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 : 2986256 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 : ['2714574'] with mtr_portfolio_ids : ['21958970'] and first list_photo_ids : [] new path : /proc/2986256/ 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 , BFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 21 ; length of list_pids : 21 ; length of list_args : 21 time to download the photos : 3.675989866256714 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 Tue Apr 1 22:30:31 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Beginning of datou step mask_detect ! save_polygon : True begin detect begin to check gpu status inside check gpu memory l 3637 free memory gpu now : 6814 max_wait_temp : 1 max_wait : 0 gpu_flag : 0 2025-04-01 22:30:34.432078: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2025-04-01 22:30:34.459146: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493065000 Hz 2025-04-01 22:30:34.461070: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7feeb8000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-04-01 22:30:34.461139: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-04-01 22:30:34.465354: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-04-01 22:30:34.610024: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x97faa60 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-04-01 22:30:34.610085: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-04-01 22:30:34.611353: 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 2025-04-01 22:30:34.611777: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-04-01 22:30:34.614909: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-04-01 22:30:34.617926: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-04-01 22:30:34.618434: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-04-01 22:30:34.621166: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-04-01 22:30:34.622353: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-04-01 22:30:34.626928: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-04-01 22:30:34.628223: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-04-01 22:30:34.628300: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-04-01 22:30:34.628971: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-04-01 22:30:34.628987: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-04-01 22:30:34.628996: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-04-01 22:30:34.630527: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 6119 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. 2025-04-01 22:30:34.994880: 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 2025-04-01 22:30:34.994983: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-04-01 22:30:34.995005: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-04-01 22:30:34.995024: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-04-01 22:30:34.995042: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-04-01 22:30:34.995059: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-04-01 22:30:34.995077: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-04-01 22:30:34.995094: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-04-01 22:30:34.996366: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-04-01 22:30:34.997684: 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 2025-04-01 22:30:34.997768: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-04-01 22:30:34.997791: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-04-01 22:30:34.997812: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-04-01 22:30:34.997832: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-04-01 22:30:34.997852: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-04-01 22:30:34.997871: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-04-01 22:30:34.997891: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-04-01 22:30:34.999297: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-04-01 22:30:34.999363: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-04-01 22:30:34.999379: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-04-01 22:30:34.999389: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-04-01 22:30:35.000764: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 6119 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 : [] 2025-04-01 22:30:46.916695: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-04-01 22:30:47.192092: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-04-01 22:30:49.005292: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.008445: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 3.60G (3865470464 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.008994: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 3.24G (3478923264 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.009526: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.92G (3131030784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.010064: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.62G (2817927680 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.010595: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.36G (2536134912 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.011135: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.12G (2282521344 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.011171: 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. 2025-04-01 22:30:49.011895: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.011914: 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. 2025-04-01 22:30:49.018436: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.018488: 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. 2025-04-01 22:30:49.019252: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.019275: 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. 2025-04-01 22:30:49.025573: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.025643: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 466.56MiB 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. 2025-04-01 22:30:49.026349: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.026369: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 466.56MiB 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. 2025-04-01 22:30:49.053080: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.053128: 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. 2025-04-01 22:30:49.053642: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.053657: 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. 2025-04-01 22:30:49.059056: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.059101: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 243.25MiB 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. 2025-04-01 22:30:49.059652: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.059670: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 243.25MiB 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. 2025-04-01 22:30:49.087816: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.088429: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.090163: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.090775: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.126951: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.127530: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.129500: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.130050: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.155436: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.156020: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.157546: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.158097: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.164751: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.165335: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.167046: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.167610: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.174014: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.174597: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.176151: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.176706: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.204113: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.204691: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.205231: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.205782: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.209386: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.209947: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.225904: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.226531: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.227096: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.227644: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.241085: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.241676: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.242223: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.242766: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.247456: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.248033: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.252921: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.253494: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.266049: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.266633: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.271083: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.271687: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.272243: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.272812: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.273623: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.274175: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.285046: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.285629: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.286189: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.286736: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.287331: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.287898: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.288450: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.289006: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.298727: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.299353: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.305781: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.306351: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.344855: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.344914: 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. 2025-04-01 22:30:49.345866: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.346888: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.353728: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.354312: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.354876: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.355428: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.363363: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.363941: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.386983: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.387996: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.388613: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.389161: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.393196: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.393754: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.394304: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.394845: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.397574: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.406082: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.406660: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.415931: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.416487: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.417043: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.417587: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.418142: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-01 22:30:49.418690: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 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 : 21 NEW PHOTO Processing 1 images image shape: (2160, 3264, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 3264.00000 nb d'objets trouves : 100 NEW PHOTO Processing 1 images image shape: (2160, 3264, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 3264.00000 nb d'objets trouves : 98 NEW PHOTO Processing 1 images image shape: (2160, 3264, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 3264.00000 nb d'objets trouves : 100 NEW PHOTO Processing 1 images image shape: (2160, 3264, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 3264.00000 nb d'objets trouves : 100 NEW PHOTO Processing 1 images image shape: (2160, 3264, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 3264.00000 nb d'objets trouves : 100 NEW PHOTO Processing 1 images image shape: (2160, 3264, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 3264.00000 nb d'objets trouves : 100 NEW PHOTO Processing 1 images image shape: (2160, 3264, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 3264.00000 nb d'objets trouves : 97 NEW PHOTO Processing 1 images image shape: (2160, 3264, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 3264.00000 nb d'objets trouves : 100 NEW PHOTO Processing 1 images image shape: (2160, 3264, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 3264.00000 nb d'objets trouves : 100 NEW PHOTO Processing 1 images image shape: (2160, 3264, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 3264.00000 nb d'objets trouves : 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 : 74 NEW PHOTO Processing 1 images image shape: (2160, 3264, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 3264.00000 nb d'objets trouves : 66 NEW PHOTO Processing 1 images image shape: (2160, 3264, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 3264.00000 nb d'objets trouves : 66 NEW PHOTO Processing 1 images image shape: (2160, 3264, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 3264.00000 nb d'objets trouves : 66 NEW PHOTO Processing 1 images image shape: (2160, 3264, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 3264.00000 nb d'objets trouves : 75 NEW PHOTO Processing 1 images image shape: (2160, 3264, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 3264.00000 nb d'objets trouves : 100 NEW PHOTO Processing 1 images image shape: (2160, 3264, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 3264.00000 nb d'objets trouves : 100 NEW PHOTO Processing 1 images image shape: (2160, 3264, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 3264.00000 nb d'objets trouves : 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 : 100 NEW PHOTO Processing 1 images image shape: (2160, 3264, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 3264.00000 nb d'objets trouves : 100 NEW PHOTO Processing 1 images image shape: (2160, 3264, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 3264.00000 nb d'objets trouves : 100 Detection mask done ! Trying to reset tf kernel 2986772 begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 1844 tf kernel not reseted sub process len(results) : 21 len(list_Values) 0 None max_time_sub_proc : 3600 parent process len(results) : 21 len(list_Values) 0 process is alive process is alive process is alive finish correctly or not : True after detect begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 10814 list_Values should be empty [] To do loadFromThcl(), then load ParamDescType : thcl2847 Catched exception ! Connect or reconnect ! thcls : [{'id': 2847, 'mtr_user_id': 31, 'name': 'learn_RUBBIA_REFUS_AMIENS_23', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'photo_desc_type': 5275, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'}] thcl {'id': 2847, 'mtr_user_id': 31, 'name': 'learn_RUBBIA_REFUS_AMIENS_23', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'photo_desc_type': 5275, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'} Update svm_hashtag_type_desc : 5275 ['background', 'papier', 'carton', 'metal', 'pet_clair', 'autre', 'pehd', 'pet_fonce', 'environnement'] time for calcul the mask position with numpy : 0.4377131462097168 nb_pixel_total : 204651 time to create 1 rle with new method : 0.030714988708496094 length of segment : 533 time for calcul the mask position with numpy : 0.16526579856872559 nb_pixel_total : 26748 time to create 1 rle with old method : 0.03702807426452637 length of segment : 357 time for calcul the mask position with numpy : 0.10535073280334473 nb_pixel_total : 25178 time to create 1 rle with old method : 0.03698015213012695 length of segment : 201 time for calcul the mask position with numpy : 0.17456507682800293 nb_pixel_total : 45855 time to create 1 rle with old method : 0.08543133735656738 length of segment : 252 time for calcul the mask position with numpy : 0.06790590286254883 nb_pixel_total : 14450 time to create 1 rle with old method : 0.030666589736938477 length of segment : 232 time for calcul the mask position with numpy : 0.04792904853820801 nb_pixel_total : 10788 time to create 1 rle with old method : 0.02358531951904297 length of segment : 119 time for calcul the mask position with numpy : 0.06378722190856934 nb_pixel_total : 12383 time to create 1 rle with old method : 0.028621435165405273 length of segment : 125 time for calcul the mask position with numpy : 0.08320188522338867 nb_pixel_total : 14180 time to create 1 rle with old method : 0.020658493041992188 length of segment : 169 time for calcul the mask position with numpy : 0.1915571689605713 nb_pixel_total : 41233 time to create 1 rle with old method : 0.04938483238220215 length of segment : 486 time for calcul the mask position with numpy : 0.09126877784729004 nb_pixel_total : 21836 time to create 1 rle with old method : 0.02410292625427246 length of segment : 360 time for calcul the mask position with numpy : 0.05686759948730469 nb_pixel_total : 31873 time to create 1 rle with old method : 0.036393165588378906 length of segment : 179 time for calcul the mask position with numpy : 0.1399843692779541 nb_pixel_total : 51114 time to create 1 rle with old method : 0.05929160118103027 length of segment : 329 time for calcul the mask position with numpy : 0.04538679122924805 nb_pixel_total : 20985 time to create 1 rle with old method : 0.025328397750854492 length of segment : 155 time for calcul the mask position with numpy : 0.08148336410522461 nb_pixel_total : 21057 time to create 1 rle with old method : 0.0324399471282959 length of segment : 244 time for calcul the mask position with numpy : 0.05034279823303223 nb_pixel_total : 15413 time to create 1 rle with old method : 0.021971702575683594 length of segment : 140 time for calcul the mask position with numpy : 0.0874478816986084 nb_pixel_total : 25648 time to create 1 rle with old method : 0.030308008193969727 length of segment : 250 time for calcul the mask position with numpy : 0.03943824768066406 nb_pixel_total : 14703 time to create 1 rle with old method : 0.02027130126953125 length of segment : 137 time for calcul the mask position with numpy : 0.06184554100036621 nb_pixel_total : 19553 time to create 1 rle with old method : 0.02651810646057129 length of segment : 135 time for calcul the mask position with numpy : 0.045635223388671875 nb_pixel_total : 18174 time to create 1 rle with old method : 0.030071735382080078 length of segment : 219 time for calcul the mask position with numpy : 0.07802152633666992 nb_pixel_total : 17293 time to create 1 rle with old method : 0.023451566696166992 length of segment : 199 time for calcul the mask position with numpy : 0.0432429313659668 nb_pixel_total : 21196 time to create 1 rle with old method : 0.026593685150146484 length of segment : 117 time for calcul the mask position with numpy : 0.05215620994567871 nb_pixel_total : 9404 time to create 1 rle with old method : 0.015350580215454102 length of segment : 120 time for calcul the mask position with numpy : 0.060259342193603516 nb_pixel_total : 18659 time to create 1 rle with old method : 0.024017333984375 length of segment : 139 time for calcul the mask position with numpy : 0.0823519229888916 nb_pixel_total : 19981 time to create 1 rle with old method : 0.024691343307495117 length of segment : 124 time for calcul the mask position with numpy : 0.15188050270080566 nb_pixel_total : 42863 time to create 1 rle with old method : 0.05040764808654785 length of segment : 269 time for calcul the mask position with numpy : 0.03460049629211426 nb_pixel_total : 4714 time to create 1 rle with old method : 0.00841975212097168 length of segment : 147 time for calcul the mask position with numpy : 0.033742666244506836 nb_pixel_total : 11048 time to create 1 rle with old method : 0.0149688720703125 length of segment : 173 time for calcul the mask position with numpy : 0.06275296211242676 nb_pixel_total : 25280 time to create 1 rle with old method : 0.03009486198425293 length of segment : 175 time for calcul the mask position with numpy : 0.15637421607971191 nb_pixel_total : 65330 time to create 1 rle with old method : 0.10706567764282227 length of segment : 332 time for calcul the mask position with numpy : 0.14824247360229492 nb_pixel_total : 35022 time to create 1 rle with old method : 0.042452096939086914 length of segment : 251 time for calcul the mask position with numpy : 0.0005307197570800781 nb_pixel_total : 17430 time to create 1 rle with old method : 0.01917886734008789 length of segment : 229 time for calcul the mask position with numpy : 0.008779764175415039 nb_pixel_total : 7195 time to create 1 rle with old method : 0.010333776473999023 length of segment : 93 time for calcul the mask position with numpy : 0.030945539474487305 nb_pixel_total : 19340 time to create 1 rle with old method : 0.024801254272460938 length of segment : 161 time for calcul the mask position with numpy : 0.14029955863952637 nb_pixel_total : 36498 time to create 1 rle with old method : 0.04921269416809082 length of segment : 288 time for calcul the mask position with numpy : 0.008516311645507812 nb_pixel_total : 5734 time to create 1 rle with old method : 0.011504888534545898 length of segment : 158 time for calcul the mask position with numpy : 0.02002573013305664 nb_pixel_total : 12846 time to create 1 rle with old method : 0.019675016403198242 length of segment : 166 time for calcul the mask position with numpy : 0.037438154220581055 nb_pixel_total : 9318 time to create 1 rle with old method : 0.016809463500976562 length of segment : 98 time for calcul the mask position with numpy : 0.02261972427368164 nb_pixel_total : 6757 time to create 1 rle with old method : 0.0072743892669677734 length of segment : 97 time for calcul the mask position with numpy : 0.42806506156921387 nb_pixel_total : 118315 time to create 1 rle with old method : 0.1414344310760498 length of segment : 653 time for calcul the mask position with numpy : 0.008317947387695312 nb_pixel_total : 6282 time to create 1 rle with old method : 0.011069536209106445 length of segment : 75 time for calcul the mask position with numpy : 0.13882207870483398 nb_pixel_total : 31411 time to create 1 rle with old method : 0.03737640380859375 length of segment : 239 time for calcul the mask position with numpy : 0.010081052780151367 nb_pixel_total : 6281 time to create 1 rle with old method : 0.011551618576049805 length of segment : 111 time for calcul the mask position with numpy : 0.030757904052734375 nb_pixel_total : 8329 time to create 1 rle with old method : 0.009462356567382812 length of segment : 106 time for calcul the mask position with numpy : 0.016565799713134766 nb_pixel_total : 24822 time to create 1 rle with old method : 0.036650896072387695 length of segment : 296 time for calcul the mask position with numpy : 0.04215526580810547 nb_pixel_total : 20596 time to create 1 rle with old method : 0.03202533721923828 length of segment : 138 time for calcul the mask position with numpy : 0.04202151298522949 nb_pixel_total : 14866 time to create 1 rle with old method : 0.019217729568481445 length of segment : 139 time for calcul the mask position with numpy : 0.0405881404876709 nb_pixel_total : 38252 time to create 1 rle with old method : 0.05105423927307129 length of segment : 286 time for calcul the mask position with numpy : 0.022343873977661133 nb_pixel_total : 8686 time to create 1 rle with old method : 0.014654397964477539 length of segment : 123 time for calcul the mask position with numpy : 0.020360946655273438 nb_pixel_total : 7117 time to create 1 rle with old method : 0.013506650924682617 length of segment : 138 time for calcul the mask position with numpy : 0.01777935028076172 nb_pixel_total : 42603 time to create 1 rle with old method : 0.054499149322509766 length of segment : 176 time for calcul the mask position with numpy : 0.027715206146240234 nb_pixel_total : 35392 time to create 1 rle with old method : 0.04591655731201172 length of segment : 272 time for calcul the mask position with numpy : 0.11408400535583496 nb_pixel_total : 49056 time to create 1 rle with old method : 0.05972599983215332 length of segment : 193 time for calcul the mask position with numpy : 0.0003237724304199219 nb_pixel_total : 10189 time to create 1 rle with old method : 0.01198124885559082 length of segment : 98 time for calcul the mask position with numpy : 0.07930302619934082 nb_pixel_total : 43478 time to create 1 rle with old method : 0.049996137619018555 length of segment : 279 time for calcul the mask position with numpy : 0.0063724517822265625 nb_pixel_total : 9486 time to create 1 rle with old method : 0.01260995864868164 length of segment : 188 time for calcul the mask position with numpy : 0.05493807792663574 nb_pixel_total : 10373 time to create 1 rle with old method : 0.014702081680297852 length of segment : 145 time for calcul the mask position with numpy : 0.3060269355773926 nb_pixel_total : 36813 time to create 1 rle with old method : 0.04349851608276367 length of segment : 298 time for calcul the mask position with numpy : 0.14632916450500488 nb_pixel_total : 31955 time to create 1 rle with old method : 0.037215232849121094 length of segment : 284 time for calcul the mask position with numpy : 0.05506467819213867 nb_pixel_total : 19194 time to create 1 rle with old method : 0.023361682891845703 length of segment : 101 time for calcul the mask position with numpy : 0.042542457580566406 nb_pixel_total : 14079 time to create 1 rle with old method : 0.019638538360595703 length of segment : 144 time for calcul the mask position with numpy : 0.12833690643310547 nb_pixel_total : 32602 time to create 1 rle with old method : 0.03692126274108887 length of segment : 235 time for calcul the mask position with numpy : 0.08546185493469238 nb_pixel_total : 37742 time to create 1 rle with old method : 0.044763803482055664 length of segment : 235 time for calcul the mask position with numpy : 0.03861093521118164 nb_pixel_total : 11153 time to create 1 rle with old method : 0.017386198043823242 length of segment : 103 time for calcul the mask position with numpy : 0.11756229400634766 nb_pixel_total : 30192 time to create 1 rle with old method : 0.03691887855529785 length of segment : 267 time for calcul the mask position with numpy : 0.07183575630187988 nb_pixel_total : 26088 time to create 1 rle with old method : 0.032720088958740234 length of segment : 190 time for calcul the mask position with numpy : 0.10430574417114258 nb_pixel_total : 34918 time to create 1 rle with old method : 0.040987253189086914 length of segment : 587 time for calcul the mask position with numpy : 0.10620284080505371 nb_pixel_total : 32685 time to create 1 rle with old method : 0.03848886489868164 length of segment : 198 time for calcul the mask position with numpy : 0.07906341552734375 nb_pixel_total : 16720 time to create 1 rle with old method : 0.02211904525756836 length of segment : 122 time for calcul the mask position with numpy : 0.028550386428833008 nb_pixel_total : 7933 time to create 1 rle with old method : 0.013086795806884766 length of segment : 101 time for calcul the mask position with numpy : 0.04489588737487793 nb_pixel_total : 11863 time to create 1 rle with old method : 0.0167999267578125 length of segment : 202 time for calcul the mask position with numpy : 0.09214568138122559 nb_pixel_total : 27309 time to create 1 rle with old method : 0.03654360771179199 length of segment : 204 time for calcul the mask position with numpy : 0.08607316017150879 nb_pixel_total : 24566 time to create 1 rle with old method : 0.03795433044433594 length of segment : 182 time for calcul the mask position with numpy : 0.1819603443145752 nb_pixel_total : 57071 time to create 1 rle with old method : 0.06327056884765625 length of segment : 256 time for calcul the mask position with numpy : 0.134535551071167 nb_pixel_total : 43835 time to create 1 rle with old method : 0.05101299285888672 length of segment : 348 time for calcul the mask position with numpy : 0.09319162368774414 nb_pixel_total : 36375 time to create 1 rle with old method : 0.041550636291503906 length of segment : 268 time for calcul the mask position with numpy : 0.11493134498596191 nb_pixel_total : 39847 time to create 1 rle with old method : 0.04835844039916992 length of segment : 172 time for calcul the mask position with numpy : 0.023205995559692383 nb_pixel_total : 8288 time to create 1 rle with old method : 0.01386117935180664 length of segment : 94 time for calcul the mask position with numpy : 0.1200261116027832 nb_pixel_total : 43554 time to create 1 rle with old method : 0.0547785758972168 length of segment : 406 time for calcul the mask position with numpy : 0.013188362121582031 nb_pixel_total : 3783 time to create 1 rle with old method : 0.006990194320678711 length of segment : 86 time for calcul the mask position with numpy : 0.1459333896636963 nb_pixel_total : 42116 time to create 1 rle with old method : 0.047760009765625 length of segment : 256 time for calcul the mask position with numpy : 0.13031554222106934 nb_pixel_total : 49352 time to create 1 rle with old method : 0.05583071708679199 length of segment : 266 time for calcul the mask position with numpy : 0.13672327995300293 nb_pixel_total : 42168 time to create 1 rle with old method : 0.04825997352600098 length of segment : 276 time for calcul the mask position with numpy : 0.13509273529052734 nb_pixel_total : 67998 time to create 1 rle with old method : 0.08334994316101074 length of segment : 428 time for calcul the mask position with numpy : 0.04898428916931152 nb_pixel_total : 15449 time to create 1 rle with old method : 0.021112680435180664 length of segment : 102 time for calcul the mask position with numpy : 0.05359601974487305 nb_pixel_total : 13992 time to create 1 rle with old method : 0.018359899520874023 length of segment : 178 time for calcul the mask position with numpy : 0.11681914329528809 nb_pixel_total : 13409 time to create 1 rle with old method : 0.020446300506591797 length of segment : 225 time for calcul the mask position with numpy : 0.045709848403930664 nb_pixel_total : 18136 time to create 1 rle with old method : 0.02500319480895996 length of segment : 149 time for calcul the mask position with numpy : 0.10101151466369629 nb_pixel_total : 25350 time to create 1 rle with old method : 0.032349348068237305 length of segment : 273 time for calcul the mask position with numpy : 0.2231893539428711 nb_pixel_total : 74723 time to create 1 rle with old method : 0.08274650573730469 length of segment : 421 time for calcul the mask position with numpy : 0.007447242736816406 nb_pixel_total : 5001 time to create 1 rle with old method : 0.005425930023193359 length of segment : 74 time for calcul the mask position with numpy : 0.04695606231689453 nb_pixel_total : 30775 time to create 1 rle with old method : 0.041692495346069336 length of segment : 272 time for calcul the mask position with numpy : 0.14542150497436523 nb_pixel_total : 59299 time to create 1 rle with old method : 0.07006311416625977 length of segment : 299 time for calcul the mask position with numpy : 0.042127370834350586 nb_pixel_total : 12580 time to create 1 rle with old method : 0.01876091957092285 length of segment : 122 time for calcul the mask position with numpy : 0.003351926803588867 nb_pixel_total : 10457 time to create 1 rle with old method : 0.014755010604858398 length of segment : 129 time for calcul the mask position with numpy : 0.03109884262084961 nb_pixel_total : 6300 time to create 1 rle with old method : 0.009555339813232422 length of segment : 69 time for calcul the mask position with numpy : 0.09272503852844238 nb_pixel_total : 16592 time to create 1 rle with old method : 0.02625894546508789 length of segment : 181 time for calcul the mask position with numpy : 0.18806099891662598 nb_pixel_total : 59361 time to create 1 rle with old method : 0.06668710708618164 length of segment : 279 time for calcul the mask position with numpy : 0.06342649459838867 nb_pixel_total : 12246 time to create 1 rle with old method : 0.017627716064453125 length of segment : 154 time for calcul the mask position with numpy : 0.028841257095336914 nb_pixel_total : 13178 time to create 1 rle with old method : 0.0168912410736084 length of segment : 223 time for calcul the mask position with numpy : 0.2163393497467041 nb_pixel_total : 59535 time to create 1 rle with old method : 0.0672903060913086 length of segment : 359 time for calcul the mask position with numpy : 0.06614470481872559 nb_pixel_total : 13037 time to create 1 rle with old method : 0.019397258758544922 length of segment : 166 time for calcul the mask position with numpy : 0.07408380508422852 nb_pixel_total : 23206 time to create 1 rle with old method : 0.02778339385986328 length of segment : 161 time for calcul the mask position with numpy : 0.06518006324768066 nb_pixel_total : 20253 time to create 1 rle with old method : 0.02848672866821289 length of segment : 170 time for calcul the mask position with numpy : 0.12224912643432617 nb_pixel_total : 22400 time to create 1 rle with old method : 0.02889561653137207 length of segment : 227 time for calcul the mask position with numpy : 0.021846294403076172 nb_pixel_total : 5876 time to create 1 rle with old method : 0.011006355285644531 length of segment : 85 time for calcul the mask position with numpy : 0.10337138175964355 nb_pixel_total : 24327 time to create 1 rle with old method : 0.03189659118652344 length of segment : 239 time for calcul the mask position with numpy : 0.21846365928649902 nb_pixel_total : 51811 time to create 1 rle with old method : 0.06390261650085449 length of segment : 455 time for calcul the mask position with numpy : 0.02579188346862793 nb_pixel_total : 7621 time to create 1 rle with old method : 0.009396791458129883 length of segment : 74 time for calcul the mask position with numpy : 0.02562713623046875 nb_pixel_total : 6503 time to create 1 rle with old method : 0.011378049850463867 length of segment : 91 time for calcul the mask position with numpy : 0.09517788887023926 nb_pixel_total : 22634 time to create 1 rle with old method : 0.02800750732421875 length of segment : 290 time for calcul the mask position with numpy : 0.09186625480651855 nb_pixel_total : 28039 time to create 1 rle with old method : 0.035301923751831055 length of segment : 205 time for calcul the mask position with numpy : 0.0268099308013916 nb_pixel_total : 9690 time to create 1 rle with old method : 0.01540517807006836 length of segment : 140 time for calcul the mask position with numpy : 0.10036301612854004 nb_pixel_total : 22559 time to create 1 rle with old method : 0.028005361557006836 length of segment : 230 time for calcul the mask position with numpy : 0.07402777671813965 nb_pixel_total : 23362 time to create 1 rle with old method : 0.029923439025878906 length of segment : 211 time for calcul the mask position with numpy : 0.10435009002685547 nb_pixel_total : 35740 time to create 1 rle with old method : 0.0432589054107666 length of segment : 343 time for calcul the mask position with numpy : 0.05149674415588379 nb_pixel_total : 25520 time to create 1 rle with old method : 0.027913331985473633 length of segment : 270 time for calcul the mask position with numpy : 0.08997154235839844 nb_pixel_total : 22439 time to create 1 rle with old method : 0.02850508689880371 length of segment : 288 time for calcul the mask position with numpy : 0.06374669075012207 nb_pixel_total : 31197 time to create 1 rle with old method : 0.038205623626708984 length of segment : 201 time for calcul the mask position with numpy : 0.07360577583312988 nb_pixel_total : 34177 time to create 1 rle with old method : 0.04281949996948242 length of segment : 434 time for calcul the mask position with numpy : 0.07164883613586426 nb_pixel_total : 28203 time to create 1 rle with old method : 0.037339210510253906 length of segment : 177 time for calcul the mask position with numpy : 0.02736806869506836 nb_pixel_total : 6503 time to create 1 rle with old method : 0.01229238510131836 length of segment : 89 time for calcul the mask position with numpy : 0.11486196517944336 nb_pixel_total : 33418 time to create 1 rle with old method : 0.04066920280456543 length of segment : 393 time for calcul the mask position with numpy : 0.015614509582519531 nb_pixel_total : 6003 time to create 1 rle with old method : 0.011587142944335938 length of segment : 90 time for calcul the mask position with numpy : 0.1085515022277832 nb_pixel_total : 50579 time to create 1 rle with old method : 0.059290409088134766 length of segment : 347 time for calcul the mask position with numpy : 0.04662322998046875 nb_pixel_total : 19779 time to create 1 rle with old method : 0.026019573211669922 length of segment : 192 time for calcul the mask position with numpy : 0.03109145164489746 nb_pixel_total : 8775 time to create 1 rle with old method : 0.015293598175048828 length of segment : 117 time for calcul the mask position with numpy : 0.07604718208312988 nb_pixel_total : 25284 time to create 1 rle with old method : 0.029796361923217773 length of segment : 193 time for calcul the mask position with numpy : 0.052803993225097656 nb_pixel_total : 15231 time to create 1 rle with old method : 0.02614450454711914 length of segment : 174 time for calcul the mask position with numpy : 0.04007077217102051 nb_pixel_total : 26963 time to create 1 rle with old method : 0.03643465042114258 length of segment : 142 time for calcul the mask position with numpy : 0.12901043891906738 nb_pixel_total : 29702 time to create 1 rle with old method : 0.03427910804748535 length of segment : 287 time for calcul the mask position with numpy : 0.1535656452178955 nb_pixel_total : 27546 time to create 1 rle with old method : 0.0316159725189209 length of segment : 336 time for calcul the mask position with numpy : 0.07670927047729492 nb_pixel_total : 44214 time to create 1 rle with old method : 0.054543256759643555 length of segment : 279 time for calcul the mask position with numpy : 0.13038015365600586 nb_pixel_total : 51385 time to create 1 rle with old method : 0.05943703651428223 length of segment : 263 time for calcul the mask position with numpy : 0.15796303749084473 nb_pixel_total : 67011 time to create 1 rle with old method : 0.07700037956237793 length of segment : 259 time for calcul the mask position with numpy : 0.06820535659790039 nb_pixel_total : 48118 time to create 1 rle with old method : 0.05510115623474121 length of segment : 328 time for calcul the mask position with numpy : 0.08501672744750977 nb_pixel_total : 22466 time to create 1 rle with old method : 0.02988290786743164 length of segment : 164 time for calcul the mask position with numpy : 0.44502949714660645 nb_pixel_total : 202568 time to create 1 rle with new method : 0.021494626998901367 length of segment : 717 time for calcul the mask position with numpy : 0.014600753784179688 nb_pixel_total : 14677 time to create 1 rle with old method : 0.01603078842163086 length of segment : 112 time for calcul the mask position with numpy : 0.054308414459228516 nb_pixel_total : 12673 time to create 1 rle with old method : 0.01920032501220703 length of segment : 174 time for calcul the mask position with numpy : 0.012436151504516602 nb_pixel_total : 18597 time to create 1 rle with old method : 0.026244640350341797 length of segment : 190 time for calcul the mask position with numpy : 0.007804155349731445 nb_pixel_total : 14636 time to create 1 rle with old method : 0.019642114639282227 length of segment : 190 time for calcul the mask position with numpy : 0.03556418418884277 nb_pixel_total : 6666 time to create 1 rle with old method : 0.010173797607421875 length of segment : 145 time for calcul the mask position with numpy : 0.10621857643127441 nb_pixel_total : 21491 time to create 1 rle with old method : 0.02720808982849121 length of segment : 349 time for calcul the mask position with numpy : 0.2377932071685791 nb_pixel_total : 72762 time to create 1 rle with old method : 0.0803985595703125 length of segment : 449 time for calcul the mask position with numpy : 0.050322532653808594 nb_pixel_total : 23942 time to create 1 rle with old method : 0.030571937561035156 length of segment : 210 time for calcul the mask position with numpy : 0.019488096237182617 nb_pixel_total : 39880 time to create 1 rle with old method : 0.04772830009460449 length of segment : 262 time for calcul the mask position with numpy : 0.052991390228271484 nb_pixel_total : 43178 time to create 1 rle with old method : 0.05325889587402344 length of segment : 274 time for calcul the mask position with numpy : 0.1884162425994873 nb_pixel_total : 77090 time to create 1 rle with old method : 0.08451962471008301 length of segment : 371 time for calcul the mask position with numpy : 0.028666257858276367 nb_pixel_total : 10189 time to create 1 rle with old method : 0.01670551300048828 length of segment : 109 time for calcul the mask position with numpy : 0.07802677154541016 nb_pixel_total : 35832 time to create 1 rle with old method : 0.042459726333618164 length of segment : 244 time for calcul the mask position with numpy : 0.036710262298583984 nb_pixel_total : 33946 time to create 1 rle with old method : 0.04388284683227539 length of segment : 374 time for calcul the mask position with numpy : 0.05286717414855957 nb_pixel_total : 12847 time to create 1 rle with old method : 0.016693115234375 length of segment : 225 time for calcul the mask position with numpy : 0.06444787979125977 nb_pixel_total : 51258 time to create 1 rle with old method : 0.058573246002197266 length of segment : 303 time for calcul the mask position with numpy : 0.045745134353637695 nb_pixel_total : 26229 time to create 1 rle with old method : 0.032105207443237305 length of segment : 168 time for calcul the mask position with numpy : 0.04716324806213379 nb_pixel_total : 19679 time to create 1 rle with old method : 0.027567386627197266 length of segment : 124 time for calcul the mask position with numpy : 0.04342198371887207 nb_pixel_total : 26695 time to create 1 rle with old method : 0.030904054641723633 length of segment : 312 time for calcul the mask position with numpy : 0.0751650333404541 nb_pixel_total : 41361 time to create 1 rle with old method : 0.04955887794494629 length of segment : 288 time for calcul the mask position with numpy : 0.016918182373046875 nb_pixel_total : 7553 time to create 1 rle with old method : 0.012897729873657227 length of segment : 101 time for calcul the mask position with numpy : 0.038399457931518555 nb_pixel_total : 11064 time to create 1 rle with old method : 0.018009424209594727 length of segment : 139 time for calcul the mask position with numpy : 0.023807764053344727 nb_pixel_total : 7509 time to create 1 rle with old method : 0.012902021408081055 length of segment : 119 time for calcul the mask position with numpy : 0.1602013111114502 nb_pixel_total : 93642 time to create 1 rle with old method : 0.10590767860412598 length of segment : 442 time for calcul the mask position with numpy : 0.002997159957885742 nb_pixel_total : 17891 time to create 1 rle with old method : 0.02309894561767578 length of segment : 160 time for calcul the mask position with numpy : 0.026020526885986328 nb_pixel_total : 18309 time to create 1 rle with old method : 0.02256917953491211 length of segment : 135 time for calcul the mask position with numpy : 0.09248805046081543 nb_pixel_total : 27846 time to create 1 rle with old method : 0.034737586975097656 length of segment : 304 time for calcul the mask position with numpy : 0.021773338317871094 nb_pixel_total : 14824 time to create 1 rle with old method : 0.019138813018798828 length of segment : 176 time for calcul the mask position with numpy : 0.10068702697753906 nb_pixel_total : 74748 time to create 1 rle with old method : 0.0879204273223877 length of segment : 702 time for calcul the mask position with numpy : 0.038817405700683594 nb_pixel_total : 23447 time to create 1 rle with old method : 0.03438115119934082 length of segment : 253 time for calcul the mask position with numpy : 0.07084298133850098 nb_pixel_total : 53362 time to create 1 rle with old method : 0.06407046318054199 length of segment : 284 time for calcul the mask position with numpy : 0.0008816719055175781 nb_pixel_total : 39840 time to create 1 rle with old method : 0.04752182960510254 length of segment : 279 time for calcul the mask position with numpy : 0.04076337814331055 nb_pixel_total : 12375 time to create 1 rle with old method : 0.019370079040527344 length of segment : 147 time for calcul the mask position with numpy : 0.17709827423095703 nb_pixel_total : 61468 time to create 1 rle with old method : 0.07037138938903809 length of segment : 384 time for calcul the mask position with numpy : 0.34882593154907227 nb_pixel_total : 104649 time to create 1 rle with old method : 0.12506318092346191 length of segment : 412 time for calcul the mask position with numpy : 0.11106085777282715 nb_pixel_total : 49656 time to create 1 rle with old method : 0.05865621566772461 length of segment : 378 time for calcul the mask position with numpy : 0.020513296127319336 nb_pixel_total : 5318 time to create 1 rle with old method : 0.008057355880737305 length of segment : 85 time for calcul the mask position with numpy : 0.03011465072631836 nb_pixel_total : 15664 time to create 1 rle with old method : 0.0198822021484375 length of segment : 188 time for calcul the mask position with numpy : 0.0500185489654541 nb_pixel_total : 16299 time to create 1 rle with old method : 0.02283501625061035 length of segment : 153 time for calcul the mask position with numpy : 0.05226397514343262 nb_pixel_total : 12931 time to create 1 rle with old method : 0.018220901489257812 length of segment : 172 time for calcul the mask position with numpy : 0.03467416763305664 nb_pixel_total : 8840 time to create 1 rle with old method : 0.014052391052246094 length of segment : 138 time for calcul the mask position with numpy : 0.028601884841918945 nb_pixel_total : 8088 time to create 1 rle with old method : 0.014021873474121094 length of segment : 123 time for calcul the mask position with numpy : 0.02719902992248535 nb_pixel_total : 7794 time to create 1 rle with old method : 0.02023792266845703 length of segment : 82 time for calcul the mask position with numpy : 0.08696937561035156 nb_pixel_total : 25291 time to create 1 rle with old method : 0.031778573989868164 length of segment : 202 time for calcul the mask position with numpy : 0.2862977981567383 nb_pixel_total : 60527 time to create 1 rle with old method : 0.07006120681762695 length of segment : 591 time for calcul the mask position with numpy : 0.24742770195007324 nb_pixel_total : 89080 time to create 1 rle with old method : 0.09502291679382324 length of segment : 304 time for calcul the mask position with numpy : 0.042616844177246094 nb_pixel_total : 15937 time to create 1 rle with old method : 0.022838830947875977 length of segment : 234 time for calcul the mask position with numpy : 0.02806997299194336 nb_pixel_total : 8647 time to create 1 rle with old method : 0.01404881477355957 length of segment : 111 time for calcul the mask position with numpy : 0.02079629898071289 nb_pixel_total : 5090 time to create 1 rle with old method : 0.009105443954467773 length of segment : 93 time for calcul the mask position with numpy : 0.07133746147155762 nb_pixel_total : 32134 time to create 1 rle with old method : 0.03847026824951172 length of segment : 170 time for calcul the mask position with numpy : 0.07901930809020996 nb_pixel_total : 16964 time to create 1 rle with old method : 0.022349119186401367 length of segment : 183 time for calcul the mask position with numpy : 0.045481204986572266 nb_pixel_total : 13595 time to create 1 rle with old method : 0.020728588104248047 length of segment : 145 time for calcul the mask position with numpy : 0.020345211029052734 nb_pixel_total : 9385 time to create 1 rle with old method : 0.015504598617553711 length of segment : 142 time for calcul the mask position with numpy : 0.06576848030090332 nb_pixel_total : 31261 time to create 1 rle with old method : 0.035945892333984375 length of segment : 241 time for calcul the mask position with numpy : 0.04245448112487793 nb_pixel_total : 40068 time to create 1 rle with old method : 0.04465675354003906 length of segment : 303 time for calcul the mask position with numpy : 0.16533708572387695 nb_pixel_total : 38657 time to create 1 rle with old method : 0.05853772163391113 length of segment : 372 time for calcul the mask position with numpy : 0.044522762298583984 nb_pixel_total : 16707 time to create 1 rle with old method : 0.01842331886291504 length of segment : 142 time for calcul the mask position with numpy : 0.045720577239990234 nb_pixel_total : 12867 time to create 1 rle with old method : 0.016245603561401367 length of segment : 169 time for calcul the mask position with numpy : 0.08702206611633301 nb_pixel_total : 23105 time to create 1 rle with old method : 0.02759861946105957 length of segment : 372 time for calcul the mask position with numpy : 0.08452033996582031 nb_pixel_total : 26818 time to create 1 rle with old method : 0.03242778778076172 length of segment : 285 time for calcul the mask position with numpy : 0.04193544387817383 nb_pixel_total : 26625 time to create 1 rle with old method : 0.03542280197143555 length of segment : 174 time for calcul the mask position with numpy : 0.07522153854370117 nb_pixel_total : 25403 time to create 1 rle with old method : 0.029230594635009766 length of segment : 195 time for calcul the mask position with numpy : 0.09266018867492676 nb_pixel_total : 31861 time to create 1 rle with old method : 0.0359039306640625 length of segment : 255 time for calcul the mask position with numpy : 0.06524300575256348 nb_pixel_total : 22830 time to create 1 rle with old method : 0.03036046028137207 length of segment : 163 time for calcul the mask position with numpy : 0.0005443096160888672 nb_pixel_total : 21939 time to create 1 rle with old method : 0.02645564079284668 length of segment : 164 time for calcul the mask position with numpy : 0.0830378532409668 nb_pixel_total : 44645 time to create 1 rle with old method : 0.051989078521728516 length of segment : 284 time for calcul the mask position with numpy : 0.27332615852355957 nb_pixel_total : 57033 time to create 1 rle with old method : 0.0683755874633789 length of segment : 521 time for calcul the mask position with numpy : 0.11161351203918457 nb_pixel_total : 42277 time to create 1 rle with old method : 0.05448341369628906 length of segment : 205 time for calcul the mask position with numpy : 0.09256768226623535 nb_pixel_total : 82312 time to create 1 rle with old method : 0.10132193565368652 length of segment : 502 time for calcul the mask position with numpy : 0.09053397178649902 nb_pixel_total : 26944 time to create 1 rle with old method : 0.03153085708618164 length of segment : 348 time for calcul the mask position with numpy : 0.11846613883972168 nb_pixel_total : 61797 time to create 1 rle with old method : 0.07750988006591797 length of segment : 361 time for calcul the mask position with numpy : 0.08143019676208496 nb_pixel_total : 20611 time to create 1 rle with old method : 0.028278589248657227 length of segment : 251 time for calcul the mask position with numpy : 0.005930900573730469 nb_pixel_total : 11840 time to create 1 rle with old method : 0.01739335060119629 length of segment : 153 time for calcul the mask position with numpy : 0.09108638763427734 nb_pixel_total : 46360 time to create 1 rle with old method : 0.054701805114746094 length of segment : 215 time for calcul the mask position with numpy : 0.010886907577514648 nb_pixel_total : 5480 time to create 1 rle with old method : 0.012317419052124023 length of segment : 122 time for calcul the mask position with numpy : 0.01898479461669922 nb_pixel_total : 10118 time to create 1 rle with old method : 0.01508188247680664 length of segment : 97 time for calcul the mask position with numpy : 0.07457590103149414 nb_pixel_total : 35438 time to create 1 rle with old method : 0.04239320755004883 length of segment : 266 time for calcul the mask position with numpy : 0.09435176849365234 nb_pixel_total : 33177 time to create 1 rle with old method : 0.03977155685424805 length of segment : 220 time for calcul the mask position with numpy : 0.045879364013671875 nb_pixel_total : 16123 time to create 1 rle with old method : 0.02143120765686035 length of segment : 155 time for calcul the mask position with numpy : 0.05036497116088867 nb_pixel_total : 13655 time to create 1 rle with old method : 0.021404743194580078 length of segment : 274 time for calcul the mask position with numpy : 0.06089210510253906 nb_pixel_total : 21219 time to create 1 rle with old method : 0.028052568435668945 length of segment : 207 time for calcul the mask position with numpy : 0.1614222526550293 nb_pixel_total : 75435 time to create 1 rle with old method : 0.08493566513061523 length of segment : 501 time for calcul the mask position with numpy : 0.1323080062866211 nb_pixel_total : 87905 time to create 1 rle with old method : 0.09868168830871582 length of segment : 349 time for calcul the mask position with numpy : 0.0023958683013916016 nb_pixel_total : 2728 time to create 1 rle with old method : 0.0031576156616210938 length of segment : 93 time for calcul the mask position with numpy : 0.015245914459228516 nb_pixel_total : 10766 time to create 1 rle with old method : 0.015616178512573242 length of segment : 112 time for calcul the mask position with numpy : 0.02323317527770996 nb_pixel_total : 21723 time to create 1 rle with old method : 0.027004241943359375 length of segment : 195 time for calcul the mask position with numpy : 0.01467442512512207 nb_pixel_total : 10792 time to create 1 rle with old method : 0.016954898834228516 length of segment : 138 time for calcul the mask position with numpy : 0.012001991271972656 nb_pixel_total : 9845 time to create 1 rle with old method : 0.016399621963500977 length of segment : 146 time for calcul the mask position with numpy : 0.026003599166870117 nb_pixel_total : 17500 time to create 1 rle with old method : 0.02522897720336914 length of segment : 173 time for calcul the mask position with numpy : 0.0009367465972900391 nb_pixel_total : 19562 time to create 1 rle with old method : 0.021985769271850586 length of segment : 199 time for calcul the mask position with numpy : 0.07750725746154785 nb_pixel_total : 109544 time to create 1 rle with old method : 0.12496447563171387 length of segment : 375 time for calcul the mask position with numpy : 0.047228336334228516 nb_pixel_total : 28398 time to create 1 rle with old method : 0.03999137878417969 length of segment : 160 time for calcul the mask position with numpy : 0.01514291763305664 nb_pixel_total : 68291 time to create 1 rle with old method : 0.07232451438903809 length of segment : 378 time for calcul the mask position with numpy : 0.00017452239990234375 nb_pixel_total : 5429 time to create 1 rle with old method : 0.006070137023925781 length of segment : 78 time for calcul the mask position with numpy : 0.04249238967895508 nb_pixel_total : 15708 time to create 1 rle with old method : 0.021364212036132812 length of segment : 257 time for calcul the mask position with numpy : 0.04532480239868164 nb_pixel_total : 15891 time to create 1 rle with old method : 0.02257084846496582 length of segment : 116 time for calcul the mask position with numpy : 0.061911821365356445 nb_pixel_total : 30285 time to create 1 rle with old method : 0.03814530372619629 length of segment : 302 time for calcul the mask position with numpy : 0.01511836051940918 nb_pixel_total : 15162 time to create 1 rle with old method : 0.02280592918395996 length of segment : 182 time for calcul the mask position with numpy : 0.011168956756591797 nb_pixel_total : 32132 time to create 1 rle with old method : 0.05447268486022949 length of segment : 346 time for calcul the mask position with numpy : 0.026986360549926758 nb_pixel_total : 21552 time to create 1 rle with old method : 0.026535987854003906 length of segment : 344 time for calcul the mask position with numpy : 0.013566017150878906 nb_pixel_total : 23769 time to create 1 rle with old method : 0.029927492141723633 length of segment : 170 time for calcul the mask position with numpy : 0.07372331619262695 nb_pixel_total : 6217 time to create 1 rle with old method : 0.011378288269042969 length of segment : 164 time for calcul the mask position with numpy : 0.039351701736450195 nb_pixel_total : 23185 time to create 1 rle with old method : 0.0313262939453125 length of segment : 181 time for calcul the mask position with numpy : 0.13210105895996094 nb_pixel_total : 51468 time to create 1 rle with old method : 0.06908988952636719 length of segment : 208 time for calcul the mask position with numpy : 0.12543797492980957 nb_pixel_total : 22611 time to create 1 rle with old method : 0.029815196990966797 length of segment : 276 time for calcul the mask position with numpy : 0.14083337783813477 nb_pixel_total : 47927 time to create 1 rle with old method : 0.06790566444396973 length of segment : 233 time for calcul the mask position with numpy : 0.06287026405334473 nb_pixel_total : 13453 time to create 1 rle with old method : 0.02086353302001953 length of segment : 167 time for calcul the mask position with numpy : 0.13606476783752441 nb_pixel_total : 36222 time to create 1 rle with old method : 0.04241347312927246 length of segment : 311 time for calcul the mask position with numpy : 0.038443803787231445 nb_pixel_total : 10474 time to create 1 rle with old method : 0.01585674285888672 length of segment : 137 time for calcul the mask position with numpy : 0.11439871788024902 nb_pixel_total : 40063 time to create 1 rle with old method : 0.048116207122802734 length of segment : 334 time for calcul the mask position with numpy : 0.15068459510803223 nb_pixel_total : 29470 time to create 1 rle with old method : 0.03838038444519043 length of segment : 416 time for calcul the mask position with numpy : 0.0834355354309082 nb_pixel_total : 26585 time to create 1 rle with old method : 0.03234720230102539 length of segment : 172 time for calcul the mask position with numpy : 0.22117042541503906 nb_pixel_total : 64510 time to create 1 rle with old method : 0.08696699142456055 length of segment : 338 time for calcul the mask position with numpy : 0.029809236526489258 nb_pixel_total : 6022 time to create 1 rle with old method : 0.010191679000854492 length of segment : 114 time for calcul the mask position with numpy : 0.13300347328186035 nb_pixel_total : 38332 time to create 1 rle with old method : 0.05108523368835449 length of segment : 390 time for calcul the mask position with numpy : 0.06281757354736328 nb_pixel_total : 19164 time to create 1 rle with old method : 0.028425216674804688 length of segment : 145 time for calcul the mask position with numpy : 0.09028768539428711 nb_pixel_total : 30052 time to create 1 rle with old method : 0.05497121810913086 length of segment : 239 time for calcul the mask position with numpy : 0.025307178497314453 nb_pixel_total : 29741 time to create 1 rle with old method : 0.04241347312927246 length of segment : 324 time for calcul the mask position with numpy : 0.07224702835083008 nb_pixel_total : 19566 time to create 1 rle with old method : 0.028334856033325195 length of segment : 210 time for calcul the mask position with numpy : 0.2513265609741211 nb_pixel_total : 110090 time to create 1 rle with old method : 0.1408696174621582 length of segment : 356 time for calcul the mask position with numpy : 0.19704270362854004 nb_pixel_total : 29538 time to create 1 rle with old method : 0.03756284713745117 length of segment : 222 time for calcul the mask position with numpy : 0.054702043533325195 nb_pixel_total : 12769 time to create 1 rle with old method : 0.018973827362060547 length of segment : 150 time for calcul the mask position with numpy : 0.02817368507385254 nb_pixel_total : 13097 time to create 1 rle with old method : 0.0263063907623291 length of segment : 125 time for calcul the mask position with numpy : 0.08572530746459961 nb_pixel_total : 34519 time to create 1 rle with old method : 0.042181968688964844 length of segment : 206 time for calcul the mask position with numpy : 0.05081677436828613 nb_pixel_total : 9851 time to create 1 rle with old method : 0.014957904815673828 length of segment : 158 time for calcul the mask position with numpy : 0.024549484252929688 nb_pixel_total : 5542 time to create 1 rle with old method : 0.010441780090332031 length of segment : 60 time for calcul the mask position with numpy : 0.11193060874938965 nb_pixel_total : 29794 time to create 1 rle with old method : 0.035627126693725586 length of segment : 237 time for calcul the mask position with numpy : 0.044656991958618164 nb_pixel_total : 9730 time to create 1 rle with old method : 0.014979839324951172 length of segment : 210 time for calcul the mask position with numpy : 0.040021419525146484 nb_pixel_total : 14758 time to create 1 rle with old method : 0.02149367332458496 length of segment : 141 time for calcul the mask position with numpy : 0.0775914192199707 nb_pixel_total : 44587 time to create 1 rle with old method : 0.09485340118408203 length of segment : 181 time for calcul the mask position with numpy : 0.055799007415771484 nb_pixel_total : 22505 time to create 1 rle with old method : 0.03093576431274414 length of segment : 200 time for calcul the mask position with numpy : 0.2236638069152832 nb_pixel_total : 98538 time to create 1 rle with old method : 0.12194323539733887 length of segment : 477 time for calcul the mask position with numpy : 0.03659510612487793 nb_pixel_total : 5455 time to create 1 rle with old method : 0.008196830749511719 length of segment : 171 time for calcul the mask position with numpy : 0.0001533031463623047 nb_pixel_total : 2015 time to create 1 rle with old method : 0.002544403076171875 length of segment : 62 time for calcul the mask position with numpy : 0.06693077087402344 nb_pixel_total : 20904 time to create 1 rle with old method : 0.02655482292175293 length of segment : 125 time for calcul the mask position with numpy : 0.021818876266479492 nb_pixel_total : 7684 time to create 1 rle with old method : 0.013678312301635742 length of segment : 120 time for calcul the mask position with numpy : 0.08916640281677246 nb_pixel_total : 31662 time to create 1 rle with old method : 0.03888392448425293 length of segment : 234 time for calcul the mask position with numpy : 0.052756547927856445 nb_pixel_total : 46851 time to create 1 rle with old method : 0.05014920234680176 length of segment : 263 time for calcul the mask position with numpy : 0.06072235107421875 nb_pixel_total : 22748 time to create 1 rle with old method : 0.02923130989074707 length of segment : 185 time for calcul the mask position with numpy : 0.13743805885314941 nb_pixel_total : 37200 time to create 1 rle with old method : 0.04281949996948242 length of segment : 484 time for calcul the mask position with numpy : 0.18471693992614746 nb_pixel_total : 92257 time to create 1 rle with old method : 0.10179948806762695 length of segment : 415 time for calcul the mask position with numpy : 0.021898746490478516 nb_pixel_total : 5246 time to create 1 rle with old method : 0.009300947189331055 length of segment : 89 time for calcul the mask position with numpy : 0.022030353546142578 nb_pixel_total : 13868 time to create 1 rle with old method : 0.018574953079223633 length of segment : 175 time for calcul the mask position with numpy : 0.02805805206298828 nb_pixel_total : 20724 time to create 1 rle with old method : 0.024950504302978516 length of segment : 234 time for calcul the mask position with numpy : 0.002628326416015625 nb_pixel_total : 21770 time to create 1 rle with old method : 0.02300715446472168 length of segment : 171 time for calcul the mask position with numpy : 0.024532556533813477 nb_pixel_total : 9955 time to create 1 rle with old method : 0.01635599136352539 length of segment : 124 time for calcul the mask position with numpy : 0.0031042098999023438 nb_pixel_total : 8887 time to create 1 rle with old method : 0.009641647338867188 length of segment : 127 time for calcul the mask position with numpy : 0.0634775161743164 nb_pixel_total : 26009 time to create 1 rle with old method : 0.03159618377685547 length of segment : 249 time for calcul the mask position with numpy : 0.0003199577331542969 nb_pixel_total : 13456 time to create 1 rle with old method : 0.01550745964050293 length of segment : 123 time for calcul the mask position with numpy : 0.02494215965270996 nb_pixel_total : 8772 time to create 1 rle with old method : 0.013898849487304688 length of segment : 86 time for calcul the mask position with numpy : 0.027186155319213867 nb_pixel_total : 11141 time to create 1 rle with old method : 0.01749110221862793 length of segment : 129 time for calcul the mask position with numpy : 0.028731584548950195 nb_pixel_total : 7638 time to create 1 rle with old method : 0.010822057723999023 length of segment : 114 time for calcul the mask position with numpy : 0.11754584312438965 nb_pixel_total : 44605 time to create 1 rle with old method : 0.0536189079284668 length of segment : 336 time for calcul the mask position with numpy : 0.0013530254364013672 nb_pixel_total : 7674 time to create 1 rle with old method : 0.012692451477050781 length of segment : 215 time for calcul the mask position with numpy : 0.04371976852416992 nb_pixel_total : 12733 time to create 1 rle with old method : 0.01838088035583496 length of segment : 136 time for calcul the mask position with numpy : 0.027914762496948242 nb_pixel_total : 19396 time to create 1 rle with old method : 0.02532339096069336 length of segment : 221 time for calcul the mask position with numpy : 0.05464577674865723 nb_pixel_total : 40938 time to create 1 rle with old method : 0.04851937294006348 length of segment : 212 time for calcul the mask position with numpy : 0.01559758186340332 nb_pixel_total : 7267 time to create 1 rle with old method : 0.011982917785644531 length of segment : 111 time for calcul the mask position with numpy : 0.0037391185760498047 nb_pixel_total : 697 time to create 1 rle with old method : 0.0009992122650146484 length of segment : 81 time for calcul the mask position with numpy : 0.0801689624786377 nb_pixel_total : 20841 time to create 1 rle with old method : 0.027708053588867188 length of segment : 211 time for calcul the mask position with numpy : 0.04341411590576172 nb_pixel_total : 10952 time to create 1 rle with old method : 0.020412921905517578 length of segment : 137 time for calcul the mask position with numpy : 0.036457061767578125 nb_pixel_total : 9967 time to create 1 rle with old method : 0.016736984252929688 length of segment : 100 time for calcul the mask position with numpy : 0.08926248550415039 nb_pixel_total : 38490 time to create 1 rle with old method : 0.04244732856750488 length of segment : 301 time for calcul the mask position with numpy : 0.07714128494262695 nb_pixel_total : 21396 time to create 1 rle with old method : 0.026311874389648438 length of segment : 201 time for calcul the mask position with numpy : 0.05473613739013672 nb_pixel_total : 11603 time to create 1 rle with old method : 0.015081167221069336 length of segment : 186 time for calcul the mask position with numpy : 0.09808754920959473 nb_pixel_total : 41716 time to create 1 rle with old method : 0.04985618591308594 length of segment : 275 time for calcul the mask position with numpy : 0.04331398010253906 nb_pixel_total : 16841 time to create 1 rle with old method : 0.02321314811706543 length of segment : 154 time for calcul the mask position with numpy : 0.01065206527709961 nb_pixel_total : 3914 time to create 1 rle with old method : 0.0063533782958984375 length of segment : 85 time for calcul the mask position with numpy : 0.15425539016723633 nb_pixel_total : 75847 time to create 1 rle with old method : 0.08064746856689453 length of segment : 462 time for calcul the mask position with numpy : 0.06952977180480957 nb_pixel_total : 46465 time to create 1 rle with old method : 0.05446052551269531 length of segment : 282 time for calcul the mask position with numpy : 0.0012679100036621094 nb_pixel_total : 22082 time to create 1 rle with old method : 0.025300979614257812 length of segment : 282 time for calcul the mask position with numpy : 0.05978059768676758 nb_pixel_total : 17974 time to create 1 rle with old method : 0.025536298751831055 length of segment : 179 time for calcul the mask position with numpy : 0.04629945755004883 nb_pixel_total : 28478 time to create 1 rle with old method : 0.036865949630737305 length of segment : 228 time for calcul the mask position with numpy : 0.021174907684326172 nb_pixel_total : 5883 time to create 1 rle with old method : 0.010353565216064453 length of segment : 107 time for calcul the mask position with numpy : 0.03231000900268555 nb_pixel_total : 13134 time to create 1 rle with old method : 0.01862645149230957 length of segment : 92 time for calcul the mask position with numpy : 0.04552865028381348 nb_pixel_total : 15117 time to create 1 rle with old method : 0.01988983154296875 length of segment : 137 time for calcul the mask position with numpy : 0.05297517776489258 nb_pixel_total : 18479 time to create 1 rle with old method : 0.025801897048950195 length of segment : 134 time for calcul the mask position with numpy : 0.062478065490722656 nb_pixel_total : 21700 time to create 1 rle with old method : 0.027144908905029297 length of segment : 171 time for calcul the mask position with numpy : 0.07722139358520508 nb_pixel_total : 30453 time to create 1 rle with old method : 0.037335872650146484 length of segment : 224 time for calcul the mask position with numpy : 0.04212760925292969 nb_pixel_total : 27432 time to create 1 rle with old method : 0.03201723098754883 length of segment : 196 time for calcul the mask position with numpy : 0.0858464241027832 nb_pixel_total : 17803 time to create 1 rle with old method : 0.022716283798217773 length of segment : 251 time for calcul the mask position with numpy : 0.004625797271728516 nb_pixel_total : 3925 time to create 1 rle with old method : 0.0043506622314453125 length of segment : 50 time for calcul the mask position with numpy : 0.022469758987426758 nb_pixel_total : 5563 time to create 1 rle with old method : 0.010255575180053711 length of segment : 98 time for calcul the mask position with numpy : 0.20230507850646973 nb_pixel_total : 46641 time to create 1 rle with old method : 0.05237102508544922 length of segment : 213 time for calcul the mask position with numpy : 0.020839929580688477 nb_pixel_total : 5188 time to create 1 rle with old method : 0.009607076644897461 length of segment : 70 time for calcul the mask position with numpy : 0.058330535888671875 nb_pixel_total : 45859 time to create 1 rle with old method : 0.05032181739807129 length of segment : 381 time for calcul the mask position with numpy : 0.0667269229888916 nb_pixel_total : 22959 time to create 1 rle with old method : 0.029607295989990234 length of segment : 177 time for calcul the mask position with numpy : 0.10007262229919434 nb_pixel_total : 20722 time to create 1 rle with old method : 0.02640676498413086 length of segment : 251 time for calcul the mask position with numpy : 0.1327495574951172 nb_pixel_total : 51825 time to create 1 rle with old method : 0.06287455558776855 length of segment : 217 time for calcul the mask position with numpy : 0.04562187194824219 nb_pixel_total : 10610 time to create 1 rle with old method : 0.01562809944152832 length of segment : 104 time for calcul the mask position with numpy : 0.06561112403869629 nb_pixel_total : 22357 time to create 1 rle with old method : 0.029723644256591797 length of segment : 150 time for calcul the mask position with numpy : 0.07956790924072266 nb_pixel_total : 24507 time to create 1 rle with old method : 0.03459429740905762 length of segment : 189 time for calcul the mask position with numpy : 0.11757349967956543 nb_pixel_total : 46584 time to create 1 rle with old method : 0.055258989334106445 length of segment : 292 time for calcul the mask position with numpy : 0.16602492332458496 nb_pixel_total : 53715 time to create 1 rle with old method : 0.0764169692993164 length of segment : 365 time for calcul the mask position with numpy : 0.04987788200378418 nb_pixel_total : 9944 time to create 1 rle with old method : 0.01366734504699707 length of segment : 142 time for calcul the mask position with numpy : 0.0014297962188720703 nb_pixel_total : 4770 time to create 1 rle with old method : 0.006003618240356445 length of segment : 83 time for calcul the mask position with numpy : 0.09852123260498047 nb_pixel_total : 35586 time to create 1 rle with old method : 0.04320502281188965 length of segment : 258 time for calcul the mask position with numpy : 0.011581182479858398 nb_pixel_total : 8129 time to create 1 rle with old method : 0.014340400695800781 length of segment : 83 time for calcul the mask position with numpy : 0.08154463768005371 nb_pixel_total : 29882 time to create 1 rle with old method : 0.039101362228393555 length of segment : 209 time for calcul the mask position with numpy : 0.08890223503112793 nb_pixel_total : 65821 time to create 1 rle with old method : 0.07163071632385254 length of segment : 230 time for calcul the mask position with numpy : 0.06845402717590332 nb_pixel_total : 29888 time to create 1 rle with old method : 0.04242086410522461 length of segment : 154 time for calcul the mask position with numpy : 0.1082611083984375 nb_pixel_total : 76394 time to create 1 rle with old method : 0.10187435150146484 length of segment : 505 time for calcul the mask position with numpy : 0.06005239486694336 nb_pixel_total : 13014 time to create 1 rle with old method : 0.01940131187438965 length of segment : 175 time for calcul the mask position with numpy : 0.0059511661529541016 nb_pixel_total : 22207 time to create 1 rle with old method : 0.025552988052368164 length of segment : 213 time for calcul the mask position with numpy : 0.12750005722045898 nb_pixel_total : 109226 time to create 1 rle with old method : 0.13289928436279297 length of segment : 459 time for calcul the mask position with numpy : 0.04305219650268555 nb_pixel_total : 15942 time to create 1 rle with old method : 0.025384902954101562 length of segment : 136 time for calcul the mask position with numpy : 0.010481595993041992 nb_pixel_total : 7423 time to create 1 rle with old method : 0.014600992202758789 length of segment : 172 time for calcul the mask position with numpy : 0.02964305877685547 nb_pixel_total : 33162 time to create 1 rle with old method : 0.04191231727600098 length of segment : 146 time for calcul the mask position with numpy : 0.027155637741088867 nb_pixel_total : 21196 time to create 1 rle with old method : 0.027115583419799805 length of segment : 192 time for calcul the mask position with numpy : 0.06337857246398926 nb_pixel_total : 21105 time to create 1 rle with old method : 0.02874922752380371 length of segment : 190 time for calcul the mask position with numpy : 0.008972406387329102 nb_pixel_total : 5819 time to create 1 rle with old method : 0.009481430053710938 length of segment : 87 time for calcul the mask position with numpy : 0.06794023513793945 nb_pixel_total : 25757 time to create 1 rle with old method : 0.047098636627197266 length of segment : 204 time for calcul the mask position with numpy : 0.024619340896606445 nb_pixel_total : 4590 time to create 1 rle with old method : 0.007408618927001953 length of segment : 77 time for calcul the mask position with numpy : 0.0022606849670410156 nb_pixel_total : 5714 time to create 1 rle with old method : 0.007189750671386719 length of segment : 173 time for calcul the mask position with numpy : 0.017408132553100586 nb_pixel_total : 6913 time to create 1 rle with old method : 0.01498866081237793 length of segment : 104 time for calcul the mask position with numpy : 0.0012907981872558594 nb_pixel_total : 12873 time to create 1 rle with old method : 0.016637563705444336 length of segment : 146 time for calcul the mask position with numpy : 0.1871657371520996 nb_pixel_total : 51245 time to create 1 rle with old method : 0.08414435386657715 length of segment : 389 time for calcul the mask position with numpy : 0.17372870445251465 nb_pixel_total : 25521 time to create 1 rle with old method : 0.03208017349243164 length of segment : 200 time for calcul the mask position with numpy : 0.14091706275939941 nb_pixel_total : 43406 time to create 1 rle with old method : 0.05299782752990723 length of segment : 327 time for calcul the mask position with numpy : 0.0020699501037597656 nb_pixel_total : 6335 time to create 1 rle with old method : 0.017464637756347656 length of segment : 170 time for calcul the mask position with numpy : 0.00902700424194336 nb_pixel_total : 14660 time to create 1 rle with old method : 0.016289472579956055 length of segment : 135 time for calcul the mask position with numpy : 0.00070953369140625 nb_pixel_total : 30900 time to create 1 rle with old method : 0.04154562950134277 length of segment : 188 time for calcul the mask position with numpy : 0.045590877532958984 nb_pixel_total : 11158 time to create 1 rle with old method : 0.016256093978881836 length of segment : 101 time for calcul the mask position with numpy : 0.046918392181396484 nb_pixel_total : 8164 time to create 1 rle with old method : 0.011101245880126953 length of segment : 156 time for calcul the mask position with numpy : 0.1254284381866455 nb_pixel_total : 69025 time to create 1 rle with old method : 0.07872772216796875 length of segment : 389 time for calcul the mask position with numpy : 0.0018389225006103516 nb_pixel_total : 7924 time to create 1 rle with old method : 0.009356021881103516 length of segment : 143 time for calcul the mask position with numpy : 0.02111029624938965 nb_pixel_total : 8494 time to create 1 rle with old method : 0.011937141418457031 length of segment : 115 time for calcul the mask position with numpy : 0.023529052734375 nb_pixel_total : 19441 time to create 1 rle with old method : 0.029259443283081055 length of segment : 168 time for calcul the mask position with numpy : 0.31397032737731934 nb_pixel_total : 178358 time to create 1 rle with new method : 0.014049530029296875 length of segment : 510 time for calcul the mask position with numpy : 0.06267762184143066 nb_pixel_total : 15681 time to create 1 rle with old method : 0.019636869430541992 length of segment : 176 time for calcul the mask position with numpy : 0.08635592460632324 nb_pixel_total : 36454 time to create 1 rle with old method : 0.05529379844665527 length of segment : 216 time for calcul the mask position with numpy : 0.05276036262512207 nb_pixel_total : 17855 time to create 1 rle with old method : 0.022554874420166016 length of segment : 165 time for calcul the mask position with numpy : 0.06633472442626953 nb_pixel_total : 20087 time to create 1 rle with old method : 0.025439023971557617 length of segment : 160 time for calcul the mask position with numpy : 0.02355360984802246 nb_pixel_total : 9398 time to create 1 rle with old method : 0.013566255569458008 length of segment : 63 time for calcul the mask position with numpy : 0.027776002883911133 nb_pixel_total : 8311 time to create 1 rle with old method : 0.014284610748291016 length of segment : 103 time for calcul the mask position with numpy : 0.08020615577697754 nb_pixel_total : 16716 time to create 1 rle with old method : 0.02148723602294922 length of segment : 260 time for calcul the mask position with numpy : 0.04556536674499512 nb_pixel_total : 14846 time to create 1 rle with old method : 0.02184271812438965 length of segment : 137 time for calcul the mask position with numpy : 0.09873700141906738 nb_pixel_total : 47404 time to create 1 rle with old method : 0.055692195892333984 length of segment : 344 time for calcul the mask position with numpy : 0.0645287036895752 nb_pixel_total : 17685 time to create 1 rle with old method : 0.022004365921020508 length of segment : 189 time for calcul the mask position with numpy : 0.024846553802490234 nb_pixel_total : 4772 time to create 1 rle with old method : 0.008973360061645508 length of segment : 76 time for calcul the mask position with numpy : 0.054799556732177734 nb_pixel_total : 18222 time to create 1 rle with old method : 0.02331089973449707 length of segment : 134 time for calcul the mask position with numpy : 0.03737616539001465 nb_pixel_total : 16846 time to create 1 rle with old method : 0.021783828735351562 length of segment : 128 time for calcul the mask position with numpy : 0.14801883697509766 nb_pixel_total : 100449 time to create 1 rle with old method : 0.12598395347595215 length of segment : 487 time for calcul the mask position with numpy : 0.045603275299072266 nb_pixel_total : 12982 time to create 1 rle with old method : 0.01708054542541504 length of segment : 170 time for calcul the mask position with numpy : 0.04140734672546387 nb_pixel_total : 15792 time to create 1 rle with old method : 0.02214837074279785 length of segment : 113 time for calcul the mask position with numpy : 0.019938945770263672 nb_pixel_total : 9971 time to create 1 rle with old method : 0.015275716781616211 length of segment : 120 time for calcul the mask position with numpy : 0.025701284408569336 nb_pixel_total : 47501 time to create 1 rle with old method : 0.05602073669433594 length of segment : 242 time for calcul the mask position with numpy : 0.06605005264282227 nb_pixel_total : 25134 time to create 1 rle with old method : 0.032933712005615234 length of segment : 230 time for calcul the mask position with numpy : 0.03591418266296387 nb_pixel_total : 13093 time to create 1 rle with old method : 0.018278837203979492 length of segment : 273 time for calcul the mask position with numpy : 0.08131551742553711 nb_pixel_total : 12559 time to create 1 rle with old method : 0.014962196350097656 length of segment : 143 time for calcul the mask position with numpy : 0.08715534210205078 nb_pixel_total : 23853 time to create 1 rle with old method : 0.029867887496948242 length of segment : 295 time for calcul the mask position with numpy : 0.1681194305419922 nb_pixel_total : 34587 time to create 1 rle with old method : 0.0441436767578125 length of segment : 251 time for calcul the mask position with numpy : 0.11664223670959473 nb_pixel_total : 46305 time to create 1 rle with old method : 0.05646181106567383 length of segment : 266 time for calcul the mask position with numpy : 0.19695520401000977 nb_pixel_total : 47850 time to create 1 rle with old method : 0.05827188491821289 length of segment : 299 time for calcul the mask position with numpy : 0.14866232872009277 nb_pixel_total : 98352 time to create 1 rle with old method : 0.10763287544250488 length of segment : 508 time for calcul the mask position with numpy : 0.04925966262817383 nb_pixel_total : 21720 time to create 1 rle with old method : 0.02893662452697754 length of segment : 140 time for calcul the mask position with numpy : 0.38684844970703125 nb_pixel_total : 151795 time to create 1 rle with new method : 0.02049708366394043 length of segment : 695 time for calcul the mask position with numpy : 0.009040355682373047 nb_pixel_total : 18288 time to create 1 rle with old method : 0.022713184356689453 length of segment : 202 time for calcul the mask position with numpy : 0.03850841522216797 nb_pixel_total : 18127 time to create 1 rle with old method : 0.025776147842407227 length of segment : 276 time for calcul the mask position with numpy : 0.20253229141235352 nb_pixel_total : 49424 time to create 1 rle with old method : 0.05972790718078613 length of segment : 478 time for calcul the mask position with numpy : 0.03194856643676758 nb_pixel_total : 11243 time to create 1 rle with old method : 0.01711559295654297 length of segment : 152 time for calcul the mask position with numpy : 0.01412343978881836 nb_pixel_total : 7313 time to create 1 rle with old method : 0.01221013069152832 length of segment : 104 time for calcul the mask position with numpy : 0.055748939514160156 nb_pixel_total : 18259 time to create 1 rle with old method : 0.023700475692749023 length of segment : 172 time for calcul the mask position with numpy : 0.05063009262084961 nb_pixel_total : 13259 time to create 1 rle with old method : 0.015370607376098633 length of segment : 132 time for calcul the mask position with numpy : 0.00432133674621582 nb_pixel_total : 15787 time to create 1 rle with old method : 0.020084857940673828 length of segment : 229 time for calcul the mask position with numpy : 0.20077753067016602 nb_pixel_total : 63959 time to create 1 rle with old method : 0.06955289840698242 length of segment : 380 time for calcul the mask position with numpy : 0.04932832717895508 nb_pixel_total : 13945 time to create 1 rle with old method : 0.01583242416381836 length of segment : 179 time for calcul the mask position with numpy : 0.04189920425415039 nb_pixel_total : 17349 time to create 1 rle with old method : 0.023143529891967773 length of segment : 120 time for calcul the mask position with numpy : 0.08314633369445801 nb_pixel_total : 30450 time to create 1 rle with old method : 0.046369075775146484 length of segment : 214 time for calcul the mask position with numpy : 0.0261685848236084 nb_pixel_total : 24946 time to create 1 rle with old method : 0.031603097915649414 length of segment : 220 time for calcul the mask position with numpy : 0.027187585830688477 nb_pixel_total : 32476 time to create 1 rle with old method : 0.05168795585632324 length of segment : 309 time for calcul the mask position with numpy : 0.011139631271362305 nb_pixel_total : 4695 time to create 1 rle with old method : 0.0079345703125 length of segment : 70 time for calcul the mask position with numpy : 0.011437416076660156 nb_pixel_total : 19765 time to create 1 rle with old method : 0.026917695999145508 length of segment : 187 time for calcul the mask position with numpy : 0.02292323112487793 nb_pixel_total : 14665 time to create 1 rle with old method : 0.020246267318725586 length of segment : 150 time for calcul the mask position with numpy : 0.07651782035827637 nb_pixel_total : 24601 time to create 1 rle with old method : 0.04749894142150879 length of segment : 207 time for calcul the mask position with numpy : 0.07460284233093262 nb_pixel_total : 19495 time to create 1 rle with old method : 0.02922821044921875 length of segment : 207 time for calcul the mask position with numpy : 0.06444120407104492 nb_pixel_total : 8650 time to create 1 rle with old method : 0.022526264190673828 length of segment : 126 time for calcul the mask position with numpy : 0.1458120346069336 nb_pixel_total : 43569 time to create 1 rle with old method : 0.06488680839538574 length of segment : 278 time for calcul the mask position with numpy : 0.02535724639892578 nb_pixel_total : 6631 time to create 1 rle with old method : 0.010202884674072266 length of segment : 100 time for calcul the mask position with numpy : 0.1403794288635254 nb_pixel_total : 42490 time to create 1 rle with old method : 0.06483840942382812 length of segment : 272 time for calcul the mask position with numpy : 0.061125993728637695 nb_pixel_total : 11532 time to create 1 rle with old method : 0.01838850975036621 length of segment : 137 time for calcul the mask position with numpy : 0.03864550590515137 nb_pixel_total : 13622 time to create 1 rle with old method : 0.019332408905029297 length of segment : 137 time for calcul the mask position with numpy : 0.11267638206481934 nb_pixel_total : 23716 time to create 1 rle with old method : 0.029367923736572266 length of segment : 264 time for calcul the mask position with numpy : 0.10481500625610352 nb_pixel_total : 25182 time to create 1 rle with old method : 0.03170895576477051 length of segment : 158 time for calcul the mask position with numpy : 0.09107446670532227 nb_pixel_total : 30425 time to create 1 rle with old method : 0.03773188591003418 length of segment : 146 time for calcul the mask position with numpy : 0.11542630195617676 nb_pixel_total : 25786 time to create 1 rle with old method : 0.03180265426635742 length of segment : 227 time for calcul the mask position with numpy : 0.03861570358276367 nb_pixel_total : 8424 time to create 1 rle with old method : 0.013380289077758789 length of segment : 103 time for calcul the mask position with numpy : 0.09704089164733887 nb_pixel_total : 42772 time to create 1 rle with old method : 0.04946756362915039 length of segment : 257 time for calcul the mask position with numpy : 0.06878662109375 nb_pixel_total : 27010 time to create 1 rle with old method : 0.032776594161987305 length of segment : 317 time for calcul the mask position with numpy : 0.021862030029296875 nb_pixel_total : 4813 time to create 1 rle with old method : 0.009269952774047852 length of segment : 87 time for calcul the mask position with numpy : 0.022100210189819336 nb_pixel_total : 6714 time to create 1 rle with old method : 0.015372753143310547 length of segment : 92 length of segment : 0 time for calcul the mask position with numpy : 0.05707526206970215 nb_pixel_total : 16125 time to create 1 rle with old method : 0.020935535430908203 length of segment : 230 time for calcul the mask position with numpy : 0.1842648983001709 nb_pixel_total : 85561 time to create 1 rle with old method : 0.09757161140441895 length of segment : 577 time for calcul the mask position with numpy : 0.19504904747009277 nb_pixel_total : 87370 time to create 1 rle with old method : 0.09963536262512207 length of segment : 418 time for calcul the mask position with numpy : 0.03323769569396973 nb_pixel_total : 8844 time to create 1 rle with old method : 0.01416468620300293 length of segment : 132 time for calcul the mask position with numpy : 0.028304576873779297 nb_pixel_total : 5349 time to create 1 rle with old method : 0.010983705520629883 length of segment : 98 time for calcul the mask position with numpy : 0.03206658363342285 nb_pixel_total : 6841 time to create 1 rle with old method : 0.010402917861938477 length of segment : 100 time for calcul the mask position with numpy : 0.1857008934020996 nb_pixel_total : 46474 time to create 1 rle with old method : 0.055205583572387695 length of segment : 305 time for calcul the mask position with numpy : 0.09897255897521973 nb_pixel_total : 23111 time to create 1 rle with old method : 0.03287458419799805 length of segment : 243 time for calcul the mask position with numpy : 0.08499526977539062 nb_pixel_total : 21324 time to create 1 rle with old method : 0.038826942443847656 length of segment : 182 time for calcul the mask position with numpy : 0.11523580551147461 nb_pixel_total : 15441 time to create 1 rle with old method : 0.027680397033691406 length of segment : 217 time for calcul the mask position with numpy : 0.010307550430297852 nb_pixel_total : 5484 time to create 1 rle with old method : 0.010273218154907227 length of segment : 83 time for calcul the mask position with numpy : 0.06383013725280762 nb_pixel_total : 25438 time to create 1 rle with old method : 0.0389711856842041 length of segment : 112 time for calcul the mask position with numpy : 0.23285746574401855 nb_pixel_total : 41864 time to create 1 rle with old method : 0.04862213134765625 length of segment : 649 time for calcul the mask position with numpy : 0.0026540756225585938 nb_pixel_total : 13897 time to create 1 rle with old method : 0.015243291854858398 length of segment : 145 time for calcul the mask position with numpy : 0.04563021659851074 nb_pixel_total : 21181 time to create 1 rle with old method : 0.043271541595458984 length of segment : 183 time for calcul the mask position with numpy : 0.09621024131774902 nb_pixel_total : 30574 time to create 1 rle with old method : 0.03953409194946289 length of segment : 190 time for calcul the mask position with numpy : 0.07907271385192871 nb_pixel_total : 16116 time to create 1 rle with old method : 0.022625207901000977 length of segment : 135 time for calcul the mask position with numpy : 0.10595059394836426 nb_pixel_total : 48974 time to create 1 rle with old method : 0.059853315353393555 length of segment : 322 time for calcul the mask position with numpy : 0.04768824577331543 nb_pixel_total : 23097 time to create 1 rle with old method : 0.03374958038330078 length of segment : 180 time for calcul the mask position with numpy : 0.10592412948608398 nb_pixel_total : 28736 time to create 1 rle with old method : 0.03437304496765137 length of segment : 240 time for calcul the mask position with numpy : 0.029087543487548828 nb_pixel_total : 5872 time to create 1 rle with old method : 0.01279306411743164 length of segment : 94 time for calcul the mask position with numpy : 0.0034894943237304688 nb_pixel_total : 4038 time to create 1 rle with old method : 0.005520820617675781 length of segment : 79 time for calcul the mask position with numpy : 0.01319432258605957 nb_pixel_total : 8627 time to create 1 rle with old method : 0.012614250183105469 length of segment : 102 time for calcul the mask position with numpy : 0.013555049896240234 nb_pixel_total : 10258 time to create 1 rle with old method : 0.016281604766845703 length of segment : 213 time for calcul the mask position with numpy : 0.11596512794494629 nb_pixel_total : 70440 time to create 1 rle with old method : 0.08138275146484375 length of segment : 337 time for calcul the mask position with numpy : 0.011163473129272461 nb_pixel_total : 20234 time to create 1 rle with old method : 0.02582836151123047 length of segment : 269 time for calcul the mask position with numpy : 0.03225851058959961 nb_pixel_total : 22009 time to create 1 rle with old method : 0.02724623680114746 length of segment : 167 time for calcul the mask position with numpy : 0.1803290843963623 nb_pixel_total : 96485 time to create 1 rle with old method : 0.10786914825439453 length of segment : 275 time for calcul the mask position with numpy : 0.14266133308410645 nb_pixel_total : 46442 time to create 1 rle with old method : 0.057601213455200195 length of segment : 324 time for calcul the mask position with numpy : 0.017993450164794922 nb_pixel_total : 24022 time to create 1 rle with old method : 0.03152585029602051 length of segment : 201 time for calcul the mask position with numpy : 0.07863068580627441 nb_pixel_total : 43292 time to create 1 rle with old method : 0.05182766914367676 length of segment : 360 time for calcul the mask position with numpy : 0.06681323051452637 nb_pixel_total : 27173 time to create 1 rle with old method : 0.03495049476623535 length of segment : 164 time for calcul the mask position with numpy : 0.07653188705444336 nb_pixel_total : 19817 time to create 1 rle with old method : 0.027036666870117188 length of segment : 154 time for calcul the mask position with numpy : 0.0235445499420166 nb_pixel_total : 8496 time to create 1 rle with old method : 0.012459278106689453 length of segment : 216 time for calcul the mask position with numpy : 0.05610299110412598 nb_pixel_total : 50235 time to create 1 rle with old method : 0.06657958030700684 length of segment : 351 time for calcul the mask position with numpy : 0.0786137580871582 nb_pixel_total : 18096 time to create 1 rle with old method : 0.024472713470458984 length of segment : 154 time for calcul the mask position with numpy : 0.09919953346252441 nb_pixel_total : 43699 time to create 1 rle with old method : 0.053530216217041016 length of segment : 254 time for calcul the mask position with numpy : 0.000400543212890625 nb_pixel_total : 8380 time to create 1 rle with old method : 0.009738683700561523 length of segment : 100 time for calcul the mask position with numpy : 0.0004935264587402344 nb_pixel_total : 3896 time to create 1 rle with old method : 0.0049669742584228516 length of segment : 172 time for calcul the mask position with numpy : 0.04475593566894531 nb_pixel_total : 11902 time to create 1 rle with old method : 0.025899887084960938 length of segment : 134 time for calcul the mask position with numpy : 0.041591644287109375 nb_pixel_total : 8241 time to create 1 rle with old method : 0.013871908187866211 length of segment : 111 time for calcul the mask position with numpy : 0.041431427001953125 nb_pixel_total : 11813 time to create 1 rle with old method : 0.016963720321655273 length of segment : 116 time for calcul the mask position with numpy : 0.0354769229888916 nb_pixel_total : 11775 time to create 1 rle with old method : 0.014200925827026367 length of segment : 126 time for calcul the mask position with numpy : 0.06373858451843262 nb_pixel_total : 42674 time to create 1 rle with old method : 0.05196785926818848 length of segment : 231 time for calcul the mask position with numpy : 0.05316019058227539 nb_pixel_total : 22275 time to create 1 rle with old method : 0.029017925262451172 length of segment : 220 time for calcul the mask position with numpy : 0.02519965171813965 nb_pixel_total : 12823 time to create 1 rle with old method : 0.019896268844604492 length of segment : 101 time for calcul the mask position with numpy : 0.04838299751281738 nb_pixel_total : 15112 time to create 1 rle with old method : 0.025972604751586914 length of segment : 145 time for calcul the mask position with numpy : 0.03436636924743652 nb_pixel_total : 30417 time to create 1 rle with old method : 0.03849935531616211 length of segment : 256 time for calcul the mask position with numpy : 0.019748926162719727 nb_pixel_total : 12480 time to create 1 rle with old method : 0.021109819412231445 length of segment : 178 time for calcul the mask position with numpy : 0.04752540588378906 nb_pixel_total : 17171 time to create 1 rle with old method : 0.023214101791381836 length of segment : 127 time for calcul the mask position with numpy : 0.0642697811126709 nb_pixel_total : 23083 time to create 1 rle with old method : 0.04478812217712402 length of segment : 169 time for calcul the mask position with numpy : 0.05987358093261719 nb_pixel_total : 15080 time to create 1 rle with old method : 0.02588820457458496 length of segment : 162 time for calcul the mask position with numpy : 0.05003976821899414 nb_pixel_total : 15756 time to create 1 rle with old method : 0.019505739212036133 length of segment : 169 time for calcul the mask position with numpy : 0.060477495193481445 nb_pixel_total : 23831 time to create 1 rle with old method : 0.03143191337585449 length of segment : 162 time for calcul the mask position with numpy : 0.04237818717956543 nb_pixel_total : 12654 time to create 1 rle with old method : 0.018376588821411133 length of segment : 124 time for calcul the mask position with numpy : 0.12484002113342285 nb_pixel_total : 56586 time to create 1 rle with old method : 0.06702065467834473 length of segment : 303 time for calcul the mask position with numpy : 0.10592269897460938 nb_pixel_total : 29847 time to create 1 rle with old method : 0.03719830513000488 length of segment : 241 time for calcul the mask position with numpy : 0.08724021911621094 nb_pixel_total : 30915 time to create 1 rle with old method : 0.03825211524963379 length of segment : 235 time for calcul the mask position with numpy : 0.030182838439941406 nb_pixel_total : 16103 time to create 1 rle with old method : 0.023397445678710938 length of segment : 223 time for calcul the mask position with numpy : 0.08556962013244629 nb_pixel_total : 40523 time to create 1 rle with old method : 0.0516510009765625 length of segment : 260 time for calcul the mask position with numpy : 0.041292667388916016 nb_pixel_total : 12363 time to create 1 rle with old method : 0.016179323196411133 length of segment : 135 time for calcul the mask position with numpy : 0.07460975646972656 nb_pixel_total : 46826 time to create 1 rle with old method : 0.05536341667175293 length of segment : 199 time for calcul the mask position with numpy : 0.013390541076660156 nb_pixel_total : 5213 time to create 1 rle with old method : 0.010084867477416992 length of segment : 65 time for calcul the mask position with numpy : 0.08575725555419922 nb_pixel_total : 37732 time to create 1 rle with old method : 0.04619240760803223 length of segment : 217 time for calcul the mask position with numpy : 0.03389930725097656 nb_pixel_total : 13066 time to create 1 rle with old method : 0.02093815803527832 length of segment : 171 time for calcul the mask position with numpy : 0.05930805206298828 nb_pixel_total : 23321 time to create 1 rle with old method : 0.02485060691833496 length of segment : 149 time for calcul the mask position with numpy : 0.13053631782531738 nb_pixel_total : 44052 time to create 1 rle with old method : 0.055417537689208984 length of segment : 511 time for calcul the mask position with numpy : 0.020389318466186523 nb_pixel_total : 5832 time to create 1 rle with old method : 0.011223554611206055 length of segment : 101 time for calcul the mask position with numpy : 0.04375720024108887 nb_pixel_total : 15917 time to create 1 rle with old method : 0.018930435180664062 length of segment : 140 time for calcul the mask position with numpy : 0.024113178253173828 nb_pixel_total : 7521 time to create 1 rle with old method : 0.008209943771362305 length of segment : 111 time for calcul the mask position with numpy : 0.06378459930419922 nb_pixel_total : 26974 time to create 1 rle with old method : 0.033243417739868164 length of segment : 170 time for calcul the mask position with numpy : 0.02907538414001465 nb_pixel_total : 16884 time to create 1 rle with old method : 0.01886463165283203 length of segment : 169 time for calcul the mask position with numpy : 0.041159868240356445 nb_pixel_total : 10095 time to create 1 rle with old method : 0.015387535095214844 length of segment : 120 time for calcul the mask position with numpy : 0.024953365325927734 nb_pixel_total : 20017 time to create 1 rle with old method : 0.03492403030395508 length of segment : 160 time for calcul the mask position with numpy : 0.06211733818054199 nb_pixel_total : 24506 time to create 1 rle with old method : 0.02608013153076172 length of segment : 183 time for calcul the mask position with numpy : 0.03244447708129883 nb_pixel_total : 8674 time to create 1 rle with old method : 0.009491920471191406 length of segment : 99 time for calcul the mask position with numpy : 0.08927106857299805 nb_pixel_total : 29670 time to create 1 rle with old method : 0.03713631629943848 length of segment : 222 time for calcul the mask position with numpy : 0.07205510139465332 nb_pixel_total : 18416 time to create 1 rle with old method : 0.022676467895507812 length of segment : 132 time for calcul the mask position with numpy : 0.12633919715881348 nb_pixel_total : 24608 time to create 1 rle with old method : 0.03363037109375 length of segment : 300 time for calcul the mask position with numpy : 0.07416963577270508 nb_pixel_total : 21255 time to create 1 rle with old method : 0.027853012084960938 length of segment : 140 time for calcul the mask position with numpy : 0.0929567813873291 nb_pixel_total : 31895 time to create 1 rle with old method : 0.04205179214477539 length of segment : 199 time for calcul the mask position with numpy : 0.11087942123413086 nb_pixel_total : 29858 time to create 1 rle with old method : 0.036712646484375 length of segment : 219 time for calcul the mask position with numpy : 0.06241154670715332 nb_pixel_total : 7798 time to create 1 rle with old method : 0.02403545379638672 length of segment : 154 time for calcul the mask position with numpy : 0.06588554382324219 nb_pixel_total : 34912 time to create 1 rle with old method : 0.07302093505859375 length of segment : 182 time for calcul the mask position with numpy : 0.040050506591796875 nb_pixel_total : 20341 time to create 1 rle with old method : 0.03040003776550293 length of segment : 189 time for calcul the mask position with numpy : 0.2622804641723633 nb_pixel_total : 87840 time to create 1 rle with old method : 0.12105226516723633 length of segment : 305 time for calcul the mask position with numpy : 0.042391300201416016 nb_pixel_total : 16978 time to create 1 rle with old method : 0.02359461784362793 length of segment : 192 time for calcul the mask position with numpy : 0.20214223861694336 nb_pixel_total : 57282 time to create 1 rle with old method : 0.06612372398376465 length of segment : 410 time for calcul the mask position with numpy : 0.22939491271972656 nb_pixel_total : 63145 time to create 1 rle with old method : 0.07303619384765625 length of segment : 516 time for calcul the mask position with numpy : 0.05816006660461426 nb_pixel_total : 10875 time to create 1 rle with old method : 0.017099380493164062 length of segment : 143 time for calcul the mask position with numpy : 0.03445696830749512 nb_pixel_total : 5239 time to create 1 rle with old method : 0.005903482437133789 length of segment : 119 time for calcul the mask position with numpy : 0.13842296600341797 nb_pixel_total : 47053 time to create 1 rle with old method : 0.05720996856689453 length of segment : 366 time for calcul the mask position with numpy : 0.05507326126098633 nb_pixel_total : 30980 time to create 1 rle with old method : 0.041223764419555664 length of segment : 165 time for calcul the mask position with numpy : 0.006867408752441406 nb_pixel_total : 12090 time to create 1 rle with old method : 0.01714158058166504 length of segment : 139 time for calcul the mask position with numpy : 0.02960348129272461 nb_pixel_total : 21718 time to create 1 rle with old method : 0.039739131927490234 length of segment : 240 time for calcul the mask position with numpy : 0.0010950565338134766 nb_pixel_total : 30589 time to create 1 rle with old method : 0.034905195236206055 length of segment : 183 time for calcul the mask position with numpy : 0.048187971115112305 nb_pixel_total : 15516 time to create 1 rle with old method : 0.019388437271118164 length of segment : 166 time for calcul the mask position with numpy : 0.038887977600097656 nb_pixel_total : 15878 time to create 1 rle with old method : 0.0221560001373291 length of segment : 152 time for calcul the mask position with numpy : 0.03205752372741699 nb_pixel_total : 13311 time to create 1 rle with old method : 0.014671087265014648 length of segment : 104 time for calcul the mask position with numpy : 0.05774569511413574 nb_pixel_total : 17877 time to create 1 rle with old method : 0.023204565048217773 length of segment : 223 time for calcul the mask position with numpy : 0.04593849182128906 nb_pixel_total : 24848 time to create 1 rle with old method : 0.031165599822998047 length of segment : 153 time for calcul the mask position with numpy : 0.11477780342102051 nb_pixel_total : 45790 time to create 1 rle with old method : 0.05717730522155762 length of segment : 229 time for calcul the mask position with numpy : 0.0006811618804931641 nb_pixel_total : 20578 time to create 1 rle with old method : 0.022670984268188477 length of segment : 153 time for calcul the mask position with numpy : 0.050534963607788086 nb_pixel_total : 13608 time to create 1 rle with old method : 0.019468307495117188 length of segment : 114 time for calcul the mask position with numpy : 0.10498189926147461 nb_pixel_total : 45685 time to create 1 rle with old method : 0.054692745208740234 length of segment : 219 time for calcul the mask position with numpy : 0.029094457626342773 nb_pixel_total : 24079 time to create 1 rle with old method : 0.032989501953125 length of segment : 185 time for calcul the mask position with numpy : 0.0004265308380126953 nb_pixel_total : 14031 time to create 1 rle with old method : 0.01727581024169922 length of segment : 118 time for calcul the mask position with numpy : 0.09067559242248535 nb_pixel_total : 27501 time to create 1 rle with old method : 0.03580141067504883 length of segment : 246 time for calcul the mask position with numpy : 0.0509335994720459 nb_pixel_total : 37239 time to create 1 rle with old method : 0.05213809013366699 length of segment : 267 time for calcul the mask position with numpy : 0.5947341918945312 nb_pixel_total : 224537 time to create 1 rle with new method : 0.04077029228210449 length of segment : 1054 time for calcul the mask position with numpy : 0.1397416591644287 nb_pixel_total : 85582 time to create 1 rle with old method : 0.09841799736022949 length of segment : 310 time for calcul the mask position with numpy : 0.0959312915802002 nb_pixel_total : 36298 time to create 1 rle with old method : 0.0420377254486084 length of segment : 312 time for calcul the mask position with numpy : 0.2093651294708252 nb_pixel_total : 58118 time to create 1 rle with old method : 0.06686115264892578 length of segment : 477 time for calcul the mask position with numpy : 0.0437469482421875 nb_pixel_total : 46658 time to create 1 rle with old method : 0.05733990669250488 length of segment : 207 time for calcul the mask position with numpy : 0.20309162139892578 nb_pixel_total : 46182 time to create 1 rle with old method : 0.08451199531555176 length of segment : 444 time for calcul the mask position with numpy : 0.08287930488586426 nb_pixel_total : 20987 time to create 1 rle with old method : 0.037468671798706055 length of segment : 190 time for calcul the mask position with numpy : 0.04759025573730469 nb_pixel_total : 14472 time to create 1 rle with old method : 0.03536367416381836 length of segment : 156 time for calcul the mask position with numpy : 0.16746068000793457 nb_pixel_total : 50094 time to create 1 rle with old method : 0.05999755859375 length of segment : 419 time for calcul the mask position with numpy : 0.031746625900268555 nb_pixel_total : 12561 time to create 1 rle with old method : 0.018218278884887695 length of segment : 104 time for calcul the mask position with numpy : 0.05116724967956543 nb_pixel_total : 25194 time to create 1 rle with old method : 0.0337374210357666 length of segment : 186 time for calcul the mask position with numpy : 0.22265338897705078 nb_pixel_total : 80145 time to create 1 rle with old method : 0.09888362884521484 length of segment : 670 time for calcul the mask position with numpy : 0.04227876663208008 nb_pixel_total : 40546 time to create 1 rle with old method : 0.04930901527404785 length of segment : 156 time for calcul the mask position with numpy : 0.03876137733459473 nb_pixel_total : 35767 time to create 1 rle with old method : 0.04442119598388672 length of segment : 245 time for calcul the mask position with numpy : 0.04554033279418945 nb_pixel_total : 14320 time to create 1 rle with old method : 0.021835803985595703 length of segment : 126 time for calcul the mask position with numpy : 0.042912960052490234 nb_pixel_total : 20271 time to create 1 rle with old method : 0.0312044620513916 length of segment : 135 time for calcul the mask position with numpy : 0.14617490768432617 nb_pixel_total : 92842 time to create 1 rle with old method : 0.11765432357788086 length of segment : 382 time for calcul the mask position with numpy : 0.027274608612060547 nb_pixel_total : 13827 time to create 1 rle with old method : 0.020191431045532227 length of segment : 185 time for calcul the mask position with numpy : 0.25421833992004395 nb_pixel_total : 97083 time to create 1 rle with old method : 0.11176681518554688 length of segment : 400 time for calcul the mask position with numpy : 0.0037004947662353516 nb_pixel_total : 23505 time to create 1 rle with old method : 0.028677701950073242 length of segment : 182 time for calcul the mask position with numpy : 0.19317054748535156 nb_pixel_total : 142453 time to create 1 rle with old method : 0.1836411952972412 length of segment : 359 time for calcul the mask position with numpy : 0.03697061538696289 nb_pixel_total : 30309 time to create 1 rle with old method : 0.039006710052490234 length of segment : 222 time for calcul the mask position with numpy : 0.08850574493408203 nb_pixel_total : 18191 time to create 1 rle with old method : 0.027399539947509766 length of segment : 303 time for calcul the mask position with numpy : 0.00972604751586914 nb_pixel_total : 5965 time to create 1 rle with old method : 0.008579492568969727 length of segment : 73 time for calcul the mask position with numpy : 0.020659685134887695 nb_pixel_total : 49724 time to create 1 rle with old method : 0.08422613143920898 length of segment : 231 time for calcul the mask position with numpy : 0.09292078018188477 nb_pixel_total : 44022 time to create 1 rle with old method : 0.05227088928222656 length of segment : 319 time for calcul the mask position with numpy : 0.017235994338989258 nb_pixel_total : 17497 time to create 1 rle with old method : 0.024823427200317383 length of segment : 181 time for calcul the mask position with numpy : 0.29771947860717773 nb_pixel_total : 241665 time to create 1 rle with new method : 0.02038860321044922 length of segment : 766 time for calcul the mask position with numpy : 0.0015869140625 nb_pixel_total : 8049 time to create 1 rle with old method : 0.009045600891113281 length of segment : 91 time for calcul the mask position with numpy : 0.017734289169311523 nb_pixel_total : 10411 time to create 1 rle with old method : 0.016934633255004883 length of segment : 162 time for calcul the mask position with numpy : 0.1168205738067627 nb_pixel_total : 149053 time to create 1 rle with old method : 0.16717052459716797 length of segment : 291 time for calcul the mask position with numpy : 0.17439508438110352 nb_pixel_total : 106965 time to create 1 rle with old method : 0.12212443351745605 length of segment : 393 time for calcul the mask position with numpy : 0.003644704818725586 nb_pixel_total : 17170 time to create 1 rle with old method : 0.022020578384399414 length of segment : 119 time for calcul the mask position with numpy : 0.001550436019897461 nb_pixel_total : 33974 time to create 1 rle with old method : 0.038080692291259766 length of segment : 322 time for calcul the mask position with numpy : 0.030461788177490234 nb_pixel_total : 63502 time to create 1 rle with old method : 0.07471179962158203 length of segment : 336 time for calcul the mask position with numpy : 0.016588449478149414 nb_pixel_total : 121571 time to create 1 rle with old method : 0.14005517959594727 length of segment : 530 time for calcul the mask position with numpy : 0.04999566078186035 nb_pixel_total : 58411 time to create 1 rle with old method : 0.09251165390014648 length of segment : 450 time for calcul the mask position with numpy : 0.008708477020263672 nb_pixel_total : 32393 time to create 1 rle with old method : 0.04541921615600586 length of segment : 238 time for calcul the mask position with numpy : 0.07546210289001465 nb_pixel_total : 145745 time to create 1 rle with old method : 0.16556334495544434 length of segment : 829 time for calcul the mask position with numpy : 0.05051469802856445 nb_pixel_total : 8415 time to create 1 rle with old method : 0.012107133865356445 length of segment : 171 time for calcul the mask position with numpy : 0.09174346923828125 nb_pixel_total : 31273 time to create 1 rle with old method : 0.040148258209228516 length of segment : 388 time for calcul the mask position with numpy : 0.13152241706848145 nb_pixel_total : 303220 time to create 1 rle with new method : 0.09169816970825195 length of segment : 842 time for calcul the mask position with numpy : 0.0038115978240966797 nb_pixel_total : 11680 time to create 1 rle with old method : 0.016033172607421875 length of segment : 176 time for calcul the mask position with numpy : 0.04254746437072754 nb_pixel_total : 50149 time to create 1 rle with old method : 0.05873513221740723 length of segment : 508 time for calcul the mask position with numpy : 0.0250704288482666 nb_pixel_total : 45021 time to create 1 rle with old method : 0.053639888763427734 length of segment : 270 time for calcul the mask position with numpy : 0.14063405990600586 nb_pixel_total : 41600 time to create 1 rle with old method : 0.051367998123168945 length of segment : 327 time for calcul the mask position with numpy : 0.022927045822143555 nb_pixel_total : 185274 time to create 1 rle with new method : 0.013609647750854492 length of segment : 518 time for calcul the mask position with numpy : 0.00620722770690918 nb_pixel_total : 12532 time to create 1 rle with old method : 0.017609834671020508 length of segment : 170 time for calcul the mask position with numpy : 0.043302059173583984 nb_pixel_total : 68574 time to create 1 rle with old method : 0.09673118591308594 length of segment : 231 time for calcul the mask position with numpy : 0.007093667984008789 nb_pixel_total : 47881 time to create 1 rle with old method : 0.06745100021362305 length of segment : 243 time for calcul the mask position with numpy : 0.011052846908569336 nb_pixel_total : 1658 time to create 1 rle with old method : 0.0034711360931396484 length of segment : 59 time for calcul the mask position with numpy : 0.01359701156616211 nb_pixel_total : 42906 time to create 1 rle with old method : 0.05177950859069824 length of segment : 218 time for calcul the mask position with numpy : 0.013638973236083984 nb_pixel_total : 25065 time to create 1 rle with old method : 0.03240823745727539 length of segment : 247 time for calcul the mask position with numpy : 0.028034448623657227 nb_pixel_total : 155750 time to create 1 rle with new method : 0.009856700897216797 length of segment : 412 time for calcul the mask position with numpy : 0.0012121200561523438 nb_pixel_total : 32941 time to create 1 rle with old method : 0.0416104793548584 length of segment : 314 time for calcul the mask position with numpy : 0.009591817855834961 nb_pixel_total : 59151 time to create 1 rle with old method : 0.06818008422851562 length of segment : 327 time for calcul the mask position with numpy : 0.023532867431640625 nb_pixel_total : 27903 time to create 1 rle with old method : 0.03601336479187012 length of segment : 212 time for calcul the mask position with numpy : 0.018299579620361328 nb_pixel_total : 17611 time to create 1 rle with old method : 0.025621652603149414 length of segment : 239 time for calcul the mask position with numpy : 0.03825235366821289 nb_pixel_total : 352745 time to create 1 rle with new method : 0.04784989356994629 length of segment : 355 time for calcul the mask position with numpy : 0.026947736740112305 nb_pixel_total : 90495 time to create 1 rle with old method : 0.10350728034973145 length of segment : 439 time for calcul the mask position with numpy : 0.0012555122375488281 nb_pixel_total : 37081 time to create 1 rle with old method : 0.0478060245513916 length of segment : 256 time for calcul the mask position with numpy : 0.014317035675048828 nb_pixel_total : 60547 time to create 1 rle with old method : 0.07189536094665527 length of segment : 495 time for calcul the mask position with numpy : 0.007016897201538086 nb_pixel_total : 2505 time to create 1 rle with old method : 0.007961511611938477 length of segment : 67 time for calcul the mask position with numpy : 0.039650917053222656 nb_pixel_total : 12925 time to create 1 rle with old method : 0.021476268768310547 length of segment : 91 time for calcul the mask position with numpy : 0.0034143924713134766 nb_pixel_total : 30344 time to create 1 rle with old method : 0.03545427322387695 length of segment : 177 time for calcul the mask position with numpy : 0.03671598434448242 nb_pixel_total : 19511 time to create 1 rle with old method : 0.027753829956054688 length of segment : 225 time for calcul the mask position with numpy : 0.005814552307128906 nb_pixel_total : 24365 time to create 1 rle with old method : 0.03752899169921875 length of segment : 230 time for calcul the mask position with numpy : 0.021598339080810547 nb_pixel_total : 61650 time to create 1 rle with old method : 0.07413673400878906 length of segment : 547 time for calcul the mask position with numpy : 0.05036330223083496 nb_pixel_total : 95322 time to create 1 rle with old method : 0.13290691375732422 length of segment : 399 time for calcul the mask position with numpy : 0.004662990570068359 nb_pixel_total : 109085 time to create 1 rle with old method : 0.11672091484069824 length of segment : 802 time for calcul the mask position with numpy : 0.013273954391479492 nb_pixel_total : 2814 time to create 1 rle with old method : 0.005307197570800781 length of segment : 106 time for calcul the mask position with numpy : 0.05237746238708496 nb_pixel_total : 32410 time to create 1 rle with old method : 0.040540456771850586 length of segment : 156 time for calcul the mask position with numpy : 0.00041294097900390625 nb_pixel_total : 4410 time to create 1 rle with old method : 0.005230903625488281 length of segment : 144 time for calcul the mask position with numpy : 0.00585484504699707 nb_pixel_total : 15451 time to create 1 rle with old method : 0.017568111419677734 length of segment : 137 time for calcul the mask position with numpy : 0.006480693817138672 nb_pixel_total : 53256 time to create 1 rle with old method : 0.05971264839172363 length of segment : 377 time for calcul the mask position with numpy : 0.0007722377777099609 nb_pixel_total : 10213 time to create 1 rle with old method : 0.011852741241455078 length of segment : 149 time for calcul the mask position with numpy : 0.0013353824615478516 nb_pixel_total : 10392 time to create 1 rle with old method : 0.011965513229370117 length of segment : 114 time for calcul the mask position with numpy : 0.00033926963806152344 nb_pixel_total : 5958 time to create 1 rle with old method : 0.006832599639892578 length of segment : 87 time for calcul the mask position with numpy : 0.0030519962310791016 nb_pixel_total : 29168 time to create 1 rle with old method : 0.03173494338989258 length of segment : 328 time for calcul the mask position with numpy : 0.0023946762084960938 nb_pixel_total : 29959 time to create 1 rle with old method : 0.03258538246154785 length of segment : 372 time for calcul the mask position with numpy : 0.0007610321044921875 nb_pixel_total : 14225 time to create 1 rle with old method : 0.01600170135498047 length of segment : 78 time for calcul the mask position with numpy : 0.0017986297607421875 nb_pixel_total : 19140 time to create 1 rle with old method : 0.023197650909423828 length of segment : 267 time for calcul the mask position with numpy : 0.0034160614013671875 nb_pixel_total : 35506 time to create 1 rle with old method : 0.038527727127075195 length of segment : 281 time for calcul the mask position with numpy : 0.0023996829986572266 nb_pixel_total : 25178 time to create 1 rle with old method : 0.03129172325134277 length of segment : 169 time for calcul the mask position with numpy : 0.015185832977294922 nb_pixel_total : 88307 time to create 1 rle with old method : 0.09897589683532715 length of segment : 347 time for calcul the mask position with numpy : 0.0204775333404541 nb_pixel_total : 225177 time to create 1 rle with new method : 0.01860523223876953 length of segment : 630 time for calcul the mask position with numpy : 0.000518798828125 nb_pixel_total : 11724 time to create 1 rle with old method : 0.012861967086791992 length of segment : 130 time for calcul the mask position with numpy : 0.011594295501708984 nb_pixel_total : 11002 time to create 1 rle with old method : 0.017449617385864258 length of segment : 208 time for calcul the mask position with numpy : 0.00398564338684082 nb_pixel_total : 56022 time to create 1 rle with old method : 0.06141924858093262 length of segment : 214 time for calcul the mask position with numpy : 0.01932239532470703 nb_pixel_total : 98977 time to create 1 rle with old method : 0.1083371639251709 length of segment : 406 time for calcul the mask position with numpy : 0.0017008781433105469 nb_pixel_total : 24791 time to create 1 rle with old method : 0.025645971298217773 length of segment : 244 time for calcul the mask position with numpy : 0.0012214183807373047 nb_pixel_total : 18010 time to create 1 rle with old method : 0.01960277557373047 length of segment : 196 time for calcul the mask position with numpy : 0.0032110214233398438 nb_pixel_total : 22699 time to create 1 rle with old method : 0.025552988052368164 length of segment : 274 time for calcul the mask position with numpy : 0.00409245491027832 nb_pixel_total : 69402 time to create 1 rle with old method : 0.07491040229797363 length of segment : 427 time for calcul the mask position with numpy : 0.0018851757049560547 nb_pixel_total : 28211 time to create 1 rle with old method : 0.03127431869506836 length of segment : 181 time for calcul the mask position with numpy : 0.01798415184020996 nb_pixel_total : 65138 time to create 1 rle with old method : 0.07403731346130371 length of segment : 272 time for calcul the mask position with numpy : 0.0002808570861816406 nb_pixel_total : 4094 time to create 1 rle with old method : 0.004624843597412109 length of segment : 75 time for calcul the mask position with numpy : 0.008621454238891602 nb_pixel_total : 56901 time to create 1 rle with old method : 0.0619654655456543 length of segment : 249 time for calcul the mask position with numpy : 0.0012598037719726562 nb_pixel_total : 17065 time to create 1 rle with old method : 0.018167972564697266 length of segment : 158 time for calcul the mask position with numpy : 0.0005025863647460938 nb_pixel_total : 8968 time to create 1 rle with old method : 0.009613037109375 length of segment : 170 time for calcul the mask position with numpy : 0.015635013580322266 nb_pixel_total : 75525 time to create 1 rle with old method : 0.08034205436706543 length of segment : 317 time for calcul the mask position with numpy : 0.0004622936248779297 nb_pixel_total : 11326 time to create 1 rle with old method : 0.012501001358032227 length of segment : 155 time for calcul the mask position with numpy : 0.031113386154174805 nb_pixel_total : 116759 time to create 1 rle with old method : 0.13182926177978516 length of segment : 673 time for calcul the mask position with numpy : 0.009727716445922852 nb_pixel_total : 60898 time to create 1 rle with old method : 0.06812787055969238 length of segment : 324 time for calcul the mask position with numpy : 0.0019412040710449219 nb_pixel_total : 26632 time to create 1 rle with old method : 0.028805971145629883 length of segment : 169 time for calcul the mask position with numpy : 0.0009522438049316406 nb_pixel_total : 15076 time to create 1 rle with old method : 0.01726818084716797 length of segment : 85 time for calcul the mask position with numpy : 0.003790616989135742 nb_pixel_total : 25559 time to create 1 rle with old method : 0.028522729873657227 length of segment : 250 time for calcul the mask position with numpy : 0.0015017986297607422 nb_pixel_total : 18767 time to create 1 rle with old method : 0.02116084098815918 length of segment : 143 time for calcul the mask position with numpy : 0.007679462432861328 nb_pixel_total : 79547 time to create 1 rle with old method : 0.08817696571350098 length of segment : 291 time for calcul the mask position with numpy : 0.006011009216308594 nb_pixel_total : 10713 time to create 1 rle with old method : 0.014459371566772461 length of segment : 108 time for calcul the mask position with numpy : 0.004301309585571289 nb_pixel_total : 48741 time to create 1 rle with old method : 0.05386829376220703 length of segment : 660 time for calcul the mask position with numpy : 0.0013632774353027344 nb_pixel_total : 67093 time to create 1 rle with old method : 0.07313179969787598 length of segment : 341 time for calcul the mask position with numpy : 0.004521369934082031 nb_pixel_total : 10923 time to create 1 rle with old method : 0.015074491500854492 length of segment : 141 time for calcul the mask position with numpy : 0.001905679702758789 nb_pixel_total : 43956 time to create 1 rle with old method : 0.04969048500061035 length of segment : 603 time for calcul the mask position with numpy : 0.0019731521606445312 nb_pixel_total : 10429 time to create 1 rle with old method : 0.011435270309448242 length of segment : 203 time for calcul the mask position with numpy : 0.0024907588958740234 nb_pixel_total : 12602 time to create 1 rle with old method : 0.0169677734375 length of segment : 182 time for calcul the mask position with numpy : 0.006181001663208008 nb_pixel_total : 83031 time to create 1 rle with old method : 0.10491466522216797 length of segment : 338 time for calcul the mask position with numpy : 0.06169486045837402 nb_pixel_total : 32140 time to create 1 rle with old method : 0.039139747619628906 length of segment : 233 time for calcul the mask position with numpy : 0.0049343109130859375 nb_pixel_total : 60556 time to create 1 rle with old method : 0.07243871688842773 length of segment : 315 time for calcul the mask position with numpy : 0.0018868446350097656 nb_pixel_total : 18193 time to create 1 rle with old method : 0.0270845890045166 length of segment : 180 time for calcul the mask position with numpy : 0.004410743713378906 nb_pixel_total : 7569 time to create 1 rle with old method : 0.010653972625732422 length of segment : 129 time for calcul the mask position with numpy : 0.0018773078918457031 nb_pixel_total : 12020 time to create 1 rle with old method : 0.014174938201904297 length of segment : 150 time for calcul the mask position with numpy : 0.0007851123809814453 nb_pixel_total : 8636 time to create 1 rle with old method : 0.009869813919067383 length of segment : 125 time for calcul the mask position with numpy : 0.013051986694335938 nb_pixel_total : 21143 time to create 1 rle with old method : 0.035230398178100586 length of segment : 148 time for calcul the mask position with numpy : 0.030065298080444336 nb_pixel_total : 11055 time to create 1 rle with old method : 0.016460895538330078 length of segment : 171 time for calcul the mask position with numpy : 0.01627635955810547 nb_pixel_total : 18452 time to create 1 rle with old method : 0.027172088623046875 length of segment : 170 time for calcul the mask position with numpy : 0.0467226505279541 nb_pixel_total : 23169 time to create 1 rle with old method : 0.025994062423706055 length of segment : 195 time for calcul the mask position with numpy : 0.0013535022735595703 nb_pixel_total : 10601 time to create 1 rle with old method : 0.012160778045654297 length of segment : 113 time for calcul the mask position with numpy : 0.0010619163513183594 nb_pixel_total : 16744 time to create 1 rle with old method : 0.019254684448242188 length of segment : 173 time for calcul the mask position with numpy : 0.0020596981048583984 nb_pixel_total : 7326 time to create 1 rle with old method : 0.008613348007202148 length of segment : 134 time for calcul the mask position with numpy : 0.0862281322479248 nb_pixel_total : 15337 time to create 1 rle with old method : 0.019835233688354492 length of segment : 274 time for calcul the mask position with numpy : 0.013247966766357422 nb_pixel_total : 16759 time to create 1 rle with old method : 0.021330595016479492 length of segment : 235 time for calcul the mask position with numpy : 0.0012631416320800781 nb_pixel_total : 10071 time to create 1 rle with old method : 0.01182699203491211 length of segment : 101 time for calcul the mask position with numpy : 0.0033593177795410156 nb_pixel_total : 8057 time to create 1 rle with old method : 0.01052713394165039 length of segment : 70 time for calcul the mask position with numpy : 0.001146554946899414 nb_pixel_total : 7973 time to create 1 rle with old method : 0.009058237075805664 length of segment : 138 time for calcul the mask position with numpy : 0.03479504585266113 nb_pixel_total : 238270 time to create 1 rle with new method : 0.028239965438842773 length of segment : 1095 time for calcul the mask position with numpy : 0.0002968311309814453 nb_pixel_total : 2682 time to create 1 rle with old method : 0.0032892227172851562 length of segment : 50 time for calcul the mask position with numpy : 0.002439737319946289 nb_pixel_total : 23119 time to create 1 rle with old method : 0.0262148380279541 length of segment : 211 time for calcul the mask position with numpy : 0.028668880462646484 nb_pixel_total : 11854 time to create 1 rle with old method : 0.01854562759399414 length of segment : 94 time for calcul the mask position with numpy : 0.028655290603637695 nb_pixel_total : 17215 time to create 1 rle with old method : 0.024905920028686523 length of segment : 146 time for calcul the mask position with numpy : 0.004971981048583984 nb_pixel_total : 7545 time to create 1 rle with old method : 0.010378837585449219 length of segment : 79 time for calcul the mask position with numpy : 0.0034928321838378906 nb_pixel_total : 28844 time to create 1 rle with old method : 0.033535003662109375 length of segment : 146 time for calcul the mask position with numpy : 0.16014671325683594 nb_pixel_total : 107176 time to create 1 rle with old method : 0.12644219398498535 length of segment : 290 time for calcul the mask position with numpy : 0.003332853317260742 nb_pixel_total : 14879 time to create 1 rle with old method : 0.016429424285888672 length of segment : 145 time for calcul the mask position with numpy : 0.0017995834350585938 nb_pixel_total : 24236 time to create 1 rle with old method : 0.02664923667907715 length of segment : 148 time for calcul the mask position with numpy : 0.03905510902404785 nb_pixel_total : 33725 time to create 1 rle with old method : 0.04078793525695801 length of segment : 243 time for calcul the mask position with numpy : 0.003412961959838867 nb_pixel_total : 17192 time to create 1 rle with old method : 0.021648645401000977 length of segment : 170 time for calcul the mask position with numpy : 0.0025129318237304688 nb_pixel_total : 12032 time to create 1 rle with old method : 0.016195297241210938 length of segment : 123 time for calcul the mask position with numpy : 0.021624088287353516 nb_pixel_total : 2492 time to create 1 rle with old method : 0.005174398422241211 length of segment : 96 time for calcul the mask position with numpy : 0.0030252933502197266 nb_pixel_total : 49044 time to create 1 rle with old method : 0.05344891548156738 length of segment : 183 time for calcul the mask position with numpy : 0.006647348403930664 nb_pixel_total : 30048 time to create 1 rle with old method : 0.03489351272583008 length of segment : 187 time for calcul the mask position with numpy : 0.000438690185546875 nb_pixel_total : 23440 time to create 1 rle with old method : 0.025734901428222656 length of segment : 153 time for calcul the mask position with numpy : 0.0004582405090332031 nb_pixel_total : 27058 time to create 1 rle with old method : 0.029152631759643555 length of segment : 161 time for calcul the mask position with numpy : 0.03176093101501465 nb_pixel_total : 24889 time to create 1 rle with old method : 0.029620647430419922 length of segment : 236 time for calcul the mask position with numpy : 0.002586841583251953 nb_pixel_total : 16216 time to create 1 rle with old method : 0.017877817153930664 length of segment : 175 time for calcul the mask position with numpy : 0.01232290267944336 nb_pixel_total : 6717 time to create 1 rle with old method : 0.012469053268432617 length of segment : 89 time for calcul the mask position with numpy : 0.04062175750732422 nb_pixel_total : 16276 time to create 1 rle with old method : 0.021875381469726562 length of segment : 273 time for calcul the mask position with numpy : 0.007081031799316406 nb_pixel_total : 42700 time to create 1 rle with old method : 0.048429012298583984 length of segment : 396 time for calcul the mask position with numpy : 0.01887679100036621 nb_pixel_total : 10792 time to create 1 rle with old method : 0.016208648681640625 length of segment : 140 time for calcul the mask position with numpy : 0.016177654266357422 nb_pixel_total : 83781 time to create 1 rle with old method : 0.09342288970947266 length of segment : 453 time for calcul the mask position with numpy : 0.012733221054077148 nb_pixel_total : 61517 time to create 1 rle with old method : 0.06761288642883301 length of segment : 392 time for calcul the mask position with numpy : 0.0037508010864257812 nb_pixel_total : 21763 time to create 1 rle with old method : 0.026264190673828125 length of segment : 261 time for calcul the mask position with numpy : 0.0017609596252441406 nb_pixel_total : 8545 time to create 1 rle with old method : 0.009445905685424805 length of segment : 88 time for calcul the mask position with numpy : 0.0035076141357421875 nb_pixel_total : 27415 time to create 1 rle with old method : 0.030182361602783203 length of segment : 405 time for calcul the mask position with numpy : 0.0018353462219238281 nb_pixel_total : 7500 time to create 1 rle with old method : 0.008351564407348633 length of segment : 94 time for calcul the mask position with numpy : 0.0028564929962158203 nb_pixel_total : 28196 time to create 1 rle with old method : 0.030109643936157227 length of segment : 219 time for calcul the mask position with numpy : 0.018924951553344727 nb_pixel_total : 9491 time to create 1 rle with old method : 0.012981653213500977 length of segment : 166 time for calcul the mask position with numpy : 0.005288362503051758 nb_pixel_total : 53860 time to create 1 rle with old method : 0.06123828887939453 length of segment : 468 time for calcul the mask position with numpy : 0.0049097537994384766 nb_pixel_total : 29631 time to create 1 rle with old method : 0.03495144844055176 length of segment : 362 time for calcul the mask position with numpy : 0.009168148040771484 nb_pixel_total : 14666 time to create 1 rle with old method : 0.019143104553222656 length of segment : 165 time for calcul the mask position with numpy : 0.0060579776763916016 nb_pixel_total : 51955 time to create 1 rle with old method : 0.06064748764038086 length of segment : 317 time for calcul the mask position with numpy : 0.017200946807861328 nb_pixel_total : 14584 time to create 1 rle with old method : 0.020254850387573242 length of segment : 103 time for calcul the mask position with numpy : 0.01740574836730957 nb_pixel_total : 62377 time to create 1 rle with old method : 0.07095551490783691 length of segment : 362 time for calcul the mask position with numpy : 0.0012311935424804688 nb_pixel_total : 9754 time to create 1 rle with old method : 0.010942697525024414 length of segment : 108 time for calcul the mask position with numpy : 0.03429293632507324 nb_pixel_total : 29807 time to create 1 rle with old method : 0.03718376159667969 length of segment : 535 time for calcul the mask position with numpy : 0.003222227096557617 nb_pixel_total : 3829 time to create 1 rle with old method : 0.017004966735839844 length of segment : 65 time for calcul the mask position with numpy : 0.004840850830078125 nb_pixel_total : 4164 time to create 1 rle with old method : 0.005044698715209961 length of segment : 56 time for calcul the mask position with numpy : 0.05058145523071289 nb_pixel_total : 56947 time to create 1 rle with old method : 0.08242535591125488 length of segment : 396 time for calcul the mask position with numpy : 0.01303410530090332 nb_pixel_total : 51442 time to create 1 rle with old method : 0.05955815315246582 length of segment : 569 time for calcul the mask position with numpy : 0.010110855102539062 nb_pixel_total : 59569 time to create 1 rle with old method : 0.06879186630249023 length of segment : 303 time for calcul the mask position with numpy : 0.03030705451965332 nb_pixel_total : 38859 time to create 1 rle with old method : 0.046138763427734375 length of segment : 341 time for calcul the mask position with numpy : 0.005025386810302734 nb_pixel_total : 47730 time to create 1 rle with old method : 0.05439257621765137 length of segment : 237 time for calcul the mask position with numpy : 0.0015506744384765625 nb_pixel_total : 14467 time to create 1 rle with old method : 0.015552043914794922 length of segment : 164 time for calcul the mask position with numpy : 0.004586219787597656 nb_pixel_total : 41081 time to create 1 rle with old method : 0.044860124588012695 length of segment : 252 time for calcul the mask position with numpy : 0.0208587646484375 nb_pixel_total : 61810 time to create 1 rle with old method : 0.09276270866394043 length of segment : 309 time for calcul the mask position with numpy : 0.02208733558654785 nb_pixel_total : 69288 time to create 1 rle with old method : 0.07224059104919434 length of segment : 428 time for calcul the mask position with numpy : 0.008305072784423828 nb_pixel_total : 19842 time to create 1 rle with old method : 0.02433180809020996 length of segment : 218 time for calcul the mask position with numpy : 0.007016181945800781 nb_pixel_total : 8593 time to create 1 rle with old method : 0.01585102081298828 length of segment : 96 time for calcul the mask position with numpy : 0.010784387588500977 nb_pixel_total : 85315 time to create 1 rle with old method : 0.10581016540527344 length of segment : 404 time for calcul the mask position with numpy : 0.0007636547088623047 nb_pixel_total : 10884 time to create 1 rle with old method : 0.011766672134399414 length of segment : 127 time for calcul the mask position with numpy : 0.0018267631530761719 nb_pixel_total : 19023 time to create 1 rle with old method : 0.021112918853759766 length of segment : 196 time for calcul the mask position with numpy : 0.06394481658935547 nb_pixel_total : 126923 time to create 1 rle with old method : 0.13990259170532227 length of segment : 388 time for calcul the mask position with numpy : 0.015098333358764648 nb_pixel_total : 46406 time to create 1 rle with old method : 0.05160355567932129 length of segment : 430 time for calcul the mask position with numpy : 0.0175020694732666 nb_pixel_total : 72299 time to create 1 rle with old method : 0.08240675926208496 length of segment : 229 time for calcul the mask position with numpy : 0.08742260932922363 nb_pixel_total : 404386 time to create 1 rle with new method : 0.03611159324645996 length of segment : 869 time for calcul the mask position with numpy : 0.0010020732879638672 nb_pixel_total : 6201 time to create 1 rle with old method : 0.0071027278900146484 length of segment : 82 time for calcul the mask position with numpy : 0.0059092044830322266 nb_pixel_total : 107154 time to create 1 rle with old method : 0.12099909782409668 length of segment : 445 time for calcul the mask position with numpy : 0.012789487838745117 nb_pixel_total : 10726 time to create 1 rle with old method : 0.017412662506103516 length of segment : 95 time for calcul the mask position with numpy : 0.02836918830871582 nb_pixel_total : 165626 time to create 1 rle with new method : 0.007920980453491211 length of segment : 323 time for calcul the mask position with numpy : 0.06380319595336914 nb_pixel_total : 257627 time to create 1 rle with new method : 0.019954681396484375 length of segment : 815 time for calcul the mask position with numpy : 0.0014369487762451172 nb_pixel_total : 2784 time to create 1 rle with old method : 0.003197908401489258 length of segment : 85 time for calcul the mask position with numpy : 0.0052530765533447266 nb_pixel_total : 53476 time to create 1 rle with old method : 0.05997943878173828 length of segment : 352 time for calcul the mask position with numpy : 0.0073604583740234375 nb_pixel_total : 22561 time to create 1 rle with old method : 0.027360200881958008 length of segment : 157 time for calcul the mask position with numpy : 0.0025920867919921875 nb_pixel_total : 26846 time to create 1 rle with old method : 0.028431177139282227 length of segment : 257 time for calcul the mask position with numpy : 0.006678581237792969 nb_pixel_total : 80502 time to create 1 rle with old method : 0.08809423446655273 length of segment : 267 time for calcul the mask position with numpy : 0.005509376525878906 nb_pixel_total : 27042 time to create 1 rle with old method : 0.03360724449157715 length of segment : 201 time for calcul the mask position with numpy : 0.007141590118408203 nb_pixel_total : 36941 time to create 1 rle with old method : 0.04259467124938965 length of segment : 199 time for calcul the mask position with numpy : 0.009120464324951172 nb_pixel_total : 7006 time to create 1 rle with old method : 0.013321876525878906 length of segment : 86 time for calcul the mask position with numpy : 0.003611326217651367 nb_pixel_total : 50111 time to create 1 rle with old method : 0.054842472076416016 length of segment : 277 time for calcul the mask position with numpy : 0.0012485980987548828 nb_pixel_total : 19064 time to create 1 rle with old method : 0.02074122428894043 length of segment : 275 time for calcul the mask position with numpy : 0.0011565685272216797 nb_pixel_total : 9014 time to create 1 rle with old method : 0.010111331939697266 length of segment : 186 time for calcul the mask position with numpy : 0.0029532909393310547 nb_pixel_total : 17222 time to create 1 rle with old method : 0.01941061019897461 length of segment : 145 time for calcul the mask position with numpy : 0.0010623931884765625 nb_pixel_total : 16367 time to create 1 rle with old method : 0.018219470977783203 length of segment : 126 time for calcul the mask position with numpy : 0.07310366630554199 nb_pixel_total : 231204 time to create 1 rle with new method : 0.01979374885559082 length of segment : 664 time for calcul the mask position with numpy : 0.006117105484008789 nb_pixel_total : 19295 time to create 1 rle with old method : 0.02532219886779785 length of segment : 270 time for calcul the mask position with numpy : 0.0056383609771728516 nb_pixel_total : 25879 time to create 1 rle with old method : 0.028867721557617188 length of segment : 404 time for calcul the mask position with numpy : 0.0047607421875 nb_pixel_total : 34933 time to create 1 rle with old method : 0.03999829292297363 length of segment : 174 time for calcul the mask position with numpy : 0.008409738540649414 nb_pixel_total : 35048 time to create 1 rle with old method : 0.04060840606689453 length of segment : 461 time for calcul the mask position with numpy : 0.004698038101196289 nb_pixel_total : 38676 time to create 1 rle with old method : 0.042108774185180664 length of segment : 283 time for calcul the mask position with numpy : 0.0016033649444580078 nb_pixel_total : 6656 time to create 1 rle with old method : 0.007740974426269531 length of segment : 86 time for calcul the mask position with numpy : 0.13072752952575684 nb_pixel_total : 89213 time to create 1 rle with old method : 0.10595822334289551 length of segment : 361 time for calcul the mask position with numpy : 0.0024755001068115234 nb_pixel_total : 20130 time to create 1 rle with old method : 0.02250814437866211 length of segment : 189 time for calcul the mask position with numpy : 0.0016870498657226562 nb_pixel_total : 10425 time to create 1 rle with old method : 0.011928558349609375 length of segment : 96 time for calcul the mask position with numpy : 0.006571054458618164 nb_pixel_total : 21994 time to create 1 rle with old method : 0.02453899383544922 length of segment : 158 time for calcul the mask position with numpy : 0.038982391357421875 nb_pixel_total : 12287 time to create 1 rle with old method : 0.020068883895874023 length of segment : 106 time for calcul the mask position with numpy : 0.004337310791015625 nb_pixel_total : 26354 time to create 1 rle with old method : 0.028810977935791016 length of segment : 225 time for calcul the mask position with numpy : 0.005136013031005859 nb_pixel_total : 14286 time to create 1 rle with old method : 0.018014192581176758 length of segment : 275 time for calcul the mask position with numpy : 0.00045943260192871094 nb_pixel_total : 8955 time to create 1 rle with old method : 0.01048731803894043 length of segment : 96 time for calcul the mask position with numpy : 0.004029750823974609 nb_pixel_total : 24827 time to create 1 rle with old method : 0.029459714889526367 length of segment : 154 time for calcul the mask position with numpy : 0.006932735443115234 nb_pixel_total : 39185 time to create 1 rle with old method : 0.046639442443847656 length of segment : 350 time for calcul the mask position with numpy : 0.004701137542724609 nb_pixel_total : 21118 time to create 1 rle with old method : 0.022377729415893555 length of segment : 242 time for calcul the mask position with numpy : 0.0006270408630371094 nb_pixel_total : 7273 time to create 1 rle with old method : 0.008265495300292969 length of segment : 121 time for calcul the mask position with numpy : 0.003703594207763672 nb_pixel_total : 29640 time to create 1 rle with old method : 0.034243106842041016 length of segment : 247 time for calcul the mask position with numpy : 0.007207393646240234 nb_pixel_total : 23208 time to create 1 rle with old method : 0.02753472328186035 length of segment : 202 time for calcul the mask position with numpy : 0.0018134117126464844 nb_pixel_total : 11684 time to create 1 rle with old method : 0.012632608413696289 length of segment : 144 time for calcul the mask position with numpy : 0.0021877288818359375 nb_pixel_total : 20065 time to create 1 rle with old method : 0.021989822387695312 length of segment : 166 time for calcul the mask position with numpy : 0.07488751411437988 nb_pixel_total : 45690 time to create 1 rle with old method : 0.0539240837097168 length of segment : 257 time for calcul the mask position with numpy : 0.024957895278930664 nb_pixel_total : 66355 time to create 1 rle with old method : 0.09092903137207031 length of segment : 418 time for calcul the mask position with numpy : 0.002449512481689453 nb_pixel_total : 19683 time to create 1 rle with old method : 0.021240711212158203 length of segment : 211 time for calcul the mask position with numpy : 0.008779764175415039 nb_pixel_total : 27371 time to create 1 rle with old method : 0.034758567810058594 length of segment : 263 time for calcul the mask position with numpy : 0.00037097930908203125 nb_pixel_total : 4560 time to create 1 rle with old method : 0.005232810974121094 length of segment : 71 time for calcul the mask position with numpy : 0.0009095668792724609 nb_pixel_total : 7080 time to create 1 rle with old method : 0.007901191711425781 length of segment : 96 time for calcul the mask position with numpy : 0.0005190372467041016 nb_pixel_total : 15369 time to create 1 rle with old method : 0.016873836517333984 length of segment : 164 time for calcul the mask position with numpy : 0.00038433074951171875 nb_pixel_total : 12366 time to create 1 rle with old method : 0.014137983322143555 length of segment : 190 time for calcul the mask position with numpy : 0.0016775131225585938 nb_pixel_total : 20325 time to create 1 rle with old method : 0.023203372955322266 length of segment : 175 time for calcul the mask position with numpy : 0.003754854202270508 nb_pixel_total : 7513 time to create 1 rle with old method : 0.00908660888671875 length of segment : 146 time for calcul the mask position with numpy : 0.008926153182983398 nb_pixel_total : 15701 time to create 1 rle with old method : 0.019763469696044922 length of segment : 283 time for calcul the mask position with numpy : 0.0030851364135742188 nb_pixel_total : 26307 time to create 1 rle with old method : 0.030444860458374023 length of segment : 184 time for calcul the mask position with numpy : 0.003178834915161133 nb_pixel_total : 14160 time to create 1 rle with old method : 0.018080711364746094 length of segment : 144 time for calcul the mask position with numpy : 0.0008130073547363281 nb_pixel_total : 5201 time to create 1 rle with old method : 0.005689859390258789 length of segment : 208 time for calcul the mask position with numpy : 0.0005304813385009766 nb_pixel_total : 24132 time to create 1 rle with old method : 0.027501583099365234 length of segment : 164 time for calcul the mask position with numpy : 0.0040132999420166016 nb_pixel_total : 42816 time to create 1 rle with old method : 0.047156333923339844 length of segment : 265 time for calcul the mask position with numpy : 0.04254508018493652 nb_pixel_total : 25997 time to create 1 rle with old method : 0.03385806083679199 length of segment : 132 time for calcul the mask position with numpy : 0.0021402835845947266 nb_pixel_total : 11825 time to create 1 rle with old method : 0.013949394226074219 length of segment : 156 time for calcul the mask position with numpy : 0.0013883113861083984 nb_pixel_total : 26652 time to create 1 rle with old method : 0.02996039390563965 length of segment : 170 time for calcul the mask position with numpy : 0.015936613082885742 nb_pixel_total : 29940 time to create 1 rle with old method : 0.033312082290649414 length of segment : 244 time for calcul the mask position with numpy : 0.006525754928588867 nb_pixel_total : 15683 time to create 1 rle with old method : 0.018071889877319336 length of segment : 147 time for calcul the mask position with numpy : 0.003487825393676758 nb_pixel_total : 22559 time to create 1 rle with old method : 0.025107145309448242 length of segment : 245 time for calcul the mask position with numpy : 0.000911712646484375 nb_pixel_total : 13114 time to create 1 rle with old method : 0.015063047409057617 length of segment : 173 time for calcul the mask position with numpy : 0.011491537094116211 nb_pixel_total : 26089 time to create 1 rle with old method : 0.03202486038208008 length of segment : 188 time for calcul the mask position with numpy : 0.0019457340240478516 nb_pixel_total : 10559 time to create 1 rle with old method : 0.012243032455444336 length of segment : 121 time for calcul the mask position with numpy : 0.013423919677734375 nb_pixel_total : 43405 time to create 1 rle with old method : 0.051168203353881836 length of segment : 246 time for calcul the mask position with numpy : 0.009885072708129883 nb_pixel_total : 25064 time to create 1 rle with old method : 0.03601694107055664 length of segment : 397 time for calcul the mask position with numpy : 0.01944136619567871 nb_pixel_total : 117128 time to create 1 rle with old method : 0.1888110637664795 length of segment : 433 time for calcul the mask position with numpy : 0.002624034881591797 nb_pixel_total : 15876 time to create 1 rle with old method : 0.04161500930786133 length of segment : 214 time for calcul the mask position with numpy : 0.03174424171447754 nb_pixel_total : 24981 time to create 1 rle with old method : 0.11828446388244629 length of segment : 258 time for calcul the mask position with numpy : 0.12538695335388184 nb_pixel_total : 27270 time to create 1 rle with old method : 0.053028106689453125 length of segment : 291 time for calcul the mask position with numpy : 0.014297246932983398 nb_pixel_total : 9937 time to create 1 rle with old method : 0.030124902725219727 length of segment : 145 time for calcul the mask position with numpy : 0.006041765213012695 nb_pixel_total : 5933 time to create 1 rle with old method : 0.01413273811340332 length of segment : 147 time for calcul the mask position with numpy : 0.024631738662719727 nb_pixel_total : 37782 time to create 1 rle with old method : 0.0713040828704834 length of segment : 268 time for calcul the mask position with numpy : 0.003969907760620117 nb_pixel_total : 9348 time to create 1 rle with old method : 0.017464160919189453 length of segment : 133 time for calcul the mask position with numpy : 0.006896018981933594 nb_pixel_total : 32823 time to create 1 rle with old method : 0.06328392028808594 length of segment : 204 time for calcul the mask position with numpy : 0.00573420524597168 nb_pixel_total : 35928 time to create 1 rle with old method : 0.08034133911132812 length of segment : 230 time for calcul the mask position with numpy : 0.027251720428466797 nb_pixel_total : 57583 time to create 1 rle with old method : 0.12288808822631836 length of segment : 358 time for calcul the mask position with numpy : 0.0014185905456542969 nb_pixel_total : 11004 time to create 1 rle with old method : 0.02022385597229004 length of segment : 116 time for calcul the mask position with numpy : 0.0007579326629638672 nb_pixel_total : 2022 time to create 1 rle with old method : 0.004142045974731445 length of segment : 137 time for calcul the mask position with numpy : 0.00854182243347168 nb_pixel_total : 36298 time to create 1 rle with old method : 0.0659637451171875 length of segment : 329 time for calcul the mask position with numpy : 0.0016283988952636719 nb_pixel_total : 8395 time to create 1 rle with old method : 0.021260738372802734 length of segment : 151 time for calcul the mask position with numpy : 0.004232168197631836 nb_pixel_total : 17198 time to create 1 rle with old method : 0.03520512580871582 length of segment : 168 time for calcul the mask position with numpy : 0.008778095245361328 nb_pixel_total : 14282 time to create 1 rle with old method : 0.02433919906616211 length of segment : 101 time for calcul the mask position with numpy : 0.002712726593017578 nb_pixel_total : 15324 time to create 1 rle with old method : 0.019491195678710938 length of segment : 159 time for calcul the mask position with numpy : 0.011219263076782227 nb_pixel_total : 20785 time to create 1 rle with old method : 0.029022932052612305 length of segment : 194 time for calcul the mask position with numpy : 0.005733966827392578 nb_pixel_total : 29931 time to create 1 rle with old method : 0.04880857467651367 length of segment : 195 time for calcul the mask position with numpy : 0.0022482872009277344 nb_pixel_total : 19898 time to create 1 rle with old method : 0.02288675308227539 length of segment : 228 time for calcul the mask position with numpy : 0.011075019836425781 nb_pixel_total : 36593 time to create 1 rle with old method : 0.04127311706542969 length of segment : 370 time for calcul the mask position with numpy : 0.0027053356170654297 nb_pixel_total : 30758 time to create 1 rle with old method : 0.03446674346923828 length of segment : 216 time for calcul the mask position with numpy : 0.0023839473724365234 nb_pixel_total : 17702 time to create 1 rle with old method : 0.019469499588012695 length of segment : 231 time for calcul the mask position with numpy : 0.004283905029296875 nb_pixel_total : 17023 time to create 1 rle with old method : 0.02868342399597168 length of segment : 112 time for calcul the mask position with numpy : 0.008845329284667969 nb_pixel_total : 60444 time to create 1 rle with old method : 0.0701594352722168 length of segment : 399 time for calcul the mask position with numpy : 0.004010677337646484 nb_pixel_total : 37328 time to create 1 rle with old method : 0.04114985466003418 length of segment : 281 time for calcul the mask position with numpy : 0.004049539566040039 nb_pixel_total : 36207 time to create 1 rle with old method : 0.0406947135925293 length of segment : 281 time for calcul the mask position with numpy : 0.0019104480743408203 nb_pixel_total : 22588 time to create 1 rle with old method : 0.0275723934173584 length of segment : 106 time for calcul the mask position with numpy : 0.010536909103393555 nb_pixel_total : 35343 time to create 1 rle with old method : 0.04412102699279785 length of segment : 188 time for calcul the mask position with numpy : 0.005873441696166992 nb_pixel_total : 10373 time to create 1 rle with old method : 0.012026548385620117 length of segment : 86 time for calcul the mask position with numpy : 0.002186298370361328 nb_pixel_total : 12771 time to create 1 rle with old method : 0.015048503875732422 length of segment : 145 time for calcul the mask position with numpy : 0.003890514373779297 nb_pixel_total : 45421 time to create 1 rle with old method : 0.05110669136047363 length of segment : 233 time for calcul the mask position with numpy : 0.002324342727661133 nb_pixel_total : 19107 time to create 1 rle with old method : 0.02174830436706543 length of segment : 339 time for calcul the mask position with numpy : 0.001931905746459961 nb_pixel_total : 19317 time to create 1 rle with old method : 0.021893739700317383 length of segment : 211 time for calcul the mask position with numpy : 0.0016126632690429688 nb_pixel_total : 26921 time to create 1 rle with old method : 0.030751705169677734 length of segment : 258 time for calcul the mask position with numpy : 0.00316619873046875 nb_pixel_total : 19555 time to create 1 rle with old method : 0.02264237403869629 length of segment : 191 time for calcul the mask position with numpy : 0.0011188983917236328 nb_pixel_total : 3712 time to create 1 rle with old method : 0.00452876091003418 length of segment : 64 time for calcul the mask position with numpy : 0.002877950668334961 nb_pixel_total : 10718 time to create 1 rle with old method : 0.012325525283813477 length of segment : 201 time for calcul the mask position with numpy : 0.003502368927001953 nb_pixel_total : 19601 time to create 1 rle with old method : 0.02245926856994629 length of segment : 195 time for calcul the mask position with numpy : 0.004738569259643555 nb_pixel_total : 29794 time to create 1 rle with old method : 0.03825020790100098 length of segment : 254 time for calcul the mask position with numpy : 0.0010459423065185547 nb_pixel_total : 12036 time to create 1 rle with old method : 0.013735055923461914 length of segment : 121 time for calcul the mask position with numpy : 0.0031723976135253906 nb_pixel_total : 23520 time to create 1 rle with old method : 0.034294843673706055 length of segment : 222 time for calcul the mask position with numpy : 0.0024385452270507812 nb_pixel_total : 17132 time to create 1 rle with old method : 0.02590012550354004 length of segment : 220 time for calcul the mask position with numpy : 0.0049135684967041016 nb_pixel_total : 51850 time to create 1 rle with old method : 0.05842399597167969 length of segment : 297 time for calcul the mask position with numpy : 0.0011489391326904297 nb_pixel_total : 13734 time to create 1 rle with old method : 0.016053438186645508 length of segment : 136 time for calcul the mask position with numpy : 0.002173185348510742 nb_pixel_total : 12768 time to create 1 rle with old method : 0.015242815017700195 length of segment : 90 time for calcul the mask position with numpy : 0.002856731414794922 nb_pixel_total : 23060 time to create 1 rle with old method : 0.026317834854125977 length of segment : 224 time for calcul the mask position with numpy : 0.0017571449279785156 nb_pixel_total : 20895 time to create 1 rle with old method : 0.02420330047607422 length of segment : 154 time for calcul the mask position with numpy : 0.012480735778808594 nb_pixel_total : 56436 time to create 1 rle with old method : 0.06504392623901367 length of segment : 456 time for calcul the mask position with numpy : 0.0006577968597412109 nb_pixel_total : 4714 time to create 1 rle with old method : 0.008023738861083984 length of segment : 95 time for calcul the mask position with numpy : 0.00811767578125 nb_pixel_total : 57017 time to create 1 rle with old method : 0.06354212760925293 length of segment : 382 time for calcul the mask position with numpy : 0.004422664642333984 nb_pixel_total : 25931 time to create 1 rle with old method : 0.029305696487426758 length of segment : 199 time for calcul the mask position with numpy : 0.0022373199462890625 nb_pixel_total : 19032 time to create 1 rle with old method : 0.021552324295043945 length of segment : 160 time for calcul the mask position with numpy : 0.017237186431884766 nb_pixel_total : 101856 time to create 1 rle with old method : 0.11556482315063477 length of segment : 813 time for calcul the mask position with numpy : 0.0003998279571533203 nb_pixel_total : 11293 time to create 1 rle with old method : 0.013094186782836914 length of segment : 191 time for calcul the mask position with numpy : 0.01524806022644043 nb_pixel_total : 20464 time to create 1 rle with old method : 0.028293132781982422 length of segment : 133 time for calcul the mask position with numpy : 0.026526689529418945 nb_pixel_total : 43325 time to create 1 rle with old method : 0.07360291481018066 length of segment : 256 time for calcul the mask position with numpy : 0.009253978729248047 nb_pixel_total : 9086 time to create 1 rle with old method : 0.012012958526611328 length of segment : 115 time for calcul the mask position with numpy : 0.01027989387512207 nb_pixel_total : 48326 time to create 1 rle with old method : 0.059374094009399414 length of segment : 285 time for calcul the mask position with numpy : 0.0012664794921875 nb_pixel_total : 12347 time to create 1 rle with old method : 0.01408839225769043 length of segment : 156 time for calcul the mask position with numpy : 0.0019376277923583984 nb_pixel_total : 31516 time to create 1 rle with old method : 0.035709381103515625 length of segment : 227 time for calcul the mask position with numpy : 0.002191305160522461 nb_pixel_total : 24286 time to create 1 rle with old method : 0.0269014835357666 length of segment : 306 time for calcul the mask position with numpy : 0.003969669342041016 nb_pixel_total : 14140 time to create 1 rle with old method : 0.015891551971435547 length of segment : 192 time for calcul the mask position with numpy : 0.008205413818359375 nb_pixel_total : 74838 time to create 1 rle with old method : 0.08646750450134277 length of segment : 316 time for calcul the mask position with numpy : 0.001009225845336914 nb_pixel_total : 3776 time to create 1 rle with old method : 0.004540205001831055 length of segment : 66 time for calcul the mask position with numpy : 0.00668644905090332 nb_pixel_total : 41024 time to create 1 rle with old method : 0.049103498458862305 length of segment : 382 time for calcul the mask position with numpy : 0.06871938705444336 nb_pixel_total : 4662 time to create 1 rle with old method : 0.009389162063598633 length of segment : 68 time for calcul the mask position with numpy : 0.003106832504272461 nb_pixel_total : 40269 time to create 1 rle with old method : 0.044933319091796875 length of segment : 349 time for calcul the mask position with numpy : 0.0024688243865966797 nb_pixel_total : 20648 time to create 1 rle with old method : 0.023236513137817383 length of segment : 174 time for calcul the mask position with numpy : 0.0006194114685058594 nb_pixel_total : 12456 time to create 1 rle with old method : 0.014413833618164062 length of segment : 161 time for calcul the mask position with numpy : 0.0010395050048828125 nb_pixel_total : 11818 time to create 1 rle with old method : 0.013625621795654297 length of segment : 169 time for calcul the mask position with numpy : 0.005570411682128906 nb_pixel_total : 7799 time to create 1 rle with old method : 0.011168241500854492 length of segment : 106 time for calcul the mask position with numpy : 0.0007703304290771484 nb_pixel_total : 20416 time to create 1 rle with old method : 0.024187803268432617 length of segment : 144 time for calcul the mask position with numpy : 0.0005927085876464844 nb_pixel_total : 9670 time to create 1 rle with old method : 0.011287212371826172 length of segment : 104 time for calcul the mask position with numpy : 0.008828401565551758 nb_pixel_total : 20749 time to create 1 rle with old method : 0.02378225326538086 length of segment : 174 time for calcul the mask position with numpy : 0.0026252269744873047 nb_pixel_total : 4075 time to create 1 rle with old method : 0.0051419734954833984 length of segment : 72 time for calcul the mask position with numpy : 0.0028939247131347656 nb_pixel_total : 32819 time to create 1 rle with old method : 0.03693413734436035 length of segment : 375 time for calcul the mask position with numpy : 0.0006256103515625 nb_pixel_total : 6346 time to create 1 rle with old method : 0.010944366455078125 length of segment : 122 time for calcul the mask position with numpy : 0.0007405281066894531 nb_pixel_total : 11836 time to create 1 rle with old method : 0.018816471099853516 length of segment : 94 time for calcul the mask position with numpy : 0.018860340118408203 nb_pixel_total : 51645 time to create 1 rle with old method : 0.0688788890838623 length of segment : 501 time for calcul the mask position with numpy : 0.0012664794921875 nb_pixel_total : 19778 time to create 1 rle with old method : 0.025155305862426758 length of segment : 196 time for calcul the mask position with numpy : 0.001990795135498047 nb_pixel_total : 20334 time to create 1 rle with old method : 0.028566837310791016 length of segment : 175 time for calcul the mask position with numpy : 0.004038333892822266 nb_pixel_total : 30810 time to create 1 rle with old method : 0.03927803039550781 length of segment : 216 time for calcul the mask position with numpy : 0.004894733428955078 nb_pixel_total : 49137 time to create 1 rle with old method : 0.06345033645629883 length of segment : 439 time for calcul the mask position with numpy : 0.0028307437896728516 nb_pixel_total : 39463 time to create 1 rle with old method : 0.044618844985961914 length of segment : 327 time for calcul the mask position with numpy : 0.0021295547485351562 nb_pixel_total : 45898 time to create 1 rle with old method : 0.0599212646484375 length of segment : 360 time for calcul the mask position with numpy : 0.0007281303405761719 nb_pixel_total : 14902 time to create 1 rle with old method : 0.02065873146057129 length of segment : 260 time for calcul the mask position with numpy : 0.0007252693176269531 nb_pixel_total : 4773 time to create 1 rle with old method : 0.005753993988037109 length of segment : 80 time for calcul the mask position with numpy : 0.0018804073333740234 nb_pixel_total : 25430 time to create 1 rle with old method : 0.02960038185119629 length of segment : 229 time for calcul the mask position with numpy : 0.0006604194641113281 nb_pixel_total : 12710 time to create 1 rle with old method : 0.015071630477905273 length of segment : 139 time for calcul the mask position with numpy : 0.00470280647277832 nb_pixel_total : 27468 time to create 1 rle with old method : 0.03270459175109863 length of segment : 206 time for calcul the mask position with numpy : 0.004044294357299805 nb_pixel_total : 50244 time to create 1 rle with old method : 0.05714702606201172 length of segment : 375 time for calcul the mask position with numpy : 0.0021486282348632812 nb_pixel_total : 17248 time to create 1 rle with old method : 0.019941091537475586 length of segment : 167 time for calcul the mask position with numpy : 0.0011322498321533203 nb_pixel_total : 6241 time to create 1 rle with old method : 0.0070037841796875 length of segment : 118 time for calcul the mask position with numpy : 0.0021986961364746094 nb_pixel_total : 32058 time to create 1 rle with old method : 0.03575253486633301 length of segment : 325 time for calcul the mask position with numpy : 0.007554292678833008 nb_pixel_total : 90264 time to create 1 rle with old method : 0.10034751892089844 length of segment : 383 time for calcul the mask position with numpy : 0.005319833755493164 nb_pixel_total : 32807 time to create 1 rle with old method : 0.03718113899230957 length of segment : 308 time for calcul the mask position with numpy : 0.0007443428039550781 nb_pixel_total : 10854 time to create 1 rle with old method : 0.012274742126464844 length of segment : 144 time for calcul the mask position with numpy : 0.0030417442321777344 nb_pixel_total : 72753 time to create 1 rle with old method : 0.08019542694091797 length of segment : 248 time for calcul the mask position with numpy : 0.002719879150390625 nb_pixel_total : 19105 time to create 1 rle with old method : 0.02123236656188965 length of segment : 159 time for calcul the mask position with numpy : 0.0026884078979492188 nb_pixel_total : 32275 time to create 1 rle with old method : 0.03613424301147461 length of segment : 366 time for calcul the mask position with numpy : 0.004076957702636719 nb_pixel_total : 43174 time to create 1 rle with old method : 0.045900821685791016 length of segment : 427 time for calcul the mask position with numpy : 0.0008051395416259766 nb_pixel_total : 10391 time to create 1 rle with old method : 0.012156486511230469 length of segment : 86 time for calcul the mask position with numpy : 0.003910064697265625 nb_pixel_total : 45793 time to create 1 rle with old method : 0.0520632266998291 length of segment : 385 time for calcul the mask position with numpy : 0.0019571781158447266 nb_pixel_total : 38863 time to create 1 rle with old method : 0.04416537284851074 length of segment : 205 time for calcul the mask position with numpy : 0.0008769035339355469 nb_pixel_total : 11174 time to create 1 rle with old method : 0.013418912887573242 length of segment : 71 time for calcul the mask position with numpy : 0.0008606910705566406 nb_pixel_total : 11445 time to create 1 rle with old method : 0.013271093368530273 length of segment : 132 time for calcul the mask position with numpy : 0.005347013473510742 nb_pixel_total : 64385 time to create 1 rle with old method : 0.0958714485168457 length of segment : 362 time for calcul the mask position with numpy : 0.0008306503295898438 nb_pixel_total : 8769 time to create 1 rle with old method : 0.010290861129760742 length of segment : 133 time for calcul the mask position with numpy : 0.0010960102081298828 nb_pixel_total : 17018 time to create 1 rle with old method : 0.01959395408630371 length of segment : 154 time for calcul the mask position with numpy : 0.0070912837982177734 nb_pixel_total : 71440 time to create 1 rle with old method : 0.08004498481750488 length of segment : 464 time for calcul the mask position with numpy : 0.004830837249755859 nb_pixel_total : 57904 time to create 1 rle with old method : 0.0655977725982666 length of segment : 405 time for calcul the mask position with numpy : 0.001567840576171875 nb_pixel_total : 31595 time to create 1 rle with old method : 0.03781914710998535 length of segment : 259 time for calcul the mask position with numpy : 0.000522613525390625 nb_pixel_total : 7464 time to create 1 rle with old method : 0.008704662322998047 length of segment : 112 time for calcul the mask position with numpy : 0.0010819435119628906 nb_pixel_total : 19490 time to create 1 rle with old method : 0.0227663516998291 length of segment : 155 time for calcul the mask position with numpy : 0.0049860477447509766 nb_pixel_total : 28523 time to create 1 rle with old method : 0.032509803771972656 length of segment : 291 time for calcul the mask position with numpy : 0.00046634674072265625 nb_pixel_total : 6766 time to create 1 rle with old method : 0.007970333099365234 length of segment : 79 time for calcul the mask position with numpy : 0.0008194446563720703 nb_pixel_total : 11070 time to create 1 rle with old method : 0.012885093688964844 length of segment : 120 time for calcul the mask position with numpy : 0.001554727554321289 nb_pixel_total : 23159 time to create 1 rle with old method : 0.0266573429107666 length of segment : 122 time for calcul the mask position with numpy : 0.000598907470703125 nb_pixel_total : 8835 time to create 1 rle with old method : 0.01046299934387207 length of segment : 112 time for calcul the mask position with numpy : 0.0009427070617675781 nb_pixel_total : 11888 time to create 1 rle with old method : 0.013854026794433594 length of segment : 155 time for calcul the mask position with numpy : 0.0035429000854492188 nb_pixel_total : 34279 time to create 1 rle with old method : 0.039290666580200195 length of segment : 325 time for calcul the mask position with numpy : 0.00176239013671875 nb_pixel_total : 21983 time to create 1 rle with old method : 0.02546215057373047 length of segment : 206 time for calcul the mask position with numpy : 0.0037527084350585938 nb_pixel_total : 37166 time to create 1 rle with old method : 0.04075455665588379 length of segment : 281 time for calcul the mask position with numpy : 0.0006279945373535156 nb_pixel_total : 12901 time to create 1 rle with old method : 0.014818191528320312 length of segment : 116 time for calcul the mask position with numpy : 0.0015232563018798828 nb_pixel_total : 20680 time to create 1 rle with old method : 0.022808551788330078 length of segment : 147 time for calcul the mask position with numpy : 0.0020139217376708984 nb_pixel_total : 30329 time to create 1 rle with old method : 0.03391838073730469 length of segment : 334 time for calcul the mask position with numpy : 0.0016744136810302734 nb_pixel_total : 21858 time to create 1 rle with old method : 0.024161577224731445 length of segment : 207 time for calcul the mask position with numpy : 0.005628108978271484 nb_pixel_total : 70514 time to create 1 rle with old method : 0.0843665599822998 length of segment : 393 time for calcul the mask position with numpy : 0.001413583755493164 nb_pixel_total : 22121 time to create 1 rle with old method : 0.025434017181396484 length of segment : 139 time for calcul the mask position with numpy : 0.004079103469848633 nb_pixel_total : 51420 time to create 1 rle with old method : 0.0578768253326416 length of segment : 375 time for calcul the mask position with numpy : 0.0007262229919433594 nb_pixel_total : 10339 time to create 1 rle with old method : 0.011946916580200195 length of segment : 111 time for calcul the mask position with numpy : 0.008606195449829102 nb_pixel_total : 69686 time to create 1 rle with old method : 0.08069491386413574 length of segment : 392 time for calcul the mask position with numpy : 0.0012664794921875 nb_pixel_total : 16386 time to create 1 rle with old method : 0.01919078826904297 length of segment : 141 time for calcul the mask position with numpy : 0.010566234588623047 nb_pixel_total : 97942 time to create 1 rle with old method : 0.11092543601989746 length of segment : 502 time for calcul the mask position with numpy : 0.009842872619628906 nb_pixel_total : 131590 time to create 1 rle with old method : 0.1476597785949707 length of segment : 555 time for calcul the mask position with numpy : 0.0017855167388916016 nb_pixel_total : 14727 time to create 1 rle with old method : 0.017091751098632812 length of segment : 189 time for calcul the mask position with numpy : 0.003584623336791992 nb_pixel_total : 38870 time to create 1 rle with old method : 0.044088125228881836 length of segment : 296 time for calcul the mask position with numpy : 0.0002856254577636719 nb_pixel_total : 5724 time to create 1 rle with old method : 0.007665872573852539 length of segment : 95 time for calcul the mask position with numpy : 0.0017466545104980469 nb_pixel_total : 33466 time to create 1 rle with old method : 0.038099050521850586 length of segment : 305 time for calcul the mask position with numpy : 0.0013740062713623047 nb_pixel_total : 17157 time to create 1 rle with old method : 0.019843578338623047 length of segment : 172 time for calcul the mask position with numpy : 0.0007219314575195312 nb_pixel_total : 9011 time to create 1 rle with old method : 0.010602951049804688 length of segment : 114 time for calcul the mask position with numpy : 0.004045009613037109 nb_pixel_total : 51849 time to create 1 rle with old method : 0.05884194374084473 length of segment : 241 time for calcul the mask position with numpy : 0.0014345645904541016 nb_pixel_total : 20860 time to create 1 rle with old method : 0.024115800857543945 length of segment : 214 time for calcul the mask position with numpy : 0.0010540485382080078 nb_pixel_total : 34985 time to create 1 rle with old method : 0.041014909744262695 length of segment : 146 time for calcul the mask position with numpy : 0.002401113510131836 nb_pixel_total : 40143 time to create 1 rle with old method : 0.05042576789855957 length of segment : 457 time for calcul the mask position with numpy : 0.006880760192871094 nb_pixel_total : 80677 time to create 1 rle with old method : 0.09293365478515625 length of segment : 339 time for calcul the mask position with numpy : 0.0006511211395263672 nb_pixel_total : 16606 time to create 1 rle with old method : 0.019348621368408203 length of segment : 238 time for calcul the mask position with numpy : 0.0007789134979248047 nb_pixel_total : 7783 time to create 1 rle with old method : 0.009086370468139648 length of segment : 103 time for calcul the mask position with numpy : 0.0006811618804931641 nb_pixel_total : 12512 time to create 1 rle with old method : 0.014499187469482422 length of segment : 186 time for calcul the mask position with numpy : 0.001346588134765625 nb_pixel_total : 29171 time to create 1 rle with old method : 0.033614158630371094 length of segment : 238 time for calcul the mask position with numpy : 0.0009403228759765625 nb_pixel_total : 14057 time to create 1 rle with old method : 0.01652073860168457 length of segment : 135 time for calcul the mask position with numpy : 0.001068115234375 nb_pixel_total : 15503 time to create 1 rle with old method : 0.01786327362060547 length of segment : 203 time for calcul the mask position with numpy : 0.0009746551513671875 nb_pixel_total : 8650 time to create 1 rle with old method : 0.010206937789916992 length of segment : 132 time for calcul the mask position with numpy : 0.0014290809631347656 nb_pixel_total : 10645 time to create 1 rle with old method : 0.012306451797485352 length of segment : 166 time for calcul the mask position with numpy : 0.0008862018585205078 nb_pixel_total : 9190 time to create 1 rle with old method : 0.010751485824584961 length of segment : 141 time for calcul the mask position with numpy : 0.0012285709381103516 nb_pixel_total : 11849 time to create 1 rle with old method : 0.013952493667602539 length of segment : 159 time for calcul the mask position with numpy : 0.0002827644348144531 nb_pixel_total : 9012 time to create 1 rle with old method : 0.010739564895629883 length of segment : 114 time for calcul the mask position with numpy : 0.0004177093505859375 nb_pixel_total : 4325 time to create 1 rle with old method : 0.005183219909667969 length of segment : 72 time for calcul the mask position with numpy : 0.004491567611694336 nb_pixel_total : 55056 time to create 1 rle with old method : 0.06247353553771973 length of segment : 292 time for calcul the mask position with numpy : 0.0011265277862548828 nb_pixel_total : 9548 time to create 1 rle with old method : 0.011349916458129883 length of segment : 126 time for calcul the mask position with numpy : 0.0004532337188720703 nb_pixel_total : 4962 time to create 1 rle with old method : 0.005734920501708984 length of segment : 71 time for calcul the mask position with numpy : 0.0043447017669677734 nb_pixel_total : 42688 time to create 1 rle with old method : 0.05062127113342285 length of segment : 494 time for calcul the mask position with numpy : 0.0013110637664794922 nb_pixel_total : 14160 time to create 1 rle with old method : 0.01591968536376953 length of segment : 341 time for calcul the mask position with numpy : 0.002481222152709961 nb_pixel_total : 45869 time to create 1 rle with old method : 0.05161643028259277 length of segment : 249 time for calcul the mask position with numpy : 0.0014815330505371094 nb_pixel_total : 19643 time to create 1 rle with old method : 0.025046825408935547 length of segment : 185 time for calcul the mask position with numpy : 0.0027573108673095703 nb_pixel_total : 34326 time to create 1 rle with old method : 0.04280853271484375 length of segment : 205 time for calcul the mask position with numpy : 0.004799365997314453 nb_pixel_total : 79731 time to create 1 rle with old method : 0.09702754020690918 length of segment : 431 time for calcul the mask position with numpy : 0.0010135173797607422 nb_pixel_total : 11600 time to create 1 rle with old method : 0.014198780059814453 length of segment : 130 time for calcul the mask position with numpy : 0.0029668807983398438 nb_pixel_total : 21111 time to create 1 rle with old method : 0.025198936462402344 length of segment : 331 time for calcul the mask position with numpy : 0.0020232200622558594 nb_pixel_total : 33477 time to create 1 rle with old method : 0.053914785385131836 length of segment : 312 time for calcul the mask position with numpy : 0.0007507801055908203 nb_pixel_total : 11318 time to create 1 rle with old method : 0.013065099716186523 length of segment : 119 time for calcul the mask position with numpy : 0.011792421340942383 nb_pixel_total : 147787 time to create 1 rle with old method : 0.16606903076171875 length of segment : 448 time for calcul the mask position with numpy : 0.00026154518127441406 nb_pixel_total : 10881 time to create 1 rle with old method : 0.01277780532836914 length of segment : 112 time for calcul the mask position with numpy : 0.0007069110870361328 nb_pixel_total : 6806 time to create 1 rle with old method : 0.008128643035888672 length of segment : 128 time for calcul the mask position with numpy : 0.0006868839263916016 nb_pixel_total : 12332 time to create 1 rle with old method : 0.014307498931884766 length of segment : 154 time for calcul the mask position with numpy : 0.004060029983520508 nb_pixel_total : 67504 time to create 1 rle with old method : 0.07483696937561035 length of segment : 374 time for calcul the mask position with numpy : 0.003282785415649414 nb_pixel_total : 32500 time to create 1 rle with old method : 0.03632926940917969 length of segment : 404 time for calcul the mask position with numpy : 0.004434108734130859 nb_pixel_total : 77357 time to create 1 rle with old method : 0.0848078727722168 length of segment : 666 time for calcul the mask position with numpy : 0.0028562545776367188 nb_pixel_total : 37368 time to create 1 rle with old method : 0.04017066955566406 length of segment : 226 time for calcul the mask position with numpy : 0.0011136531829833984 nb_pixel_total : 20526 time to create 1 rle with old method : 0.02343893051147461 length of segment : 124 time for calcul the mask position with numpy : 0.001226186752319336 nb_pixel_total : 30879 time to create 1 rle with old method : 0.03439068794250488 length of segment : 253 time for calcul the mask position with numpy : 0.003524303436279297 nb_pixel_total : 51972 time to create 1 rle with old method : 0.05629563331604004 length of segment : 520 time for calcul the mask position with numpy : 0.0007925033569335938 nb_pixel_total : 9235 time to create 1 rle with old method : 0.010412454605102539 length of segment : 126 time for calcul the mask position with numpy : 0.0019834041595458984 nb_pixel_total : 34958 time to create 1 rle with old method : 0.04611802101135254 length of segment : 168 time for calcul the mask position with numpy : 0.0005269050598144531 nb_pixel_total : 5413 time to create 1 rle with old method : 0.006503105163574219 length of segment : 96 time for calcul the mask position with numpy : 0.0019276142120361328 nb_pixel_total : 38022 time to create 1 rle with old method : 0.04409980773925781 length of segment : 191 time for calcul the mask position with numpy : 0.0015938282012939453 nb_pixel_total : 24353 time to create 1 rle with old method : 0.028664588928222656 length of segment : 181 time for calcul the mask position with numpy : 0.00018477439880371094 nb_pixel_total : 7094 time to create 1 rle with old method : 0.008492469787597656 length of segment : 117 time for calcul the mask position with numpy : 0.002981424331665039 nb_pixel_total : 35749 time to create 1 rle with old method : 0.04348301887512207 length of segment : 226 time for calcul the mask position with numpy : 0.0006232261657714844 nb_pixel_total : 8319 time to create 1 rle with old method : 0.010899543762207031 length of segment : 85 time for calcul the mask position with numpy : 0.002324342727661133 nb_pixel_total : 26579 time to create 1 rle with old method : 0.03341484069824219 length of segment : 300 time for calcul the mask position with numpy : 0.012912273406982422 nb_pixel_total : 153110 time to create 1 rle with new method : 0.01415252685546875 length of segment : 706 time for calcul the mask position with numpy : 0.004804372787475586 nb_pixel_total : 59580 time to create 1 rle with old method : 0.06720972061157227 length of segment : 612 time for calcul the mask position with numpy : 0.0022830963134765625 nb_pixel_total : 17796 time to create 1 rle with old method : 0.020817995071411133 length of segment : 275 time for calcul the mask position with numpy : 0.0008025169372558594 nb_pixel_total : 11896 time to create 1 rle with old method : 0.019024372100830078 length of segment : 122 time for calcul the mask position with numpy : 0.0028765201568603516 nb_pixel_total : 35796 time to create 1 rle with old method : 0.04352903366088867 length of segment : 245 time for calcul the mask position with numpy : 0.00420689582824707 nb_pixel_total : 50721 time to create 1 rle with old method : 0.05688810348510742 length of segment : 274 time for calcul the mask position with numpy : 0.001188516616821289 nb_pixel_total : 10437 time to create 1 rle with old method : 0.013083219528198242 length of segment : 217 time for calcul the mask position with numpy : 0.0013382434844970703 nb_pixel_total : 21465 time to create 1 rle with old method : 0.026282310485839844 length of segment : 131 time for calcul the mask position with numpy : 0.005572080612182617 nb_pixel_total : 58202 time to create 1 rle with old method : 0.06786823272705078 length of segment : 331 time for calcul the mask position with numpy : 0.0025408267974853516 nb_pixel_total : 34512 time to create 1 rle with old method : 0.04003190994262695 length of segment : 262 time for calcul the mask position with numpy : 0.0016236305236816406 nb_pixel_total : 19569 time to create 1 rle with old method : 0.022390127182006836 length of segment : 189 time for calcul the mask position with numpy : 0.0014464855194091797 nb_pixel_total : 22629 time to create 1 rle with old method : 0.025773286819458008 length of segment : 210 time for calcul the mask position with numpy : 0.001199960708618164 nb_pixel_total : 17921 time to create 1 rle with old method : 0.02064990997314453 length of segment : 158 time for calcul the mask position with numpy : 0.0027322769165039062 nb_pixel_total : 39579 time to create 1 rle with old method : 0.04479861259460449 length of segment : 358 time for calcul the mask position with numpy : 0.0020079612731933594 nb_pixel_total : 37630 time to create 1 rle with old method : 0.04208111763000488 length of segment : 216 time for calcul the mask position with numpy : 0.0013146400451660156 nb_pixel_total : 13085 time to create 1 rle with old method : 0.01538538932800293 length of segment : 173 time for calcul the mask position with numpy : 0.003133058547973633 nb_pixel_total : 39227 time to create 1 rle with old method : 0.044431447982788086 length of segment : 315 time for calcul the mask position with numpy : 0.0008294582366943359 nb_pixel_total : 9075 time to create 1 rle with old method : 0.010413646697998047 length of segment : 168 time for calcul the mask position with numpy : 0.0012972354888916016 nb_pixel_total : 13756 time to create 1 rle with old method : 0.016373872756958008 length of segment : 172 time for calcul the mask position with numpy : 0.0011126995086669922 nb_pixel_total : 19288 time to create 1 rle with old method : 0.02207779884338379 length of segment : 282 time for calcul the mask position with numpy : 0.0038034915924072266 nb_pixel_total : 63375 time to create 1 rle with old method : 0.07206535339355469 length of segment : 181 time for calcul the mask position with numpy : 0.0005900859832763672 nb_pixel_total : 6642 time to create 1 rle with old method : 0.007950544357299805 length of segment : 130 time for calcul the mask position with numpy : 0.0011615753173828125 nb_pixel_total : 12226 time to create 1 rle with old method : 0.014185905456542969 length of segment : 155 time for calcul the mask position with numpy : 0.0007607936859130859 nb_pixel_total : 9405 time to create 1 rle with old method : 0.011142492294311523 length of segment : 93 time for calcul the mask position with numpy : 0.0035440921783447266 nb_pixel_total : 24419 time to create 1 rle with old method : 0.031423091888427734 length of segment : 481 time for calcul the mask position with numpy : 0.0025429725646972656 nb_pixel_total : 46566 time to create 1 rle with old method : 0.0540928840637207 length of segment : 255 time for calcul the mask position with numpy : 0.002397775650024414 nb_pixel_total : 32159 time to create 1 rle with old method : 0.036159515380859375 length of segment : 245 time for calcul the mask position with numpy : 0.001585245132446289 nb_pixel_total : 14368 time to create 1 rle with old method : 0.024021387100219727 length of segment : 199 time for calcul the mask position with numpy : 0.001789093017578125 nb_pixel_total : 21109 time to create 1 rle with old method : 0.03255772590637207 length of segment : 179 time for calcul the mask position with numpy : 0.0014200210571289062 nb_pixel_total : 20441 time to create 1 rle with old method : 0.023145198822021484 length of segment : 173 time for calcul the mask position with numpy : 0.010007143020629883 nb_pixel_total : 150082 time to create 1 rle with new method : 0.011367082595825195 length of segment : 414 time for calcul the mask position with numpy : 0.0016813278198242188 nb_pixel_total : 23481 time to create 1 rle with old method : 0.0265958309173584 length of segment : 251 time for calcul the mask position with numpy : 0.0006051063537597656 nb_pixel_total : 10721 time to create 1 rle with old method : 0.012729167938232422 length of segment : 143 time for calcul the mask position with numpy : 0.009116649627685547 nb_pixel_total : 98833 time to create 1 rle with old method : 0.12291502952575684 length of segment : 398 time for calcul the mask position with numpy : 0.00258636474609375 nb_pixel_total : 51470 time to create 1 rle with old method : 0.058356285095214844 length of segment : 232 time for calcul the mask position with numpy : 0.0007340908050537109 nb_pixel_total : 9621 time to create 1 rle with old method : 0.011016368865966797 length of segment : 139 time for calcul the mask position with numpy : 0.0016744136810302734 nb_pixel_total : 16557 time to create 1 rle with old method : 0.01915264129638672 length of segment : 151 time for calcul the mask position with numpy : 0.0008330345153808594 nb_pixel_total : 14364 time to create 1 rle with old method : 0.017174482345581055 length of segment : 114 time for calcul the mask position with numpy : 0.000762939453125 nb_pixel_total : 7952 time to create 1 rle with old method : 0.009382009506225586 length of segment : 110 time for calcul the mask position with numpy : 0.00041937828063964844 nb_pixel_total : 10630 time to create 1 rle with old method : 0.012241601943969727 length of segment : 121 time for calcul the mask position with numpy : 0.002482175827026367 nb_pixel_total : 49348 time to create 1 rle with old method : 0.06505393981933594 length of segment : 254 time for calcul the mask position with numpy : 0.006537914276123047 nb_pixel_total : 97974 time to create 1 rle with old method : 0.12343978881835938 length of segment : 347 time for calcul the mask position with numpy : 0.007941961288452148 nb_pixel_total : 109536 time to create 1 rle with old method : 0.12978601455688477 length of segment : 486 time for calcul the mask position with numpy : 0.001569986343383789 nb_pixel_total : 22627 time to create 1 rle with old method : 0.028404712677001953 length of segment : 132 time for calcul the mask position with numpy : 0.002496004104614258 nb_pixel_total : 40335 time to create 1 rle with old method : 0.04562664031982422 length of segment : 375 time for calcul the mask position with numpy : 0.00045871734619140625 nb_pixel_total : 4911 time to create 1 rle with old method : 0.005906105041503906 length of segment : 74 time for calcul the mask position with numpy : 0.0007212162017822266 nb_pixel_total : 11535 time to create 1 rle with old method : 0.013537406921386719 length of segment : 106 time for calcul the mask position with numpy : 0.0018680095672607422 nb_pixel_total : 21543 time to create 1 rle with old method : 0.027618408203125 length of segment : 135 time for calcul the mask position with numpy : 0.001157522201538086 nb_pixel_total : 14110 time to create 1 rle with old method : 0.016397476196289062 length of segment : 168 time for calcul the mask position with numpy : 0.002386808395385742 nb_pixel_total : 26073 time to create 1 rle with old method : 0.030239343643188477 length of segment : 252 time for calcul the mask position with numpy : 0.0002624988555908203 nb_pixel_total : 4198 time to create 1 rle with old method : 0.0050432682037353516 length of segment : 105 time for calcul the mask position with numpy : 0.002089977264404297 nb_pixel_total : 25282 time to create 1 rle with old method : 0.03203535079956055 length of segment : 278 time for calcul the mask position with numpy : 0.004396200180053711 nb_pixel_total : 36940 time to create 1 rle with old method : 0.04308509826660156 length of segment : 210 time for calcul the mask position with numpy : 0.005104541778564453 nb_pixel_total : 44841 time to create 1 rle with old method : 0.05510711669921875 length of segment : 436 time for calcul the mask position with numpy : 0.0007472038269042969 nb_pixel_total : 17471 time to create 1 rle with old method : 0.02425670623779297 length of segment : 189 time for calcul the mask position with numpy : 0.002328634262084961 nb_pixel_total : 29033 time to create 1 rle with old method : 0.058347463607788086 length of segment : 180 time for calcul the mask position with numpy : 0.0006473064422607422 nb_pixel_total : 8342 time to create 1 rle with old method : 0.010104656219482422 length of segment : 85 time for calcul the mask position with numpy : 0.00042057037353515625 nb_pixel_total : 6435 time to create 1 rle with old method : 0.009072542190551758 length of segment : 100 time for calcul the mask position with numpy : 0.006027698516845703 nb_pixel_total : 16664 time to create 1 rle with old method : 0.035834312438964844 length of segment : 116 time for calcul the mask position with numpy : 0.0022323131561279297 nb_pixel_total : 23923 time to create 1 rle with old method : 0.032872676849365234 length of segment : 194 time for calcul the mask position with numpy : 0.004131317138671875 nb_pixel_total : 33706 time to create 1 rle with old method : 0.04337739944458008 length of segment : 515 time for calcul the mask position with numpy : 0.0016322135925292969 nb_pixel_total : 46518 time to create 1 rle with old method : 0.060410261154174805 length of segment : 225 time for calcul the mask position with numpy : 0.0006458759307861328 nb_pixel_total : 8866 time to create 1 rle with old method : 0.01019906997680664 length of segment : 170 time for calcul the mask position with numpy : 0.0010023117065429688 nb_pixel_total : 11329 time to create 1 rle with old method : 0.013447761535644531 length of segment : 134 time for calcul the mask position with numpy : 0.0016107559204101562 nb_pixel_total : 18247 time to create 1 rle with old method : 0.02290940284729004 length of segment : 201 time for calcul the mask position with numpy : 0.0016977787017822266 nb_pixel_total : 10460 time to create 1 rle with old method : 0.014760017395019531 length of segment : 182 time for calcul the mask position with numpy : 0.0032711029052734375 nb_pixel_total : 39959 time to create 1 rle with old method : 0.04631376266479492 length of segment : 324 time for calcul the mask position with numpy : 0.0004799365997314453 nb_pixel_total : 5700 time to create 1 rle with old method : 0.007018327713012695 length of segment : 72 time for calcul the mask position with numpy : 0.0021827220916748047 nb_pixel_total : 29321 time to create 1 rle with old method : 0.03431081771850586 length of segment : 149 time for calcul the mask position with numpy : 0.0008959770202636719 nb_pixel_total : 10421 time to create 1 rle with old method : 0.012375831604003906 length of segment : 112 time for calcul the mask position with numpy : 0.0003457069396972656 nb_pixel_total : 4323 time to create 1 rle with old method : 0.0059967041015625 length of segment : 83 time for calcul the mask position with numpy : 0.0005919933319091797 nb_pixel_total : 7889 time to create 1 rle with old method : 0.009402036666870117 length of segment : 119 time for calcul the mask position with numpy : 0.0044252872467041016 nb_pixel_total : 34063 time to create 1 rle with old method : 0.04116058349609375 length of segment : 313 time for calcul the mask position with numpy : 0.0016283988952636719 nb_pixel_total : 21460 time to create 1 rle with old method : 0.024919986724853516 length of segment : 215 time for calcul the mask position with numpy : 0.0021533966064453125 nb_pixel_total : 33165 time to create 1 rle with old method : 0.03818774223327637 length of segment : 257 time for calcul the mask position with numpy : 0.002198457717895508 nb_pixel_total : 20274 time to create 1 rle with old method : 0.023798227310180664 length of segment : 206 time for calcul the mask position with numpy : 0.0012288093566894531 nb_pixel_total : 15014 time to create 1 rle with old method : 0.017442941665649414 length of segment : 139 time for calcul the mask position with numpy : 0.0007257461547851562 nb_pixel_total : 21705 time to create 1 rle with old method : 0.025066614151000977 length of segment : 201 time for calcul the mask position with numpy : 0.0009853839874267578 nb_pixel_total : 16555 time to create 1 rle with old method : 0.022736787796020508 length of segment : 153 time for calcul the mask position with numpy : 0.004141330718994141 nb_pixel_total : 59732 time to create 1 rle with old method : 0.06836247444152832 length of segment : 237 time for calcul the mask position with numpy : 0.0021932125091552734 nb_pixel_total : 33188 time to create 1 rle with old method : 0.038825035095214844 length of segment : 219 time for calcul the mask position with numpy : 0.0020585060119628906 nb_pixel_total : 21474 time to create 1 rle with old method : 0.025068283081054688 length of segment : 163 time for calcul the mask position with numpy : 0.00030803680419921875 nb_pixel_total : 5119 time to create 1 rle with old method : 0.006097555160522461 length of segment : 293 time for calcul the mask position with numpy : 0.0029630661010742188 nb_pixel_total : 30706 time to create 1 rle with old method : 0.03501701354980469 length of segment : 302 time for calcul the mask position with numpy : 0.0007076263427734375 nb_pixel_total : 6119 time to create 1 rle with old method : 0.007185459136962891 length of segment : 97 time for calcul the mask position with numpy : 0.0009844303131103516 nb_pixel_total : 11800 time to create 1 rle with old method : 0.013795614242553711 length of segment : 118 time for calcul the mask position with numpy : 0.00671076774597168 nb_pixel_total : 46795 time to create 1 rle with old method : 0.052860260009765625 length of segment : 230 time for calcul the mask position with numpy : 0.0019359588623046875 nb_pixel_total : 20775 time to create 1 rle with old method : 0.024026870727539062 length of segment : 164 time for calcul the mask position with numpy : 0.0021102428436279297 nb_pixel_total : 20538 time to create 1 rle with old method : 0.0239565372467041 length of segment : 165 time for calcul the mask position with numpy : 0.0017685890197753906 nb_pixel_total : 22387 time to create 1 rle with old method : 0.025534629821777344 length of segment : 274 time for calcul the mask position with numpy : 0.0002675056457519531 nb_pixel_total : 3027 time to create 1 rle with old method : 0.003692626953125 length of segment : 50 time for calcul the mask position with numpy : 0.0014138221740722656 nb_pixel_total : 13024 time to create 1 rle with old method : 0.016532421112060547 length of segment : 87 time for calcul the mask position with numpy : 0.0005362033843994141 nb_pixel_total : 15227 time to create 1 rle with old method : 0.017870187759399414 length of segment : 139 time for calcul the mask position with numpy : 0.0021393299102783203 nb_pixel_total : 37594 time to create 1 rle with old method : 0.04360485076904297 length of segment : 194 time for calcul the mask position with numpy : 0.00417637825012207 nb_pixel_total : 39945 time to create 1 rle with old method : 0.04625844955444336 length of segment : 446 time for calcul the mask position with numpy : 0.0007531642913818359 nb_pixel_total : 6388 time to create 1 rle with old method : 0.007616996765136719 length of segment : 113 time for calcul the mask position with numpy : 0.0022187232971191406 nb_pixel_total : 29019 time to create 1 rle with old method : 0.03388857841491699 length of segment : 208 time for calcul the mask position with numpy : 0.0018887519836425781 nb_pixel_total : 26751 time to create 1 rle with old method : 0.031322479248046875 length of segment : 191 time for calcul the mask position with numpy : 0.0010933876037597656 nb_pixel_total : 31182 time to create 1 rle with old method : 0.036124467849731445 length of segment : 147 time for calcul the mask position with numpy : 0.0019135475158691406 nb_pixel_total : 25327 time to create 1 rle with old method : 0.029205799102783203 length of segment : 204 time for calcul the mask position with numpy : 0.0005733966827392578 nb_pixel_total : 5334 time to create 1 rle with old method : 0.008936643600463867 length of segment : 72 time for calcul the mask position with numpy : 0.0010426044464111328 nb_pixel_total : 10944 time to create 1 rle with old method : 0.017888307571411133 length of segment : 156 time for calcul the mask position with numpy : 0.0034685134887695312 nb_pixel_total : 47248 time to create 1 rle with old method : 0.053668975830078125 length of segment : 282 time for calcul the mask position with numpy : 0.0014438629150390625 nb_pixel_total : 17779 time to create 1 rle with old method : 0.02057504653930664 length of segment : 230 time for calcul the mask position with numpy : 0.0037817955017089844 nb_pixel_total : 34784 time to create 1 rle with old method : 0.04059648513793945 length of segment : 181 time for calcul the mask position with numpy : 0.004475116729736328 nb_pixel_total : 49398 time to create 1 rle with old method : 0.05667734146118164 length of segment : 239 time for calcul the mask position with numpy : 0.0008225440979003906 nb_pixel_total : 5577 time to create 1 rle with old method : 0.006642818450927734 length of segment : 98 time for calcul the mask position with numpy : 0.0022897720336914062 nb_pixel_total : 32605 time to create 1 rle with old method : 0.03751969337463379 length of segment : 167 time for calcul the mask position with numpy : 0.00272369384765625 nb_pixel_total : 16084 time to create 1 rle with old method : 0.018555402755737305 length of segment : 177 time for calcul the mask position with numpy : 0.005074024200439453 nb_pixel_total : 30065 time to create 1 rle with old method : 0.03412771224975586 length of segment : 283 time for calcul the mask position with numpy : 0.0037403106689453125 nb_pixel_total : 12694 time to create 1 rle with old method : 0.015046834945678711 length of segment : 216 time for calcul the mask position with numpy : 0.0035185813903808594 nb_pixel_total : 16815 time to create 1 rle with old method : 0.02178049087524414 length of segment : 168 time for calcul the mask position with numpy : 0.028148651123046875 nb_pixel_total : 115227 time to create 1 rle with old method : 0.1323082447052002 length of segment : 506 time for calcul the mask position with numpy : 0.0025954246520996094 nb_pixel_total : 21380 time to create 1 rle with old method : 0.024672985076904297 length of segment : 351 time for calcul the mask position with numpy : 0.0035266876220703125 nb_pixel_total : 13686 time to create 1 rle with old method : 0.0162198543548584 length of segment : 128 time for calcul the mask position with numpy : 0.008796215057373047 nb_pixel_total : 8941 time to create 1 rle with old method : 0.012228727340698242 length of segment : 173 time for calcul the mask position with numpy : 0.004370212554931641 nb_pixel_total : 8837 time to create 1 rle with old method : 0.010366678237915039 length of segment : 178 time for calcul the mask position with numpy : 0.0228731632232666 nb_pixel_total : 33075 time to create 1 rle with old method : 0.06078338623046875 length of segment : 328 time for calcul the mask position with numpy : 0.00735020637512207 nb_pixel_total : 36948 time to create 1 rle with old method : 0.04198288917541504 length of segment : 368 time for calcul the mask position with numpy : 0.007376670837402344 nb_pixel_total : 24890 time to create 1 rle with old method : 0.028285980224609375 length of segment : 224 time for calcul the mask position with numpy : 0.005906581878662109 nb_pixel_total : 30051 time to create 1 rle with old method : 0.036510467529296875 length of segment : 359 time for calcul the mask position with numpy : 0.0011906623840332031 nb_pixel_total : 6691 time to create 1 rle with old method : 0.007726430892944336 length of segment : 122 time for calcul the mask position with numpy : 0.0003631114959716797 nb_pixel_total : 8541 time to create 1 rle with old method : 0.010309457778930664 length of segment : 188 time for calcul the mask position with numpy : 0.0032205581665039062 nb_pixel_total : 15602 time to create 1 rle with old method : 0.02028203010559082 length of segment : 138 time for calcul the mask position with numpy : 0.061430931091308594 nb_pixel_total : 51664 time to create 1 rle with old method : 0.061625003814697266 length of segment : 461 time for calcul the mask position with numpy : 0.0020143985748291016 nb_pixel_total : 4490 time to create 1 rle with old method : 0.009154319763183594 length of segment : 138 time for calcul the mask position with numpy : 0.0012636184692382812 nb_pixel_total : 7121 time to create 1 rle with old method : 0.008484601974487305 length of segment : 163 time for calcul the mask position with numpy : 0.005865812301635742 nb_pixel_total : 20183 time to create 1 rle with old method : 0.025687694549560547 length of segment : 196 time for calcul the mask position with numpy : 0.04990983009338379 nb_pixel_total : 52748 time to create 1 rle with old method : 0.07109737396240234 length of segment : 392 time for calcul the mask position with numpy : 0.00022172927856445312 nb_pixel_total : 1489 time to create 1 rle with old method : 0.002079010009765625 length of segment : 44 time for calcul the mask position with numpy : 0.025321006774902344 nb_pixel_total : 20778 time to create 1 rle with old method : 0.029750347137451172 length of segment : 184 time spent for convertir_results : 123.22792029380798 Inside saveOutput : final : False verbose : 0 eke 12-6-18 : saveMask need to be cleaned for new output ! Number saved : None batch 1 Loaded 1738 chid ids of type : 3594 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 256448 save missing photos in datou_result : time spend for datou_step_exec : 619.0472671985626 time spend to save output : 22.583214282989502 total time spend for step 1 : 641.6304814815521 step2:crop_condition Tue Apr 1 22:41:13 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! 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 : 21 ! batch 1 Loaded 1738 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 ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! 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 : 1386 About to insert : list_path_to_insert length 1386 new photo from crops ! About to upload 1386 photos upload in portfolio : 3736932 init cache_photo without model_param we have 1386 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1743540212_2986256 we have uploaded 1386 photos in the portfolio 3736932 time of upload the photos Elapsed time : 479.6238832473755 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 ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! 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 : 194 About to insert : list_path_to_insert length 194 new photo from crops ! About to upload 194 photos upload in portfolio : 3736932 init cache_photo without model_param we have 194 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1743540717_2986256 we have uploaded 194 photos in the portfolio 3736932 time of upload the photos Elapsed time : 69.03853511810303 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 ! map_result returned by crop_photo_return_map_crop : length : 8 About to insert : list_path_to_insert length 8 new photo from crops ! About to upload 8 photos upload in portfolio : 3736932 init cache_photo without model_param we have 8 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1743540791_2986256 we have uploaded 8 photos in the portfolio 3736932 time of upload the photos Elapsed time : 3.201077461242676 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 ! map_result returned by crop_photo_return_map_crop : length : 79 About to insert : list_path_to_insert length 79 new photo from crops ! About to upload 79 photos upload in portfolio : 3736932 init cache_photo without model_param we have 79 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1743540811_2986256 we have uploaded 79 photos in the portfolio 3736932 time of upload the photos Elapsed time : 32.898435831069946 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 ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! 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 : 26 About to insert : list_path_to_insert length 26 new photo from crops ! About to upload 26 photos upload in portfolio : 3736932 init cache_photo without model_param we have 26 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1743540849_2986256 we have uploaded 26 photos in the portfolio 3736932 time of upload the photos Elapsed time : 7.977176666259766 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 ! map_result returned by crop_photo_return_map_crop : length : 2 About to insert : list_path_to_insert length 2 new photo from crops ! About to upload 2 photos upload in portfolio : 3736932 init cache_photo without model_param we have 2 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1743540861_2986256 we have uploaded 2 photos in the portfolio 3736932 time of upload the photos Elapsed time : 0.7414124011993408 we have finished the crop for the class : pehd begin to crop the class : pet_fonce param for this class : {'min_score': 0.7} filtre for class : pet_fonce hashtag_id of this class : 2107755900 we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! map_result returned by crop_photo_return_map_crop : length : 14 About to insert : list_path_to_insert length 14 new photo from crops ! About to upload 14 photos upload in portfolio : 3736932 init cache_photo without model_param we have 14 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1743540868_2986256 we have uploaded 14 photos in the portfolio 3736932 time of upload the photos Elapsed time : 3.987501859664917 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 Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : crop_condition we use saveGeneral [1349346061, 1349346025, 1349346023, 1349345767, 1349345764, 1349345708, 1349345704, 1349345700, 1349345661, 1349296605, 1349296574, 1349296398, 1349296394, 1349296389, 1349296385, 1349296212, 1349296210, 1349296206, 1349296201, 1349296194, 1349296189] Looping around the photos to save general results len do output : 1709 /1349378156Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378157Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378158Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378159Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378160Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378161Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378162Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378163Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378164Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378165Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378166Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378167Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378168Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378169Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378171Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378172Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378173Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378174Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378175Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378176Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378177Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378178Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378179Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378180Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378181Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378182Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378183Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378184Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378185Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378186Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378187Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378188Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378189Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378190Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378191Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378192Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378193Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378194Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378195Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378196Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378197Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378198Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378199Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378200Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378201Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378202Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378203Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378204Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378205Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378206Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378207Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378208Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378209Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378210Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378211Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378212Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378213Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378214Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378215Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378216Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378217Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378219Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378220Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378222Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378223Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378224Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378226Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378227Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378228Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378230Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378231Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378232Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378236Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378237Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378240Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378241Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378243Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378245Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378246Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378248Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378250Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378251Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378253Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378256Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378258Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378260Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378261Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378262Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378264Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378266Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378267Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378269Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378271Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378272Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378274Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378276Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378277Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378279Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378281Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378283Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378285Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378286Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378288Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378290Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378291Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378293Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378295Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378296Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378298Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378300Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378301Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378303Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378305Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378306Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378307Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378310Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378311Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378312Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378314Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378315Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378316Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378318Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378319Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378320Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378323Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378324Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378325Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378327Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378328Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378329Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378331Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378332Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378333Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378334Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378337Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378339Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378340Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378342Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378343Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378344Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378346Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378347Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378348Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378350Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378351Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378352Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378353Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378355Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378356Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378357Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378359Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378360Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378361Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378363Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378364Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378365Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378367Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378368Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378370Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378371Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378372Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378374Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378375Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378376Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378377Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378379Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378380Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378381Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378383Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378385Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378387Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378388Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378389Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378390Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378392Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378393Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378394Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378396Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378397Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378398Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378400Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378401Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378402Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378404Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378405Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378406Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378408Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378409Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378410Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378412Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378413Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378414Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378416Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378418Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378419Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378421Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378423Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378424Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378427Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378429Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378431Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378432Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378435Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378437Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378438Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378440Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378442Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378443Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378445Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378447Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378448Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378450Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378452Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378454Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378455Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378457Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378459Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378460Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378462Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378465Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378466Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378469Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378470Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378471Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378473Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378474Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378475Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378478Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378479Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378480Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378482Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378483Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378484Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378486Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378487Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378488Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378490Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378491Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378492Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378494Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378495Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378499Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378500Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378502Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378503Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378504Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378506Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378507Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378510Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378511Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378512Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378513Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378514Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378515Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378516Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378517Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378518Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378519Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378520Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378521Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378522Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378523Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378524Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378525Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378526Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378527Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378528Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378529Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378530Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378531Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378532Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378533Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378534Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378535Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378536Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378537Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378538Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378539Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378540Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378541Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378542Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378543Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378544Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378545Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378546Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378547Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378548Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378549Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378550Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378551Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378552Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378553Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378554Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378555Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378556Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378557Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378558Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378559Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378561Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378563Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378564Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378565Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378566Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378567Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378568Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378569Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378570Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378571Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378572Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378573Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378574Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349378575Didn't retrieve data 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retrieve data . /1349382560Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349382783Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349382784Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349382785Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349382787Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349382788Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349382789Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349382791Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349382792Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349382793Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349382795Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349382796Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349382797Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349382799Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1349382800Didn'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, '2714574') ('3318', '21958970', '1349346061', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349346025', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349346023', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349345767', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349345764', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349345708', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349345704', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349345700', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349345661', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296605', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296574', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296398', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296394', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296389', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296385', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296212', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296210', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296206', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296201', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296194', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296189', None, None, None, None, None, '2714574') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 5148 time used for this insertion : 0.2224593162536621 save_final save missing photos in datou_result : time spend for datou_step_exec : 799.7434039115906 time spend to save output : 0.2765347957611084 total time spend for step 2 : 800.0199387073517 step3:rle_unique_nms_with_priority Tue Apr 1 22:54:33 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array 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 1738 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++nb_obj : 54 nb_hashtags : 4 time to prepare the origin masks : 4.076628684997559 time for calcul the mask position with numpy : 0.6003119945526123 nb_pixel_total : 5591217 time to create 1 rle with new method : 0.6184923648834229 time for calcul the mask position with numpy : 0.028722047805786133 nb_pixel_total : 9318 time to create 1 rle with old method : 0.01095890998840332 time for calcul the mask position with numpy : 0.02835249900817871 nb_pixel_total : 9404 time to create 1 rle with old method : 0.010225296020507812 time for calcul the mask position with numpy : 0.028955459594726562 nb_pixel_total : 6281 time to create 1 rle with old method : 0.0068073272705078125 time for calcul the mask position with numpy : 0.02999091148376465 nb_pixel_total : 204651 time to create 1 rle with new method : 0.794797420501709 time for calcul the mask position with numpy : 0.028491735458374023 nb_pixel_total : 42863 time to create 1 rle with old method : 0.045883893966674805 time for calcul the mask position with numpy : 0.028492212295532227 nb_pixel_total : 6282 time to create 1 rle with old method : 0.00690913200378418 time for calcul the mask position with numpy : 0.029031753540039062 nb_pixel_total : 15413 time to create 1 rle with old method : 0.0172731876373291 time for calcul the mask position with numpy : 0.028985023498535156 nb_pixel_total : 19340 time to create 1 rle with old method : 0.02148127555847168 time for calcul the mask position with numpy : 0.028959989547729492 nb_pixel_total : 15464 time to create 1 rle with old method : 0.017441749572753906 time for calcul the mask position with numpy : 0.029159069061279297 nb_pixel_total : 8329 time to create 1 rle with old method : 0.010179519653320312 time for calcul the mask position with numpy : 0.030976057052612305 nb_pixel_total : 4714 time to create 1 rle with old method : 0.007454872131347656 time for calcul the mask position with numpy : 0.03155684471130371 nb_pixel_total : 41233 time to create 1 rle with old method : 0.05054807662963867 time for calcul the mask position with numpy : 0.032395124435424805 nb_pixel_total : 7971 time to create 1 rle with old method : 0.01308131217956543 time for calcul the mask position with numpy : 0.03302478790283203 nb_pixel_total : 17293 time to create 1 rle with old method : 0.02076268196105957 time for calcul the mask position with numpy : 0.028809785842895508 nb_pixel_total : 25280 time to create 1 rle with old method : 0.027659177780151367 time for calcul the mask position with numpy : 0.028896093368530273 nb_pixel_total : 65330 time to create 1 rle with old method : 0.07282233238220215 time for calcul the mask position with numpy : 0.028670787811279297 nb_pixel_total : 37224 time to create 1 rle with old method : 0.04451107978820801 time for calcul the mask position with numpy : 0.029387950897216797 nb_pixel_total : 8686 time to create 1 rle with old method : 0.009826898574829102 time for calcul the mask position with numpy : 0.029497146606445312 nb_pixel_total : 21836 time to create 1 rle with old method : 0.027999401092529297 time for calcul the mask position with numpy : 0.02983379364013672 nb_pixel_total : 14703 time to create 1 rle with old method : 0.024158000946044922 time for calcul the mask position with numpy : 0.04568314552307129 nb_pixel_total : 12846 time to create 1 rle with old method : 0.01780557632446289 time for calcul the mask position with numpy : 0.0310366153717041 nb_pixel_total : 5734 time to create 1 rle with old method : 0.011133432388305664 time for calcul the mask position with numpy : 0.033559560775756836 nb_pixel_total : 21057 time to create 1 rle with old method : 0.028999805450439453 time for calcul the mask position with numpy : 0.02974867820739746 nb_pixel_total : 31873 time to create 1 rle with old method : 0.035291433334350586 time for calcul the mask position with numpy : 0.029056310653686523 nb_pixel_total : 51114 time to create 1 rle with old method : 0.0571746826171875 time for calcul the mask position with numpy : 0.028207063674926758 nb_pixel_total : 14450 time to create 1 rle with old method : 0.01621699333190918 time for calcul the mask position with numpy : 0.02888965606689453 nb_pixel_total : 11048 time to create 1 rle with old method : 0.012396574020385742 time for calcul the mask position with numpy : 0.03010392189025879 nb_pixel_total : 18174 time to create 1 rle with old method : 0.021165847778320312 time for calcul the mask position with numpy : 0.030222177505493164 nb_pixel_total : 20596 time to create 1 rle with old method : 0.02399921417236328 time for calcul the mask position with numpy : 0.030288219451904297 nb_pixel_total : 35392 time to create 1 rle with old method : 0.03981614112854004 time for calcul the mask position with numpy : 0.02963423728942871 nb_pixel_total : 118315 time to create 1 rle with old method : 0.1348400115966797 time for calcul the mask position with numpy : 0.02986598014831543 nb_pixel_total : 25647 time to create 1 rle with old method : 0.0396876335144043 time for calcul the mask position with numpy : 0.035332679748535156 nb_pixel_total : 12383 time to create 1 rle with old method : 0.021188735961914062 time for calcul the mask position with numpy : 0.034689903259277344 nb_pixel_total : 45855 time to create 1 rle with old method : 0.07820296287536621 time for calcul the mask position with numpy : 0.033739328384399414 nb_pixel_total : 19981 time to create 1 rle with old method : 0.024545669555664062 time for calcul the mask position with numpy : 0.029072046279907227 nb_pixel_total : 31411 time to create 1 rle with old method : 0.03418421745300293 time for calcul the mask position with numpy : 0.028216838836669922 nb_pixel_total : 36498 time to create 1 rle with old method : 0.03981614112854004 time for calcul the mask position with numpy : 0.029380083084106445 nb_pixel_total : 26748 time to create 1 rle with old method : 0.02924323081970215 time for calcul the mask position with numpy : 0.029520273208618164 nb_pixel_total : 20985 time to create 1 rle with old method : 0.023078441619873047 time for calcul the mask position with numpy : 0.02875971794128418 nb_pixel_total : 9486 time to create 1 rle with old method : 0.010391473770141602 time for calcul the mask position with numpy : 0.02851557731628418 nb_pixel_total : 43478 time to create 1 rle with old method : 0.04831719398498535 time for calcul the mask position with numpy : 0.029275178909301758 nb_pixel_total : 25178 time to create 1 rle with old method : 0.02819371223449707 time for calcul the mask position with numpy : 0.029104948043823242 nb_pixel_total : 35022 time to create 1 rle with old method : 0.04372262954711914 time for calcul the mask position with numpy : 0.03138113021850586 nb_pixel_total : 49056 time to create 1 rle with old method : 0.057153940200805664 time for calcul the mask position with numpy : 0.029447555541992188 nb_pixel_total : 7195 time to create 1 rle with old method : 0.00787496566772461 time for calcul the mask position with numpy : 0.028064727783203125 nb_pixel_total : 6757 time to create 1 rle with old method : 0.008598566055297852 time for calcul the mask position with numpy : 0.028926372528076172 nb_pixel_total : 14180 time to create 1 rle with old method : 0.016330957412719727 time for calcul the mask position with numpy : 0.029676198959350586 nb_pixel_total : 14866 time to create 1 rle with old method : 0.016150712966918945 time for calcul the mask position with numpy : 0.029143810272216797 nb_pixel_total : 19553 time to create 1 rle with old method : 0.0237274169921875 time for calcul the mask position with numpy : 0.02973008155822754 nb_pixel_total : 18659 time to create 1 rle with old method : 0.020936965942382812 time for calcul the mask position with numpy : 0.02960824966430664 nb_pixel_total : 34770 time to create 1 rle with old method : 0.04127836227416992 time for calcul the mask position with numpy : 0.03040456771850586 nb_pixel_total : 10788 time to create 1 rle with old method : 0.013208627700805664 time for calcul the mask position with numpy : 0.029697418212890625 nb_pixel_total : 21196 time to create 1 rle with old method : 0.026053428649902344 time for calcul the mask position with numpy : 0.029078960418701172 nb_pixel_total : 7117 time to create 1 rle with old method : 0.008270978927612305 create new chi : 5.206183910369873 time to delete rle : 0.019337892532348633 batch 1 Loaded 110 chid ids of type : 3594 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 24312 TO DO : save crop sub photo not yet done ! save time : 1.4499545097351074 nb_obj : 44 nb_hashtags : 2 time to prepare the origin masks : 4.176091909408569 time for calcul the mask position with numpy : 0.5198426246643066 nb_pixel_total : 5837892 time to create 1 rle with new method : 0.8871805667877197 time for calcul the mask position with numpy : 0.02888202667236328 nb_pixel_total : 16592 time to create 1 rle with old method : 0.018794775009155273 time for calcul the mask position with numpy : 0.029129505157470703 nb_pixel_total : 13409 time to create 1 rle with old method : 0.015258073806762695 time for calcul the mask position with numpy : 0.029261350631713867 nb_pixel_total : 18136 time to create 1 rle with old method : 0.020600557327270508 time for calcul the mask position with numpy : 0.030295610427856445 nb_pixel_total : 43835 time to create 1 rle with old method : 0.049340009689331055 time for calcul the mask position with numpy : 0.027992725372314453 nb_pixel_total : 13178 time to create 1 rle with old method : 0.014491081237792969 time for calcul the mask position with numpy : 0.02860879898071289 nb_pixel_total : 74723 time to create 1 rle with old method : 0.08197140693664551 time for calcul the mask position with numpy : 0.029133319854736328 nb_pixel_total : 29246 time to create 1 rle with old method : 0.03228425979614258 time for calcul the mask position with numpy : 0.02769327163696289 nb_pixel_total : 3783 time to create 1 rle with old method : 0.004053592681884766 time for calcul the mask position with numpy : 0.027401208877563477 nb_pixel_total : 19194 time to create 1 rle with old method : 0.020370960235595703 time for calcul the mask position with numpy : 0.027744293212890625 nb_pixel_total : 57071 time to create 1 rle with old method : 0.06183314323425293 time for calcul the mask position with numpy : 0.02820730209350586 nb_pixel_total : 36375 time to create 1 rle with old method : 0.03968548774719238 time for calcul the mask position with numpy : 0.02657318115234375 nb_pixel_total : 13992 time to create 1 rle with old method : 0.014453887939453125 time for calcul the mask position with numpy : 0.026309490203857422 nb_pixel_total : 30192 time to create 1 rle with old method : 0.03207254409790039 time for calcul the mask position with numpy : 0.028245210647583008 nb_pixel_total : 16720 time to create 1 rle with old method : 0.01878190040588379 time for calcul the mask position with numpy : 0.027642250061035156 nb_pixel_total : 42168 time to create 1 rle with old method : 0.044031381607055664 time for calcul the mask position with numpy : 0.027451276779174805 nb_pixel_total : 32685 time to create 1 rle with old method : 0.03554987907409668 time for calcul the mask position with numpy : 0.028470277786254883 nb_pixel_total : 10457 time to create 1 rle with old method : 0.011160135269165039 time for calcul the mask position with numpy : 0.027985811233520508 nb_pixel_total : 59299 time to create 1 rle with old method : 0.06432366371154785 time for calcul the mask position with numpy : 0.02729940414428711 nb_pixel_total : 27309 time to create 1 rle with old method : 0.030217885971069336 time for calcul the mask position with numpy : 0.028306245803833008 nb_pixel_total : 8288 time to create 1 rle with old method : 0.009498834609985352 time for calcul the mask position with numpy : 0.02810359001159668 nb_pixel_total : 31955 time to create 1 rle with old method : 0.03465080261230469 time for calcul the mask position with numpy : 0.027923107147216797 nb_pixel_total : 25350 time to create 1 rle with old method : 0.027428388595581055 time for calcul the mask position with numpy : 0.028047561645507812 nb_pixel_total : 14079 time to create 1 rle with old method : 0.01568889617919922 time for calcul the mask position with numpy : 0.032570838928222656 nb_pixel_total : 27057 time to create 1 rle with old method : 0.03356671333312988 time for calcul the mask position with numpy : 0.03125596046447754 nb_pixel_total : 43554 time to create 1 rle with old method : 0.04667973518371582 time for calcul the mask position with numpy : 0.02863478660583496 nb_pixel_total : 67998 time to create 1 rle with old method : 0.07496809959411621 time for calcul the mask position with numpy : 0.028511524200439453 nb_pixel_total : 6181 time to create 1 rle with old method : 0.0069544315338134766 time for calcul the mask position with numpy : 0.028711795806884766 nb_pixel_total : 10373 time to create 1 rle with old method : 0.011885404586791992 time for calcul the mask position with numpy : 0.028896808624267578 nb_pixel_total : 49352 time to create 1 rle with old method : 0.05447840690612793 time for calcul the mask position with numpy : 0.02857375144958496 nb_pixel_total : 32602 time to create 1 rle with old method : 0.03748321533203125 time for calcul the mask position with numpy : 0.02843952178955078 nb_pixel_total : 26088 time to create 1 rle with old method : 0.0289609432220459 time for calcul the mask position with numpy : 0.02823662757873535 nb_pixel_total : 37742 time to create 1 rle with old method : 0.04151010513305664 time for calcul the mask position with numpy : 0.028456449508666992 nb_pixel_total : 39847 time to create 1 rle with old method : 0.0437777042388916 time for calcul the mask position with numpy : 0.02813887596130371 nb_pixel_total : 6300 time to create 1 rle with old method : 0.006718873977661133 time for calcul the mask position with numpy : 0.027730226516723633 nb_pixel_total : 24566 time to create 1 rle with old method : 0.026075124740600586 time for calcul the mask position with numpy : 0.027824878692626953 nb_pixel_total : 36813 time to create 1 rle with old method : 0.0438230037689209 time for calcul the mask position with numpy : 0.028767824172973633 nb_pixel_total : 59361 time to create 1 rle with old method : 0.06589913368225098 time for calcul the mask position with numpy : 0.03096938133239746 nb_pixel_total : 5001 time to create 1 rle with old method : 0.00578761100769043 time for calcul the mask position with numpy : 0.0290830135345459 nb_pixel_total : 11153 time to create 1 rle with old method : 0.012276172637939453 time for calcul the mask position with numpy : 0.028537988662719727 nb_pixel_total : 42116 time to create 1 rle with old method : 0.04749321937561035 time for calcul the mask position with numpy : 0.028737306594848633 nb_pixel_total : 12580 time to create 1 rle with old method : 0.013935327529907227 time for calcul the mask position with numpy : 0.03014993667602539 nb_pixel_total : 12246 time to create 1 rle with old method : 0.019587039947509766 time for calcul the mask position with numpy : 0.032985687255859375 nb_pixel_total : 15449 time to create 1 rle with old method : 0.020417213439941406 time for calcul the mask position with numpy : 0.030544519424438477 nb_pixel_total : 7933 time to create 1 rle with old method : 0.00906229019165039 create new chi : 4.05482292175293 time to delete rle : 0.002691030502319336 batch 1 Loaded 89 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 20994 TO DO : save crop sub photo not yet done ! save time : 1.3484559059143066 nb_obj : 71 nb_hashtags : 3 time to prepare the origin masks : 4.388922214508057 time for calcul the mask position with numpy : 0.6897456645965576 nb_pixel_total : 4887541 time to create 1 rle with new method : 0.9082152843475342 time for calcul the mask position with numpy : 0.028695106506347656 nb_pixel_total : 7553 time to create 1 rle with old method : 0.008274555206298828 time for calcul the mask position with numpy : 0.028580427169799805 nb_pixel_total : 31197 time to create 1 rle with old method : 0.03734731674194336 time for calcul the mask position with numpy : 0.03243565559387207 nb_pixel_total : 34177 time to create 1 rle with old method : 0.03962349891662598 time for calcul the mask position with numpy : 0.02877521514892578 nb_pixel_total : 6503 time to create 1 rle with old method : 0.007565975189208984 time for calcul the mask position with numpy : 0.028888225555419922 nb_pixel_total : 35740 time to create 1 rle with old method : 0.03950762748718262 time for calcul the mask position with numpy : 0.027702808380126953 nb_pixel_total : 13037 time to create 1 rle with old method : 0.014252185821533203 time for calcul the mask position with numpy : 0.02790093421936035 nb_pixel_total : 22400 time to create 1 rle with old method : 0.024407625198364258 time for calcul the mask position with numpy : 0.028319358825683594 nb_pixel_total : 6666 time to create 1 rle with old method : 0.007480144500732422 time for calcul the mask position with numpy : 0.028537273406982422 nb_pixel_total : 22559 time to create 1 rle with old method : 0.024345874786376953 time for calcul the mask position with numpy : 0.027702808380126953 nb_pixel_total : 24327 time to create 1 rle with old method : 0.026324033737182617 time for calcul the mask position with numpy : 0.027524709701538086 nb_pixel_total : 28203 time to create 1 rle with old method : 0.03041219711303711 time for calcul the mask position with numpy : 0.028031349182128906 nb_pixel_total : 44214 time to create 1 rle with old method : 0.04691267013549805 time for calcul the mask position with numpy : 0.028051376342773438 nb_pixel_total : 50579 time to create 1 rle with old method : 0.053609371185302734 time for calcul the mask position with numpy : 0.027970314025878906 nb_pixel_total : 48070 time to create 1 rle with old method : 0.05093884468078613 time for calcul the mask position with numpy : 0.028729677200317383 nb_pixel_total : 59535 time to create 1 rle with old method : 0.06643557548522949 time for calcul the mask position with numpy : 0.030975818634033203 nb_pixel_total : 33418 time to create 1 rle with old method : 0.05443096160888672 time for calcul the mask position with numpy : 0.02913832664489746 nb_pixel_total : 23447 time to create 1 rle with old method : 0.026270627975463867 time for calcul the mask position with numpy : 0.028891801834106445 nb_pixel_total : 25284 time to create 1 rle with old method : 0.028143644332885742 time for calcul the mask position with numpy : 0.028527021408081055 nb_pixel_total : 8775 time to create 1 rle with old method : 0.009574174880981445 time for calcul the mask position with numpy : 0.028687238693237305 nb_pixel_total : 51258 time to create 1 rle with old method : 0.05660581588745117 time for calcul the mask position with numpy : 0.02894306182861328 nb_pixel_total : 22466 time to create 1 rle with old method : 0.025017261505126953 time for calcul the mask position with numpy : 0.029027938842773438 nb_pixel_total : 9690 time to create 1 rle with old method : 0.01087641716003418 time for calcul the mask position with numpy : 0.028975248336791992 nb_pixel_total : 15231 time to create 1 rle with old method : 0.0169830322265625 time for calcul the mask position with numpy : 0.02899932861328125 nb_pixel_total : 35832 time to create 1 rle with old method : 0.03977394104003906 time for calcul the mask position with numpy : 0.02798175811767578 nb_pixel_total : 19779 time to create 1 rle with old method : 0.021317005157470703 time for calcul the mask position with numpy : 0.027817726135253906 nb_pixel_total : 17769 time to create 1 rle with old method : 0.019418716430664062 time for calcul the mask position with numpy : 0.02813410758972168 nb_pixel_total : 10189 time to create 1 rle with old method : 0.011372089385986328 time for calcul the mask position with numpy : 0.028212308883666992 nb_pixel_total : 51811 time to create 1 rle with old method : 0.0566859245300293 time for calcul the mask position with numpy : 0.029155492782592773 nb_pixel_total : 202568 time to create 1 rle with new method : 0.5942537784576416 time for calcul the mask position with numpy : 0.028489112854003906 nb_pixel_total : 27546 time to create 1 rle with old method : 0.02999114990234375 time for calcul the mask position with numpy : 0.028313159942626953 nb_pixel_total : 14824 time to create 1 rle with old method : 0.0161440372467041 time for calcul the mask position with numpy : 0.028064250946044922 nb_pixel_total : 14636 time to create 1 rle with old method : 0.01585841178894043 time for calcul the mask position with numpy : 0.028827428817749023 nb_pixel_total : 72735 time to create 1 rle with old method : 0.07715845108032227 time for calcul the mask position with numpy : 0.027887821197509766 nb_pixel_total : 22439 time to create 1 rle with old method : 0.02516007423400879 time for calcul the mask position with numpy : 0.028269290924072266 nb_pixel_total : 51385 time to create 1 rle with old method : 0.058537960052490234 time for calcul the mask position with numpy : 0.027823925018310547 nb_pixel_total : 18309 time to create 1 rle with old method : 0.020178556442260742 time for calcul the mask position with numpy : 0.028327226638793945 nb_pixel_total : 43178 time to create 1 rle with old method : 0.047429561614990234 time for calcul the mask position with numpy : 0.02780461311340332 nb_pixel_total : 12673 time to create 1 rle with old method : 0.013640403747558594 time for calcul the mask position with numpy : 0.0276639461517334 nb_pixel_total : 38135 time to create 1 rle with old method : 0.04179978370666504 time for calcul the mask position with numpy : 0.028446674346923828 nb_pixel_total : 67011 time to create 1 rle with old method : 0.07194280624389648 time for calcul the mask position with numpy : 0.02787017822265625 nb_pixel_total : 11064 time to create 1 rle with old method : 0.012348651885986328 time for calcul the mask position with numpy : 0.028742551803588867 nb_pixel_total : 23206 time to create 1 rle with old method : 0.02578592300415039 time for calcul the mask position with numpy : 0.028291940689086914 nb_pixel_total : 53362 time to create 1 rle with old method : 0.05707287788391113 time for calcul the mask position with numpy : 0.02844405174255371 nb_pixel_total : 12375 time to create 1 rle with old method : 0.01371622085571289 time for calcul the mask position with numpy : 0.028359413146972656 nb_pixel_total : 41361 time to create 1 rle with old method : 0.04476332664489746 time for calcul the mask position with numpy : 0.0285646915435791 nb_pixel_total : 22634 time to create 1 rle with old method : 0.02458024024963379 time for calcul the mask position with numpy : 0.02792644500732422 nb_pixel_total : 260 time to create 1 rle with old method : 0.0004334449768066406 time for calcul the mask position with numpy : 0.026826858520507812 nb_pixel_total : 29702 time to create 1 rle with old method : 0.031456947326660156 time for calcul the mask position with numpy : 0.027444124221801758 nb_pixel_total : 21491 time to create 1 rle with old method : 0.023554086685180664 time for calcul the mask position with numpy : 0.027721166610717773 nb_pixel_total : 33946 time to create 1 rle with old method : 0.038803815841674805 time for calcul the mask position with numpy : 0.028200626373291016 nb_pixel_total : 17883 time to create 1 rle with old method : 0.019348621368408203 time for calcul the mask position with numpy : 0.027719736099243164 nb_pixel_total : 7621 time to create 1 rle with old method : 0.008094310760498047 time for calcul the mask position with numpy : 0.027885913848876953 nb_pixel_total : 77090 time to create 1 rle with old method : 0.08364391326904297 time for calcul the mask position with numpy : 0.028351545333862305 nb_pixel_total : 93642 time to create 1 rle with old method : 0.09938335418701172 time for calcul the mask position with numpy : 0.030011653900146484 nb_pixel_total : 23170 time to create 1 rle with old method : 0.02780771255493164 time for calcul the mask position with numpy : 0.027308225631713867 nb_pixel_total : 74675 time to create 1 rle with old method : 0.07852482795715332 time for calcul the mask position with numpy : 0.027318954467773438 nb_pixel_total : 22763 time to create 1 rle with old method : 0.024261474609375 time for calcul the mask position with numpy : 0.027338504791259766 nb_pixel_total : 19679 time to create 1 rle with old method : 0.021140575408935547 time for calcul the mask position with numpy : 0.027884244918823242 nb_pixel_total : 27846 time to create 1 rle with old method : 0.029525279998779297 time for calcul the mask position with numpy : 0.02780318260192871 nb_pixel_total : 6003 time to create 1 rle with old method : 0.0063135623931884766 time for calcul the mask position with numpy : 0.02947545051574707 nb_pixel_total : 20253 time to create 1 rle with old method : 0.022150754928588867 time for calcul the mask position with numpy : 0.027817726135253906 nb_pixel_total : 26963 time to create 1 rle with old method : 0.02910590171813965 time for calcul the mask position with numpy : 0.027763843536376953 nb_pixel_total : 28039 time to create 1 rle with old method : 0.03035426139831543 time for calcul the mask position with numpy : 0.028069496154785156 nb_pixel_total : 23362 time to create 1 rle with old method : 0.025056123733520508 time for calcul the mask position with numpy : 0.02752232551574707 nb_pixel_total : 25520 time to create 1 rle with old method : 0.02689218521118164 time for calcul the mask position with numpy : 0.0282135009765625 nb_pixel_total : 6503 time to create 1 rle with old method : 0.007113218307495117 time for calcul the mask position with numpy : 0.027902603149414062 nb_pixel_total : 12847 time to create 1 rle with old method : 0.013812541961669922 time for calcul the mask position with numpy : 0.028149843215942383 nb_pixel_total : 26229 time to create 1 rle with old method : 0.028264522552490234 time for calcul the mask position with numpy : 0.0274200439453125 nb_pixel_total : 7509 time to create 1 rle with old method : 0.0078105926513671875 time for calcul the mask position with numpy : 0.02733445167541504 nb_pixel_total : 14677 time to create 1 rle with old method : 0.01593303680419922 time for calcul the mask position with numpy : 0.02755451202392578 nb_pixel_total : 5876 time to create 1 rle with old method : 0.006381988525390625 create new chi : 6.417042016983032 time to delete rle : 0.005087375640869141 batch 1 Loaded 143 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 35994 TO DO : save crop sub photo not yet done ! save time : 2.608290195465088 nb_obj : 70 nb_hashtags : 3 time to prepare the origin masks : 4.407249212265015 time for calcul the mask position with numpy : 0.6316230297088623 nb_pixel_total : 5078461 time to create 1 rle with new method : 0.6791791915893555 time for calcul the mask position with numpy : 0.02864527702331543 nb_pixel_total : 15891 time to create 1 rle with old method : 0.020082950592041016 time for calcul the mask position with numpy : 0.03286480903625488 nb_pixel_total : 8088 time to create 1 rle with old method : 0.013398408889770508 time for calcul the mask position with numpy : 0.03241372108459473 nb_pixel_total : 7355 time to create 1 rle with old method : 0.008627891540527344 time for calcul the mask position with numpy : 0.029473543167114258 nb_pixel_total : 61797 time to create 1 rle with old method : 0.06891822814941406 time for calcul the mask position with numpy : 0.029085874557495117 nb_pixel_total : 26818 time to create 1 rle with old method : 0.030252695083618164 time for calcul the mask position with numpy : 0.029258251190185547 nb_pixel_total : 12931 time to create 1 rle with old method : 0.014545679092407227 time for calcul the mask position with numpy : 0.029376745223999023 nb_pixel_total : 26944 time to create 1 rle with old method : 0.030170202255249023 time for calcul the mask position with numpy : 0.029583215713500977 nb_pixel_total : 15937 time to create 1 rle with old method : 0.018059730529785156 time for calcul the mask position with numpy : 0.029554128646850586 nb_pixel_total : 31261 time to create 1 rle with old method : 0.03507637977600098 time for calcul the mask position with numpy : 0.029596328735351562 nb_pixel_total : 16123 time to create 1 rle with old method : 0.018189430236816406 time for calcul the mask position with numpy : 0.029370546340942383 nb_pixel_total : 26625 time to create 1 rle with old method : 0.03017568588256836 time for calcul the mask position with numpy : 0.02873516082763672 nb_pixel_total : 61468 time to create 1 rle with old method : 0.06770849227905273 time for calcul the mask position with numpy : 0.0286407470703125 nb_pixel_total : 41882 time to create 1 rle with old method : 0.045227766036987305 time for calcul the mask position with numpy : 0.027761459350585938 nb_pixel_total : 23105 time to create 1 rle with old method : 0.024831533432006836 time for calcul the mask position with numpy : 0.026950597763061523 nb_pixel_total : 35101 time to create 1 rle with old method : 0.037751197814941406 time for calcul the mask position with numpy : 0.027266979217529297 nb_pixel_total : 25291 time to create 1 rle with old method : 0.027265071868896484 time for calcul the mask position with numpy : 0.027940034866333008 nb_pixel_total : 13655 time to create 1 rle with old method : 0.014774322509765625 time for calcul the mask position with numpy : 0.027849435806274414 nb_pixel_total : 15162 time to create 1 rle with old method : 0.01648426055908203 time for calcul the mask position with numpy : 0.02793264389038086 nb_pixel_total : 44645 time to create 1 rle with old method : 0.049788713455200195 time for calcul the mask position with numpy : 0.028267860412597656 nb_pixel_total : 22830 time to create 1 rle with old method : 0.023888587951660156 time for calcul the mask position with numpy : 0.027504920959472656 nb_pixel_total : 9385 time to create 1 rle with old method : 0.010001182556152344 time for calcul the mask position with numpy : 0.027593135833740234 nb_pixel_total : 35438 time to create 1 rle with old method : 0.03942704200744629 time for calcul the mask position with numpy : 0.0317845344543457 nb_pixel_total : 21723 time to create 1 rle with old method : 0.02424931526184082 time for calcul the mask position with numpy : 0.028810977935791016 nb_pixel_total : 31861 time to create 1 rle with old method : 0.03519487380981445 time for calcul the mask position with numpy : 0.028687477111816406 nb_pixel_total : 75435 time to create 1 rle with old method : 0.08301520347595215 time for calcul the mask position with numpy : 0.02866506576538086 nb_pixel_total : 32132 time to create 1 rle with old method : 0.03555130958557129 time for calcul the mask position with numpy : 0.02870798110961914 nb_pixel_total : 25403 time to create 1 rle with old method : 0.028141021728515625 time for calcul the mask position with numpy : 0.028377532958984375 nb_pixel_total : 30285 time to create 1 rle with old method : 0.033202409744262695 time for calcul the mask position with numpy : 0.028554916381835938 nb_pixel_total : 5429 time to create 1 rle with old method : 0.005926847457885742 time for calcul the mask position with numpy : 0.028066158294677734 nb_pixel_total : 109544 time to create 1 rle with old method : 0.11919450759887695 time for calcul the mask position with numpy : 0.028364896774291992 nb_pixel_total : 17500 time to create 1 rle with old method : 0.019026517868041992 time for calcul the mask position with numpy : 0.027917861938476562 nb_pixel_total : 10764 time to create 1 rle with old method : 0.01205897331237793 time for calcul the mask position with numpy : 0.028895139694213867 nb_pixel_total : 104649 time to create 1 rle with old method : 0.1138155460357666 time for calcul the mask position with numpy : 0.02703118324279785 nb_pixel_total : 21552 time to create 1 rle with old method : 0.022387981414794922 time for calcul the mask position with numpy : 0.027164220809936523 nb_pixel_total : 38657 time to create 1 rle with old method : 0.03964734077453613 time for calcul the mask position with numpy : 0.02646613121032715 nb_pixel_total : 16964 time to create 1 rle with old method : 0.018021821975708008 time for calcul the mask position with numpy : 0.02697610855102539 nb_pixel_total : 46360 time to create 1 rle with old method : 0.05019974708557129 time for calcul the mask position with numpy : 0.03318500518798828 nb_pixel_total : 89080 time to create 1 rle with old method : 0.1167900562286377 time for calcul the mask position with numpy : 0.029702425003051758 nb_pixel_total : 21219 time to create 1 rle with old method : 0.02428150177001953 time for calcul the mask position with numpy : 0.029259443283081055 nb_pixel_total : 23769 time to create 1 rle with old method : 0.02766108512878418 time for calcul the mask position with numpy : 0.02900862693786621 nb_pixel_total : 20611 time to create 1 rle with old method : 0.02265620231628418 time for calcul the mask position with numpy : 0.028456687927246094 nb_pixel_total : 33177 time to create 1 rle with old method : 0.03864240646362305 time for calcul the mask position with numpy : 0.02899956703186035 nb_pixel_total : 87905 time to create 1 rle with old method : 0.0968470573425293 time for calcul the mask position with numpy : 0.02795720100402832 nb_pixel_total : 19562 time to create 1 rle with old method : 0.021442174911499023 time for calcul the mask position with numpy : 0.027898550033569336 nb_pixel_total : 7794 time to create 1 rle with old method : 0.00846242904663086 time for calcul the mask position with numpy : 0.02783036231994629 nb_pixel_total : 16707 time to create 1 rle with old method : 0.018219709396362305 time for calcul the mask position with numpy : 0.02803325653076172 nb_pixel_total : 12867 time to create 1 rle with old method : 0.014183759689331055 time for calcul the mask position with numpy : 0.027650117874145508 nb_pixel_total : 14695 time to create 1 rle with old method : 0.015900135040283203 time for calcul the mask position with numpy : 0.028319358825683594 nb_pixel_total : 60527 time to create 1 rle with old method : 0.06643438339233398 time for calcul the mask position with numpy : 0.029201507568359375 nb_pixel_total : 79217 time to create 1 rle with old method : 0.0965111255645752 time for calcul the mask position with numpy : 0.03300738334655762 nb_pixel_total : 32134 time to create 1 rle with old method : 0.04155111312866211 time for calcul the mask position with numpy : 0.0283203125 nb_pixel_total : 5090 time to create 1 rle with old method : 0.0055446624755859375 time for calcul the mask position with numpy : 0.027688026428222656 nb_pixel_total : 6217 time to create 1 rle with old method : 0.006938934326171875 time for calcul the mask position with numpy : 0.028120040893554688 nb_pixel_total : 13595 time to create 1 rle with old method : 0.014934301376342773 time for calcul the mask position with numpy : 0.028162240982055664 nb_pixel_total : 15708 time to create 1 rle with old method : 0.017371654510498047 time for calcul the mask position with numpy : 0.02819061279296875 nb_pixel_total : 11840 time to create 1 rle with old method : 0.01265263557434082 time for calcul the mask position with numpy : 0.02865767478942871 nb_pixel_total : 23185 time to create 1 rle with old method : 0.025632858276367188 time for calcul the mask position with numpy : 0.028860807418823242 nb_pixel_total : 15664 time to create 1 rle with old method : 0.017250537872314453 time for calcul the mask position with numpy : 0.02820611000061035 nb_pixel_total : 49656 time to create 1 rle with old method : 0.05714559555053711 time for calcul the mask position with numpy : 0.02906036376953125 nb_pixel_total : 5480 time to create 1 rle with old method : 0.006290912628173828 time for calcul the mask position with numpy : 0.02880549430847168 nb_pixel_total : 39131 time to create 1 rle with old method : 0.04282665252685547 time for calcul the mask position with numpy : 0.027931928634643555 nb_pixel_total : 5318 time to create 1 rle with old method : 0.005629062652587891 time for calcul the mask position with numpy : 0.027672529220581055 nb_pixel_total : 8647 time to create 1 rle with old method : 0.009054422378540039 time for calcul the mask position with numpy : 0.02751755714416504 nb_pixel_total : 9845 time to create 1 rle with old method : 0.010812997817993164 time for calcul the mask position with numpy : 0.027575254440307617 nb_pixel_total : 16299 time to create 1 rle with old method : 0.01791071891784668 time for calcul the mask position with numpy : 0.028043031692504883 nb_pixel_total : 28398 time to create 1 rle with old method : 0.03136467933654785 time for calcul the mask position with numpy : 0.02855515480041504 nb_pixel_total : 8840 time to create 1 rle with old method : 0.01001739501953125 time for calcul the mask position with numpy : 0.028461694717407227 nb_pixel_total : 2728 time to create 1 rle with old method : 0.0030374526977539062 time for calcul the mask position with numpy : 0.026808977127075195 nb_pixel_total : 10118 time to create 1 rle with old method : 0.01112818717956543 time for calcul the mask position with numpy : 0.027811527252197266 nb_pixel_total : 10766 time to create 1 rle with old method : 0.011863231658935547 create new chi : 5.561136484146118 time to delete rle : 0.0046193599700927734 batch 1 Loaded 141 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 33909 TO DO : save crop sub photo not yet done ! save time : 2.1339778900146484 nb_obj : 56 nb_hashtags : 4 time to prepare the origin masks : 4.291203260421753 time for calcul the mask position with numpy : 1.0087995529174805 nb_pixel_total : 5594137 time to create 1 rle with new method : 0.9170329570770264 time for calcul the mask position with numpy : 0.030092716217041016 nb_pixel_total : 38332 time to create 1 rle with old method : 0.04447031021118164 time for calcul the mask position with numpy : 0.028841257095336914 nb_pixel_total : 697 time to create 1 rle with old method : 0.0007755756378173828 time for calcul the mask position with numpy : 0.028078556060791016 nb_pixel_total : 5246 time to create 1 rle with old method : 0.005707740783691406 time for calcul the mask position with numpy : 0.027950763702392578 nb_pixel_total : 34519 time to create 1 rle with old method : 0.03883647918701172 time for calcul the mask position with numpy : 0.02825021743774414 nb_pixel_total : 8887 time to create 1 rle with old method : 0.009608268737792969 time for calcul the mask position with numpy : 0.027948856353759766 nb_pixel_total : 14758 time to create 1 rle with old method : 0.01607489585876465 time for calcul the mask position with numpy : 0.02823638916015625 nb_pixel_total : 7267 time to create 1 rle with old method : 0.008070230484008789 time for calcul the mask position with numpy : 0.029279232025146484 nb_pixel_total : 44587 time to create 1 rle with old method : 0.04924440383911133 time for calcul the mask position with numpy : 0.03569316864013672 nb_pixel_total : 22748 time to create 1 rle with old method : 0.03682112693786621 time for calcul the mask position with numpy : 0.032770395278930664 nb_pixel_total : 6022 time to create 1 rle with old method : 0.008849143981933594 time for calcul the mask position with numpy : 0.028192996978759766 nb_pixel_total : 7638 time to create 1 rle with old method : 0.008229255676269531 time for calcul the mask position with numpy : 0.027675151824951172 nb_pixel_total : 13097 time to create 1 rle with old method : 0.014676809310913086 time for calcul the mask position with numpy : 0.027083158493041992 nb_pixel_total : 13453 time to create 1 rle with old method : 0.014623403549194336 time for calcul the mask position with numpy : 0.02685832977294922 nb_pixel_total : 22611 time to create 1 rle with old method : 0.023998260498046875 time for calcul the mask position with numpy : 0.0272982120513916 nb_pixel_total : 36222 time to create 1 rle with old method : 0.039266347885131836 time for calcul the mask position with numpy : 0.028374433517456055 nb_pixel_total : 47927 time to create 1 rle with old method : 0.05376553535461426 time for calcul the mask position with numpy : 0.029146671295166016 nb_pixel_total : 29794 time to create 1 rle with old method : 0.040158748626708984 time for calcul the mask position with numpy : 0.03178524971008301 nb_pixel_total : 5542 time to create 1 rle with old method : 0.006242513656616211 time for calcul the mask position with numpy : 0.02797222137451172 nb_pixel_total : 26009 time to create 1 rle with old method : 0.02807450294494629 time for calcul the mask position with numpy : 0.0289461612701416 nb_pixel_total : 29538 time to create 1 rle with old method : 0.03238201141357422 time for calcul the mask position with numpy : 0.030002593994140625 nb_pixel_total : 19396 time to create 1 rle with old method : 0.03151297569274902 time for calcul the mask position with numpy : 0.03267812728881836 nb_pixel_total : 40063 time to create 1 rle with old method : 0.043915748596191406 time for calcul the mask position with numpy : 0.02863168716430664 nb_pixel_total : 31662 time to create 1 rle with old method : 0.03534293174743652 time for calcul the mask position with numpy : 0.029697418212890625 nb_pixel_total : 9955 time to create 1 rle with old method : 0.012255191802978516 time for calcul the mask position with numpy : 0.02879810333251953 nb_pixel_total : 20724 time to create 1 rle with old method : 0.02282857894897461 time for calcul the mask position with numpy : 0.02794361114501953 nb_pixel_total : 13456 time to create 1 rle with old method : 0.014944791793823242 time for calcul the mask position with numpy : 0.027980804443359375 nb_pixel_total : 51468 time to create 1 rle with old method : 0.056185245513916016 time for calcul the mask position with numpy : 0.028111696243286133 nb_pixel_total : 98538 time to create 1 rle with old method : 0.10683417320251465 time for calcul the mask position with numpy : 0.027535200119018555 nb_pixel_total : 46851 time to create 1 rle with old method : 0.050595760345458984 time for calcul the mask position with numpy : 0.028583526611328125 nb_pixel_total : 64510 time to create 1 rle with old method : 0.06888222694396973 time for calcul the mask position with numpy : 0.027737140655517578 nb_pixel_total : 9730 time to create 1 rle with old method : 0.010479927062988281 time for calcul the mask position with numpy : 0.028029918670654297 nb_pixel_total : 1332 time to create 1 rle with old method : 0.0015256404876708984 time for calcul the mask position with numpy : 0.028178930282592773 nb_pixel_total : 28579 time to create 1 rle with old method : 0.031213998794555664 time for calcul the mask position with numpy : 0.02772045135498047 nb_pixel_total : 20904 time to create 1 rle with old method : 0.02236628532409668 time for calcul the mask position with numpy : 0.02734088897705078 nb_pixel_total : 29741 time to create 1 rle with old method : 0.03103804588317871 time for calcul the mask position with numpy : 0.0277252197265625 nb_pixel_total : 92257 time to create 1 rle with old method : 0.1002202033996582 time for calcul the mask position with numpy : 0.028653621673583984 nb_pixel_total : 20811 time to create 1 rle with old method : 0.022689104080200195 time for calcul the mask position with numpy : 0.027614831924438477 nb_pixel_total : 7684 time to create 1 rle with old method : 0.008080482482910156 time for calcul the mask position with numpy : 0.026953458786010742 nb_pixel_total : 110090 time to create 1 rle with old method : 0.1264638900756836 time for calcul the mask position with numpy : 0.027998685836791992 nb_pixel_total : 5455 time to create 1 rle with old method : 0.0060269832611083984 time for calcul the mask position with numpy : 0.028182029724121094 nb_pixel_total : 22505 time to create 1 rle with old method : 0.02387070655822754 time for calcul the mask position with numpy : 0.027322053909301758 nb_pixel_total : 11141 time to create 1 rle with old method : 0.012590169906616211 time for calcul the mask position with numpy : 0.028518199920654297 nb_pixel_total : 29470 time to create 1 rle with old method : 0.03210020065307617 time for calcul the mask position with numpy : 0.027961254119873047 nb_pixel_total : 19164 time to create 1 rle with old method : 0.020861148834228516 time for calcul the mask position with numpy : 0.028735876083374023 nb_pixel_total : 26585 time to create 1 rle with old method : 0.03366565704345703 time for calcul the mask position with numpy : 0.028408527374267578 nb_pixel_total : 19566 time to create 1 rle with old method : 0.020728588104248047 time for calcul the mask position with numpy : 0.027985572814941406 nb_pixel_total : 44605 time to create 1 rle with old method : 0.047577619552612305 time for calcul the mask position with numpy : 0.028481483459472656 nb_pixel_total : 9851 time to create 1 rle with old method : 0.011072874069213867 time for calcul the mask position with numpy : 0.02930450439453125 nb_pixel_total : 5981 time to create 1 rle with old method : 0.007024526596069336 time for calcul the mask position with numpy : 0.02825927734375 nb_pixel_total : 10474 time to create 1 rle with old method : 0.013657808303833008 time for calcul the mask position with numpy : 0.02888011932373047 nb_pixel_total : 12769 time to create 1 rle with old method : 0.014003753662109375 time for calcul the mask position with numpy : 0.028885841369628906 nb_pixel_total : 40938 time to create 1 rle with old method : 0.0442500114440918 time for calcul the mask position with numpy : 0.028164148330688477 nb_pixel_total : 13397 time to create 1 rle with old method : 0.014762639999389648 time for calcul the mask position with numpy : 0.028583526611328125 nb_pixel_total : 30052 time to create 1 rle with old method : 0.031690359115600586 time for calcul the mask position with numpy : 0.027747154235839844 nb_pixel_total : 12733 time to create 1 rle with old method : 0.014111518859863281 time for calcul the mask position with numpy : 0.0295257568359375 nb_pixel_total : 8772 time to create 1 rle with old method : 0.009661197662353516 create new chi : 5.206892728805542 time to delete rle : 0.0032083988189697266 batch 1 Loaded 113 chid ids of type : 3594 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 25035 TO DO : save crop sub photo not yet done ! save time : 1.5930109024047852 nb_obj : 69 nb_hashtags : 5 time to prepare the origin masks : 4.317643404006958 time for calcul the mask position with numpy : 0.41618990898132324 nb_pixel_total : 5383054 time to create 1 rle with new method : 0.7135679721832275 time for calcul the mask position with numpy : 0.028783082962036133 nb_pixel_total : 33162 time to create 1 rle with old method : 0.03649592399597168 time for calcul the mask position with numpy : 0.02904510498046875 nb_pixel_total : 46641 time to create 1 rle with old method : 0.05122232437133789 time for calcul the mask position with numpy : 0.02868938446044922 nb_pixel_total : 7423 time to create 1 rle with old method : 0.008603572845458984 time for calcul the mask position with numpy : 0.03090214729309082 nb_pixel_total : 17803 time to create 1 rle with old method : 0.021727561950683594 time for calcul the mask position with numpy : 0.030179738998413086 nb_pixel_total : 51825 time to create 1 rle with old method : 0.06021523475646973 time for calcul the mask position with numpy : 0.02911972999572754 nb_pixel_total : 13014 time to create 1 rle with old method : 0.014455556869506836 time for calcul the mask position with numpy : 0.029256582260131836 nb_pixel_total : 25727 time to create 1 rle with old method : 0.02854442596435547 time for calcul the mask position with numpy : 0.03003525733947754 nb_pixel_total : 24507 time to create 1 rle with old method : 0.028612852096557617 time for calcul the mask position with numpy : 0.029440879821777344 nb_pixel_total : 15117 time to create 1 rle with old method : 0.01790475845336914 time for calcul the mask position with numpy : 0.030684471130371094 nb_pixel_total : 16841 time to create 1 rle with old method : 0.021169424057006836 time for calcul the mask position with numpy : 0.030872821807861328 nb_pixel_total : 13134 time to create 1 rle with old method : 0.01724839210510254 time for calcul the mask position with numpy : 0.02942824363708496 nb_pixel_total : 5819 time to create 1 rle with old method : 0.006590127944946289 time for calcul the mask position with numpy : 0.02948904037475586 nb_pixel_total : 25521 time to create 1 rle with old method : 0.029247760772705078 time for calcul the mask position with numpy : 0.02933955192565918 nb_pixel_total : 5281 time to create 1 rle with old method : 0.006556034088134766 time for calcul the mask position with numpy : 0.02947258949279785 nb_pixel_total : 9967 time to create 1 rle with old method : 0.011399984359741211 time for calcul the mask position with numpy : 0.029700756072998047 nb_pixel_total : 19441 time to create 1 rle with old method : 0.021677494049072266 time for calcul the mask position with numpy : 0.029436349868774414 nb_pixel_total : 21105 time to create 1 rle with old method : 0.02387714385986328 time for calcul the mask position with numpy : 0.029367923736572266 nb_pixel_total : 74559 time to create 1 rle with old method : 0.09393692016601562 time for calcul the mask position with numpy : 0.03300809860229492 nb_pixel_total : 17974 time to create 1 rle with old method : 0.02747511863708496 time for calcul the mask position with numpy : 0.028072118759155273 nb_pixel_total : 38776 time to create 1 rle with old method : 0.042177438735961914 time for calcul the mask position with numpy : 0.02849888801574707 nb_pixel_total : 28478 time to create 1 rle with old method : 0.03119039535522461 time for calcul the mask position with numpy : 0.027828693389892578 nb_pixel_total : 21396 time to create 1 rle with old method : 0.023396968841552734 time for calcul the mask position with numpy : 0.028566837310791016 nb_pixel_total : 9944 time to create 1 rle with old method : 0.010881423950195312 time for calcul the mask position with numpy : 0.028701066970825195 nb_pixel_total : 22959 time to create 1 rle with old method : 0.026011228561401367 time for calcul the mask position with numpy : 0.029150962829589844 nb_pixel_total : 4763 time to create 1 rle with old method : 0.005476951599121094 time for calcul the mask position with numpy : 0.02883601188659668 nb_pixel_total : 27432 time to create 1 rle with old method : 0.03072977066040039 time for calcul the mask position with numpy : 0.03777718544006348 nb_pixel_total : 41716 time to create 1 rle with old method : 0.0521693229675293 time for calcul the mask position with numpy : 0.03731989860534668 nb_pixel_total : 46584 time to create 1 rle with old method : 0.05322527885437012 time for calcul the mask position with numpy : 0.029545068740844727 nb_pixel_total : 109223 time to create 1 rle with old method : 0.13115668296813965 time for calcul the mask position with numpy : 0.029019832611083984 nb_pixel_total : 53715 time to create 1 rle with old method : 0.06016731262207031 time for calcul the mask position with numpy : 0.02921772003173828 nb_pixel_total : 8129 time to create 1 rle with old method : 0.009357452392578125 time for calcul the mask position with numpy : 0.029415607452392578 nb_pixel_total : 21700 time to create 1 rle with old method : 0.024502277374267578 time for calcul the mask position with numpy : 0.029694318771362305 nb_pixel_total : 8494 time to create 1 rle with old method : 0.009738445281982422 time for calcul the mask position with numpy : 0.029933929443359375 nb_pixel_total : 43406 time to create 1 rle with old method : 0.04841423034667969 time for calcul the mask position with numpy : 0.028553009033203125 nb_pixel_total : 29888 time to create 1 rle with old method : 0.03255510330200195 time for calcul the mask position with numpy : 0.029122114181518555 nb_pixel_total : 29882 time to create 1 rle with old method : 0.03369498252868652 time for calcul the mask position with numpy : 0.029135704040527344 nb_pixel_total : 35586 time to create 1 rle with old method : 0.04016733169555664 time for calcul the mask position with numpy : 0.029262781143188477 nb_pixel_total : 21993 time to create 1 rle with old method : 0.03209853172302246 time for calcul the mask position with numpy : 0.029056787490844727 nb_pixel_total : 73407 time to create 1 rle with old method : 0.08154153823852539 time for calcul the mask position with numpy : 0.0284731388092041 nb_pixel_total : 12197 time to create 1 rle with old method : 0.013463497161865234 time for calcul the mask position with numpy : 0.03583884239196777 nb_pixel_total : 46465 time to create 1 rle with old method : 0.06503987312316895 time for calcul the mask position with numpy : 0.028461456298828125 nb_pixel_total : 1337 time to create 1 rle with old method : 0.0016312599182128906 time for calcul the mask position with numpy : 0.028776884078979492 nb_pixel_total : 14660 time to create 1 rle with old method : 0.016233444213867188 time for calcul the mask position with numpy : 0.03285646438598633 nb_pixel_total : 38490 time to create 1 rle with old method : 0.05677461624145508 time for calcul the mask position with numpy : 0.029051780700683594 nb_pixel_total : 65821 time to create 1 rle with old method : 0.07282137870788574 time for calcul the mask position with numpy : 0.028656959533691406 nb_pixel_total : 11603 time to create 1 rle with old method : 0.012820959091186523 time for calcul the mask position with numpy : 0.028841257095336914 nb_pixel_total : 51245 time to create 1 rle with old method : 0.056800127029418945 time for calcul the mask position with numpy : 0.029413938522338867 nb_pixel_total : 8164 time to create 1 rle with old method : 0.009265899658203125 time for calcul the mask position with numpy : 0.02940845489501953 nb_pixel_total : 4590 time to create 1 rle with old method : 0.0053348541259765625 time for calcul the mask position with numpy : 0.028821229934692383 nb_pixel_total : 22357 time to create 1 rle with old method : 0.024965524673461914 time for calcul the mask position with numpy : 0.029402732849121094 nb_pixel_total : 10952 time to create 1 rle with old method : 0.012166976928710938 time for calcul the mask position with numpy : 0.029159069061279297 nb_pixel_total : 68253 time to create 1 rle with old method : 0.07787752151489258 time for calcul the mask position with numpy : 0.02886176109313965 nb_pixel_total : 30453 time to create 1 rle with old method : 0.033437490463256836 time for calcul the mask position with numpy : 0.028638124465942383 nb_pixel_total : 20722 time to create 1 rle with old method : 0.02211165428161621 time for calcul the mask position with numpy : 0.027823448181152344 nb_pixel_total : 18479 time to create 1 rle with old method : 0.02014946937561035 time for calcul the mask position with numpy : 0.02922987937927246 nb_pixel_total : 21196 time to create 1 rle with old method : 0.023662090301513672 time for calcul the mask position with numpy : 0.028870820999145508 nb_pixel_total : 5563 time to create 1 rle with old method : 0.006075859069824219 time for calcul the mask position with numpy : 0.028224706649780273 nb_pixel_total : 2992 time to create 1 rle with old method : 0.0032689571380615234 time for calcul the mask position with numpy : 0.028011322021484375 nb_pixel_total : 20841 time to create 1 rle with old method : 0.022701025009155273 time for calcul the mask position with numpy : 0.02886795997619629 nb_pixel_total : 15942 time to create 1 rle with old method : 0.017969846725463867 time for calcul the mask position with numpy : 0.02934741973876953 nb_pixel_total : 999 time to create 1 rle with old method : 0.0012276172637939453 time for calcul the mask position with numpy : 0.029344558715820312 nb_pixel_total : 3914 time to create 1 rle with old method : 0.004443645477294922 time for calcul the mask position with numpy : 0.031071186065673828 nb_pixel_total : 5883 time to create 1 rle with old method : 0.0067369937896728516 time for calcul the mask position with numpy : 0.029620885848999023 nb_pixel_total : 11158 time to create 1 rle with old method : 0.012105464935302734 time for calcul the mask position with numpy : 0.028796672821044922 nb_pixel_total : 3925 time to create 1 rle with old method : 0.0044155120849609375 time for calcul the mask position with numpy : 0.027808189392089844 nb_pixel_total : 10610 time to create 1 rle with old method : 0.011435985565185547 time for calcul the mask position with numpy : 0.029208898544311523 nb_pixel_total : 4477 time to create 1 rle with old method : 0.005162715911865234 time for calcul the mask position with numpy : 0.02874279022216797 nb_pixel_total : 6378 time to create 1 rle with old method : 0.007277250289916992 time for calcul the mask position with numpy : 0.03035283088684082 nb_pixel_total : 5188 time to create 1 rle with old method : 0.005872964859008789 create new chi : 5.147872686386108 time to delete rle : 0.0046918392181396484 batch 1 Loaded 139 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 27503 TO DO : save crop sub photo not yet done ! save time : 1.8238232135772705 nb_obj : 47 nb_hashtags : 4 time to prepare the origin masks : 4.048229455947876 time for calcul the mask position with numpy : 0.9543945789337158 nb_pixel_total : 5597407 time to create 1 rle with new method : 0.5143156051635742 time for calcul the mask position with numpy : 0.029234647750854492 nb_pixel_total : 15792 time to create 1 rle with old method : 0.01765608787536621 time for calcul the mask position with numpy : 0.03189826011657715 nb_pixel_total : 12982 time to create 1 rle with old method : 0.021245718002319336 time for calcul the mask position with numpy : 0.03293132781982422 nb_pixel_total : 15681 time to create 1 rle with old method : 0.025625944137573242 time for calcul the mask position with numpy : 0.03322124481201172 nb_pixel_total : 13945 time to create 1 rle with old method : 0.019643068313598633 time for calcul the mask position with numpy : 0.033338069915771484 nb_pixel_total : 13259 time to create 1 rle with old method : 0.021546363830566406 time for calcul the mask position with numpy : 0.03405499458312988 nb_pixel_total : 14846 time to create 1 rle with old method : 0.016535520553588867 time for calcul the mask position with numpy : 0.029327392578125 nb_pixel_total : 25134 time to create 1 rle with old method : 0.0279386043548584 time for calcul the mask position with numpy : 0.029367923736572266 nb_pixel_total : 30450 time to create 1 rle with old method : 0.03408622741699219 time for calcul the mask position with numpy : 0.02901935577392578 nb_pixel_total : 4772 time to create 1 rle with old method : 0.005344867706298828 time for calcul the mask position with numpy : 0.030846834182739258 nb_pixel_total : 46305 time to create 1 rle with old method : 0.054357051849365234 time for calcul the mask position with numpy : 0.028768539428710938 nb_pixel_total : 19765 time to create 1 rle with old method : 0.022058725357055664 time for calcul the mask position with numpy : 0.028345108032226562 nb_pixel_total : 20087 time to create 1 rle with old method : 0.02234196662902832 time for calcul the mask position with numpy : 0.029103517532348633 nb_pixel_total : 131106 time to create 1 rle with old method : 0.14481186866760254 time for calcul the mask position with numpy : 0.02840137481689453 nb_pixel_total : 23853 time to create 1 rle with old method : 0.026169538497924805 time for calcul the mask position with numpy : 0.028449296951293945 nb_pixel_total : 12626 time to create 1 rle with old method : 0.013892650604248047 time for calcul the mask position with numpy : 0.0271453857421875 nb_pixel_total : 24946 time to create 1 rle with old method : 0.027265310287475586 time for calcul the mask position with numpy : 0.028311729431152344 nb_pixel_total : 14296 time to create 1 rle with old method : 0.015168190002441406 time for calcul the mask position with numpy : 0.027890920639038086 nb_pixel_total : 18222 time to create 1 rle with old method : 0.019507646560668945 time for calcul the mask position with numpy : 0.0279538631439209 nb_pixel_total : 98352 time to create 1 rle with old method : 0.10502266883850098 time for calcul the mask position with numpy : 0.029723405838012695 nb_pixel_total : 178358 time to create 1 rle with new method : 1.3767354488372803 time for calcul the mask position with numpy : 0.029436588287353516 nb_pixel_total : 100449 time to create 1 rle with old method : 0.11011505126953125 time for calcul the mask position with numpy : 0.028153419494628906 nb_pixel_total : 12559 time to create 1 rle with old method : 0.014067649841308594 time for calcul the mask position with numpy : 0.02817821502685547 nb_pixel_total : 34587 time to create 1 rle with old method : 0.0382840633392334 time for calcul the mask position with numpy : 0.028800249099731445 nb_pixel_total : 7313 time to create 1 rle with old method : 0.008315801620483398 time for calcul the mask position with numpy : 0.028717756271362305 nb_pixel_total : 12863 time to create 1 rle with old method : 0.014429807662963867 time for calcul the mask position with numpy : 0.02878117561340332 nb_pixel_total : 32476 time to create 1 rle with old method : 0.03652667999267578 time for calcul the mask position with numpy : 0.02898430824279785 nb_pixel_total : 36454 time to create 1 rle with old method : 0.04113149642944336 time for calcul the mask position with numpy : 0.028896808624267578 nb_pixel_total : 45277 time to create 1 rle with old method : 0.05063199996948242 time for calcul the mask position with numpy : 0.029003143310546875 nb_pixel_total : 47850 time to create 1 rle with old method : 0.06844758987426758 time for calcul the mask position with numpy : 0.02925252914428711 nb_pixel_total : 16716 time to create 1 rle with old method : 0.018808364868164062 time for calcul the mask position with numpy : 0.029260873794555664 nb_pixel_total : 18127 time to create 1 rle with old method : 0.020502567291259766 time for calcul the mask position with numpy : 0.029163360595703125 nb_pixel_total : 17685 time to create 1 rle with old method : 0.02034449577331543 time for calcul the mask position with numpy : 0.03160214424133301 nb_pixel_total : 63959 time to create 1 rle with old method : 0.07334494590759277 time for calcul the mask position with numpy : 0.029445886611938477 nb_pixel_total : 49424 time to create 1 rle with old method : 0.05533862113952637 time for calcul the mask position with numpy : 0.029138565063476562 nb_pixel_total : 18259 time to create 1 rle with old method : 0.020331859588623047 time for calcul the mask position with numpy : 0.02921581268310547 nb_pixel_total : 24601 time to create 1 rle with old method : 0.027796506881713867 time for calcul the mask position with numpy : 0.029288053512573242 nb_pixel_total : 8311 time to create 1 rle with old method : 0.009693622589111328 time for calcul the mask position with numpy : 0.02934741973876953 nb_pixel_total : 16846 time to create 1 rle with old method : 0.019065141677856445 time for calcul the mask position with numpy : 0.02944803237915039 nb_pixel_total : 47404 time to create 1 rle with old method : 0.07621026039123535 time for calcul the mask position with numpy : 0.03076457977294922 nb_pixel_total : 17855 time to create 1 rle with old method : 0.020017147064208984 time for calcul the mask position with numpy : 0.029056310653686523 nb_pixel_total : 21720 time to create 1 rle with old method : 0.024441242218017578 time for calcul the mask position with numpy : 0.02899932861328125 nb_pixel_total : 9971 time to create 1 rle with old method : 0.011244535446166992 time for calcul the mask position with numpy : 0.029262542724609375 nb_pixel_total : 14665 time to create 1 rle with old method : 0.016352176666259766 time for calcul the mask position with numpy : 0.031558990478515625 nb_pixel_total : 11243 time to create 1 rle with old method : 0.012676715850830078 time for calcul the mask position with numpy : 0.02954554557800293 nb_pixel_total : 4695 time to create 1 rle with old method : 0.006178140640258789 time for calcul the mask position with numpy : 0.03359413146972656 nb_pixel_total : 17349 time to create 1 rle with old method : 0.023064374923706055 time for calcul the mask position with numpy : 0.02967667579650879 nb_pixel_total : 9398 time to create 1 rle with old method : 0.01065206527709961 create new chi : 5.787063121795654 time to delete rle : 0.006358146667480469 batch 1 Loaded 95 chid ids of type : 3594 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 23003 TO DO : save crop sub photo not yet done ! save time : 2.2580442428588867 nb_obj : 65 nb_hashtags : 3 time to prepare the origin masks : 4.252228260040283 time for calcul the mask position with numpy : 0.9561831951141357 nb_pixel_total : 5445950 time to create 1 rle with new method : 0.9665477275848389 time for calcul the mask position with numpy : 0.029529094696044922 nb_pixel_total : 13622 time to create 1 rle with old method : 0.015211105346679688 time for calcul the mask position with numpy : 0.03176069259643555 nb_pixel_total : 11813 time to create 1 rle with old method : 0.013203144073486328 time for calcul the mask position with numpy : 0.028878450393676758 nb_pixel_total : 6631 time to create 1 rle with old method : 0.007500886917114258 time for calcul the mask position with numpy : 0.029339313507080078 nb_pixel_total : 2385 time to create 1 rle with old method : 0.0027201175689697266 time for calcul the mask position with numpy : 0.029534101486206055 nb_pixel_total : 5349 time to create 1 rle with old method : 0.006256818771362305 time for calcul the mask position with numpy : 0.029843568801879883 nb_pixel_total : 19495 time to create 1 rle with old method : 0.026056289672851562 time for calcul the mask position with numpy : 0.033455848693847656 nb_pixel_total : 5872 time to create 1 rle with old method : 0.008339881896972656 time for calcul the mask position with numpy : 0.030118942260742188 nb_pixel_total : 27173 time to create 1 rle with old method : 0.03192591667175293 time for calcul the mask position with numpy : 0.030560016632080078 nb_pixel_total : 43569 time to create 1 rle with old method : 0.04833650588989258 time for calcul the mask position with numpy : 0.029769182205200195 nb_pixel_total : 28736 time to create 1 rle with old method : 0.031914710998535156 time for calcul the mask position with numpy : 0.032945871353149414 nb_pixel_total : 30425 time to create 1 rle with old method : 0.03972649574279785 time for calcul the mask position with numpy : 0.03059864044189453 nb_pixel_total : 8241 time to create 1 rle with old method : 0.009116411209106445 time for calcul the mask position with numpy : 0.031180143356323242 nb_pixel_total : 22275 time to create 1 rle with old method : 0.024760723114013672 time for calcul the mask position with numpy : 0.02883148193359375 nb_pixel_total : 42674 time to create 1 rle with old method : 0.045896291732788086 time for calcul the mask position with numpy : 0.028656721115112305 nb_pixel_total : 18096 time to create 1 rle with old method : 0.019867420196533203 time for calcul the mask position with numpy : 0.03145551681518555 nb_pixel_total : 84978 time to create 1 rle with old method : 0.09527397155761719 time for calcul the mask position with numpy : 0.028834819793701172 nb_pixel_total : 42772 time to create 1 rle with old method : 0.0464475154876709 time for calcul the mask position with numpy : 0.028391361236572266 nb_pixel_total : 19817 time to create 1 rle with old method : 0.02214956283569336 time for calcul the mask position with numpy : 0.028401851654052734 nb_pixel_total : 49736 time to create 1 rle with old method : 0.054474830627441406 time for calcul the mask position with numpy : 0.029091835021972656 nb_pixel_total : 43292 time to create 1 rle with old method : 0.055737972259521484 time for calcul the mask position with numpy : 0.029814720153808594 nb_pixel_total : 11532 time to create 1 rle with old method : 0.012861251831054688 time for calcul the mask position with numpy : 0.0281221866607666 nb_pixel_total : 16116 time to create 1 rle with old method : 0.017422199249267578 time for calcul the mask position with numpy : 0.029233217239379883 nb_pixel_total : 27010 time to create 1 rle with old method : 0.029929161071777344 time for calcul the mask position with numpy : 0.028910160064697266 nb_pixel_total : 25786 time to create 1 rle with old method : 0.028463125228881836 time for calcul the mask position with numpy : 0.02875971794128418 nb_pixel_total : 30574 time to create 1 rle with old method : 0.03384113311767578 time for calcul the mask position with numpy : 0.029487133026123047 nb_pixel_total : 96485 time to create 1 rle with old method : 0.11250686645507812 time for calcul the mask position with numpy : 0.03301882743835449 nb_pixel_total : 23097 time to create 1 rle with old method : 0.02643728256225586 time for calcul the mask position with numpy : 0.029300212860107422 nb_pixel_total : 48974 time to create 1 rle with old method : 0.05489921569824219 time for calcul the mask position with numpy : 0.029291868209838867 nb_pixel_total : 15441 time to create 1 rle with old method : 0.01760244369506836 time for calcul the mask position with numpy : 0.03053903579711914 nb_pixel_total : 10258 time to create 1 rle with old method : 0.011699676513671875 time for calcul the mask position with numpy : 0.028756141662597656 nb_pixel_total : 21324 time to create 1 rle with old method : 0.02337932586669922 time for calcul the mask position with numpy : 0.029232501983642578 nb_pixel_total : 24022 time to create 1 rle with old method : 0.02704644203186035 time for calcul the mask position with numpy : 0.02904224395751953 nb_pixel_total : 30417 time to create 1 rle with old method : 0.03414011001586914 time for calcul the mask position with numpy : 0.028429269790649414 nb_pixel_total : 11902 time to create 1 rle with old method : 0.013283729553222656 time for calcul the mask position with numpy : 0.029636383056640625 nb_pixel_total : 87370 time to create 1 rle with old method : 0.10037994384765625 time for calcul the mask position with numpy : 0.02974390983581543 nb_pixel_total : 23716 time to create 1 rle with old method : 0.026337146759033203 time for calcul the mask position with numpy : 0.0288238525390625 nb_pixel_total : 22009 time to create 1 rle with old method : 0.02457880973815918 time for calcul the mask position with numpy : 0.030762672424316406 nb_pixel_total : 41864 time to create 1 rle with old method : 0.04716372489929199 time for calcul the mask position with numpy : 0.02896904945373535 nb_pixel_total : 16125 time to create 1 rle with old method : 0.018108606338500977 time for calcul the mask position with numpy : 0.028705596923828125 nb_pixel_total : 597 time to create 1 rle with old method : 0.0008363723754882812 time for calcul the mask position with numpy : 0.028897762298583984 nb_pixel_total : 4813 time to create 1 rle with old method : 0.005499601364135742 time for calcul the mask position with numpy : 0.029166698455810547 nb_pixel_total : 42490 time to create 1 rle with old method : 0.04890775680541992 time for calcul the mask position with numpy : 0.029033899307250977 nb_pixel_total : 8844 time to create 1 rle with old method : 0.009983539581298828 time for calcul the mask position with numpy : 0.029129743576049805 nb_pixel_total : 5484 time to create 1 rle with old method : 0.006163358688354492 time for calcul the mask position with numpy : 0.03283810615539551 nb_pixel_total : 19919 time to create 1 rle with old method : 0.022342205047607422 time for calcul the mask position with numpy : 0.029047727584838867 nb_pixel_total : 1075 time to create 1 rle with old method : 0.0013508796691894531 time for calcul the mask position with numpy : 0.0291898250579834 nb_pixel_total : 23111 time to create 1 rle with old method : 0.025872468948364258 time for calcul the mask position with numpy : 0.0291140079498291 nb_pixel_total : 15112 time to create 1 rle with old method : 0.017060518264770508 time for calcul the mask position with numpy : 0.029317617416381836 nb_pixel_total : 43699 time to create 1 rle with old method : 0.048506736755371094 time for calcul the mask position with numpy : 0.02970290184020996 nb_pixel_total : 70246 time to create 1 rle with old method : 0.07889628410339355 time for calcul the mask position with numpy : 0.029027700424194336 nb_pixel_total : 46474 time to create 1 rle with old method : 0.051871299743652344 time for calcul the mask position with numpy : 0.029556751251220703 nb_pixel_total : 46442 time to create 1 rle with old method : 0.057189226150512695 time for calcul the mask position with numpy : 0.029422521591186523 nb_pixel_total : 12480 time to create 1 rle with old method : 0.015035152435302734 time for calcul the mask position with numpy : 0.02937030792236328 nb_pixel_total : 25182 time to create 1 rle with old method : 0.02859663963317871 time for calcul the mask position with numpy : 0.029299497604370117 nb_pixel_total : 8650 time to create 1 rle with old method : 0.00990748405456543 time for calcul the mask position with numpy : 0.029161930084228516 nb_pixel_total : 8496 time to create 1 rle with old method : 0.00976872444152832 time for calcul the mask position with numpy : 0.030853271484375 nb_pixel_total : 8627 time to create 1 rle with old method : 0.010393619537353516 time for calcul the mask position with numpy : 0.029198884963989258 nb_pixel_total : 11775 time to create 1 rle with old method : 0.013738155364990234 time for calcul the mask position with numpy : 0.029066085815429688 nb_pixel_total : 21181 time to create 1 rle with old method : 0.025153398513793945 time for calcul the mask position with numpy : 0.03313779830932617 nb_pixel_total : 8380 time to create 1 rle with old method : 0.013631105422973633 time for calcul the mask position with numpy : 0.03333139419555664 nb_pixel_total : 12823 time to create 1 rle with old method : 0.014480352401733398 time for calcul the mask position with numpy : 0.03168010711669922 nb_pixel_total : 6841 time to create 1 rle with old method : 0.009308815002441406 time for calcul the mask position with numpy : 0.030646085739135742 nb_pixel_total : 25438 time to create 1 rle with old method : 0.028644561767578125 time for calcul the mask position with numpy : 0.028867483139038086 nb_pixel_total : 8424 time to create 1 rle with old method : 0.00964975357055664 time for calcul the mask position with numpy : 0.02841973304748535 nb_pixel_total : 6714 time to create 1 rle with old method : 0.0072784423828125 create new chi : 5.732922077178955 time to delete rle : 0.005972623825073242 batch 1 Loaded 132 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 27983 TO DO : save crop sub photo not yet done ! save time : 1.7581243515014648 nb_obj : 60 nb_hashtags : 5 time to prepare the origin masks : 4.102796316146851 time for calcul the mask position with numpy : 0.7540144920349121 nb_pixel_total : 5568735 time to create 1 rle with new method : 0.6415178775787354 time for calcul the mask position with numpy : 0.029420137405395508 nb_pixel_total : 26974 time to create 1 rle with old method : 0.03135395050048828 time for calcul the mask position with numpy : 0.029594898223876953 nb_pixel_total : 16884 time to create 1 rle with old method : 0.019140005111694336 time for calcul the mask position with numpy : 0.028996944427490234 nb_pixel_total : 24079 time to create 1 rle with old method : 0.0271146297454834 time for calcul the mask position with numpy : 0.029142141342163086 nb_pixel_total : 24608 time to create 1 rle with old method : 0.027943134307861328 time for calcul the mask position with numpy : 0.02892136573791504 nb_pixel_total : 10875 time to create 1 rle with old method : 0.01238703727722168 time for calcul the mask position with numpy : 0.028935670852661133 nb_pixel_total : 7798 time to create 1 rle with old method : 0.00893402099609375 time for calcul the mask position with numpy : 0.029438018798828125 nb_pixel_total : 45790 time to create 1 rle with old method : 0.051489830017089844 time for calcul the mask position with numpy : 0.028950929641723633 nb_pixel_total : 15756 time to create 1 rle with old method : 0.017614126205444336 time for calcul the mask position with numpy : 0.029196739196777344 nb_pixel_total : 12090 time to create 1 rle with old method : 0.013686180114746094 time for calcul the mask position with numpy : 0.029207944869995117 nb_pixel_total : 29858 time to create 1 rle with old method : 0.03358793258666992 time for calcul the mask position with numpy : 0.028866052627563477 nb_pixel_total : 20335 time to create 1 rle with old method : 0.02545642852783203 time for calcul the mask position with numpy : 0.030642032623291016 nb_pixel_total : 63145 time to create 1 rle with old method : 0.07391643524169922 time for calcul the mask position with numpy : 0.029864788055419922 nb_pixel_total : 24506 time to create 1 rle with old method : 0.02836155891418457 time for calcul the mask position with numpy : 0.03831934928894043 nb_pixel_total : 17171 time to create 1 rle with old method : 0.01908707618713379 time for calcul the mask position with numpy : 0.02902674674987793 nb_pixel_total : 21718 time to create 1 rle with old method : 0.025602102279663086 time for calcul the mask position with numpy : 0.02979564666748047 nb_pixel_total : 16103 time to create 1 rle with old method : 0.020319461822509766 time for calcul the mask position with numpy : 0.030589580535888672 nb_pixel_total : 15080 time to create 1 rle with old method : 0.018880367279052734 time for calcul the mask position with numpy : 0.02932286262512207 nb_pixel_total : 47053 time to create 1 rle with old method : 0.052995920181274414 time for calcul the mask position with numpy : 0.030881643295288086 nb_pixel_total : 13066 time to create 1 rle with old method : 0.019576072692871094 time for calcul the mask position with numpy : 0.029873371124267578 nb_pixel_total : 20017 time to create 1 rle with old method : 0.023331880569458008 time for calcul the mask position with numpy : 0.029436111450195312 nb_pixel_total : 40523 time to create 1 rle with old method : 0.051419973373413086 time for calcul the mask position with numpy : 0.030512332916259766 nb_pixel_total : 17877 time to create 1 rle with old method : 0.02179241180419922 time for calcul the mask position with numpy : 0.02903008460998535 nb_pixel_total : 15917 time to create 1 rle with old method : 0.019374847412109375 time for calcul the mask position with numpy : 0.02941727638244629 nb_pixel_total : 12654 time to create 1 rle with old method : 0.014453887939453125 time for calcul the mask position with numpy : 0.029110431671142578 nb_pixel_total : 57282 time to create 1 rle with old method : 0.06397891044616699 time for calcul the mask position with numpy : 0.02909708023071289 nb_pixel_total : 46826 time to create 1 rle with old method : 0.05221295356750488 time for calcul the mask position with numpy : 0.028992652893066406 nb_pixel_total : 23321 time to create 1 rle with old method : 0.026630163192749023 time for calcul the mask position with numpy : 0.029193878173828125 nb_pixel_total : 29847 time to create 1 rle with old method : 0.03335118293762207 time for calcul the mask position with numpy : 0.028734445571899414 nb_pixel_total : 15878 time to create 1 rle with old method : 0.018028974533081055 time for calcul the mask position with numpy : 0.028864383697509766 nb_pixel_total : 20341 time to create 1 rle with old method : 0.025658845901489258 time for calcul the mask position with numpy : 0.030500173568725586 nb_pixel_total : 29761 time to create 1 rle with old method : 0.03419637680053711 time for calcul the mask position with numpy : 0.028843402862548828 nb_pixel_total : 44052 time to create 1 rle with old method : 0.0495905876159668 time for calcul the mask position with numpy : 0.02896428108215332 nb_pixel_total : 30915 time to create 1 rle with old method : 0.036940813064575195 time for calcul the mask position with numpy : 0.02915191650390625 nb_pixel_total : 16978 time to create 1 rle with old method : 0.019120454788208008 time for calcul the mask position with numpy : 0.030120372772216797 nb_pixel_total : 34912 time to create 1 rle with old method : 0.042079925537109375 time for calcul the mask position with numpy : 0.02987074851989746 nb_pixel_total : 15516 time to create 1 rle with old method : 0.018369674682617188 time for calcul the mask position with numpy : 0.03162884712219238 nb_pixel_total : 23083 time to create 1 rle with old method : 0.026053190231323242 time for calcul the mask position with numpy : 0.029474735260009766 nb_pixel_total : 29670 time to create 1 rle with old method : 0.034978628158569336 time for calcul the mask position with numpy : 0.0299224853515625 nb_pixel_total : 31895 time to create 1 rle with old method : 0.038010597229003906 time for calcul the mask position with numpy : 0.030257463455200195 nb_pixel_total : 23831 time to create 1 rle with old method : 0.029105186462402344 time for calcul the mask position with numpy : 0.03012561798095703 nb_pixel_total : 30980 time to create 1 rle with old method : 0.03704023361206055 time for calcul the mask position with numpy : 0.030073881149291992 nb_pixel_total : 45685 time to create 1 rle with old method : 0.0574498176574707 time for calcul the mask position with numpy : 0.05579423904418945 nb_pixel_total : 10095 time to create 1 rle with old method : 0.012509584426879883 time for calcul the mask position with numpy : 0.03092646598815918 nb_pixel_total : 7521 time to create 1 rle with old method : 0.00994110107421875 time for calcul the mask position with numpy : 0.030147790908813477 nb_pixel_total : 21255 time to create 1 rle with old method : 0.025094985961914062 time for calcul the mask position with numpy : 0.0306856632232666 nb_pixel_total : 87840 time to create 1 rle with old method : 0.09822392463684082 time for calcul the mask position with numpy : 0.02901005744934082 nb_pixel_total : 790 time to create 1 rle with old method : 0.0010547637939453125 time for calcul the mask position with numpy : 0.02893519401550293 nb_pixel_total : 5832 time to create 1 rle with old method : 0.006638288497924805 time for calcul the mask position with numpy : 0.028974294662475586 nb_pixel_total : 5239 time to create 1 rle with old method : 0.005980253219604492 time for calcul the mask position with numpy : 0.028992652893066406 nb_pixel_total : 14031 time to create 1 rle with old method : 0.01688861846923828 time for calcul the mask position with numpy : 0.0296630859375 nb_pixel_total : 56586 time to create 1 rle with old method : 0.06331729888916016 time for calcul the mask position with numpy : 0.029251813888549805 nb_pixel_total : 24848 time to create 1 rle with old method : 0.027851343154907227 time for calcul the mask position with numpy : 0.029506683349609375 nb_pixel_total : 27501 time to create 1 rle with old method : 0.030886173248291016 time for calcul the mask position with numpy : 0.029317378997802734 nb_pixel_total : 37732 time to create 1 rle with old method : 0.04226398468017578 time for calcul the mask position with numpy : 0.02900862693786621 nb_pixel_total : 18416 time to create 1 rle with old method : 0.020638227462768555 time for calcul the mask position with numpy : 0.030277490615844727 nb_pixel_total : 12363 time to create 1 rle with old method : 0.014736652374267578 time for calcul the mask position with numpy : 0.03188920021057129 nb_pixel_total : 13608 time to create 1 rle with old method : 0.01565241813659668 time for calcul the mask position with numpy : 0.030082225799560547 nb_pixel_total : 8674 time to create 1 rle with old method : 0.00970315933227539 time for calcul the mask position with numpy : 0.02915334701538086 nb_pixel_total : 13311 time to create 1 rle with old method : 0.01491236686706543 time for calcul the mask position with numpy : 0.028537988662719727 nb_pixel_total : 5213 time to create 1 rle with old method : 0.0063250064849853516 create new chi : 4.969475030899048 time to delete rle : 0.0036118030548095703 batch 1 Loaded 121 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 25025 TO DO : save crop sub photo not yet done ! save time : 1.5936360359191895 nb_obj : 35 nb_hashtags : 6 time to prepare the origin masks : 4.5541253089904785 time for calcul the mask position with numpy : 0.8736047744750977 nb_pixel_total : 5191753 time to create 1 rle with new method : 0.7674179077148438 time for calcul the mask position with numpy : 0.02776336669921875 nb_pixel_total : 14320 time to create 1 rle with old method : 0.015617847442626953 time for calcul the mask position with numpy : 0.029323816299438477 nb_pixel_total : 149053 time to create 1 rle with old method : 0.1628267765045166 time for calcul the mask position with numpy : 0.029537677764892578 nb_pixel_total : 46182 time to create 1 rle with old method : 0.05125761032104492 time for calcul the mask position with numpy : 0.02858734130859375 nb_pixel_total : 14472 time to create 1 rle with old method : 0.01571965217590332 time for calcul the mask position with numpy : 0.029117107391357422 nb_pixel_total : 97083 time to create 1 rle with old method : 0.10525321960449219 time for calcul the mask position with numpy : 0.03326749801635742 nb_pixel_total : 40200 time to create 1 rle with old method : 0.062445640563964844 time for calcul the mask position with numpy : 0.030739307403564453 nb_pixel_total : 18191 time to create 1 rle with old method : 0.020704984664916992 time for calcul the mask position with numpy : 0.030500411987304688 nb_pixel_total : 92842 time to create 1 rle with old method : 0.13751816749572754 time for calcul the mask position with numpy : 0.06011009216308594 nb_pixel_total : 241665 time to create 1 rle with new method : 1.044346570968628 time for calcul the mask position with numpy : 0.029138803482055664 nb_pixel_total : 13827 time to create 1 rle with old method : 0.015442132949829102 time for calcul the mask position with numpy : 0.02986001968383789 nb_pixel_total : 50094 time to create 1 rle with old method : 0.05724358558654785 time for calcul the mask position with numpy : 0.02863597869873047 nb_pixel_total : 40546 time to create 1 rle with old method : 0.04496932029724121 time for calcul the mask position with numpy : 0.02812480926513672 nb_pixel_total : 16785 time to create 1 rle with old method : 0.01838064193725586 time for calcul the mask position with numpy : 0.02862834930419922 nb_pixel_total : 80145 time to create 1 rle with old method : 0.08807635307312012 time for calcul the mask position with numpy : 0.032587528228759766 nb_pixel_total : 312 time to create 1 rle with old method : 0.0006709098815917969 time for calcul the mask position with numpy : 0.02959609031677246 nb_pixel_total : 86353 time to create 1 rle with old method : 0.09884476661682129 time for calcul the mask position with numpy : 0.04260396957397461 nb_pixel_total : 224537 time to create 1 rle with new method : 0.7089998722076416 time for calcul the mask position with numpy : 0.028522014617919922 nb_pixel_total : 36298 time to create 1 rle with old method : 0.039279937744140625 time for calcul the mask position with numpy : 0.029222488403320312 nb_pixel_total : 30309 time to create 1 rle with old method : 0.03442788124084473 time for calcul the mask position with numpy : 0.0314335823059082 nb_pixel_total : 106965 time to create 1 rle with old method : 0.13663721084594727 time for calcul the mask position with numpy : 0.027873992919921875 nb_pixel_total : 20987 time to create 1 rle with old method : 0.0225369930267334 time for calcul the mask position with numpy : 0.02710747718811035 nb_pixel_total : 58118 time to create 1 rle with old method : 0.05988645553588867 time for calcul the mask position with numpy : 0.02686142921447754 nb_pixel_total : 3681 time to create 1 rle with old method : 0.004134178161621094 time for calcul the mask position with numpy : 0.027825117111206055 nb_pixel_total : 46658 time to create 1 rle with old method : 0.04986071586608887 time for calcul the mask position with numpy : 0.02780437469482422 nb_pixel_total : 20271 time to create 1 rle with old method : 0.02169966697692871 time for calcul the mask position with numpy : 0.02774500846862793 nb_pixel_total : 35767 time to create 1 rle with old method : 0.03772711753845215 time for calcul the mask position with numpy : 0.02767038345336914 nb_pixel_total : 142453 time to create 1 rle with old method : 0.1510467529296875 time for calcul the mask position with numpy : 0.02705073356628418 nb_pixel_total : 17497 time to create 1 rle with old method : 0.017714500427246094 time for calcul the mask position with numpy : 0.02807450294494629 nb_pixel_total : 25194 time to create 1 rle with old method : 0.028172969818115234 time for calcul the mask position with numpy : 0.029474496841430664 nb_pixel_total : 8049 time to create 1 rle with old method : 0.009077310562133789 time for calcul the mask position with numpy : 0.029340505599975586 nb_pixel_total : 33526 time to create 1 rle with old method : 0.037627220153808594 time for calcul the mask position with numpy : 0.02882838249206543 nb_pixel_total : 5965 time to create 1 rle with old method : 0.006657123565673828 time for calcul the mask position with numpy : 0.02882099151611328 nb_pixel_total : 10411 time to create 1 rle with old method : 0.011572837829589844 time for calcul the mask position with numpy : 0.029106855392456055 nb_pixel_total : 17170 time to create 1 rle with old method : 0.01835179328918457 time for calcul the mask position with numpy : 0.027866125106811523 nb_pixel_total : 12561 time to create 1 rle with old method : 0.013901472091674805 create new chi : 6.13020658493042 time to delete rle : 0.00457453727722168 batch 1 Loaded 72 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 22276 TO DO : save crop sub photo not yet done ! save time : 1.4529364109039307 nb_obj : 43 nb_hashtags : 3 time to prepare the origin masks : 5.496492624282837 time for calcul the mask position with numpy : 0.19782257080078125 nb_pixel_total : 4511709 time to create 1 rle with new method : 0.6834473609924316 time for calcul the mask position with numpy : 0.029846906661987305 nb_pixel_total : 352745 time to create 1 rle with new method : 0.697232723236084 time for calcul the mask position with numpy : 0.02904653549194336 nb_pixel_total : 155750 time to create 1 rle with new method : 0.2979469299316406 time for calcul the mask position with numpy : 0.029292821884155273 nb_pixel_total : 42906 time to create 1 rle with old method : 0.057018280029296875 time for calcul the mask position with numpy : 0.03084087371826172 nb_pixel_total : 32941 time to create 1 rle with old method : 0.036968231201171875 time for calcul the mask position with numpy : 0.02953052520751953 nb_pixel_total : 59151 time to create 1 rle with old method : 0.06791019439697266 time for calcul the mask position with numpy : 0.029076099395751953 nb_pixel_total : 25065 time to create 1 rle with old method : 0.027456045150756836 time for calcul the mask position with numpy : 0.03174090385437012 nb_pixel_total : 68574 time to create 1 rle with old method : 0.08349967002868652 time for calcul the mask position with numpy : 0.031236648559570312 nb_pixel_total : 58411 time to create 1 rle with old method : 0.07166075706481934 time for calcul the mask position with numpy : 0.03102588653564453 nb_pixel_total : 47881 time to create 1 rle with old method : 0.060834646224975586 time for calcul the mask position with numpy : 0.029837608337402344 nb_pixel_total : 17611 time to create 1 rle with old method : 0.020899295806884766 time for calcul the mask position with numpy : 0.03535890579223633 nb_pixel_total : 50149 time to create 1 rle with old method : 0.05481290817260742 time for calcul the mask position with numpy : 0.02870345115661621 nb_pixel_total : 27903 time to create 1 rle with old method : 0.030497074127197266 time for calcul the mask position with numpy : 0.030293703079223633 nb_pixel_total : 61650 time to create 1 rle with old method : 0.06681275367736816 time for calcul the mask position with numpy : 0.02757120132446289 nb_pixel_total : 11680 time to create 1 rle with old method : 0.012808084487915039 time for calcul the mask position with numpy : 0.02798295021057129 nb_pixel_total : 90495 time to create 1 rle with old method : 0.09452295303344727 time for calcul the mask position with numpy : 0.02835822105407715 nb_pixel_total : 24365 time to create 1 rle with old method : 0.02643752098083496 time for calcul the mask position with numpy : 0.02755570411682129 nb_pixel_total : 30344 time to create 1 rle with old method : 0.03232002258300781 time for calcul the mask position with numpy : 0.026995182037353516 nb_pixel_total : 63502 time to create 1 rle with old method : 0.06615567207336426 time for calcul the mask position with numpy : 0.02727961540222168 nb_pixel_total : 145745 time to create 1 rle with old method : 0.15607666969299316 time for calcul the mask position with numpy : 0.027396440505981445 nb_pixel_total : 58680 time to create 1 rle with old method : 0.06396031379699707 time for calcul the mask position with numpy : 0.028359651565551758 nb_pixel_total : 45021 time to create 1 rle with old method : 0.04830789566040039 time for calcul the mask position with numpy : 0.027462005615234375 nb_pixel_total : 37081 time to create 1 rle with old method : 0.03989815711975098 time for calcul the mask position with numpy : 0.028326034545898438 nb_pixel_total : 106067 time to create 1 rle with old method : 0.11844229698181152 time for calcul the mask position with numpy : 0.02739858627319336 nb_pixel_total : 2226 time to create 1 rle with old method : 0.0031571388244628906 time for calcul the mask position with numpy : 0.028906583786010742 nb_pixel_total : 303220 time to create 1 rle with new method : 0.5612220764160156 time for calcul the mask position with numpy : 0.027217388153076172 nb_pixel_total : 185274 time to create 1 rle with new method : 0.41073036193847656 time for calcul the mask position with numpy : 0.029246091842651367 nb_pixel_total : 121571 time to create 1 rle with old method : 0.1352241039276123 time for calcul the mask position with numpy : 0.03040790557861328 nb_pixel_total : 2034 time to create 1 rle with old method : 0.0025882720947265625 time for calcul the mask position with numpy : 0.029040813446044922 nb_pixel_total : 95322 time to create 1 rle with old method : 0.10574126243591309 time for calcul the mask position with numpy : 0.032860517501831055 nb_pixel_total : 443 time to create 1 rle with old method : 0.0011131763458251953 time for calcul the mask position with numpy : 0.032941579818725586 nb_pixel_total : 32393 time to create 1 rle with old method : 0.03684830665588379 time for calcul the mask position with numpy : 0.028306961059570312 nb_pixel_total : 31273 time to create 1 rle with old method : 0.03441882133483887 time for calcul the mask position with numpy : 0.0285642147064209 nb_pixel_total : 19511 time to create 1 rle with old method : 0.021651506423950195 time for calcul the mask position with numpy : 0.028859376907348633 nb_pixel_total : 41600 time to create 1 rle with old method : 0.0454707145690918 time for calcul the mask position with numpy : 0.03469252586364746 nb_pixel_total : 12532 time to create 1 rle with old method : 0.01896834373474121 time for calcul the mask position with numpy : 0.028959274291992188 nb_pixel_total : 8415 time to create 1 rle with old method : 0.009460687637329102 time for calcul the mask position with numpy : 0.028168678283691406 nb_pixel_total : 2505 time to create 1 rle with old method : 0.0027751922607421875 time for calcul the mask position with numpy : 0.027927160263061523 nb_pixel_total : 1237 time to create 1 rle with old method : 0.0014805793762207031 time for calcul the mask position with numpy : 0.02844977378845215 nb_pixel_total : 1658 time to create 1 rle with old method : 0.001874685287475586 time for calcul the mask position with numpy : 0.028468847274780273 nb_pixel_total : 2814 time to create 1 rle with old method : 0.0032300949096679688 time for calcul the mask position with numpy : 0.028831958770751953 nb_pixel_total : 15451 time to create 1 rle with old method : 0.017371654510498047 time for calcul the mask position with numpy : 0.02889275550842285 nb_pixel_total : 32410 time to create 1 rle with old method : 0.046518564224243164 time for calcul the mask position with numpy : 0.03298592567443848 nb_pixel_total : 12925 time to create 1 rle with old method : 0.020303726196289062 create new chi : 5.985581398010254 time to delete rle : 0.004339694976806641 batch 1 Loaded 94 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 28869 TO DO : save crop sub photo not yet done ! save time : 4.076925277709961 nb_obj : 48 nb_hashtags : 4 time to prepare the origin masks : 5.7284533977508545 time for calcul the mask position with numpy : 0.839674711227417 nb_pixel_total : 5440303 time to create 1 rle with new method : 0.6883480548858643 time for calcul the mask position with numpy : 0.029062271118164062 nb_pixel_total : 26632 time to create 1 rle with old method : 0.029674291610717773 time for calcul the mask position with numpy : 0.02956390380859375 nb_pixel_total : 10392 time to create 1 rle with old method : 0.011514425277709961 time for calcul the mask position with numpy : 0.02953505516052246 nb_pixel_total : 56022 time to create 1 rle with old method : 0.06520366668701172 time for calcul the mask position with numpy : 0.03412961959838867 nb_pixel_total : 69402 time to create 1 rle with old method : 0.09195995330810547 time for calcul the mask position with numpy : 0.029766082763671875 nb_pixel_total : 24791 time to create 1 rle with old method : 0.02931833267211914 time for calcul the mask position with numpy : 0.0296323299407959 nb_pixel_total : 15076 time to create 1 rle with old method : 0.025367259979248047 time for calcul the mask position with numpy : 0.033133745193481445 nb_pixel_total : 4094 time to create 1 rle with old method : 0.00684809684753418 time for calcul the mask position with numpy : 0.03113412857055664 nb_pixel_total : 18010 time to create 1 rle with old method : 0.021148204803466797 time for calcul the mask position with numpy : 0.0299990177154541 nb_pixel_total : 48741 time to create 1 rle with old method : 0.06225776672363281 time for calcul the mask position with numpy : 0.03009796142578125 nb_pixel_total : 673 time to create 1 rle with old method : 0.0009541511535644531 time for calcul the mask position with numpy : 0.02958989143371582 nb_pixel_total : 19140 time to create 1 rle with old method : 0.022464990615844727 time for calcul the mask position with numpy : 0.030480623245239258 nb_pixel_total : 10213 time to create 1 rle with old method : 0.011984825134277344 time for calcul the mask position with numpy : 0.030537843704223633 nb_pixel_total : 35506 time to create 1 rle with old method : 0.048833608627319336 time for calcul the mask position with numpy : 0.03322005271911621 nb_pixel_total : 11724 time to create 1 rle with old method : 0.019774913787841797 time for calcul the mask position with numpy : 0.029407501220703125 nb_pixel_total : 29168 time to create 1 rle with old method : 0.03743338584899902 time for calcul the mask position with numpy : 0.03641247749328613 nb_pixel_total : 224578 time to create 1 rle with new method : 0.5901718139648438 time for calcul the mask position with numpy : 0.029268264770507812 nb_pixel_total : 12602 time to create 1 rle with old method : 0.014150857925415039 time for calcul the mask position with numpy : 0.029306888580322266 nb_pixel_total : 53256 time to create 1 rle with old method : 0.06841826438903809 time for calcul the mask position with numpy : 0.030185222625732422 nb_pixel_total : 28211 time to create 1 rle with old method : 0.03198814392089844 time for calcul the mask position with numpy : 0.029308319091796875 nb_pixel_total : 17065 time to create 1 rle with old method : 0.01933741569519043 time for calcul the mask position with numpy : 0.02909231185913086 nb_pixel_total : 11326 time to create 1 rle with old method : 0.012720346450805664 time for calcul the mask position with numpy : 0.029198169708251953 nb_pixel_total : 39 time to create 1 rle with old method : 0.00011992454528808594 time for calcul the mask position with numpy : 0.02924346923828125 nb_pixel_total : 29959 time to create 1 rle with old method : 0.034423112869262695 time for calcul the mask position with numpy : 0.029198408126831055 nb_pixel_total : 25178 time to create 1 rle with old method : 0.028463363647460938 time for calcul the mask position with numpy : 0.029050588607788086 nb_pixel_total : 939 time to create 1 rle with old method : 0.001270294189453125 time for calcul the mask position with numpy : 0.02897024154663086 nb_pixel_total : 22699 time to create 1 rle with old method : 0.02521991729736328 time for calcul the mask position with numpy : 0.02898120880126953 nb_pixel_total : 10429 time to create 1 rle with old method : 0.011891841888427734 time for calcul the mask position with numpy : 0.02942371368408203 nb_pixel_total : 88307 time to create 1 rle with old method : 0.09952235221862793 time for calcul the mask position with numpy : 0.028891563415527344 nb_pixel_total : 79513 time to create 1 rle with old method : 0.08870244026184082 time for calcul the mask position with numpy : 0.02942633628845215 nb_pixel_total : 98977 time to create 1 rle with old method : 0.11039519309997559 time for calcul the mask position with numpy : 0.027819395065307617 nb_pixel_total : 2037 time to create 1 rle with old method : 0.002361297607421875 time for calcul the mask position with numpy : 0.027077436447143555 nb_pixel_total : 43119 time to create 1 rle with old method : 0.04821157455444336 time for calcul the mask position with numpy : 0.029120206832885742 nb_pixel_total : 56901 time to create 1 rle with old method : 0.06302165985107422 time for calcul the mask position with numpy : 0.029044628143310547 nb_pixel_total : 18767 time to create 1 rle with old method : 0.019864320755004883 time for calcul the mask position with numpy : 0.027773380279541016 nb_pixel_total : 25559 time to create 1 rle with old method : 0.026816368103027344 time for calcul the mask position with numpy : 0.027983665466308594 nb_pixel_total : 523 time to create 1 rle with old method : 0.0008378028869628906 time for calcul the mask position with numpy : 0.029323816299438477 nb_pixel_total : 116759 time to create 1 rle with old method : 0.1391315460205078 time for calcul the mask position with numpy : 0.028817176818847656 nb_pixel_total : 60898 time to create 1 rle with old method : 0.0677947998046875 time for calcul the mask position with numpy : 0.02870035171508789 nb_pixel_total : 8793 time to create 1 rle with old method : 0.010270833969116211 time for calcul the mask position with numpy : 0.028990507125854492 nb_pixel_total : 11002 time to create 1 rle with old method : 0.012274980545043945 time for calcul the mask position with numpy : 0.0292208194732666 nb_pixel_total : 74847 time to create 1 rle with old method : 0.08249211311340332 time for calcul the mask position with numpy : 0.02843952178955078 nb_pixel_total : 814 time to create 1 rle with old method : 0.0013751983642578125 time for calcul the mask position with numpy : 0.028609514236450195 nb_pixel_total : 10713 time to create 1 rle with old method : 0.012356758117675781 time for calcul the mask position with numpy : 0.02881169319152832 nb_pixel_total : 10923 time to create 1 rle with old method : 0.012082815170288086 time for calcul the mask position with numpy : 0.029031038284301758 nb_pixel_total : 65138 time to create 1 rle with old method : 0.07198810577392578 time for calcul the mask position with numpy : 0.02924966812133789 nb_pixel_total : 299 time to create 1 rle with old method : 0.0006883144378662109 time for calcul the mask position with numpy : 0.029312610626220703 nb_pixel_total : 5958 time to create 1 rle with old method : 0.0067746639251708984 time for calcul the mask position with numpy : 0.02930736541748047 nb_pixel_total : 14225 time to create 1 rle with old method : 0.01603102684020996 create new chi : 5.227303504943848 time to delete rle : 0.005327463150024414 batch 1 Loaded 102 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 24704 TO DO : save crop sub photo not yet done ! save time : 2.43902850151062 nb_obj : 38 nb_hashtags : 4 time to prepare the origin masks : 4.6463847160339355 time for calcul the mask position with numpy : 0.6516261100769043 nb_pixel_total : 5971385 time to create 1 rle with new method : 0.9272360801696777 time for calcul the mask position with numpy : 0.02983379364013672 nb_pixel_total : 8057 time to create 1 rle with old method : 0.011693954467773438 time for calcul the mask position with numpy : 0.031050443649291992 nb_pixel_total : 7545 time to create 1 rle with old method : 0.008687019348144531 time for calcul the mask position with numpy : 0.030142784118652344 nb_pixel_total : 7326 time to create 1 rle with old method : 0.00849461555480957 time for calcul the mask position with numpy : 0.03165555000305176 nb_pixel_total : 28844 time to create 1 rle with old method : 0.033675193786621094 time for calcul the mask position with numpy : 0.029227256774902344 nb_pixel_total : 18193 time to create 1 rle with old method : 0.02155017852783203 time for calcul the mask position with numpy : 0.029974937438964844 nb_pixel_total : 8636 time to create 1 rle with old method : 0.010593891143798828 time for calcul the mask position with numpy : 0.031210660934448242 nb_pixel_total : 236664 time to create 1 rle with new method : 0.5731570720672607 time for calcul the mask position with numpy : 0.028495073318481445 nb_pixel_total : 2682 time to create 1 rle with old method : 0.002986907958984375 time for calcul the mask position with numpy : 0.028259754180908203 nb_pixel_total : 24236 time to create 1 rle with old method : 0.026282310485839844 time for calcul the mask position with numpy : 0.029444217681884766 nb_pixel_total : 7973 time to create 1 rle with old method : 0.009032011032104492 time for calcul the mask position with numpy : 0.028355836868286133 nb_pixel_total : 10601 time to create 1 rle with old method : 0.011802434921264648 time for calcul the mask position with numpy : 0.028685569763183594 nb_pixel_total : 60556 time to create 1 rle with old method : 0.06600809097290039 time for calcul the mask position with numpy : 0.02957296371459961 nb_pixel_total : 83031 time to create 1 rle with old method : 0.10912537574768066 time for calcul the mask position with numpy : 0.03326916694641113 nb_pixel_total : 16744 time to create 1 rle with old method : 0.018997907638549805 time for calcul the mask position with numpy : 0.029366731643676758 nb_pixel_total : 23119 time to create 1 rle with old method : 0.026017189025878906 time for calcul the mask position with numpy : 0.028705596923828125 nb_pixel_total : 49044 time to create 1 rle with old method : 0.05427980422973633 time for calcul the mask position with numpy : 0.029131174087524414 nb_pixel_total : 48281 time to create 1 rle with old method : 0.054688215255737305 time for calcul the mask position with numpy : 0.029162883758544922 nb_pixel_total : 10071 time to create 1 rle with old method : 0.012294530868530273 time for calcul the mask position with numpy : 0.0299074649810791 nb_pixel_total : 30048 time to create 1 rle with old method : 0.035643577575683594 time for calcul the mask position with numpy : 0.02927374839782715 nb_pixel_total : 202 time to create 1 rle with old method : 0.00038695335388183594 time for calcul the mask position with numpy : 0.03056502342224121 nb_pixel_total : 17192 time to create 1 rle with old method : 0.02338099479675293 time for calcul the mask position with numpy : 0.030411720275878906 nb_pixel_total : 14879 time to create 1 rle with old method : 0.016672134399414062 time for calcul the mask position with numpy : 0.029097795486450195 nb_pixel_total : 12020 time to create 1 rle with old method : 0.013758182525634766 time for calcul the mask position with numpy : 0.029324054718017578 nb_pixel_total : 7569 time to create 1 rle with old method : 0.009173393249511719 time for calcul the mask position with numpy : 0.03066396713256836 nb_pixel_total : 21143 time to create 1 rle with old method : 0.026855945587158203 time for calcul the mask position with numpy : 0.031122684478759766 nb_pixel_total : 33725 time to create 1 rle with old method : 0.037026166915893555 time for calcul the mask position with numpy : 0.03044748306274414 nb_pixel_total : 17215 time to create 1 rle with old method : 0.02039504051208496 time for calcul the mask position with numpy : 0.029498815536499023 nb_pixel_total : 32140 time to create 1 rle with old method : 0.03726935386657715 time for calcul the mask position with numpy : 0.030223846435546875 nb_pixel_total : 14690 time to create 1 rle with old method : 0.01623392105102539 time for calcul the mask position with numpy : 0.029413938522338867 nb_pixel_total : 2492 time to create 1 rle with old method : 0.0029878616333007812 time for calcul the mask position with numpy : 0.030307769775390625 nb_pixel_total : 16759 time to create 1 rle with old method : 0.018061161041259766 time for calcul the mask position with numpy : 0.029499053955078125 nb_pixel_total : 18452 time to create 1 rle with old method : 0.020224571228027344 time for calcul the mask position with numpy : 0.02997279167175293 nb_pixel_total : 12032 time to create 1 rle with old method : 0.013209342956542969 time for calcul the mask position with numpy : 0.03250718116760254 nb_pixel_total : 107176 time to create 1 rle with old method : 0.12053680419921875 time for calcul the mask position with numpy : 0.02938985824584961 nb_pixel_total : 23440 time to create 1 rle with old method : 0.026185989379882812 time for calcul the mask position with numpy : 0.0296170711517334 nb_pixel_total : 23169 time to create 1 rle with old method : 0.026210784912109375 time for calcul the mask position with numpy : 0.029572248458862305 nb_pixel_total : 11055 time to create 1 rle with old method : 0.012737751007080078 time for calcul the mask position with numpy : 0.031055688858032227 nb_pixel_total : 11854 time to create 1 rle with old method : 0.013628959655761719 create new chi : 4.334729433059692 time to delete rle : 0.002790689468383789 batch 1 Loaded 78 chid ids of type : 3594 ++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 16730 TO DO : save crop sub photo not yet done ! save time : 1.2935376167297363 nb_obj : 28 nb_hashtags : 4 time to prepare the origin masks : 3.7145771980285645 time for calcul the mask position with numpy : 1.1101305484771729 nb_pixel_total : 6203708 time to create 1 rle with new method : 1.5336518287658691 time for calcul the mask position with numpy : 0.029097795486450195 nb_pixel_total : 29089 time to create 1 rle with old method : 0.04793047904968262 time for calcul the mask position with numpy : 0.0315093994140625 nb_pixel_total : 42700 time to create 1 rle with old method : 0.047174930572509766 time for calcul the mask position with numpy : 0.02844977378845215 nb_pixel_total : 59569 time to create 1 rle with old method : 0.06309890747070312 time for calcul the mask position with numpy : 0.02733588218688965 nb_pixel_total : 21763 time to create 1 rle with old method : 0.02287602424621582 time for calcul the mask position with numpy : 0.02734518051147461 nb_pixel_total : 16216 time to create 1 rle with old method : 0.017825603485107422 time for calcul the mask position with numpy : 0.0282132625579834 nb_pixel_total : 7500 time to create 1 rle with old method : 0.008059024810791016 time for calcul the mask position with numpy : 0.028946638107299805 nb_pixel_total : 83781 time to create 1 rle with old method : 0.08970880508422852 time for calcul the mask position with numpy : 0.028240680694580078 nb_pixel_total : 28196 time to create 1 rle with old method : 0.03064107894897461 time for calcul the mask position with numpy : 0.02831244468688965 nb_pixel_total : 51442 time to create 1 rle with old method : 0.056396484375 time for calcul the mask position with numpy : 0.029404163360595703 nb_pixel_total : 27415 time to create 1 rle with old method : 0.0471494197845459 time for calcul the mask position with numpy : 0.0401151180267334 nb_pixel_total : 9754 time to create 1 rle with old method : 0.011662721633911133 time for calcul the mask position with numpy : 0.028876781463623047 nb_pixel_total : 53860 time to create 1 rle with old method : 0.05939006805419922 time for calcul the mask position with numpy : 0.029094457626342773 nb_pixel_total : 61517 time to create 1 rle with old method : 0.06840872764587402 time for calcul the mask position with numpy : 0.02867889404296875 nb_pixel_total : 51955 time to create 1 rle with old method : 0.05771493911743164 time for calcul the mask position with numpy : 0.028737306594848633 nb_pixel_total : 8545 time to create 1 rle with old method : 0.009451627731323242 time for calcul the mask position with numpy : 0.028876543045043945 nb_pixel_total : 62377 time to create 1 rle with old method : 0.06899070739746094 time for calcul the mask position with numpy : 0.02862071990966797 nb_pixel_total : 14666 time to create 1 rle with old method : 0.016365528106689453 time for calcul the mask position with numpy : 0.02818441390991211 nb_pixel_total : 3829 time to create 1 rle with old method : 0.004292964935302734 time for calcul the mask position with numpy : 0.029655933380126953 nb_pixel_total : 38859 time to create 1 rle with old method : 0.04295849800109863 time for calcul the mask position with numpy : 0.028492450714111328 nb_pixel_total : 56947 time to create 1 rle with old method : 0.06247711181640625 time for calcul the mask position with numpy : 0.028322696685791016 nb_pixel_total : 10792 time to create 1 rle with old method : 0.011690378189086914 time for calcul the mask position with numpy : 0.028312206268310547 nb_pixel_total : 24889 time to create 1 rle with old method : 0.029345035552978516 time for calcul the mask position with numpy : 0.027993440628051758 nb_pixel_total : 4164 time to create 1 rle with old method : 0.004685878753662109 time for calcul the mask position with numpy : 0.028005123138427734 nb_pixel_total : 14584 time to create 1 rle with old method : 0.016355037689208984 time for calcul the mask position with numpy : 0.02888035774230957 nb_pixel_total : 16276 time to create 1 rle with old method : 0.01849079132080078 time for calcul the mask position with numpy : 0.028673171997070312 nb_pixel_total : 29639 time to create 1 rle with old method : 0.032550811767578125 time for calcul the mask position with numpy : 0.027635574340820312 nb_pixel_total : 6717 time to create 1 rle with old method : 0.0072154998779296875 time for calcul the mask position with numpy : 0.028022289276123047 nb_pixel_total : 9491 time to create 1 rle with old method : 0.010420799255371094 create new chi : 4.457207441329956 time to delete rle : 0.002328634262084961 batch 1 Loaded 58 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 17128 TO DO : save crop sub photo not yet done ! save time : 1.37095308303833 nb_obj : 31 nb_hashtags : 5 time to prepare the origin masks : 5.200155019760132 time for calcul the mask position with numpy : 0.923567533493042 nb_pixel_total : 5138362 time to create 1 rle with new method : 0.8346772193908691 time for calcul the mask position with numpy : 0.02940964698791504 nb_pixel_total : 2784 time to create 1 rle with old method : 0.003157377243041992 time for calcul the mask position with numpy : 0.028961658477783203 nb_pixel_total : 22561 time to create 1 rle with old method : 0.02530503273010254 time for calcul the mask position with numpy : 0.029455184936523438 nb_pixel_total : 165626 time to create 1 rle with new method : 0.759657621383667 time for calcul the mask position with numpy : 0.028130531311035156 nb_pixel_total : 19842 time to create 1 rle with old method : 0.02201223373413086 time for calcul the mask position with numpy : 0.029005050659179688 nb_pixel_total : 36941 time to create 1 rle with old method : 0.04133486747741699 time for calcul the mask position with numpy : 0.0285646915435791 nb_pixel_total : 14467 time to create 1 rle with old method : 0.015925168991088867 time for calcul the mask position with numpy : 0.028528928756713867 nb_pixel_total : 85315 time to create 1 rle with old method : 0.09236693382263184 time for calcul the mask position with numpy : 0.027866840362548828 nb_pixel_total : 46406 time to create 1 rle with old method : 0.05053400993347168 time for calcul the mask position with numpy : 0.028749942779541016 nb_pixel_total : 26846 time to create 1 rle with old method : 0.030303478240966797 time for calcul the mask position with numpy : 0.027751684188842773 nb_pixel_total : 18967 time to create 1 rle with old method : 0.020061731338500977 time for calcul the mask position with numpy : 0.028315305709838867 nb_pixel_total : 257627 time to create 1 rle with new method : 0.45082616806030273 time for calcul the mask position with numpy : 0.03062748908996582 nb_pixel_total : 404299 time to create 1 rle with new method : 0.5832540988922119 time for calcul the mask position with numpy : 0.030286788940429688 nb_pixel_total : 27042 time to create 1 rle with old method : 0.029722213745117188 time for calcul the mask position with numpy : 0.02785944938659668 nb_pixel_total : 53476 time to create 1 rle with old method : 0.05855989456176758 time for calcul the mask position with numpy : 0.028159618377685547 nb_pixel_total : 61810 time to create 1 rle with old method : 0.06805109977722168 time for calcul the mask position with numpy : 0.02858901023864746 nb_pixel_total : 72299 time to create 1 rle with old method : 0.0779564380645752 time for calcul the mask position with numpy : 0.028242826461791992 nb_pixel_total : 80502 time to create 1 rle with old method : 0.08731818199157715 time for calcul the mask position with numpy : 0.027997970581054688 nb_pixel_total : 10884 time to create 1 rle with old method : 0.01178288459777832 time for calcul the mask position with numpy : 0.028699636459350586 nb_pixel_total : 632 time to create 1 rle with old method : 0.0011096000671386719 time for calcul the mask position with numpy : 0.028342485427856445 nb_pixel_total : 107856 time to create 1 rle with old method : 0.1142582893371582 time for calcul the mask position with numpy : 0.027672767639160156 nb_pixel_total : 50111 time to create 1 rle with old method : 0.05353212356567383 time for calcul the mask position with numpy : 0.026958227157592773 nb_pixel_total : 19023 time to create 1 rle with old method : 0.019798755645751953 time for calcul the mask position with numpy : 0.027228355407714844 nb_pixel_total : 9014 time to create 1 rle with old method : 0.0095672607421875 time for calcul the mask position with numpy : 0.02699565887451172 nb_pixel_total : 69288 time to create 1 rle with old method : 0.07472634315490723 time for calcul the mask position with numpy : 0.028416872024536133 nb_pixel_total : 47730 time to create 1 rle with old method : 0.05246448516845703 time for calcul the mask position with numpy : 0.0290987491607666 nb_pixel_total : 41081 time to create 1 rle with old method : 0.04580330848693848 time for calcul the mask position with numpy : 0.029407262802124023 nb_pixel_total : 126923 time to create 1 rle with old method : 0.13899469375610352 time for calcul the mask position with numpy : 0.027771472930908203 nb_pixel_total : 6201 time to create 1 rle with old method : 0.006670951843261719 time for calcul the mask position with numpy : 0.027604103088378906 nb_pixel_total : 7006 time to create 1 rle with old method : 0.01032710075378418 time for calcul the mask position with numpy : 0.03172016143798828 nb_pixel_total : 8593 time to create 1 rle with old method : 0.009737253189086914 time for calcul the mask position with numpy : 0.028986454010009766 nb_pixel_total : 10726 time to create 1 rle with old method : 0.012129545211791992 create new chi : 5.728706359863281 time to delete rle : 0.002867460250854492 batch 1 Loaded 65 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++Number RLEs to save : 19219 TO DO : save crop sub photo not yet done ! save time : 6.9598469734191895 nb_obj : 66 nb_hashtags : 2 time to prepare the origin masks : 4.445821285247803 time for calcul the mask position with numpy : 0.6338107585906982 nb_pixel_total : 5245662 time to create 1 rle with new method : 0.4352147579193115 time for calcul the mask position with numpy : 0.028615713119506836 nb_pixel_total : 27270 time to create 1 rle with old method : 0.03072953224182129 time for calcul the mask position with numpy : 0.028943300247192383 nb_pixel_total : 25064 time to create 1 rle with old method : 0.028162479400634766 time for calcul the mask position with numpy : 0.03270101547241211 nb_pixel_total : 231204 time to create 1 rle with new method : 0.6249616146087646 time for calcul the mask position with numpy : 0.027179479598999023 nb_pixel_total : 7080 time to create 1 rle with old method : 0.007757902145385742 time for calcul the mask position with numpy : 0.028241395950317383 nb_pixel_total : 7513 time to create 1 rle with old method : 0.008098602294921875 time for calcul the mask position with numpy : 0.02841639518737793 nb_pixel_total : 21994 time to create 1 rle with old method : 0.02348804473876953 time for calcul the mask position with numpy : 0.028542757034301758 nb_pixel_total : 42816 time to create 1 rle with old method : 0.04671597480773926 time for calcul the mask position with numpy : 0.027556657791137695 nb_pixel_total : 19683 time to create 1 rle with old method : 0.021191120147705078 time for calcul the mask position with numpy : 0.02854180335998535 nb_pixel_total : 26629 time to create 1 rle with old method : 0.029119491577148438 time for calcul the mask position with numpy : 0.028795957565307617 nb_pixel_total : 22559 time to create 1 rle with old method : 0.025569915771484375 time for calcul the mask position with numpy : 0.029021263122558594 nb_pixel_total : 24981 time to create 1 rle with old method : 0.028053998947143555 time for calcul the mask position with numpy : 0.029046058654785156 nb_pixel_total : 8955 time to create 1 rle with old method : 0.010153055191040039 time for calcul the mask position with numpy : 0.028519392013549805 nb_pixel_total : 5201 time to create 1 rle with old method : 0.005740642547607422 time for calcul the mask position with numpy : 0.02904820442199707 nb_pixel_total : 32823 time to create 1 rle with old method : 0.036498069763183594 time for calcul the mask position with numpy : 0.029910564422607422 nb_pixel_total : 24827 time to create 1 rle with old method : 0.03373384475708008 time for calcul the mask position with numpy : 0.02929997444152832 nb_pixel_total : 39185 time to create 1 rle with old method : 0.04370856285095215 time for calcul the mask position with numpy : 0.02831292152404785 nb_pixel_total : 9348 time to create 1 rle with old method : 0.010524272918701172 time for calcul the mask position with numpy : 0.028707027435302734 nb_pixel_total : 43405 time to create 1 rle with old method : 0.048833370208740234 time for calcul the mask position with numpy : 0.029327869415283203 nb_pixel_total : 14286 time to create 1 rle with old method : 0.016363859176635742 time for calcul the mask position with numpy : 0.02939891815185547 nb_pixel_total : 26089 time to create 1 rle with old method : 0.02946782112121582 time for calcul the mask position with numpy : 0.029600143432617188 nb_pixel_total : 12366 time to create 1 rle with old method : 0.013913869857788086 time for calcul the mask position with numpy : 0.03050708770751953 nb_pixel_total : 23208 time to create 1 rle with old method : 0.03032684326171875 time for calcul the mask position with numpy : 0.03392910957336426 nb_pixel_total : 37782 time to create 1 rle with old method : 0.04227638244628906 time for calcul the mask position with numpy : 0.02924323081970215 nb_pixel_total : 36298 time to create 1 rle with old method : 0.040617942810058594 time for calcul the mask position with numpy : 0.029485225677490234 nb_pixel_total : 20065 time to create 1 rle with old method : 0.022545576095581055 time for calcul the mask position with numpy : 0.029061317443847656 nb_pixel_total : 26307 time to create 1 rle with old method : 0.03130650520324707 time for calcul the mask position with numpy : 0.029265642166137695 nb_pixel_total : 20130 time to create 1 rle with old method : 0.022432565689086914 time for calcul the mask position with numpy : 0.029029130935668945 nb_pixel_total : 11004 time to create 1 rle with old method : 0.012412548065185547 time for calcul the mask position with numpy : 0.02991008758544922 nb_pixel_total : 117128 time to create 1 rle with old method : 0.15224790573120117 time for calcul the mask position with numpy : 0.02898883819580078 nb_pixel_total : 13114 time to create 1 rle with old method : 0.0146484375 time for calcul the mask position with numpy : 0.028974533081054688 nb_pixel_total : 57583 time to create 1 rle with old method : 0.06423711776733398 time for calcul the mask position with numpy : 0.03161358833312988 nb_pixel_total : 66355 time to create 1 rle with old method : 0.07714319229125977 time for calcul the mask position with numpy : 0.032994747161865234 nb_pixel_total : 27371 time to create 1 rle with old method : 0.043955087661743164 time for calcul the mask position with numpy : 0.02928924560546875 nb_pixel_total : 25879 time to create 1 rle with old method : 0.02888035774230957 time for calcul the mask position with numpy : 0.028964757919311523 nb_pixel_total : 10559 time to create 1 rle with old method : 0.012038469314575195 time for calcul the mask position with numpy : 0.02784442901611328 nb_pixel_total : 402 time to create 1 rle with old method : 0.0006325244903564453 time for calcul the mask position with numpy : 0.028376102447509766 nb_pixel_total : 14160 time to create 1 rle with old method : 0.015312433242797852 time for calcul the mask position with numpy : 0.02797865867614746 nb_pixel_total : 11825 time to create 1 rle with old method : 0.013106822967529297 time for calcul the mask position with numpy : 0.028257131576538086 nb_pixel_total : 8395 time to create 1 rle with old method : 0.011532068252563477 time for calcul the mask position with numpy : 0.027935504913330078 nb_pixel_total : 35048 time to create 1 rle with old method : 0.03821730613708496 time for calcul the mask position with numpy : 0.028086423873901367 nb_pixel_total : 20325 time to create 1 rle with old method : 0.02555084228515625 time for calcul the mask position with numpy : 0.028350353240966797 nb_pixel_total : 19295 time to create 1 rle with old method : 0.0210721492767334 time for calcul the mask position with numpy : 0.028647899627685547 nb_pixel_total : 26354 time to create 1 rle with old method : 0.029733896255493164 time for calcul the mask position with numpy : 0.02920246124267578 nb_pixel_total : 21118 time to create 1 rle with old method : 0.025425195693969727 time for calcul the mask position with numpy : 0.02952122688293457 nb_pixel_total : 15876 time to create 1 rle with old method : 0.025574684143066406 time for calcul the mask position with numpy : 0.03326129913330078 nb_pixel_total : 38676 time to create 1 rle with old method : 0.053342580795288086 time for calcul the mask position with numpy : 0.02950739860534668 nb_pixel_total : 34933 time to create 1 rle with old method : 0.03939533233642578 time for calcul the mask position with numpy : 0.03282928466796875 nb_pixel_total : 10425 time to create 1 rle with old method : 0.011789083480834961 time for calcul the mask position with numpy : 0.0292661190032959 nb_pixel_total : 5933 time to create 1 rle with old method : 0.007380485534667969 time for calcul the mask position with numpy : 0.029271841049194336 nb_pixel_total : 29640 time to create 1 rle with old method : 0.03578495979309082 time for calcul the mask position with numpy : 0.02922654151916504 nb_pixel_total : 4560 time to create 1 rle with old method : 0.00513768196105957 time for calcul the mask position with numpy : 0.028736591339111328 nb_pixel_total : 35928 time to create 1 rle with old method : 0.041368961334228516 time for calcul the mask position with numpy : 0.02972269058227539 nb_pixel_total : 7273 time to create 1 rle with old method : 0.008368730545043945 time for calcul the mask position with numpy : 0.029748916625976562 nb_pixel_total : 16367 time to create 1 rle with old method : 0.018922805786132812 time for calcul the mask position with numpy : 0.029970169067382812 nb_pixel_total : 17222 time to create 1 rle with old method : 0.020579814910888672 time for calcul the mask position with numpy : 0.030551910400390625 nb_pixel_total : 1974 time to create 1 rle with old method : 0.0022881031036376953 time for calcul the mask position with numpy : 0.031850337982177734 nb_pixel_total : 11684 time to create 1 rle with old method : 0.014354705810546875 time for calcul the mask position with numpy : 0.02963399887084961 nb_pixel_total : 89213 time to create 1 rle with old method : 0.10027122497558594 time for calcul the mask position with numpy : 0.029012680053710938 nb_pixel_total : 15701 time to create 1 rle with old method : 0.01785564422607422 time for calcul the mask position with numpy : 0.029227495193481445 nb_pixel_total : 6656 time to create 1 rle with old method : 0.010201215744018555 time for calcul the mask position with numpy : 0.031752586364746094 nb_pixel_total : 29940 time to create 1 rle with old method : 0.03452873229980469 time for calcul the mask position with numpy : 0.02923870086669922 nb_pixel_total : 45690 time to create 1 rle with old method : 0.057115793228149414 time for calcul the mask position with numpy : 0.029286623001098633 nb_pixel_total : 9937 time to create 1 rle with old method : 0.01122593879699707 time for calcul the mask position with numpy : 0.030631065368652344 nb_pixel_total : 15683 time to create 1 rle with old method : 0.01717376708984375 time for calcul the mask position with numpy : 0.0286865234375 nb_pixel_total : 25997 time to create 1 rle with old method : 0.02889251708984375 time for calcul the mask position with numpy : 0.028820514678955078 nb_pixel_total : 12287 time to create 1 rle with old method : 0.013566732406616211 create new chi : 5.543522596359253 time to delete rle : 0.00463557243347168 batch 1 Loaded 136 chid ids of type : 3594 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 30735 TO DO : save crop sub photo not yet done ! save time : 2.1574230194091797 nb_obj : 66 nb_hashtags : 4 time to prepare the origin masks : 4.061843156814575 time for calcul the mask position with numpy : 0.31555747985839844 nb_pixel_total : 5419478 time to create 1 rle with new method : 0.4321136474609375 time for calcul the mask position with numpy : 0.03294515609741211 nb_pixel_total : 7799 time to create 1 rle with old method : 0.009453535079956055 time for calcul the mask position with numpy : 0.02926349639892578 nb_pixel_total : 36593 time to create 1 rle with old method : 0.04070544242858887 time for calcul the mask position with numpy : 0.02922844886779785 nb_pixel_total : 74838 time to create 1 rle with old method : 0.0835270881652832 time for calcul the mask position with numpy : 0.029106855392456055 nb_pixel_total : 25931 time to create 1 rle with old method : 0.029188871383666992 time for calcul the mask position with numpy : 0.029077529907226562 nb_pixel_total : 17198 time to create 1 rle with old method : 0.0196225643157959 time for calcul the mask position with numpy : 0.02925872802734375 nb_pixel_total : 6346 time to create 1 rle with old method : 0.007601261138916016 time for calcul the mask position with numpy : 0.02977275848388672 nb_pixel_total : 12347 time to create 1 rle with old method : 0.014028310775756836 time for calcul the mask position with numpy : 0.02987504005432129 nb_pixel_total : 32819 time to create 1 rle with old method : 0.040143728256225586 time for calcul the mask position with numpy : 0.029138803482055664 nb_pixel_total : 37328 time to create 1 rle with old method : 0.04021167755126953 time for calcul the mask position with numpy : 0.02839207649230957 nb_pixel_total : 23520 time to create 1 rle with old method : 0.025377273559570312 time for calcul the mask position with numpy : 0.028330087661743164 nb_pixel_total : 4714 time to create 1 rle with old method : 0.0070438385009765625 time for calcul the mask position with numpy : 0.02897167205810547 nb_pixel_total : 18213 time to create 1 rle with old method : 0.020348310470581055 time for calcul the mask position with numpy : 0.028310298919677734 nb_pixel_total : 26921 time to create 1 rle with old method : 0.028863906860351562 time for calcul the mask position with numpy : 0.027461528778076172 nb_pixel_total : 29931 time to create 1 rle with old method : 0.030728816986083984 time for calcul the mask position with numpy : 0.027046918869018555 nb_pixel_total : 12771 time to create 1 rle with old method : 0.013560295104980469 time for calcul the mask position with numpy : 0.02784276008605957 nb_pixel_total : 19107 time to create 1 rle with old method : 0.01994037628173828 time for calcul the mask position with numpy : 0.027341127395629883 nb_pixel_total : 45421 time to create 1 rle with old method : 0.04995083808898926 time for calcul the mask position with numpy : 0.02700018882751465 nb_pixel_total : 20749 time to create 1 rle with old method : 0.02143549919128418 time for calcul the mask position with numpy : 0.026508092880249023 nb_pixel_total : 30758 time to create 1 rle with old method : 0.03261971473693848 time for calcul the mask position with numpy : 0.03284478187561035 nb_pixel_total : 17702 time to create 1 rle with old method : 0.019017696380615234 time for calcul the mask position with numpy : 0.02797698974609375 nb_pixel_total : 1033 time to create 1 rle with old method : 0.0013184547424316406 time for calcul the mask position with numpy : 0.027393102645874023 nb_pixel_total : 17132 time to create 1 rle with old method : 0.018576860427856445 time for calcul the mask position with numpy : 0.027820587158203125 nb_pixel_total : 20895 time to create 1 rle with old method : 0.02221822738647461 time for calcul the mask position with numpy : 0.027562856674194336 nb_pixel_total : 9670 time to create 1 rle with old method : 0.010925054550170898 time for calcul the mask position with numpy : 0.028943538665771484 nb_pixel_total : 29794 time to create 1 rle with old method : 0.03363370895385742 time for calcul the mask position with numpy : 0.028601646423339844 nb_pixel_total : 40269 time to create 1 rle with old method : 0.044617414474487305 time for calcul the mask position with numpy : 0.028906822204589844 nb_pixel_total : 19555 time to create 1 rle with old method : 0.020598649978637695 time for calcul the mask position with numpy : 0.026868104934692383 nb_pixel_total : 101856 time to create 1 rle with old method : 0.10787653923034668 time for calcul the mask position with numpy : 0.027675151824951172 nb_pixel_total : 36207 time to create 1 rle with old method : 0.03773236274719238 time for calcul the mask position with numpy : 0.026248931884765625 nb_pixel_total : 15324 time to create 1 rle with old method : 0.016096115112304688 time for calcul the mask position with numpy : 0.026224851608276367 nb_pixel_total : 19898 time to create 1 rle with old method : 0.02029728889465332 time for calcul the mask position with numpy : 0.027291059494018555 nb_pixel_total : 51850 time to create 1 rle with old method : 0.054143428802490234 time for calcul the mask position with numpy : 0.02741384506225586 nb_pixel_total : 60444 time to create 1 rle with old method : 0.061295270919799805 time for calcul the mask position with numpy : 0.027995824813842773 nb_pixel_total : 31504 time to create 1 rle with old method : 0.03326892852783203 time for calcul the mask position with numpy : 0.026645421981811523 nb_pixel_total : 22588 time to create 1 rle with old method : 0.024312496185302734 time for calcul the mask position with numpy : 0.027208328247070312 nb_pixel_total : 20155 time to create 1 rle with old method : 0.02263188362121582 time for calcul the mask position with numpy : 0.02920055389404297 nb_pixel_total : 13734 time to create 1 rle with old method : 0.015381097793579102 time for calcul the mask position with numpy : 0.028896570205688477 nb_pixel_total : 12036 time to create 1 rle with old method : 0.01323556900024414 time for calcul the mask position with numpy : 0.027606487274169922 nb_pixel_total : 13589 time to create 1 rle with old method : 0.015095949172973633 time for calcul the mask position with numpy : 0.028540372848510742 nb_pixel_total : 57017 time to create 1 rle with old method : 0.060404300689697266 time for calcul the mask position with numpy : 0.027513742446899414 nb_pixel_total : 19032 time to create 1 rle with old method : 0.020734310150146484 time for calcul the mask position with numpy : 0.028182268142700195 nb_pixel_total : 20785 time to create 1 rle with old method : 0.022612571716308594 time for calcul the mask position with numpy : 0.027872323989868164 nb_pixel_total : 49668 time to create 1 rle with old method : 0.05338406562805176 time for calcul the mask position with numpy : 0.0283205509185791 nb_pixel_total : 56436 time to create 1 rle with old method : 0.06114983558654785 time for calcul the mask position with numpy : 0.02765202522277832 nb_pixel_total : 10718 time to create 1 rle with old method : 0.011742830276489258 time for calcul the mask position with numpy : 0.028577804565429688 nb_pixel_total : 12456 time to create 1 rle with old method : 0.013772726058959961 time for calcul the mask position with numpy : 0.028047800064086914 nb_pixel_total : 3712 time to create 1 rle with old method : 0.004117727279663086 time for calcul the mask position with numpy : 0.02810359001159668 nb_pixel_total : 14140 time to create 1 rle with old method : 0.01528620719909668 time for calcul the mask position with numpy : 0.028369903564453125 nb_pixel_total : 11818 time to create 1 rle with old method : 0.013345479965209961 time for calcul the mask position with numpy : 0.027868270874023438 nb_pixel_total : 19601 time to create 1 rle with old method : 0.021388769149780273 time for calcul the mask position with numpy : 0.030048370361328125 nb_pixel_total : 36567 time to create 1 rle with old method : 0.03930521011352539 time for calcul the mask position with numpy : 0.02707386016845703 nb_pixel_total : 11836 time to create 1 rle with old method : 0.012560606002807617 time for calcul the mask position with numpy : 0.02754950523376465 nb_pixel_total : 17023 time to create 1 rle with old method : 0.017785072326660156 time for calcul the mask position with numpy : 0.026180028915405273 nb_pixel_total : 24286 time to create 1 rle with old method : 0.024866580963134766 time for calcul the mask position with numpy : 0.026604890823364258 nb_pixel_total : 48326 time to create 1 rle with old method : 0.05154156684875488 time for calcul the mask position with numpy : 0.027794361114501953 nb_pixel_total : 20648 time to create 1 rle with old method : 0.022543907165527344 time for calcul the mask position with numpy : 0.027319908142089844 nb_pixel_total : 12768 time to create 1 rle with old method : 0.013436317443847656 time for calcul the mask position with numpy : 0.027541399002075195 nb_pixel_total : 43325 time to create 1 rle with old method : 0.04494619369506836 time for calcul the mask position with numpy : 0.026985883712768555 nb_pixel_total : 20464 time to create 1 rle with old method : 0.021138429641723633 time for calcul the mask position with numpy : 0.02757406234741211 nb_pixel_total : 35343 time to create 1 rle with old method : 0.03673911094665527 time for calcul the mask position with numpy : 0.027185678482055664 nb_pixel_total : 4662 time to create 1 rle with old method : 0.005197048187255859 time for calcul the mask position with numpy : 0.027688026428222656 nb_pixel_total : 9086 time to create 1 rle with old method : 0.009647846221923828 time for calcul the mask position with numpy : 0.027256011962890625 nb_pixel_total : 14282 time to create 1 rle with old method : 0.015935182571411133 time for calcul the mask position with numpy : 0.028545618057250977 nb_pixel_total : 10373 time to create 1 rle with old method : 0.01099252700805664 time for calcul the mask position with numpy : 0.02735757827758789 nb_pixel_total : 4075 time to create 1 rle with old method : 0.004384040832519531 time for calcul the mask position with numpy : 0.027283906936645508 nb_pixel_total : 3776 time to create 1 rle with old method : 0.0039920806884765625 create new chi : 4.409633636474609 time to delete rle : 0.004489898681640625 batch 1 Loaded 133 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 29769 TO DO : save crop sub photo not yet done ! save time : 2.1647539138793945 nb_obj : 49 nb_hashtags : 4 time to prepare the origin masks : 4.585700750350952 time for calcul the mask position with numpy : 0.44375157356262207 nb_pixel_total : 5685055 time to create 1 rle with new method : 0.9015169143676758 time for calcul the mask position with numpy : 0.02971506118774414 nb_pixel_total : 11070 time to create 1 rle with old method : 0.013381242752075195 time for calcul the mask position with numpy : 0.03159689903259277 nb_pixel_total : 6766 time to create 1 rle with old method : 0.007798433303833008 time for calcul the mask position with numpy : 0.029575347900390625 nb_pixel_total : 23159 time to create 1 rle with old method : 0.027295827865600586 time for calcul the mask position with numpy : 0.030055761337280273 nb_pixel_total : 11445 time to create 1 rle with old method : 0.014878273010253906 time for calcul the mask position with numpy : 0.028805971145629883 nb_pixel_total : 20680 time to create 1 rle with old method : 0.022908449172973633 time for calcul the mask position with numpy : 0.029416322708129883 nb_pixel_total : 37166 time to create 1 rle with old method : 0.051581382751464844 time for calcul the mask position with numpy : 0.03304171562194824 nb_pixel_total : 25430 time to create 1 rle with old method : 0.03872227668762207 time for calcul the mask position with numpy : 0.029479503631591797 nb_pixel_total : 14902 time to create 1 rle with old method : 0.016531705856323242 time for calcul the mask position with numpy : 0.027627944946289062 nb_pixel_total : 34279 time to create 1 rle with old method : 0.038251399993896484 time for calcul the mask position with numpy : 0.030471324920654297 nb_pixel_total : 38863 time to create 1 rle with old method : 0.04849100112915039 time for calcul the mask position with numpy : 0.028848886489868164 nb_pixel_total : 30810 time to create 1 rle with old method : 0.0357968807220459 time for calcul the mask position with numpy : 0.029469013214111328 nb_pixel_total : 32058 time to create 1 rle with old method : 0.03537702560424805 time for calcul the mask position with numpy : 0.029979705810546875 nb_pixel_total : 20334 time to create 1 rle with old method : 0.024766921997070312 time for calcul the mask position with numpy : 0.029084444046020508 nb_pixel_total : 19490 time to create 1 rle with old method : 0.022008895874023438 time for calcul the mask position with numpy : 0.029129981994628906 nb_pixel_total : 45898 time to create 1 rle with old method : 0.05483222007751465 time for calcul the mask position with numpy : 0.030270814895629883 nb_pixel_total : 39463 time to create 1 rle with old method : 0.04483747482299805 time for calcul the mask position with numpy : 0.028314828872680664 nb_pixel_total : 19778 time to create 1 rle with old method : 0.021924734115600586 time for calcul the mask position with numpy : 0.029039382934570312 nb_pixel_total : 10854 time to create 1 rle with old method : 0.012067794799804688 time for calcul the mask position with numpy : 0.028734445571899414 nb_pixel_total : 49137 time to create 1 rle with old method : 0.054903268814086914 time for calcul the mask position with numpy : 0.02907586097717285 nb_pixel_total : 64385 time to create 1 rle with old method : 0.07066512107849121 time for calcul the mask position with numpy : 0.02921462059020996 nb_pixel_total : 57904 time to create 1 rle with old method : 0.06335902214050293 time for calcul the mask position with numpy : 0.02699565887451172 nb_pixel_total : 2647 time to create 1 rle with old method : 0.0031676292419433594 time for calcul the mask position with numpy : 0.028058290481567383 nb_pixel_total : 11532 time to create 1 rle with old method : 0.012955427169799805 time for calcul the mask position with numpy : 0.028803586959838867 nb_pixel_total : 27468 time to create 1 rle with old method : 0.030343055725097656 time for calcul the mask position with numpy : 0.028978586196899414 nb_pixel_total : 30329 time to create 1 rle with old method : 0.034137725830078125 time for calcul the mask position with numpy : 0.029293060302734375 nb_pixel_total : 71440 time to create 1 rle with old method : 0.08499264717102051 time for calcul the mask position with numpy : 0.02963852882385254 nb_pixel_total : 90264 time to create 1 rle with old method : 0.10151147842407227 time for calcul the mask position with numpy : 0.028728246688842773 nb_pixel_total : 43174 time to create 1 rle with old method : 0.04772806167602539 time for calcul the mask position with numpy : 0.02856135368347168 nb_pixel_total : 72753 time to create 1 rle with old method : 0.08083343505859375 time for calcul the mask position with numpy : 0.028853654861450195 nb_pixel_total : 28523 time to create 1 rle with old method : 0.031421661376953125 time for calcul the mask position with numpy : 0.029237747192382812 nb_pixel_total : 32275 time to create 1 rle with old method : 0.03762245178222656 time for calcul the mask position with numpy : 0.030556917190551758 nb_pixel_total : 50244 time to create 1 rle with old method : 0.05476188659667969 time for calcul the mask position with numpy : 0.028885364532470703 nb_pixel_total : 12901 time to create 1 rle with old method : 0.01654052734375 time for calcul the mask position with numpy : 0.028315305709838867 nb_pixel_total : 21858 time to create 1 rle with old method : 0.023587703704833984 time for calcul the mask position with numpy : 0.027886152267456055 nb_pixel_total : 21983 time to create 1 rle with old method : 0.02445197105407715 time for calcul the mask position with numpy : 0.028636932373046875 nb_pixel_total : 17248 time to create 1 rle with old method : 0.01897883415222168 time for calcul the mask position with numpy : 0.028349637985229492 nb_pixel_total : 45793 time to create 1 rle with old method : 0.04963183403015137 time for calcul the mask position with numpy : 0.030445575714111328 nb_pixel_total : 19105 time to create 1 rle with old method : 0.03137636184692383 time for calcul the mask position with numpy : 0.03238677978515625 nb_pixel_total : 32807 time to create 1 rle with old method : 0.0366816520690918 time for calcul the mask position with numpy : 0.028882265090942383 nb_pixel_total : 17018 time to create 1 rle with old method : 0.01892375946044922 time for calcul the mask position with numpy : 0.029230356216430664 nb_pixel_total : 7464 time to create 1 rle with old method : 0.008356809616088867 time for calcul the mask position with numpy : 0.028929948806762695 nb_pixel_total : 6241 time to create 1 rle with old method : 0.0070149898529052734 time for calcul the mask position with numpy : 0.029186010360717773 nb_pixel_total : 8769 time to create 1 rle with old method : 0.00988459587097168 time for calcul the mask position with numpy : 0.028993844985961914 nb_pixel_total : 8835 time to create 1 rle with old method : 0.010147571563720703 time for calcul the mask position with numpy : 0.02897953987121582 nb_pixel_total : 31595 time to create 1 rle with old method : 0.035431861877441406 time for calcul the mask position with numpy : 0.028570175170898438 nb_pixel_total : 10391 time to create 1 rle with old method : 0.013254642486572266 time for calcul the mask position with numpy : 0.028453826904296875 nb_pixel_total : 4773 time to create 1 rle with old method : 0.0051953792572021484 time for calcul the mask position with numpy : 0.0281829833984375 nb_pixel_total : 12710 time to create 1 rle with old method : 0.014000177383422852 time for calcul the mask position with numpy : 0.02864241600036621 nb_pixel_total : 11174 time to create 1 rle with old method : 0.01223301887512207 create new chi : 4.389904022216797 time to delete rle : 0.0060465335845947266 batch 1 Loaded 100 chid ids of type : 3594 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 24477 TO DO : save crop sub photo not yet done ! save time : 1.6519370079040527 nb_obj : 62 nb_hashtags : 5 time to prepare the origin masks : 4.533288478851318 time for calcul the mask position with numpy : 0.5525550842285156 nb_pixel_total : 5153957 time to create 1 rle with new method : 0.7805695533752441 time for calcul the mask position with numpy : 0.027378082275390625 nb_pixel_total : 34326 time to create 1 rle with old method : 0.035787343978881836 time for calcul the mask position with numpy : 0.027697086334228516 nb_pixel_total : 20860 time to create 1 rle with old method : 0.02241230010986328 time for calcul the mask position with numpy : 0.028911590576171875 nb_pixel_total : 10645 time to create 1 rle with old method : 0.01185154914855957 time for calcul the mask position with numpy : 0.02852344512939453 nb_pixel_total : 14160 time to create 1 rle with old method : 0.01567816734313965 time for calcul the mask position with numpy : 0.028368711471557617 nb_pixel_total : 33466 time to create 1 rle with old method : 0.03597235679626465 time for calcul the mask position with numpy : 0.02798748016357422 nb_pixel_total : 9548 time to create 1 rle with old method : 0.010265827178955078 time for calcul the mask position with numpy : 0.028530359268188477 nb_pixel_total : 5724 time to create 1 rle with old method : 0.006403446197509766 time for calcul the mask position with numpy : 0.031011581420898438 nb_pixel_total : 79995 time to create 1 rle with old method : 0.10614275932312012 time for calcul the mask position with numpy : 0.028698444366455078 nb_pixel_total : 42688 time to create 1 rle with old method : 0.04610776901245117 time for calcul the mask position with numpy : 0.028255701065063477 nb_pixel_total : 32968 time to create 1 rle with old method : 0.036367177963256836 time for calcul the mask position with numpy : 0.028101682662963867 nb_pixel_total : 15503 time to create 1 rle with old method : 0.016790390014648438 time for calcul the mask position with numpy : 0.027382850646972656 nb_pixel_total : 22121 time to create 1 rle with old method : 0.023635387420654297 time for calcul the mask position with numpy : 0.028032302856445312 nb_pixel_total : 8650 time to create 1 rle with old method : 0.00927281379699707 time for calcul the mask position with numpy : 0.028246402740478516 nb_pixel_total : 70514 time to create 1 rle with old method : 0.07615828514099121 time for calcul the mask position with numpy : 0.02709484100341797 nb_pixel_total : 37368 time to create 1 rle with old method : 0.040122270584106445 time for calcul the mask position with numpy : 0.027849435806274414 nb_pixel_total : 449 time to create 1 rle with old method : 0.0008234977722167969 time for calcul the mask position with numpy : 0.028270959854125977 nb_pixel_total : 34759 time to create 1 rle with old method : 0.037277936935424805 time for calcul the mask position with numpy : 0.027007102966308594 nb_pixel_total : 4962 time to create 1 rle with old method : 0.005109548568725586 time for calcul the mask position with numpy : 0.0266420841217041 nb_pixel_total : 23880 time to create 1 rle with old method : 0.024705171585083008 time for calcul the mask position with numpy : 0.02769303321838379 nb_pixel_total : 9190 time to create 1 rle with old method : 0.010318756103515625 time for calcul the mask position with numpy : 0.028288841247558594 nb_pixel_total : 17157 time to create 1 rle with old method : 0.01890397071838379 time for calcul the mask position with numpy : 0.02769923210144043 nb_pixel_total : 30879 time to create 1 rle with old method : 0.03302359580993652 time for calcul the mask position with numpy : 0.028015613555908203 nb_pixel_total : 10438 time to create 1 rle with old method : 0.011313438415527344 time for calcul the mask position with numpy : 0.026968717575073242 nb_pixel_total : 69686 time to create 1 rle with old method : 0.07549881935119629 time for calcul the mask position with numpy : 0.027714014053344727 nb_pixel_total : 16386 time to create 1 rle with old method : 0.01803874969482422 time for calcul the mask position with numpy : 0.028105974197387695 nb_pixel_total : 38022 time to create 1 rle with old method : 0.04089856147766113 time for calcul the mask position with numpy : 0.026657819747924805 nb_pixel_total : 11931 time to create 1 rle with old method : 0.012365341186523438 time for calcul the mask position with numpy : 0.028386354446411133 nb_pixel_total : 38870 time to create 1 rle with old method : 0.043103694915771484 time for calcul the mask position with numpy : 0.0282437801361084 nb_pixel_total : 8878 time to create 1 rle with old method : 0.00982666015625 time for calcul the mask position with numpy : 0.02855229377746582 nb_pixel_total : 55056 time to create 1 rle with old method : 0.06149625778198242 time for calcul the mask position with numpy : 0.0290682315826416 nb_pixel_total : 80677 time to create 1 rle with old method : 0.0900273323059082 time for calcul the mask position with numpy : 0.028738975524902344 nb_pixel_total : 32500 time to create 1 rle with old method : 0.03610539436340332 time for calcul the mask position with numpy : 0.028087615966796875 nb_pixel_total : 9235 time to create 1 rle with old method : 0.010466337203979492 time for calcul the mask position with numpy : 0.029002904891967773 nb_pixel_total : 51420 time to create 1 rle with old method : 0.05652594566345215 time for calcul the mask position with numpy : 0.02828049659729004 nb_pixel_total : 51972 time to create 1 rle with old method : 0.05731606483459473 time for calcul the mask position with numpy : 0.02832341194152832 nb_pixel_total : 14057 time to create 1 rle with old method : 0.015728235244750977 time for calcul the mask position with numpy : 0.02906322479248047 nb_pixel_total : 67504 time to create 1 rle with old method : 0.07505369186401367 time for calcul the mask position with numpy : 0.02832198143005371 nb_pixel_total : 12512 time to create 1 rle with old method : 0.013669729232788086 time for calcul the mask position with numpy : 0.028304338455200195 nb_pixel_total : 11849 time to create 1 rle with old method : 0.013135671615600586 time for calcul the mask position with numpy : 0.028501272201538086 nb_pixel_total : 34038 time to create 1 rle with old method : 0.03750753402709961 time for calcul the mask position with numpy : 0.028580665588378906 nb_pixel_total : 79719 time to create 1 rle with old method : 0.11208033561706543 time for calcul the mask position with numpy : 0.030228614807128906 nb_pixel_total : 23 time to create 1 rle with old method : 4.887580871582031e-05 time for calcul the mask position with numpy : 0.028506040573120117 nb_pixel_total : 97942 time to create 1 rle with old method : 0.10862493515014648 time for calcul the mask position with numpy : 0.028806209564208984 nb_pixel_total : 20526 time to create 1 rle with old method : 0.022215604782104492 time for calcul the mask position with numpy : 0.028775930404663086 nb_pixel_total : 147787 time to create 1 rle with old method : 0.1580190658569336 time for calcul the mask position with numpy : 0.027979373931884766 nb_pixel_total : 40143 time to create 1 rle with old method : 0.04333376884460449 time for calcul the mask position with numpy : 0.028089523315429688 nb_pixel_total : 24353 time to create 1 rle with old method : 0.026566028594970703 time for calcul the mask position with numpy : 0.02830982208251953 nb_pixel_total : 6806 time to create 1 rle with old method : 0.007452249526977539 time for calcul the mask position with numpy : 0.028295516967773438 nb_pixel_total : 51849 time to create 1 rle with old method : 0.05503964424133301 time for calcul the mask position with numpy : 0.027202129364013672 nb_pixel_total : 45350 time to create 1 rle with old method : 0.04993271827697754 time for calcul the mask position with numpy : 0.027887344360351562 nb_pixel_total : 14315 time to create 1 rle with old method : 0.015661239624023438 time for calcul the mask position with numpy : 0.02884960174560547 nb_pixel_total : 77357 time to create 1 rle with old method : 0.0840291976928711 time for calcul the mask position with numpy : 0.027513980865478516 nb_pixel_total : 11600 time to create 1 rle with old method : 0.012457847595214844 time for calcul the mask position with numpy : 0.02801990509033203 nb_pixel_total : 21111 time to create 1 rle with old method : 0.023878097534179688 time for calcul the mask position with numpy : 0.028679370880126953 nb_pixel_total : 9011 time to create 1 rle with old method : 0.010014533996582031 time for calcul the mask position with numpy : 0.028950929641723633 nb_pixel_total : 4325 time to create 1 rle with old method : 0.004887819290161133 time for calcul the mask position with numpy : 0.02874279022216797 nb_pixel_total : 10339 time to create 1 rle with old method : 0.011240720748901367 time for calcul the mask position with numpy : 0.028083086013793945 nb_pixel_total : 7783 time to create 1 rle with old method : 0.008694648742675781 time for calcul the mask position with numpy : 0.027603626251220703 nb_pixel_total : 14727 time to create 1 rle with old method : 0.01573657989501953 time for calcul the mask position with numpy : 0.027952194213867188 nb_pixel_total : 19643 time to create 1 rle with old method : 0.021494150161743164 time for calcul the mask position with numpy : 0.029077768325805664 nb_pixel_total : 5413 time to create 1 rle with old method : 0.006103992462158203 time for calcul the mask position with numpy : 0.028753995895385742 nb_pixel_total : 11318 time to create 1 rle with old method : 0.012727022171020508 create new chi : 5.231032133102417 time to delete rle : 0.004366636276245117 batch 1 Loaded 127 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 30250 TO DO : save crop sub photo not yet done ! save time : 2.3323521614074707 nb_obj : 67 nb_hashtags : 5 time to prepare the origin masks : 4.980846881866455 time for calcul the mask position with numpy : 0.277587890625 nb_pixel_total : 4963386 time to create 1 rle with new method : 1.9028136730194092 time for calcul the mask position with numpy : 0.028867244720458984 nb_pixel_total : 10721 time to create 1 rle with old method : 0.012039899826049805 time for calcul the mask position with numpy : 0.028977394104003906 nb_pixel_total : 19288 time to create 1 rle with old method : 0.021547794342041016 time for calcul the mask position with numpy : 0.030559301376342773 nb_pixel_total : 32074 time to create 1 rle with old method : 0.03588604927062988 time for calcul the mask position with numpy : 0.028850793838500977 nb_pixel_total : 7162 time to create 1 rle with old method : 0.008115530014038086 time for calcul the mask position with numpy : 0.028903484344482422 nb_pixel_total : 9405 time to create 1 rle with old method : 0.01053762435913086 time for calcul the mask position with numpy : 0.028896093368530273 nb_pixel_total : 23923 time to create 1 rle with old method : 0.02653336524963379 time for calcul the mask position with numpy : 0.028285741806030273 nb_pixel_total : 4911 time to create 1 rle with old method : 0.00524449348449707 time for calcul the mask position with numpy : 0.028754711151123047 nb_pixel_total : 50204 time to create 1 rle with old method : 0.055684804916381836 time for calcul the mask position with numpy : 0.03431844711303711 nb_pixel_total : 59580 time to create 1 rle with old method : 0.0652155876159668 time for calcul the mask position with numpy : 0.029376983642578125 nb_pixel_total : 6434 time to create 1 rle with old method : 0.0071566104888916016 time for calcul the mask position with numpy : 0.02792048454284668 nb_pixel_total : 10437 time to create 1 rle with old method : 0.010861873626708984 time for calcul the mask position with numpy : 0.028845787048339844 nb_pixel_total : 17796 time to create 1 rle with old method : 0.019073009490966797 time for calcul the mask position with numpy : 0.028455018997192383 nb_pixel_total : 98833 time to create 1 rle with old method : 0.10721921920776367 time for calcul the mask position with numpy : 0.02840590476989746 nb_pixel_total : 26579 time to create 1 rle with old method : 0.02950739860534668 time for calcul the mask position with numpy : 0.028587818145751953 nb_pixel_total : 40335 time to create 1 rle with old method : 0.04411172866821289 time for calcul the mask position with numpy : 0.028684377670288086 nb_pixel_total : 22629 time to create 1 rle with old method : 0.025030851364135742 time for calcul the mask position with numpy : 0.02870321273803711 nb_pixel_total : 34512 time to create 1 rle with old method : 0.038390398025512695 time for calcul the mask position with numpy : 0.029064178466796875 nb_pixel_total : 12226 time to create 1 rle with old method : 0.013721942901611328 time for calcul the mask position with numpy : 0.0287628173828125 nb_pixel_total : 21109 time to create 1 rle with old method : 0.02318716049194336 time for calcul the mask position with numpy : 0.02862095832824707 nb_pixel_total : 109536 time to create 1 rle with old method : 0.11709380149841309 time for calcul the mask position with numpy : 0.028215408325195312 nb_pixel_total : 39227 time to create 1 rle with old method : 0.04354500770568848 time for calcul the mask position with numpy : 0.02764439582824707 nb_pixel_total : 46518 time to create 1 rle with old method : 0.05146336555480957 time for calcul the mask position with numpy : 0.028394222259521484 nb_pixel_total : 17471 time to create 1 rle with old method : 0.018592357635498047 time for calcul the mask position with numpy : 0.02910614013671875 nb_pixel_total : 51424 time to create 1 rle with old method : 0.055555105209350586 time for calcul the mask position with numpy : 0.030204296112060547 nb_pixel_total : 39579 time to create 1 rle with old method : 0.0434107780456543 time for calcul the mask position with numpy : 0.028197050094604492 nb_pixel_total : 97468 time to create 1 rle with old method : 0.13211989402770996 time for calcul the mask position with numpy : 0.030954360961914062 nb_pixel_total : 46566 time to create 1 rle with old method : 0.05049705505371094 time for calcul the mask position with numpy : 0.028285503387451172 nb_pixel_total : 21465 time to create 1 rle with old method : 0.023459911346435547 time for calcul the mask position with numpy : 0.027460098266601562 nb_pixel_total : 11535 time to create 1 rle with old method : 0.01239323616027832 time for calcul the mask position with numpy : 0.02873539924621582 nb_pixel_total : 153110 time to create 1 rle with new method : 0.6309466361999512 time for calcul the mask position with numpy : 0.02884840965270996 nb_pixel_total : 14368 time to create 1 rle with old method : 0.01608586311340332 time for calcul the mask position with numpy : 0.028734922409057617 nb_pixel_total : 26073 time to create 1 rle with old method : 0.028792381286621094 time for calcul the mask position with numpy : 0.029019832611083984 nb_pixel_total : 35796 time to create 1 rle with old method : 0.039443254470825195 time for calcul the mask position with numpy : 0.02870941162109375 nb_pixel_total : 13756 time to create 1 rle with old method : 0.015586376190185547 time for calcul the mask position with numpy : 0.028867483139038086 nb_pixel_total : 33706 time to create 1 rle with old method : 0.038536787033081055 time for calcul the mask position with numpy : 0.0299530029296875 nb_pixel_total : 37630 time to create 1 rle with old method : 0.041150569915771484 time for calcul the mask position with numpy : 0.028635501861572266 nb_pixel_total : 11896 time to create 1 rle with old method : 0.013288259506225586 time for calcul the mask position with numpy : 0.028787612915039062 nb_pixel_total : 32159 time to create 1 rle with old method : 0.03529548645019531 time for calcul the mask position with numpy : 0.028855085372924805 nb_pixel_total : 6642 time to create 1 rle with old method : 0.007367372512817383 time for calcul the mask position with numpy : 0.02843785285949707 nb_pixel_total : 9621 time to create 1 rle with old method : 0.010753870010375977 time for calcul the mask position with numpy : 0.02845597267150879 nb_pixel_total : 24419 time to create 1 rle with old method : 0.027286529541015625 time for calcul the mask position with numpy : 0.028561115264892578 nb_pixel_total : 49348 time to create 1 rle with old method : 0.05394411087036133 time for calcul the mask position with numpy : 0.02869105339050293 nb_pixel_total : 8342 time to create 1 rle with old method : 0.009130477905273438 time for calcul the mask position with numpy : 0.027980566024780273 nb_pixel_total : 20441 time to create 1 rle with old method : 0.021713972091674805 time for calcul the mask position with numpy : 0.027942657470703125 nb_pixel_total : 17921 time to create 1 rle with old method : 0.019591808319091797 time for calcul the mask position with numpy : 0.028876066207885742 nb_pixel_total : 26954 time to create 1 rle with old method : 0.030536651611328125 time for calcul the mask position with numpy : 0.030252933502197266 nb_pixel_total : 170 time to create 1 rle with old method : 0.00037741661071777344 time for calcul the mask position with numpy : 0.03338789939880371 nb_pixel_total : 10630 time to create 1 rle with old method : 0.011957406997680664 time for calcul the mask position with numpy : 0.029113292694091797 nb_pixel_total : 21543 time to create 1 rle with old method : 0.025147438049316406 time for calcul the mask position with numpy : 0.029369831085205078 nb_pixel_total : 13085 time to create 1 rle with old method : 0.014734983444213867 time for calcul the mask position with numpy : 0.029865741729736328 nb_pixel_total : 150082 time to create 1 rle with new method : 0.6640143394470215 time for calcul the mask position with numpy : 0.027660608291625977 nb_pixel_total : 16557 time to create 1 rle with old method : 0.017661571502685547 time for calcul the mask position with numpy : 0.028753042221069336 nb_pixel_total : 16664 time to create 1 rle with old method : 0.017927885055541992 time for calcul the mask position with numpy : 0.028606891632080078 nb_pixel_total : 58202 time to create 1 rle with old method : 0.06347823143005371 time for calcul the mask position with numpy : 0.02799391746520996 nb_pixel_total : 22627 time to create 1 rle with old method : 0.02381277084350586 time for calcul the mask position with numpy : 0.02762889862060547 nb_pixel_total : 14110 time to create 1 rle with old method : 0.015233039855957031 time for calcul the mask position with numpy : 0.026907682418823242 nb_pixel_total : 4198 time to create 1 rle with old method : 0.004347801208496094 time for calcul the mask position with numpy : 0.027251720428466797 nb_pixel_total : 35749 time to create 1 rle with old method : 0.039220571517944336 time for calcul the mask position with numpy : 0.027913808822631836 nb_pixel_total : 19569 time to create 1 rle with old method : 0.021138906478881836 time for calcul the mask position with numpy : 0.027491331100463867 nb_pixel_total : 9075 time to create 1 rle with old method : 0.009440422058105469 time for calcul the mask position with numpy : 0.027472257614135742 nb_pixel_total : 36940 time to create 1 rle with old method : 0.04027557373046875 time for calcul the mask position with numpy : 0.027760028839111328 nb_pixel_total : 8319 time to create 1 rle with old method : 0.009301185607910156 time for calcul the mask position with numpy : 0.027485370635986328 nb_pixel_total : 14364 time to create 1 rle with old method : 0.015212535858154297 time for calcul the mask position with numpy : 0.027067899703979492 nb_pixel_total : 23481 time to create 1 rle with old method : 0.024500608444213867 time for calcul the mask position with numpy : 0.027898550033569336 nb_pixel_total : 63375 time to create 1 rle with old method : 0.0673670768737793 time for calcul the mask position with numpy : 0.028500795364379883 nb_pixel_total : 29033 time to create 1 rle with old method : 0.03222179412841797 time for calcul the mask position with numpy : 0.027101755142211914 nb_pixel_total : 7952 time to create 1 rle with old method : 0.008644819259643555 create new chi : 7.467782020568848 time to delete rle : 0.004540920257568359 batch 1 Loaded 138 chid ids of type : 3594 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 32236 TO DO : save crop sub photo not yet done ! save time : 2.3049919605255127 nb_obj : 70 nb_hashtags : 4 time to prepare the origin masks : 4.705564498901367 time for calcul the mask position with numpy : 1.4209637641906738 nb_pixel_total : 5530032 time to create 1 rle with new method : 1.3367810249328613 time for calcul the mask position with numpy : 0.028507232666015625 nb_pixel_total : 31182 time to create 1 rle with old method : 0.033071279525756836 time for calcul the mask position with numpy : 0.027314186096191406 nb_pixel_total : 46795 time to create 1 rle with old method : 0.06454753875732422 time for calcul the mask position with numpy : 0.03283810615539551 nb_pixel_total : 16815 time to create 1 rle with old method : 0.020591259002685547 time for calcul the mask position with numpy : 0.027399301528930664 nb_pixel_total : 20274 time to create 1 rle with old method : 0.021489620208740234 time for calcul the mask position with numpy : 0.02883601188659668 nb_pixel_total : 6119 time to create 1 rle with old method : 0.006908416748046875 time for calcul the mask position with numpy : 0.02955794334411621 nb_pixel_total : 59732 time to create 1 rle with old method : 0.06349015235900879 time for calcul the mask position with numpy : 0.0285036563873291 nb_pixel_total : 10944 time to create 1 rle with old method : 0.011930704116821289 time for calcul the mask position with numpy : 0.027825117111206055 nb_pixel_total : 30065 time to create 1 rle with old method : 0.032300472259521484 time for calcul the mask position with numpy : 0.02844548225402832 nb_pixel_total : 37594 time to create 1 rle with old method : 0.040769338607788086 time for calcul the mask position with numpy : 0.027248382568359375 nb_pixel_total : 49398 time to create 1 rle with old method : 0.054326534271240234 time for calcul the mask position with numpy : 0.027755022048950195 nb_pixel_total : 39945 time to create 1 rle with old method : 0.04181385040283203 time for calcul the mask position with numpy : 0.027310609817504883 nb_pixel_total : 15014 time to create 1 rle with old method : 0.015577316284179688 time for calcul the mask position with numpy : 0.028059005737304688 nb_pixel_total : 15227 time to create 1 rle with old method : 0.016289234161376953 time for calcul the mask position with numpy : 0.02761077880859375 nb_pixel_total : 25327 time to create 1 rle with old method : 0.027735233306884766 time for calcul the mask position with numpy : 0.02840566635131836 nb_pixel_total : 137 time to create 1 rle with old method : 0.0003120899200439453 time for calcul the mask position with numpy : 0.027706146240234375 nb_pixel_total : 34063 time to create 1 rle with old method : 0.03519916534423828 time for calcul the mask position with numpy : 0.029569387435913086 nb_pixel_total : 9097 time to create 1 rle with old method : 0.010184526443481445 time for calcul the mask position with numpy : 0.027727603912353516 nb_pixel_total : 10421 time to create 1 rle with old method : 0.01106405258178711 time for calcul the mask position with numpy : 0.027810096740722656 nb_pixel_total : 21460 time to create 1 rle with old method : 0.02342534065246582 time for calcul the mask position with numpy : 0.02777552604675293 nb_pixel_total : 20183 time to create 1 rle with old method : 0.022007465362548828 time for calcul the mask position with numpy : 0.027935266494750977 nb_pixel_total : 33165 time to create 1 rle with old method : 0.03463912010192871 time for calcul the mask position with numpy : 0.028875112533569336 nb_pixel_total : 20066 time to create 1 rle with old method : 0.02228832244873047 time for calcul the mask position with numpy : 0.028444290161132812 nb_pixel_total : 15602 time to create 1 rle with old method : 0.01894545555114746 time for calcul the mask position with numpy : 0.02838420867919922 nb_pixel_total : 16084 time to create 1 rle with old method : 0.017362117767333984 time for calcul the mask position with numpy : 0.027974843978881836 nb_pixel_total : 33188 time to create 1 rle with old method : 0.03618335723876953 time for calcul the mask position with numpy : 0.02933669090270996 nb_pixel_total : 39959 time to create 1 rle with old method : 0.044382572174072266 time for calcul the mask position with numpy : 0.02911686897277832 nb_pixel_total : 33075 time to create 1 rle with old method : 0.036829471588134766 time for calcul the mask position with numpy : 0.028356075286865234 nb_pixel_total : 26751 time to create 1 rle with old method : 0.028832197189331055 time for calcul the mask position with numpy : 0.027590274810791016 nb_pixel_total : 12694 time to create 1 rle with old method : 0.013399124145507812 time for calcul the mask position with numpy : 0.027769088745117188 nb_pixel_total : 22387 time to create 1 rle with old method : 0.024483680725097656 time for calcul the mask position with numpy : 0.028160810470581055 nb_pixel_total : 21474 time to create 1 rle with old method : 0.022913217544555664 time for calcul the mask position with numpy : 0.027485370635986328 nb_pixel_total : 52883 time to create 1 rle with old method : 0.07073688507080078 time for calcul the mask position with numpy : 0.03306770324707031 nb_pixel_total : 52748 time to create 1 rle with old method : 0.05850362777709961 time for calcul the mask position with numpy : 0.027414560317993164 nb_pixel_total : 29019 time to create 1 rle with old method : 0.03256082534790039 time for calcul the mask position with numpy : 0.028027772903442383 nb_pixel_total : 29321 time to create 1 rle with old method : 0.03179001808166504 time for calcul the mask position with numpy : 0.028343677520751953 nb_pixel_total : 30369 time to create 1 rle with old method : 0.03318333625793457 time for calcul the mask position with numpy : 0.027638673782348633 nb_pixel_total : 20778 time to create 1 rle with old method : 0.0223386287689209 time for calcul the mask position with numpy : 0.028565645217895508 nb_pixel_total : 47248 time to create 1 rle with old method : 0.05263495445251465 time for calcul the mask position with numpy : 0.028283357620239258 nb_pixel_total : 24890 time to create 1 rle with old method : 0.02711009979248047 time for calcul the mask position with numpy : 0.02798295021057129 nb_pixel_total : 850 time to create 1 rle with old method : 0.001271963119506836 time for calcul the mask position with numpy : 0.027693748474121094 nb_pixel_total : 30706 time to create 1 rle with old method : 0.032724618911743164 time for calcul the mask position with numpy : 0.026597261428833008 nb_pixel_total : 20538 time to create 1 rle with old method : 0.022302865982055664 time for calcul the mask position with numpy : 0.02731776237487793 nb_pixel_total : 3027 time to create 1 rle with old method : 0.003336668014526367 time for calcul the mask position with numpy : 0.027051448822021484 nb_pixel_total : 10460 time to create 1 rle with old method : 0.011110782623291016 time for calcul the mask position with numpy : 0.026513099670410156 nb_pixel_total : 8837 time to create 1 rle with old method : 0.009276151657104492 time for calcul the mask position with numpy : 0.027726173400878906 nb_pixel_total : 115227 time to create 1 rle with old method : 0.11994647979736328 time for calcul the mask position with numpy : 0.027943134307861328 nb_pixel_total : 8941 time to create 1 rle with old method : 0.009486913681030273 time for calcul the mask position with numpy : 0.027489900588989258 nb_pixel_total : 5577 time to create 1 rle with old method : 0.006271839141845703 time for calcul the mask position with numpy : 0.028472900390625 nb_pixel_total : 16555 time to create 1 rle with old method : 0.01728367805480957 time for calcul the mask position with numpy : 0.026960372924804688 nb_pixel_total : 13686 time to create 1 rle with old method : 0.01473546028137207 time for calcul the mask position with numpy : 0.02729058265686035 nb_pixel_total : 11329 time to create 1 rle with old method : 0.01235651969909668 time for calcul the mask position with numpy : 0.028641462326049805 nb_pixel_total : 17779 time to create 1 rle with old method : 0.020474910736083984 time for calcul the mask position with numpy : 0.030308961868286133 nb_pixel_total : 20775 time to create 1 rle with old method : 0.026511669158935547 time for calcul the mask position with numpy : 0.02901625633239746 nb_pixel_total : 16069 time to create 1 rle with old method : 0.018027782440185547 time for calcul the mask position with numpy : 0.02863454818725586 nb_pixel_total : 634 time to create 1 rle with old method : 0.0007741451263427734 time for calcul the mask position with numpy : 0.02814483642578125 nb_pixel_total : 6691 time to create 1 rle with old method : 0.007414817810058594 time for calcul the mask position with numpy : 0.028378009796142578 nb_pixel_total : 6388 time to create 1 rle with old method : 0.0071430206298828125 time for calcul the mask position with numpy : 0.028618335723876953 nb_pixel_total : 32605 time to create 1 rle with old method : 0.03545022010803223 time for calcul the mask position with numpy : 0.028530120849609375 nb_pixel_total : 18247 time to create 1 rle with old method : 0.020192384719848633 time for calcul the mask position with numpy : 0.028865337371826172 nb_pixel_total : 34784 time to create 1 rle with old method : 0.03849339485168457 time for calcul the mask position with numpy : 0.028972625732421875 nb_pixel_total : 4490 time to create 1 rle with old method : 0.004954814910888672 time for calcul the mask position with numpy : 0.02750229835510254 nb_pixel_total : 864 time to create 1 rle with old method : 0.0010483264923095703 time for calcul the mask position with numpy : 0.028425216674804688 nb_pixel_total : 4312 time to create 1 rle with old method : 0.004775524139404297 time for calcul the mask position with numpy : 0.027805089950561523 nb_pixel_total : 11800 time to create 1 rle with old method : 0.012990474700927734 time for calcul the mask position with numpy : 0.027909278869628906 nb_pixel_total : 7889 time to create 1 rle with old method : 0.008522748947143555 time for calcul the mask position with numpy : 0.02840733528137207 nb_pixel_total : 5700 time to create 1 rle with old method : 0.0063762664794921875 time for calcul the mask position with numpy : 0.028745412826538086 nb_pixel_total : 4144 time to create 1 rle with old method : 0.004788398742675781 time for calcul the mask position with numpy : 0.02884960174560547 nb_pixel_total : 1453 time to create 1 rle with old method : 0.0015511512756347656 time for calcul the mask position with numpy : 0.028089523315429688 nb_pixel_total : 13024 time to create 1 rle with old method : 0.014478683471679688 time for calcul the mask position with numpy : 0.028614282608032227 nb_pixel_total : 5334 time to create 1 rle with old method : 0.005824565887451172 create new chi : 6.45422625541687 time to delete rle : 0.006862640380859375 batch 1 Loaded 147 chid ids of type : 3594 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 28488 TO DO : save crop sub photo not yet done ! save time : 1.929441213607788 map_output_result : {1349346061: (0.0, 'Should be the crop_list due to order', 0), 1349346025: (0.0, 'Should be the crop_list due to order', 0), 1349346023: (0.0, 'Should be the crop_list due to order', 0), 1349345767: (0.0, 'Should be the crop_list due to order', 0), 1349345764: (0.0, 'Should be the crop_list due to order', 0), 1349345708: (0.0, 'Should be the crop_list due to order', 0), 1349345704: (0.0, 'Should be the crop_list due to order', 0), 1349345700: (0.0, 'Should be the crop_list due to order', 0), 1349345661: (0.0, 'Should be the crop_list due to order', 0), 1349296605: (0.0, 'Should be the crop_list due to order', 0), 1349296574: (0.0, 'Should be the crop_list due to order', 0), 1349296398: (0.0, 'Should be the crop_list due to order', 0), 1349296394: (0.0, 'Should be the crop_list due to order', 0), 1349296389: (0.0, 'Should be the crop_list due to order', 0), 1349296385: (0.0, 'Should be the crop_list due to order', 0), 1349296212: (0.0, 'Should be the crop_list due to order', 0), 1349296210: (0.0, 'Should be the crop_list due to order', 0), 1349296206: (0.0, 'Should be the crop_list due to order', 0), 1349296201: (0.0, 'Should be the crop_list due to order', 0), 1349296194: (0.0, 'Should be the crop_list due to order', 0), 1349296189: (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 [1349346061, 1349346025, 1349346023, 1349345767, 1349345764, 1349345708, 1349345704, 1349345700, 1349345661, 1349296605, 1349296574, 1349296398, 1349296394, 1349296389, 1349296385, 1349296212, 1349296210, 1349296206, 1349296201, 1349296194, 1349296189] Looping around the photos to save general results len do output : 21 /1349346061.Didn't retrieve data . /1349346025.Didn't retrieve data . /1349346023.Didn't retrieve data . /1349345767.Didn't retrieve data . /1349345764.Didn't retrieve data . /1349345708.Didn't retrieve data . /1349345704.Didn't retrieve data . /1349345700.Didn't retrieve data . /1349345661.Didn't retrieve data . /1349296605.Didn't retrieve data . /1349296574.Didn't retrieve data . /1349296398.Didn't retrieve data . /1349296394.Didn't retrieve data . /1349296389.Didn't retrieve data . /1349296385.Didn't retrieve data . /1349296212.Didn't retrieve data . /1349296210.Didn't retrieve data . /1349296206.Didn't retrieve data . /1349296201.Didn't retrieve data . /1349296194.Didn't retrieve data . /1349296189.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, '2714574') ('3318', '21958970', '1349346061', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349346025', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349346023', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349345767', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349345764', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349345708', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349345704', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349345700', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349345661', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296605', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296574', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296398', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296394', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296389', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296385', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296212', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296210', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296206', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296201', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296194', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296189', None, None, None, None, None, '2714574') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 63 time used for this insertion : 0.014673948287963867 save_final save missing photos in datou_result : time spend for datou_step_exec : 259.7950391769409 time spend to save output : 0.01533055305480957 total time spend for step 3 : 259.8103697299957 step4:ventilate_hashtags_in_portfolio Tue Apr 1 22:58:53 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 : 21958970 get user id for portfolio 21958970 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`=21958970 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('autre','pet_fonce','flou','mal_croppe','background','carton','metal','pet_clair','environnement','papier','pehd')) 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`=21958970 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('autre','pet_fonce','flou','mal_croppe','background','carton','metal','pet_clair','environnement','papier','pehd')) AND mptpi.`min_score`=0.5 To do 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`=21958970 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('autre','pet_fonce','flou','mal_croppe','background','carton','metal','pet_clair','environnement','papier','pehd')) AND mptpi.`min_score`=0.5 To do lien utilise dans velours : https://www.fotonower.com/velours/21961007,21961008,21961009,21961010,21961011,21961012,21961013,21961014,21961015,21961016,21961017?tags=autre,pet_fonce,flou,mal_croppe,background,carton,metal,pet_clair,environnement,papier,pehd Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : ventilate_hashtags_in_portfolio we use saveGeneral [1349346061, 1349346025, 1349346023, 1349345767, 1349345764, 1349345708, 1349345704, 1349345700, 1349345661, 1349296605, 1349296574, 1349296398, 1349296394, 1349296389, 1349296385, 1349296212, 1349296210, 1349296206, 1349296201, 1349296194, 1349296189] Looping around the photos to save general results len do output : 1 /21958970. 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, '2714574') ('3318', '21958970', '1349346061', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349346025', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349346023', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349345767', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349345764', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349345708', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349345704', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349345700', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349345661', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296605', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296574', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296398', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296394', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296389', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296385', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296212', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296210', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296206', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296201', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296194', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296189', None, None, None, None, None, '2714574') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 22 time used for this insertion : 0.022682666778564453 save_final save missing photos in datou_result : time spend for datou_step_exec : 0.9274263381958008 time spend to save output : 0.022948503494262695 total time spend for step 4 : 0.9503748416900635 step5:final Tue Apr 1 22:58:54 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 : {1349346061: ('0.23380396911851156',), 1349346025: ('0.23380396911851156',), 1349346023: ('0.23380396911851156',), 1349345767: ('0.23380396911851156',), 1349345764: ('0.23380396911851156',), 1349345708: ('0.23380396911851156',), 1349345704: ('0.23380396911851156',), 1349345700: ('0.23380396911851156',), 1349345661: ('0.23380396911851156',), 1349296605: ('0.23380396911851156',), 1349296574: ('0.23380396911851156',), 1349296398: ('0.23380396911851156',), 1349296394: ('0.23380396911851156',), 1349296389: ('0.23380396911851156',), 1349296385: ('0.23380396911851156',), 1349296212: ('0.23380396911851156',), 1349296210: ('0.23380396911851156',), 1349296206: ('0.23380396911851156',), 1349296201: ('0.23380396911851156',), 1349296194: ('0.23380396911851156',), 1349296189: ('0.23380396911851156',)} new output for save of step final : {1349346061: ('0.23380396911851156',), 1349346025: ('0.23380396911851156',), 1349346023: ('0.23380396911851156',), 1349345767: ('0.23380396911851156',), 1349345764: ('0.23380396911851156',), 1349345708: ('0.23380396911851156',), 1349345704: ('0.23380396911851156',), 1349345700: ('0.23380396911851156',), 1349345661: ('0.23380396911851156',), 1349296605: ('0.23380396911851156',), 1349296574: ('0.23380396911851156',), 1349296398: ('0.23380396911851156',), 1349296394: ('0.23380396911851156',), 1349296389: ('0.23380396911851156',), 1349296385: ('0.23380396911851156',), 1349296212: ('0.23380396911851156',), 1349296210: ('0.23380396911851156',), 1349296206: ('0.23380396911851156',), 1349296201: ('0.23380396911851156',), 1349296194: ('0.23380396911851156',), 1349296189: ('0.23380396911851156',)} [1349346061, 1349346025, 1349346023, 1349345767, 1349345764, 1349345708, 1349345704, 1349345700, 1349345661, 1349296605, 1349296574, 1349296398, 1349296394, 1349296389, 1349296385, 1349296212, 1349296210, 1349296206, 1349296201, 1349296194, 1349296189] Looping around the photos to save general results len do output : 21 /1349346061.Didn't retrieve data . /1349346025.Didn't retrieve data . /1349346023.Didn't retrieve data . /1349345767.Didn't retrieve data . /1349345764.Didn't retrieve data . /1349345708.Didn't retrieve data . /1349345704.Didn't retrieve data . /1349345700.Didn't retrieve data . /1349345661.Didn't retrieve data . /1349296605.Didn't retrieve data . /1349296574.Didn't retrieve data . /1349296398.Didn't retrieve data . /1349296394.Didn't retrieve data . /1349296389.Didn't retrieve data . /1349296385.Didn't retrieve data . /1349296212.Didn't retrieve data . /1349296210.Didn't retrieve data . /1349296206.Didn't retrieve data . /1349296201.Didn't retrieve data . /1349296194.Didn't retrieve data . /1349296189.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, '2714574') ('3318', '21958970', '1349346061', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349346025', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349346023', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349345767', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349345764', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349345708', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349345704', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349345700', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349345661', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296605', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296574', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296398', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296394', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296389', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296385', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296212', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296210', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296206', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296201', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296194', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296189', None, None, None, None, None, '2714574') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 63 time used for this insertion : 0.019449949264526367 save_final save missing photos in datou_result : time spend for datou_step_exec : 0.11217427253723145 time spend to save output : 0.020430803298950195 total time spend for step 5 : 0.13260507583618164 step6:blur_detection Tue Apr 1 22:58:54 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/1743539428_2986256_1349346061_3128c64ff19d4d3f1fb6cbfed9de1394.jpg resize: (2160, 3264) 1349346061 -5.213218713687599 treat image : temp/1743539428_2986256_1349346025_8c247ca07f092ebb8fab31003d5c926c.jpg resize: (2160, 3264) 1349346025 -5.188821028516717 treat image : temp/1743539428_2986256_1349346023_dc3d8b89c0521fd8e035fe0440a4b4ba.jpg resize: (2160, 3264) 1349346023 -7.055629921799791 treat image : temp/1743539428_2986256_1349345767_f3d1f238a88664ffb905a60121e52582.jpg resize: (2160, 3264) 1349345767 -7.050363472763353 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d.jpg resize: (2160, 3264) 1349345764 -5.066881805820806 treat image : temp/1743539428_2986256_1349345708_fefdd8d6a4f839b5449bdbb0f1407f1f.jpg resize: (2160, 3264) 1349345708 -7.086632316005067 treat image : temp/1743539428_2986256_1349345704_3f358a59b620a7026afba8c6ca3befcb.jpg resize: (2160, 3264) 1349345704 -5.923297879881592 treat image : temp/1743539428_2986256_1349345700_579a4f8d194584e7e7928a207b9b852a.jpg resize: (2160, 3264) 1349345700 -5.433244014633328 treat image : temp/1743539428_2986256_1349345661_f3e4f02dee8e5d72bd46fa391322b7d9.jpg resize: (2160, 3264) 1349345661 -5.668371720274745 treat image : temp/1743539428_2986256_1349296605_6de79aca085501698c33406f1c547fbd.jpg resize: (2160, 3264) 1349296605 -5.765564654463542 treat image : temp/1743539428_2986256_1349296574_20872def0aa791d52aa1c8b062439ab5.jpg resize: (2160, 3264) 1349296574 -4.61835610107578 treat image : temp/1743539428_2986256_1349296398_3fd996f28245f7d67f29ee0feace0d17.jpg resize: (2160, 3264) 1349296398 -3.7886068352114375 treat image : temp/1743539428_2986256_1349296394_7d4422d9fa58dcc7a74f15dc6fd88396.jpg resize: (2160, 3264) 1349296394 -3.639972876809175 treat image : temp/1743539428_2986256_1349296389_fad33807bc375d78b66abbe66c1625d1.jpg resize: (2160, 3264) 1349296389 -4.22708573329271 treat image : temp/1743539428_2986256_1349296385_73cadeeb6e94b0eacb6ca7d35ccacff4.jpg resize: (2160, 3264) 1349296385 -6.751002389457053 treat image : temp/1743539428_2986256_1349296212_7b597f3589e4e6e3471d35f7ead1bd93.jpg resize: (2160, 3264) 1349296212 -5.1892629115807045 treat image : temp/1743539428_2986256_1349296210_be53d7dc5adbb63739301bf84412eb67.jpg resize: (2160, 3264) 1349296210 -5.226733871344534 treat image : temp/1743539428_2986256_1349296206_69105ab5502ee7f10fd4863eb143da16.jpg resize: (2160, 3264) 1349296206 -5.481487610066554 treat image : temp/1743539428_2986256_1349296201_3526d2e0a43c7256edd42e1c478ebbdb.jpg resize: (2160, 3264) 1349296201 -4.61693736556437 treat image : temp/1743539428_2986256_1349296194_ff3517a11fb28c75e7d112fc9490a5fd.jpg resize: (2160, 3264) 1349296194 -4.448755402938918 treat image : temp/1743539428_2986256_1349296189_1ca191cbbba234c6123cda854ee4f30c.jpg resize: (2160, 3264) 1349296189 -6.362929622765458 treat image : temp/1743539428_2986256_1349346061_3128c64ff19d4d3f1fb6cbfed9de1394_rle_crop_3743375275_0.png resize: (521, 527) 1349378156 -1.1615342723535433 treat image : temp/1743539428_2986256_1349346061_3128c64ff19d4d3f1fb6cbfed9de1394_rle_crop_3743375320_0.png resize: (135, 159) 1349378157 -1.7854445252986424 treat image : temp/1743539428_2986256_1349346061_3128c64ff19d4d3f1fb6cbfed9de1394_rle_crop_3743375285_0.png resize: (170, 280) 1349378158 -3.0641275577499902 treat image : temp/1743539428_2986256_1349346061_3128c64ff19d4d3f1fb6cbfed9de1394_rle_crop_3743375290_0.png resize: (167, 387) 1349378159 -3.159774289521632 treat image : temp/1743539428_2986256_1349346061_3128c64ff19d4d3f1fb6cbfed9de1394_rle_crop_3743375329_0.png resize: (150, 136) 1349378160 -3.7437303080154782 treat image : temp/1743539428_2986256_1349346061_3128c64ff19d4d3f1fb6cbfed9de1394_rle_crop_3743375276_0.png resize: (260, 225) 1349378161 -2.7890620422910457 treat image : temp/1743539428_2986256_1349346061_3128c64ff19d4d3f1fb6cbfed9de1394_rle_crop_3743375327_0.png resize: (97, 151) 1349378162 -2.5395393964150133 treat image : temp/1743539428_2986256_1349346061_3128c64ff19d4d3f1fb6cbfed9de1394_rle_crop_3743375282_0.png resize: (167, 142) 1349378163 -2.3056807369948897 treat image : temp/1743539428_2986256_1349346061_3128c64ff19d4d3f1fb6cbfed9de1394_rle_crop_3743375305_0.png resize: (229, 127) 1349378164 -2.0488453361722945 treat image : temp/1743539428_2986256_1349346061_3128c64ff19d4d3f1fb6cbfed9de1394_rle_crop_3743375307_0.png resize: (159, 171) 1349378165 -1.6226153226915412 treat image : temp/1743539428_2986256_1349346061_3128c64ff19d4d3f1fb6cbfed9de1394_rle_crop_3743375281_0.png resize: (122, 181) 1349378166 -3.245816198180341 treat image : temp/1743539428_2986256_1349346061_3128c64ff19d4d3f1fb6cbfed9de1394_rle_crop_3743375304_0.png resize: (180, 313) 1349378167 -3.228140775266529 treat image : temp/1743539428_2986256_1349346061_3128c64ff19d4d3f1fb6cbfed9de1394_rle_crop_3743375287_0.png resize: (155, 185) 1349378168 -2.8720035205625187 treat image : temp/1743539428_2986256_1349346061_3128c64ff19d4d3f1fb6cbfed9de1394_rle_crop_3743375279_0.png resize: (230, 89) 1349378169 -1.6869006601282093 treat image : temp/1743539428_2986256_1349346061_3128c64ff19d4d3f1fb6cbfed9de1394_rle_crop_3743375323_0.png resize: (92, 126) 1349378171 -2.54731832262316 treat image : temp/1743539428_2986256_1349346061_3128c64ff19d4d3f1fb6cbfed9de1394_rle_crop_3743375306_0.png resize: (94, 137) 1349378172 -2.87936905892363 treat image : temp/1743539428_2986256_1349346061_3128c64ff19d4d3f1fb6cbfed9de1394_rle_crop_3743375280_0.png resize: (119, 124) 1349378173 -1.6781429738876281 treat image : temp/1743539428_2986256_1349346061_3128c64ff19d4d3f1fb6cbfed9de1394_rle_crop_3743375318_0.png resize: (192, 215) 1349378174 -3.110857763676124 treat image : temp/1743539428_2986256_1349346061_3128c64ff19d4d3f1fb6cbfed9de1394_rle_crop_3743375293_0.png resize: (214, 140) 1349378175 -2.032781021533913 treat image : temp/1743539428_2986256_1349346061_3128c64ff19d4d3f1fb6cbfed9de1394_rle_crop_3743375286_0.png resize: (326, 240) 1349378176 -3.3158208155134083 treat image : temp/1743539428_2986256_1349346061_3128c64ff19d4d3f1fb6cbfed9de1394_rle_crop_3743375297_0.png resize: (138, 217) 1349378177 -3.604262225197867 treat image : temp/1743539428_2986256_1349346061_3128c64ff19d4d3f1fb6cbfed9de1394_rle_crop_3743375300_0.png resize: (144, 44) 1349378178 -1.9002754737966494 treat image : temp/1743539428_2986256_1349346061_3128c64ff19d4d3f1fb6cbfed9de1394_rle_crop_3743375308_0.png resize: (280, 176) 1349378179 -2.4086101951110046 treat image : temp/1743539428_2986256_1349346061_3128c64ff19d4d3f1fb6cbfed9de1394_rle_crop_3743375298_0.png resize: (124, 288) 1349378180 -2.9040308789019496 treat image : temp/1743539428_2986256_1349346061_3128c64ff19d4d3f1fb6cbfed9de1394_rle_crop_3743375322_0.png resize: (123, 111) 1349378181 -2.515486676689163 treat image : temp/1743539428_2986256_1349346061_3128c64ff19d4d3f1fb6cbfed9de1394_rle_crop_3743375309_0.png resize: (151, 51) 1349378182 -1.9698916988704964 treat image : temp/1743539428_2986256_1349346061_3128c64ff19d4d3f1fb6cbfed9de1394_rle_crop_3743375301_0.png resize: (171, 106) 1349378183 -1.764209180938536 treat image : temp/1743539428_2986256_1349346061_3128c64ff19d4d3f1fb6cbfed9de1394_rle_crop_3743375289_0.png resize: (140, 169) 1349378184 -2.650647854864034 treat image : temp/1743539428_2986256_1349346061_3128c64ff19d4d3f1fb6cbfed9de1394_rle_crop_3743375288_0.png resize: (244, 133) 1349378185 -2.91664426934176 treat image : temp/1743539428_2986256_1349346061_3128c64ff19d4d3f1fb6cbfed9de1394_rle_crop_3743375312_0.png resize: (93, 101) 1349378186 -0.5206708158324667 treat image : temp/1743539428_2986256_1349346061_3128c64ff19d4d3f1fb6cbfed9de1394_rle_crop_3743375294_0.png resize: (159, 149) 1349378187 -3.949757854822686 treat image : temp/1743539428_2986256_1349346061_3128c64ff19d4d3f1fb6cbfed9de1394_rle_crop_3743375296_0.png resize: (120, 123) 1349378188 -1.3089001450164508 treat image : temp/1743539428_2986256_1349346061_3128c64ff19d4d3f1fb6cbfed9de1394_rle_crop_3743375313_0.png resize: (464, 451) 1349378189 -3.594806162756106 treat image : temp/1743539428_2986256_1349346061_3128c64ff19d4d3f1fb6cbfed9de1394_rle_crop_3743375295_0.png resize: (99, 269) 1349378190 -2.471936548233807 treat image : temp/1743539428_2986256_1349346061_3128c64ff19d4d3f1fb6cbfed9de1394_rle_crop_3743375303_0.png resize: (229, 432) 1349378191 -2.6455106865866904 treat image : temp/1743539428_2986256_1349346061_3128c64ff19d4d3f1fb6cbfed9de1394_rle_crop_3743375292_0.png resize: (130, 192) 1349378192 -2.5340407588019467 treat image : temp/1743539428_2986256_1349346061_3128c64ff19d4d3f1fb6cbfed9de1394_rle_crop_3743375317_0.png resize: (99, 105) 1349378193 -2.7718320822896465 treat image : temp/1743539428_2986256_1349346061_3128c64ff19d4d3f1fb6cbfed9de1394_rle_crop_3743375325_0.png resize: (243, 187) 1349378194 -3.760884162659551 treat image : temp/1743539428_2986256_1349346061_3128c64ff19d4d3f1fb6cbfed9de1394_rle_crop_3743375283_0.png resize: (407, 218) 1349378195 -3.517651401675706 treat image : temp/1743539428_2986256_1349346061_3128c64ff19d4d3f1fb6cbfed9de1394_rle_crop_3743375315_0.png resize: (189, 307) 1349378196 -3.5668531043579494 treat image : temp/1743539428_2986256_1349346061_3128c64ff19d4d3f1fb6cbfed9de1394_rle_crop_3743375284_0.png resize: (360, 119) 1349378197 -2.528923362846255 treat image : temp/1743539428_2986256_1349346061_3128c64ff19d4d3f1fb6cbfed9de1394_rle_crop_3743375310_0.png resize: (166, 104) 1349378198 -4.200675174604072 treat image : temp/1743539428_2986256_1349346025_8c247ca07f092ebb8fab31003d5c926c_rle_crop_3743375350_0.png resize: (160, 332) 1349378199 -2.0400400318393825 treat image : temp/1743539428_2986256_1349346025_8c247ca07f092ebb8fab31003d5c926c_rle_crop_3743375337_0.png resize: (99, 194) 1349378200 -2.395164512603369 treat image : temp/1743539428_2986256_1349346025_8c247ca07f092ebb8fab31003d5c926c_rle_crop_3743375367_0.png resize: (97, 188) 1349378201 -2.7515819649652067 treat image : temp/1743539428_2986256_1349346025_8c247ca07f092ebb8fab31003d5c926c_rle_crop_3743375364_0.png resize: (72, 97) 1349378202 -2.046702111845248 treat image : temp/1743539428_2986256_1349346025_8c247ca07f092ebb8fab31003d5c926c_rle_crop_3743375332_0.png resize: (284, 268) 1349378203 -3.888070428245216 treat image : temp/1743539428_2986256_1349346025_8c247ca07f092ebb8fab31003d5c926c_rle_crop_3743375358_0.png resize: (99, 188) 1349378204 -0.48805775004365015 treat image : temp/1743539428_2986256_1349346025_8c247ca07f092ebb8fab31003d5c926c_rle_crop_3743375366_0.png resize: (251, 368) 1349378205 -3.690591641239936 treat image : temp/1743539428_2986256_1349346025_8c247ca07f092ebb8fab31003d5c926c_rle_crop_3743375333_0.png resize: (90, 276) 1349378206 -2.698755432257459 treat image : temp/1743539428_2986256_1349346025_8c247ca07f092ebb8fab31003d5c926c_rle_crop_3743375336_0.png resize: (230, 240) 1349378207 -3.2345633586585767 treat image : temp/1743539428_2986256_1349346025_8c247ca07f092ebb8fab31003d5c926c_rle_crop_3743375372_0.png resize: (154, 201) 1349378208 -3.456275770437477 treat image : temp/1743539428_2986256_1349346025_8c247ca07f092ebb8fab31003d5c926c_rle_crop_3743375342_0.png resize: (102, 263) 1349378209 -3.2268124729031364 treat image : temp/1743539428_2986256_1349346025_8c247ca07f092ebb8fab31003d5c926c_rle_crop_3743375348_0.png resize: (232, 282) 1349378210 -4.069572165938159 treat image : temp/1743539428_2986256_1349346025_8c247ca07f092ebb8fab31003d5c926c_rle_crop_3743375362_0.png resize: (251, 164) 1349378211 -3.0722019747273266 treat image : temp/1743539428_2986256_1349346025_8c247ca07f092ebb8fab31003d5c926c_rle_crop_3743375335_0.png resize: (231, 230) 1349378212 -3.1520947832680393 treat image : temp/1743539428_2986256_1349346025_8c247ca07f092ebb8fab31003d5c926c_rle_crop_3743375356_0.png resize: (276, 257) 1349378213 -3.521095185147019 treat image : temp/1743539428_2986256_1349346025_8c247ca07f092ebb8fab31003d5c926c_rle_crop_3743375347_0.png resize: (215, 391) 1349378214 -4.702201881280729 treat image : temp/1743539428_2986256_1349346025_8c247ca07f092ebb8fab31003d5c926c_rle_crop_3743375365_0.png resize: (220, 304) 1349378215 -4.002007477196146 treat image : temp/1743539428_2986256_1349346025_8c247ca07f092ebb8fab31003d5c926c_rle_crop_3743375353_0.png resize: (86, 67) 1349378216 -3.967684776567278 treat image : temp/1743539428_2986256_1349346025_8c247ca07f092ebb8fab31003d5c926c_rle_crop_3743375352_0.png resize: (362, 209) 1349378217 -3.494851288999719 treat image : temp/1743539428_2986256_1349346025_8c247ca07f092ebb8fab31003d5c926c_rle_crop_3743375349_0.png resize: (210, 374) 1349378219 -2.7990930955723003 treat image : temp/1743539428_2986256_1349346025_8c247ca07f092ebb8fab31003d5c926c_rle_crop_3743375331_0.png resize: (305, 381) 1349378220 -2.645562027078118 treat image : temp/1743539428_2986256_1349346025_8c247ca07f092ebb8fab31003d5c926c_rle_crop_3743375339_0.png resize: (174, 196) 1349378222 -1.5304897620786033 treat image : temp/1743539428_2986256_1349346025_8c247ca07f092ebb8fab31003d5c926c_rle_crop_3743375351_0.png resize: (91, 110) 1349378223 -1.8227484345090335 treat image : temp/1743539428_2986256_1349346025_8c247ca07f092ebb8fab31003d5c926c_rle_crop_3743375334_0.png resize: (131, 131) 1349378224 -1.8238607570355525 treat image : temp/1743539428_2986256_1349346025_8c247ca07f092ebb8fab31003d5c926c_rle_crop_3743375340_0.png resize: (352, 180) 1349378226 -3.2138698505614767 treat image : temp/1743539428_2986256_1349346025_8c247ca07f092ebb8fab31003d5c926c_rle_crop_3743375360_0.png resize: (221, 207) 1349378227 -3.403093374716001 treat image : temp/1743539428_2986256_1349346025_8c247ca07f092ebb8fab31003d5c926c_rle_crop_3743375341_0.png resize: (189, 240) 1349378228 -4.2285307135941474 treat image : temp/1743539428_2986256_1349346025_8c247ca07f092ebb8fab31003d5c926c_rle_crop_3743375369_0.png resize: (65, 140) 1349378230 -1.8154097945083991 treat image : temp/1743539428_2986256_1349346025_8c247ca07f092ebb8fab31003d5c926c_rle_crop_3743375343_0.png resize: (101, 130) 1349378231 -2.45053861226907 treat image : temp/1743539428_2986256_1349346025_8c247ca07f092ebb8fab31003d5c926c_rle_crop_3743375359_0.png resize: (162, 131) 1349378232 -4.429658949075867 treat image : temp/1743539428_2986256_1349346025_8c247ca07f092ebb8fab31003d5c926c_rle_crop_3743375368_0.png resize: (129, 95) 1349378236 -1.045761333757672 treat image : temp/1743539428_2986256_1349346025_8c247ca07f092ebb8fab31003d5c926c_rle_crop_3743375345_0.png resize: (203, 183) 1349378237 -0.8715426247149167 treat image : temp/1743539428_2986256_1349346025_8c247ca07f092ebb8fab31003d5c926c_rle_crop_3743375338_0.png resize: (259, 192) 1349378240 -3.569216874330051 treat image : temp/1743539428_2986256_1349346025_8c247ca07f092ebb8fab31003d5c926c_rle_crop_3743375354_0.png resize: (189, 348) 1349378241 -1.8713241047428038 treat image : temp/1743539428_2986256_1349346025_8c247ca07f092ebb8fab31003d5c926c_rle_crop_3743375371_0.png resize: (236, 485) 1349378243 -2.270541552456259 treat image : 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temp/1743539428_2986256_1349346023_dc3d8b89c0521fd8e035fe0440a4b4ba_rle_crop_3743375384_0.png resize: (290, 121) 1349378256 -2.0212918521402927 treat image : temp/1743539428_2986256_1349346023_dc3d8b89c0521fd8e035fe0440a4b4ba_rle_crop_3743375424_0.png resize: (243, 200) 1349378258 -1.6218038430456527 treat image : temp/1743539428_2986256_1349346023_dc3d8b89c0521fd8e035fe0440a4b4ba_rle_crop_3743375393_0.png resize: (421, 108) 1349378260 -3.072878269535842 treat image : temp/1743539428_2986256_1349346023_dc3d8b89c0521fd8e035fe0440a4b4ba_rle_crop_3743375403_0.png resize: (124, 261) 1349378261 -1.6849936507361374 treat image : temp/1743539428_2986256_1349346023_dc3d8b89c0521fd8e035fe0440a4b4ba_rle_crop_3743375433_0.png resize: (132, 113) 1349378262 -3.073789563857052 treat image : temp/1743539428_2986256_1349346023_dc3d8b89c0521fd8e035fe0440a4b4ba_rle_crop_3743375418_0.png resize: (390, 382) 1349378264 -4.601921899123594 treat image : 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temp/1743539428_2986256_1349345767_f3d1f238a88664ffb905a60121e52582_rle_crop_3743375472_0.png resize: (166, 206) 1349378390 -4.976183546013057 treat image : temp/1743539428_2986256_1349345767_f3d1f238a88664ffb905a60121e52582_rle_crop_3743375456_0.png resize: (428, 370) 1349378392 -4.916847599599541 treat image : temp/1743539428_2986256_1349345767_f3d1f238a88664ffb905a60121e52582_rle_crop_3743375501_0.png resize: (156, 207) 1349378393 -5.686026487117995 treat image : temp/1743539428_2986256_1349345767_f3d1f238a88664ffb905a60121e52582_rle_crop_3743375500_0.png resize: (172, 187) 1349378394 -2.4146260306443286 treat image : temp/1743539428_2986256_1349345767_f3d1f238a88664ffb905a60121e52582_rle_crop_3743375488_0.png resize: (225, 271) 1349378396 -3.6774583086746984 treat image : temp/1743539428_2986256_1349345767_f3d1f238a88664ffb905a60121e52582_rle_crop_3743375457_0.png resize: (277, 497) 1349378397 -4.765941796524197 treat image : temp/1743539428_2986256_1349345767_f3d1f238a88664ffb905a60121e52582_rle_crop_3743375470_0.png resize: (295, 144) 1349378398 -4.8194159028716586 treat image : temp/1743539428_2986256_1349345767_f3d1f238a88664ffb905a60121e52582_rle_crop_3743375485_0.png resize: (175, 406) 1349378400 -5.302448773496512 treat image : temp/1743539428_2986256_1349345767_f3d1f238a88664ffb905a60121e52582_rle_crop_3743375502_0.png resize: (314, 579) 1349378401 -5.912493475973693 treat image : temp/1743539428_2986256_1349345767_f3d1f238a88664ffb905a60121e52582_rle_crop_3743375465_0.png resize: (234, 158) 1349378402 -1.7488271060254057 treat image : temp/1743539428_2986256_1349345767_f3d1f238a88664ffb905a60121e52582_rle_crop_3743375479_0.png resize: (200, 322) 1349378404 -4.954039077500709 treat image : temp/1743539428_2986256_1349345767_f3d1f238a88664ffb905a60121e52582_rle_crop_3743375473_0.png resize: (195, 221) 1349378405 -1.6028697421611289 treat image : temp/1743539428_2986256_1349345767_f3d1f238a88664ffb905a60121e52582_rle_crop_3743375458_0.png resize: (234, 94) 1349378406 -5.224396784026101 treat image : temp/1743539428_2986256_1349345767_f3d1f238a88664ffb905a60121e52582_rle_crop_3743375451_0.png resize: (172, 121) 1349378408 -2.591468235462384 treat image : temp/1743539428_2986256_1349345767_f3d1f238a88664ffb905a60121e52582_rle_crop_3743375468_0.png resize: (140, 157) 1349378409 -4.008793762146568 treat image : temp/1743539428_2986256_1349345767_f3d1f238a88664ffb905a60121e52582_rle_crop_3743375499_0.png resize: (146, 145) 1349378410 -4.139972694755967 treat image : temp/1743539428_2986256_1349345767_f3d1f238a88664ffb905a60121e52582_rle_crop_3743375509_0.png resize: (182, 107) 1349378412 -4.058755776486396 treat image : temp/1743539428_2986256_1349345767_f3d1f238a88664ffb905a60121e52582_rle_crop_3743375463_0.png resize: (139, 121) 1349378413 -5.615082413612591 treat image : temp/1743539428_2986256_1349345767_f3d1f238a88664ffb905a60121e52582_rle_crop_3743375448_0.png resize: (81, 87) 1349378414 -4.199659904375513 treat image : temp/1743539428_2986256_1349345767_f3d1f238a88664ffb905a60121e52582_rle_crop_3743375493_0.png resize: (494, 287) 1349378416 -4.986521374241276 treat image : temp/1743539428_2986256_1349345767_f3d1f238a88664ffb905a60121e52582_rle_crop_3743375495_0.png resize: (76, 61) 1349378418 -4.139816278337405 treat image : temp/1743539428_2986256_1349345767_f3d1f238a88664ffb905a60121e52582_rle_crop_3743375452_0.png resize: (121, 118) 1349378419 -4.2316277507150355 treat image : temp/1743539428_2986256_1349345767_f3d1f238a88664ffb905a60121e52582_rle_crop_3743375459_0.png resize: (111, 105) 1349378421 -5.899597347154032 treat image : temp/1743539428_2986256_1349345767_f3d1f238a88664ffb905a60121e52582_rle_crop_3743375496_0.png resize: (99, 185) 1349378423 -4.236566625029022 treat image : temp/1743539428_2986256_1349345767_f3d1f238a88664ffb905a60121e52582_rle_crop_3743375486_0.png resize: (117, 55) 1349378424 -3.9778137674853733 treat image : temp/1743539428_2986256_1349345767_f3d1f238a88664ffb905a60121e52582_rle_crop_3743375478_0.png resize: (327, 509) 1349378427 -3.7336869356519324 treat image : temp/1743539428_2986256_1349345767_f3d1f238a88664ffb905a60121e52582_rle_crop_3743375455_0.png resize: (202, 230) 1349378429 -5.101039475580974 treat image : temp/1743539428_2986256_1349345767_f3d1f238a88664ffb905a60121e52582_rle_crop_3743375513_0.png resize: (170, 279) 1349378431 -3.408935560750845 treat image : temp/1743539428_2986256_1349345767_f3d1f238a88664ffb905a60121e52582_rle_crop_3743375505_0.png resize: (77, 97) 1349378432 -2.1058543826505773 treat image : temp/1743539428_2986256_1349345767_f3d1f238a88664ffb905a60121e52582_rle_crop_3743375462_0.png resize: (181, 222) 1349378435 -4.466405814225217 treat image : temp/1743539428_2986256_1349345767_f3d1f238a88664ffb905a60121e52582_rle_crop_3743375483_0.png resize: (189, 239) 1349378437 -4.3569084028831435 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d_rle_crop_3743375556_0.png resize: (171, 205) 1349378438 -1.7456638283752346 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d_rle_crop_3743375521_0.png resize: (248, 242) 1349378440 -3.209301625640283 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d_rle_crop_3743375519_0.png resize: (304, 185) 1349378442 -2.899869702069563 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d_rle_crop_3743375530_0.png resize: (203, 154) 1349378443 -2.558584849967545 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d_rle_crop_3743375552_0.png resize: (406, 332) 1349378445 -2.2726196880914964 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d_rle_crop_3743375527_0.png resize: (140, 188) 1349378447 -2.143120894043423 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d_rle_crop_3743375515_0.png resize: (204, 296) 1349378448 -2.3840396136610473 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d_rle_crop_3743375542_0.png resize: (177, 170) 1349378450 -1.5283273456221678 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d_rle_crop_3743375543_0.png resize: (431, 464) 1349378452 -3.8078421231254973 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d_rle_crop_3743375517_0.png resize: (220, 290) 1349378454 -2.222371846027953 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d_rle_crop_3743375567_0.png resize: (179, 152) 1349378455 -2.758833503160708 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d_rle_crop_3743375560_0.png resize: (121, 148) 1349378457 -1.3756441887938575 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d_rle_crop_3743375564_0.png resize: (294, 251) 1349378459 -2.8753963317383717 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d_rle_crop_3743375532_0.png resize: (218, 266) 1349378460 -3.4489928085843045 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d_rle_crop_3743375565_0.png resize: (174, 57) 1349378462 -1.4381358501282302 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d_rle_crop_3743375536_0.png resize: (154, 90) 1349378465 -2.5663740292255572 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d_rle_crop_3743375566_0.png resize: (135, 170) 1349378466 -4.969325308162029 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d_rle_crop_3743375559_0.png resize: (221, 176) 1349378469 -4.517998486224913 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d_rle_crop_3743375518_0.png resize: (166, 126) 1349378470 -1.6387621706018702 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d_rle_crop_3743375551_0.png resize: (209, 420) 1349378471 -3.244869594746929 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d_rle_crop_3743375526_0.png resize: (340, 142) 1349378473 -3.3744103185021603 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d_rle_crop_3743375546_0.png resize: (124, 250) 1349378474 -2.090780435718476 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d_rle_crop_3743375547_0.png resize: (120, 125) 1349378475 -2.2747539928684555 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d_rle_crop_3743375558_0.png resize: (120, 96) 1349378478 -2.173789041437206 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d_rle_crop_3743375537_0.png resize: (60, 114) 1349378479 -0.8810132780628861 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d_rle_crop_3743375541_0.png resize: (148, 403) 1349378480 -2.5744100872752753 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d_rle_crop_3743375540_0.png resize: (141, 134) 1349378482 -3.798933901228526 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d_rle_crop_3743375548_0.png resize: (215, 276) 1349378483 -4.681841263518733 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d_rle_crop_3743375531_0.png resize: (316, 586) 1349378484 -3.340430654373001 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d_rle_crop_3743375561_0.png resize: (86, 129) 1349378486 -1.5052368614576237 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d_rle_crop_3743375549_0.png resize: (250, 261) 1349378487 -3.0842347813408657 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d_rle_crop_3743375520_0.png resize: (137, 98) 1349378488 -1.7731910948938259 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d_rle_crop_3743375557_0.png resize: (124, 112) 1349378490 -3.1253951292279454 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d_rle_crop_3743375553_0.png resize: (89, 84) 1349378491 -0.619844343320875 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d_rle_crop_3743375516_0.png resize: (276, 187) 1349378492 -3.1927021025339815 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d_rle_crop_3743375569_0.png resize: (95, 113) 1349378494 -2.0061068909215467 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d_rle_crop_3743375529_0.png resize: (172, 267) 1349378495 -2.0187217797254866 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d_rle_crop_3743375524_0.png resize: (309, 315) 1349378499 -3.8904241169723925 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d_rle_crop_3743375538_0.png resize: (219, 185) 1349378500 -3.843074121408561 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d_rle_crop_3743375545_0.png resize: (61, 40) 1349378502 -0.9010471321268532 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d_rle_crop_3743375555_0.png resize: (206, 144) 1349378503 -4.240752782233851 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d_rle_crop_3743375533_0.png resize: (133, 125) 1349378504 -2.399359777233251 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d_rle_crop_3743375562_0.png resize: (125, 114) 1349378506 -1.0821882252811725 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d_rle_crop_3743375554_0.png resize: (175, 108) 1349378507 -3.792969029222629 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d_rle_crop_3743375522_0.png resize: (415, 96) 1349378510 -3.6069718984362518 treat image : temp/1743539428_2986256_1349345764_2e4610abd802a4138d9a1ea23c445f2d_rle_crop_3743375539_0.png resize: (221, 90) 1349378511 -3.251643934380736 treat image : temp/1743539428_2986256_1349345708_fefdd8d6a4f839b5449bdbb0f1407f1f_rle_crop_3743375623_0.png resize: (190, 273) 1349378512 -3.3505299663170938 treat image : temp/1743539428_2986256_1349345708_fefdd8d6a4f839b5449bdbb0f1407f1f_rle_crop_3743375603_0.png resize: (128, 341) 1349378513 -3.5477894187672225 treat image : temp/1743539428_2986256_1349345708_fefdd8d6a4f839b5449bdbb0f1407f1f_rle_crop_3743375613_0.png resize: (371, 395) 1349378514 -3.379848953604478 treat image : temp/1743539428_2986256_1349345708_fefdd8d6a4f839b5449bdbb0f1407f1f_rle_crop_3743375598_0.png resize: (176, 187) 1349378515 -3.5652781553641955 treat image : temp/1743539428_2986256_1349345708_fefdd8d6a4f839b5449bdbb0f1407f1f_rle_crop_3743375612_0.png resize: (147, 287) 1349378516 -2.0437974626205837 treat image : temp/1743539428_2986256_1349345708_fefdd8d6a4f839b5449bdbb0f1407f1f_rle_crop_3743375572_0.png resize: (137, 140) 1349378517 -3.3967335863737977 treat image : temp/1743539428_2986256_1349345708_fefdd8d6a4f839b5449bdbb0f1407f1f_rle_crop_3743375577_0.png resize: (273, 254) 1349378518 -4.237251992449113 treat image : 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temp/1743539428_2986256_1349345700_579a4f8d194584e7e7928a207b9b852a_rle_crop_3743375710_0.png resize: (305, 224) 1349378650 -1.195169093877042 treat image : temp/1743539428_2986256_1349345700_579a4f8d194584e7e7928a207b9b852a_rle_crop_3743375687_0.png resize: (207, 145) 1349378651 -3.229384715412929 treat image : temp/1743539428_2986256_1349345700_579a4f8d194584e7e7928a207b9b852a_rle_crop_3743375723_0.png resize: (232, 287) 1349378652 -3.110650893067023 treat image : temp/1743539428_2986256_1349345700_579a4f8d194584e7e7928a207b9b852a_rle_crop_3743375717_0.png resize: (134, 138) 1349378653 -2.73178072644956 treat image : temp/1743539428_2986256_1349345700_579a4f8d194584e7e7928a207b9b852a_rle_crop_3743375691_0.png resize: (248, 256) 1349378654 -3.313096219537383 treat image : temp/1743539428_2986256_1349345700_579a4f8d194584e7e7928a207b9b852a_rle_crop_3743375743_0.png resize: (127, 209) 1349378655 -3.504251159789559 treat image : temp/1743539428_2986256_1349345700_579a4f8d194584e7e7928a207b9b852a_rle_crop_3743375728_0.png resize: (308, 364) 1349378656 -4.076360150280084 treat image : temp/1743539428_2986256_1349345700_579a4f8d194584e7e7928a207b9b852a_rle_crop_3743375729_0.png resize: (215, 188) 1349378657 -3.0862954810780843 treat image : temp/1743539428_2986256_1349345700_579a4f8d194584e7e7928a207b9b852a_rle_crop_3743375751_0.png resize: (244, 176) 1349378658 -3.619317378685909 treat image : temp/1743539428_2986256_1349345700_579a4f8d194584e7e7928a207b9b852a_rle_crop_3743375714_0.png resize: (82, 98) 1349378659 -2.9733240140888904 treat image : temp/1743539428_2986256_1349345700_579a4f8d194584e7e7928a207b9b852a_rle_crop_3743375711_0.png resize: (243, 133) 1349378660 -3.639484936388343 treat image : temp/1743539428_2986256_1349345700_579a4f8d194584e7e7928a207b9b852a_rle_crop_3743375741_0.png resize: (89, 122) 1349378661 -2.8007459060636397 treat image : temp/1743539428_2986256_1349345700_579a4f8d194584e7e7928a207b9b852a_rle_crop_3743375697_0.png resize: (227, 169) 1349378662 -3.3303015528147792 treat image : temp/1743539428_2986256_1349345700_579a4f8d194584e7e7928a207b9b852a_rle_crop_3743375688_0.png resize: (124, 94) 1349378663 -3.004734382721676 treat image : temp/1743539428_2986256_1349345700_579a4f8d194584e7e7928a207b9b852a_rle_crop_3743375716_0.png resize: (328, 245) 1349378664 -3.6850960413125557 treat image : temp/1743539428_2986256_1349345700_579a4f8d194584e7e7928a207b9b852a_rle_crop_3743375733_0.png resize: (189, 184) 1349378665 -3.938282497749667 treat image : temp/1743539428_2986256_1349345700_579a4f8d194584e7e7928a207b9b852a_bib_crop_3743375703_0.jpg resize: (81, 81) 1349378666 -2.0626232144941072 treat image : temp/1743539428_2986256_1349345700_579a4f8d194584e7e7928a207b9b852a_rle_crop_3743375698_0.png resize: (90, 133) 1349378667 -3.87468508862533 treat image : temp/1743539428_2986256_1349345700_579a4f8d194584e7e7928a207b9b852a_rle_crop_3743375737_0.png resize: (160, 133) 1349378668 -3.698568798646833 treat image : temp/1743539428_2986256_1349345700_579a4f8d194584e7e7928a207b9b852a_rle_crop_3743375742_0.png resize: (142, 139) 1349378669 -2.3724773832877863 treat image : temp/1743539428_2986256_1349345700_579a4f8d194584e7e7928a207b9b852a_rle_crop_3743375701_0.png resize: (86, 72) 1349378670 -2.8888668450483417 treat image : temp/1743539428_2986256_1349345700_579a4f8d194584e7e7928a207b9b852a_rle_crop_3743375700_0.png resize: (280, 160) 1349378671 -3.3946655134117276 treat image : temp/1743539428_2986256_1349345700_579a4f8d194584e7e7928a207b9b852a_rle_crop_3743375707_0.png resize: (132, 84) 1349378672 -3.478276419848011 treat image : temp/1743539428_2986256_1349345700_579a4f8d194584e7e7928a207b9b852a_rle_crop_3743375736_0.png resize: (120, 284) 1349378673 -3.285024716177353 treat image : temp/1743539428_2986256_1349345700_579a4f8d194584e7e7928a207b9b852a_rle_crop_3743375708_0.png resize: (97, 84) 1349378674 -2.798339279484153 treat image : temp/1743539428_2986256_1349345700_579a4f8d194584e7e7928a207b9b852a_rle_crop_3743375722_0.png resize: (177, 178) 1349378675 -1.9339695113502426 treat image : temp/1743539428_2986256_1349345700_579a4f8d194584e7e7928a207b9b852a_rle_crop_3743375735_0.png resize: (158, 231) 1349378677 -3.56883901764523 treat image : temp/1743539428_2986256_1349345700_579a4f8d194584e7e7928a207b9b852a_rle_crop_3743375709_0.png resize: (97, 88) 1349378678 -1.20916029340879 treat image : temp/1743539428_2986256_1349345700_579a4f8d194584e7e7928a207b9b852a_rle_crop_3743375713_0.png resize: (140, 204) 1349378679 -4.074186000237527 treat image : temp/1743539428_2986256_1349345700_579a4f8d194584e7e7928a207b9b852a_rle_crop_3743375746_0.png resize: (116, 174) 1349378680 -4.04343580573745 treat image : temp/1743539428_2986256_1349345700_579a4f8d194584e7e7928a207b9b852a_rle_crop_3743375724_0.png resize: (92, 93) 1349378682 -2.7406754688123613 treat image : temp/1743539428_2986256_1349345700_579a4f8d194584e7e7928a207b9b852a_rle_crop_3743375712_0.png resize: (182, 152) 1349378683 -3.419339180677759 treat image : temp/1743539428_2986256_1349345700_579a4f8d194584e7e7928a207b9b852a_rle_crop_3743375732_0.png resize: (309, 218) 1349378684 -3.205389562133219 treat image : temp/1743539428_2986256_1349345700_579a4f8d194584e7e7928a207b9b852a_rle_crop_3743375690_0.png resize: (91, 104) 1349378686 -2.0121665157634196 treat image : temp/1743539428_2986256_1349345661_f3e4f02dee8e5d72bd46fa391322b7d9_rle_crop_3743375757_0.png resize: (162, 225) 1349378687 -2.9885255620596642 treat image : temp/1743539428_2986256_1349345661_f3e4f02dee8e5d72bd46fa391322b7d9_rle_crop_3743375802_0.png resize: (98, 189) 1349378688 -1.818424153472737 treat image : temp/1743539428_2986256_1349345661_f3e4f02dee8e5d72bd46fa391322b7d9_rle_crop_3743375769_0.png resize: (149, 208) 1349378690 -2.9305146686289203 treat image : temp/1743539428_2986256_1349345661_f3e4f02dee8e5d72bd46fa391322b7d9_rle_crop_3743375770_0.png resize: (284, 289) 1349378691 -3.7952840446528104 treat image : temp/1743539428_2986256_1349345661_f3e4f02dee8e5d72bd46fa391322b7d9_rle_crop_3743375759_0.png resize: (252, 320) 1349378692 -2.8824443405135467 treat image : temp/1743539428_2986256_1349345661_f3e4f02dee8e5d72bd46fa391322b7d9_rle_crop_3743375772_0.png resize: (138, 152) 1349378694 -2.230667252330153 treat image : temp/1743539428_2986256_1349345661_f3e4f02dee8e5d72bd46fa391322b7d9_rle_crop_3743375756_0.png resize: (169, 138) 1349378695 -2.7084110127226033 treat image : temp/1743539428_2986256_1349345661_f3e4f02dee8e5d72bd46fa391322b7d9_rle_crop_3743375771_0.png resize: (98, 90) 1349378696 -3.0407938559263936 treat image : temp/1743539428_2986256_1349345661_f3e4f02dee8e5d72bd46fa391322b7d9_rle_crop_3743375773_0.png resize: (110, 102) 1349378697 -1.9589793128623763 treat image : temp/1743539428_2986256_1349345661_f3e4f02dee8e5d72bd46fa391322b7d9_rle_crop_3743375779_0.png resize: (99, 128) 1349378699 -1.837049627204504 treat image : temp/1743539428_2986256_1349345661_f3e4f02dee8e5d72bd46fa391322b7d9_rle_crop_3743375777_0.png resize: (159, 162) 1349378700 -2.7577011168369476 treat image : temp/1743539428_2986256_1349345661_f3e4f02dee8e5d72bd46fa391322b7d9_rle_crop_3743375778_0.png resize: (181, 199) 1349378701 -2.1075322646813346 treat image : temp/1743539428_2986256_1349345661_f3e4f02dee8e5d72bd46fa391322b7d9_rle_crop_3743375763_0.png resize: (249, 291) 1349378703 -2.476549242872552 treat image : temp/1743539428_2986256_1349345661_f3e4f02dee8e5d72bd46fa391322b7d9_rle_crop_3743375784_0.png resize: (198, 232) 1349378704 -3.9069684619620406 treat image : temp/1743539428_2986256_1349345661_f3e4f02dee8e5d72bd46fa391322b7d9_rle_crop_3743375797_0.png resize: (138, 116) 1349378705 -2.9404966012220313 treat image : temp/1743539428_2986256_1349345661_f3e4f02dee8e5d72bd46fa391322b7d9_rle_crop_3743375774_0.png resize: (150, 305) 1349378707 -1.8567072100653719 treat image : temp/1743539428_2986256_1349345661_f3e4f02dee8e5d72bd46fa391322b7d9_rle_crop_3743375782_0.png resize: (225, 297) 1349378708 -2.8675809251523 treat image : temp/1743539428_2986256_1349345661_f3e4f02dee8e5d72bd46fa391322b7d9_rle_crop_3743375762_0.png resize: (206, 110) 1349378709 -3.982567111996855 treat image : temp/1743539428_2986256_1349345661_f3e4f02dee8e5d72bd46fa391322b7d9_rle_crop_3743375808_0.png resize: (204, 292) 1349378711 -4.617178269333589 treat image : temp/1743539428_2986256_1349345661_f3e4f02dee8e5d72bd46fa391322b7d9_rle_crop_3743375787_0.png resize: (179, 288) 1349378712 -4.2874731160257324 treat image : temp/1743539428_2986256_1349345661_f3e4f02dee8e5d72bd46fa391322b7d9_rle_crop_3743375755_0.png resize: (150, 161) 1349378716 -3.4642987576800786 treat image : temp/1743539428_2986256_1349345661_f3e4f02dee8e5d72bd46fa391322b7d9_rle_crop_3743375764_0.png resize: (124, 148) 1349378720 -3.181630491254575 treat image : temp/1743539428_2986256_1349345661_f3e4f02dee8e5d72bd46fa391322b7d9_rle_crop_3743375792_0.png resize: (397, 465) 1349378725 -2.6309433061670258 treat image : temp/1743539428_2986256_1349345661_f3e4f02dee8e5d72bd46fa391322b7d9_rle_crop_3743375811_0.png resize: (246, 262) 1349378727 -3.020819517835809 treat image : temp/1743539428_2986256_1349345661_f3e4f02dee8e5d72bd46fa391322b7d9_rle_crop_3743375806_0.png resize: (147, 243) 1349378728 -2.360829825426009 treat image : temp/1743539428_2986256_1349345661_f3e4f02dee8e5d72bd46fa391322b7d9_rle_crop_3743375789_0.png resize: (302, 554) 1349378731 -4.017118109669672 treat image : temp/1743539428_2986256_1349345661_f3e4f02dee8e5d72bd46fa391322b7d9_rle_crop_3743375760_0.png resize: (241, 219) 1349378732 -3.7990223327381387 treat image : temp/1743539428_2986256_1349345661_f3e4f02dee8e5d72bd46fa391322b7d9_rle_crop_3743375790_0.png resize: (192, 174) 1349378733 -2.691244081004412 treat image : temp/1743539428_2986256_1349345661_f3e4f02dee8e5d72bd46fa391322b7d9_rle_crop_3743375798_0.png resize: (229, 162) 1349378736 -3.2439253678881768 treat image : temp/1743539428_2986256_1349345661_f3e4f02dee8e5d72bd46fa391322b7d9_rle_crop_3743375767_0.png resize: (199, 259) 1349378737 -3.250571416407778 treat image : temp/1743539428_2986256_1349345661_f3e4f02dee8e5d72bd46fa391322b7d9_rle_crop_3743375761_0.png resize: (235, 200) 1349378738 -5.022032571408595 treat image : temp/1743539428_2986256_1349345661_f3e4f02dee8e5d72bd46fa391322b7d9_rle_crop_3743375786_0.png resize: (154, 85) 1349378741 -2.365643078801407 treat image : 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temp/1743539428_2986256_1349296389_fad33807bc375d78b66abbe66c1625d1_bib_crop_3743063641_0.jpg resize: (332, 302) 1349379123 -4.575277671604183 treat image : temp/1743539428_2986256_1349296389_fad33807bc375d78b66abbe66c1625d1_rle_crop_3743052666_0.png resize: (350, 315) 1349379124 -2.659441747690641 treat image : temp/1743539428_2986256_1349296389_fad33807bc375d78b66abbe66c1625d1_rle_crop_3743052670_0.png resize: (73, 142) 1349379125 -2.6113083276065856 treat image : temp/1743539428_2986256_1349296389_fad33807bc375d78b66abbe66c1625d1_bib_crop_3743063635_0.jpg resize: (72, 141) 1349379126 -1.831322929262245 treat image : temp/1743539428_2986256_1349296389_fad33807bc375d78b66abbe66c1625d1_bib_crop_3743063642_0.jpg resize: (349, 314) 1349379127 -2.0918055317922657 treat image : temp/1743539428_2986256_1349296389_fad33807bc375d78b66abbe66c1625d1_rle_crop_3743052680_0.png resize: (108, 130) 1349379128 -1.7748742130402209 treat image : 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temp/1743539428_2986256_1349296201_3526d2e0a43c7256edd42e1c478ebbdb_rle_crop_3743052957_0.png resize: (111, 129) 1349379659 -3.173350166637833 treat image : temp/1743539428_2986256_1349296201_3526d2e0a43c7256edd42e1c478ebbdb_bib_crop_3743064402_0.jpg resize: (110, 128) 1349379660 -1.1089497637652452 treat image : temp/1743539428_2986256_1349296201_3526d2e0a43c7256edd42e1c478ebbdb_bib_crop_3743064375_0.jpg resize: (291, 319) 1349379661 -0.21786135527907638 treat image : temp/1743539428_2986256_1349296201_3526d2e0a43c7256edd42e1c478ebbdb_rle_crop_3743053011_0.png resize: (96, 91) 1349379663 -3.6006449620110064 treat image : temp/1743539428_2986256_1349296201_3526d2e0a43c7256edd42e1c478ebbdb_bib_crop_3743064406_0.jpg resize: (95, 90) 1349379664 -1.158637239927744 treat image : temp/1743539428_2986256_1349296201_3526d2e0a43c7256edd42e1c478ebbdb_rle_crop_3743052971_0.png resize: (264, 292) 1349379665 -1.9673563182088354 treat image : temp/1743539428_2986256_1349296201_3526d2e0a43c7256edd42e1c478ebbdb_bib_crop_3743064391_0.jpg resize: (263, 291) 1349379667 -0.31258230392590525 treat image : temp/1743539428_2986256_1349296201_3526d2e0a43c7256edd42e1c478ebbdb_rle_crop_3743053004_0.png resize: (371, 313) 1349379668 -3.815312036484605 treat image : temp/1743539428_2986256_1349296201_3526d2e0a43c7256edd42e1c478ebbdb_bib_crop_3743064397_0.jpg resize: (370, 312) 1349379669 -2.3737779582674023 treat image : temp/1743539428_2986256_1349296201_3526d2e0a43c7256edd42e1c478ebbdb_rle_crop_3743052986_0.png resize: (126, 143) 1349379670 -3.9818771819380574 treat image : temp/1743539428_2986256_1349296201_3526d2e0a43c7256edd42e1c478ebbdb_bib_crop_3743064352_0.jpg resize: (125, 142) 1349379672 -3.277357374605257 treat image : temp/1743539428_2986256_1349296201_3526d2e0a43c7256edd42e1c478ebbdb_rle_crop_3743052979_0.png resize: (132, 108) 1349379673 -2.6137656991289737 treat image : temp/1743539428_2986256_1349296201_3526d2e0a43c7256edd42e1c478ebbdb_rle_crop_3743053006_0.png resize: (124, 234) 1349379674 -3.7144308089846176 treat image : temp/1743539428_2986256_1349296201_3526d2e0a43c7256edd42e1c478ebbdb_bib_crop_3743064389_0.jpg resize: (123, 233) 1349379676 -2.3169611043877985 treat image : temp/1743539428_2986256_1349296201_3526d2e0a43c7256edd42e1c478ebbdb_bib_crop_3743064359_0.jpg resize: (131, 107) 1349379677 -2.2916497617708687 treat image : temp/1743539428_2986256_1349296201_3526d2e0a43c7256edd42e1c478ebbdb_rle_crop_3743052966_0.png resize: (164, 128) 1349379678 -1.468781835333296 treat image : temp/1743539428_2986256_1349296201_3526d2e0a43c7256edd42e1c478ebbdb_bib_crop_3743064366_0.jpg resize: (163, 127) 1349379680 1.084159005872046 treat image : temp/1743539428_2986256_1349296201_3526d2e0a43c7256edd42e1c478ebbdb_rle_crop_3743052965_0.png resize: (298, 175) 1349379681 -4.057936238198654 treat image : temp/1743539428_2986256_1349296201_3526d2e0a43c7256edd42e1c478ebbdb_bib_crop_3743064351_0.jpg resize: (297, 174) 1349379682 -3.892241849287774 treat image : temp/1743539428_2986256_1349296201_3526d2e0a43c7256edd42e1c478ebbdb_rle_crop_3743052954_0.png resize: (348, 304) 1349379684 -1.3477201081467929 treat image : temp/1743539428_2986256_1349296201_3526d2e0a43c7256edd42e1c478ebbdb_bib_crop_3743064360_0.jpg resize: (347, 303) 1349379685 -1.1937192046231162 treat image : temp/1743539428_2986256_1349296201_3526d2e0a43c7256edd42e1c478ebbdb_rle_crop_3743052961_0.png resize: (419, 623) 1349379686 -3.459432756857734 treat image : temp/1743539428_2986256_1349296201_3526d2e0a43c7256edd42e1c478ebbdb_rle_crop_3743052962_0.png resize: (187, 197) 1349379688 -3.357331028678652 treat image : temp/1743539428_2986256_1349296201_3526d2e0a43c7256edd42e1c478ebbdb_bib_crop_3743064404_0.jpg resize: (186, 196) 1349379689 -0.7273163619681767 treat image : temp/1743539428_2986256_1349296201_3526d2e0a43c7256edd42e1c478ebbdb_rle_crop_3743052964_0.png resize: (104, 112) 1349379690 -3.035772092785255 treat image : temp/1743539428_2986256_1349296201_3526d2e0a43c7256edd42e1c478ebbdb_bib_crop_3743064353_0.jpg resize: (103, 111) 1349379692 -2.1110301747351157 treat image : temp/1743539428_2986256_1349296201_3526d2e0a43c7256edd42e1c478ebbdb_bib_crop_3743064354_0.jpg resize: (283, 493) 1349379693 -4.339091390107706 treat image : temp/1743539428_2986256_1349296201_3526d2e0a43c7256edd42e1c478ebbdb_rle_crop_3743052989_0.png resize: (261, 115) 1349379694 -3.5034896891346925 treat image : temp/1743539428_2986256_1349296201_3526d2e0a43c7256edd42e1c478ebbdb_bib_crop_3743064350_0.jpg resize: (260, 114) 1349379696 -2.925664236852912 treat image : temp/1743539428_2986256_1349296194_ff3517a11fb28c75e7d112fc9490a5fd_rle_crop_3743053019_0.png resize: (414, 244) 1349379697 -2.160502945603467 treat image : temp/1743539428_2986256_1349296194_ff3517a11fb28c75e7d112fc9490a5fd_rle_crop_3743053044_0.png resize: (238, 242) 1349379698 -2.3947787717386495 treat image : temp/1743539428_2986256_1349296194_ff3517a11fb28c75e7d112fc9490a5fd_bib_crop_3743066335_0.jpg resize: (414, 243) 1349379700 2.319000718480958 treat image : temp/1743539428_2986256_1349296194_ff3517a11fb28c75e7d112fc9490a5fd_bib_crop_3743066364_0.jpg resize: (237, 241) 1349379701 4.075284507656553 treat image : temp/1743539428_2986256_1349296194_ff3517a11fb28c75e7d112fc9490a5fd_rle_crop_3743053031_0.png resize: (353, 138) 1349379702 -1.665974045983011 treat image : temp/1743539428_2986256_1349296194_ff3517a11fb28c75e7d112fc9490a5fd_bib_crop_3743066351_0.jpg resize: (352, 137) 1349379704 4.841813847461498 treat image : temp/1743539428_2986256_1349296194_ff3517a11fb28c75e7d112fc9490a5fd_rle_crop_3743053050_0.png resize: (140, 96) 1349379705 -0.6920607035780002 treat image : temp/1743539428_2986256_1349296194_ff3517a11fb28c75e7d112fc9490a5fd_bib_crop_3743066327_0.jpg resize: (139, 95) 1349379706 5.573356411247227 treat image : temp/1743539428_2986256_1349296194_ff3517a11fb28c75e7d112fc9490a5fd_rle_crop_3743053033_0.png resize: (165, 152) 1349379708 -2.1950180623399187 treat image : temp/1743539428_2986256_1349296194_ff3517a11fb28c75e7d112fc9490a5fd_bib_crop_3743066375_0.jpg resize: (164, 151) 1349379709 9.127686088694146 treat image : temp/1743539428_2986256_1349296194_ff3517a11fb28c75e7d112fc9490a5fd_rle_crop_3743053055_0.png resize: (106, 177) 1349379710 -1.3847169713938572 treat image : temp/1743539428_2986256_1349296194_ff3517a11fb28c75e7d112fc9490a5fd_rle_crop_3743053032_0.png resize: (208, 243) 1349379712 -2.617684236086768 treat image : temp/1743539428_2986256_1349296194_ff3517a11fb28c75e7d112fc9490a5fd_bib_crop_3743066362_0.jpg resize: (207, 242) 1349379713 2.0911150276052664 treat image : temp/1743539428_2986256_1349296194_ff3517a11fb28c75e7d112fc9490a5fd_bib_crop_3743066388_0.jpg resize: (105, 176) 1349379714 5.476644703998506 treat image : temp/1743539428_2986256_1349296194_ff3517a11fb28c75e7d112fc9490a5fd_rle_crop_3743053080_0.png resize: (170, 63) 1349379716 0.7672473187380255 treat image : temp/1743539428_2986256_1349296194_ff3517a11fb28c75e7d112fc9490a5fd_bib_crop_3743066330_0.jpg resize: (168, 62) 1349379717 4.020594495643446 treat image : temp/1743539428_2986256_1349296194_ff3517a11fb28c75e7d112fc9490a5fd_rle_crop_3743053060_0.png resize: (486, 461) 1349379718 -1.5107567030454747 treat image : temp/1743539428_2986256_1349296194_ff3517a11fb28c75e7d112fc9490a5fd_rle_crop_3743053065_0.png resize: (135, 226) 1349379720 -2.0950400234161166 treat image : temp/1743539428_2986256_1349296194_ff3517a11fb28c75e7d112fc9490a5fd_rle_crop_3743053068_0.png resize: (98, 78) 1349379721 -2.938931106428665 treat image : temp/1743539428_2986256_1349296194_ff3517a11fb28c75e7d112fc9490a5fd_bib_crop_3743066382_0.jpg resize: (97, 77) 1349379722 5.642555122861102 treat image : temp/1743539428_2986256_1349296194_ff3517a11fb28c75e7d112fc9490a5fd_rle_crop_3743053015_0.png resize: (216, 272) 1349379724 -2.6481225169925287 treat image : temp/1743539428_2986256_1349296194_ff3517a11fb28c75e7d112fc9490a5fd_bib_crop_3743066346_0.jpg resize: (485, 460) 1349379725 -1.2234760814149852 treat image : temp/1743539428_2986256_1349296194_ff3517a11fb28c75e7d112fc9490a5fd_bib_crop_3743066374_0.jpg resize: (134, 225) 1349379726 20.0 treat image : temp/1743539428_2986256_1349296194_ff3517a11fb28c75e7d112fc9490a5fd_bib_crop_3743066383_0.jpg resize: (215, 271) 1349379728 1.5996439926365114 treat image : temp/1743539428_2986256_1349296194_ff3517a11fb28c75e7d112fc9490a5fd_rle_crop_3743053026_0.png resize: (353, 362) 1349379729 -1.5116697445257183 treat image : 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temp/1743539428_2986256_1349296194_ff3517a11fb28c75e7d112fc9490a5fd_bib_crop_3743066334_0.jpg resize: (238, 287) 1349379738 0.7874105001282564 treat image : temp/1743539428_2986256_1349296194_ff3517a11fb28c75e7d112fc9490a5fd_bib_crop_3743066369_0.jpg resize: (79, 171) 1349379740 1.4721206394681168 treat image : temp/1743539428_2986256_1349296194_ff3517a11fb28c75e7d112fc9490a5fd_rle_crop_3743053074_0.png resize: (80, 172) 1349379741 -2.412661131806493 treat image : temp/1743539428_2986256_1349296194_ff3517a11fb28c75e7d112fc9490a5fd_rle_crop_3743376275_0.png resize: (205, 213) 1349379742 -2.988277390542094 treat image : temp/1743539428_2986256_1349296194_ff3517a11fb28c75e7d112fc9490a5fd_bib_crop_3743066372_0.jpg resize: (203, 213) 1349379744 2.5739529454103383 treat image : temp/1743539428_2986256_1349296194_ff3517a11fb28c75e7d112fc9490a5fd_rle_crop_3743053018_0.png resize: (631, 486) 1349379745 -2.6513865950707114 treat image : 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list_values into class_photo_scores : length of list_valuse in save_photo_hashtag_id_thcl_score : 1730 Catched exception ! Connect or reconnect ! In save_photo_hashtag_id_thcl_score : (1205, 'Lock wait timeout exceeded; try restarting transaction') [('1533', '1349346061', '492609224', '-5.213218713687599'), ('1533', '1349346025', '492609224', '-5.188821028516717'), ('1533', '1349346023', '492609224', '-7.055629921799791'), ('1533', '1349345767', '492609224', '-7.050363472763353'), ('1533', '1349345764', '492609224', '-5.066881805820806'), ('1533', '1349345708', '492609224', '-7.086632316005067'), ('1533', '1349345704', '492609224', '-5.923297879881592'), ('1533', '1349345700', '492609224', '-5.433244014633328'), ('1533', '1349345661', '492609224', '-5.668371720274745'), ('1533', '1349296605', '492609224', '-5.765564654463542'), ('1533', '1349296574', '492609224', '-4.61835610107578'), ('1533', '1349296398', '492609224', '-3.7886068352114375'), ('1533', '1349296394', '492609224', '-3.639972876809175'), ('1533', '1349296389', '492609224', '-4.22708573329271'), ('1533', '1349296385', '492609224', '-6.751002389457053'), ('1533', 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('1533', '1349382788', '492609224', '-3.6232770838962667'), ('1533', '1349382789', '492688767', '-1.4492253830044473'), ('1533', '1349382791', '492688767', '-1.736473617793145'), ('1533', '1349382792', '492688767', '1.8768271661052283'), ('1533', '1349382793', '492609224', '-3.1216340053564005'), ('1533', '1349382795', '492688767', '-1.0940023845673532'), ('1533', '1349382796', '492688767', '-0.4187055298537825'), ('1533', '1349382797', '492688767', '4.493476587962755'), ('1533', '1349382799', '492609224', '-4.247311567243846'), ('1533', '1349382800', '492609224', '-2.317770191586379')] time used for this insertion : 51.439178228378296 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 1730 time used for this insertion : 0.6767287254333496 save missing photos in datou_result : time spend for datou_step_exec : 99.62223267555237 time spend to save output : 52.14373278617859 total time spend for step 6 : 151.76596546173096 step7:brightness Tue Apr 1 23:01:25 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! 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temp/1743539428_2986256_1349296206_69105ab5502ee7f10fd4863eb143da16_rle_crop_3743052942_0.png treat image : temp/1743539428_2986256_1349296206_69105ab5502ee7f10fd4863eb143da16_bib_crop_3743064299_0.jpg treat image : temp/1743539428_2986256_1349296194_ff3517a11fb28c75e7d112fc9490a5fd_rle_crop_3743053049_0.png treat image : temp/1743539428_2986256_1349296194_ff3517a11fb28c75e7d112fc9490a5fd_bib_crop_3743066389_0.jpg treat image : temp/1743539428_2986256_1349296189_1ca191cbbba234c6123cda854ee4f30c_bib_crop_3743066394_0.jpg treat image : temp/1743539428_2986256_1349296189_1ca191cbbba234c6123cda854ee4f30c_rle_crop_3743053116_0.png treat image : temp/1743539428_2986256_1349296189_1ca191cbbba234c6123cda854ee4f30c_rle_crop_3743053104_0.png treat image : temp/1743539428_2986256_1349296189_1ca191cbbba234c6123cda854ee4f30c_bib_crop_3743066395_0.jpg treat image : temp/1743539428_2986256_1349296189_1ca191cbbba234c6123cda854ee4f30c_rle_crop_3743053102_0.png treat image : temp/1743539428_2986256_1349296189_1ca191cbbba234c6123cda854ee4f30c_bib_crop_3743066398_0.jpg treat image : temp/1743539428_2986256_1349296201_3526d2e0a43c7256edd42e1c478ebbdb_rle_crop_3743052987_0.png treat image : temp/1743539428_2986256_1349296201_3526d2e0a43c7256edd42e1c478ebbdb_bib_crop_3743064363_0.jpg treat image : temp/1743539428_2986256_1349346061_3128c64ff19d4d3f1fb6cbfed9de1394_rle_crop_3743375326_0.png treat image : temp/1743539428_2986256_1349345708_fefdd8d6a4f839b5449bdbb0f1407f1f_rle_crop_3743375632_0.png treat image : temp/1743539428_2986256_1349345661_f3e4f02dee8e5d72bd46fa391322b7d9_rle_crop_3743375801_0.png treat image : temp/1743539428_2986256_1349345661_f3e4f02dee8e5d72bd46fa391322b7d9_rle_crop_3743375780_0.png treat image : temp/1743539428_2986256_1349296605_6de79aca085501698c33406f1c547fbd_rle_crop_3743052442_0.png treat image : temp/1743539428_2986256_1349296605_6de79aca085501698c33406f1c547fbd_bib_crop_3743063014_0.jpg treat image : temp/1743539428_2986256_1349296398_3fd996f28245f7d67f29ee0feace0d17_rle_crop_3743052610_0.png treat image : temp/1743539428_2986256_1349296398_3fd996f28245f7d67f29ee0feace0d17_bib_crop_3743063528_0.jpg treat image : temp/1743539428_2986256_1349296398_3fd996f28245f7d67f29ee0feace0d17_rle_crop_3743052616_0.png treat image : temp/1743539428_2986256_1349296398_3fd996f28245f7d67f29ee0feace0d17_bib_crop_3743063561_0.jpg treat image : temp/1743539428_2986256_1349296201_3526d2e0a43c7256edd42e1c478ebbdb_rle_crop_3743053012_0.png treat image : temp/1743539428_2986256_1349296201_3526d2e0a43c7256edd42e1c478ebbdb_bib_crop_3743064371_0.jpg treat image : temp/1743539428_2986256_1349296201_3526d2e0a43c7256edd42e1c478ebbdb_rle_crop_3743375828_0.png treat image : temp/1743539428_2986256_1349296201_3526d2e0a43c7256edd42e1c478ebbdb_bib_crop_3743064362_0.jpg Inside saveOutput : final : False verbose : 0 begin to insert list_values into class_photo_scores : length of list_valuse in save_photo_hashtag_id_thcl_score : 1730 time used for this insertion : 0.13837718963623047 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 1730 time used for this insertion : 0.5738246440887451 save missing photos in datou_result : time spend for datou_step_exec : 31.277397394180298 time spend to save output : 0.7298169136047363 total time spend for step 7 : 32.007214307785034 step8:velours_tree Tue Apr 1 23:01:58 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 : 1.0574517250061035 time spend to save output : 7.128715515136719e-05 total time spend for step 8 : 1.0575230121612549 step9:send_mail_cod Tue Apr 1 23:01:59 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed 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_P21958970_01-04-2025_23_01_59.pdf 21961007 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 .imagette219610071743541319 21961008 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 .imagette219610081743541320 21961009 imagette219610091743541321 21961010 imagette219610101743541321 21961011 imagette219610111743541321 21961012 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 .imagette219610121743541321 21961013 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 .imagette219610131743541322 21961014 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 .imagette219610141743541323 21961016 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 .imagette219610161743541324 21961017 change filename to text .change filename to text .imagette219610171743541326 SELECT h.hashtag,pcr.value FROM MTRUser.portfolio_carac_ratio pcr, MTRBack.hashtags h where pcr.portfolio_id=21958970 and hashtag_type = 3594 and pcr.hashtag_id = h.hashtag_id; velour_link : https://www.fotonower.com/velours/21961007,21961008,21961009,21961010,21961011,21961012,21961013,21961014,21961015,21961016,21961017?tags=autre,pet_fonce,flou,mal_croppe,background,carton,metal,pet_clair,environnement,papier,pehd args[1349346061] : ((1349346061, -5.213218713687599, 492609224), (1349346061, -0.14932735456743143, 496442774), '0.23380396911851156') We are sending mail with results at report@fotonower.com args[1349346025] : ((1349346025, -5.188821028516717, 492609224), (1349346025, -0.088869700595312, 496442774), '0.23380396911851156') We are sending mail with results at report@fotonower.com args[1349346023] : ((1349346023, -7.055629921799791, 492609224), (1349346023, -0.08827061600629922, 496442774), '0.23380396911851156') We are sending mail with results at report@fotonower.com args[1349345767] : ((1349345767, -7.050363472763353, 492609224), (1349345767, -0.07900465232242453, 496442774), '0.23380396911851156') We are sending mail with results at report@fotonower.com args[1349345764] : ((1349345764, -5.066881805820806, 492609224), (1349345764, -0.2022132000222634, 496442774), '0.23380396911851156') We are sending mail with results at report@fotonower.com args[1349345708] : ((1349345708, -7.086632316005067, 492609224), (1349345708, -0.25651988449961705, 496442774), '0.23380396911851156') We are sending mail with results at report@fotonower.com args[1349345704] : ((1349345704, -5.923297879881592, 492609224), (1349345704, 0.06443365720272586, 2107752395), '0.23380396911851156') We are sending mail with results at report@fotonower.com args[1349345700] : ((1349345700, -5.433244014633328, 492609224), (1349345700, -0.15743131779895378, 496442774), '0.23380396911851156') We are sending mail with results at report@fotonower.com args[1349345661] : ((1349345661, -5.668371720274745, 492609224), (1349345661, -0.0959180400573074, 496442774), '0.23380396911851156') We are sending mail with results at report@fotonower.com args[1349296605] : ((1349296605, -5.765564654463542, 492609224), (1349296605, -0.15440340531578484, 496442774), '0.23380396911851156') We are sending mail with results at report@fotonower.com args[1349296574] : ((1349296574, -4.61835610107578, 492609224), (1349296574, -0.09727921499400467, 496442774), '0.23380396911851156') We are sending mail with results at report@fotonower.com args[1349296398] : ((1349296398, -3.7886068352114375, 492609224), (1349296398, -0.0907151229293273, 496442774), '0.23380396911851156') We are sending mail with results at report@fotonower.com args[1349296394] : ((1349296394, -3.639972876809175, 492609224), (1349296394, -0.24922369931961036, 496442774), '0.23380396911851156') We are sending mail with results at report@fotonower.com args[1349296389] : ((1349296389, -4.22708573329271, 492609224), (1349296389, 0.26160921271711485, 2107752395), '0.23380396911851156') We are sending mail with results at report@fotonower.com args[1349296385] : ((1349296385, -6.751002389457053, 492609224), (1349296385, -0.16360334543862298, 496442774), '0.23380396911851156') We are sending mail with results at report@fotonower.com args[1349296212] : ((1349296212, -5.1892629115807045, 492609224), (1349296212, -0.14370098009695623, 496442774), '0.23380396911851156') We are sending mail with results at report@fotonower.com args[1349296210] : ((1349296210, -5.226733871344534, 492609224), (1349296210, -0.08166090912590593, 496442774), '0.23380396911851156') We are sending mail with results at report@fotonower.com args[1349296206] : ((1349296206, -5.481487610066554, 492609224), (1349296206, 0.047094951438126025, 2107752395), '0.23380396911851156') We are sending mail with results at report@fotonower.com args[1349296201] : ((1349296201, -4.61693736556437, 492609224), (1349296201, -0.1654428844523662, 496442774), '0.23380396911851156') We are sending mail with results at report@fotonower.com args[1349296194] : ((1349296194, -4.448755402938918, 492609224), (1349296194, -0.10041320234763723, 496442774), '0.23380396911851156') We are sending mail with results at report@fotonower.com args[1349296189] : ((1349296189, -6.362929622765458, 492609224), (1349296189, -0.2682572403422784, 496442774), '0.23380396911851156') We are sending mail with results at report@fotonower.com refus_total : 0.23380396911851156 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=21958970 AND mpp.hide_status=0 ORDER BY mpp.order LIMIT 0, 1000 SELECT photo_id, url FROM MTRBack.photos ph WHERE photo_id IN (1349296574,1349346061,1349346025,1349346023,1349345767,1349345704,1349345661,1349296605,1349296212,1349296210,1349296206,1349296201,1349296194,1349296394,1349296398,1349296389,1349296385,1349345700,1349345708,1349345764) Found this number of photos: 20 begin to download photo : 1349296574 begin to download photo : 1349345704 begin to download photo : 1349296206 begin to download photo : 1349296389 download finish for photo 1349296206 begin to download photo : 1349296201 download finish for photo 1349296389 begin to download photo : 1349296385 download finish for photo 1349345704 begin to download photo : 1349345661 download finish for photo 1349296574 begin to download photo : 1349346061 download finish for photo 1349296385 begin to download photo : 1349345700 download finish for photo 1349345661 begin to download photo : 1349296605 download finish for photo 1349346061 begin to download photo : 1349346025 download finish for photo 1349345700 begin to download photo : 1349345708 download finish for photo 1349296605 begin to download photo : 1349296212 download finish for photo 1349346025 begin to download photo : 1349346023 download finish for photo 1349345708 begin to download photo : 1349345764 download finish for photo 1349346023 begin to download photo : 1349345767 download finish for photo 1349296212 begin to download photo : 1349296210 download finish for photo 1349345764 download finish for photo 1349296201 begin to download photo : 1349296194 download finish for photo 1349296210 download finish for photo 1349345767 download finish for photo 1349296194 begin to download photo : 1349296394 download finish for photo 1349296394 begin to download photo : 1349296398 download finish for photo 1349296398 start upload file to ovh https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P21958970_01-04-2025_23_01_59.pdf results_Auto_P21958970_01-04-2025_23_01_59.pdf uploaded to url https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P21958970_01-04-2025_23_01_59.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','21958970','results_Auto_P21958970_01-04-2025_23_01_59.pdf','https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P21958970_01-04-2025_23_01_59.pdf','pdf','','1.13','0.23380396911851156') message_in_mail: Bonjour,
Veuillez trouver ci dessous les résultats du service carac on demand pour le portfolio: https://www.fotonower.com/view/21958970

https://www.fotonower.com/image?json=false&list_photos_id=1349346061
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1349346025
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1349346023
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1349345767
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1349345764
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1349345708
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1349345704
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1349345700
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1349345661
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1349296605
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1349296574
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1349296398
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1349296394
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1349296389
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1349296385
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1349296212
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1349296210
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1349296206
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1349296201
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1349296194
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1349296189
Bravo, la photo est bien prise.

Dans ces conditions,le taux de refus est: 23.38%
Veuillez trouver les photos des contaminants.

exemples de contaminants: autre: https://www.fotonower.com/view/21961007?limit=200
exemples de contaminants: pet_fonce: https://www.fotonower.com/view/21961008?limit=200
exemples de contaminants: carton: https://www.fotonower.com/view/21961012?limit=200
exemples de contaminants: metal: https://www.fotonower.com/view/21961013?limit=200
exemples de contaminants: pet_clair: https://www.fotonower.com/view/21961014?limit=200
exemples de contaminants: papier: https://www.fotonower.com/view/21961016?limit=200
exemples de contaminants: pehd: https://www.fotonower.com/view/21961017?limit=200
Veuillez trouver le rapport en pdf:https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P21958970_01-04-2025_23_01_59.pdf.

Lien vers velours :https://www.fotonower.com/velours/21961007,21961008,21961009,21961010,21961011,21961012,21961013,21961014,21961015,21961016,21961017?tags=autre,pet_fonce,flou,mal_croppe,background,carton,metal,pet_clair,environnement,papier,pehd.


L'équipe Fotonower 202 b'' Server: nginx Date: Tue, 01 Apr 2025 21:02:12 GMT Content-Length: 0 Connection: close X-Message-Id: HABsLiteTgy7pdnMjC1tgQ 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 [1349346061, 1349346025, 1349346023, 1349345767, 1349345764, 1349345708, 1349345704, 1349345700, 1349345661, 1349296605, 1349296574, 1349296398, 1349296394, 1349296389, 1349296385, 1349296212, 1349296210, 1349296206, 1349296201, 1349296194, 1349296189] 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, '2714574') ('3318', '21958970', '1349346061', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349346025', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349346023', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349345767', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349345764', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349345708', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349345704', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349345700', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349345661', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296605', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296574', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296398', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296394', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296389', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296385', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296212', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296210', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296206', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296201', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296194', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296189', None, None, None, None, None, '2714574') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 21 time used for this insertion : 0.014688968658447266 save_final save missing photos in datou_result : time spend for datou_step_exec : 12.988515615463257 time spend to save output : 0.01497340202331543 total time spend for step 9 : 13.003489017486572 step10:split_time_score Tue Apr 1 23:02:12 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'}] (('15', 21),) ERROR counted https://github.com/fotonower/Velours/issues/663#issuecomment-421136223 {} 01042025 21958970 Nombre de photos uploadées : 21 / 23040 (0%) 01042025 21958970 Nombre de photos taguées (types de déchets): 0 / 21 (0%) 01042025 21958970 Nombre de photos taguées (volume) : 0 / 21 (0%) elapsed_time : load_data_split_time_score 1.9073486328125e-06 elapsed_time : order_list_meta_photo_and_scores 5.0067901611328125e-06 ????????????????????? elapsed_time : fill_and_build_computed_from_old_data 0.001478433609008789 elapsed_time : insert_dashboard_record_day_entry 0.027790546417236328 We will return after consolidate but for now we need the day, how to get it, for now depending on the previous heavy steps Qualite : 0.19774587565145885 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P21941555_01-04-2025_10_34_21.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 21941555 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`=21941555 AND mptpi.`type`=3594 To do Qualite : 0.10205312159586055 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 21944149 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`=21944149 AND mptpi.`type`=3594 To do Qualite : 0.06586668547792947 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P21943744_01-04-2025_12_02_21.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 21943744 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`=21943744 AND mptpi.`type`=3726 To do Qualite : 0.12964564531795053 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P21958966_01-04-2025_22_12_27.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 21958966 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`=21958966 AND mptpi.`type`=3726 To do Qualite : 0.23380396911851156 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P21958970_01-04-2025_23_01_59.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 21958970 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`=21958970 AND mptpi.`type`=3594 To do Qualite : 0.2497809117136438 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P21958972_01-04-2025_22_39_56.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 21958972 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`=21958972 AND mptpi.`type`=3594 To do find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 21960954 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 21960981 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 21960997 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 21961002 order by id desc limit 1 Qualite : 0.23863599614403855 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P21958982_01-04-2025_22_25_08.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 21958982 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`=21958982 AND mptpi.`type`=3594 To do find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 21961004 order by id desc limit 1 NUMBER BATCH : 0 # DISPLAY ALL COLLECTED DATA : {'01042025': {'nb_upload': 21, '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 [1349346061, 1349346025, 1349346023, 1349345767, 1349345764, 1349345708, 1349345704, 1349345700, 1349345661, 1349296605, 1349296574, 1349296398, 1349296394, 1349296389, 1349296385, 1349296212, 1349296210, 1349296206, 1349296201, 1349296194, 1349296189] Looping around the photos to save general results len do output : 1 /21958970Didn'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, '2714574') ('3318', '21958970', '1349346061', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349346025', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349346023', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349345767', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349345764', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349345708', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349345704', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349345700', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349345661', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296605', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296574', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296398', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296394', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296389', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296385', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296212', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296210', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296206', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296201', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296194', None, None, None, None, None, '2714574') ('3318', None, None, None, None, None, None, None, '2714574') ('3318', '21958970', '1349296189', None, None, None, None, None, '2714574') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 22 time used for this insertion : 0.01883983612060547 save_final save missing photos in datou_result : time spend for datou_step_exec : 5.568053245544434 time spend to save output : 0.019209623336791992 total time spend for step 10 : 5.587262868881226 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) : 21 set_done_treatment 720.29user 327.36system 31:52.58elapsed 54%CPU (0avgtext+0avgdata 9962884maxresident)k 41269912inputs+532952outputs (1381546major+69120642minor)pagefaults 0swaps