nb_pixel_total : 9926 time to create 1 rle with old method : 0.012591361999511719 length of segment : 79 time for calcul the mask position with numpy : 0.03217792510986328 nb_pixel_total : 52684 time to create 1 rle with old method : 0.06534266471862793 length of segment : 280 time for calcul the mask position with numpy : 0.01378631591796875 nb_pixel_total : 3711 time to create 1 rle with old method : 0.006941556930541992 length of segment : 80 time for calcul the mask position with numpy : 0.011223554611206055 nb_pixel_total : 35208 time to create 1 rle with old method : 0.04897189140319824 length of segment : 414 time for calcul the mask position with numpy : 0.00258636474609375 nb_pixel_total : 31234 time to create 1 rle with old method : 0.03638005256652832 length of segment : 199 time for calcul the mask position with numpy : 0.038750648498535156 nb_pixel_total : 83006 time to create 1 rle with old method : 0.12095499038696289 length of segment : 538 time for calcul the mask position with numpy : 0.0060842037200927734 nb_pixel_total : 27271 time to create 1 rle with old method : 0.03418588638305664 length of segment : 202 time for calcul the mask position with numpy : 0.01842021942138672 nb_pixel_total : 24949 time to create 1 rle with old method : 0.033905744552612305 length of segment : 166 time for calcul the mask position with numpy : 0.005074977874755859 nb_pixel_total : 12830 time to create 1 rle with old method : 0.02047896385192871 length of segment : 144 time for calcul the mask position with numpy : 0.002099275588989258 nb_pixel_total : 14237 time to create 1 rle with old method : 0.017625808715820312 length of segment : 99 time for calcul the mask position with numpy : 0.014379262924194336 nb_pixel_total : 84503 time to create 1 rle with old method : 0.09630966186523438 length of segment : 364 time for calcul the mask position with numpy : 0.002569437026977539 nb_pixel_total : 15399 time to create 1 rle with old method : 0.0172882080078125 length of segment : 171 time for calcul the mask position with numpy : 0.0011191368103027344 nb_pixel_total : 7398 time to create 1 rle with old method : 0.008530616760253906 length of segment : 104 time for calcul the mask position with numpy : 0.0015606880187988281 nb_pixel_total : 15483 time to create 1 rle with old method : 0.017841577529907227 length of segment : 125 time for calcul the mask position with numpy : 0.009159326553344727 nb_pixel_total : 13908 time to create 1 rle with old method : 0.020075559616088867 length of segment : 134 time for calcul the mask position with numpy : 0.007763385772705078 nb_pixel_total : 34878 time to create 1 rle with old method : 0.04180598258972168 length of segment : 281 time for calcul the mask position with numpy : 0.002064943313598633 nb_pixel_total : 33465 time to create 1 rle with old method : 0.036904096603393555 length of segment : 234 time for calcul the mask position with numpy : 0.010615348815917969 nb_pixel_total : 61781 time to create 1 rle with old method : 0.06911325454711914 length of segment : 339 time for calcul the mask position with numpy : 0.0019273757934570312 nb_pixel_total : 24125 time to create 1 rle with old method : 0.02783942222595215 length of segment : 192 time for calcul the mask position with numpy : 0.010181665420532227 nb_pixel_total : 50459 time to create 1 rle with old method : 0.05923128128051758 length of segment : 343 time for calcul the mask position with numpy : 0.0023872852325439453 nb_pixel_total : 14140 time to create 1 rle with old method : 0.016213655471801758 length of segment : 213 time for calcul the mask position with numpy : 0.00039005279541015625 nb_pixel_total : 8737 time to create 1 rle with old method : 0.009747028350830078 length of segment : 129 time for calcul the mask position with numpy : 0.001226663589477539 nb_pixel_total : 12063 time to create 1 rle with old method : 0.013618230819702148 length of segment : 163 time for calcul the mask position with numpy : 0.003516674041748047 nb_pixel_total : 11823 time to create 1 rle with old method : 0.0133056640625 length of segment : 154 time for calcul the mask position with numpy : 0.05901193618774414 nb_pixel_total : 189824 time to create 1 rle with new method : 0.012098073959350586 length of segment : 505 time for calcul the mask position with numpy : 0.0006515979766845703 nb_pixel_total : 12261 time to create 1 rle with old method : 0.013657808303833008 length of segment : 111 time for calcul the mask position with numpy : 0.00024199485778808594 nb_pixel_total : 11270 time to create 1 rle with old method : 0.013027191162109375 length of segment : 82 time for calcul the mask position with numpy : 0.005115509033203125 nb_pixel_total : 39254 time to create 1 rle with old method : 0.04660201072692871 length of segment : 216 time for calcul the mask position with numpy : 0.0008642673492431641 nb_pixel_total : 15265 time to create 1 rle with old method : 0.016804933547973633 length of segment : 172 time for calcul the mask position with numpy : 0.0018336772918701172 nb_pixel_total : 17551 time to create 1 rle with old method : 0.01935410499572754 length of segment : 243 time for calcul the mask position with numpy : 0.0002567768096923828 nb_pixel_total : 3886 time to create 1 rle with old method : 0.00461578369140625 length of segment : 64 time for calcul the mask position with numpy : 0.0016150474548339844 nb_pixel_total : 6873 time to create 1 rle with old method : 0.013279914855957031 length of segment : 115 time for calcul the mask position with numpy : 0.015035390853881836 nb_pixel_total : 40663 time to create 1 rle with old method : 0.06002235412597656 length of segment : 496 time for calcul the mask position with numpy : 0.006698131561279297 nb_pixel_total : 62958 time to create 1 rle with old method : 0.07509016990661621 length of segment : 418 time for calcul the mask position with numpy : 0.0023245811462402344 nb_pixel_total : 22566 time to create 1 rle with old method : 0.026309728622436523 length of segment : 117 time for calcul the mask position with numpy : 0.0009465217590332031 nb_pixel_total : 11394 time to create 1 rle with old method : 0.013348102569580078 length of segment : 134 time for calcul the mask position with numpy : 0.0049991607666015625 nb_pixel_total : 53108 time to create 1 rle with old method : 0.060399532318115234 length of segment : 383 time for calcul the mask position with numpy : 0.0017817020416259766 nb_pixel_total : 16004 time to create 1 rle with old method : 0.023594379425048828 length of segment : 84 time for calcul the mask position with numpy : 0.002652406692504883 nb_pixel_total : 20696 time to create 1 rle with old method : 0.023894071578979492 length of segment : 204 time for calcul the mask position with numpy : 0.006032228469848633 nb_pixel_total : 69885 time to create 1 rle with old method : 0.07949328422546387 length of segment : 326 time for calcul the mask position with numpy : 0.004180908203125 nb_pixel_total : 19951 time to create 1 rle with old method : 0.029326915740966797 length of segment : 193 time for calcul the mask position with numpy : 0.004641532897949219 nb_pixel_total : 30256 time to create 1 rle with old method : 0.03505825996398926 length of segment : 234 time for calcul the mask position with numpy : 0.0005643367767333984 nb_pixel_total : 12461 time to create 1 rle with old method : 0.0167391300201416 length of segment : 136 time for calcul the mask position with numpy : 0.0014481544494628906 nb_pixel_total : 21940 time to create 1 rle with old method : 0.02551555633544922 length of segment : 147 time for calcul the mask position with numpy : 0.003311634063720703 nb_pixel_total : 23755 time to create 1 rle with old method : 0.0393524169921875 length of segment : 240 time for calcul the mask position with numpy : 0.004338979721069336 nb_pixel_total : 57850 time to create 1 rle with old method : 0.07190608978271484 length of segment : 280 time for calcul the mask position with numpy : 0.002651691436767578 nb_pixel_total : 18915 time to create 1 rle with old method : 0.031342506408691406 length of segment : 176 time for calcul the mask position with numpy : 0.013379812240600586 nb_pixel_total : 39198 time to create 1 rle with old method : 0.04573941230773926 length of segment : 229 time for calcul the mask position with numpy : 0.023523330688476562 nb_pixel_total : 55024 time to create 1 rle with old method : 0.08040547370910645 length of segment : 641 time for calcul the mask position with numpy : 0.003309011459350586 nb_pixel_total : 42356 time to create 1 rle with old method : 0.0498967170715332 length of segment : 272 time for calcul the mask position with numpy : 0.0017933845520019531 nb_pixel_total : 14635 time to create 1 rle with old method : 0.016836881637573242 length of segment : 166 time for calcul the mask position with numpy : 0.003026723861694336 nb_pixel_total : 18770 time to create 1 rle with old method : 0.021332740783691406 length of segment : 153 time for calcul the mask position with numpy : 0.0007295608520507812 nb_pixel_total : 14832 time to create 1 rle with old method : 0.017098665237426758 length of segment : 137 time for calcul the mask position with numpy : 0.010222911834716797 nb_pixel_total : 129875 time to create 1 rle with old method : 0.1480724811553955 length of segment : 516 time for calcul the mask position with numpy : 0.0016946792602539062 nb_pixel_total : 27763 time to create 1 rle with old method : 0.03089451789855957 length of segment : 191 time for calcul the mask position with numpy : 0.0049250125885009766 nb_pixel_total : 42545 time to create 1 rle with old method : 0.04850411415100098 length of segment : 267 time for calcul the mask position with numpy : 0.005931854248046875 nb_pixel_total : 26861 time to create 1 rle with old method : 0.03539586067199707 length of segment : 270 time for calcul the mask position with numpy : 0.000644683837890625 nb_pixel_total : 9193 time to create 1 rle with old method : 0.010437488555908203 length of segment : 202 time for calcul the mask position with numpy : 0.003175020217895508 nb_pixel_total : 41549 time to create 1 rle with old method : 0.046762943267822266 length of segment : 220 time for calcul the mask position with numpy : 0.001703023910522461 nb_pixel_total : 20496 time to create 1 rle with old method : 0.023618459701538086 length of segment : 168 time for calcul the mask position with numpy : 0.001222372055053711 nb_pixel_total : 10583 time to create 1 rle with old method : 0.013623476028442383 length of segment : 140 time for calcul the mask position with numpy : 0.0014421939849853516 nb_pixel_total : 16934 time to create 1 rle with old method : 0.0196533203125 length of segment : 127 time for calcul the mask position with numpy : 0.0009207725524902344 nb_pixel_total : 8671 time to create 1 rle with old method : 0.011039257049560547 length of segment : 84 time for calcul the mask position with numpy : 0.0028383731842041016 nb_pixel_total : 43391 time to create 1 rle with old method : 0.05161595344543457 length of segment : 356 time for calcul the mask position with numpy : 0.0014069080352783203 nb_pixel_total : 22673 time to create 1 rle with old method : 0.027358055114746094 length of segment : 251 time for calcul the mask position with numpy : 0.0036873817443847656 nb_pixel_total : 75550 time to create 1 rle with old method : 0.08641290664672852 length of segment : 425 time for calcul the mask position with numpy : 0.0009872913360595703 nb_pixel_total : 12704 time to create 1 rle with old method : 0.014724493026733398 length of segment : 118 time for calcul the mask position with numpy : 0.0006561279296875 nb_pixel_total : 4650 time to create 1 rle with old method : 0.005802631378173828 length of segment : 75 time for calcul the mask position with numpy : 0.0006084442138671875 nb_pixel_total : 6607 time to create 1 rle with old method : 0.007733821868896484 length of segment : 129 time for calcul the mask position with numpy : 0.001556396484375 nb_pixel_total : 22642 time to create 1 rle with old method : 0.026715993881225586 length of segment : 151 time for calcul the mask position with numpy : 0.0004742145538330078 nb_pixel_total : 13461 time to create 1 rle with old method : 0.015747785568237305 length of segment : 232 time for calcul the mask position with numpy : 0.015247106552124023 nb_pixel_total : 25165 time to create 1 rle with old method : 0.032926321029663086 length of segment : 183 time for calcul the mask position with numpy : 0.00042128562927246094 nb_pixel_total : 12835 time to create 1 rle with old method : 0.015151023864746094 length of segment : 150 time for calcul the mask position with numpy : 0.012067556381225586 nb_pixel_total : 22126 time to create 1 rle with old method : 0.031610965728759766 length of segment : 159 time for calcul the mask position with numpy : 0.0026390552520751953 nb_pixel_total : 24420 time to create 1 rle with old method : 0.027181625366210938 length of segment : 226 time for calcul the mask position with numpy : 0.0022962093353271484 nb_pixel_total : 36298 time to create 1 rle with old method : 0.04108119010925293 length of segment : 299 time for calcul the mask position with numpy : 0.0007810592651367188 nb_pixel_total : 14514 time to create 1 rle with old method : 0.017105579376220703 length of segment : 121 time for calcul the mask position with numpy : 0.0009684562683105469 nb_pixel_total : 15208 time to create 1 rle with old method : 0.017247438430786133 length of segment : 153 time for calcul the mask position with numpy : 0.002284526824951172 nb_pixel_total : 16827 time to create 1 rle with old method : 0.018275976181030273 length of segment : 188 time for calcul the mask position with numpy : 0.0007393360137939453 nb_pixel_total : 9634 time to create 1 rle with old method : 0.010331392288208008 length of segment : 94 time for calcul the mask position with numpy : 0.001911163330078125 nb_pixel_total : 34102 time to create 1 rle with old method : 0.03705859184265137 length of segment : 232 time for calcul the mask position with numpy : 0.0011050701141357422 nb_pixel_total : 11896 time to create 1 rle with old method : 0.012971878051757812 length of segment : 165 time for calcul the mask position with numpy : 0.003983259201049805 nb_pixel_total : 24606 time to create 1 rle with old method : 0.026910066604614258 length of segment : 193 time for calcul the mask position with numpy : 0.00530552864074707 nb_pixel_total : 18439 time to create 1 rle with old method : 0.022393226623535156 length of segment : 198 time for calcul the mask position with numpy : 0.0019505023956298828 nb_pixel_total : 9179 time to create 1 rle with old method : 0.010701417922973633 length of segment : 196 time for calcul the mask position with numpy : 0.0010833740234375 nb_pixel_total : 13953 time to create 1 rle with old method : 0.015398979187011719 length of segment : 173 time for calcul the mask position with numpy : 0.0026397705078125 nb_pixel_total : 17094 time to create 1 rle with old method : 0.0210268497467041 length of segment : 202 time for calcul the mask position with numpy : 0.0016188621520996094 nb_pixel_total : 17189 time to create 1 rle with old method : 0.01957845687866211 length of segment : 179 time for calcul the mask position with numpy : 0.003393888473510742 nb_pixel_total : 56785 time to create 1 rle with old method : 0.06250905990600586 length of segment : 247 time for calcul the mask position with numpy : 0.001882314682006836 nb_pixel_total : 22167 time to create 1 rle with old method : 0.02408289909362793 length of segment : 202 time for calcul the mask position with numpy : 0.012330770492553711 nb_pixel_total : 41598 time to create 1 rle with old method : 0.04889082908630371 length of segment : 253 time for calcul the mask position with numpy : 0.0005276203155517578 nb_pixel_total : 6236 time to create 1 rle with old method : 0.006967782974243164 length of segment : 90 time for calcul the mask position with numpy : 0.0021076202392578125 nb_pixel_total : 24439 time to create 1 rle with old method : 0.027613401412963867 length of segment : 203 time for calcul the mask position with numpy : 0.0011444091796875 nb_pixel_total : 12866 time to create 1 rle with old method : 0.015088796615600586 length of segment : 151 time for calcul the mask position with numpy : 0.0011951923370361328 nb_pixel_total : 15369 time to create 1 rle with old method : 0.01752471923828125 length of segment : 190 time for calcul the mask position with numpy : 0.0008466243743896484 nb_pixel_total : 15786 time to create 1 rle with old method : 0.017544984817504883 length of segment : 142 time for calcul the mask position with numpy : 0.0042514801025390625 nb_pixel_total : 26982 time to create 1 rle with old method : 0.031350135803222656 length of segment : 245 time for calcul the mask position with numpy : 0.0017604827880859375 nb_pixel_total : 20805 time to create 1 rle with old method : 0.023560762405395508 length of segment : 175 time for calcul the mask position with numpy : 0.0008184909820556641 nb_pixel_total : 12837 time to create 1 rle with old method : 0.014927387237548828 length of segment : 114 time for calcul the mask position with numpy : 0.003086090087890625 nb_pixel_total : 46584 time to create 1 rle with old method : 0.051599740982055664 length of segment : 484 time for calcul the mask position with numpy : 0.0024824142456054688 nb_pixel_total : 23478 time to create 1 rle with old method : 0.02692556381225586 length of segment : 185 time for calcul the mask position with numpy : 0.0011844635009765625 nb_pixel_total : 14054 time to create 1 rle with old method : 0.016180992126464844 length of segment : 300 time for calcul the mask position with numpy : 0.0025620460510253906 nb_pixel_total : 37166 time to create 1 rle with old method : 0.04097127914428711 length of segment : 254 time for calcul the mask position with numpy : 0.0016069412231445312 nb_pixel_total : 17981 time to create 1 rle with old method : 0.0204317569732666 length of segment : 156 time for calcul the mask position with numpy : 0.0006728172302246094 nb_pixel_total : 9433 time to create 1 rle with old method : 0.011251688003540039 length of segment : 97 time for calcul the mask position with numpy : 0.0030641555786132812 nb_pixel_total : 29867 time to create 1 rle with old method : 0.03351283073425293 length of segment : 339 time for calcul the mask position with numpy : 0.002731800079345703 nb_pixel_total : 53649 time to create 1 rle with old method : 0.06031322479248047 length of segment : 310 time for calcul the mask position with numpy : 0.0008103847503662109 nb_pixel_total : 14158 time to create 1 rle with old method : 0.016593217849731445 length of segment : 135 time for calcul the mask position with numpy : 0.0017535686492919922 nb_pixel_total : 14320 time to create 1 rle with old method : 0.01674056053161621 length of segment : 177 time for calcul the mask position with numpy : 0.0028252601623535156 nb_pixel_total : 40934 time to create 1 rle with old method : 0.04615306854248047 length of segment : 270 time for calcul the mask position with numpy : 0.0010230541229248047 nb_pixel_total : 14626 time to create 1 rle with old method : 0.016895532608032227 length of segment : 135 time for calcul the mask position with numpy : 0.00520014762878418 nb_pixel_total : 47054 time to create 1 rle with old method : 0.053182363510131836 length of segment : 427 time for calcul the mask position with numpy : 0.0036945343017578125 nb_pixel_total : 50743 time to create 1 rle with old method : 0.05818653106689453 length of segment : 225 time for calcul the mask position with numpy : 0.0014445781707763672 nb_pixel_total : 16191 time to create 1 rle with old method : 0.018642425537109375 length of segment : 144 time for calcul the mask position with numpy : 0.00040531158447265625 nb_pixel_total : 4285 time to create 1 rle with old method : 0.004911184310913086 length of segment : 98 time for calcul the mask position with numpy : 0.005970954895019531 nb_pixel_total : 106557 time to create 1 rle with old method : 0.11858534812927246 length of segment : 493 time for calcul the mask position with numpy : 0.0011565685272216797 nb_pixel_total : 7194 time to create 1 rle with old method : 0.009104013442993164 length of segment : 117 time for calcul the mask position with numpy : 0.0008358955383300781 nb_pixel_total : 10494 time to create 1 rle with old method : 0.01298975944519043 length of segment : 84 time for calcul the mask position with numpy : 0.008173465728759766 nb_pixel_total : 30977 time to create 1 rle with old method : 0.03769087791442871 length of segment : 206 time for calcul the mask position with numpy : 0.016920089721679688 nb_pixel_total : 50742 time to create 1 rle with old method : 0.08936190605163574 length of segment : 257 time for calcul the mask position with numpy : 0.005087137222290039 nb_pixel_total : 34775 time to create 1 rle with old method : 0.045494794845581055 length of segment : 246 time for calcul the mask position with numpy : 0.0011396408081054688 nb_pixel_total : 21409 time to create 1 rle with old method : 0.024842023849487305 length of segment : 187 time for calcul the mask position with numpy : 0.004219532012939453 nb_pixel_total : 54813 time to create 1 rle with old method : 0.06226205825805664 length of segment : 331 time for calcul the mask position with numpy : 0.0016140937805175781 nb_pixel_total : 17762 time to create 1 rle with old method : 0.020611047744750977 length of segment : 193 time for calcul the mask position with numpy : 0.005576372146606445 nb_pixel_total : 85335 time to create 1 rle with old method : 0.09850668907165527 length of segment : 327 time for calcul the mask position with numpy : 0.0019311904907226562 nb_pixel_total : 28713 time to create 1 rle with old method : 0.032726287841796875 length of segment : 218 time for calcul the mask position with numpy : 0.0009882450103759766 nb_pixel_total : 17896 time to create 1 rle with old method : 0.02082538604736328 length of segment : 151 time for calcul the mask position with numpy : 0.0005054473876953125 nb_pixel_total : 9562 time to create 1 rle with old method : 0.010926961898803711 length of segment : 136 time for calcul the mask position with numpy : 0.001445770263671875 nb_pixel_total : 24501 time to create 1 rle with old method : 0.028278112411499023 length of segment : 196 time for calcul the mask position with numpy : 0.0015528202056884766 nb_pixel_total : 24379 time to create 1 rle with old method : 0.02830362319946289 length of segment : 191 time for calcul the mask position with numpy : 0.0009341239929199219 nb_pixel_total : 15877 time to create 1 rle with old method : 0.017802953720092773 length of segment : 356 time for calcul the mask position with numpy : 0.010355234146118164 nb_pixel_total : 167597 time to create 1 rle with new method : 0.014867067337036133 length of segment : 683 time for calcul the mask position with numpy : 0.0019648075103759766 nb_pixel_total : 28323 time to create 1 rle with old method : 0.03766751289367676 length of segment : 336 time for calcul the mask position with numpy : 0.005179166793823242 nb_pixel_total : 14632 time to create 1 rle with old method : 0.019656896591186523 length of segment : 143 time for calcul the mask position with numpy : 0.002124309539794922 nb_pixel_total : 39760 time to create 1 rle with old method : 0.04852652549743652 length of segment : 348 time for calcul the mask position with numpy : 0.0009722709655761719 nb_pixel_total : 18296 time to create 1 rle with old method : 0.020905256271362305 length of segment : 134 time for calcul the mask position with numpy : 0.006093502044677734 nb_pixel_total : 22021 time to create 1 rle with old method : 0.028837919235229492 length of segment : 405 time for calcul the mask position with numpy : 0.016860246658325195 nb_pixel_total : 342280 time to create 1 rle with new method : 0.03495502471923828 length of segment : 866 time for calcul the mask position with numpy : 0.00046944618225097656 nb_pixel_total : 5804 time to create 1 rle with old method : 0.007049083709716797 length of segment : 61 time for calcul the mask position with numpy : 0.0013110637664794922 nb_pixel_total : 27972 time to create 1 rle with old method : 0.032453060150146484 length of segment : 180 time for calcul the mask position with numpy : 0.002171754837036133 nb_pixel_total : 11728 time to create 1 rle with old method : 0.01391148567199707 length of segment : 166 time for calcul the mask position with numpy : 0.006887912750244141 nb_pixel_total : 36803 time to create 1 rle with old method : 0.04378056526184082 length of segment : 168 time for calcul the mask position with numpy : 0.0013375282287597656 nb_pixel_total : 17756 time to create 1 rle with old method : 0.02036762237548828 length of segment : 149 time for calcul the mask position with numpy : 0.0032596588134765625 nb_pixel_total : 49702 time to create 1 rle with old method : 0.055155277252197266 length of segment : 259 time for calcul the mask position with numpy : 0.0010356903076171875 nb_pixel_total : 15925 time to create 1 rle with old method : 0.0188446044921875 length of segment : 146 time for calcul the mask position with numpy : 0.004263162612915039 nb_pixel_total : 184245 time to create 1 rle with new method : 0.009658575057983398 length of segment : 445 time for calcul the mask position with numpy : 0.005049943923950195 nb_pixel_total : 83325 time to create 1 rle with old method : 0.09293341636657715 length of segment : 521 time for calcul the mask position with numpy : 0.00234222412109375 nb_pixel_total : 63502 time to create 1 rle with old method : 0.07022237777709961 length of segment : 242 time for calcul the mask position with numpy : 0.0010142326354980469 nb_pixel_total : 11399 time to create 1 rle with old method : 0.013127565383911133 length of segment : 132 time for calcul the mask position with numpy : 0.0007879734039306641 nb_pixel_total : 14194 time to create 1 rle with old method : 0.01676774024963379 length of segment : 102 time for calcul the mask position with numpy : 0.0008606910705566406 nb_pixel_total : 13410 time to create 1 rle with old method : 0.015827178955078125 length of segment : 131 time for calcul the mask position with numpy : 0.0008127689361572266 nb_pixel_total : 12685 time to create 1 rle with old method : 0.015140295028686523 length of segment : 122 time for calcul the mask position with numpy : 0.0007922649383544922 nb_pixel_total : 7964 time to create 1 rle with old method : 0.00959467887878418 length of segment : 109 time for calcul the mask position with numpy : 0.0041697025299072266 nb_pixel_total : 37908 time to create 1 rle with old method : 0.04634976387023926 length of segment : 260 time for calcul the mask position with numpy : 0.0015611648559570312 nb_pixel_total : 14611 time to create 1 rle with old method : 0.016739368438720703 length of segment : 234 time for calcul the mask position with numpy : 0.0007393360137939453 nb_pixel_total : 5417 time to create 1 rle with old method : 0.006459236145019531 length of segment : 115 time for calcul the mask position with numpy : 0.0012428760528564453 nb_pixel_total : 16400 time to create 1 rle with old method : 0.0190427303314209 length of segment : 115 time for calcul the mask position with numpy : 0.060861825942993164 nb_pixel_total : 850390 time to create 1 rle with new method : 0.08258914947509766 length of segment : 1219 time for calcul the mask position with numpy : 0.0012657642364501953 nb_pixel_total : 24372 time to create 1 rle with old method : 0.02978372573852539 length of segment : 191 time for calcul the mask position with numpy : 0.000629425048828125 nb_pixel_total : 9922 time to create 1 rle with old method : 0.011873483657836914 length of segment : 85 time for calcul the mask position with numpy : 0.002238750457763672 nb_pixel_total : 41677 time to create 1 rle with old method : 0.047508955001831055 length of segment : 337 time for calcul the mask position with numpy : 0.005429983139038086 nb_pixel_total : 115352 time to create 1 rle with old method : 0.12954092025756836 length of segment : 387 time for calcul the mask position with numpy : 0.0011548995971679688 nb_pixel_total : 14386 time to create 1 rle with old method : 0.01648426055908203 length of segment : 188 time for calcul the mask position with numpy : 0.004110813140869141 nb_pixel_total : 70512 time to create 1 rle with old method : 0.08051848411560059 length of segment : 288 time for calcul the mask position with numpy : 0.0007364749908447266 nb_pixel_total : 11436 time to create 1 rle with old method : 0.013069868087768555 length of segment : 236 time for calcul the mask position with numpy : 0.003983259201049805 nb_pixel_total : 77378 time to create 1 rle with old method : 0.08966708183288574 length of segment : 360 time for calcul the mask position with numpy : 0.0012443065643310547 nb_pixel_total : 16594 time to create 1 rle with old method : 0.021074533462524414 length of segment : 128 time for calcul the mask position with numpy : 0.0002963542938232422 nb_pixel_total : 3258 time to create 1 rle with old method : 0.00408625602722168 length of segment : 50 time for calcul the mask position with numpy : 0.001623392105102539 nb_pixel_total : 26433 time to create 1 rle with old method : 0.03158712387084961 length of segment : 187 time for calcul the mask position with numpy : 0.003259420394897461 nb_pixel_total : 39736 time to create 1 rle with old method : 0.04714536666870117 length of segment : 559 time for calcul the mask position with numpy : 0.000560760498046875 nb_pixel_total : 9245 time to create 1 rle with old method : 0.010954856872558594 length of segment : 58 time for calcul the mask position with numpy : 0.0018913745880126953 nb_pixel_total : 40016 time to create 1 rle with old method : 0.045574188232421875 length of segment : 182 time for calcul the mask position with numpy : 0.000934600830078125 nb_pixel_total : 13219 time to create 1 rle with old method : 0.014932632446289062 length of segment : 161 time for calcul the mask position with numpy : 0.0017864704132080078 nb_pixel_total : 27191 time to create 1 rle with old method : 0.03039407730102539 length of segment : 168 time for calcul the mask position with numpy : 0.003242969512939453 nb_pixel_total : 24681 time to create 1 rle with old method : 0.02845025062561035 length of segment : 273 time for calcul the mask position with numpy : 0.0011661052703857422 nb_pixel_total : 22434 time to create 1 rle with old method : 0.025858163833618164 length of segment : 139 time for calcul the mask position with numpy : 0.0004074573516845703 nb_pixel_total : 6473 time to create 1 rle with old method : 0.007593631744384766 length of segment : 111 time for calcul the mask position with numpy : 0.0014579296112060547 nb_pixel_total : 25668 time to create 1 rle with old method : 0.030063867568969727 length of segment : 123 time for calcul the mask position with numpy : 0.0007510185241699219 nb_pixel_total : 10491 time to create 1 rle with old method : 0.014632701873779297 length of segment : 119 time for calcul the mask position with numpy : 0.0021207332611083984 nb_pixel_total : 36681 time to create 1 rle with old method : 0.042255401611328125 length of segment : 199 time for calcul the mask position with numpy : 0.002824068069458008 nb_pixel_total : 40249 time to create 1 rle with old method : 0.04662466049194336 length of segment : 397 time for calcul the mask position with numpy : 0.0010042190551757812 nb_pixel_total : 16646 time to create 1 rle with old method : 0.019779682159423828 length of segment : 225 time for calcul the mask position with numpy : 0.00028586387634277344 nb_pixel_total : 8540 time to create 1 rle with old method : 0.010096073150634766 length of segment : 79 time for calcul the mask position with numpy : 0.0037839412689208984 nb_pixel_total : 51147 time to create 1 rle with old method : 0.06005263328552246 length of segment : 266 time for calcul the mask position with numpy : 0.00018787384033203125 nb_pixel_total : 5137 time to create 1 rle with old method : 0.006087541580200195 length of segment : 93 time for calcul the mask position with numpy : 0.0006618499755859375 nb_pixel_total : 9345 time to create 1 rle with old method : 0.010557174682617188 length of segment : 162 time for calcul the mask position with numpy : 0.0012998580932617188 nb_pixel_total : 15167 time to create 1 rle with old method : 0.017527103424072266 length of segment : 194 time for calcul the mask position with numpy : 0.0020296573638916016 nb_pixel_total : 40977 time to create 1 rle with old method : 0.046380043029785156 length of segment : 285 time for calcul the mask position with numpy : 0.003579854965209961 nb_pixel_total : 69733 time to create 1 rle with old method : 0.0789022445678711 length of segment : 290 time for calcul the mask position with numpy : 0.0002353191375732422 nb_pixel_total : 2142 time to create 1 rle with old method : 0.0026628971099853516 length of segment : 68 time for calcul the mask position with numpy : 0.0007851123809814453 nb_pixel_total : 9558 time to create 1 rle with old method : 0.011159896850585938 length of segment : 119 time for calcul the mask position with numpy : 0.00433349609375 nb_pixel_total : 92239 time to create 1 rle with old method : 0.10474467277526855 length of segment : 357 time for calcul the mask position with numpy : 0.010474920272827148 nb_pixel_total : 103247 time to create 1 rle with old method : 0.13074779510498047 length of segment : 385 time for calcul the mask position with numpy : 0.001383066177368164 nb_pixel_total : 23910 time to create 1 rle with old method : 0.027667760848999023 length of segment : 124 time for calcul the mask position with numpy : 8.344650268554688e-05 nb_pixel_total : 151 time to create 1 rle with old method : 0.0002715587615966797 length of segment : 29 time for calcul the mask position with numpy : 0.0054166316986083984 nb_pixel_total : 105836 time to create 1 rle with old method : 0.11926913261413574 length of segment : 525 time for calcul the mask position with numpy : 0.008429527282714844 nb_pixel_total : 92093 time to create 1 rle with old method : 0.10227060317993164 length of segment : 694 time for calcul the mask position with numpy : 0.001707315444946289 nb_pixel_total : 25220 time to create 1 rle with old method : 0.028602123260498047 length of segment : 237 time for calcul the mask position with numpy : 0.006635427474975586 nb_pixel_total : 122186 time to create 1 rle with old method : 0.14118099212646484 length of segment : 438 time for calcul the mask position with numpy : 0.0023262500762939453 nb_pixel_total : 52132 time to create 1 rle with old method : 0.05931377410888672 length of segment : 266 time for calcul the mask position with numpy : 0.0038373470306396484 nb_pixel_total : 65509 time to create 1 rle with old method : 0.07653474807739258 length of segment : 305 time for calcul the mask position with numpy : 0.0008530616760253906 nb_pixel_total : 13271 time to create 1 rle with old method : 0.015203237533569336 length of segment : 185 time for calcul the mask position with numpy : 0.005732059478759766 nb_pixel_total : 127274 time to create 1 rle with old method : 0.14571905136108398 length of segment : 664 time for calcul the mask position with numpy : 0.0016596317291259766 nb_pixel_total : 32161 time to create 1 rle with old method : 0.036278724670410156 length of segment : 359 time for calcul the mask position with numpy : 0.0007748603820800781 nb_pixel_total : 23111 time to create 1 rle with old method : 0.02655339241027832 length of segment : 185 time for calcul the mask position with numpy : 0.0011222362518310547 nb_pixel_total : 15080 time to create 1 rle with old method : 0.01744532585144043 length of segment : 183 time for calcul the mask position with numpy : 0.0010943412780761719 nb_pixel_total : 17213 time to create 1 rle with old method : 0.019888877868652344 length of segment : 161 time for calcul the mask position with numpy : 0.0007085800170898438 nb_pixel_total : 10743 time to create 1 rle with old method : 0.01342463493347168 length of segment : 210 time for calcul the mask position with numpy : 0.0015578269958496094 nb_pixel_total : 36010 time to create 1 rle with old method : 0.03972649574279785 length of segment : 251 time for calcul the mask position with numpy : 0.005392313003540039 nb_pixel_total : 139793 time to create 1 rle with old method : 0.15616774559020996 length of segment : 471 time for calcul the mask position with numpy : 0.0034389495849609375 nb_pixel_total : 95456 time to create 1 rle with old method : 0.10620570182800293 length of segment : 378 time for calcul the mask position with numpy : 0.00048828125 nb_pixel_total : 7971 time to create 1 rle with old method : 0.00901484489440918 length of segment : 135 time for calcul the mask position with numpy : 0.0018701553344726562 nb_pixel_total : 36653 time to create 1 rle with old method : 0.04268956184387207 length of segment : 449 time for calcul the mask position with numpy : 0.0030155181884765625 nb_pixel_total : 61880 time to create 1 rle with old method : 0.06904220581054688 length of segment : 386 time for calcul the mask position with numpy : 0.0031690597534179688 nb_pixel_total : 72949 time to create 1 rle with old method : 0.08257031440734863 length of segment : 314 time for calcul the mask position with numpy : 0.0029397010803222656 nb_pixel_total : 67110 time to create 1 rle with old method : 0.07850027084350586 length of segment : 344 time for calcul the mask position with numpy : 0.0041768550872802734 nb_pixel_total : 74828 time to create 1 rle with old method : 0.0840749740600586 length of segment : 266 time for calcul the mask position with numpy : 0.0014481544494628906 nb_pixel_total : 18630 time to create 1 rle with old method : 0.021732330322265625 length of segment : 286 time for calcul the mask position with numpy : 0.005395412445068359 nb_pixel_total : 111162 time to create 1 rle with old method : 0.12777376174926758 length of segment : 366 time for calcul the mask position with numpy : 0.0007216930389404297 nb_pixel_total : 9174 time to create 1 rle with old method : 0.010614871978759766 length of segment : 157 time for calcul the mask position with numpy : 0.0037758350372314453 nb_pixel_total : 75050 time to create 1 rle with old method : 0.08515238761901855 length of segment : 365 time for calcul the mask position with numpy : 0.0007402896881103516 nb_pixel_total : 9079 time to create 1 rle with old method : 0.010433673858642578 length of segment : 147 time for calcul the mask position with numpy : 0.0019638538360595703 nb_pixel_total : 95246 time to create 1 rle with old method : 0.1081240177154541 length of segment : 392 time for calcul the mask position with numpy : 0.0034444332122802734 nb_pixel_total : 42168 time to create 1 rle with old method : 0.04817509651184082 length of segment : 234 time for calcul the mask position with numpy : 0.0009288787841796875 nb_pixel_total : 14513 time to create 1 rle with old method : 0.017035484313964844 length of segment : 126 time for calcul the mask position with numpy : 0.0011463165283203125 nb_pixel_total : 16361 time to create 1 rle with old method : 0.018782377243041992 length of segment : 167 time for calcul the mask position with numpy : 0.0003631114959716797 nb_pixel_total : 2930 time to create 1 rle with old method : 0.0036547183990478516 length of segment : 160 time for calcul the mask position with numpy : 0.0015184879302978516 nb_pixel_total : 71582 time to create 1 rle with old method : 0.07904505729675293 length of segment : 382 time for calcul the mask position with numpy : 0.0007464885711669922 nb_pixel_total : 10541 time to create 1 rle with old method : 0.01259922981262207 length of segment : 92 time for calcul the mask position with numpy : 0.00017881393432617188 nb_pixel_total : 4274 time to create 1 rle with old method : 0.0052509307861328125 length of segment : 61 time for calcul the mask position with numpy : 0.002496957778930664 nb_pixel_total : 38378 time to create 1 rle with old method : 0.043985605239868164 length of segment : 243 time for calcul the mask position with numpy : 0.0002460479736328125 nb_pixel_total : 7622 time to create 1 rle with old method : 0.008730411529541016 length of segment : 163 time for calcul the mask position with numpy : 0.0026564598083496094 nb_pixel_total : 45749 time to create 1 rle with old method : 0.05100131034851074 length of segment : 441 time for calcul the mask position with numpy : 0.0006628036499023438 nb_pixel_total : 15882 time to create 1 rle with old method : 0.017884016036987305 length of segment : 135 time for calcul the mask position with numpy : 0.0017752647399902344 nb_pixel_total : 35297 time to create 1 rle with old method : 0.039789438247680664 length of segment : 184 time for calcul the mask position with numpy : 0.0008494853973388672 nb_pixel_total : 15476 time to create 1 rle with old method : 0.017347335815429688 length of segment : 140 time for calcul the mask position with numpy : 0.0012521743774414062 nb_pixel_total : 33277 time to create 1 rle with old method : 0.03709769248962402 length of segment : 225 time for calcul the mask position with numpy : 0.0013568401336669922 nb_pixel_total : 17596 time to create 1 rle with old method : 0.02414536476135254 length of segment : 244 time for calcul the mask position with numpy : 0.0005369186401367188 nb_pixel_total : 7412 time to create 1 rle with old method : 0.00830078125 length of segment : 91 time for calcul the mask position with numpy : 0.0018303394317626953 nb_pixel_total : 48513 time to create 1 rle with old method : 0.053986549377441406 length of segment : 425 time for calcul the mask position with numpy : 0.00041103363037109375 nb_pixel_total : 14455 time to create 1 rle with old method : 0.01598072052001953 length of segment : 135 time for calcul the mask position with numpy : 0.011995077133178711 nb_pixel_total : 598698 time to create 1 rle with new method : 0.14606809616088867 length of segment : 965 time for calcul the mask position with numpy : 0.0011060237884521484 nb_pixel_total : 40710 time to create 1 rle with old method : 0.04497361183166504 length of segment : 240 time for calcul the mask position with numpy : 0.0008170604705810547 nb_pixel_total : 27232 time to create 1 rle with old method : 0.031109094619750977 length of segment : 302 time for calcul the mask position with numpy : 0.0038492679595947266 nb_pixel_total : 227842 time to create 1 rle with new method : 0.007155656814575195 length of segment : 538 time for calcul the mask position with numpy : 0.0014567375183105469 nb_pixel_total : 65956 time to create 1 rle with old method : 0.0775611400604248 length of segment : 410 time for calcul the mask position with numpy : 0.005183219909667969 nb_pixel_total : 261052 time to create 1 rle with new method : 0.010589599609375 length of segment : 1065 time for calcul the mask position with numpy : 0.0005872249603271484 nb_pixel_total : 11766 time to create 1 rle with old method : 0.013091802597045898 length of segment : 412 time for calcul the mask position with numpy : 0.0004444122314453125 nb_pixel_total : 16872 time to create 1 rle with old method : 0.019429922103881836 length of segment : 235 time for calcul the mask position with numpy : 0.00225067138671875 nb_pixel_total : 52630 time to create 1 rle with old method : 0.05913090705871582 length of segment : 313 time for calcul the mask position with numpy : 0.0010304450988769531 nb_pixel_total : 14769 time to create 1 rle with old method : 0.016408443450927734 length of segment : 163 time for calcul the mask position with numpy : 0.0014829635620117188 nb_pixel_total : 31036 time to create 1 rle with old method : 0.03539156913757324 length of segment : 265 time for calcul the mask position with numpy : 0.0005259513854980469 nb_pixel_total : 8993 time to create 1 rle with old method : 0.010640859603881836 length of segment : 129 time for calcul the mask position with numpy : 0.0011603832244873047 nb_pixel_total : 23250 time to create 1 rle with old method : 0.026835918426513672 length of segment : 171 time for calcul the mask position with numpy : 0.0005176067352294922 nb_pixel_total : 15626 time to create 1 rle with old method : 0.017812490463256836 length of segment : 176 time for calcul the mask position with numpy : 0.002298116683959961 nb_pixel_total : 31139 time to create 1 rle with old method : 0.03425860404968262 length of segment : 329 time for calcul the mask position with numpy : 0.00028443336486816406 nb_pixel_total : 3543 time to create 1 rle with old method : 0.004036664962768555 length of segment : 106 time for calcul the mask position with numpy : 0.0013964176177978516 nb_pixel_total : 21258 time to create 1 rle with old method : 0.02409839630126953 length of segment : 184 time for calcul the mask position with numpy : 0.0015530586242675781 nb_pixel_total : 41953 time to create 1 rle with old method : 0.045114755630493164 length of segment : 280 time for calcul the mask position with numpy : 0.0005114078521728516 nb_pixel_total : 10076 time to create 1 rle with old method : 0.01134634017944336 length of segment : 160 time for calcul the mask position with numpy : 0.0018246173858642578 nb_pixel_total : 39374 time to create 1 rle with old method : 0.043752431869506836 length of segment : 220 time for calcul the mask position with numpy : 0.001878976821899414 nb_pixel_total : 39611 time to create 1 rle with old method : 0.04427361488342285 length of segment : 440 time for calcul the mask position with numpy : 0.0004248619079589844 nb_pixel_total : 8070 time to create 1 rle with old method : 0.009462118148803711 length of segment : 133 time for calcul the mask position with numpy : 0.0013399124145507812 nb_pixel_total : 32296 time to create 1 rle with old method : 0.03560614585876465 length of segment : 196 time for calcul the mask position with numpy : 0.0003094673156738281 nb_pixel_total : 10720 time to create 1 rle with old method : 0.011850833892822266 length of segment : 108 time for calcul the mask position with numpy : 0.0031647682189941406 nb_pixel_total : 75930 time to create 1 rle with old method : 0.08867859840393066 length of segment : 528 time for calcul the mask position with numpy : 0.0009052753448486328 nb_pixel_total : 27522 time to create 1 rle with old method : 0.039685726165771484 length of segment : 205 time for calcul the mask position with numpy : 0.0004105567932128906 nb_pixel_total : 9802 time to create 1 rle with old method : 0.013471841812133789 length of segment : 109 time for calcul the mask position with numpy : 0.003443479537963867 nb_pixel_total : 91912 time to create 1 rle with old method : 0.09978771209716797 length of segment : 541 time for calcul the mask position with numpy : 0.001531362533569336 nb_pixel_total : 34068 time to create 1 rle with old method : 0.03904104232788086 length of segment : 365 time for calcul the mask position with numpy : 0.0006694793701171875 nb_pixel_total : 16672 time to create 1 rle with old method : 0.021840810775756836 length of segment : 187 time for calcul the mask position with numpy : 0.00047469139099121094 nb_pixel_total : 10157 time to create 1 rle with old method : 0.012077569961547852 length of segment : 153 time for calcul the mask position with numpy : 0.0005860328674316406 nb_pixel_total : 16870 time to create 1 rle with old method : 0.0195314884185791 length of segment : 154 time for calcul the mask position with numpy : 0.0009946823120117188 nb_pixel_total : 36643 time to create 1 rle with old method : 0.041489362716674805 length of segment : 252 time for calcul the mask position with numpy : 0.00043964385986328125 nb_pixel_total : 12850 time to create 1 rle with old method : 0.015059232711791992 length of segment : 90 time for calcul the mask position with numpy : 0.0005614757537841797 nb_pixel_total : 16338 time to create 1 rle with old method : 0.01914834976196289 length of segment : 152 time for calcul the mask position with numpy : 0.0004863739013671875 nb_pixel_total : 13663 time to create 1 rle with old method : 0.015899181365966797 length of segment : 173 time for calcul the mask position with numpy : 0.001310586929321289 nb_pixel_total : 38625 time to create 1 rle with old method : 0.04300117492675781 length of segment : 296 time for calcul the mask position with numpy : 0.0009868144989013672 nb_pixel_total : 25893 time to create 1 rle with old method : 0.02978372573852539 length of segment : 183 time for calcul the mask position with numpy : 0.00028443336486816406 nb_pixel_total : 6415 time to create 1 rle with old method : 0.0078008174896240234 length of segment : 108 time for calcul the mask position with numpy : 0.00030112266540527344 nb_pixel_total : 8379 time to create 1 rle with old method : 0.009722709655761719 length of segment : 87 time for calcul the mask position with numpy : 0.001560211181640625 nb_pixel_total : 49226 time to create 1 rle with old method : 0.054090023040771484 length of segment : 309 time for calcul the mask position with numpy : 0.0026252269744873047 nb_pixel_total : 30894 time to create 1 rle with old method : 0.036031484603881836 length of segment : 158 time for calcul the mask position with numpy : 0.0018434524536132812 nb_pixel_total : 20408 time to create 1 rle with old method : 0.024898767471313477 length of segment : 189 time for calcul the mask position with numpy : 0.0015411376953125 nb_pixel_total : 20587 time to create 1 rle with old method : 0.024314403533935547 length of segment : 187 time for calcul the mask position with numpy : 0.0005645751953125 nb_pixel_total : 6714 time to create 1 rle with old method : 0.008218050003051758 length of segment : 74 time for calcul the mask position with numpy : 0.001415252685546875 nb_pixel_total : 24328 time to create 1 rle with old method : 0.027690410614013672 length of segment : 190 time for calcul the mask position with numpy : 0.0009751319885253906 nb_pixel_total : 14212 time to create 1 rle with old method : 0.01681232452392578 length of segment : 99 time for calcul the mask position with numpy : 0.019447803497314453 nb_pixel_total : 380473 time to create 1 rle with new method : 0.024434804916381836 length of segment : 672 time for calcul the mask position with numpy : 0.0020885467529296875 nb_pixel_total : 25268 time to create 1 rle with old method : 0.028811931610107422 length of segment : 283 time for calcul the mask position with numpy : 0.00069427490234375 nb_pixel_total : 9979 time to create 1 rle with old method : 0.011671304702758789 length of segment : 134 time for calcul the mask position with numpy : 0.0018095970153808594 nb_pixel_total : 26161 time to create 1 rle with old method : 0.030272245407104492 length of segment : 208 time for calcul the mask position with numpy : 0.001695871353149414 nb_pixel_total : 25526 time to create 1 rle with old method : 0.029427051544189453 length of segment : 184 time for calcul the mask position with numpy : 0.00482487678527832 nb_pixel_total : 71073 time to create 1 rle with old method : 0.07973384857177734 length of segment : 635 time for calcul the mask position with numpy : 0.0008134841918945312 nb_pixel_total : 12597 time to create 1 rle with old method : 0.01470041275024414 length of segment : 121 time for calcul the mask position with numpy : 0.0014674663543701172 nb_pixel_total : 14678 time to create 1 rle with old method : 0.01718616485595703 length of segment : 262 time for calcul the mask position with numpy : 0.003020048141479492 nb_pixel_total : 31232 time to create 1 rle with old method : 0.0351099967956543 length of segment : 239 time for calcul the mask position with numpy : 0.0027360916137695312 nb_pixel_total : 34200 time to create 1 rle with old method : 0.038712263107299805 length of segment : 325 time for calcul the mask position with numpy : 0.0007243156433105469 nb_pixel_total : 10515 time to create 1 rle with old method : 0.012237548828125 length of segment : 173 time for calcul the mask position with numpy : 0.0028443336486816406 nb_pixel_total : 34970 time to create 1 rle with old method : 0.039624929428100586 length of segment : 340 time for calcul the mask position with numpy : 0.001432657241821289 nb_pixel_total : 23760 time to create 1 rle with old method : 0.0271608829498291 length of segment : 172 time for calcul the mask position with numpy : 0.0006854534149169922 nb_pixel_total : 8523 time to create 1 rle with old method : 0.010104656219482422 length of segment : 143 time for calcul the mask position with numpy : 0.0007061958312988281 nb_pixel_total : 10079 time to create 1 rle with old method : 0.012290000915527344 length of segment : 138 time for calcul the mask position with numpy : 0.0002579689025878906 nb_pixel_total : 5181 time to create 1 rle with old method : 0.0062100887298583984 length of segment : 102 time for calcul the mask position with numpy : 0.0011827945709228516 nb_pixel_total : 10929 time to create 1 rle with old method : 0.013411521911621094 length of segment : 140 time for calcul the mask position with numpy : 0.0029015541076660156 nb_pixel_total : 22023 time to create 1 rle with old method : 0.026626110076904297 length of segment : 320 time for calcul the mask position with numpy : 0.002257823944091797 nb_pixel_total : 36409 time to create 1 rle with old method : 0.04092597961425781 length of segment : 236 time for calcul the mask position with numpy : 0.005198001861572266 nb_pixel_total : 55710 time to create 1 rle with old method : 0.062364816665649414 length of segment : 413 time for calcul the mask position with numpy : 0.006947994232177734 nb_pixel_total : 85553 time to create 1 rle with old method : 0.09608244895935059 length of segment : 467 time for calcul the mask position with numpy : 0.0015721321105957031 nb_pixel_total : 16205 time to create 1 rle with old method : 0.019587039947509766 length of segment : 190 time for calcul the mask position with numpy : 0.0046384334564208984 nb_pixel_total : 63905 time to create 1 rle with old method : 0.07378959655761719 length of segment : 291 time for calcul the mask position with numpy : 0.0011248588562011719 nb_pixel_total : 22315 time to create 1 rle with old method : 0.02516031265258789 length of segment : 198 time for calcul the mask position with numpy : 0.0013430118560791016 nb_pixel_total : 19693 time to create 1 rle with old method : 0.022545337677001953 length of segment : 172 time for calcul the mask position with numpy : 0.0001647472381591797 nb_pixel_total : 7157 time to create 1 rle with old method : 0.007897615432739258 length of segment : 108 time for calcul the mask position with numpy : 0.00043129920959472656 nb_pixel_total : 19005 time to create 1 rle with old method : 0.021451711654663086 length of segment : 154 time for calcul the mask position with numpy : 0.00096893310546875 nb_pixel_total : 11766 time to create 1 rle with old method : 0.013606786727905273 length of segment : 110 time for calcul the mask position with numpy : 0.002213001251220703 nb_pixel_total : 26811 time to create 1 rle with old method : 0.03027510643005371 length of segment : 249 time for calcul the mask position with numpy : 0.006727457046508789 nb_pixel_total : 88385 time to create 1 rle with old method : 0.09671568870544434 length of segment : 429 time for calcul the mask position with numpy : 0.017305612564086914 nb_pixel_total : 326856 time to create 1 rle with new method : 0.02095198631286621 length of segment : 901 time for calcul the mask position with numpy : 0.00048542022705078125 nb_pixel_total : 6901 time to create 1 rle with old method : 0.007763862609863281 length of segment : 105 time for calcul the mask position with numpy : 0.0010533332824707031 nb_pixel_total : 14689 time to create 1 rle with old method : 0.01675271987915039 length of segment : 151 time for calcul the mask position with numpy : 0.002654552459716797 nb_pixel_total : 37963 time to create 1 rle with old method : 0.042168617248535156 length of segment : 251 time for calcul the mask position with numpy : 0.0010075569152832031 nb_pixel_total : 21420 time to create 1 rle with old method : 0.023731231689453125 length of segment : 198 time for calcul the mask position with numpy : 0.001984119415283203 nb_pixel_total : 26475 time to create 1 rle with old method : 0.029849767684936523 length of segment : 183 time spent for convertir_results : 97.07996869087219 Inside saveOutput : final : False verbose : 0 eke 12-6-18 : saveMask need to be cleaned for new output ! Number saved : None batch 1 Loaded 791 chid ids of type : 3594 Number RLEs to save : 194396 save missing photos in datou_result : time spend for datou_step_exec : 464.44329833984375 time spend to save output : 25.517191410064697 total time spend for step 1 : 489.96048974990845 step2:crop_condition Wed Apr 9 12:38:43 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 : 24 ! batch 1 Loaded 791 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 ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! 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 : 575 About to insert : list_path_to_insert length 575 new photo from crops ! About to upload 575 photos upload in portfolio : 3736932 init cache_photo without model_param we have 575 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1744195234_977867 we have uploaded 575 photos in the portfolio 3736932 time of upload the photos Elapsed time : 165.46986985206604 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 ! we have both polygon and rles Next one ! 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 : 108 About to insert : list_path_to_insert length 108 new photo from crops ! About to upload 108 photos upload in portfolio : 3736932 init cache_photo without model_param we have 108 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1744195425_977867 we have uploaded 108 photos in the portfolio 3736932 time of upload the photos Elapsed time : 33.16782188415527 we have finished the crop for the class : carton begin to crop the class : metal param for this class : {'min_score': 0.7} filtre for class : metal hashtag_id of this class : 492628673 we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! map_result returned by crop_photo_return_map_crop : length : 7 About to insert : list_path_to_insert length 7 new photo from crops ! About to upload 7 photos upload in portfolio : 3736932 init cache_photo without model_param we have 7 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1744195465_977867 we have uploaded 7 photos in the portfolio 3736932 time of upload the photos Elapsed time : 4.377202272415161 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 ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! 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 : 75 About to insert : list_path_to_insert length 75 new photo from crops ! About to upload 75 photos upload in portfolio : 3736932 init cache_photo without model_param we have 75 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1744195500_977867 we have uploaded 75 photos in the portfolio 3736932 time of upload the photos Elapsed time : 21.327582359313965 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 ! we have both polygon and rles Next one ! map_result returned by crop_photo_return_map_crop : length : 11 About to insert : list_path_to_insert length 11 new photo from crops ! About to upload 11 photos upload in portfolio : 3736932 init cache_photo without model_param we have 11 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1744195527_977867 we have uploaded 11 photos in the portfolio 3736932 time of upload the photos Elapsed time : 2.8251616954803467 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 ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! 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 : 9 About to insert : list_path_to_insert length 9 new photo from crops ! About to upload 9 photos upload in portfolio : 3736932 init cache_photo without model_param we have 9 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1744195534_977867 we have uploaded 9 photos in the portfolio 3736932 time of upload the photos Elapsed time : 2.563551187515259 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 ! map_result returned by crop_photo_return_map_crop : length : 6 About to insert : list_path_to_insert length 6 new photo from crops ! About to upload 6 photos upload in portfolio : 3736932 init cache_photo without model_param we have 6 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1744195541_977867 we have uploaded 6 photos in the portfolio 3736932 time of upload the photos Elapsed time : 2.159780740737915 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 Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : crop_condition we use saveGeneral [1350741936, 1350741933, 1350741771, 1350741769, 1350741659, 1350741627, 1350741601, 1350741579, 1350741267, 1350741217, 1350741215, 1350741212, 1350738338, 1350738296, 1350737578, 1350737511, 1350737419, 1350737410, 1350737230, 1350737086, 1350736919, 1350736896, 1350736747, 1350736614] Looping around the photos to save general results len do output : 791 /1350757683Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757684Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757685Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757686Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757687Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757688Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757689Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757690Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757691Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757692Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757693Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757694Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757695Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757696Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757697Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757698Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757699Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757700Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757701Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757702Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757703Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757704Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757705Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757706Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757707Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757708Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757709Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757711Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757712Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757713Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757714Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757715Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757716Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757718Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757719Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757720Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757721Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757722Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757723Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757724Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757725Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757726Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757727Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757728Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757729Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757730Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757731Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757732Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757733Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757734Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757735Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757736Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757737Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350757738Didn't retrieve data .Didn't retrieve 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data .Didn't retrieve data . /1350758571Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350758572Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350758573Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350758574Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350758575Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350758576Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350758577Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350758579Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350758580Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350758581Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350758582Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350758583Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350758584Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350758585Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350758586Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350758587Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350758588Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350758589Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350758593Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350758594Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350758595Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350758596Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350758597Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350758598Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350758599Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350758600Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350758601Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350758607Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350758608Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350758609Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350758610Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350758611Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1350758612Didn'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, '2734295') ('3318', '22161073', '1350741936', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741933', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741771', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741769', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741659', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741627', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741601', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741579', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741267', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741217', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741215', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741212', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350738338', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350738296', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350737578', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350737511', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350737419', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350737410', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350737230', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350737086', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350736919', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350736896', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350736747', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350736614', None, None, None, None, None, '2734295') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 2397 time used for this insertion : 0.09923481941223145 save_final save missing photos in datou_result : time spend for datou_step_exec : 420.26020336151123 time spend to save output : 0.4489562511444092 total time spend for step 2 : 420.70915961265564 step3:rle_unique_nms_with_priority Wed Apr 9 12:45:44 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 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 791 chid ids of type : 3594 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++nb_obj : 42 nb_hashtags : 4 time to prepare the origin masks : 4.174290418624878 time for calcul the mask position with numpy : 0.2722294330596924 nb_pixel_total : 5591913 time to create 1 rle with new method : 0.5382146835327148 time for calcul the mask position with numpy : 0.02903008460998535 nb_pixel_total : 16031 time to create 1 rle with old method : 0.017963171005249023 time for calcul the mask position with numpy : 0.028896331787109375 nb_pixel_total : 17089 time to create 1 rle with old method : 0.02488088607788086 time for calcul the mask position with numpy : 0.0346827507019043 nb_pixel_total : 151880 time to create 1 rle with new method : 0.39563560485839844 time for calcul the mask position with numpy : 0.029281139373779297 nb_pixel_total : 4376 time to create 1 rle with old method : 0.004961490631103516 time for calcul the mask position with numpy : 0.029164552688598633 nb_pixel_total : 19255 time to create 1 rle with old method : 0.021598100662231445 time for calcul the mask position with numpy : 0.029313325881958008 nb_pixel_total : 25031 time to create 1 rle with old method : 0.028104543685913086 time for calcul the mask position with numpy : 0.029025793075561523 nb_pixel_total : 54258 time to create 1 rle with old method : 0.060578107833862305 time for calcul the mask position with numpy : 0.02911663055419922 nb_pixel_total : 15828 time to create 1 rle with old method : 0.01793980598449707 time for calcul the mask position with numpy : 0.029077529907226562 nb_pixel_total : 8052 time to create 1 rle with old method : 0.009260416030883789 time for calcul the mask position with numpy : 0.029110431671142578 nb_pixel_total : 12563 time to create 1 rle with old method : 0.016588211059570312 time for calcul the mask position with numpy : 0.028916120529174805 nb_pixel_total : 18012 time to create 1 rle with old method : 0.020510196685791016 time for calcul the mask position with numpy : 0.02924203872680664 nb_pixel_total : 13883 time to create 1 rle with old method : 0.01589679718017578 time for calcul the mask position with numpy : 0.029660701751708984 nb_pixel_total : 29957 time to create 1 rle with old method : 0.0341794490814209 time for calcul the mask position with numpy : 0.02906489372253418 nb_pixel_total : 26027 time to create 1 rle with old method : 0.02930283546447754 time for calcul the mask position with numpy : 0.0291595458984375 nb_pixel_total : 24488 time to create 1 rle with old method : 0.027765750885009766 time for calcul the mask position with numpy : 0.028858423233032227 nb_pixel_total : 23851 time to create 1 rle with old method : 0.027463197708129883 time for calcul the mask position with numpy : 0.032370567321777344 nb_pixel_total : 38464 time to create 1 rle with old method : 0.04391932487487793 time for calcul the mask position with numpy : 0.028964519500732422 nb_pixel_total : 7695 time to create 1 rle with old method : 0.008708000183105469 time for calcul the mask position with numpy : 0.028899192810058594 nb_pixel_total : 21333 time to create 1 rle with old method : 0.024149179458618164 time for calcul the mask position with numpy : 0.029293060302734375 nb_pixel_total : 77903 time to create 1 rle with old method : 0.10736489295959473 time for calcul the mask position with numpy : 0.03217577934265137 nb_pixel_total : 33217 time to create 1 rle with old method : 0.04063701629638672 time for calcul the mask position with numpy : 0.030443906784057617 nb_pixel_total : 14567 time to create 1 rle with old method : 0.01774883270263672 time for calcul the mask position with numpy : 0.029182910919189453 nb_pixel_total : 15799 time to create 1 rle with old method : 0.018060922622680664 time for calcul the mask position with numpy : 0.029697895050048828 nb_pixel_total : 39188 time to create 1 rle with old method : 0.044460296630859375 time for calcul the mask position with numpy : 0.029253721237182617 nb_pixel_total : 17800 time to create 1 rle with old method : 0.020221471786499023 time for calcul the mask position with numpy : 0.029390811920166016 nb_pixel_total : 101730 time to create 1 rle with old method : 0.12340021133422852 time for calcul the mask position with numpy : 0.031059980392456055 nb_pixel_total : 44485 time to create 1 rle with old method : 0.05056595802307129 time for calcul the mask position with numpy : 0.03213620185852051 nb_pixel_total : 253164 time to create 1 rle with new method : 0.570650577545166 time for calcul the mask position with numpy : 0.03190493583679199 nb_pixel_total : 10039 time to create 1 rle with old method : 0.011661767959594727 time for calcul the mask position with numpy : 0.030075550079345703 nb_pixel_total : 25890 time to create 1 rle with old method : 0.029695510864257812 time for calcul the mask position with numpy : 0.02963566780090332 nb_pixel_total : 35263 time to create 1 rle with old method : 0.039983510971069336 time for calcul the mask position with numpy : 0.029785871505737305 nb_pixel_total : 42605 time to create 1 rle with old method : 0.047460079193115234 time for calcul the mask position with numpy : 0.02977299690246582 nb_pixel_total : 63544 time to create 1 rle with old method : 0.0709676742553711 time for calcul the mask position with numpy : 0.029220104217529297 nb_pixel_total : 9245 time to create 1 rle with old method : 0.010544538497924805 time for calcul the mask position with numpy : 0.02923750877380371 nb_pixel_total : 16032 time to create 1 rle with old method : 0.018062591552734375 time for calcul the mask position with numpy : 0.029203176498413086 nb_pixel_total : 2999 time to create 1 rle with old method : 0.004978179931640625 time for calcul the mask position with numpy : 0.03336191177368164 nb_pixel_total : 40226 time to create 1 rle with old method : 0.05922269821166992 time for calcul the mask position with numpy : 0.02957296371459961 nb_pixel_total : 43969 time to create 1 rle with old method : 0.049785614013671875 time for calcul the mask position with numpy : 0.029172897338867188 nb_pixel_total : 6882 time to create 1 rle with old method : 0.007937192916870117 time for calcul the mask position with numpy : 0.02929210662841797 nb_pixel_total : 12850 time to create 1 rle with old method : 0.014655828475952148 time for calcul the mask position with numpy : 0.029225826263427734 nb_pixel_total : 13302 time to create 1 rle with old method : 0.015154600143432617 time for calcul the mask position with numpy : 0.02902698516845703 nb_pixel_total : 9555 time to create 1 rle with old method : 0.010967493057250977 create new chi : 4.3625805377960205 time to delete rle : 0.016015052795410156 batch 1 Loaded 85 chid ids of type : 3594 ++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 21817 TO DO : save crop sub photo not yet done ! save time : 2.998746395111084 nb_obj : 33 nb_hashtags : 4 time to prepare the origin masks : 4.254151105880737 time for calcul the mask position with numpy : 1.1727540493011475 nb_pixel_total : 5836413 time to create 1 rle with new method : 0.9965715408325195 time for calcul the mask position with numpy : 0.03258943557739258 nb_pixel_total : 62530 time to create 1 rle with old method : 0.071563720703125 time for calcul the mask position with numpy : 0.03062295913696289 nb_pixel_total : 9017 time to create 1 rle with old method : 0.010521650314331055 time for calcul the mask position with numpy : 0.02994537353515625 nb_pixel_total : 21934 time to create 1 rle with old method : 0.02521371841430664 time for calcul the mask position with numpy : 0.029084444046020508 nb_pixel_total : 10309 time to create 1 rle with old method : 0.01199483871459961 time for calcul the mask position with numpy : 0.0298309326171875 nb_pixel_total : 7896 time to create 1 rle with old method : 0.009988069534301758 time for calcul the mask position with numpy : 0.030510425567626953 nb_pixel_total : 14868 time to create 1 rle with old method : 0.018234968185424805 time for calcul the mask position with numpy : 0.03300905227661133 nb_pixel_total : 38604 time to create 1 rle with old method : 0.04506278038024902 time for calcul the mask position with numpy : 0.029716014862060547 nb_pixel_total : 13632 time to create 1 rle with old method : 0.015345335006713867 time for calcul the mask position with numpy : 0.030335187911987305 nb_pixel_total : 15214 time to create 1 rle with old method : 0.018777132034301758 time for calcul the mask position with numpy : 0.0322723388671875 nb_pixel_total : 186507 time to create 1 rle with new method : 0.7076404094696045 time for calcul the mask position with numpy : 0.03089284896850586 nb_pixel_total : 127318 time to create 1 rle with old method : 0.1476154327392578 time for calcul the mask position with numpy : 0.02962779998779297 nb_pixel_total : 15499 time to create 1 rle with old method : 0.017629384994506836 time for calcul the mask position with numpy : 0.030379533767700195 nb_pixel_total : 20588 time to create 1 rle with old method : 0.023975133895874023 time for calcul the mask position with numpy : 0.030716896057128906 nb_pixel_total : 17603 time to create 1 rle with old method : 0.019841432571411133 time for calcul the mask position with numpy : 0.030585289001464844 nb_pixel_total : 22870 time to create 1 rle with old method : 0.0275266170501709 time for calcul the mask position with numpy : 0.03015613555908203 nb_pixel_total : 9426 time to create 1 rle with old method : 0.012058496475219727 time for calcul the mask position with numpy : 0.031465768814086914 nb_pixel_total : 102881 time to create 1 rle with old method : 0.11978578567504883 time for calcul the mask position with numpy : 0.030373573303222656 nb_pixel_total : 22240 time to create 1 rle with old method : 0.02781081199645996 time for calcul the mask position with numpy : 0.030223369598388672 nb_pixel_total : 13976 time to create 1 rle with old method : 0.0173642635345459 time for calcul the mask position with numpy : 0.030799388885498047 nb_pixel_total : 41105 time to create 1 rle with old method : 0.05280017852783203 time for calcul the mask position with numpy : 0.03129291534423828 nb_pixel_total : 70439 time to create 1 rle with old method : 0.10552692413330078 time for calcul the mask position with numpy : 0.030225753784179688 nb_pixel_total : 26052 time to create 1 rle with old method : 0.03029918670654297 time for calcul the mask position with numpy : 0.029532432556152344 nb_pixel_total : 26814 time to create 1 rle with old method : 0.0320429801940918 time for calcul the mask position with numpy : 0.03033304214477539 nb_pixel_total : 51623 time to create 1 rle with old method : 0.058899641036987305 time for calcul the mask position with numpy : 0.03017711639404297 nb_pixel_total : 10702 time to create 1 rle with old method : 0.01269388198852539 time for calcul the mask position with numpy : 0.03037881851196289 nb_pixel_total : 12397 time to create 1 rle with old method : 0.014479875564575195 time for calcul the mask position with numpy : 0.03307151794433594 nb_pixel_total : 42735 time to create 1 rle with old method : 0.048935651779174805 time for calcul the mask position with numpy : 0.030088424682617188 nb_pixel_total : 43408 time to create 1 rle with old method : 0.05545663833618164 time for calcul the mask position with numpy : 0.029431819915771484 nb_pixel_total : 33358 time to create 1 rle with old method : 0.03794288635253906 time for calcul the mask position with numpy : 0.029282093048095703 nb_pixel_total : 40796 time to create 1 rle with old method : 0.0506281852722168 time for calcul the mask position with numpy : 0.031456708908081055 nb_pixel_total : 48758 time to create 1 rle with old method : 0.057570695877075195 time for calcul the mask position with numpy : 0.030240535736083984 nb_pixel_total : 5705 time to create 1 rle with old method : 0.006662845611572266 time for calcul the mask position with numpy : 0.02922344207763672 nb_pixel_total : 27023 time to create 1 rle with old method : 0.030382156372070312 create new chi : 5.1860880851745605 time to delete rle : 0.0024755001068115234 batch 1 Loaded 67 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++Number RLEs to save : 16590 TO DO : save crop sub photo not yet done ! save time : 1.0442206859588623 nb_obj : 41 nb_hashtags : 3 time to prepare the origin masks : 4.051008224487305 time for calcul the mask position with numpy : 0.4256770610809326 nb_pixel_total : 5799654 time to create 1 rle with new method : 0.645859956741333 time for calcul the mask position with numpy : 0.031569480895996094 nb_pixel_total : 7408 time to create 1 rle with old method : 0.01179647445678711 time for calcul the mask position with numpy : 0.031584739685058594 nb_pixel_total : 53088 time to create 1 rle with old method : 0.061110734939575195 time for calcul the mask position with numpy : 0.0300748348236084 nb_pixel_total : 32077 time to create 1 rle with old method : 0.04429888725280762 time for calcul the mask position with numpy : 0.030936717987060547 nb_pixel_total : 69589 time to create 1 rle with old method : 0.08292484283447266 time for calcul the mask position with numpy : 0.031153440475463867 nb_pixel_total : 24181 time to create 1 rle with old method : 0.028449058532714844 time for calcul the mask position with numpy : 0.030075550079345703 nb_pixel_total : 15394 time to create 1 rle with old method : 0.019005537033081055 time for calcul the mask position with numpy : 0.03007984161376953 nb_pixel_total : 26872 time to create 1 rle with old method : 0.03111577033996582 time for calcul the mask position with numpy : 0.030614137649536133 nb_pixel_total : 14002 time to create 1 rle with old method : 0.01743483543395996 time for calcul the mask position with numpy : 0.02975916862487793 nb_pixel_total : 12920 time to create 1 rle with old method : 0.015031814575195312 time for calcul the mask position with numpy : 0.030939340591430664 nb_pixel_total : 31793 time to create 1 rle with old method : 0.038597822189331055 time for calcul the mask position with numpy : 0.030927658081054688 nb_pixel_total : 10879 time to create 1 rle with old method : 0.01444244384765625 time for calcul the mask position with numpy : 0.030913591384887695 nb_pixel_total : 77644 time to create 1 rle with old method : 0.08945775032043457 time for calcul the mask position with numpy : 0.029357433319091797 nb_pixel_total : 13875 time to create 1 rle with old method : 0.015599966049194336 time for calcul the mask position with numpy : 0.029445409774780273 nb_pixel_total : 27311 time to create 1 rle with old method : 0.032653093338012695 time for calcul the mask position with numpy : 0.029405593872070312 nb_pixel_total : 17448 time to create 1 rle with old method : 0.020308732986450195 time for calcul the mask position with numpy : 0.029642343521118164 nb_pixel_total : 66586 time to create 1 rle with old method : 0.07872438430786133 time for calcul the mask position with numpy : 0.029646873474121094 nb_pixel_total : 44526 time to create 1 rle with old method : 0.04977059364318848 time for calcul the mask position with numpy : 0.02943134307861328 nb_pixel_total : 22295 time to create 1 rle with old method : 0.02518439292907715 time for calcul the mask position with numpy : 0.029511690139770508 nb_pixel_total : 19444 time to create 1 rle with old method : 0.02208113670349121 time for calcul the mask position with numpy : 0.029056787490844727 nb_pixel_total : 26551 time to create 1 rle with old method : 0.030228853225708008 time for calcul the mask position with numpy : 0.0292813777923584 nb_pixel_total : 19588 time to create 1 rle with old method : 0.022481203079223633 time for calcul the mask position with numpy : 0.029422998428344727 nb_pixel_total : 41182 time to create 1 rle with old method : 0.049526214599609375 time for calcul the mask position with numpy : 0.031897544860839844 nb_pixel_total : 71931 time to create 1 rle with old method : 0.08134293556213379 time for calcul the mask position with numpy : 0.029260873794555664 nb_pixel_total : 115226 time to create 1 rle with old method : 0.1296083927154541 time for calcul the mask position with numpy : 0.02923870086669922 nb_pixel_total : 21242 time to create 1 rle with old method : 0.023973703384399414 time for calcul the mask position with numpy : 0.029536962509155273 nb_pixel_total : 133886 time to create 1 rle with old method : 0.15172719955444336 time for calcul the mask position with numpy : 0.031174898147583008 nb_pixel_total : 36286 time to create 1 rle with old method : 0.0407254695892334 time for calcul the mask position with numpy : 0.029190778732299805 nb_pixel_total : 6854 time to create 1 rle with old method : 0.007884740829467773 time for calcul the mask position with numpy : 0.0289609432220459 nb_pixel_total : 15047 time to create 1 rle with old method : 0.01704549789428711 time for calcul the mask position with numpy : 0.02922201156616211 nb_pixel_total : 9135 time to create 1 rle with old method : 0.010436058044433594 time for calcul the mask position with numpy : 0.029215097427368164 nb_pixel_total : 2658 time to create 1 rle with old method : 0.0030722618103027344 time for calcul the mask position with numpy : 0.029217243194580078 nb_pixel_total : 10128 time to create 1 rle with old method : 0.011778116226196289 time for calcul the mask position with numpy : 0.02920389175415039 nb_pixel_total : 12286 time to create 1 rle with old method : 0.014474868774414062 time for calcul the mask position with numpy : 0.029518842697143555 nb_pixel_total : 5160 time to create 1 rle with old method : 0.005834341049194336 time for calcul the mask position with numpy : 0.029891014099121094 nb_pixel_total : 4634 time to create 1 rle with old method : 0.00525665283203125 time for calcul the mask position with numpy : 0.029075145721435547 nb_pixel_total : 32692 time to create 1 rle with old method : 0.03669428825378418 time for calcul the mask position with numpy : 0.029308080673217773 nb_pixel_total : 21738 time to create 1 rle with old method : 0.024552583694458008 time for calcul the mask position with numpy : 0.02969980239868164 nb_pixel_total : 42722 time to create 1 rle with old method : 0.04854130744934082 time for calcul the mask position with numpy : 0.02946615219116211 nb_pixel_total : 9795 time to create 1 rle with old method : 0.011193275451660156 time for calcul the mask position with numpy : 0.02965688705444336 nb_pixel_total : 8667 time to create 1 rle with old method : 0.009896993637084961 time for calcul the mask position with numpy : 0.02956366539001465 nb_pixel_total : 15846 time to create 1 rle with old method : 0.0181734561920166 create new chi : 3.791604995727539 time to delete rle : 0.005070924758911133 batch 1 Loaded 83 chid ids of type : 3594 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 20679 TO DO : save crop sub photo not yet done ! save time : 1.2266526222229004 nb_obj : 42 nb_hashtags : 4 time to prepare the origin masks : 3.7623581886291504 time for calcul the mask position with numpy : 0.49727797508239746 nb_pixel_total : 6107307 time to create 1 rle with new method : 0.781078577041626 time for calcul the mask position with numpy : 0.028929710388183594 nb_pixel_total : 8543 time to create 1 rle with old method : 0.009718656539916992 time for calcul the mask position with numpy : 0.028887033462524414 nb_pixel_total : 6433 time to create 1 rle with old method : 0.0073091983795166016 time for calcul the mask position with numpy : 0.029326200485229492 nb_pixel_total : 33900 time to create 1 rle with old method : 0.038483619689941406 time for calcul the mask position with numpy : 0.029521465301513672 nb_pixel_total : 22627 time to create 1 rle with old method : 0.025448322296142578 time for calcul the mask position with numpy : 0.028946638107299805 nb_pixel_total : 7486 time to create 1 rle with old method : 0.008527278900146484 time for calcul the mask position with numpy : 0.029297590255737305 nb_pixel_total : 28320 time to create 1 rle with old method : 0.03215146064758301 time for calcul the mask position with numpy : 0.029974937438964844 nb_pixel_total : 19910 time to create 1 rle with old method : 0.024924516677856445 time for calcul the mask position with numpy : 0.03305530548095703 nb_pixel_total : 12625 time to create 1 rle with old method : 0.020721912384033203 time for calcul the mask position with numpy : 0.03187227249145508 nb_pixel_total : 12200 time to create 1 rle with old method : 0.013808965682983398 time for calcul the mask position with numpy : 0.02965569496154785 nb_pixel_total : 89845 time to create 1 rle with old method : 0.10097002983093262 time for calcul the mask position with numpy : 0.02917933464050293 nb_pixel_total : 25009 time to create 1 rle with old method : 0.028603076934814453 time for calcul the mask position with numpy : 0.030699491500854492 nb_pixel_total : 48820 time to create 1 rle with old method : 0.05515336990356445 time for calcul the mask position with numpy : 0.02950572967529297 nb_pixel_total : 8745 time to create 1 rle with old method : 0.009882211685180664 time for calcul the mask position with numpy : 0.02896857261657715 nb_pixel_total : 37719 time to create 1 rle with old method : 0.04237246513366699 time for calcul the mask position with numpy : 0.02885150909423828 nb_pixel_total : 17605 time to create 1 rle with old method : 0.019848346710205078 time for calcul the mask position with numpy : 0.02891254425048828 nb_pixel_total : 8880 time to create 1 rle with old method : 0.009935855865478516 time for calcul the mask position with numpy : 0.03476762771606445 nb_pixel_total : 11541 time to create 1 rle with old method : 0.013221263885498047 time for calcul the mask position with numpy : 0.030179500579833984 nb_pixel_total : 16146 time to create 1 rle with old method : 0.019286632537841797 time for calcul the mask position with numpy : 0.02897953987121582 nb_pixel_total : 6452 time to create 1 rle with old method : 0.008668899536132812 time for calcul the mask position with numpy : 0.02979898452758789 nb_pixel_total : 37342 time to create 1 rle with old method : 0.04878735542297363 time for calcul the mask position with numpy : 0.02980828285217285 nb_pixel_total : 59656 time to create 1 rle with old method : 0.06916022300720215 time for calcul the mask position with numpy : 0.029615402221679688 nb_pixel_total : 22032 time to create 1 rle with old method : 0.025688648223876953 time for calcul the mask position with numpy : 0.029785633087158203 nb_pixel_total : 5360 time to create 1 rle with old method : 0.006246089935302734 time for calcul the mask position with numpy : 0.02932286262512207 nb_pixel_total : 29300 time to create 1 rle with old method : 0.033786773681640625 time for calcul the mask position with numpy : 0.029059648513793945 nb_pixel_total : 8609 time to create 1 rle with old method : 0.009706497192382812 time for calcul the mask position with numpy : 0.029262542724609375 nb_pixel_total : 22139 time to create 1 rle with old method : 0.025124311447143555 time for calcul the mask position with numpy : 0.030187129974365234 nb_pixel_total : 23106 time to create 1 rle with old method : 0.025963306427001953 time for calcul the mask position with numpy : 0.02925276756286621 nb_pixel_total : 25143 time to create 1 rle with old method : 0.028270959854125977 time for calcul the mask position with numpy : 0.029421091079711914 nb_pixel_total : 9631 time to create 1 rle with old method : 0.011119842529296875 time for calcul the mask position with numpy : 0.02962207794189453 nb_pixel_total : 26603 time to create 1 rle with old method : 0.03029799461364746 time for calcul the mask position with numpy : 0.031131505966186523 nb_pixel_total : 57357 time to create 1 rle with old method : 0.06488776206970215 time for calcul the mask position with numpy : 0.030277490615844727 nb_pixel_total : 30120 time to create 1 rle with old method : 0.036031484603881836 time for calcul the mask position with numpy : 0.029022932052612305 nb_pixel_total : 25303 time to create 1 rle with old method : 0.028536319732666016 time for calcul the mask position with numpy : 0.02969646453857422 nb_pixel_total : 29069 time to create 1 rle with old method : 0.032709360122680664 time for calcul the mask position with numpy : 0.02913498878479004 nb_pixel_total : 18499 time to create 1 rle with old method : 0.021039962768554688 time for calcul the mask position with numpy : 0.02974104881286621 nb_pixel_total : 22768 time to create 1 rle with old method : 0.02611851692199707 time for calcul the mask position with numpy : 0.029201984405517578 nb_pixel_total : 25335 time to create 1 rle with old method : 0.041761159896850586 time for calcul the mask position with numpy : 0.029887914657592773 nb_pixel_total : 10042 time to create 1 rle with old method : 0.011418581008911133 time for calcul the mask position with numpy : 0.029140710830688477 nb_pixel_total : 10666 time to create 1 rle with old method : 0.012206315994262695 time for calcul the mask position with numpy : 0.030292749404907227 nb_pixel_total : 10916 time to create 1 rle with old method : 0.012376070022583008 time for calcul the mask position with numpy : 0.029664993286132812 nb_pixel_total : 4732 time to create 1 rle with old method : 0.005429983139038086 time for calcul the mask position with numpy : 0.0294187068939209 nb_pixel_total : 6399 time to create 1 rle with old method : 0.007348060607910156 create new chi : 3.6697750091552734 time to delete rle : 0.0037813186645507812 batch 1 Loaded 85 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 17183 TO DO : save crop sub photo not yet done ! save time : 1.0525686740875244 nb_obj : 29 nb_hashtags : 5 time to prepare the origin masks : 3.9322004318237305 time for calcul the mask position with numpy : 0.7440674304962158 nb_pixel_total : 6078633 time to create 1 rle with new method : 0.9656858444213867 time for calcul the mask position with numpy : 0.03133583068847656 nb_pixel_total : 4572 time to create 1 rle with old method : 0.005346536636352539 time for calcul the mask position with numpy : 0.031546831130981445 nb_pixel_total : 9533 time to create 1 rle with old method : 0.011812210083007812 time for calcul the mask position with numpy : 0.03200173377990723 nb_pixel_total : 20433 time to create 1 rle with old method : 0.023897886276245117 time for calcul the mask position with numpy : 0.03164982795715332 nb_pixel_total : 22690 time to create 1 rle with old method : 0.026031017303466797 time for calcul the mask position with numpy : 0.03186750411987305 nb_pixel_total : 10792 time to create 1 rle with old method : 0.015279054641723633 time for calcul the mask position with numpy : 0.031410932540893555 nb_pixel_total : 6726 time to create 1 rle with old method : 0.0077741146087646484 time for calcul the mask position with numpy : 0.06703901290893555 nb_pixel_total : 21718 time to create 1 rle with old method : 0.06456160545349121 time for calcul the mask position with numpy : 0.06226301193237305 nb_pixel_total : 61314 time to create 1 rle with old method : 0.10817432403564453 time for calcul the mask position with numpy : 0.03042435646057129 nb_pixel_total : 115425 time to create 1 rle with old method : 0.13623285293579102 time for calcul the mask position with numpy : 0.029581546783447266 nb_pixel_total : 9814 time to create 1 rle with old method : 0.011357784271240234 time for calcul the mask position with numpy : 0.029619455337524414 nb_pixel_total : 19528 time to create 1 rle with old method : 0.023141145706176758 time for calcul the mask position with numpy : 0.030323266983032227 nb_pixel_total : 33867 time to create 1 rle with old method : 0.04431486129760742 time for calcul the mask position with numpy : 0.03055572509765625 nb_pixel_total : 34186 time to create 1 rle with old method : 0.03877973556518555 time for calcul the mask position with numpy : 0.03019571304321289 nb_pixel_total : 26753 time to create 1 rle with old method : 0.030636072158813477 time for calcul the mask position with numpy : 0.029568195343017578 nb_pixel_total : 52980 time to create 1 rle with old method : 0.061292409896850586 time for calcul the mask position with numpy : 0.03125166893005371 nb_pixel_total : 11271 time to create 1 rle with old method : 0.013297319412231445 time for calcul the mask position with numpy : 0.0295255184173584 nb_pixel_total : 5457 time to create 1 rle with old method : 0.006291627883911133 time for calcul the mask position with numpy : 0.030289649963378906 nb_pixel_total : 20033 time to create 1 rle with old method : 0.028409242630004883 time for calcul the mask position with numpy : 0.03152799606323242 nb_pixel_total : 59268 time to create 1 rle with old method : 0.09208917617797852 time for calcul the mask position with numpy : 0.029776334762573242 nb_pixel_total : 31073 time to create 1 rle with old method : 0.03675436973571777 time for calcul the mask position with numpy : 0.029419422149658203 nb_pixel_total : 84581 time to create 1 rle with old method : 0.0996394157409668 time for calcul the mask position with numpy : 0.029450654983520508 nb_pixel_total : 10842 time to create 1 rle with old method : 0.012388944625854492 time for calcul the mask position with numpy : 0.03248429298400879 nb_pixel_total : 57573 time to create 1 rle with old method : 0.08348703384399414 time for calcul the mask position with numpy : 0.03754401206970215 nb_pixel_total : 41234 time to create 1 rle with old method : 0.06839847564697266 time for calcul the mask position with numpy : 0.03095555305480957 nb_pixel_total : 31851 time to create 1 rle with old method : 0.036249637603759766 time for calcul the mask position with numpy : 0.029768705368041992 nb_pixel_total : 115095 time to create 1 rle with old method : 0.13736653327941895 time for calcul the mask position with numpy : 0.03151655197143555 nb_pixel_total : 19374 time to create 1 rle with old method : 0.02191305160522461 time for calcul the mask position with numpy : 0.031032323837280273 nb_pixel_total : 12758 time to create 1 rle with old method : 0.01597905158996582 time for calcul the mask position with numpy : 0.03163003921508789 nb_pixel_total : 20866 time to create 1 rle with old method : 0.0259857177734375 create new chi : 4.009168863296509 time to delete rle : 0.0034770965576171875 batch 1 Loaded 59 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 14912 TO DO : save crop sub photo not yet done ! save time : 1.6200041770935059 nb_obj : 28 nb_hashtags : 5 time to prepare the origin masks : 3.7524256706237793 time for calcul the mask position with numpy : 0.6201069355010986 nb_pixel_total : 6235425 time to create 1 rle with new method : 0.5372748374938965 time for calcul the mask position with numpy : 0.029484033584594727 nb_pixel_total : 4511 time to create 1 rle with old method : 0.005194664001464844 time for calcul the mask position with numpy : 0.029494762420654297 nb_pixel_total : 18605 time to create 1 rle with old method : 0.021452903747558594 time for calcul the mask position with numpy : 0.0346674919128418 nb_pixel_total : 51127 time to create 1 rle with old method : 0.060726165771484375 time for calcul the mask position with numpy : 0.02951979637145996 nb_pixel_total : 13023 time to create 1 rle with old method : 0.01468515396118164 time for calcul the mask position with numpy : 0.02998828887939453 nb_pixel_total : 8187 time to create 1 rle with old method : 0.013274669647216797 time for calcul the mask position with numpy : 0.033687591552734375 nb_pixel_total : 60208 time to create 1 rle with old method : 0.07695221900939941 time for calcul the mask position with numpy : 0.02920675277709961 nb_pixel_total : 41365 time to create 1 rle with old method : 0.04672884941101074 time for calcul the mask position with numpy : 0.029694318771362305 nb_pixel_total : 14271 time to create 1 rle with old method : 0.01636791229248047 time for calcul the mask position with numpy : 0.029345989227294922 nb_pixel_total : 9169 time to create 1 rle with old method : 0.010615825653076172 time for calcul the mask position with numpy : 0.02969503402709961 nb_pixel_total : 20397 time to create 1 rle with old method : 0.02366495132446289 time for calcul the mask position with numpy : 0.030663728713989258 nb_pixel_total : 39665 time to create 1 rle with old method : 0.04609394073486328 time for calcul the mask position with numpy : 0.0299224853515625 nb_pixel_total : 44227 time to create 1 rle with old method : 0.050257205963134766 time for calcul the mask position with numpy : 0.03203773498535156 nb_pixel_total : 8920 time to create 1 rle with old method : 0.010329723358154297 time for calcul the mask position with numpy : 0.029895782470703125 nb_pixel_total : 11481 time to create 1 rle with old method : 0.016413211822509766 time for calcul the mask position with numpy : 0.029396772384643555 nb_pixel_total : 10906 time to create 1 rle with old method : 0.012285470962524414 time for calcul the mask position with numpy : 0.029302358627319336 nb_pixel_total : 20027 time to create 1 rle with old method : 0.022543668746948242 time for calcul the mask position with numpy : 0.029288291931152344 nb_pixel_total : 23556 time to create 1 rle with old method : 0.026818275451660156 time for calcul the mask position with numpy : 0.0296783447265625 nb_pixel_total : 55446 time to create 1 rle with old method : 0.06487083435058594 time for calcul the mask position with numpy : 0.03028106689453125 nb_pixel_total : 14459 time to create 1 rle with old method : 0.017763853073120117 time for calcul the mask position with numpy : 0.033887386322021484 nb_pixel_total : 61701 time to create 1 rle with old method : 0.07491707801818848 time for calcul the mask position with numpy : 0.030091285705566406 nb_pixel_total : 13910 time to create 1 rle with old method : 0.015750885009765625 time for calcul the mask position with numpy : 0.030157089233398438 nb_pixel_total : 32824 time to create 1 rle with old method : 0.03757023811340332 time for calcul the mask position with numpy : 0.030547618865966797 nb_pixel_total : 33516 time to create 1 rle with old method : 0.03953433036804199 time for calcul the mask position with numpy : 0.03233957290649414 nb_pixel_total : 30686 time to create 1 rle with old method : 0.03877449035644531 time for calcul the mask position with numpy : 0.030059337615966797 nb_pixel_total : 13863 time to create 1 rle with old method : 0.016029834747314453 time for calcul the mask position with numpy : 0.03171992301940918 nb_pixel_total : 51247 time to create 1 rle with old method : 0.059746742248535156 time for calcul the mask position with numpy : 0.030275821685791016 nb_pixel_total : 27741 time to create 1 rle with old method : 0.03260922431945801 time for calcul the mask position with numpy : 0.0314176082611084 nb_pixel_total : 79777 time to create 1 rle with old method : 0.09059453010559082 create new chi : 3.0213661193847656 time to delete rle : 0.003812074661254883 batch 1 Loaded 57 chid ids of type : 3594 ++++++++++++++++++++++++++++++++++++++Number RLEs to save : 14517 TO DO : save crop sub photo not yet done ! save time : 0.9983766078948975 nb_obj : 33 nb_hashtags : 3 time to prepare the origin masks : 4.234974145889282 time for calcul the mask position with numpy : 0.29003477096557617 nb_pixel_total : 5626037 time to create 1 rle with new method : 0.38013434410095215 time for calcul the mask position with numpy : 0.02995610237121582 nb_pixel_total : 43912 time to create 1 rle with old method : 0.04920363426208496 time for calcul the mask position with numpy : 0.029923677444458008 nb_pixel_total : 59780 time to create 1 rle with old method : 0.06714248657226562 time for calcul the mask position with numpy : 0.029114723205566406 nb_pixel_total : 23023 time to create 1 rle with old method : 0.02945852279663086 time for calcul the mask position with numpy : 0.02922677993774414 nb_pixel_total : 36804 time to create 1 rle with old method : 0.04145503044128418 time for calcul the mask position with numpy : 0.028935909271240234 nb_pixel_total : 27600 time to create 1 rle with old method : 0.03145313262939453 time for calcul the mask position with numpy : 0.0310518741607666 nb_pixel_total : 192852 time to create 1 rle with new method : 0.298581600189209 time for calcul the mask position with numpy : 0.029206514358520508 nb_pixel_total : 30176 time to create 1 rle with old method : 0.03432035446166992 time for calcul the mask position with numpy : 0.029261350631713867 nb_pixel_total : 21369 time to create 1 rle with old method : 0.02398514747619629 time for calcul the mask position with numpy : 0.029430866241455078 nb_pixel_total : 41604 time to create 1 rle with old method : 0.04706931114196777 time for calcul the mask position with numpy : 0.029144287109375 nb_pixel_total : 55035 time to create 1 rle with old method : 0.06209444999694824 time for calcul the mask position with numpy : 0.029371261596679688 nb_pixel_total : 80461 time to create 1 rle with old method : 0.09003257751464844 time for calcul the mask position with numpy : 0.02918553352355957 nb_pixel_total : 27043 time to create 1 rle with old method : 0.031213045120239258 time for calcul the mask position with numpy : 0.02957439422607422 nb_pixel_total : 41815 time to create 1 rle with old method : 0.04864668846130371 time for calcul the mask position with numpy : 0.02883434295654297 nb_pixel_total : 39237 time to create 1 rle with old method : 0.044011592864990234 time for calcul the mask position with numpy : 0.028933286666870117 nb_pixel_total : 33913 time to create 1 rle with old method : 0.03871560096740723 time for calcul the mask position with numpy : 0.029392004013061523 nb_pixel_total : 7589 time to create 1 rle with old method : 0.008765459060668945 time for calcul the mask position with numpy : 0.029753446578979492 nb_pixel_total : 29164 time to create 1 rle with old method : 0.03322434425354004 time for calcul the mask position with numpy : 0.02904820442199707 nb_pixel_total : 12996 time to create 1 rle with old method : 0.014887571334838867 time for calcul the mask position with numpy : 0.02924799919128418 nb_pixel_total : 26093 time to create 1 rle with old method : 0.029880046844482422 time for calcul the mask position with numpy : 0.03394484519958496 nb_pixel_total : 98672 time to create 1 rle with old method : 0.1291658878326416 time for calcul the mask position with numpy : 0.030037403106689453 nb_pixel_total : 34142 time to create 1 rle with old method : 0.038420915603637695 time for calcul the mask position with numpy : 0.029742717742919922 nb_pixel_total : 84600 time to create 1 rle with old method : 0.09519362449645996 time for calcul the mask position with numpy : 0.029400348663330078 nb_pixel_total : 64883 time to create 1 rle with old method : 0.07351279258728027 time for calcul the mask position with numpy : 0.029430150985717773 nb_pixel_total : 30748 time to create 1 rle with old method : 0.03470325469970703 time for calcul the mask position with numpy : 0.0294189453125 nb_pixel_total : 56292 time to create 1 rle with old method : 0.06278586387634277 time for calcul the mask position with numpy : 0.029022932052612305 nb_pixel_total : 112 time to create 1 rle with old method : 0.00017833709716796875 time for calcul the mask position with numpy : 0.029400110244750977 nb_pixel_total : 33758 time to create 1 rle with old method : 0.03841447830200195 time for calcul the mask position with numpy : 0.029248952865600586 nb_pixel_total : 21412 time to create 1 rle with old method : 0.023993968963623047 time for calcul the mask position with numpy : 0.029122591018676758 nb_pixel_total : 14201 time to create 1 rle with old method : 0.015966176986694336 time for calcul the mask position with numpy : 0.030230998992919922 nb_pixel_total : 12991 time to create 1 rle with old method : 0.014747858047485352 time for calcul the mask position with numpy : 0.0314335823059082 nb_pixel_total : 23659 time to create 1 rle with old method : 0.028011083602905273 time for calcul the mask position with numpy : 0.033041954040527344 nb_pixel_total : 110409 time to create 1 rle with old method : 0.13433456420898438 time for calcul the mask position with numpy : 0.031233549118041992 nb_pixel_total : 7858 time to create 1 rle with old method : 0.009206295013427734 create new chi : 3.4379260540008545 time to delete rle : 0.0034027099609375 batch 1 Loaded 67 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 20940 TO DO : save crop sub photo not yet done ! save time : 1.2634150981903076 nb_obj : 38 nb_hashtags : 6 time to prepare the origin masks : 4.328815937042236 time for calcul the mask position with numpy : 1.4218790531158447 nb_pixel_total : 5806726 time to create 1 rle with new method : 1.4469268321990967 time for calcul the mask position with numpy : 0.029378652572631836 nb_pixel_total : 22701 time to create 1 rle with old method : 0.02709054946899414 time for calcul the mask position with numpy : 0.02919626235961914 nb_pixel_total : 16753 time to create 1 rle with old method : 0.02170538902282715 time for calcul the mask position with numpy : 0.029183626174926758 nb_pixel_total : 14997 time to create 1 rle with old method : 0.01788926124572754 time for calcul the mask position with numpy : 0.029531002044677734 nb_pixel_total : 44064 time to create 1 rle with old method : 0.055472612380981445 time for calcul the mask position with numpy : 0.03248095512390137 nb_pixel_total : 54887 time to create 1 rle with old method : 0.06756138801574707 time for calcul the mask position with numpy : 0.030138731002807617 nb_pixel_total : 18483 time to create 1 rle with old method : 0.02104783058166504 time for calcul the mask position with numpy : 0.032711029052734375 nb_pixel_total : 6090 time to create 1 rle with old method : 0.0070285797119140625 time for calcul the mask position with numpy : 0.02980351448059082 nb_pixel_total : 28336 time to create 1 rle with old method : 0.034751176834106445 time for calcul the mask position with numpy : 0.03631758689880371 nb_pixel_total : 17803 time to create 1 rle with old method : 0.02175426483154297 time for calcul the mask position with numpy : 0.029512405395507812 nb_pixel_total : 26487 time to create 1 rle with old method : 0.029817819595336914 time for calcul the mask position with numpy : 0.030893802642822266 nb_pixel_total : 130724 time to create 1 rle with old method : 0.1486802101135254 time for calcul the mask position with numpy : 0.030724763870239258 nb_pixel_total : 50502 time to create 1 rle with old method : 0.05684351921081543 time for calcul the mask position with numpy : 0.02903580665588379 nb_pixel_total : 57703 time to create 1 rle with old method : 0.06501197814941406 time for calcul the mask position with numpy : 0.029103755950927734 nb_pixel_total : 29800 time to create 1 rle with old method : 0.033516645431518555 time for calcul the mask position with numpy : 0.02902078628540039 nb_pixel_total : 54606 time to create 1 rle with old method : 0.061423301696777344 time for calcul the mask position with numpy : 0.02889561653137207 nb_pixel_total : 18257 time to create 1 rle with old method : 0.020780324935913086 time for calcul the mask position with numpy : 0.02943706512451172 nb_pixel_total : 134437 time to create 1 rle with old method : 0.15425467491149902 time for calcul the mask position with numpy : 0.0294954776763916 nb_pixel_total : 25566 time to create 1 rle with old method : 0.02902388572692871 time for calcul the mask position with numpy : 0.028944969177246094 nb_pixel_total : 6252 time to create 1 rle with old method : 0.007189512252807617 time for calcul the mask position with numpy : 0.03196835517883301 nb_pixel_total : 36313 time to create 1 rle with old method : 0.054070472717285156 time for calcul the mask position with numpy : 0.03625774383544922 nb_pixel_total : 28173 time to create 1 rle with old method : 0.04339337348937988 time for calcul the mask position with numpy : 0.029046297073364258 nb_pixel_total : 7223 time to create 1 rle with old method : 0.008208274841308594 time for calcul the mask position with numpy : 0.02889847755432129 nb_pixel_total : 16929 time to create 1 rle with old method : 0.019051074981689453 time for calcul the mask position with numpy : 0.029137134552001953 nb_pixel_total : 25625 time to create 1 rle with old method : 0.029088497161865234 time for calcul the mask position with numpy : 0.02895212173461914 nb_pixel_total : 25605 time to create 1 rle with old method : 0.02897024154663086 time for calcul the mask position with numpy : 0.02901768684387207 nb_pixel_total : 27377 time to create 1 rle with old method : 0.03088545799255371 time for calcul the mask position with numpy : 0.03284740447998047 nb_pixel_total : 28656 time to create 1 rle with old method : 0.03233146667480469 time for calcul the mask position with numpy : 0.02893376350402832 nb_pixel_total : 6444 time to create 1 rle with old method : 0.007353305816650391 time for calcul the mask position with numpy : 0.028865814208984375 nb_pixel_total : 4037 time to create 1 rle with old method : 0.004938364028930664 time for calcul the mask position with numpy : 0.030747413635253906 nb_pixel_total : 30161 time to create 1 rle with old method : 0.03369927406311035 time for calcul the mask position with numpy : 0.02891230583190918 nb_pixel_total : 33209 time to create 1 rle with old method : 0.03720545768737793 time for calcul the mask position with numpy : 0.029149532318115234 nb_pixel_total : 15990 time to create 1 rle with old method : 0.018137454986572266 time for calcul the mask position with numpy : 0.030469417572021484 nb_pixel_total : 108448 time to create 1 rle with old method : 0.12531757354736328 time for calcul the mask position with numpy : 0.029619932174682617 nb_pixel_total : 14132 time to create 1 rle with old method : 0.016377925872802734 time for calcul the mask position with numpy : 0.031196117401123047 nb_pixel_total : 44345 time to create 1 rle with old method : 0.052480459213256836 time for calcul the mask position with numpy : 0.02994513511657715 nb_pixel_total : 5073 time to create 1 rle with old method : 0.005976438522338867 time for calcul the mask position with numpy : 0.029626846313476562 nb_pixel_total : 21999 time to create 1 rle with old method : 0.025125980377197266 time for calcul the mask position with numpy : 0.030246496200561523 nb_pixel_total : 5327 time to create 1 rle with old method : 0.007422447204589844 create new chi : 5.518195390701294 time to delete rle : 0.0028455257415771484 batch 1 Loaded 77 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 18570 TO DO : save crop sub photo not yet done ! save time : 1.1084926128387451 nb_obj : 27 nb_hashtags : 6 time to prepare the origin masks : 4.131100177764893 time for calcul the mask position with numpy : 0.5919051170349121 nb_pixel_total : 5579708 time to create 1 rle with new method : 1.0384373664855957 time for calcul the mask position with numpy : 0.02914142608642578 nb_pixel_total : 12134 time to create 1 rle with old method : 0.013679981231689453 time for calcul the mask position with numpy : 0.029352903366088867 nb_pixel_total : 46544 time to create 1 rle with old method : 0.05242466926574707 time for calcul the mask position with numpy : 0.03002166748046875 nb_pixel_total : 26023 time to create 1 rle with old method : 0.029294967651367188 time for calcul the mask position with numpy : 0.02898573875427246 nb_pixel_total : 23123 time to create 1 rle with old method : 0.026894092559814453 time for calcul the mask position with numpy : 0.030629873275756836 nb_pixel_total : 16867 time to create 1 rle with old method : 0.01904010772705078 time for calcul the mask position with numpy : 0.03336644172668457 nb_pixel_total : 39413 time to create 1 rle with old method : 0.04829263687133789 time for calcul the mask position with numpy : 0.03151822090148926 nb_pixel_total : 26893 time to create 1 rle with old method : 0.03072047233581543 time for calcul the mask position with numpy : 0.029155492782592773 nb_pixel_total : 52887 time to create 1 rle with old method : 0.05942106246948242 time for calcul the mask position with numpy : 0.02900099754333496 nb_pixel_total : 61212 time to create 1 rle with old method : 0.06945276260375977 time for calcul the mask position with numpy : 0.02883005142211914 nb_pixel_total : 16168 time to create 1 rle with old method : 0.018285512924194336 time for calcul the mask position with numpy : 0.02891254425048828 nb_pixel_total : 52652 time to create 1 rle with old method : 0.05940365791320801 time for calcul the mask position with numpy : 0.028757095336914062 nb_pixel_total : 9742 time to create 1 rle with old method : 0.010943889617919922 time for calcul the mask position with numpy : 0.030397891998291016 nb_pixel_total : 106170 time to create 1 rle with old method : 0.11848187446594238 time for calcul the mask position with numpy : 0.028986454010009766 nb_pixel_total : 31424 time to create 1 rle with old method : 0.03540658950805664 time for calcul the mask position with numpy : 0.029026508331298828 nb_pixel_total : 63253 time to create 1 rle with old method : 0.07128763198852539 time for calcul the mask position with numpy : 0.029457807540893555 nb_pixel_total : 13288 time to create 1 rle with old method : 0.015033245086669922 time for calcul the mask position with numpy : 0.030663013458251953 nb_pixel_total : 269519 time to create 1 rle with new method : 0.49202942848205566 time for calcul the mask position with numpy : 0.02966785430908203 nb_pixel_total : 86668 time to create 1 rle with old method : 0.09695219993591309 time for calcul the mask position with numpy : 0.029695749282836914 nb_pixel_total : 74236 time to create 1 rle with old method : 0.08349776268005371 time for calcul the mask position with numpy : 0.03029322624206543 nb_pixel_total : 84251 time to create 1 rle with old method : 0.09714221954345703 time for calcul the mask position with numpy : 0.030393123626708984 nb_pixel_total : 149070 time to create 1 rle with old method : 0.17029690742492676 time for calcul the mask position with numpy : 0.029679298400878906 nb_pixel_total : 51454 time to create 1 rle with old method : 0.05856633186340332 time for calcul the mask position with numpy : 0.029816150665283203 nb_pixel_total : 32381 time to create 1 rle with old method : 0.03750324249267578 time for calcul the mask position with numpy : 0.029288053512573242 nb_pixel_total : 45658 time to create 1 rle with old method : 0.05129241943359375 time for calcul the mask position with numpy : 0.029427289962768555 nb_pixel_total : 56058 time to create 1 rle with old method : 0.06343555450439453 time for calcul the mask position with numpy : 0.029012441635131836 nb_pixel_total : 5964 time to create 1 rle with old method : 0.006899118423461914 time for calcul the mask position with numpy : 0.029246807098388672 nb_pixel_total : 17480 time to create 1 rle with old method : 0.01982855796813965 create new chi : 4.3489038944244385 time to delete rle : 0.0027675628662109375 batch 1 Loaded 55 chid ids of type : 3594 ++++++++++++++++++++++++++++++++++++Number RLEs to save : 18176 TO DO : save crop sub photo not yet done ! save time : 1.0707025527954102 nb_obj : 28 nb_hashtags : 4 time to prepare the origin masks : 4.59898042678833 time for calcul the mask position with numpy : 0.31607866287231445 nb_pixel_total : 4841419 time to create 1 rle with new method : 0.5215368270874023 time for calcul the mask position with numpy : 0.029753446578979492 nb_pixel_total : 61538 time to create 1 rle with old method : 0.06926870346069336 time for calcul the mask position with numpy : 0.029085397720336914 nb_pixel_total : 20840 time to create 1 rle with old method : 0.02382040023803711 time for calcul the mask position with numpy : 0.02892279624938965 nb_pixel_total : 26463 time to create 1 rle with old method : 0.029915571212768555 time for calcul the mask position with numpy : 0.030267000198364258 nb_pixel_total : 250511 time to create 1 rle with new method : 0.48427772521972656 time for calcul the mask position with numpy : 0.029413461685180664 nb_pixel_total : 29740 time to create 1 rle with old method : 0.03431344032287598 time for calcul the mask position with numpy : 0.028986692428588867 nb_pixel_total : 37946 time to create 1 rle with old method : 0.04292488098144531 time for calcul the mask position with numpy : 0.029046297073364258 nb_pixel_total : 65081 time to create 1 rle with old method : 0.07301855087280273 time for calcul the mask position with numpy : 0.028792142868041992 nb_pixel_total : 60832 time to create 1 rle with old method : 0.07077836990356445 time for calcul the mask position with numpy : 0.029638290405273438 nb_pixel_total : 194303 time to create 1 rle with new method : 0.5543677806854248 time for calcul the mask position with numpy : 0.02948737144470215 nb_pixel_total : 410937 time to create 1 rle with new method : 0.607975959777832 time for calcul the mask position with numpy : 0.028989076614379883 nb_pixel_total : 65485 time to create 1 rle with old method : 0.0743265151977539 time for calcul the mask position with numpy : 0.029259920120239258 nb_pixel_total : 165811 time to create 1 rle with new method : 0.6077938079833984 time for calcul the mask position with numpy : 0.029157161712646484 nb_pixel_total : 28896 time to create 1 rle with old method : 0.0325474739074707 time for calcul the mask position with numpy : 0.02959728240966797 nb_pixel_total : 98181 time to create 1 rle with old method : 0.11285853385925293 time for calcul the mask position with numpy : 0.028966665267944336 nb_pixel_total : 74289 time to create 1 rle with old method : 0.08346104621887207 time for calcul the mask position with numpy : 0.030020713806152344 nb_pixel_total : 97534 time to create 1 rle with old method : 0.13130688667297363 time for calcul the mask position with numpy : 0.028942584991455078 nb_pixel_total : 29244 time to create 1 rle with old method : 0.03293943405151367 time for calcul the mask position with numpy : 0.03032088279724121 nb_pixel_total : 251128 time to create 1 rle with new method : 0.8752915859222412 time for calcul the mask position with numpy : 0.029538393020629883 nb_pixel_total : 53291 time to create 1 rle with old method : 0.06901788711547852 time for calcul the mask position with numpy : 0.029430389404296875 nb_pixel_total : 21979 time to create 1 rle with old method : 0.02693915367126465 time for calcul the mask position with numpy : 0.029986143112182617 nb_pixel_total : 16934 time to create 1 rle with old method : 0.018955707550048828 time for calcul the mask position with numpy : 0.029152393341064453 nb_pixel_total : 16122 time to create 1 rle with old method : 0.01831197738647461 time for calcul the mask position with numpy : 0.0293118953704834 nb_pixel_total : 59760 time to create 1 rle with old method : 0.06760287284851074 time for calcul the mask position with numpy : 0.02941608428955078 nb_pixel_total : 23464 time to create 1 rle with old method : 0.02685856819152832 time for calcul the mask position with numpy : 0.02896738052368164 nb_pixel_total : 5703 time to create 1 rle with old method : 0.0064449310302734375 time for calcul the mask position with numpy : 0.029261112213134766 nb_pixel_total : 20860 time to create 1 rle with old method : 0.023680686950683594 time for calcul the mask position with numpy : 0.029256105422973633 nb_pixel_total : 13683 time to create 1 rle with old method : 0.01670384407043457 time for calcul the mask position with numpy : 0.029006481170654297 nb_pixel_total : 8266 time to create 1 rle with old method : 0.009437084197998047 create new chi : 6.047032117843628 time to delete rle : 0.004157066345214844 batch 1 Loaded 57 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 20524 TO DO : save crop sub photo not yet done ! save time : 1.378671407699585 nb_obj : 32 nb_hashtags : 3 time to prepare the origin masks : 4.483651876449585 time for calcul the mask position with numpy : 0.4976949691772461 nb_pixel_total : 5296474 time to create 1 rle with new method : 1.1038212776184082 time for calcul the mask position with numpy : 0.030397653579711914 nb_pixel_total : 34984 time to create 1 rle with old method : 0.041674137115478516 time for calcul the mask position with numpy : 0.03316092491149902 nb_pixel_total : 128179 time to create 1 rle with old method : 0.16349029541015625 time for calcul the mask position with numpy : 0.03265500068664551 nb_pixel_total : 15424 time to create 1 rle with old method : 0.017375946044921875 time for calcul the mask position with numpy : 0.028978347778320312 nb_pixel_total : 14786 time to create 1 rle with old method : 0.016707897186279297 time for calcul the mask position with numpy : 0.0298612117767334 nb_pixel_total : 92996 time to create 1 rle with old method : 0.10667562484741211 time for calcul the mask position with numpy : 0.03093552589416504 nb_pixel_total : 204551 time to create 1 rle with new method : 0.8189020156860352 time for calcul the mask position with numpy : 0.02904963493347168 nb_pixel_total : 1629 time to create 1 rle with old method : 0.0023877620697021484 time for calcul the mask position with numpy : 0.03482699394226074 nb_pixel_total : 117200 time to create 1 rle with old method : 0.14250516891479492 time for calcul the mask position with numpy : 0.030218839645385742 nb_pixel_total : 10453 time to create 1 rle with old method : 0.01182246208190918 time for calcul the mask position with numpy : 0.02892470359802246 nb_pixel_total : 20680 time to create 1 rle with old method : 0.023797988891601562 time for calcul the mask position with numpy : 0.029294729232788086 nb_pixel_total : 18573 time to create 1 rle with old method : 0.020831584930419922 time for calcul the mask position with numpy : 0.029414653778076172 nb_pixel_total : 26907 time to create 1 rle with old method : 0.030291080474853516 time for calcul the mask position with numpy : 0.03229951858520508 nb_pixel_total : 20261 time to create 1 rle with old method : 0.024579524993896484 time for calcul the mask position with numpy : 0.030390501022338867 nb_pixel_total : 123870 time to create 1 rle with old method : 0.14445853233337402 time for calcul the mask position with numpy : 0.02921271324157715 nb_pixel_total : 38879 time to create 1 rle with old method : 0.04625558853149414 time for calcul the mask position with numpy : 0.03179025650024414 nb_pixel_total : 42984 time to create 1 rle with old method : 0.0484616756439209 time for calcul the mask position with numpy : 0.0302579402923584 nb_pixel_total : 247672 time to create 1 rle with new method : 0.521151065826416 time for calcul the mask position with numpy : 0.02883005142211914 nb_pixel_total : 20851 time to create 1 rle with old method : 0.02370429039001465 time for calcul the mask position with numpy : 0.02991771697998047 nb_pixel_total : 167226 time to create 1 rle with new method : 0.8627245426177979 time for calcul the mask position with numpy : 0.02905750274658203 nb_pixel_total : 5926 time to create 1 rle with old method : 0.0067026615142822266 time for calcul the mask position with numpy : 0.02906179428100586 nb_pixel_total : 9006 time to create 1 rle with old method : 0.010432004928588867 time for calcul the mask position with numpy : 0.03166055679321289 nb_pixel_total : 100123 time to create 1 rle with old method : 0.1138303279876709 time for calcul the mask position with numpy : 0.029566287994384766 nb_pixel_total : 21259 time to create 1 rle with old method : 0.02440667152404785 time for calcul the mask position with numpy : 0.033112287521362305 nb_pixel_total : 22990 time to create 1 rle with old method : 0.03706955909729004 time for calcul the mask position with numpy : 0.03156781196594238 nb_pixel_total : 26072 time to create 1 rle with old method : 0.029415130615234375 time for calcul the mask position with numpy : 0.0290069580078125 nb_pixel_total : 6985 time to create 1 rle with old method : 0.007830381393432617 time for calcul the mask position with numpy : 0.02944779396057129 nb_pixel_total : 48320 time to create 1 rle with old method : 0.05395007133483887 time for calcul the mask position with numpy : 0.02902054786682129 nb_pixel_total : 16605 time to create 1 rle with old method : 0.018976449966430664 time for calcul the mask position with numpy : 0.030487775802612305 nb_pixel_total : 68410 time to create 1 rle with old method : 0.08259010314941406 time for calcul the mask position with numpy : 0.029163122177124023 nb_pixel_total : 34334 time to create 1 rle with old method : 0.041159868240356445 time for calcul the mask position with numpy : 0.03008270263671875 nb_pixel_total : 25992 time to create 1 rle with old method : 0.029567956924438477 time for calcul the mask position with numpy : 0.03194785118103027 nb_pixel_total : 19639 time to create 1 rle with old method : 0.0224454402923584 create new chi : 6.224265813827515 time to delete rle : 0.0036613941192626953 batch 1 Loaded 65 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 20109 TO DO : save crop sub photo not yet done ! save time : 2.033339262008667 nb_obj : 37 nb_hashtags : 6 time to prepare the origin masks : 4.437834024429321 time for calcul the mask position with numpy : 0.4805581569671631 nb_pixel_total : 5426482 time to create 1 rle with new method : 0.7983214855194092 time for calcul the mask position with numpy : 0.029816865921020508 nb_pixel_total : 29780 time to create 1 rle with old method : 0.033795833587646484 time for calcul the mask position with numpy : 0.03145241737365723 nb_pixel_total : 143948 time to create 1 rle with old method : 0.16067123413085938 time for calcul the mask position with numpy : 0.029095888137817383 nb_pixel_total : 24119 time to create 1 rle with old method : 0.02705693244934082 time for calcul the mask position with numpy : 0.029340744018554688 nb_pixel_total : 35219 time to create 1 rle with old method : 0.03924369812011719 time for calcul the mask position with numpy : 0.028909921646118164 nb_pixel_total : 6420 time to create 1 rle with old method : 0.007228374481201172 time for calcul the mask position with numpy : 0.029587507247924805 nb_pixel_total : 68823 time to create 1 rle with old method : 0.07789158821105957 time for calcul the mask position with numpy : 0.029254436492919922 nb_pixel_total : 24619 time to create 1 rle with old method : 0.029610157012939453 time for calcul the mask position with numpy : 0.029947996139526367 nb_pixel_total : 155030 time to create 1 rle with new method : 0.6793472766876221 time for calcul the mask position with numpy : 0.02940082550048828 nb_pixel_total : 113864 time to create 1 rle with old method : 0.13036847114562988 time for calcul the mask position with numpy : 0.028906822204589844 nb_pixel_total : 13921 time to create 1 rle with old method : 0.015669584274291992 time for calcul the mask position with numpy : 0.02873826026916504 nb_pixel_total : 23690 time to create 1 rle with old method : 0.026553630828857422 time for calcul the mask position with numpy : 0.028781652450561523 nb_pixel_total : 26812 time to create 1 rle with old method : 0.03012371063232422 time for calcul the mask position with numpy : 0.029155492782592773 nb_pixel_total : 117223 time to create 1 rle with old method : 0.13184213638305664 time for calcul the mask position with numpy : 0.029177188873291016 nb_pixel_total : 67334 time to create 1 rle with old method : 0.07491064071655273 time for calcul the mask position with numpy : 0.02895212173461914 nb_pixel_total : 33001 time to create 1 rle with old method : 0.037138938903808594 time for calcul the mask position with numpy : 0.02890467643737793 nb_pixel_total : 19791 time to create 1 rle with old method : 0.022732973098754883 time for calcul the mask position with numpy : 0.02917766571044922 nb_pixel_total : 23984 time to create 1 rle with old method : 0.027364253997802734 time for calcul the mask position with numpy : 0.029088497161865234 nb_pixel_total : 43101 time to create 1 rle with old method : 0.04858684539794922 time for calcul the mask position with numpy : 0.028982877731323242 nb_pixel_total : 47220 time to create 1 rle with old method : 0.053693294525146484 time for calcul the mask position with numpy : 0.028832197189331055 nb_pixel_total : 4511 time to create 1 rle with old method : 0.005275249481201172 time for calcul the mask position with numpy : 0.0290834903717041 nb_pixel_total : 50653 time to create 1 rle with old method : 0.07621121406555176 time for calcul the mask position with numpy : 0.032418012619018555 nb_pixel_total : 33282 time to create 1 rle with old method : 0.03774714469909668 time for calcul the mask position with numpy : 0.028973817825317383 nb_pixel_total : 45324 time to create 1 rle with old method : 0.05101823806762695 time for calcul the mask position with numpy : 0.02974677085876465 nb_pixel_total : 14570 time to create 1 rle with old method : 0.01652240753173828 time for calcul the mask position with numpy : 0.029452085494995117 nb_pixel_total : 12579 time to create 1 rle with old method : 0.01417684555053711 time for calcul the mask position with numpy : 0.029440641403198242 nb_pixel_total : 24729 time to create 1 rle with old method : 0.029306888580322266 time for calcul the mask position with numpy : 0.03221297264099121 nb_pixel_total : 10518 time to create 1 rle with old method : 0.011994123458862305 time for calcul the mask position with numpy : 0.030953168869018555 nb_pixel_total : 16353 time to create 1 rle with old method : 0.01906585693359375 time for calcul the mask position with numpy : 0.02936077117919922 nb_pixel_total : 40119 time to create 1 rle with old method : 0.045438528060913086 time for calcul the mask position with numpy : 0.029980182647705078 nb_pixel_total : 11158 time to create 1 rle with old method : 0.012628555297851562 time for calcul the mask position with numpy : 0.02941107749938965 nb_pixel_total : 43727 time to create 1 rle with old method : 0.048959970474243164 time for calcul the mask position with numpy : 0.03013467788696289 nb_pixel_total : 83044 time to create 1 rle with old method : 0.09426188468933105 time for calcul the mask position with numpy : 0.03077077865600586 nb_pixel_total : 121658 time to create 1 rle with old method : 0.1621105670928955 time for calcul the mask position with numpy : 0.0295257568359375 nb_pixel_total : 16986 time to create 1 rle with old method : 0.019501686096191406 time for calcul the mask position with numpy : 0.029151201248168945 nb_pixel_total : 19691 time to create 1 rle with old method : 0.022348403930664062 time for calcul the mask position with numpy : 0.030225515365600586 nb_pixel_total : 41419 time to create 1 rle with old method : 0.06695556640625 time for calcul the mask position with numpy : 0.0300443172454834 nb_pixel_total : 15538 time to create 1 rle with old method : 0.017403125762939453 create new chi : 4.842645168304443 time to delete rle : 0.0030994415283203125 batch 1 Loaded 75 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 20252 TO DO : save crop sub photo not yet done ! save time : 1.1751289367675781 nb_obj : 37 nb_hashtags : 5 time to prepare the origin masks : 4.54827094078064 time for calcul the mask position with numpy : 0.22369742393493652 nb_pixel_total : 5156495 time to create 1 rle with new method : 0.779679536819458 time for calcul the mask position with numpy : 0.029642105102539062 nb_pixel_total : 44532 time to create 1 rle with old method : 0.05244255065917969 time for calcul the mask position with numpy : 0.028977155685424805 nb_pixel_total : 22676 time to create 1 rle with old method : 0.025593996047973633 time for calcul the mask position with numpy : 0.03336954116821289 nb_pixel_total : 411357 time to create 1 rle with new method : 0.47251105308532715 time for calcul the mask position with numpy : 0.029485464096069336 nb_pixel_total : 34162 time to create 1 rle with old method : 0.040259361267089844 time for calcul the mask position with numpy : 0.03331279754638672 nb_pixel_total : 54630 time to create 1 rle with old method : 0.07287096977233887 time for calcul the mask position with numpy : 0.02942180633544922 nb_pixel_total : 36170 time to create 1 rle with old method : 0.04105091094970703 time for calcul the mask position with numpy : 0.02917623519897461 nb_pixel_total : 20214 time to create 1 rle with old method : 0.022808313369750977 time for calcul the mask position with numpy : 0.0290524959564209 nb_pixel_total : 8114 time to create 1 rle with old method : 0.009458780288696289 time for calcul the mask position with numpy : 0.029358863830566406 nb_pixel_total : 36540 time to create 1 rle with old method : 0.041201114654541016 time for calcul the mask position with numpy : 0.02938675880432129 nb_pixel_total : 93942 time to create 1 rle with old method : 0.11686110496520996 time for calcul the mask position with numpy : 0.029424428939819336 nb_pixel_total : 10457 time to create 1 rle with old method : 0.012017488479614258 time for calcul the mask position with numpy : 0.028959989547729492 nb_pixel_total : 13709 time to create 1 rle with old method : 0.015653133392333984 time for calcul the mask position with numpy : 0.029511213302612305 nb_pixel_total : 149351 time to create 1 rle with old method : 0.17558836936950684 time for calcul the mask position with numpy : 0.02890467643737793 nb_pixel_total : 42629 time to create 1 rle with old method : 0.0478518009185791 time for calcul the mask position with numpy : 0.028923511505126953 nb_pixel_total : 24327 time to create 1 rle with old method : 0.02737116813659668 time for calcul the mask position with numpy : 0.028849124908447266 nb_pixel_total : 25626 time to create 1 rle with old method : 0.029070138931274414 time for calcul the mask position with numpy : 0.030185461044311523 nb_pixel_total : 215636 time to create 1 rle with new method : 0.5687606334686279 time for calcul the mask position with numpy : 0.028923511505126953 nb_pixel_total : 46315 time to create 1 rle with old method : 0.05193448066711426 time for calcul the mask position with numpy : 0.02926015853881836 nb_pixel_total : 3433 time to create 1 rle with old method : 0.003963470458984375 time for calcul the mask position with numpy : 0.02904534339904785 nb_pixel_total : 80763 time to create 1 rle with old method : 0.09152436256408691 time for calcul the mask position with numpy : 0.02895975112915039 nb_pixel_total : 10523 time to create 1 rle with old method : 0.012003183364868164 time for calcul the mask position with numpy : 0.02930307388305664 nb_pixel_total : 145199 time to create 1 rle with old method : 0.16320157051086426 time for calcul the mask position with numpy : 0.029019832611083984 nb_pixel_total : 39700 time to create 1 rle with old method : 0.04503917694091797 time for calcul the mask position with numpy : 0.0289919376373291 nb_pixel_total : 32366 time to create 1 rle with old method : 0.03675031661987305 time for calcul the mask position with numpy : 0.028971195220947266 nb_pixel_total : 23146 time to create 1 rle with old method : 0.026210546493530273 time for calcul the mask position with numpy : 0.02924060821533203 nb_pixel_total : 65963 time to create 1 rle with old method : 0.07457828521728516 time for calcul the mask position with numpy : 0.02920365333557129 nb_pixel_total : 79352 time to create 1 rle with old method : 0.08917069435119629 time for calcul the mask position with numpy : 0.028797388076782227 nb_pixel_total : 10831 time to create 1 rle with old method : 0.012369155883789062 time for calcul the mask position with numpy : 0.028689861297607422 nb_pixel_total : 5644 time to create 1 rle with old method : 0.0064678192138671875 time for calcul the mask position with numpy : 0.028795242309570312 nb_pixel_total : 13343 time to create 1 rle with old method : 0.015010833740234375 time for calcul the mask position with numpy : 0.02886199951171875 nb_pixel_total : 6492 time to create 1 rle with old method : 0.0073473453521728516 time for calcul the mask position with numpy : 0.02899336814880371 nb_pixel_total : 29430 time to create 1 rle with old method : 0.033478736877441406 time for calcul the mask position with numpy : 0.028858661651611328 nb_pixel_total : 6768 time to create 1 rle with old method : 0.007850170135498047 time for calcul the mask position with numpy : 0.028813838958740234 nb_pixel_total : 17345 time to create 1 rle with old method : 0.019700288772583008 time for calcul the mask position with numpy : 0.028964757919311523 nb_pixel_total : 9324 time to create 1 rle with old method : 0.010641336441040039 time for calcul the mask position with numpy : 0.02884054183959961 nb_pixel_total : 15651 time to create 1 rle with old method : 0.01781606674194336 time for calcul the mask position with numpy : 0.029103994369506836 nb_pixel_total : 8085 time to create 1 rle with old method : 0.009238243103027344 create new chi : 4.67863917350769 time to delete rle : 0.004571676254272461 batch 1 Loaded 75 chid ids of type : 3594 ++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 20973 TO DO : save crop sub photo not yet done ! save time : 1.1958487033843994 nb_obj : 28 nb_hashtags : 5 time to prepare the origin masks : 4.12024450302124 time for calcul the mask position with numpy : 0.6027512550354004 nb_pixel_total : 5842384 time to create 1 rle with new method : 0.6116321086883545 time for calcul the mask position with numpy : 0.029746294021606445 nb_pixel_total : 5735 time to create 1 rle with old method : 0.0065190792083740234 time for calcul the mask position with numpy : 0.030146360397338867 nb_pixel_total : 45745 time to create 1 rle with old method : 0.0568087100982666 time for calcul the mask position with numpy : 0.033640384674072266 nb_pixel_total : 36322 time to create 1 rle with old method : 0.04402756690979004 time for calcul the mask position with numpy : 0.03095841407775879 nb_pixel_total : 23350 time to create 1 rle with old method : 0.030259132385253906 time for calcul the mask position with numpy : 0.034348249435424805 nb_pixel_total : 118169 time to create 1 rle with old method : 0.148115873336792 time for calcul the mask position with numpy : 0.029439210891723633 nb_pixel_total : 82986 time to create 1 rle with old method : 0.09270977973937988 time for calcul the mask position with numpy : 0.02956676483154297 nb_pixel_total : 10435 time to create 1 rle with old method : 0.01193690299987793 time for calcul the mask position with numpy : 0.02916717529296875 nb_pixel_total : 101468 time to create 1 rle with old method : 0.1146845817565918 time for calcul the mask position with numpy : 0.029181241989135742 nb_pixel_total : 13573 time to create 1 rle with old method : 0.015248775482177734 time for calcul the mask position with numpy : 0.028776168823242188 nb_pixel_total : 35208 time to create 1 rle with old method : 0.03933262825012207 time for calcul the mask position with numpy : 0.029577016830444336 nb_pixel_total : 3711 time to create 1 rle with old method : 0.004183053970336914 time for calcul the mask position with numpy : 0.028922557830810547 nb_pixel_total : 61372 time to create 1 rle with old method : 0.07018327713012695 time for calcul the mask position with numpy : 0.02913665771484375 nb_pixel_total : 46905 time to create 1 rle with old method : 0.07267260551452637 time for calcul the mask position with numpy : 0.031575918197631836 nb_pixel_total : 52684 time to create 1 rle with old method : 0.0589447021484375 time for calcul the mask position with numpy : 0.02905583381652832 nb_pixel_total : 58111 time to create 1 rle with old method : 0.06517386436462402 time for calcul the mask position with numpy : 0.029191017150878906 nb_pixel_total : 83912 time to create 1 rle with old method : 0.09366655349731445 time for calcul the mask position with numpy : 0.029018878936767578 nb_pixel_total : 27271 time to create 1 rle with old method : 0.03079676628112793 time for calcul the mask position with numpy : 0.028885364532470703 nb_pixel_total : 20172 time to create 1 rle with old method : 0.022579431533813477 time for calcul the mask position with numpy : 0.028955698013305664 nb_pixel_total : 48866 time to create 1 rle with old method : 0.05525851249694824 time for calcul the mask position with numpy : 0.028931140899658203 nb_pixel_total : 29594 time to create 1 rle with old method : 0.033274173736572266 time for calcul the mask position with numpy : 0.0288541316986084 nb_pixel_total : 24949 time to create 1 rle with old method : 0.028069734573364258 time for calcul the mask position with numpy : 0.028914451599121094 nb_pixel_total : 13859 time to create 1 rle with old method : 0.015709400177001953 time for calcul the mask position with numpy : 0.030715227127075195 nb_pixel_total : 98913 time to create 1 rle with old method : 0.11038613319396973 time for calcul the mask position with numpy : 0.02977299690246582 nb_pixel_total : 56211 time to create 1 rle with old method : 0.06822848320007324 time for calcul the mask position with numpy : 0.0295255184173584 nb_pixel_total : 43769 time to create 1 rle with old method : 0.04954648017883301 time for calcul the mask position with numpy : 0.029167890548706055 nb_pixel_total : 23406 time to create 1 rle with old method : 0.02670907974243164 time for calcul the mask position with numpy : 0.02928900718688965 nb_pixel_total : 31234 time to create 1 rle with old method : 0.03798651695251465 time for calcul the mask position with numpy : 0.030214309692382812 nb_pixel_total : 9926 time to create 1 rle with old method : 0.011815786361694336 create new chi : 3.500351905822754 time to delete rle : 0.0035219192504882812 batch 1 Loaded 57 chid ids of type : 3594 ++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 18716 TO DO : save crop sub photo not yet done ! save time : 1.093574047088623 nb_obj : 37 nb_hashtags : 4 time to prepare the origin masks : 3.901538610458374 time for calcul the mask position with numpy : 0.5747098922729492 nb_pixel_total : 5933407 time to create 1 rle with new method : 0.7724449634552002 time for calcul the mask position with numpy : 0.028949499130249023 nb_pixel_total : 16004 time to create 1 rle with old method : 0.017980098724365234 time for calcul the mask position with numpy : 0.029219865798950195 nb_pixel_total : 62958 time to create 1 rle with old method : 0.07362222671508789 time for calcul the mask position with numpy : 0.02874469757080078 nb_pixel_total : 17551 time to create 1 rle with old method : 0.019879579544067383 time for calcul the mask position with numpy : 0.028852224349975586 nb_pixel_total : 39254 time to create 1 rle with old method : 0.04448056221008301 time for calcul the mask position with numpy : 0.02884840965270996 nb_pixel_total : 20696 time to create 1 rle with old method : 0.023348093032836914 time for calcul the mask position with numpy : 0.029099702835083008 nb_pixel_total : 7398 time to create 1 rle with old method : 0.008406400680541992 time for calcul the mask position with numpy : 0.031673431396484375 nb_pixel_total : 30039 time to create 1 rle with old method : 0.03440117835998535 time for calcul the mask position with numpy : 0.030502796173095703 nb_pixel_total : 69885 time to create 1 rle with old method : 0.07819986343383789 time for calcul the mask position with numpy : 0.028696298599243164 nb_pixel_total : 14140 time to create 1 rle with old method : 0.015447616577148438 time for calcul the mask position with numpy : 0.028566360473632812 nb_pixel_total : 15265 time to create 1 rle with old method : 0.017136573791503906 time for calcul the mask position with numpy : 0.02894902229309082 nb_pixel_total : 14237 time to create 1 rle with old method : 0.016033411026000977 time for calcul the mask position with numpy : 0.03200244903564453 nb_pixel_total : 23755 time to create 1 rle with old method : 0.030828475952148438 time for calcul the mask position with numpy : 0.028162240982055664 nb_pixel_total : 40663 time to create 1 rle with old method : 0.0458221435546875 time for calcul the mask position with numpy : 0.028188228607177734 nb_pixel_total : 15399 time to create 1 rle with old method : 0.017111539840698242 time for calcul the mask position with numpy : 0.028527021408081055 nb_pixel_total : 19951 time to create 1 rle with old method : 0.0222017765045166 time for calcul the mask position with numpy : 0.03015279769897461 nb_pixel_total : 189824 time to create 1 rle with new method : 0.6271319389343262 time for calcul the mask position with numpy : 0.03292536735534668 nb_pixel_total : 13908 time to create 1 rle with old method : 0.017046689987182617 time for calcul the mask position with numpy : 0.028952836990356445 nb_pixel_total : 6873 time to create 1 rle with old method : 0.007699489593505859 time for calcul the mask position with numpy : 0.02938699722290039 nb_pixel_total : 12830 time to create 1 rle with old method : 0.015835285186767578 time for calcul the mask position with numpy : 0.02888655662536621 nb_pixel_total : 53108 time to create 1 rle with old method : 0.060613155364990234 time for calcul the mask position with numpy : 0.029093027114868164 nb_pixel_total : 22566 time to create 1 rle with old method : 0.025040864944458008 time for calcul the mask position with numpy : 0.029175996780395508 nb_pixel_total : 21940 time to create 1 rle with old method : 0.024578571319580078 time for calcul the mask position with numpy : 0.028985977172851562 nb_pixel_total : 15483 time to create 1 rle with old method : 0.018117189407348633 time for calcul the mask position with numpy : 0.02958202362060547 nb_pixel_total : 12063 time to create 1 rle with old method : 0.013317584991455078 time for calcul the mask position with numpy : 0.029368162155151367 nb_pixel_total : 8737 time to create 1 rle with old method : 0.009673118591308594 time for calcul the mask position with numpy : 0.028980731964111328 nb_pixel_total : 24125 time to create 1 rle with old method : 0.02693796157836914 time for calcul the mask position with numpy : 0.028310537338256836 nb_pixel_total : 12461 time to create 1 rle with old method : 0.013796091079711914 time for calcul the mask position with numpy : 0.029451847076416016 nb_pixel_total : 34878 time to create 1 rle with old method : 0.04072833061218262 time for calcul the mask position with numpy : 0.03328371047973633 nb_pixel_total : 84503 time to create 1 rle with old method : 0.10996699333190918 time for calcul the mask position with numpy : 0.02825021743774414 nb_pixel_total : 11270 time to create 1 rle with old method : 0.012493133544921875 time for calcul the mask position with numpy : 0.02919793128967285 nb_pixel_total : 50459 time to create 1 rle with old method : 0.05697917938232422 time for calcul the mask position with numpy : 0.027948856353759766 nb_pixel_total : 11823 time to create 1 rle with old method : 0.012996435165405273 time for calcul the mask position with numpy : 0.027474403381347656 nb_pixel_total : 61781 time to create 1 rle with old method : 0.0680241584777832 time for calcul the mask position with numpy : 0.028371810913085938 nb_pixel_total : 33465 time to create 1 rle with old method : 0.03673720359802246 time for calcul the mask position with numpy : 0.028615713119506836 nb_pixel_total : 11394 time to create 1 rle with old method : 0.01238703727722168 time for calcul the mask position with numpy : 0.02823615074157715 nb_pixel_total : 12261 time to create 1 rle with old method : 0.013254642486572266 time for calcul the mask position with numpy : 0.027233123779296875 nb_pixel_total : 3886 time to create 1 rle with old method : 0.00409388542175293 create new chi : 4.179754734039307 time to delete rle : 0.0026662349700927734 batch 1 Loaded 75 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 17763 TO DO : save crop sub photo not yet done ! save time : 1.1239476203918457 nb_obj : 33 nb_hashtags : 4 time to prepare the origin masks : 3.6246325969696045 time for calcul the mask position with numpy : 0.8708033561706543 nb_pixel_total : 6109539 time to create 1 rle with new method : 0.9238910675048828 time for calcul the mask position with numpy : 0.028554201126098633 nb_pixel_total : 16934 time to create 1 rle with old method : 0.018314599990844727 time for calcul the mask position with numpy : 0.027812480926513672 nb_pixel_total : 4650 time to create 1 rle with old method : 0.005321502685546875 time for calcul the mask position with numpy : 0.028111934661865234 nb_pixel_total : 39198 time to create 1 rle with old method : 0.043239593505859375 time for calcul the mask position with numpy : 0.02880692481994629 nb_pixel_total : 24420 time to create 1 rle with old method : 0.027266979217529297 time for calcul the mask position with numpy : 0.02831244468688965 nb_pixel_total : 9193 time to create 1 rle with old method : 0.009936094284057617 time for calcul the mask position with numpy : 0.027873754501342773 nb_pixel_total : 20496 time to create 1 rle with old method : 0.022505760192871094 time for calcul the mask position with numpy : 0.028255462646484375 nb_pixel_total : 25165 time to create 1 rle with old method : 0.027376174926757812 time for calcul the mask position with numpy : 0.028766155242919922 nb_pixel_total : 7753 time to create 1 rle with old method : 0.009604454040527344 time for calcul the mask position with numpy : 0.028560161590576172 nb_pixel_total : 55024 time to create 1 rle with old method : 0.062181949615478516 time for calcul the mask position with numpy : 0.028768301010131836 nb_pixel_total : 22126 time to create 1 rle with old method : 0.024448871612548828 time for calcul the mask position with numpy : 0.02780461311340332 nb_pixel_total : 42545 time to create 1 rle with old method : 0.046863555908203125 time for calcul the mask position with numpy : 0.028603792190551758 nb_pixel_total : 18770 time to create 1 rle with old method : 0.02057051658630371 time for calcul the mask position with numpy : 0.028794050216674805 nb_pixel_total : 22591 time to create 1 rle with old method : 0.02528214454650879 time for calcul the mask position with numpy : 0.029110193252563477 nb_pixel_total : 26861 time to create 1 rle with old method : 0.03408360481262207 time for calcul the mask position with numpy : 0.02993917465209961 nb_pixel_total : 18915 time to create 1 rle with old method : 0.02078080177307129 time for calcul the mask position with numpy : 0.028446674346923828 nb_pixel_total : 10583 time to create 1 rle with old method : 0.01250004768371582 time for calcul the mask position with numpy : 0.03082871437072754 nb_pixel_total : 75550 time to create 1 rle with old method : 0.08722376823425293 time for calcul the mask position with numpy : 0.03379988670349121 nb_pixel_total : 41549 time to create 1 rle with old method : 0.0661780834197998 time for calcul the mask position with numpy : 0.032341718673706055 nb_pixel_total : 14635 time to create 1 rle with old method : 0.051172494888305664 time for calcul the mask position with numpy : 0.055443525314331055 nb_pixel_total : 22673 time to create 1 rle with old method : 0.045099496841430664 time for calcul the mask position with numpy : 0.0430755615234375 nb_pixel_total : 12704 time to create 1 rle with old method : 0.014525890350341797 time for calcul the mask position with numpy : 0.029452085494995117 nb_pixel_total : 12835 time to create 1 rle with old method : 0.014824628829956055 time for calcul the mask position with numpy : 0.03151750564575195 nb_pixel_total : 36298 time to create 1 rle with old method : 0.04642963409423828 time for calcul the mask position with numpy : 0.034906625747680664 nb_pixel_total : 57850 time to create 1 rle with old method : 0.09971237182617188 time for calcul the mask position with numpy : 0.03296208381652832 nb_pixel_total : 129875 time to create 1 rle with old method : 0.1817185878753662 time for calcul the mask position with numpy : 0.03743433952331543 nb_pixel_total : 14514 time to create 1 rle with old method : 0.017435073852539062 time for calcul the mask position with numpy : 0.029684066772460938 nb_pixel_total : 43391 time to create 1 rle with old method : 0.05135774612426758 time for calcul the mask position with numpy : 0.029716014862060547 nb_pixel_total : 42356 time to create 1 rle with old method : 0.04995918273925781 time for calcul the mask position with numpy : 0.02976059913635254 nb_pixel_total : 13374 time to create 1 rle with old method : 0.019150733947753906 time for calcul the mask position with numpy : 0.029573440551757812 nb_pixel_total : 14832 time to create 1 rle with old method : 0.016879796981811523 time for calcul the mask position with numpy : 0.031010866165161133 nb_pixel_total : 8671 time to create 1 rle with old method : 0.009765386581420898 time for calcul the mask position with numpy : 0.029471158981323242 nb_pixel_total : 6607 time to create 1 rle with old method : 0.007475137710571289 time for calcul the mask position with numpy : 0.029713869094848633 nb_pixel_total : 27763 time to create 1 rle with old method : 0.03247570991516113 create new chi : 4.078469514846802 time to delete rle : 0.0029878616333007812 batch 1 Loaded 67 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 16582 TO DO : save crop sub photo not yet done ! save time : 0.9983799457550049 nb_obj : 45 nb_hashtags : 4 time to prepare the origin masks : 4.08935546875 time for calcul the mask position with numpy : 0.833014726638794 nb_pixel_total : 5871106 time to create 1 rle with new method : 0.784538745880127 time for calcul the mask position with numpy : 0.02915477752685547 nb_pixel_total : 13953 time to create 1 rle with old method : 0.0166776180267334 time for calcul the mask position with numpy : 0.0298919677734375 nb_pixel_total : 10494 time to create 1 rle with old method : 0.012796640396118164 time for calcul the mask position with numpy : 0.029630661010742188 nb_pixel_total : 7194 time to create 1 rle with old method : 0.00987863540649414 time for calcul the mask position with numpy : 0.031646013259887695 nb_pixel_total : 11896 time to create 1 rle with old method : 0.013373136520385742 time for calcul the mask position with numpy : 0.03216385841369629 nb_pixel_total : 15786 time to create 1 rle with old method : 0.020921707153320312 time for calcul the mask position with numpy : 0.030255556106567383 nb_pixel_total : 46584 time to create 1 rle with old method : 0.059757232666015625 time for calcul the mask position with numpy : 0.030971765518188477 nb_pixel_total : 106132 time to create 1 rle with old method : 0.12344551086425781 time for calcul the mask position with numpy : 0.031419992446899414 nb_pixel_total : 14054 time to create 1 rle with old method : 0.016071081161499023 time for calcul the mask position with numpy : 0.029047489166259766 nb_pixel_total : 16827 time to create 1 rle with old method : 0.01900458335876465 time for calcul the mask position with numpy : 0.029385089874267578 nb_pixel_total : 14320 time to create 1 rle with old method : 0.0162503719329834 time for calcul the mask position with numpy : 0.02947711944580078 nb_pixel_total : 9179 time to create 1 rle with old method : 0.010837316513061523 time for calcul the mask position with numpy : 0.02969837188720703 nb_pixel_total : 20805 time to create 1 rle with old method : 0.024004459381103516 time for calcul the mask position with numpy : 0.029356002807617188 nb_pixel_total : 14655 time to create 1 rle with old method : 0.017146587371826172 time for calcul the mask position with numpy : 0.03346848487854004 nb_pixel_total : 16191 time to create 1 rle with old method : 0.01899433135986328 time for calcul the mask position with numpy : 0.029773950576782227 nb_pixel_total : 40934 time to create 1 rle with old method : 0.060271263122558594 time for calcul the mask position with numpy : 0.034414052963256836 nb_pixel_total : 56785 time to create 1 rle with old method : 0.06807208061218262 time for calcul the mask position with numpy : 0.03070807456970215 nb_pixel_total : 17189 time to create 1 rle with old method : 0.02002692222595215 time for calcul the mask position with numpy : 0.029195547103881836 nb_pixel_total : 12866 time to create 1 rle with old method : 0.014385223388671875 time for calcul the mask position with numpy : 0.03182196617126465 nb_pixel_total : 24439 time to create 1 rle with old method : 0.03926992416381836 time for calcul the mask position with numpy : 0.032317399978637695 nb_pixel_total : 29867 time to create 1 rle with old method : 0.0333404541015625 time for calcul the mask position with numpy : 0.029242992401123047 nb_pixel_total : 9433 time to create 1 rle with old method : 0.010779619216918945 time for calcul the mask position with numpy : 0.029158830642700195 nb_pixel_total : 4285 time to create 1 rle with old method : 0.004906892776489258 time for calcul the mask position with numpy : 0.0303652286529541 nb_pixel_total : 22167 time to create 1 rle with old method : 0.025104284286499023 time for calcul the mask position with numpy : 0.029062509536743164 nb_pixel_total : 6236 time to create 1 rle with old method : 0.007035017013549805 time for calcul the mask position with numpy : 0.028612613677978516 nb_pixel_total : 9634 time to create 1 rle with old method : 0.010957717895507812 time for calcul the mask position with numpy : 0.03119826316833496 nb_pixel_total : 21409 time to create 1 rle with old method : 0.02663564682006836 time for calcul the mask position with numpy : 0.029399633407592773 nb_pixel_total : 34102 time to create 1 rle with old method : 0.0384526252746582 time for calcul the mask position with numpy : 0.029149293899536133 nb_pixel_total : 17981 time to create 1 rle with old method : 0.020477771759033203 time for calcul the mask position with numpy : 0.028829574584960938 nb_pixel_total : 14626 time to create 1 rle with old method : 0.016558170318603516 time for calcul the mask position with numpy : 0.02958059310913086 nb_pixel_total : 37166 time to create 1 rle with old method : 0.044904232025146484 time for calcul the mask position with numpy : 0.030168771743774414 nb_pixel_total : 47054 time to create 1 rle with old method : 0.052916765213012695 time for calcul the mask position with numpy : 0.028664827346801758 nb_pixel_total : 50743 time to create 1 rle with old method : 0.056824684143066406 time for calcul the mask position with numpy : 0.028650760650634766 nb_pixel_total : 23478 time to create 1 rle with old method : 0.026615381240844727 time for calcul the mask position with numpy : 0.02914881706237793 nb_pixel_total : 53649 time to create 1 rle with old method : 0.060622453689575195 time for calcul the mask position with numpy : 0.030640125274658203 nb_pixel_total : 18439 time to create 1 rle with old method : 0.022152185440063477 time for calcul the mask position with numpy : 0.029175758361816406 nb_pixel_total : 50742 time to create 1 rle with old method : 0.05658149719238281 time for calcul the mask position with numpy : 0.029009580612182617 nb_pixel_total : 41598 time to create 1 rle with old method : 0.04710078239440918 time for calcul the mask position with numpy : 0.029123544692993164 nb_pixel_total : 14158 time to create 1 rle with old method : 0.016292572021484375 time for calcul the mask position with numpy : 0.02929067611694336 nb_pixel_total : 26982 time to create 1 rle with old method : 0.03357052803039551 time for calcul the mask position with numpy : 0.029010534286499023 nb_pixel_total : 30977 time to create 1 rle with old method : 0.03486990928649902 time for calcul the mask position with numpy : 0.031087398529052734 nb_pixel_total : 34775 time to create 1 rle with old method : 0.039130210876464844 time for calcul the mask position with numpy : 0.029239892959594727 nb_pixel_total : 54813 time to create 1 rle with old method : 0.06146883964538574 time for calcul the mask position with numpy : 0.0289456844329834 nb_pixel_total : 17094 time to create 1 rle with old method : 0.019173860549926758 time for calcul the mask position with numpy : 0.02883172035217285 nb_pixel_total : 24606 time to create 1 rle with old method : 0.027277231216430664 time for calcul the mask position with numpy : 0.028635263442993164 nb_pixel_total : 12837 time to create 1 rle with old method : 0.01403045654296875 create new chi : 4.39462423324585 time to delete rle : 0.003537416458129883 batch 1 Loaded 91 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 21064 TO DO : save crop sub photo not yet done ! save time : 1.2227280139923096 nb_obj : 33 nb_hashtags : 4 time to prepare the origin masks : 3.9718523025512695 time for calcul the mask position with numpy : 0.45618319511413574 nb_pixel_total : 5606047 time to create 1 rle with new method : 1.014488697052002 time for calcul the mask position with numpy : 0.028209686279296875 nb_pixel_total : 39760 time to create 1 rle with old method : 0.042533159255981445 time for calcul the mask position with numpy : 0.027368783950805664 nb_pixel_total : 63502 time to create 1 rle with old method : 0.06901836395263672 time for calcul the mask position with numpy : 0.029847383499145508 nb_pixel_total : 17756 time to create 1 rle with old method : 0.028705835342407227 time for calcul the mask position with numpy : 0.032900094985961914 nb_pixel_total : 24379 time to create 1 rle with old method : 0.028954029083251953 time for calcul the mask position with numpy : 0.03156447410583496 nb_pixel_total : 15877 time to create 1 rle with old method : 0.018843889236450195 time for calcul the mask position with numpy : 0.029317140579223633 nb_pixel_total : 28323 time to create 1 rle with old method : 0.03166079521179199 time for calcul the mask position with numpy : 0.028962135314941406 nb_pixel_total : 12685 time to create 1 rle with old method : 0.014323949813842773 time for calcul the mask position with numpy : 0.028531789779663086 nb_pixel_total : 18296 time to create 1 rle with old method : 0.020568370819091797 time for calcul the mask position with numpy : 0.02875232696533203 nb_pixel_total : 22021 time to create 1 rle with old method : 0.024587631225585938 time for calcul the mask position with numpy : 0.0288999080657959 nb_pixel_total : 14632 time to create 1 rle with old method : 0.016617298126220703 time for calcul the mask position with numpy : 0.028909683227539062 nb_pixel_total : 36803 time to create 1 rle with old method : 0.0410771369934082 time for calcul the mask position with numpy : 0.02878117561340332 nb_pixel_total : 49702 time to create 1 rle with old method : 0.05439877510070801 time for calcul the mask position with numpy : 0.02861952781677246 nb_pixel_total : 37908 time to create 1 rle with old method : 0.042546749114990234 time for calcul the mask position with numpy : 0.029432296752929688 nb_pixel_total : 9562 time to create 1 rle with old method : 0.010818004608154297 time for calcul the mask position with numpy : 0.029944181442260742 nb_pixel_total : 15925 time to create 1 rle with old method : 0.01803112030029297 time for calcul the mask position with numpy : 0.028347015380859375 nb_pixel_total : 14611 time to create 1 rle with old method : 0.01604461669921875 time for calcul the mask position with numpy : 0.028171539306640625 nb_pixel_total : 85335 time to create 1 rle with old method : 0.09313344955444336 time for calcul the mask position with numpy : 0.027643918991088867 nb_pixel_total : 11728 time to create 1 rle with old method : 0.012909173965454102 time for calcul the mask position with numpy : 0.027683258056640625 nb_pixel_total : 27972 time to create 1 rle with old method : 0.03131914138793945 time for calcul the mask position with numpy : 0.028648853302001953 nb_pixel_total : 24501 time to create 1 rle with old method : 0.027087926864624023 time for calcul the mask position with numpy : 0.027963638305664062 nb_pixel_total : 14194 time to create 1 rle with old method : 0.01573920249938965 time for calcul the mask position with numpy : 0.027992725372314453 nb_pixel_total : 13410 time to create 1 rle with old method : 0.014977693557739258 time for calcul the mask position with numpy : 0.028492450714111328 nb_pixel_total : 83325 time to create 1 rle with old method : 0.11817312240600586 time for calcul the mask position with numpy : 0.029440879821777344 nb_pixel_total : 11399 time to create 1 rle with old method : 0.014629364013671875 time for calcul the mask position with numpy : 0.028876543045043945 nb_pixel_total : 7964 time to create 1 rle with old method : 0.009132862091064453 time for calcul the mask position with numpy : 0.029560089111328125 nb_pixel_total : 335617 time to create 1 rle with new method : 0.6069998741149902 time for calcul the mask position with numpy : 0.028809547424316406 nb_pixel_total : 166013 time to create 1 rle with new method : 0.7745389938354492 time for calcul the mask position with numpy : 0.02907395362854004 nb_pixel_total : 28713 time to create 1 rle with old method : 0.03204083442687988 time for calcul the mask position with numpy : 0.033263206481933594 nb_pixel_total : 17896 time to create 1 rle with old method : 0.02084517478942871 time for calcul the mask position with numpy : 0.030019760131835938 nb_pixel_total : 165401 time to create 1 rle with new method : 0.6350133419036865 time for calcul the mask position with numpy : 0.028626203536987305 nb_pixel_total : 17762 time to create 1 rle with old method : 0.01984858512878418 time for calcul the mask position with numpy : 0.028658628463745117 nb_pixel_total : 5417 time to create 1 rle with old method : 0.006196022033691406 time for calcul the mask position with numpy : 0.028293371200561523 nb_pixel_total : 5804 time to create 1 rle with old method : 0.006574869155883789 create new chi : 5.448094606399536 time to delete rle : 0.002793550491333008 batch 1 Loaded 67 chid ids of type : 3594 ++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 18099 TO DO : save crop sub photo not yet done ! save time : 1.0516178607940674 nb_obj : 39 nb_hashtags : 4 time to prepare the origin masks : 4.3123109340667725 time for calcul the mask position with numpy : 0.39870786666870117 nb_pixel_total : 5038975 time to create 1 rle with new method : 0.4825763702392578 time for calcul the mask position with numpy : 0.029114246368408203 nb_pixel_total : 7816 time to create 1 rle with old method : 0.008969545364379883 time for calcul the mask position with numpy : 0.029010534286499023 nb_pixel_total : 24681 time to create 1 rle with old method : 0.027880430221557617 time for calcul the mask position with numpy : 0.02881479263305664 nb_pixel_total : 11436 time to create 1 rle with old method : 0.012974977493286133 time for calcul the mask position with numpy : 0.029846668243408203 nb_pixel_total : 115352 time to create 1 rle with old method : 0.1285254955291748 time for calcul the mask position with numpy : 0.029129505157470703 nb_pixel_total : 8693 time to create 1 rle with old method : 0.009974241256713867 time for calcul the mask position with numpy : 0.02893853187561035 nb_pixel_total : 2142 time to create 1 rle with old method : 0.0023746490478515625 time for calcul the mask position with numpy : 0.0286562442779541 nb_pixel_total : 39201 time to create 1 rle with old method : 0.043865203857421875 time for calcul the mask position with numpy : 0.028757810592651367 nb_pixel_total : 3583 time to create 1 rle with old method : 0.0040514469146728516 time for calcul the mask position with numpy : 0.03603649139404297 nb_pixel_total : 69733 time to create 1 rle with old method : 0.07796931266784668 time for calcul the mask position with numpy : 0.028690576553344727 nb_pixel_total : 151 time to create 1 rle with old method : 0.00020885467529296875 time for calcul the mask position with numpy : 0.028131961822509766 nb_pixel_total : 16646 time to create 1 rle with old method : 0.01826310157775879 time for calcul the mask position with numpy : 0.02871990203857422 nb_pixel_total : 26433 time to create 1 rle with old method : 0.042806386947631836 time for calcul the mask position with numpy : 0.03511643409729004 nb_pixel_total : 13219 time to create 1 rle with old method : 0.01610112190246582 time for calcul the mask position with numpy : 0.03220200538635254 nb_pixel_total : 850340 time to create 1 rle with new method : 0.500415563583374 time for calcul the mask position with numpy : 0.03232145309448242 nb_pixel_total : 16400 time to create 1 rle with old method : 0.025211811065673828 time for calcul the mask position with numpy : 0.029021263122558594 nb_pixel_total : 3258 time to create 1 rle with old method : 0.0037043094635009766 time for calcul the mask position with numpy : 0.029023408889770508 nb_pixel_total : 40977 time to create 1 rle with old method : 0.04600858688354492 time for calcul the mask position with numpy : 0.028311729431152344 nb_pixel_total : 15167 time to create 1 rle with old method : 0.0166323184967041 time for calcul the mask position with numpy : 0.028579235076904297 nb_pixel_total : 23910 time to create 1 rle with old method : 0.02667856216430664 time for calcul the mask position with numpy : 0.02860260009765625 nb_pixel_total : 29560 time to create 1 rle with old method : 0.032941579818725586 time for calcul the mask position with numpy : 0.028482913970947266 nb_pixel_total : 9922 time to create 1 rle with old method : 0.010762214660644531 time for calcul the mask position with numpy : 0.028098106384277344 nb_pixel_total : 9345 time to create 1 rle with old method : 0.009970664978027344 time for calcul the mask position with numpy : 0.027927398681640625 nb_pixel_total : 6473 time to create 1 rle with old method : 0.007334470748901367 time for calcul the mask position with numpy : 0.028933048248291016 nb_pixel_total : 103247 time to create 1 rle with old method : 0.11404824256896973 time for calcul the mask position with numpy : 0.028354406356811523 nb_pixel_total : 70512 time to create 1 rle with old method : 0.07856225967407227 time for calcul the mask position with numpy : 0.02917027473449707 nb_pixel_total : 77378 time to create 1 rle with old method : 0.09840250015258789 time for calcul the mask position with numpy : 0.033235788345336914 nb_pixel_total : 92239 time to create 1 rle with old method : 0.10230875015258789 time for calcul the mask position with numpy : 0.029072999954223633 nb_pixel_total : 25668 time to create 1 rle with old method : 0.028624534606933594 time for calcul the mask position with numpy : 0.028627872467041016 nb_pixel_total : 24372 time to create 1 rle with old method : 0.027065277099609375 time for calcul the mask position with numpy : 0.02855205535888672 nb_pixel_total : 10491 time to create 1 rle with old method : 0.011801958084106445 time for calcul the mask position with numpy : 0.028479576110839844 nb_pixel_total : 40016 time to create 1 rle with old method : 0.044306278228759766 time for calcul the mask position with numpy : 0.028423786163330078 nb_pixel_total : 14386 time to create 1 rle with old method : 0.01625514030456543 time for calcul the mask position with numpy : 0.02865457534790039 nb_pixel_total : 40249 time to create 1 rle with old method : 0.04528331756591797 time for calcul the mask position with numpy : 0.028588533401489258 nb_pixel_total : 51128 time to create 1 rle with old method : 0.055666208267211914 time for calcul the mask position with numpy : 0.02844381332397461 nb_pixel_total : 41677 time to create 1 rle with old method : 0.04612898826599121 time for calcul the mask position with numpy : 0.028383731842041016 nb_pixel_total : 22434 time to create 1 rle with old method : 0.024761199951171875 time for calcul the mask position with numpy : 0.028305530548095703 nb_pixel_total : 27191 time to create 1 rle with old method : 0.030286312103271484 time for calcul the mask position with numpy : 0.028451204299926758 nb_pixel_total : 16594 time to create 1 rle with old method : 0.018521547317504883 time for calcul the mask position with numpy : 0.028257369995117188 nb_pixel_total : 9245 time to create 1 rle with old method : 0.010292291641235352 create new chi : 3.9097726345062256 time to delete rle : 0.0030639171600341797 batch 1 Loaded 79 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 19766 TO DO : save crop sub photo not yet done ! save time : 1.1527447700500488 nb_obj : 45 nb_hashtags : 3 time to prepare the origin masks : 4.355880498886108 time for calcul the mask position with numpy : 0.7094566822052002 nb_pixel_total : 5205855 time to create 1 rle with new method : 0.6700348854064941 time for calcul the mask position with numpy : 0.029212474822998047 nb_pixel_total : 122186 time to create 1 rle with old method : 0.1373276710510254 time for calcul the mask position with numpy : 0.0290982723236084 nb_pixel_total : 9079 time to create 1 rle with old method : 0.010729312896728516 time for calcul the mask position with numpy : 0.03015303611755371 nb_pixel_total : 42168 time to create 1 rle with old method : 0.04857826232910156 time for calcul the mask position with numpy : 0.029215574264526367 nb_pixel_total : 14513 time to create 1 rle with old method : 0.01651620864868164 time for calcul the mask position with numpy : 0.029117107391357422 nb_pixel_total : 7412 time to create 1 rle with old method : 0.008536577224731445 time for calcul the mask position with numpy : 0.029011011123657227 nb_pixel_total : 10743 time to create 1 rle with old method : 0.012257099151611328 time for calcul the mask position with numpy : 0.028839111328125 nb_pixel_total : 18630 time to create 1 rle with old method : 0.02094578742980957 time for calcul the mask position with numpy : 0.02895832061767578 nb_pixel_total : 16361 time to create 1 rle with old method : 0.018538236618041992 time for calcul the mask position with numpy : 0.029035568237304688 nb_pixel_total : 139793 time to create 1 rle with old method : 0.15485739707946777 time for calcul the mask position with numpy : 0.031125307083129883 nb_pixel_total : 10541 time to create 1 rle with old method : 0.011732339859008789 time for calcul the mask position with numpy : 0.028764009475708008 nb_pixel_total : 35297 time to create 1 rle with old method : 0.041062355041503906 time for calcul the mask position with numpy : 0.03154921531677246 nb_pixel_total : 74828 time to create 1 rle with old method : 0.10874652862548828 time for calcul the mask position with numpy : 0.028941869735717773 nb_pixel_total : 15476 time to create 1 rle with old method : 0.019781112670898438 time for calcul the mask position with numpy : 0.03271627426147461 nb_pixel_total : 36653 time to create 1 rle with old method : 0.0534210205078125 time for calcul the mask position with numpy : 0.02918267250061035 nb_pixel_total : 2930 time to create 1 rle with old method : 0.003408670425415039 time for calcul the mask position with numpy : 0.028474092483520508 nb_pixel_total : 989 time to create 1 rle with old method : 0.0014045238494873047 time for calcul the mask position with numpy : 0.028340578079223633 nb_pixel_total : 75050 time to create 1 rle with old method : 0.08666825294494629 time for calcul the mask position with numpy : 0.02896595001220703 nb_pixel_total : 15080 time to create 1 rle with old method : 0.018236637115478516 time for calcul the mask position with numpy : 0.02904534339904785 nb_pixel_total : 111162 time to create 1 rle with old method : 0.12660741806030273 time for calcul the mask position with numpy : 0.028258323669433594 nb_pixel_total : 38378 time to create 1 rle with old method : 0.04269742965698242 time for calcul the mask position with numpy : 0.028900623321533203 nb_pixel_total : 65509 time to create 1 rle with old method : 0.07281255722045898 time for calcul the mask position with numpy : 0.03264141082763672 nb_pixel_total : 72949 time to create 1 rle with old method : 0.08365750312805176 time for calcul the mask position with numpy : 0.029207468032836914 nb_pixel_total : 52132 time to create 1 rle with old method : 0.05868792533874512 time for calcul the mask position with numpy : 0.029329538345336914 nb_pixel_total : 17213 time to create 1 rle with old method : 0.019659757614135742 time for calcul the mask position with numpy : 0.029428958892822266 nb_pixel_total : 105836 time to create 1 rle with old method : 0.12144255638122559 time for calcul the mask position with numpy : 0.029232263565063477 nb_pixel_total : 92093 time to create 1 rle with old method : 0.10305190086364746 time for calcul the mask position with numpy : 0.028767824172973633 nb_pixel_total : 15882 time to create 1 rle with old method : 0.017730712890625 time for calcul the mask position with numpy : 0.02900528907775879 nb_pixel_total : 32161 time to create 1 rle with old method : 0.05386233329772949 time for calcul the mask position with numpy : 0.042146921157836914 nb_pixel_total : 23111 time to create 1 rle with old method : 0.03230428695678711 time for calcul the mask position with numpy : 0.032936811447143555 nb_pixel_total : 7618 time to create 1 rle with old method : 0.012511491775512695 time for calcul the mask position with numpy : 0.03299522399902344 nb_pixel_total : 45749 time to create 1 rle with old method : 0.052108049392700195 time for calcul the mask position with numpy : 0.029095172882080078 nb_pixel_total : 9174 time to create 1 rle with old method : 0.01027369499206543 time for calcul the mask position with numpy : 0.02932286262512207 nb_pixel_total : 111653 time to create 1 rle with old method : 0.12425637245178223 time for calcul the mask position with numpy : 0.0290224552154541 nb_pixel_total : 7971 time to create 1 rle with old method : 0.009123802185058594 time for calcul the mask position with numpy : 0.02911972999572754 nb_pixel_total : 33277 time to create 1 rle with old method : 0.03792452812194824 time for calcul the mask position with numpy : 0.02979564666748047 nb_pixel_total : 3042 time to create 1 rle with old method : 0.004889488220214844 time for calcul the mask position with numpy : 0.03231215476989746 nb_pixel_total : 95456 time to create 1 rle with old method : 0.10869622230529785 time for calcul the mask position with numpy : 0.030053138732910156 nb_pixel_total : 61880 time to create 1 rle with old method : 0.07144975662231445 time for calcul the mask position with numpy : 0.03227686882019043 nb_pixel_total : 30946 time to create 1 rle with old method : 0.050607919692993164 time for calcul the mask position with numpy : 0.030690431594848633 nb_pixel_total : 36010 time to create 1 rle with old method : 0.04208970069885254 time for calcul the mask position with numpy : 0.02942657470703125 nb_pixel_total : 25220 time to create 1 rle with old method : 0.028497934341430664 time for calcul the mask position with numpy : 0.02935934066772461 nb_pixel_total : 17596 time to create 1 rle with old method : 0.020054340362548828 time for calcul the mask position with numpy : 0.02924489974975586 nb_pixel_total : 67093 time to create 1 rle with old method : 0.07655096054077148 time for calcul the mask position with numpy : 0.029575109481811523 nb_pixel_total : 13271 time to create 1 rle with old method : 0.01608419418334961 time for calcul the mask position with numpy : 0.029628992080688477 nb_pixel_total : 4274 time to create 1 rle with old method : 0.0060498714447021484 create new chi : 4.9440224170684814 time to delete rle : 0.005868673324584961 batch 1 Loaded 91 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 26035 TO DO : save crop sub photo not yet done ! save time : 1.5375287532806396 nb_obj : 9 nb_hashtags : 3 time to prepare the origin masks : 3.4295542240142822 time for calcul the mask position with numpy : 0.47412872314453125 nb_pixel_total : 5786168 time to create 1 rle with new method : 0.8219568729400635 time for calcul the mask position with numpy : 0.02098822593688965 nb_pixel_total : 16634 time to create 1 rle with old method : 0.018398046493530273 time for calcul the mask position with numpy : 0.021457910537719727 nb_pixel_total : 11493 time to create 1 rle with old method : 0.01305079460144043 time for calcul the mask position with numpy : 0.02286386489868164 nb_pixel_total : 261052 time to create 1 rle with new method : 0.5154514312744141 time for calcul the mask position with numpy : 0.021454572677612305 nb_pixel_total : 65956 time to create 1 rle with old method : 0.0725395679473877 time for calcul the mask position with numpy : 0.022724628448486328 nb_pixel_total : 227842 time to create 1 rle with new method : 0.6501142978668213 time for calcul the mask position with numpy : 0.02070164680480957 nb_pixel_total : 27232 time to create 1 rle with old method : 0.030414581298828125 time for calcul the mask position with numpy : 0.02150559425354004 nb_pixel_total : 40710 time to create 1 rle with old method : 0.04544568061828613 time for calcul the mask position with numpy : 0.025917768478393555 nb_pixel_total : 598698 time to create 1 rle with new method : 0.6342670917510986 time for calcul the mask position with numpy : 0.024322509765625 nb_pixel_total : 14455 time to create 1 rle with old method : 0.016186952590942383 create new chi : 3.5985138416290283 time to delete rle : 0.001905679702758789 batch 1 Loaded 19 chid ids of type : 3594 +++++++++++++++++++Number RLEs to save : 10669 TO DO : save crop sub photo not yet done ! save time : 0.6547391414642334 nb_obj : 19 nb_hashtags : 2 time to prepare the origin masks : 6.134903192520142 time for calcul the mask position with numpy : 0.6048154830932617 nb_pixel_total : 6552662 time to create 1 rle with new method : 0.9662032127380371 time for calcul the mask position with numpy : 0.03487563133239746 nb_pixel_total : 9802 time to create 1 rle with old method : 0.010812997817993164 time for calcul the mask position with numpy : 0.03409552574157715 nb_pixel_total : 27522 time to create 1 rle with old method : 0.03072214126586914 time for calcul the mask position with numpy : 0.03577780723571777 nb_pixel_total : 75930 time to create 1 rle with old method : 0.08498740196228027 time for calcul the mask position with numpy : 0.03351998329162598 nb_pixel_total : 10720 time to create 1 rle with old method : 0.011908292770385742 time for calcul the mask position with numpy : 0.03344464302062988 nb_pixel_total : 32296 time to create 1 rle with old method : 0.03489494323730469 time for calcul the mask position with numpy : 0.037305593490600586 nb_pixel_total : 8070 time to create 1 rle with old method : 0.009033918380737305 time for calcul the mask position with numpy : 0.03423571586608887 nb_pixel_total : 39611 time to create 1 rle with old method : 0.04399371147155762 time for calcul the mask position with numpy : 0.03235602378845215 nb_pixel_total : 39374 time to create 1 rle with old method : 0.043726205825805664 time for calcul the mask position with numpy : 0.03227567672729492 nb_pixel_total : 10076 time to create 1 rle with old method : 0.011340618133544922 time for calcul the mask position with numpy : 0.03390169143676758 nb_pixel_total : 41953 time to create 1 rle with old method : 0.046323299407958984 time for calcul the mask position with numpy : 0.03423953056335449 nb_pixel_total : 21258 time to create 1 rle with old method : 0.023965120315551758 time for calcul the mask position with numpy : 0.03750205039978027 nb_pixel_total : 3543 time to create 1 rle with old method : 0.004079103469848633 time for calcul the mask position with numpy : 0.03690290451049805 nb_pixel_total : 31139 time to create 1 rle with old method : 0.03380393981933594 time for calcul the mask position with numpy : 0.0333101749420166 nb_pixel_total : 15606 time to create 1 rle with old method : 0.017456769943237305 time for calcul the mask position with numpy : 0.034554481506347656 nb_pixel_total : 23250 time to create 1 rle with old method : 0.026243925094604492 time for calcul the mask position with numpy : 0.03428530693054199 nb_pixel_total : 8993 time to create 1 rle with old method : 0.010185003280639648 time for calcul the mask position with numpy : 0.0394437313079834 nb_pixel_total : 31036 time to create 1 rle with old method : 0.034969329833984375 time for calcul the mask position with numpy : 0.03938031196594238 nb_pixel_total : 14769 time to create 1 rle with old method : 0.02571725845336914 time for calcul the mask position with numpy : 0.0412142276763916 nb_pixel_total : 52630 time to create 1 rle with old method : 0.0617067813873291 create new chi : 2.8484020233154297 time to delete rle : 0.0017158985137939453 batch 1 Loaded 39 chid ids of type : 3594 ++++++++++++++++++++++++++++Number RLEs to save : 10583 TO DO : save crop sub photo not yet done ! save time : 0.7003421783447266 nb_obj : 14 nb_hashtags : 3 time to prepare the origin masks : 5.714086294174194 time for calcul the mask position with numpy : 0.4835350513458252 nb_pixel_total : 6672530 time to create 1 rle with new method : 0.6630415916442871 time for calcul the mask position with numpy : 0.03563499450683594 nb_pixel_total : 49226 time to create 1 rle with old method : 0.05504751205444336 time for calcul the mask position with numpy : 0.03474020957946777 nb_pixel_total : 8379 time to create 1 rle with old method : 0.009510040283203125 time for calcul the mask position with numpy : 0.02753281593322754 nb_pixel_total : 6415 time to create 1 rle with old method : 0.007318973541259766 time for calcul the mask position with numpy : 0.02174687385559082 nb_pixel_total : 25893 time to create 1 rle with old method : 0.029327392578125 time for calcul the mask position with numpy : 0.02511119842529297 nb_pixel_total : 38625 time to create 1 rle with old method : 0.04348182678222656 time for calcul the mask position with numpy : 0.021497726440429688 nb_pixel_total : 13663 time to create 1 rle with old method : 0.01597738265991211 time for calcul the mask position with numpy : 0.023241758346557617 nb_pixel_total : 16338 time to create 1 rle with old method : 0.018352270126342773 time for calcul the mask position with numpy : 0.021662473678588867 nb_pixel_total : 12850 time to create 1 rle with old method : 0.01466989517211914 time for calcul the mask position with numpy : 0.021566152572631836 nb_pixel_total : 36642 time to create 1 rle with old method : 0.04149770736694336 time for calcul the mask position with numpy : 0.021199941635131836 nb_pixel_total : 16870 time to create 1 rle with old method : 0.01910090446472168 time for calcul the mask position with numpy : 0.022022724151611328 nb_pixel_total : 10157 time to create 1 rle with old method : 0.011521100997924805 time for calcul the mask position with numpy : 0.021532058715820312 nb_pixel_total : 16672 time to create 1 rle with old method : 0.018823623657226562 time for calcul the mask position with numpy : 0.020624160766601562 nb_pixel_total : 34068 time to create 1 rle with old method : 0.0381314754486084 time for calcul the mask position with numpy : 0.02257704734802246 nb_pixel_total : 91912 time to create 1 rle with old method : 0.10301518440246582 create new chi : 1.9545447826385498 time to delete rle : 0.002424478530883789 batch 1 Loaded 29 chid ids of type : 3594 +++++++++++++++Number RLEs to save : 8252 TO DO : save crop sub photo not yet done ! save time : 0.5825037956237793 nb_obj : 42 nb_hashtags : 3 time to prepare the origin masks : 4.461451053619385 time for calcul the mask position with numpy : 0.40294599533081055 nb_pixel_total : 5291393 time to create 1 rle with new method : 0.7792251110076904 time for calcul the mask position with numpy : 0.030809640884399414 nb_pixel_total : 55710 time to create 1 rle with old method : 0.07062840461730957 time for calcul the mask position with numpy : 0.028588294982910156 nb_pixel_total : 8523 time to create 1 rle with old method : 0.00972437858581543 time for calcul the mask position with numpy : 0.029311656951904297 nb_pixel_total : 6901 time to create 1 rle with old method : 0.008191347122192383 time for calcul the mask position with numpy : 0.030098438262939453 nb_pixel_total : 11766 time to create 1 rle with old method : 0.016466856002807617 time for calcul the mask position with numpy : 0.029413223266601562 nb_pixel_total : 23760 time to create 1 rle with old method : 0.02687978744506836 time for calcul the mask position with numpy : 0.02947258949279785 nb_pixel_total : 25509 time to create 1 rle with old method : 0.03198504447937012 time for calcul the mask position with numpy : 0.029213666915893555 nb_pixel_total : 10929 time to create 1 rle with old method : 0.012363910675048828 time for calcul the mask position with numpy : 0.02964639663696289 nb_pixel_total : 16205 time to create 1 rle with old method : 0.019530057907104492 time for calcul the mask position with numpy : 0.02933955192565918 nb_pixel_total : 26161 time to create 1 rle with old method : 0.02973628044128418 time for calcul the mask position with numpy : 0.029154300689697266 nb_pixel_total : 31232 time to create 1 rle with old method : 0.03610873222351074 time for calcul the mask position with numpy : 0.02826833724975586 nb_pixel_total : 20587 time to create 1 rle with old method : 0.022888898849487305 time for calcul the mask position with numpy : 0.027820110321044922 nb_pixel_total : 22315 time to create 1 rle with old method : 0.025115489959716797 time for calcul the mask position with numpy : 0.02813124656677246 nb_pixel_total : 37963 time to create 1 rle with old method : 0.043302297592163086 time for calcul the mask position with numpy : 0.02836751937866211 nb_pixel_total : 26811 time to create 1 rle with old method : 0.03084278106689453 time for calcul the mask position with numpy : 0.030849456787109375 nb_pixel_total : 88385 time to create 1 rle with old method : 0.11242485046386719 time for calcul the mask position with numpy : 0.03159618377685547 nb_pixel_total : 326453 time to create 1 rle with new method : 0.6949872970581055 time for calcul the mask position with numpy : 0.029166221618652344 nb_pixel_total : 85553 time to create 1 rle with old method : 0.0986485481262207 time for calcul the mask position with numpy : 0.02813410758972168 nb_pixel_total : 19693 time to create 1 rle with old method : 0.02208995819091797 time for calcul the mask position with numpy : 0.031110048294067383 nb_pixel_total : 380473 time to create 1 rle with new method : 0.5142550468444824 time for calcul the mask position with numpy : 0.028577804565429688 nb_pixel_total : 34970 time to create 1 rle with old method : 0.04270291328430176 time for calcul the mask position with numpy : 0.03301835060119629 nb_pixel_total : 22023 time to create 1 rle with old method : 0.035785675048828125 time for calcul the mask position with numpy : 0.029404163360595703 nb_pixel_total : 30894 time to create 1 rle with old method : 0.03389596939086914 time for calcul the mask position with numpy : 0.028315305709838867 nb_pixel_total : 14678 time to create 1 rle with old method : 0.016514062881469727 time for calcul the mask position with numpy : 0.02824234962463379 nb_pixel_total : 7157 time to create 1 rle with old method : 0.008003950119018555 time for calcul the mask position with numpy : 0.028260469436645508 nb_pixel_total : 9979 time to create 1 rle with old method : 0.011211872100830078 time for calcul the mask position with numpy : 0.028478145599365234 nb_pixel_total : 25268 time to create 1 rle with old method : 0.02863311767578125 time for calcul the mask position with numpy : 0.028586387634277344 nb_pixel_total : 71073 time to create 1 rle with old method : 0.07955551147460938 time for calcul the mask position with numpy : 0.028191328048706055 nb_pixel_total : 14212 time to create 1 rle with old method : 0.016175031661987305 time for calcul the mask position with numpy : 0.029956579208374023 nb_pixel_total : 36409 time to create 1 rle with old method : 0.04276728630065918 time for calcul the mask position with numpy : 0.027930021286010742 nb_pixel_total : 18882 time to create 1 rle with old method : 0.020087480545043945 time for calcul the mask position with numpy : 0.027817249298095703 nb_pixel_total : 63905 time to create 1 rle with old method : 0.07051277160644531 time for calcul the mask position with numpy : 0.02745652198791504 nb_pixel_total : 20408 time to create 1 rle with old method : 0.021867990493774414 time for calcul the mask position with numpy : 0.026712894439697266 nb_pixel_total : 10303 time to create 1 rle with old method : 0.011057138442993164 time for calcul the mask position with numpy : 0.027489662170410156 nb_pixel_total : 24328 time to create 1 rle with old method : 0.02778792381286621 time for calcul the mask position with numpy : 0.029298067092895508 nb_pixel_total : 12597 time to create 1 rle with old method : 0.018238067626953125 time for calcul the mask position with numpy : 0.03291177749633789 nb_pixel_total : 32420 time to create 1 rle with old method : 0.04605746269226074 time for calcul the mask position with numpy : 0.028230667114257812 nb_pixel_total : 10079 time to create 1 rle with old method : 0.014090538024902344 time for calcul the mask position with numpy : 0.040036916732788086 nb_pixel_total : 5181 time to create 1 rle with old method : 0.009469032287597656 time for calcul the mask position with numpy : 0.040435075759887695 nb_pixel_total : 26475 time to create 1 rle with old method : 0.029468536376953125 time for calcul the mask position with numpy : 0.028932809829711914 nb_pixel_total : 21274 time to create 1 rle with old method : 0.024045228958129883 time for calcul the mask position with numpy : 0.028624296188354492 nb_pixel_total : 14689 time to create 1 rle with old method : 0.016344547271728516 time for calcul the mask position with numpy : 0.028365135192871094 nb_pixel_total : 6714 time to create 1 rle with old method : 0.007520437240600586 create new chi : 4.972658157348633 time to delete rle : 0.00567173957824707 batch 1 Loaded 85 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 22443 TO DO : save crop sub photo not yet done ! save time : 1.3199219703674316 map_output_result : {1350741936: (0.0, 'Should be the crop_list due to order', 0), 1350741933: (0.0, 'Should be the crop_list due to order', 0), 1350741771: (0.0, 'Should be the crop_list due to order', 0), 1350741769: (0.0, 'Should be the crop_list due to order', 0), 1350741659: (0.0, 'Should be the crop_list due to order', 0), 1350741627: (0.0, 'Should be the crop_list due to order', 0), 1350741601: (0.0, 'Should be the crop_list due to order', 0), 1350741579: (0.0, 'Should be the crop_list due to order', 0), 1350741267: (0.0, 'Should be the crop_list due to order', 0), 1350741217: (0.0, 'Should be the crop_list due to order', 0), 1350741215: (0.0, 'Should be the crop_list due to order', 0), 1350741212: (0.0, 'Should be the crop_list due to order', 0), 1350738338: (0.0, 'Should be the crop_list due to order', 0), 1350738296: (0.0, 'Should be the crop_list due to order', 0), 1350737578: (0.0, 'Should be the crop_list due to order', 0), 1350737511: (0.0, 'Should be the crop_list due to order', 0), 1350737419: (0.0, 'Should be the crop_list due to order', 0), 1350737410: (0.0, 'Should be the crop_list due to order', 0), 1350737230: (0.0, 'Should be the crop_list due to order', 0), 1350737086: (0.0, 'Should be the crop_list due to order', 0), 1350736919: (0.0, 'Should be the crop_list due to order', 0), 1350736896: (0.0, 'Should be the crop_list due to order', 0), 1350736747: (0.0, 'Should be the crop_list due to order', 0), 1350736614: (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 [1350741936, 1350741933, 1350741771, 1350741769, 1350741659, 1350741627, 1350741601, 1350741579, 1350741267, 1350741217, 1350741215, 1350741212, 1350738338, 1350738296, 1350737578, 1350737511, 1350737419, 1350737410, 1350737230, 1350737086, 1350736919, 1350736896, 1350736747, 1350736614] Looping around the photos to save general results len do output : 24 /1350741936.Didn't retrieve data . /1350741933.Didn't retrieve data . /1350741771.Didn't retrieve data . /1350741769.Didn't retrieve data . /1350741659.Didn't retrieve data . /1350741627.Didn't retrieve data . /1350741601.Didn't retrieve data . /1350741579.Didn't retrieve data . /1350741267.Didn't retrieve data . /1350741217.Didn't retrieve data . /1350741215.Didn't retrieve data . /1350741212.Didn't retrieve data . /1350738338.Didn't retrieve data . /1350738296.Didn't retrieve data . /1350737578.Didn't retrieve data . /1350737511.Didn't retrieve data . /1350737419.Didn't retrieve data . /1350737410.Didn't retrieve data . /1350737230.Didn't retrieve data . /1350737086.Didn't retrieve data . /1350736919.Didn't retrieve data . /1350736896.Didn't retrieve data . /1350736747.Didn't retrieve data . /1350736614.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, '2734295') ('3318', '22161073', '1350741936', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741933', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741771', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741769', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741659', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741627', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741601', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741579', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741267', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741217', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741215', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741212', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350738338', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350738296', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350737578', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350737511', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350737419', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350737410', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350737230', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350737086', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350736919', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350736896', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350736747', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350736614', None, None, None, None, None, '2734295') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 72 time used for this insertion : 0.013901710510253906 save_final save missing photos in datou_result : time spend for datou_step_exec : 240.34569716453552 time spend to save output : 0.014666318893432617 total time spend for step 3 : 240.36036348342896 step4:ventilate_hashtags_in_portfolio Wed Apr 9 12:49:44 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 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 : 22161073 get user id for portfolio 22161073 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`=22161073 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('pet_fonce','mal_croppe','environnement','metal','carton','autre','flou','pehd','pet_clair','background','papier')) 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`=22161073 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('pet_fonce','mal_croppe','environnement','metal','carton','autre','flou','pehd','pet_clair','background','papier')) 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`=22161073 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('pet_fonce','mal_croppe','environnement','metal','carton','autre','flou','pehd','pet_clair','background','papier')) AND mptpi.`min_score`=0.5 To do lien utilise dans velours : https://www.fotonower.com/velours/22161530,22161531,22161532,22161533,22161534,22161535,22161536,22161537,22161538,22161539,22161540?tags=pet_fonce,mal_croppe,environnement,metal,carton,autre,flou,pehd,pet_clair,background,papier Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : ventilate_hashtags_in_portfolio we use saveGeneral [1350741936, 1350741933, 1350741771, 1350741769, 1350741659, 1350741627, 1350741601, 1350741579, 1350741267, 1350741217, 1350741215, 1350741212, 1350738338, 1350738296, 1350737578, 1350737511, 1350737419, 1350737410, 1350737230, 1350737086, 1350736919, 1350736896, 1350736747, 1350736614] Looping around the photos to save general results len do output : 1 /22161073. 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, '2734295') ('3318', '22161073', '1350741936', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741933', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741771', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741769', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741659', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741627', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741601', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741579', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741267', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741217', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741215', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741212', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350738338', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350738296', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350737578', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350737511', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350737419', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350737410', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350737230', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350737086', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350736919', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350736896', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350736747', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350736614', None, None, None, None, None, '2734295') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 25 time used for this insertion : 0.01591944694519043 save_final save missing photos in datou_result : time spend for datou_step_exec : 1.721400260925293 time spend to save output : 0.01625347137451172 total time spend for step 4 : 1.7376537322998047 step5:final Wed Apr 9 12:49:46 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! 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 : {1350741936: ('0.1886047378056162',), 1350741933: ('0.1886047378056162',), 1350741771: ('0.1886047378056162',), 1350741769: ('0.1886047378056162',), 1350741659: ('0.1886047378056162',), 1350741627: ('0.1886047378056162',), 1350741601: ('0.1886047378056162',), 1350741579: ('0.1886047378056162',), 1350741267: ('0.1886047378056162',), 1350741217: ('0.1886047378056162',), 1350741215: ('0.1886047378056162',), 1350741212: ('0.1886047378056162',), 1350738338: ('0.1886047378056162',), 1350738296: ('0.1886047378056162',), 1350737578: ('0.1886047378056162',), 1350737511: ('0.1886047378056162',), 1350737419: ('0.1886047378056162',), 1350737410: ('0.1886047378056162',), 1350737230: ('0.1886047378056162',), 1350737086: ('0.1886047378056162',), 1350736919: ('0.1886047378056162',), 1350736896: ('0.1886047378056162',), 1350736747: ('0.1886047378056162',), 1350736614: ('0.1886047378056162',)} new output for save of step final : {1350741936: ('0.1886047378056162',), 1350741933: ('0.1886047378056162',), 1350741771: ('0.1886047378056162',), 1350741769: ('0.1886047378056162',), 1350741659: ('0.1886047378056162',), 1350741627: ('0.1886047378056162',), 1350741601: ('0.1886047378056162',), 1350741579: ('0.1886047378056162',), 1350741267: ('0.1886047378056162',), 1350741217: ('0.1886047378056162',), 1350741215: ('0.1886047378056162',), 1350741212: ('0.1886047378056162',), 1350738338: ('0.1886047378056162',), 1350738296: ('0.1886047378056162',), 1350737578: ('0.1886047378056162',), 1350737511: ('0.1886047378056162',), 1350737419: ('0.1886047378056162',), 1350737410: ('0.1886047378056162',), 1350737230: ('0.1886047378056162',), 1350737086: ('0.1886047378056162',), 1350736919: ('0.1886047378056162',), 1350736896: ('0.1886047378056162',), 1350736747: ('0.1886047378056162',), 1350736614: ('0.1886047378056162',)} [1350741936, 1350741933, 1350741771, 1350741769, 1350741659, 1350741627, 1350741601, 1350741579, 1350741267, 1350741217, 1350741215, 1350741212, 1350738338, 1350738296, 1350737578, 1350737511, 1350737419, 1350737410, 1350737230, 1350737086, 1350736919, 1350736896, 1350736747, 1350736614] Looping around the photos to save general results len do output : 24 /1350741936.Didn't retrieve data . /1350741933.Didn't retrieve data . /1350741771.Didn't retrieve data . /1350741769.Didn't retrieve data . /1350741659.Didn't retrieve data . /1350741627.Didn't retrieve data . /1350741601.Didn't retrieve data . /1350741579.Didn't retrieve data . /1350741267.Didn't retrieve data . /1350741217.Didn't retrieve data . /1350741215.Didn't retrieve data . /1350741212.Didn't retrieve data . /1350738338.Didn't retrieve data . /1350738296.Didn't retrieve data . /1350737578.Didn't retrieve data . /1350737511.Didn't retrieve data . /1350737419.Didn't retrieve data . /1350737410.Didn't retrieve data . /1350737230.Didn't retrieve data . /1350737086.Didn't retrieve data . /1350736919.Didn't retrieve data . /1350736896.Didn't retrieve data . /1350736747.Didn't retrieve data . /1350736614.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, '2734295') ('3318', '22161073', '1350741936', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741933', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741771', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741769', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741659', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741627', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741601', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741579', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741267', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741217', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741215', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741212', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350738338', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350738296', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350737578', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350737511', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350737419', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350737410', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350737230', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350737086', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350736919', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350736896', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350736747', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350736614', None, None, None, None, None, '2734295') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 72 time used for this insertion : 0.015611886978149414 save_final save missing photos in datou_result : time spend for datou_step_exec : 0.11971592903137207 time spend to save output : 0.016819238662719727 total time spend for step 5 : 0.1365351676940918 step6:blur_detection Wed Apr 9 12:49:46 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! 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/1744194629_977867_1350741936_956b7adfadb63d2d5c54c07a674f8664.jpg resize: (2160, 3264) 1350741936 -4.5863425124957935 treat image : temp/1744194629_977867_1350741933_3fbfbae21758090ea11bf3ed86e64dc5.jpg resize: (2160, 3264) 1350741933 -4.485918590028587 treat image : temp/1744194629_977867_1350741771_e42a33325dcfc38315442b3de0c81816.jpg resize: (2160, 3264) 1350741771 -4.791761694346002 treat image : temp/1744194629_977867_1350741769_3e98229c0892a8d90471e5b7e619509d.jpg resize: (2160, 3264) 1350741769 -5.116094837803612 treat image : temp/1744194629_977867_1350741659_38aaf39c1c176f2cee78af881399d487.jpg resize: (2160, 3264) 1350741659 -3.704869327370497 treat image : temp/1744194629_977867_1350741627_fcdd6fbd0a4f3c0b58ce056313835210.jpg resize: (2160, 3264) 1350741627 -4.795206581216873 treat image : temp/1744194629_977867_1350741601_80b24731fed692079f730c47134e781c.jpg resize: (2160, 3264) 1350741601 -6.662065926168022 treat image : temp/1744194629_977867_1350741579_6cfcf74a53301f4607874fb61c867cf5.jpg resize: (2160, 3264) 1350741579 -4.548853131805146 treat image : temp/1744194629_977867_1350741267_98074543c81e19d7632607b4b01240e8.jpg resize: (2160, 3264) 1350741267 -2.7228636579655916 treat image : temp/1744194629_977867_1350741217_d40c206a4557dfd920bb172b3c40dbe4.jpg resize: (2160, 3264) 1350741217 -4.313650452107773 treat image : temp/1744194629_977867_1350741215_632104b9eb9282ba1fb3f0d5a512efea.jpg resize: (2160, 3264) 1350741215 -5.0305164602770995 treat image : temp/1744194629_977867_1350741212_31597f385afbd872ea5b695b6fb6d2a0.jpg resize: (2160, 3264) 1350741212 -7.050535785015862 treat image : temp/1744194629_977867_1350738338_9c3fe74498d1c8c07bf2b7b487372cf2.jpg resize: (2160, 3264) 1350738338 -5.279758164945922 treat image : temp/1744194629_977867_1350738296_db51288f7d589e08cd981ee331358bcd.jpg resize: (2160, 3264) 1350738296 -3.5364295671226276 treat image : temp/1744194629_977867_1350737578_6e7583fea3eb9b07d775c46410c10685.jpg resize: (2160, 3264) 1350737578 -3.677805825302462 treat image : temp/1744194629_977867_1350737511_6a12acf005bda31cf49be9e73bd078e4.jpg resize: (2160, 3264) 1350737511 -4.58087681266481 treat image : temp/1744194629_977867_1350737419_c58fb93d6508395f6fe76f916e92590d.jpg resize: (2160, 3264) 1350737419 -4.726598228452 treat image : temp/1744194629_977867_1350737410_0fc7db67976d8f82e1991e3a06d48850.jpg resize: (2160, 3264) 1350737410 -5.118321949394586 treat image : temp/1744194629_977867_1350737230_2f6566feee10eba20b86c005bb565805.jpg resize: (2160, 3264) 1350737230 -3.088634676644146 treat image : temp/1744194629_977867_1350737086_f1d769c9e9bf4b945ec2f006390c4a2b.jpg resize: (2160, 3264) 1350737086 -5.933493571799441 treat image : temp/1744194629_977867_1350736919_73c901cc4783dd2eb50eb3a5e7256bca.jpg resize: (2160, 3264) 1350736919 -1.1221102024637264 treat image : temp/1744194629_977867_1350736896_be980c6fd34abcaacc3008a5d36345e9.jpg resize: (2160, 3264) 1350736896 -5.026987557889799 treat image : temp/1744194629_977867_1350736747_782440baf315396a3795d405c0f02ebc.jpg resize: (2160, 3264) 1350736747 -2.8465483447373607 treat image : temp/1744194629_977867_1350736614_fe356f75d434f0663482a2beaefa2c3a.jpg resize: (2160, 3264) 1350736614 -4.419635745812991 treat image : temp/1744194629_977867_1350741936_956b7adfadb63d2d5c54c07a674f8664_rle_crop_3751423990_0.png resize: (674, 803) 1350757683 -2.721132826061013 treat image : temp/1744194629_977867_1350741936_956b7adfadb63d2d5c54c07a674f8664_rle_crop_3751423989_0.png resize: (178, 363) 1350757684 -2.0648563406961733 treat image : temp/1744194629_977867_1350741936_956b7adfadb63d2d5c54c07a674f8664_rle_crop_3751423973_0.png resize: (370, 552) 1350757685 -2.3941059753657865 treat image : temp/1744194629_977867_1350741936_956b7adfadb63d2d5c54c07a674f8664_rle_crop_3751423997_0.png resize: (152, 239) 1350757686 -1.9111872343590508 treat image : temp/1744194629_977867_1350741936_956b7adfadb63d2d5c54c07a674f8664_rle_crop_3751423981_0.png resize: (135, 154) 1350757687 -1.3780530859263773 treat image : temp/1744194629_977867_1350741936_956b7adfadb63d2d5c54c07a674f8664_rle_crop_3751423976_0.png resize: (158, 213) 1350757688 -2.298708236334046 treat image : temp/1744194629_977867_1350741936_956b7adfadb63d2d5c54c07a674f8664_rle_crop_3751423975_0.png resize: (466, 204) 1350757689 -1.4533211954467813 treat image : temp/1744194629_977867_1350741936_956b7adfadb63d2d5c54c07a674f8664_rle_crop_3751423993_0.png resize: (133, 144) 1350757690 -2.346832088660716 treat image : temp/1744194629_977867_1350741936_956b7adfadb63d2d5c54c07a674f8664_rle_crop_3751423970_0.png resize: (95, 222) 1350757691 -1.7224914734165113 treat image : temp/1744194629_977867_1350741936_956b7adfadb63d2d5c54c07a674f8664_rle_crop_3751423980_0.png resize: (130, 188) 1350757692 -2.9369391664329823 treat image : temp/1744194629_977867_1350741936_956b7adfadb63d2d5c54c07a674f8664_rle_crop_3751423979_0.png resize: (191, 116) 1350757693 -1.6433587009840152 treat image : temp/1744194629_977867_1350741936_956b7adfadb63d2d5c54c07a674f8664_rle_crop_3751423994_0.png resize: (153, 132) 1350757694 0.8684652134598584 treat image : temp/1744194629_977867_1350741936_956b7adfadb63d2d5c54c07a674f8664_rle_crop_3751423999_0.png resize: (214, 175) 1350757695 -2.8663961979797024 treat image : temp/1744194629_977867_1350741936_956b7adfadb63d2d5c54c07a674f8664_rle_crop_3751423987_0.png resize: (195, 348) 1350757696 -1.7474687106179072 treat image : temp/1744194629_977867_1350741936_956b7adfadb63d2d5c54c07a674f8664_rle_crop_3751423986_0.png resize: (281, 150) 1350757697 -1.1549222508932555 treat image : temp/1744194629_977867_1350741936_956b7adfadb63d2d5c54c07a674f8664_rle_crop_3751423984_0.png resize: (113, 141) 1350757698 -3.5644098414687524 treat image : temp/1744194629_977867_1350741936_956b7adfadb63d2d5c54c07a674f8664_rle_crop_3751423982_0.png resize: (395, 274) 1350757699 -3.213119039345861 treat image : temp/1744194629_977867_1350741936_956b7adfadb63d2d5c54c07a674f8664_rle_crop_3751423992_0.png resize: (56, 173) 1350757700 -1.453868342780162 treat image : temp/1744194629_977867_1350741936_956b7adfadb63d2d5c54c07a674f8664_rle_crop_3751424005_0.png resize: (159, 179) 1350757701 -3.3548716771191023 treat image : temp/1744194629_977867_1350741936_956b7adfadb63d2d5c54c07a674f8664_rle_crop_3751423998_0.png resize: (335, 196) 1350757702 -3.3627725712983256 treat image : temp/1744194629_977867_1350741936_956b7adfadb63d2d5c54c07a674f8664_rle_crop_3751423988_0.png resize: (117, 227) 1350757703 -3.5183119959375784 treat image : temp/1744194629_977867_1350741936_956b7adfadb63d2d5c54c07a674f8664_rle_crop_3751423974_0.png resize: (369, 330) 1350757704 -3.2472121049380442 treat image : temp/1744194629_977867_1350741936_956b7adfadb63d2d5c54c07a674f8664_rle_crop_3751424006_0.png resize: (61, 70) 1350757705 -0.11745166892953353 treat image : temp/1744194629_977867_1350741936_956b7adfadb63d2d5c54c07a674f8664_rle_crop_3751424007_0.png resize: (95, 134) 1350757706 -1.0838076295853993 treat image : temp/1744194629_977867_1350741936_956b7adfadb63d2d5c54c07a674f8664_rle_crop_3751424004_0.png resize: (114, 237) 1350757707 -3.580905302715017 treat image : temp/1744194629_977867_1350741936_956b7adfadb63d2d5c54c07a674f8664_rle_crop_3751423991_0.png resize: (100, 128) 1350757708 -2.9187146222567186 treat image : temp/1744194629_977867_1350741936_956b7adfadb63d2d5c54c07a674f8664_rle_crop_3751423983_0.png resize: (141, 174) 1350757709 -1.0314964591100764 treat image : temp/1744194629_977867_1350741936_956b7adfadb63d2d5c54c07a674f8664_rle_crop_3751424001_0.png resize: (98, 63) 1350757711 -1.7300086716314476 treat image : temp/1744194629_977867_1350741936_956b7adfadb63d2d5c54c07a674f8664_rle_crop_3751423995_0.png resize: (220, 153) 1350757712 -2.271437001545009 treat image : temp/1744194629_977867_1350741933_3fbfbae21758090ea11bf3ed86e64dc5_rle_crop_3751424041_0.png resize: (145, 153) 1350757713 -2.877667602582357 treat image : temp/1744194629_977867_1350741933_3fbfbae21758090ea11bf3ed86e64dc5_rle_crop_3751424019_0.png resize: (123, 118) 1350757714 -2.167603092989612 treat image : temp/1744194629_977867_1350741933_3fbfbae21758090ea11bf3ed86e64dc5_rle_crop_3751424040_0.png resize: (185, 235) 1350757715 -1.6155582797756134 treat image : temp/1744194629_977867_1350741933_3fbfbae21758090ea11bf3ed86e64dc5_rle_crop_3751424020_0.png resize: (179, 359) 1350757716 -2.0378440592856726 treat image : temp/1744194629_977867_1350741933_3fbfbae21758090ea11bf3ed86e64dc5_rle_crop_3751424030_0.png resize: (186, 272) 1350757718 -1.9594512222889806 treat image : temp/1744194629_977867_1350741933_3fbfbae21758090ea11bf3ed86e64dc5_rle_crop_3751424013_0.png resize: (312, 479) 1350757719 -2.526136830847556 treat image : temp/1744194629_977867_1350741933_3fbfbae21758090ea11bf3ed86e64dc5_rle_crop_3751424036_0.png resize: (128, 205) 1350757720 -1.1942446435268654 treat image : temp/1744194629_977867_1350741933_3fbfbae21758090ea11bf3ed86e64dc5_rle_crop_3751424015_0.png resize: (285, 234) 1350757721 -2.498017676336009 treat image : temp/1744194629_977867_1350741933_3fbfbae21758090ea11bf3ed86e64dc5_rle_crop_3751424012_0.png resize: (141, 160) 1350757722 -0.32435110502647313 treat image : temp/1744194629_977867_1350741933_3fbfbae21758090ea11bf3ed86e64dc5_rle_crop_3751424016_0.png resize: (152, 158) 1350757723 -2.2639404891295043 treat image : temp/1744194629_977867_1350741933_3fbfbae21758090ea11bf3ed86e64dc5_rle_crop_3751424031_0.png resize: (127, 185) 1350757724 -0.7956747711629739 treat image : temp/1744194629_977867_1350741933_3fbfbae21758090ea11bf3ed86e64dc5_rle_crop_3751424033_0.png resize: (265, 324) 1350757725 -2.319667893910799 treat image : temp/1744194629_977867_1350741933_3fbfbae21758090ea11bf3ed86e64dc5_rle_crop_3751424021_0.png resize: (452, 416) 1350757726 -1.0296848549561308 treat image : temp/1744194629_977867_1350741933_3fbfbae21758090ea11bf3ed86e64dc5_rle_crop_3751424018_0.png resize: (203, 306) 1350757727 -2.61386964466467 treat image : temp/1744194629_977867_1350741933_3fbfbae21758090ea11bf3ed86e64dc5_rle_crop_3751424025_0.png resize: (228, 235) 1350757728 -2.0913458589086567 treat image : temp/1744194629_977867_1350741933_3fbfbae21758090ea11bf3ed86e64dc5_rle_crop_3751424034_0.png resize: (163, 208) 1350757729 -2.9910796374554036 treat image : temp/1744194629_977867_1350741933_3fbfbae21758090ea11bf3ed86e64dc5_rle_crop_3751424028_0.png resize: (272, 294) 1350757730 -1.9665369037475577 treat image : temp/1744194629_977867_1350741933_3fbfbae21758090ea11bf3ed86e64dc5_rle_crop_3751424022_0.png resize: (122, 190) 1350757731 -2.2499852748702356 treat image : temp/1744194629_977867_1350741933_3fbfbae21758090ea11bf3ed86e64dc5_rle_crop_3751424010_0.png resize: (280, 295) 1350757732 -2.2709148238632086 treat image : temp/1744194629_977867_1350741933_3fbfbae21758090ea11bf3ed86e64dc5_rle_crop_3751424017_0.png resize: (162, 186) 1350757733 -2.149984781867745 treat image : temp/1744194629_977867_1350741933_3fbfbae21758090ea11bf3ed86e64dc5_rle_crop_3751424027_0.png resize: (114, 131) 1350757734 -3.8388628256158346 treat image : temp/1744194629_977867_1350741933_3fbfbae21758090ea11bf3ed86e64dc5_rle_crop_3751424032_0.png resize: (191, 386) 1350757735 -2.8595876686976403 treat image : temp/1744194629_977867_1350741933_3fbfbae21758090ea11bf3ed86e64dc5_rle_crop_3751424029_0.png resize: (79, 102) 1350757736 -1.774521150310184 treat image : temp/1744194629_977867_1350741933_3fbfbae21758090ea11bf3ed86e64dc5_rle_crop_3751424042_0.png resize: (173, 98) 1350757737 -2.8282526786402533 treat image : temp/1744194629_977867_1350741933_3fbfbae21758090ea11bf3ed86e64dc5_rle_crop_3751424026_0.png resize: (172, 117) 1350757738 -2.8767589675119676 treat image : temp/1744194629_977867_1350741933_3fbfbae21758090ea11bf3ed86e64dc5_rle_crop_3751424035_0.png resize: (146, 115) 1350757739 -2.0214523446931736 treat image : temp/1744194629_977867_1350741771_e42a33325dcfc38315442b3de0c81816_rle_crop_3751424045_0.png resize: (127, 154) 1350757740 -1.5932573226453157 treat image : temp/1744194629_977867_1350741771_e42a33325dcfc38315442b3de0c81816_rle_crop_3751424074_0.png resize: (296, 309) 1350757741 -2.7301967061186097 treat image : 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temp/1744194629_977867_1350738296_db51288f7d589e08cd981ee331358bcd_rle_crop_3751424415_0.png resize: (406, 329) 1350758554 -2.3040882780148135 treat image : temp/1744194629_977867_1350738296_db51288f7d589e08cd981ee331358bcd_rle_crop_3751424425_0.png resize: (471, 363) 1350758555 -2.2310937942175797 treat image : temp/1744194629_977867_1350738296_db51288f7d589e08cd981ee331358bcd_rle_crop_3751424433_0.png resize: (181, 210) 1350758556 -1.2084474918325077 treat image : temp/1744194629_977867_1350737578_6e7583fea3eb9b07d775c46410c10685_rle_crop_3751424445_0.png resize: (361, 389) 1350758557 -1.8546506982284383 treat image : temp/1744194629_977867_1350737511_6a12acf005bda31cf49be9e73bd078e4_rle_crop_3751424500_0.png resize: (424, 218) 1350758558 -3.719623191996023 treat image : temp/1744194629_977867_1350737419_c58fb93d6508395f6fe76f916e92590d_rle_crop_3751424523_0.png resize: (221, 366) 1350758559 -3.7500385949406234 treat image : 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temp/1744194629_977867_1350737086_f1d769c9e9bf4b945ec2f006390c4a2b_rle_crop_3751424651_0.png resize: (246, 403) 1350758566 -3.986981769449616 treat image : temp/1744194629_977867_1350737086_f1d769c9e9bf4b945ec2f006390c4a2b_rle_crop_3751424648_0.png resize: (368, 266) 1350758567 -4.134905388854751 treat image : temp/1744194629_977867_1350737086_f1d769c9e9bf4b945ec2f006390c4a2b_rle_crop_3751424674_0.png resize: (346, 333) 1350758568 -3.1483587364837384 treat image : temp/1744194629_977867_1350737086_f1d769c9e9bf4b945ec2f006390c4a2b_rle_crop_3751424665_0.png resize: (243, 249) 1350758569 -4.564504079827507 treat image : temp/1744194629_977867_1350737086_f1d769c9e9bf4b945ec2f006390c4a2b_rle_crop_3751424633_0.png resize: (436, 388) 1350758570 -2.419554262800293 treat image : temp/1744194629_977867_1350736919_73c901cc4783dd2eb50eb3a5e7256bca_rle_crop_3751424680_0.png resize: (410, 242) 1350758571 -3.3583656452882935 treat image : temp/1744194629_977867_1350736896_be980c6fd34abcaacc3008a5d36345e9_rle_crop_3751424698_0.png resize: (196, 202) 1350758572 -2.598021735164914 treat image : temp/1744194629_977867_1350736896_be980c6fd34abcaacc3008a5d36345e9_rle_crop_3751424695_0.png resize: (213, 267) 1350758573 -1.1955845790394257 treat image : temp/1744194629_977867_1350736614_fe356f75d434f0663482a2beaefa2c3a_rle_crop_3751424723_0.png resize: (671, 702) 1350758574 -2.2892389241822086 treat image : temp/1744194629_977867_1350736614_fe356f75d434f0663482a2beaefa2c3a_rle_crop_3751424745_0.png resize: (289, 322) 1350758575 -2.968024193497249 treat image : temp/1744194629_977867_1350736614_fe356f75d434f0663482a2beaefa2c3a_rle_crop_3751424756_0.png resize: (251, 244) 1350758576 -3.0201156583881206 treat image : temp/1744194629_977867_1350736614_fe356f75d434f0663482a2beaefa2c3a_rle_crop_3751424728_0.png resize: (562, 189) 1350758577 -2.8428705023522545 treat image : temp/1744194629_977867_1350741933_3fbfbae21758090ea11bf3ed86e64dc5_rle_crop_3751424023_0.png resize: (132, 142) 1350758579 -1.0177813921900363 treat image : temp/1744194629_977867_1350741659_38aaf39c1c176f2cee78af881399d487_rle_crop_3751424134_0.png resize: (231, 245) 1350758580 -1.9206567441251627 treat image : temp/1744194629_977867_1350741659_38aaf39c1c176f2cee78af881399d487_rle_crop_3751424135_0.png resize: (127, 108) 1350758581 -4.11341144736293 treat image : temp/1744194629_977867_1350741627_fcdd6fbd0a4f3c0b58ce056313835210_rle_crop_3751424179_0.png resize: (52, 107) 1350758582 2.125669073955926 treat image : temp/1744194629_977867_1350741627_fcdd6fbd0a4f3c0b58ce056313835210_rle_crop_3751424162_0.png resize: (109, 103) 1350758583 -1.2333677533726801 treat image : temp/1744194629_977867_1350741267_98074543c81e19d7632607b4b01240e8_rle_crop_3751424272_0.png resize: (180, 213) 1350758584 -2.0753568089341625 treat image : temp/1744194629_977867_1350741212_31597f385afbd872ea5b695b6fb6d2a0_rle_crop_3751424373_0.png resize: (123, 108) 1350758585 -2.4776993561545364 treat image : temp/1744194629_977867_1350738338_9c3fe74498d1c8c07bf2b7b487372cf2_rle_crop_3751424414_0.png resize: (83, 100) 1350758586 -1.1658863686653527 treat image : temp/1744194629_977867_1350737419_c58fb93d6508395f6fe76f916e92590d_rle_crop_3751424530_0.png resize: (142, 135) 1350758587 -2.172736907795078 treat image : temp/1744194629_977867_1350737230_2f6566feee10eba20b86c005bb565805_rle_crop_3751424626_0.png resize: (321, 406) 1350758588 -2.5870561071097624 treat image : temp/1744194629_977867_1350736747_782440baf315396a3795d405c0f02ebc_rle_crop_3751424714_0.png resize: (95, 99) 1350758589 -1.697700782116529 treat image : temp/1744194629_977867_1350741579_6cfcf74a53301f4607874fb61c867cf5_rle_crop_3751424246_0.png resize: (189, 482) 1350758593 -1.7424351217344527 treat image : temp/1744194629_977867_1350741267_98074543c81e19d7632607b4b01240e8_rle_crop_3751424280_0.png resize: (151, 85) 1350758594 -1.6781757293239303 treat image : temp/1744194629_977867_1350741217_d40c206a4557dfd920bb172b3c40dbe4_rle_crop_3751424308_0.png resize: (174, 160) 1350758595 -1.445096402648543 treat image : temp/1744194629_977867_1350738296_db51288f7d589e08cd981ee331358bcd_rle_crop_3751424427_0.png resize: (356, 232) 1350758596 -2.2014879401219227 treat image : temp/1744194629_977867_1350738296_db51288f7d589e08cd981ee331358bcd_rle_crop_3751424437_0.png resize: (80, 68) 1350758597 -0.8704729760514256 treat image : temp/1744194629_977867_1350738296_db51288f7d589e08cd981ee331358bcd_rle_crop_3751424436_0.png resize: (280, 271) 1350758598 -1.6413205749895121 treat image : temp/1744194629_977867_1350737578_6e7583fea3eb9b07d775c46410c10685_rle_crop_3751424460_0.png resize: (110, 137) 1350758599 -1.4924487398752775 treat image : temp/1744194629_977867_1350737511_6a12acf005bda31cf49be9e73bd078e4_rle_crop_3751424499_0.png resize: (211, 160) 1350758600 -1.9393106064954575 treat image : temp/1744194629_977867_1350737410_0fc7db67976d8f82e1991e3a06d48850_rle_crop_3751424583_0.png resize: (129, 115) 1350758601 -0.7636446881359262 treat image : temp/1744194629_977867_1350741936_956b7adfadb63d2d5c54c07a674f8664_rle_crop_3751424000_0.png resize: (126, 129) 1350758607 -1.2139883640086588 treat image : temp/1744194629_977867_1350741659_38aaf39c1c176f2cee78af881399d487_rle_crop_3751424141_0.png resize: (323, 489) 1350758608 -2.227383651825879 treat image : temp/1744194629_977867_1350741579_6cfcf74a53301f4607874fb61c867cf5_rle_crop_3751424244_0.png resize: (169, 275) 1350758609 -1.7335225282043705 treat image : temp/1744194629_977867_1350741267_98074543c81e19d7632607b4b01240e8_rle_crop_3751424266_0.png resize: (186, 228) 1350758610 -1.1599984962352177 treat image : temp/1744194629_977867_1350741212_31597f385afbd872ea5b695b6fb6d2a0_rle_crop_3751424371_0.png resize: (233, 431) 1350758611 -5.637409134459556 treat image : temp/1744194629_977867_1350738338_9c3fe74498d1c8c07bf2b7b487372cf2_rle_crop_3751424409_0.png resize: (182, 261) 1350758612 -2.8402941548108966 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 : 815 Catched exception ! Connect or reconnect ! In save_photo_hashtag_id_thcl_score : (1205, 'Lock wait timeout exceeded; try restarting transaction') [('1533', '1350741936', '492609224', '-4.5863425124957935'), ('1533', '1350741933', '492609224', '-4.485918590028587'), ('1533', '1350741771', '492609224', '-4.791761694346002'), ('1533', '1350741769', '492609224', '-5.116094837803612'), ('1533', '1350741659', '492609224', '-3.704869327370497'), ('1533', '1350741627', '492609224', '-4.795206581216873'), ('1533', '1350741601', '492609224', '-6.662065926168022'), ('1533', '1350741579', '492609224', '-4.548853131805146'), ('1533', '1350741267', '492609224', '-2.7228636579655916'), ('1533', '1350741217', '492609224', '-4.313650452107773'), ('1533', '1350741215', '492609224', '-5.0305164602770995'), ('1533', '1350741212', '492609224', '-7.050535785015862'), ('1533', '1350738338', '492609224', '-5.279758164945922'), ('1533', '1350738296', '492609224', '-3.5364295671226276'), ('1533', '1350737578', '492609224', '-3.677805825302462'), ('1533', '1350737511', '492609224', '-4.58087681266481'), ('1533', '1350737419', '492609224', '-4.726598228452'), ('1533', '1350737410', '492609224', '-5.118321949394586'), ('1533', '1350737230', '492609224', '-3.088634676644146'), ('1533', '1350737086', '492609224', '-5.933493571799441'), ('1533', '1350736919', '492688767', '-1.1221102024637264'), ('1533', '1350736896', '492609224', '-5.026987557889799'), ('1533', '1350736747', '492609224', '-2.8465483447373607'), ('1533', '1350736614', '492609224', '-4.419635745812991'), ('1533', '1350757683', '492609224', '-2.721132826061013'), ('1533', '1350757684', '492609224', '-2.0648563406961733'), ('1533', '1350757685', '492609224', '-2.3941059753657865'), ('1533', '1350757686', '492688767', '-1.9111872343590508'), ('1533', '1350757687', '492688767', '-1.3780530859263773'), ('1533', '1350757688', '492609224', '-2.298708236334046'), ('1533', '1350757689', '492688767', '-1.4533211954467813'), ('1533', '1350757690', '492609224', '-2.346832088660716'), ('1533', '1350757691', '492688767', '-1.7224914734165113'), ('1533', '1350757692', '492609224', '-2.9369391664329823'), ('1533', '1350757693', '492688767', '-1.6433587009840152'), ('1533', '1350757694', '492688767', '0.8684652134598584'), ('1533', '1350757695', '492609224', '-2.8663961979797024'), ('1533', '1350757696', '492688767', '-1.7474687106179072'), ('1533', '1350757697', '492688767', '-1.1549222508932555'), ('1533', '1350757698', '492609224', '-3.5644098414687524'), ('1533', '1350757699', '492609224', '-3.213119039345861'), ('1533', '1350757700', '492688767', '-1.453868342780162'), ('1533', '1350757701', '492609224', '-3.3548716771191023'), ('1533', '1350757702', '492609224', '-3.3627725712983256'), ('1533', '1350757703', '492609224', '-3.5183119959375784'), ('1533', '1350757704', '492609224', '-3.2472121049380442'), ('1533', '1350757705', '492688767', '-0.11745166892953353'), ('1533', '1350757706', '492688767', '-1.0838076295853993'), ('1533', '1350757707', '492609224', '-3.580905302715017'), ('1533', '1350757708', '492609224', '-2.9187146222567186'), ('1533', '1350757709', '492688767', '-1.0314964591100764'), ('1533', '1350757711', '492688767', '-1.7300086716314476'), ('1533', '1350757712', '492609224', '-2.271437001545009'), ('1533', '1350757713', '492609224', '-2.877667602582357'), ('1533', '1350757714', '492609224', '-2.167603092989612'), ('1533', '1350757715', '492688767', '-1.6155582797756134'), ('1533', '1350757716', '492609224', '-2.0378440592856726'), ('1533', '1350757718', '492688767', '-1.9594512222889806'), ('1533', '1350757719', '492609224', '-2.526136830847556'), ('1533', '1350757720', '492688767', '-1.1942446435268654'), ('1533', '1350757721', '492609224', '-2.498017676336009'), ('1533', '1350757722', '492688767', '-0.32435110502647313'), ('1533', '1350757723', '492609224', '-2.2639404891295043'), ('1533', '1350757724', '492688767', '-0.7956747711629739'), ('1533', '1350757725', '492609224', 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'1350758612', '492609224', '-2.8402941548108966')] time used for this insertion : 51.118494510650635 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 815 time used for this insertion : 0.15092039108276367 save missing photos in datou_result : time spend for datou_step_exec : 103.13152718544006 time spend to save output : 51.280194997787476 total time spend for step 6 : 154.41172218322754 step7:brightness Wed Apr 9 12:52:21 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/1744194629_977867_1350736614_fe356f75d434f0663482a2beaefa2c3a_rle_crop_3751424756_0.png treat image : temp/1744194629_977867_1350736614_fe356f75d434f0663482a2beaefa2c3a_rle_crop_3751424728_0.png treat image : temp/1744194629_977867_1350741933_3fbfbae21758090ea11bf3ed86e64dc5_rle_crop_3751424023_0.png treat image : temp/1744194629_977867_1350741659_38aaf39c1c176f2cee78af881399d487_rle_crop_3751424134_0.png treat image : temp/1744194629_977867_1350741659_38aaf39c1c176f2cee78af881399d487_rle_crop_3751424135_0.png treat image : temp/1744194629_977867_1350741627_fcdd6fbd0a4f3c0b58ce056313835210_rle_crop_3751424179_0.png treat image : temp/1744194629_977867_1350741627_fcdd6fbd0a4f3c0b58ce056313835210_rle_crop_3751424162_0.png treat image : temp/1744194629_977867_1350741267_98074543c81e19d7632607b4b01240e8_rle_crop_3751424272_0.png treat image : temp/1744194629_977867_1350741212_31597f385afbd872ea5b695b6fb6d2a0_rle_crop_3751424373_0.png treat image : temp/1744194629_977867_1350738338_9c3fe74498d1c8c07bf2b7b487372cf2_rle_crop_3751424414_0.png treat image : temp/1744194629_977867_1350737419_c58fb93d6508395f6fe76f916e92590d_rle_crop_3751424530_0.png treat image : temp/1744194629_977867_1350737230_2f6566feee10eba20b86c005bb565805_rle_crop_3751424626_0.png treat image : temp/1744194629_977867_1350736747_782440baf315396a3795d405c0f02ebc_rle_crop_3751424714_0.png treat image : temp/1744194629_977867_1350741579_6cfcf74a53301f4607874fb61c867cf5_rle_crop_3751424246_0.png treat image : temp/1744194629_977867_1350741267_98074543c81e19d7632607b4b01240e8_rle_crop_3751424280_0.png treat image : temp/1744194629_977867_1350741217_d40c206a4557dfd920bb172b3c40dbe4_rle_crop_3751424308_0.png treat image : temp/1744194629_977867_1350738296_db51288f7d589e08cd981ee331358bcd_rle_crop_3751424427_0.png treat image : temp/1744194629_977867_1350738296_db51288f7d589e08cd981ee331358bcd_rle_crop_3751424437_0.png treat image : temp/1744194629_977867_1350738296_db51288f7d589e08cd981ee331358bcd_rle_crop_3751424436_0.png treat image : temp/1744194629_977867_1350737578_6e7583fea3eb9b07d775c46410c10685_rle_crop_3751424460_0.png treat image : temp/1744194629_977867_1350737511_6a12acf005bda31cf49be9e73bd078e4_rle_crop_3751424499_0.png treat image : temp/1744194629_977867_1350737410_0fc7db67976d8f82e1991e3a06d48850_rle_crop_3751424583_0.png treat image : temp/1744194629_977867_1350741936_956b7adfadb63d2d5c54c07a674f8664_rle_crop_3751424000_0.png treat image : temp/1744194629_977867_1350741659_38aaf39c1c176f2cee78af881399d487_rle_crop_3751424141_0.png treat image : temp/1744194629_977867_1350741579_6cfcf74a53301f4607874fb61c867cf5_rle_crop_3751424244_0.png treat image : temp/1744194629_977867_1350741267_98074543c81e19d7632607b4b01240e8_rle_crop_3751424266_0.png treat image : temp/1744194629_977867_1350741212_31597f385afbd872ea5b695b6fb6d2a0_rle_crop_3751424371_0.png treat image : temp/1744194629_977867_1350738338_9c3fe74498d1c8c07bf2b7b487372cf2_rle_crop_3751424409_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 : 815 time used for this insertion : 0.05342221260070801 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 815 time used for this insertion : 0.14595699310302734 save missing photos in datou_result : time spend for datou_step_exec : 26.422098875045776 time spend to save output : 0.20801162719726562 total time spend for step 7 : 26.630110502243042 step8:velours_tree Wed Apr 9 12:52:47 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed 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 : 1.3992908000946045 time spend to save output : 3.719329833984375e-05 total time spend for step 8 : 1.3993279933929443 step9:send_mail_cod Wed Apr 9 12:52:49 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed 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_P22161073_09-04-2025_12_52_49.pdf 22161530 change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .imagette221615301744195969 22161531 imagette221615311744195970 22161533 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 .imagette221615331744195970 22161534 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 .imagette221615341744195971 22161535 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 .imagette221615351744195972 22161536 imagette221615361744195974 22161537 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 .imagette221615371744195974 22161538 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 .imagette221615381744195974 22161539 imagette221615391744195976 22161540 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 .imagette221615401744195976 SELECT h.hashtag,pcr.value FROM MTRUser.portfolio_carac_ratio pcr, MTRBack.hashtags h where pcr.portfolio_id=22161073 and hashtag_type = 3594 and pcr.hashtag_id = h.hashtag_id; velour_link : https://www.fotonower.com/velours/22161530,22161531,22161532,22161533,22161534,22161535,22161536,22161537,22161538,22161539,22161540?tags=pet_fonce,mal_croppe,environnement,metal,carton,autre,flou,pehd,pet_clair,background,papier args[1350741936] : ((1350741936, -4.5863425124957935, 492609224), (1350741936, 0.17544156254263057, 2107752395), '0.1886047378056162') no score found for photo 1350741936 We are sending mail with results at report@fotonower.com args[1350741933] : ((1350741933, -4.485918590028587, 492609224), (1350741933, 0.13291609426224957, 2107752395), '0.1886047378056162') no score found for photo 1350741933 We are sending mail with results at report@fotonower.com args[1350741771] : ((1350741771, -4.791761694346002, 492609224), (1350741771, -0.023142732787434117, 2107752395), '0.1886047378056162') no score found for photo 1350741771 We are sending mail with results at report@fotonower.com args[1350741769] : ((1350741769, -5.116094837803612, 492609224), (1350741769, -0.13001049947562174, 496442774), '0.1886047378056162') no score found for photo 1350741769 We are sending mail with results at report@fotonower.com args[1350741659] : ((1350741659, -3.704869327370497, 492609224), (1350741659, -0.12765873116211043, 496442774), '0.1886047378056162') no score found for photo 1350741659 We are sending mail with results at report@fotonower.com args[1350741627] : ((1350741627, -4.795206581216873, 492609224), (1350741627, 0.16424603726904224, 2107752395), '0.1886047378056162') no score found for photo 1350741627 We are sending mail with results at report@fotonower.com args[1350741601] : ((1350741601, -6.662065926168022, 492609224), (1350741601, -0.13338576333961702, 496442774), '0.1886047378056162') no score found for photo 1350741601 We are sending mail with results at report@fotonower.com args[1350741579] : ((1350741579, -4.548853131805146, 492609224), (1350741579, -0.1533796054207111, 496442774), '0.1886047378056162') no score found for photo 1350741579 We are sending mail with results at report@fotonower.com args[1350741267] : ((1350741267, -2.7228636579655916, 492609224), (1350741267, -0.13085905118211583, 496442774), '0.1886047378056162') no score found for photo 1350741267 We are sending mail with results at report@fotonower.com args[1350741217] : ((1350741217, -4.313650452107773, 492609224), (1350741217, 0.035574943650856554, 2107752395), '0.1886047378056162') no score found for photo 1350741217 We are sending mail with results at report@fotonower.com args[1350741215] : ((1350741215, -5.0305164602770995, 492609224), (1350741215, 0.08958358328889889, 2107752395), '0.1886047378056162') no score found for photo 1350741215 We are sending mail with results at report@fotonower.com args[1350741212] : ((1350741212, -7.050535785015862, 492609224), (1350741212, -0.06392565577841187, 2107752395), '0.1886047378056162') no score found for photo 1350741212 We are sending mail with results at report@fotonower.com args[1350738338] : ((1350738338, -5.279758164945922, 492609224), (1350738338, 0.012446008028709417, 2107752395), '0.1886047378056162') no score found for photo 1350738338 We are sending mail with results at report@fotonower.com args[1350738296] : ((1350738296, -3.5364295671226276, 492609224), (1350738296, -0.10219901258215873, 496442774), '0.1886047378056162') no score found for photo 1350738296 We are sending mail with results at report@fotonower.com args[1350737578] : ((1350737578, -3.677805825302462, 492609224), (1350737578, 0.049512782411585805, 2107752395), '0.1886047378056162') no score found for photo 1350737578 We are sending mail with results at report@fotonower.com args[1350737511] : ((1350737511, -4.58087681266481, 492609224), (1350737511, 0.04507254857305283, 2107752395), '0.1886047378056162') no score found for photo 1350737511 We are sending mail with results at report@fotonower.com args[1350737419] : ((1350737419, -4.726598228452, 492609224), (1350737419, 0.004046256242473728, 2107752395), '0.1886047378056162') no score found for photo 1350737419 We are sending mail with results at report@fotonower.com args[1350737410] : ((1350737410, -5.118321949394586, 492609224), (1350737410, -0.04186029940491124, 2107752395), '0.1886047378056162') no score found for photo 1350737410 We are sending mail with results at report@fotonower.com args[1350737230] : ((1350737230, -3.088634676644146, 492609224), (1350737230, -0.01762395891483924, 2107752395), '0.1886047378056162') no score found for photo 1350737230 We are sending mail with results at report@fotonower.com args[1350737086] : ((1350737086, -5.933493571799441, 492609224), (1350737086, 0.03502284526148775, 2107752395), '0.1886047378056162') no score found for photo 1350737086 We are sending mail with results at report@fotonower.com args[1350736919] : ((1350736919, -1.1221102024637264, 492688767), (1350736919, -0.03785309881188417, 2107752395), '0.1886047378056162') no score found for photo 1350736919 We are sending mail with results at report@fotonower.com args[1350736896] : ((1350736896, -5.026987557889799, 492609224), (1350736896, -0.3841873467813383, 496442774), '0.1886047378056162') no score found for photo 1350736896 We are sending mail with results at report@fotonower.com args[1350736747] : ((1350736747, -2.8465483447373607, 492609224), (1350736747, -0.21641829580396021, 496442774), '0.1886047378056162') no score found for photo 1350736747 We are sending mail with results at report@fotonower.com args[1350736614] : ((1350736614, -4.419635745812991, 492609224), (1350736614, -0.049241870244774145, 2107752395), '0.1886047378056162') no score found for photo 1350736614 We are sending mail with results at report@fotonower.com refus_total : 0.1886047378056162 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=22161073 AND mpp.hide_status=0 ORDER BY mpp.order LIMIT 0, 1000 SELECT photo_id, url FROM MTRBack.photos ph WHERE photo_id IN (1350741936,1350737086,1350741769,1350737419,1350737511,1350737578,1350738296,1350736614,1350741217,1350741212,1350741933,1350741771,1350741659,1350741627,1350741601,1350741579,1350741267,1350741215,1350738338,1350737410) Found this number of photos: 20 begin to download photo : 1350741936 begin to download photo : 1350737578 begin to download photo : 1350741933 begin to download photo : 1350741579 download finish for photo 1350741933 begin to download photo : 1350741771 download finish for photo 1350737578 begin to download photo : 1350738296 download finish for photo 1350741936 begin to download photo : 1350737086 download finish for photo 1350741579 begin to download photo : 1350741267 download finish for photo 1350741267 begin to download photo : 1350741215 download finish for photo 1350737086 begin to download photo : 1350741769 download finish for photo 1350738296 begin to download photo : 1350736614 download finish for photo 1350741215 begin to download photo : 1350738338 download finish for photo 1350741769 begin to download photo : 1350737419 download finish for photo 1350741771 begin to download photo : 1350741659 download finish for photo 1350736614 begin to download photo : 1350741217 download finish for photo 1350741659 begin to download photo : 1350741627 download finish for photo 1350737419 begin to download photo : 1350737511 download finish for photo 1350738338 begin to download photo : 1350737410 download finish for photo 1350741217 begin to download photo : 1350741212 download finish for photo 1350741627 begin to download photo : 1350741601 download finish for photo 1350737410 download finish for photo 1350737511 download finish for photo 1350741212 download finish for photo 1350741601 start upload file to ovh https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P22161073_09-04-2025_12_52_49.pdf results_Auto_P22161073_09-04-2025_12_52_49.pdf uploaded to url https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P22161073_09-04-2025_12_52_49.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','22161073','results_Auto_P22161073_09-04-2025_12_52_49.pdf','https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P22161073_09-04-2025_12_52_49.pdf','pdf','','1.2','0.1886047378056162') message_in_mail: Bonjour,
Veuillez trouver ci dessous les résultats du service carac on demand pour le portfolio: https://www.fotonower.com/view/22161073


Dans ces conditions,le taux de refus est: 18.86%
Veuillez trouver les photos des contaminants.

exemples de contaminants: pet_fonce: https://www.fotonower.com/view/22161530?limit=200
exemples de contaminants: metal: https://www.fotonower.com/view/22161533?limit=200
exemples de contaminants: carton: https://www.fotonower.com/view/22161534?limit=200
exemples de contaminants: autre: https://www.fotonower.com/view/22161535?limit=200
exemples de contaminants: pehd: https://www.fotonower.com/view/22161537?limit=200
exemples de contaminants: pet_clair: https://www.fotonower.com/view/22161538?limit=200
exemples de contaminants: papier: https://www.fotonower.com/view/22161540?limit=200
Veuillez trouver le rapport en pdf:https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P22161073_09-04-2025_12_52_49.pdf.

Lien vers velours :https://www.fotonower.com/velours/22161530,22161531,22161532,22161533,22161534,22161535,22161536,22161537,22161538,22161539,22161540?tags=pet_fonce,mal_croppe,environnement,metal,carton,autre,flou,pehd,pet_clair,background,papier.


L'équipe Fotonower 202 b'' Server: nginx Date: Wed, 09 Apr 2025 10:53:03 GMT Content-Length: 0 Connection: close X-Message-Id: tRlf7lg1TOqbEVTNHHaYFQ 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 [1350741936, 1350741933, 1350741771, 1350741769, 1350741659, 1350741627, 1350741601, 1350741579, 1350741267, 1350741217, 1350741215, 1350741212, 1350738338, 1350738296, 1350737578, 1350737511, 1350737419, 1350737410, 1350737230, 1350737086, 1350736919, 1350736896, 1350736747, 1350736614] 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, '2734295') ('3318', '22161073', '1350741936', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741933', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741771', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741769', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741659', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741627', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741601', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741579', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741267', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741217', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741215', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741212', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350738338', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350738296', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350737578', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350737511', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350737419', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350737410', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350737230', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350737086', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350736919', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350736896', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350736747', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350736614', None, None, None, None, None, '2734295') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 24 time used for this insertion : 1.2496540546417236 save_final save missing photos in datou_result : time spend for datou_step_exec : 13.854499578475952 time spend to save output : 1.2500011920928955 total time spend for step 9 : 15.104500770568848 step10:split_time_score Wed Apr 9 12:53:04 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'}] (('11', 24),) ERROR counted https://github.com/fotonower/Velours/issues/663#issuecomment-421136223 {} 09042025 22161073 Nombre de photos uploadées : 24 / 23040 (0%) 09042025 22161073 Nombre de photos taguées (types de déchets): 0 / 24 (0%) 09042025 22161073 Nombre de photos taguées (volume) : 0 / 24 (0%) elapsed_time : load_data_split_time_score 3.337860107421875e-06 elapsed_time : order_list_meta_photo_and_scores 1.0013580322265625e-05 ???????????????????????? elapsed_time : fill_and_build_computed_from_old_data 0.0008676052093505859 elapsed_time : insert_dashboard_record_day_entry 0.05693221092224121 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 = 22161064 order by id desc limit 1 Qualite : 0.04609045052441947 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P22161067_09-04-2025_12_22_45.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 22161067 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`=22161067 AND mptpi.`type`=3726 To do Qualite : 0.1886047378056162 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P22161073_09-04-2025_12_52_49.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 22161073 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`=22161073 AND mptpi.`type`=3594 To do Qualite : 0.22379874656749282 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P22161075_09-04-2025_12_27_09.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 22161075 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`=22161075 AND mptpi.`type`=3594 To do NUMBER BATCH : 0 # DISPLAY ALL COLLECTED DATA : {'09042025': {'nb_upload': 24, '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 [1350741936, 1350741933, 1350741771, 1350741769, 1350741659, 1350741627, 1350741601, 1350741579, 1350741267, 1350741217, 1350741215, 1350741212, 1350738338, 1350738296, 1350737578, 1350737511, 1350737419, 1350737410, 1350737230, 1350737086, 1350736919, 1350736896, 1350736747, 1350736614] Looping around the photos to save general results len do output : 1 /22161073Didn'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, '2734295') ('3318', '22161073', '1350741936', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741933', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741771', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741769', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741659', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741627', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741601', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741579', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741267', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741217', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741215', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350741212', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350738338', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350738296', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350737578', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350737511', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350737419', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350737410', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350737230', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350737086', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350736919', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350736896', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350736747', None, None, None, None, None, '2734295') ('3318', None, None, None, None, None, None, None, '2734295') ('3318', '22161073', '1350736614', None, None, None, None, None, '2734295') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 25 time used for this insertion : 0.01600050926208496 save_final save missing photos in datou_result : time spend for datou_step_exec : 1.302473545074463 time spend to save output : 0.016358137130737305 total time spend for step 10 : 1.3188316822052002 caffe_path_current : /home/admin/workarea/git/Velours/python/mtr/datou/detect_blur_image.py:82: RuntimeWarning: Degrees of freedom <= 0 for slice variance = laplacian[10:(x-10),10:(y-10)].var() /home/admin/.local/lib/python3.8/site-packages/numpy/core/_methods.py:222: RuntimeWarning: invalid value encountered in true_divide arrmean = um.true_divide(arrmean, div, out=arrmean, casting='unsafe', /home/admin/.local/lib/python3.8/site-packages/numpy/core/_methods.py:254: RuntimeWarning: invalid value encountered in double_scalars ret = ret.dtype.type(ret / rcount) About to save ! 2 After save, about to update current ! ret : 2 len(input) + len(total_photo_id_missing) : 24 set_done_treatment 614.51user 305.31system 22:40.07elapsed 67%CPU (0avgtext+0avgdata 9730632maxresident)k 35381784inputs+407424outputs (1083771major+54678505minor)pagefaults 0swaps