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 : 2654573 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 : ['2535942'] with mtr_portfolio_ids : ['20128891'] and first list_photo_ids : [] new path : /proc/2654573/ 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 , BFBFBFBFBFBFBFBFBFBFBFBFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 12 ; length of list_pids : 12 ; length of list_args : 12 time to download the photos : 3.1221349239349365 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : 0 number of steps : 10 step1:mask_detect Sat Feb 1 02:10:33 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Beginning of datou step mask_detect ! save_polygon : True begin detect begin to check gpu status inside check gpu memory l 3637 free memory gpu now : 10553 max_wait_temp : 1 max_wait : 0 gpu_flag : 0 2025-02-01 02:10:35.833417: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2025-02-01 02:10:35.859525: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493020000 Hz 2025-02-01 02:10:35.861559: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f7004000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-02-01 02:10:35.861618: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-02-01 02:10:35.865609: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-02-01 02:10:36.104578: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x3e2200e0 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-02-01 02:10:36.104640: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-02-01 02:10:36.106041: 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 2025-02-01 02:10:36.106942: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-01 02:10:36.111969: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-02-01 02:10:36.115658: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-02-01 02:10:36.116431: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-02-01 02:10:36.120241: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-02-01 02:10:36.121871: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-02-01 02:10:36.127771: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-02-01 02:10:36.129233: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-02-01 02:10:36.129309: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-01 02:10:36.130070: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-02-01 02:10:36.130085: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-02-01 02:10:36.130095: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-02-01 02:10:36.131423: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 9777 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. 2025-02-01 02:10:36.445932: 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 2025-02-01 02:10:36.446054: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-01 02:10:36.446084: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-02-01 02:10:36.446109: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-02-01 02:10:36.446135: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-02-01 02:10:36.446159: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-02-01 02:10:36.446183: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-02-01 02:10:36.446208: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-02-01 02:10:36.448410: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-02-01 02:10:36.450218: 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 2025-02-01 02:10:36.450303: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-01 02:10:36.450329: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-02-01 02:10:36.450354: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-02-01 02:10:36.450378: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-02-01 02:10:36.450402: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-02-01 02:10:36.450426: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-02-01 02:10:36.450450: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-02-01 02:10:36.452386: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-02-01 02:10:36.452417: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-02-01 02:10:36.452425: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-02-01 02:10:36.452434: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-02-01 02:10:36.453726: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 9777 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 : [] 2025-02-01 02:10:48.084016: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-02-01 02:10:48.279305: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 local folder : /data/models_weight/learn_RUBBIA_REFUS_AMIENS_23 /data/models_weight/learn_RUBBIA_REFUS_AMIENS_23/mask_model.h5 size_local : 256009536 size in s3 : 256009536 create time local : 2021-08-09 09:43:22 create time in s3 : 2021-08-06 18:54:04 mask_model.h5 already exist and didn't need to update list_images length : 12 NEW PHOTO Processing 1 images image shape: (2160, 3264, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 3264.00000 nb d'objets trouves : 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 : 68 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 : 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 : 12 NEW PHOTO Processing 1 images image shape: (2160, 3264, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 3264.00000 nb d'objets trouves : 95 NEW PHOTO Processing 1 images image shape: (2160, 3264, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 3264.00000 nb d'objets trouves : 47 NEW PHOTO Processing 1 images image shape: (2160, 3264, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 3264.00000 nb d'objets trouves : 65 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 : 48 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 : 60 Detection mask done ! Trying to reset tf kernel 2654931 begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 5264 tf kernel not reseted sub process len(results) : 12 len(list_Values) 0 None max_time_sub_proc : 3600 parent process len(results) : 12 len(list_Values) 0 process is alive process is alive finish correctly or not : True after detect begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 10553 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 : 0.0034127235412597656 nb_pixel_total : 18188 time to create 1 rle with old method : 0.025120258331298828 length of segment : 218 time for calcul the mask position with numpy : 0.0007646083831787109 nb_pixel_total : 12390 time to create 1 rle with old method : 0.01381373405456543 length of segment : 122 time for calcul the mask position with numpy : 0.005879640579223633 nb_pixel_total : 24080 time to create 1 rle with old method : 0.029099225997924805 length of segment : 160 time for calcul the mask position with numpy : 0.08384537696838379 nb_pixel_total : 79704 time to create 1 rle with old method : 0.0903935432434082 length of segment : 455 time for calcul the mask position with numpy : 0.0007729530334472656 nb_pixel_total : 15235 time to create 1 rle with old method : 0.01679825782775879 length of segment : 114 time for calcul the mask position with numpy : 0.0015571117401123047 nb_pixel_total : 23221 time to create 1 rle with old method : 0.025628089904785156 length of segment : 182 time for calcul the mask position with numpy : 0.013939619064331055 nb_pixel_total : 33193 time to create 1 rle with old method : 0.03975081443786621 length of segment : 227 time for calcul the mask position with numpy : 0.003465890884399414 nb_pixel_total : 17366 time to create 1 rle with old method : 0.021172523498535156 length of segment : 211 time for calcul the mask position with numpy : 0.01208043098449707 nb_pixel_total : 280226 time to create 1 rle with new method : 0.0328061580657959 length of segment : 412 time for calcul the mask position with numpy : 0.003550291061401367 nb_pixel_total : 90928 time to create 1 rle with old method : 0.10527253150939941 length of segment : 398 time for calcul the mask position with numpy : 0.006911039352416992 nb_pixel_total : 9884 time to create 1 rle with old method : 0.014898538589477539 length of segment : 167 time for calcul the mask position with numpy : 0.10240554809570312 nb_pixel_total : 145944 time to create 1 rle with old method : 0.16685748100280762 length of segment : 529 time for calcul the mask position with numpy : 0.005474090576171875 nb_pixel_total : 23944 time to create 1 rle with old method : 0.02953505516052246 length of segment : 272 time for calcul the mask position with numpy : 0.0009067058563232422 nb_pixel_total : 13668 time to create 1 rle with old method : 0.014394521713256836 length of segment : 166 time for calcul the mask position with numpy : 0.0021944046020507812 nb_pixel_total : 25158 time to create 1 rle with old method : 0.028106212615966797 length of segment : 209 time for calcul the mask position with numpy : 0.0009000301361083984 nb_pixel_total : 4502 time to create 1 rle with old method : 0.00497746467590332 length of segment : 114 time for calcul the mask position with numpy : 0.0015761852264404297 nb_pixel_total : 30531 time to create 1 rle with old method : 0.03439521789550781 length of segment : 225 time for calcul the mask position with numpy : 0.0013222694396972656 nb_pixel_total : 31804 time to create 1 rle with old method : 0.035948753356933594 length of segment : 155 time for calcul the mask position with numpy : 0.0006158351898193359 nb_pixel_total : 9453 time to create 1 rle with old method : 0.010864734649658203 length of segment : 157 time for calcul the mask position with numpy : 0.002628803253173828 nb_pixel_total : 31065 time to create 1 rle with old method : 0.03443717956542969 length of segment : 190 time for calcul the mask position with numpy : 0.0020492076873779297 nb_pixel_total : 12927 time to create 1 rle with old method : 0.01459050178527832 length of segment : 111 time for calcul the mask position with numpy : 0.0006210803985595703 nb_pixel_total : 8144 time to create 1 rle with old method : 0.009229660034179688 length of segment : 135 time for calcul the mask position with numpy : 0.0006008148193359375 nb_pixel_total : 9135 time to create 1 rle with old method : 0.010380268096923828 length of segment : 169 time for calcul the mask position with numpy : 0.00015544891357421875 nb_pixel_total : 4165 time to create 1 rle with old method : 0.004917144775390625 length of segment : 51 time for calcul the mask position with numpy : 0.009617090225219727 nb_pixel_total : 80007 time to create 1 rle with old method : 0.09667277336120605 length of segment : 811 time for calcul the mask position with numpy : 0.0007474422454833984 nb_pixel_total : 9996 time to create 1 rle with old method : 0.010844230651855469 length of segment : 147 time for calcul the mask position with numpy : 0.0035851001739501953 nb_pixel_total : 25763 time to create 1 rle with old method : 0.028361797332763672 length of segment : 224 time for calcul the mask position with numpy : 0.00027298927307128906 nb_pixel_total : 8270 time to create 1 rle with old method : 0.008892297744750977 length of segment : 96 time for calcul the mask position with numpy : 0.00017571449279785156 nb_pixel_total : 6171 time to create 1 rle with old method : 0.007097959518432617 length of segment : 139 time for calcul the mask position with numpy : 0.008703470230102539 nb_pixel_total : 14200 time to create 1 rle with old method : 0.024192094802856445 length of segment : 156 time for calcul the mask position with numpy : 0.0058634281158447266 nb_pixel_total : 5468 time to create 1 rle with old method : 0.0077686309814453125 length of segment : 97 time for calcul the mask position with numpy : 0.012720823287963867 nb_pixel_total : 58396 time to create 1 rle with old method : 0.06897807121276855 length of segment : 274 time for calcul the mask position with numpy : 0.0004360675811767578 nb_pixel_total : 4222 time to create 1 rle with old method : 0.004834651947021484 length of segment : 77 time for calcul the mask position with numpy : 0.006971836090087891 nb_pixel_total : 71444 time to create 1 rle with old method : 0.0892782211303711 length of segment : 309 time for calcul the mask position with numpy : 0.0002105236053466797 nb_pixel_total : 3361 time to create 1 rle with old method : 0.004265785217285156 length of segment : 67 time for calcul the mask position with numpy : 0.021204233169555664 nb_pixel_total : 21328 time to create 1 rle with old method : 0.027309179306030273 length of segment : 181 time for calcul the mask position with numpy : 0.025400161743164062 nb_pixel_total : 348270 time to create 1 rle with new method : 0.0343015193939209 length of segment : 761 time for calcul the mask position with numpy : 0.002782106399536133 nb_pixel_total : 29261 time to create 1 rle with old method : 0.033727407455444336 length of segment : 423 time for calcul the mask position with numpy : 0.012580156326293945 nb_pixel_total : 176927 time to create 1 rle with new method : 0.01837635040283203 length of segment : 925 time for calcul the mask position with numpy : 0.0013115406036376953 nb_pixel_total : 59027 time to create 1 rle with old method : 0.06722378730773926 length of segment : 262 time for calcul the mask position with numpy : 0.009548425674438477 nb_pixel_total : 70968 time to create 1 rle with old method : 0.0824742317199707 length of segment : 356 time for calcul the mask position with numpy : 0.0005869865417480469 nb_pixel_total : 7163 time to create 1 rle with old method : 0.008772611618041992 length of segment : 112 time for calcul the mask position with numpy : 0.007090568542480469 nb_pixel_total : 91662 time to create 1 rle with old method : 0.10519695281982422 length of segment : 266 time for calcul the mask position with numpy : 0.0028629302978515625 nb_pixel_total : 43057 time to create 1 rle with old method : 0.051984310150146484 length of segment : 288 time for calcul the mask position with numpy : 0.0009710788726806641 nb_pixel_total : 16961 time to create 1 rle with old method : 0.020826339721679688 length of segment : 155 time for calcul the mask position with numpy : 0.005530834197998047 nb_pixel_total : 79988 time to create 1 rle with old method : 0.09748244285583496 length of segment : 256 time for calcul the mask position with numpy : 0.0005388259887695312 nb_pixel_total : 7555 time to create 1 rle with old method : 0.009286642074584961 length of segment : 96 time for calcul the mask position with numpy : 0.0009291172027587891 nb_pixel_total : 19860 time to create 1 rle with old method : 0.022952795028686523 length of segment : 171 time for calcul the mask position with numpy : 0.001605987548828125 nb_pixel_total : 15297 time to create 1 rle with old method : 0.020651578903198242 length of segment : 203 time for calcul the mask position with numpy : 0.0016636848449707031 nb_pixel_total : 16270 time to create 1 rle with old method : 0.018134593963623047 length of segment : 123 time for calcul the mask position with numpy : 0.0027017593383789062 nb_pixel_total : 33316 time to create 1 rle with old method : 0.0379638671875 length of segment : 222 time for calcul the mask position with numpy : 0.0008609294891357422 nb_pixel_total : 12602 time to create 1 rle with old method : 0.014559507369995117 length of segment : 165 time for calcul the mask position with numpy : 0.0010695457458496094 nb_pixel_total : 12689 time to create 1 rle with old method : 0.014978408813476562 length of segment : 177 time for calcul the mask position with numpy : 0.0001556873321533203 nb_pixel_total : 2532 time to create 1 rle with old method : 0.0030384063720703125 length of segment : 108 time for calcul the mask position with numpy : 0.015135049819946289 nb_pixel_total : 237825 time to create 1 rle with new method : 0.012454748153686523 length of segment : 709 time for calcul the mask position with numpy : 0.0031435489654541016 nb_pixel_total : 17539 time to create 1 rle with old method : 0.019952058792114258 length of segment : 253 time for calcul the mask position with numpy : 0.0019345283508300781 nb_pixel_total : 24270 time to create 1 rle with old method : 0.02640366554260254 length of segment : 251 time for calcul the mask position with numpy : 0.00038504600524902344 nb_pixel_total : 12089 time to create 1 rle with old method : 0.013678550720214844 length of segment : 101 time for calcul the mask position with numpy : 0.012225627899169922 nb_pixel_total : 194509 time to create 1 rle with new method : 0.011672735214233398 length of segment : 640 time for calcul the mask position with numpy : 0.0013082027435302734 nb_pixel_total : 17175 time to create 1 rle with old method : 0.019867897033691406 length of segment : 179 time for calcul the mask position with numpy : 0.004957914352416992 nb_pixel_total : 49508 time to create 1 rle with old method : 0.08786892890930176 length of segment : 273 time for calcul the mask position with numpy : 0.0007462501525878906 nb_pixel_total : 8365 time to create 1 rle with old method : 0.010322332382202148 length of segment : 129 time for calcul the mask position with numpy : 0.0008778572082519531 nb_pixel_total : 6342 time to create 1 rle with old method : 0.007635354995727539 length of segment : 127 time for calcul the mask position with numpy : 0.00019311904907226562 nb_pixel_total : 6159 time to create 1 rle with old method : 0.007706403732299805 length of segment : 80 time for calcul the mask position with numpy : 9.608268737792969e-05 nb_pixel_total : 1511 time to create 1 rle with old method : 0.0020051002502441406 length of segment : 56 time for calcul the mask position with numpy : 0.0018353462219238281 nb_pixel_total : 39202 time to create 1 rle with old method : 0.0443568229675293 length of segment : 239 time for calcul the mask position with numpy : 0.0040705204010009766 nb_pixel_total : 42041 time to create 1 rle with old method : 0.05083417892456055 length of segment : 555 time for calcul the mask position with numpy : 0.008170843124389648 nb_pixel_total : 34534 time to create 1 rle with old method : 0.040602922439575195 length of segment : 772 time for calcul the mask position with numpy : 0.001634836196899414 nb_pixel_total : 21652 time to create 1 rle with old method : 0.026053667068481445 length of segment : 225 time for calcul the mask position with numpy : 0.0015826225280761719 nb_pixel_total : 18992 time to create 1 rle with old method : 0.026607275009155273 length of segment : 171 time for calcul the mask position with numpy : 0.0017168521881103516 nb_pixel_total : 19658 time to create 1 rle with old method : 0.023290157318115234 length of segment : 193 time for calcul the mask position with numpy : 0.0003528594970703125 nb_pixel_total : 4107 time to create 1 rle with old method : 0.0049207210540771484 length of segment : 85 time for calcul the mask position with numpy : 0.0022716522216796875 nb_pixel_total : 38021 time to create 1 rle with old method : 0.04426932334899902 length of segment : 292 time for calcul the mask position with numpy : 0.0008809566497802734 nb_pixel_total : 12492 time to create 1 rle with old method : 0.015022039413452148 length of segment : 135 time for calcul the mask position with numpy : 0.0013148784637451172 nb_pixel_total : 14473 time to create 1 rle with old method : 0.01706695556640625 length of segment : 174 time for calcul the mask position with numpy : 0.0014412403106689453 nb_pixel_total : 16398 time to create 1 rle with old method : 0.019515275955200195 length of segment : 119 time for calcul the mask position with numpy : 0.0027637481689453125 nb_pixel_total : 33067 time to create 1 rle with old method : 0.03883671760559082 length of segment : 376 time for calcul the mask position with numpy : 0.003275156021118164 nb_pixel_total : 39376 time to create 1 rle with old method : 0.046553611755371094 length of segment : 580 time for calcul the mask position with numpy : 0.009869098663330078 nb_pixel_total : 97672 time to create 1 rle with old method : 0.11376094818115234 length of segment : 633 time for calcul the mask position with numpy : 0.0011835098266601562 nb_pixel_total : 16557 time to create 1 rle with old method : 0.026273012161254883 length of segment : 216 time for calcul the mask position with numpy : 0.002030611038208008 nb_pixel_total : 24034 time to create 1 rle with old method : 0.02874898910522461 length of segment : 244 time for calcul the mask position with numpy : 0.001961231231689453 nb_pixel_total : 21997 time to create 1 rle with old method : 0.02544426918029785 length of segment : 211 time for calcul the mask position with numpy : 0.0010378360748291016 nb_pixel_total : 13140 time to create 1 rle with old method : 0.01589655876159668 length of segment : 145 time for calcul the mask position with numpy : 0.0008258819580078125 nb_pixel_total : 8170 time to create 1 rle with old method : 0.013472795486450195 length of segment : 126 time for calcul the mask position with numpy : 0.001987934112548828 nb_pixel_total : 35703 time to create 1 rle with old method : 0.04148077964782715 length of segment : 137 time for calcul the mask position with numpy : 0.001911163330078125 nb_pixel_total : 26997 time to create 1 rle with old method : 0.030758380889892578 length of segment : 179 time for calcul the mask position with numpy : 0.0034596920013427734 nb_pixel_total : 45310 time to create 1 rle with old method : 0.05123305320739746 length of segment : 351 time for calcul the mask position with numpy : 0.010109186172485352 nb_pixel_total : 172463 time to create 1 rle with new method : 0.014705419540405273 length of segment : 565 time for calcul the mask position with numpy : 0.003573179244995117 nb_pixel_total : 48422 time to create 1 rle with old method : 0.05485653877258301 length of segment : 362 time for calcul the mask position with numpy : 0.0025162696838378906 nb_pixel_total : 13519 time to create 1 rle with old method : 0.015574455261230469 length of segment : 311 time for calcul the mask position with numpy : 0.0010957717895507812 nb_pixel_total : 11780 time to create 1 rle with old method : 0.01385807991027832 length of segment : 136 time for calcul the mask position with numpy : 0.0009667873382568359 nb_pixel_total : 21780 time to create 1 rle with old method : 0.025594234466552734 length of segment : 143 time for calcul the mask position with numpy : 0.0019359588623046875 nb_pixel_total : 32298 time to create 1 rle with old method : 0.03717494010925293 length of segment : 193 time for calcul the mask position with numpy : 0.0018312931060791016 nb_pixel_total : 25123 time to create 1 rle with old method : 0.027693510055541992 length of segment : 180 time for calcul the mask position with numpy : 0.0010445117950439453 nb_pixel_total : 13338 time to create 1 rle with old method : 0.016514301300048828 length of segment : 179 time for calcul the mask position with numpy : 0.007427215576171875 nb_pixel_total : 99022 time to create 1 rle with old method : 0.11551141738891602 length of segment : 402 time for calcul the mask position with numpy : 0.003028392791748047 nb_pixel_total : 46736 time to create 1 rle with old method : 0.052472829818725586 length of segment : 346 time for calcul the mask position with numpy : 0.0016307830810546875 nb_pixel_total : 16381 time to create 1 rle with old method : 0.01849961280822754 length of segment : 162 time for calcul the mask position with numpy : 0.002878904342651367 nb_pixel_total : 31805 time to create 1 rle with old method : 0.03702068328857422 length of segment : 230 time for calcul the mask position with numpy : 0.0020551681518554688 nb_pixel_total : 19865 time to create 1 rle with old method : 0.024556875228881836 length of segment : 127 time for calcul the mask position with numpy : 0.001359701156616211 nb_pixel_total : 23980 time to create 1 rle with old method : 0.028083086013793945 length of segment : 178 time for calcul the mask position with numpy : 0.0005564689636230469 nb_pixel_total : 7553 time to create 1 rle with old method : 0.009000301361083984 length of segment : 119 time for calcul the mask position with numpy : 0.0019996166229248047 nb_pixel_total : 30905 time to create 1 rle with old method : 0.03871798515319824 length of segment : 216 time for calcul the mask position with numpy : 0.002110719680786133 nb_pixel_total : 30225 time to create 1 rle with old method : 0.03584027290344238 length of segment : 219 time for calcul the mask position with numpy : 0.0008757114410400391 nb_pixel_total : 9500 time to create 1 rle with old method : 0.012198448181152344 length of segment : 134 time for calcul the mask position with numpy : 0.0011854171752929688 nb_pixel_total : 18510 time to create 1 rle with old method : 0.024454355239868164 length of segment : 140 time for calcul the mask position with numpy : 0.002347707748413086 nb_pixel_total : 41474 time to create 1 rle with old method : 0.04764223098754883 length of segment : 190 time for calcul the mask position with numpy : 0.003486156463623047 nb_pixel_total : 48609 time to create 1 rle with old method : 0.054482460021972656 length of segment : 341 time for calcul the mask position with numpy : 0.003312826156616211 nb_pixel_total : 49822 time to create 1 rle with old method : 0.059552907943725586 length of segment : 356 time for calcul the mask position with numpy : 0.0017006397247314453 nb_pixel_total : 24109 time to create 1 rle with old method : 0.02817535400390625 length of segment : 149 time for calcul the mask position with numpy : 0.0011708736419677734 nb_pixel_total : 13671 time to create 1 rle with old method : 0.01620960235595703 length of segment : 134 time for calcul the mask position with numpy : 0.0032088756561279297 nb_pixel_total : 29085 time to create 1 rle with old method : 0.03439044952392578 length of segment : 330 time for calcul the mask position with numpy : 0.0003979206085205078 nb_pixel_total : 4508 time to create 1 rle with old method : 0.00531005859375 length of segment : 63 time for calcul the mask position with numpy : 0.0027379989624023438 nb_pixel_total : 39410 time to create 1 rle with old method : 0.04761195182800293 length of segment : 171 time for calcul the mask position with numpy : 0.0012695789337158203 nb_pixel_total : 16870 time to create 1 rle with old method : 0.019870519638061523 length of segment : 157 time for calcul the mask position with numpy : 0.0006940364837646484 nb_pixel_total : 4967 time to create 1 rle with old method : 0.006021738052368164 length of segment : 81 time for calcul the mask position with numpy : 0.0009133815765380859 nb_pixel_total : 11313 time to create 1 rle with old method : 0.012256622314453125 length of segment : 140 time for calcul the mask position with numpy : 0.0003714561462402344 nb_pixel_total : 4164 time to create 1 rle with old method : 0.004804849624633789 length of segment : 70 time for calcul the mask position with numpy : 0.0018274784088134766 nb_pixel_total : 26724 time to create 1 rle with old method : 0.03022933006286621 length of segment : 174 time for calcul the mask position with numpy : 0.0014526844024658203 nb_pixel_total : 20869 time to create 1 rle with old method : 0.024675369262695312 length of segment : 157 time for calcul the mask position with numpy : 0.0006830692291259766 nb_pixel_total : 8119 time to create 1 rle with old method : 0.00930929183959961 length of segment : 114 time for calcul the mask position with numpy : 0.0004010200500488281 nb_pixel_total : 4855 time to create 1 rle with old method : 0.005627155303955078 length of segment : 112 time for calcul the mask position with numpy : 0.0007758140563964844 nb_pixel_total : 10686 time to create 1 rle with old method : 0.012270689010620117 length of segment : 134 time for calcul the mask position with numpy : 0.0017168521881103516 nb_pixel_total : 13576 time to create 1 rle with old method : 0.015786409378051758 length of segment : 134 time for calcul the mask position with numpy : 0.001965761184692383 nb_pixel_total : 24743 time to create 1 rle with old method : 0.02788090705871582 length of segment : 235 time for calcul the mask position with numpy : 0.0011363029479980469 nb_pixel_total : 11610 time to create 1 rle with old method : 0.014796972274780273 length of segment : 204 time for calcul the mask position with numpy : 0.0014159679412841797 nb_pixel_total : 14792 time to create 1 rle with old method : 0.016787290573120117 length of segment : 179 time for calcul the mask position with numpy : 0.0027816295623779297 nb_pixel_total : 23633 time to create 1 rle with old method : 0.0391993522644043 length of segment : 220 time for calcul the mask position with numpy : 0.0017170906066894531 nb_pixel_total : 11125 time to create 1 rle with old method : 0.012821197509765625 length of segment : 227 time for calcul the mask position with numpy : 0.002201557159423828 nb_pixel_total : 20851 time to create 1 rle with old method : 0.023076295852661133 length of segment : 220 time for calcul the mask position with numpy : 0.001190185546875 nb_pixel_total : 15849 time to create 1 rle with old method : 0.018438339233398438 length of segment : 132 time for calcul the mask position with numpy : 0.0020155906677246094 nb_pixel_total : 28637 time to create 1 rle with old method : 0.03130197525024414 length of segment : 273 time for calcul the mask position with numpy : 0.00043010711669921875 nb_pixel_total : 4222 time to create 1 rle with old method : 0.004687309265136719 length of segment : 97 time for calcul the mask position with numpy : 0.002488374710083008 nb_pixel_total : 34967 time to create 1 rle with old method : 0.04018855094909668 length of segment : 214 time for calcul the mask position with numpy : 0.006790876388549805 nb_pixel_total : 65613 time to create 1 rle with old method : 0.07458162307739258 length of segment : 494 time for calcul the mask position with numpy : 0.0009326934814453125 nb_pixel_total : 8767 time to create 1 rle with old method : 0.00986790657043457 length of segment : 183 time for calcul the mask position with numpy : 0.0024971961975097656 nb_pixel_total : 28315 time to create 1 rle with old method : 0.03124833106994629 length of segment : 261 time for calcul the mask position with numpy : 0.0007212162017822266 nb_pixel_total : 7093 time to create 1 rle with old method : 0.008094310760498047 length of segment : 124 time for calcul the mask position with numpy : 0.0009055137634277344 nb_pixel_total : 12387 time to create 1 rle with old method : 0.01456594467163086 length of segment : 130 time for calcul the mask position with numpy : 0.001916646957397461 nb_pixel_total : 21099 time to create 1 rle with old method : 0.024636507034301758 length of segment : 298 time for calcul the mask position with numpy : 0.0018076896667480469 nb_pixel_total : 24465 time to create 1 rle with old method : 0.02767181396484375 length of segment : 173 time for calcul the mask position with numpy : 0.0004851818084716797 nb_pixel_total : 6325 time to create 1 rle with old method : 0.007537126541137695 length of segment : 86 time for calcul the mask position with numpy : 0.0003771781921386719 nb_pixel_total : 3851 time to create 1 rle with old method : 0.004829883575439453 length of segment : 63 time for calcul the mask position with numpy : 0.0007889270782470703 nb_pixel_total : 12516 time to create 1 rle with old method : 0.01429605484008789 length of segment : 152 time for calcul the mask position with numpy : 0.002087116241455078 nb_pixel_total : 30291 time to create 1 rle with old method : 0.03438687324523926 length of segment : 357 time for calcul the mask position with numpy : 0.00022840499877929688 nb_pixel_total : 4235 time to create 1 rle with old method : 0.004749774932861328 length of segment : 72 time for calcul the mask position with numpy : 0.0007562637329101562 nb_pixel_total : 6170 time to create 1 rle with old method : 0.007814168930053711 length of segment : 115 time for calcul the mask position with numpy : 0.0009999275207519531 nb_pixel_total : 14111 time to create 1 rle with old method : 0.016097307205200195 length of segment : 160 time for calcul the mask position with numpy : 0.00035262107849121094 nb_pixel_total : 6696 time to create 1 rle with old method : 0.007615804672241211 length of segment : 100 time for calcul the mask position with numpy : 0.0010383129119873047 nb_pixel_total : 11318 time to create 1 rle with old method : 0.013224124908447266 length of segment : 139 time for calcul the mask position with numpy : 0.0008358955383300781 nb_pixel_total : 13129 time to create 1 rle with old method : 0.01531529426574707 length of segment : 139 time for calcul the mask position with numpy : 0.0009672641754150391 nb_pixel_total : 13800 time to create 1 rle with old method : 0.016127347946166992 length of segment : 163 time for calcul the mask position with numpy : 0.0010995864868164062 nb_pixel_total : 16450 time to create 1 rle with old method : 0.018280506134033203 length of segment : 171 time for calcul the mask position with numpy : 0.0007812976837158203 nb_pixel_total : 15359 time to create 1 rle with old method : 0.017203807830810547 length of segment : 155 time for calcul the mask position with numpy : 0.0012140274047851562 nb_pixel_total : 14000 time to create 1 rle with old method : 0.015928268432617188 length of segment : 132 time for calcul the mask position with numpy : 0.000213623046875 nb_pixel_total : 3993 time to create 1 rle with old method : 0.004589080810546875 length of segment : 83 time for calcul the mask position with numpy : 0.0029120445251464844 nb_pixel_total : 48701 time to create 1 rle with old method : 0.05487942695617676 length of segment : 273 time for calcul the mask position with numpy : 0.0008087158203125 nb_pixel_total : 8252 time to create 1 rle with old method : 0.009497404098510742 length of segment : 159 time for calcul the mask position with numpy : 0.0011336803436279297 nb_pixel_total : 14050 time to create 1 rle with old method : 0.016101598739624023 length of segment : 197 time for calcul the mask position with numpy : 0.0016562938690185547 nb_pixel_total : 24729 time to create 1 rle with old method : 0.028021812438964844 length of segment : 159 time for calcul the mask position with numpy : 0.0026063919067382812 nb_pixel_total : 37543 time to create 1 rle with old method : 0.04292583465576172 length of segment : 271 time for calcul the mask position with numpy : 0.0009238719940185547 nb_pixel_total : 11296 time to create 1 rle with old method : 0.013366222381591797 length of segment : 178 time for calcul the mask position with numpy : 0.001337289810180664 nb_pixel_total : 17545 time to create 1 rle with old method : 0.021202802658081055 length of segment : 150 time for calcul the mask position with numpy : 0.0026264190673828125 nb_pixel_total : 44155 time to create 1 rle with old method : 0.04950737953186035 length of segment : 230 time for calcul the mask position with numpy : 0.0008525848388671875 nb_pixel_total : 7715 time to create 1 rle with old method : 0.009153127670288086 length of segment : 133 time for calcul the mask position with numpy : 0.002229928970336914 nb_pixel_total : 39861 time to create 1 rle with old method : 0.04737114906311035 length of segment : 226 time for calcul the mask position with numpy : 0.0015366077423095703 nb_pixel_total : 19074 time to create 1 rle with old method : 0.021698951721191406 length of segment : 233 time for calcul the mask position with numpy : 0.00030541419982910156 nb_pixel_total : 3045 time to create 1 rle with old method : 0.003629922866821289 length of segment : 84 time for calcul the mask position with numpy : 0.0004208087921142578 nb_pixel_total : 4449 time to create 1 rle with old method : 0.005158901214599609 length of segment : 86 time for calcul the mask position with numpy : 0.0010471343994140625 nb_pixel_total : 18286 time to create 1 rle with old method : 0.02012491226196289 length of segment : 140 time for calcul the mask position with numpy : 0.001689910888671875 nb_pixel_total : 25563 time to create 1 rle with old method : 0.029331684112548828 length of segment : 239 time for calcul the mask position with numpy : 0.0015864372253417969 nb_pixel_total : 23410 time to create 1 rle with old method : 0.029546022415161133 length of segment : 175 time for calcul the mask position with numpy : 0.002798795700073242 nb_pixel_total : 29655 time to create 1 rle with old method : 0.03294038772583008 length of segment : 221 time for calcul the mask position with numpy : 0.0021047592163085938 nb_pixel_total : 29882 time to create 1 rle with old method : 0.03295326232910156 length of segment : 236 time for calcul the mask position with numpy : 0.0012080669403076172 nb_pixel_total : 15582 time to create 1 rle with old method : 0.0189971923828125 length of segment : 109 time for calcul the mask position with numpy : 0.0012066364288330078 nb_pixel_total : 18091 time to create 1 rle with old method : 0.021195173263549805 length of segment : 213 time for calcul the mask position with numpy : 0.005533456802368164 nb_pixel_total : 76357 time to create 1 rle with old method : 0.08756303787231445 length of segment : 541 time for calcul the mask position with numpy : 0.004008054733276367 nb_pixel_total : 49341 time to create 1 rle with old method : 0.05469822883605957 length of segment : 379 time for calcul the mask position with numpy : 0.0016105175018310547 nb_pixel_total : 21538 time to create 1 rle with old method : 0.024072885513305664 length of segment : 304 time for calcul the mask position with numpy : 0.0011115074157714844 nb_pixel_total : 12354 time to create 1 rle with old method : 0.01475834846496582 length of segment : 180 time for calcul the mask position with numpy : 0.008942127227783203 nb_pixel_total : 88195 time to create 1 rle with old method : 0.1045689582824707 length of segment : 565 time for calcul the mask position with numpy : 0.0020377635955810547 nb_pixel_total : 25231 time to create 1 rle with old method : 0.028616905212402344 length of segment : 284 time for calcul the mask position with numpy : 0.0004620552062988281 nb_pixel_total : 5927 time to create 1 rle with old method : 0.0072176456451416016 length of segment : 74 time for calcul the mask position with numpy : 0.0032367706298828125 nb_pixel_total : 51402 time to create 1 rle with old method : 0.0603947639465332 length of segment : 266 time for calcul the mask position with numpy : 0.0023314952850341797 nb_pixel_total : 22534 time to create 1 rle with old method : 0.036836862564086914 length of segment : 136 time for calcul the mask position with numpy : 0.0007350444793701172 nb_pixel_total : 8505 time to create 1 rle with old method : 0.010826587677001953 length of segment : 100 time for calcul the mask position with numpy : 0.002180814743041992 nb_pixel_total : 25427 time to create 1 rle with old method : 0.02904796600341797 length of segment : 332 time for calcul the mask position with numpy : 0.0016901493072509766 nb_pixel_total : 32188 time to create 1 rle with old method : 0.036608219146728516 length of segment : 245 time for calcul the mask position with numpy : 0.001459360122680664 nb_pixel_total : 21303 time to create 1 rle with old method : 0.025580644607543945 length of segment : 150 time for calcul the mask position with numpy : 0.0006508827209472656 nb_pixel_total : 8066 time to create 1 rle with old method : 0.0096282958984375 length of segment : 118 time for calcul the mask position with numpy : 0.0004630088806152344 nb_pixel_total : 5727 time to create 1 rle with old method : 0.006857633590698242 length of segment : 85 time for calcul the mask position with numpy : 0.004395723342895508 nb_pixel_total : 54925 time to create 1 rle with old method : 0.06289434432983398 length of segment : 374 time for calcul the mask position with numpy : 0.0005807876586914062 nb_pixel_total : 8653 time to create 1 rle with old method : 0.010044336318969727 length of segment : 108 time for calcul the mask position with numpy : 0.0010356903076171875 nb_pixel_total : 14219 time to create 1 rle with old method : 0.018741607666015625 length of segment : 113 time for calcul the mask position with numpy : 0.0013670921325683594 nb_pixel_total : 18946 time to create 1 rle with old method : 0.02165079116821289 length of segment : 137 time for calcul the mask position with numpy : 0.00037288665771484375 nb_pixel_total : 12218 time to create 1 rle with old method : 0.014698505401611328 length of segment : 141 time for calcul the mask position with numpy : 0.0016868114471435547 nb_pixel_total : 30944 time to create 1 rle with old method : 0.035280704498291016 length of segment : 199 time for calcul the mask position with numpy : 0.0027053356170654297 nb_pixel_total : 20600 time to create 1 rle with old method : 0.024890422821044922 length of segment : 162 time for calcul the mask position with numpy : 0.0037527084350585938 nb_pixel_total : 48163 time to create 1 rle with old method : 0.05212116241455078 length of segment : 330 time for calcul the mask position with numpy : 0.001027822494506836 nb_pixel_total : 15494 time to create 1 rle with old method : 0.017720699310302734 length of segment : 122 time for calcul the mask position with numpy : 0.0013060569763183594 nb_pixel_total : 10946 time to create 1 rle with old method : 0.0120697021484375 length of segment : 203 time for calcul the mask position with numpy : 0.00046181678771972656 nb_pixel_total : 12696 time to create 1 rle with old method : 0.01420736312866211 length of segment : 167 time for calcul the mask position with numpy : 0.0009436607360839844 nb_pixel_total : 13150 time to create 1 rle with old method : 0.015325307846069336 length of segment : 142 time for calcul the mask position with numpy : 0.0020618438720703125 nb_pixel_total : 18746 time to create 1 rle with old method : 0.020228147506713867 length of segment : 364 time for calcul the mask position with numpy : 0.0006573200225830078 nb_pixel_total : 6211 time to create 1 rle with old method : 0.006974697113037109 length of segment : 75 time for calcul the mask position with numpy : 0.004496335983276367 nb_pixel_total : 45022 time to create 1 rle with old method : 0.06962275505065918 length of segment : 254 time for calcul the mask position with numpy : 0.0018842220306396484 nb_pixel_total : 25295 time to create 1 rle with old method : 0.042200565338134766 length of segment : 184 time for calcul the mask position with numpy : 0.0006542205810546875 nb_pixel_total : 6302 time to create 1 rle with old method : 0.0076618194580078125 length of segment : 121 time for calcul the mask position with numpy : 0.001241445541381836 nb_pixel_total : 22639 time to create 1 rle with old method : 0.027327537536621094 length of segment : 137 time for calcul the mask position with numpy : 0.0009496212005615234 nb_pixel_total : 21860 time to create 1 rle with old method : 0.025810718536376953 length of segment : 285 time for calcul the mask position with numpy : 0.000743865966796875 nb_pixel_total : 24585 time to create 1 rle with old method : 0.02997279167175293 length of segment : 163 time for calcul the mask position with numpy : 0.00441431999206543 nb_pixel_total : 49447 time to create 1 rle with old method : 0.05903315544128418 length of segment : 358 time for calcul the mask position with numpy : 0.0011105537414550781 nb_pixel_total : 13370 time to create 1 rle with old method : 0.01616048812866211 length of segment : 199 time for calcul the mask position with numpy : 0.0020453929901123047 nb_pixel_total : 32553 time to create 1 rle with old method : 0.0368494987487793 length of segment : 277 time for calcul the mask position with numpy : 0.0003139972686767578 nb_pixel_total : 5440 time to create 1 rle with old method : 0.006603717803955078 length of segment : 132 time for calcul the mask position with numpy : 0.004378557205200195 nb_pixel_total : 51393 time to create 1 rle with old method : 0.061122894287109375 length of segment : 296 time for calcul the mask position with numpy : 0.001941680908203125 nb_pixel_total : 25643 time to create 1 rle with old method : 0.028172731399536133 length of segment : 250 time for calcul the mask position with numpy : 0.008795976638793945 nb_pixel_total : 156450 time to create 1 rle with new method : 0.011159896850585938 length of segment : 602 time for calcul the mask position with numpy : 0.0009491443634033203 nb_pixel_total : 11039 time to create 1 rle with old method : 0.012349605560302734 length of segment : 131 time for calcul the mask position with numpy : 0.0001239776611328125 nb_pixel_total : 2774 time to create 1 rle with old method : 0.0031392574310302734 length of segment : 129 time for calcul the mask position with numpy : 0.00104522705078125 nb_pixel_total : 9995 time to create 1 rle with old method : 0.011386632919311523 length of segment : 203 time for calcul the mask position with numpy : 0.0007166862487792969 nb_pixel_total : 12449 time to create 1 rle with old method : 0.01449131965637207 length of segment : 167 time for calcul the mask position with numpy : 0.0010676383972167969 nb_pixel_total : 14027 time to create 1 rle with old method : 0.01566314697265625 length of segment : 168 time for calcul the mask position with numpy : 0.0021622180938720703 nb_pixel_total : 20457 time to create 1 rle with old method : 0.023822307586669922 length of segment : 267 time for calcul the mask position with numpy : 0.0017523765563964844 nb_pixel_total : 15699 time to create 1 rle with old method : 0.018076658248901367 length of segment : 162 time for calcul the mask position with numpy : 0.0007312297821044922 nb_pixel_total : 11685 time to create 1 rle with old method : 0.012906789779663086 length of segment : 104 time for calcul the mask position with numpy : 0.0005621910095214844 nb_pixel_total : 11422 time to create 1 rle with old method : 0.012611627578735352 length of segment : 166 time for calcul the mask position with numpy : 0.001041412353515625 nb_pixel_total : 13986 time to create 1 rle with old method : 0.015820980072021484 length of segment : 197 time for calcul the mask position with numpy : 0.002223968505859375 nb_pixel_total : 27015 time to create 1 rle with old method : 0.031014442443847656 length of segment : 714 time for calcul the mask position with numpy : 0.0006494522094726562 nb_pixel_total : 6072 time to create 1 rle with old method : 0.007387399673461914 length of segment : 81 time for calcul the mask position with numpy : 0.0015277862548828125 nb_pixel_total : 15803 time to create 1 rle with old method : 0.021114349365234375 length of segment : 181 time for calcul the mask position with numpy : 0.0006010532379150391 nb_pixel_total : 8169 time to create 1 rle with old method : 0.010033369064331055 length of segment : 129 time for calcul the mask position with numpy : 0.0009722709655761719 nb_pixel_total : 12762 time to create 1 rle with old method : 0.016573667526245117 length of segment : 115 time for calcul the mask position with numpy : 0.005782127380371094 nb_pixel_total : 55425 time to create 1 rle with old method : 0.06880021095275879 length of segment : 524 time for calcul the mask position with numpy : 0.0012981891632080078 nb_pixel_total : 20039 time to create 1 rle with old method : 0.025126934051513672 length of segment : 253 time for calcul the mask position with numpy : 0.0014503002166748047 nb_pixel_total : 18445 time to create 1 rle with old method : 0.02260756492614746 length of segment : 161 time for calcul the mask position with numpy : 0.18919157981872559 nb_pixel_total : 271136 time to create 1 rle with new method : 0.02026057243347168 length of segment : 397 time for calcul the mask position with numpy : 0.002375364303588867 nb_pixel_total : 41009 time to create 1 rle with old method : 0.046234846115112305 length of segment : 314 time for calcul the mask position with numpy : 0.0005357265472412109 nb_pixel_total : 8969 time to create 1 rle with old method : 0.010612249374389648 length of segment : 71 time for calcul the mask position with numpy : 0.009521722793579102 nb_pixel_total : 186238 time to create 1 rle with new method : 0.013000726699829102 length of segment : 502 time for calcul the mask position with numpy : 0.0013234615325927734 nb_pixel_total : 18310 time to create 1 rle with old method : 0.022112131118774414 length of segment : 172 time for calcul the mask position with numpy : 0.0006513595581054688 nb_pixel_total : 9321 time to create 1 rle with old method : 0.01148223876953125 length of segment : 134 time for calcul the mask position with numpy : 0.029033660888671875 nb_pixel_total : 471504 time to create 1 rle with new method : 0.6499233245849609 length of segment : 1036 time for calcul the mask position with numpy : 0.0037729740142822266 nb_pixel_total : 72819 time to create 1 rle with old method : 0.0853261947631836 length of segment : 359 time for calcul the mask position with numpy : 0.0015461444854736328 nb_pixel_total : 35326 time to create 1 rle with old method : 0.04097485542297363 length of segment : 345 time for calcul the mask position with numpy : 0.0006546974182128906 nb_pixel_total : 27875 time to create 1 rle with old method : 0.03330707550048828 length of segment : 216 time for calcul the mask position with numpy : 0.00433349609375 nb_pixel_total : 96795 time to create 1 rle with old method : 0.11112380027770996 length of segment : 361 time for calcul the mask position with numpy : 0.0009381771087646484 nb_pixel_total : 25034 time to create 1 rle with old method : 0.02855825424194336 length of segment : 225 time for calcul the mask position with numpy : 0.0008876323699951172 nb_pixel_total : 16407 time to create 1 rle with old method : 0.019450902938842773 length of segment : 166 time for calcul the mask position with numpy : 0.000461578369140625 nb_pixel_total : 9319 time to create 1 rle with old method : 0.0107421875 length of segment : 101 time for calcul the mask position with numpy : 0.0003349781036376953 nb_pixel_total : 10185 time to create 1 rle with old method : 0.012099027633666992 length of segment : 119 time for calcul the mask position with numpy : 0.0013213157653808594 nb_pixel_total : 20708 time to create 1 rle with old method : 0.022603750228881836 length of segment : 317 time for calcul the mask position with numpy : 0.003007173538208008 nb_pixel_total : 70700 time to create 1 rle with old method : 0.08133769035339355 length of segment : 446 time for calcul the mask position with numpy : 0.011934995651245117 nb_pixel_total : 185694 time to create 1 rle with new method : 0.020644664764404297 length of segment : 644 time for calcul the mask position with numpy : 0.0026030540466308594 nb_pixel_total : 66459 time to create 1 rle with old method : 0.09909796714782715 length of segment : 152 time for calcul the mask position with numpy : 0.0002651214599609375 nb_pixel_total : 3835 time to create 1 rle with old method : 0.00443577766418457 length of segment : 72 time for calcul the mask position with numpy : 0.0006816387176513672 nb_pixel_total : 7648 time to create 1 rle with old method : 0.009391546249389648 length of segment : 126 time for calcul the mask position with numpy : 0.0028924942016601562 nb_pixel_total : 80115 time to create 1 rle with old method : 0.08974552154541016 length of segment : 198 time for calcul the mask position with numpy : 0.0010535717010498047 nb_pixel_total : 26912 time to create 1 rle with old method : 0.034018754959106445 length of segment : 205 time for calcul the mask position with numpy : 0.0001659393310546875 nb_pixel_total : 4773 time to create 1 rle with old method : 0.00580143928527832 length of segment : 87 time for calcul the mask position with numpy : 0.0018579959869384766 nb_pixel_total : 31629 time to create 1 rle with old method : 0.03510141372680664 length of segment : 388 time for calcul the mask position with numpy : 0.0016942024230957031 nb_pixel_total : 41184 time to create 1 rle with old method : 0.04667973518371582 length of segment : 319 time for calcul the mask position with numpy : 0.003258943557739258 nb_pixel_total : 71246 time to create 1 rle with old method : 0.07906126976013184 length of segment : 258 time for calcul the mask position with numpy : 0.002145051956176758 nb_pixel_total : 44393 time to create 1 rle with old method : 0.04984259605407715 length of segment : 296 time for calcul the mask position with numpy : 0.001455545425415039 nb_pixel_total : 47668 time to create 1 rle with old method : 0.06548762321472168 length of segment : 341 time for calcul the mask position with numpy : 0.005437374114990234 nb_pixel_total : 85900 time to create 1 rle with old method : 0.10126304626464844 length of segment : 377 time for calcul the mask position with numpy : 0.0004875659942626953 nb_pixel_total : 8542 time to create 1 rle with old method : 0.009797096252441406 length of segment : 108 time for calcul the mask position with numpy : 0.0021448135375976562 nb_pixel_total : 48263 time to create 1 rle with old method : 0.056433916091918945 length of segment : 301 time for calcul the mask position with numpy : 0.000202178955078125 nb_pixel_total : 3990 time to create 1 rle with old method : 0.0048182010650634766 length of segment : 55 time for calcul the mask position with numpy : 0.006078481674194336 nb_pixel_total : 250416 time to create 1 rle with new method : 0.014893054962158203 length of segment : 712 time for calcul the mask position with numpy : 0.005863666534423828 nb_pixel_total : 252325 time to create 1 rle with new method : 0.017186403274536133 length of segment : 406 time for calcul the mask position with numpy : 0.006129026412963867 nb_pixel_total : 237043 time to create 1 rle with new method : 0.015504837036132812 length of segment : 568 time for calcul the mask position with numpy : 0.0034830570220947266 nb_pixel_total : 174450 time to create 1 rle with new method : 0.008399724960327148 length of segment : 438 time for calcul the mask position with numpy : 0.12823200225830078 nb_pixel_total : 2818162 time to create 1 rle with new method : 0.8229351043701172 length of segment : 2738 time for calcul the mask position with numpy : 0.0004837512969970703 nb_pixel_total : 18706 time to create 1 rle with old method : 0.021227598190307617 length of segment : 208 time for calcul the mask position with numpy : 0.0004572868347167969 nb_pixel_total : 28711 time to create 1 rle with old method : 0.03238105773925781 length of segment : 182 time for calcul the mask position with numpy : 0.0005035400390625 nb_pixel_total : 24332 time to create 1 rle with old method : 0.027518749237060547 length of segment : 146 time for calcul the mask position with numpy : 0.014428377151489258 nb_pixel_total : 178761 time to create 1 rle with new method : 0.018787145614624023 length of segment : 666 time for calcul the mask position with numpy : 0.002914905548095703 nb_pixel_total : 57202 time to create 1 rle with old method : 0.06232881546020508 length of segment : 311 time for calcul the mask position with numpy : 0.004736900329589844 nb_pixel_total : 71440 time to create 1 rle with old method : 0.08150553703308105 length of segment : 373 time for calcul the mask position with numpy : 0.0023610591888427734 nb_pixel_total : 28201 time to create 1 rle with old method : 0.032217979431152344 length of segment : 296 time for calcul the mask position with numpy : 0.00353240966796875 nb_pixel_total : 62348 time to create 1 rle with old method : 0.07448887825012207 length of segment : 379 time for calcul the mask position with numpy : 0.003614187240600586 nb_pixel_total : 53307 time to create 1 rle with old method : 0.06271553039550781 length of segment : 386 time for calcul the mask position with numpy : 0.00560307502746582 nb_pixel_total : 101751 time to create 1 rle with old method : 0.11872577667236328 length of segment : 375 time for calcul the mask position with numpy : 0.022532224655151367 nb_pixel_total : 283417 time to create 1 rle with new method : 0.030153512954711914 length of segment : 470 time for calcul the mask position with numpy : 0.0031833648681640625 nb_pixel_total : 73653 time to create 1 rle with old method : 0.0969383716583252 length of segment : 361 time for calcul the mask position with numpy : 0.001961231231689453 nb_pixel_total : 31489 time to create 1 rle with old method : 0.035546064376831055 length of segment : 226 time for calcul the mask position with numpy : 0.001050710678100586 nb_pixel_total : 18437 time to create 1 rle with old method : 0.02039790153503418 length of segment : 195 time for calcul the mask position with numpy : 0.0005877017974853516 nb_pixel_total : 17304 time to create 1 rle with old method : 0.019089221954345703 length of segment : 180 time for calcul the mask position with numpy : 0.00439906120300293 nb_pixel_total : 77595 time to create 1 rle with old method : 0.0877079963684082 length of segment : 333 time for calcul the mask position with numpy : 0.0014274120330810547 nb_pixel_total : 19002 time to create 1 rle with old method : 0.023138046264648438 length of segment : 141 time for calcul the mask position with numpy : 0.005545139312744141 nb_pixel_total : 92313 time to create 1 rle with old method : 0.10530471801757812 length of segment : 414 time for calcul the mask position with numpy : 0.00619053840637207 nb_pixel_total : 78105 time to create 1 rle with old method : 0.11058306694030762 length of segment : 452 time for calcul the mask position with numpy : 0.004225730895996094 nb_pixel_total : 58756 time to create 1 rle with old method : 0.06689047813415527 length of segment : 334 time for calcul the mask position with numpy : 0.007057905197143555 nb_pixel_total : 61919 time to create 1 rle with old method : 0.0709223747253418 length of segment : 528 time for calcul the mask position with numpy : 0.0032608509063720703 nb_pixel_total : 61445 time to create 1 rle with old method : 0.06796598434448242 length of segment : 374 time for calcul the mask position with numpy : 0.0014383792877197266 nb_pixel_total : 34595 time to create 1 rle with old method : 0.03979349136352539 length of segment : 258 time for calcul the mask position with numpy : 0.0006003379821777344 nb_pixel_total : 9049 time to create 1 rle with old method : 0.011126518249511719 length of segment : 151 time for calcul the mask position with numpy : 0.0017924308776855469 nb_pixel_total : 32603 time to create 1 rle with old method : 0.041352033615112305 length of segment : 220 time for calcul the mask position with numpy : 0.0011837482452392578 nb_pixel_total : 16744 time to create 1 rle with old method : 0.019809961318969727 length of segment : 161 time for calcul the mask position with numpy : 0.0032944679260253906 nb_pixel_total : 101283 time to create 1 rle with old method : 0.11085176467895508 length of segment : 294 time for calcul the mask position with numpy : 0.0006628036499023438 nb_pixel_total : 15958 time to create 1 rle with old method : 0.01925945281982422 length of segment : 133 time for calcul the mask position with numpy : 0.00024199485778808594 nb_pixel_total : 3781 time to create 1 rle with old method : 0.004142284393310547 length of segment : 84 time for calcul the mask position with numpy : 0.004255771636962891 nb_pixel_total : 94317 time to create 1 rle with old method : 0.11129570007324219 length of segment : 508 time for calcul the mask position with numpy : 0.003391265869140625 nb_pixel_total : 72589 time to create 1 rle with old method : 0.08494210243225098 length of segment : 340 time for calcul the mask position with numpy : 0.0018379688262939453 nb_pixel_total : 10710 time to create 1 rle with old method : 0.01614856719970703 length of segment : 170 time for calcul the mask position with numpy : 0.0005807876586914062 nb_pixel_total : 5803 time to create 1 rle with old method : 0.008592844009399414 length of segment : 93 time for calcul the mask position with numpy : 0.0005674362182617188 nb_pixel_total : 6978 time to create 1 rle with old method : 0.010072946548461914 length of segment : 116 time for calcul the mask position with numpy : 0.01125478744506836 nb_pixel_total : 142338 time to create 1 rle with old method : 0.1905832290649414 length of segment : 520 time for calcul the mask position with numpy : 0.0003991127014160156 nb_pixel_total : 6714 time to create 1 rle with old method : 0.007961511611938477 length of segment : 121 time for calcul the mask position with numpy : 0.0010790824890136719 nb_pixel_total : 12881 time to create 1 rle with old method : 0.015530586242675781 length of segment : 156 time for calcul the mask position with numpy : 0.0053920745849609375 nb_pixel_total : 81234 time to create 1 rle with old method : 0.09624171257019043 length of segment : 517 time for calcul the mask position with numpy : 0.0006935596466064453 nb_pixel_total : 10458 time to create 1 rle with old method : 0.013029336929321289 length of segment : 196 time for calcul the mask position with numpy : 0.0008678436279296875 nb_pixel_total : 11982 time to create 1 rle with old method : 0.014916658401489258 length of segment : 125 time for calcul the mask position with numpy : 0.00034356117248535156 nb_pixel_total : 4700 time to create 1 rle with old method : 0.0060577392578125 length of segment : 147 time for calcul the mask position with numpy : 0.010658740997314453 nb_pixel_total : 18688 time to create 1 rle with old method : 0.02366471290588379 length of segment : 307 time for calcul the mask position with numpy : 0.001207590103149414 nb_pixel_total : 20632 time to create 1 rle with old method : 0.025064706802368164 length of segment : 156 time for calcul the mask position with numpy : 0.0035202503204345703 nb_pixel_total : 58739 time to create 1 rle with old method : 0.07853126525878906 length of segment : 444 time for calcul the mask position with numpy : 0.0009510517120361328 nb_pixel_total : 12710 time to create 1 rle with old method : 0.015282392501831055 length of segment : 181 time for calcul the mask position with numpy : 0.0008671283721923828 nb_pixel_total : 12792 time to create 1 rle with old method : 0.015016317367553711 length of segment : 174 time for calcul the mask position with numpy : 0.00016307830810546875 nb_pixel_total : 4159 time to create 1 rle with old method : 0.004830837249755859 length of segment : 72 time for calcul the mask position with numpy : 0.0012319087982177734 nb_pixel_total : 30597 time to create 1 rle with old method : 0.03485894203186035 length of segment : 287 time for calcul the mask position with numpy : 0.00171661376953125 nb_pixel_total : 53784 time to create 1 rle with old method : 0.060056447982788086 length of segment : 473 time for calcul the mask position with numpy : 0.00115203857421875 nb_pixel_total : 21017 time to create 1 rle with old method : 0.024872541427612305 length of segment : 251 time for calcul the mask position with numpy : 0.0012722015380859375 nb_pixel_total : 28234 time to create 1 rle with old method : 0.0327603816986084 length of segment : 233 time for calcul the mask position with numpy : 0.004265546798706055 nb_pixel_total : 131121 time to create 1 rle with old method : 0.17131829261779785 length of segment : 446 time for calcul the mask position with numpy : 0.0016086101531982422 nb_pixel_total : 28293 time to create 1 rle with old method : 0.03309965133666992 length of segment : 240 time for calcul the mask position with numpy : 0.013205766677856445 nb_pixel_total : 296575 time to create 1 rle with new method : 0.021239519119262695 length of segment : 1042 time for calcul the mask position with numpy : 0.0007541179656982422 nb_pixel_total : 16664 time to create 1 rle with old method : 0.019759178161621094 length of segment : 113 time for calcul the mask position with numpy : 0.008846044540405273 nb_pixel_total : 219072 time to create 1 rle with new method : 0.011152505874633789 length of segment : 414 time for calcul the mask position with numpy : 0.0012857913970947266 nb_pixel_total : 40602 time to create 1 rle with old method : 0.048020124435424805 length of segment : 323 time for calcul the mask position with numpy : 0.0032150745391845703 nb_pixel_total : 119524 time to create 1 rle with old method : 0.14229655265808105 length of segment : 410 time for calcul the mask position with numpy : 0.0038661956787109375 nb_pixel_total : 104222 time to create 1 rle with old method : 0.12285828590393066 length of segment : 545 time for calcul the mask position with numpy : 0.001500844955444336 nb_pixel_total : 30068 time to create 1 rle with old method : 0.03386044502258301 length of segment : 304 time for calcul the mask position with numpy : 0.0025787353515625 nb_pixel_total : 58125 time to create 1 rle with old method : 0.06702518463134766 length of segment : 527 time for calcul the mask position with numpy : 0.0005707740783691406 nb_pixel_total : 6834 time to create 1 rle with old method : 0.00805211067199707 length of segment : 140 time for calcul the mask position with numpy : 0.006079673767089844 nb_pixel_total : 168349 time to create 1 rle with new method : 0.010130882263183594 length of segment : 461 time for calcul the mask position with numpy : 0.0010190010070800781 nb_pixel_total : 23109 time to create 1 rle with old method : 0.027684450149536133 length of segment : 131 time for calcul the mask position with numpy : 0.002232074737548828 nb_pixel_total : 25888 time to create 1 rle with old method : 0.03294944763183594 length of segment : 373 time for calcul the mask position with numpy : 0.00028824806213378906 nb_pixel_total : 2367 time to create 1 rle with old method : 0.003618955612182617 length of segment : 78 time for calcul the mask position with numpy : 0.0005347728729248047 nb_pixel_total : 7911 time to create 1 rle with old method : 0.012238502502441406 length of segment : 251 time for calcul the mask position with numpy : 0.007589817047119141 nb_pixel_total : 282388 time to create 1 rle with new method : 0.014142990112304688 length of segment : 575 time for calcul the mask position with numpy : 0.0036420822143554688 nb_pixel_total : 94122 time to create 1 rle with old method : 0.10856223106384277 length of segment : 330 time for calcul the mask position with numpy : 0.004519224166870117 nb_pixel_total : 128242 time to create 1 rle with old method : 0.16660070419311523 length of segment : 361 time for calcul the mask position with numpy : 0.0016715526580810547 nb_pixel_total : 24426 time to create 1 rle with old method : 0.028430938720703125 length of segment : 251 time for calcul the mask position with numpy : 0.0012469291687011719 nb_pixel_total : 28024 time to create 1 rle with old method : 0.03987741470336914 length of segment : 311 time for calcul the mask position with numpy : 0.0067708492279052734 nb_pixel_total : 165775 time to create 1 rle with new method : 0.009043216705322266 length of segment : 428 time for calcul the mask position with numpy : 0.002052783966064453 nb_pixel_total : 36818 time to create 1 rle with old method : 0.05320239067077637 length of segment : 296 time for calcul the mask position with numpy : 0.0010857582092285156 nb_pixel_total : 21219 time to create 1 rle with old method : 0.03376483917236328 length of segment : 233 time for calcul the mask position with numpy : 0.0008096694946289062 nb_pixel_total : 16190 time to create 1 rle with old method : 0.02154541015625 length of segment : 161 time for calcul the mask position with numpy : 0.005966663360595703 nb_pixel_total : 115494 time to create 1 rle with old method : 0.13744449615478516 length of segment : 474 time for calcul the mask position with numpy : 0.0029821395874023438 nb_pixel_total : 85698 time to create 1 rle with old method : 0.10387897491455078 length of segment : 387 time for calcul the mask position with numpy : 0.0004477500915527344 nb_pixel_total : 5444 time to create 1 rle with old method : 0.00658416748046875 length of segment : 81 time for calcul the mask position with numpy : 0.004044055938720703 nb_pixel_total : 108755 time to create 1 rle with old method : 0.1261909008026123 length of segment : 410 time for calcul the mask position with numpy : 0.0008578300476074219 nb_pixel_total : 10653 time to create 1 rle with old method : 0.01278066635131836 length of segment : 110 time for calcul the mask position with numpy : 0.0004916191101074219 nb_pixel_total : 9576 time to create 1 rle with old method : 0.011862993240356445 length of segment : 98 time for calcul the mask position with numpy : 0.0011479854583740234 nb_pixel_total : 13561 time to create 1 rle with old method : 0.017284631729125977 length of segment : 89 time for calcul the mask position with numpy : 0.004824161529541016 nb_pixel_total : 97602 time to create 1 rle with old method : 0.11477971076965332 length of segment : 153 time for calcul the mask position with numpy : 0.0015294551849365234 nb_pixel_total : 50727 time to create 1 rle with old method : 0.059668540954589844 length of segment : 400 time for calcul the mask position with numpy : 0.001790761947631836 nb_pixel_total : 18901 time to create 1 rle with old method : 0.02233576774597168 length of segment : 422 time for calcul the mask position with numpy : 0.0035889148712158203 nb_pixel_total : 66924 time to create 1 rle with old method : 0.07684564590454102 length of segment : 221 time for calcul the mask position with numpy : 0.0035839080810546875 nb_pixel_total : 120123 time to create 1 rle with old method : 0.1373589038848877 length of segment : 371 time for calcul the mask position with numpy : 0.008417129516601562 nb_pixel_total : 231834 time to create 1 rle with new method : 0.01524806022644043 length of segment : 333 time for calcul the mask position with numpy : 0.0006000995635986328 nb_pixel_total : 10537 time to create 1 rle with old method : 0.017680644989013672 length of segment : 114 time for calcul the mask position with numpy : 0.0008535385131835938 nb_pixel_total : 10408 time to create 1 rle with old method : 0.015598297119140625 length of segment : 181 time for calcul the mask position with numpy : 0.001026153564453125 nb_pixel_total : 25591 time to create 1 rle with old method : 0.03468680381774902 length of segment : 198 time for calcul the mask position with numpy : 0.0007481575012207031 nb_pixel_total : 16153 time to create 1 rle with old method : 0.019762039184570312 length of segment : 254 time for calcul the mask position with numpy : 0.001257181167602539 nb_pixel_total : 26423 time to create 1 rle with old method : 0.03081822395324707 length of segment : 215 time for calcul the mask position with numpy : 0.0011386871337890625 nb_pixel_total : 27194 time to create 1 rle with old method : 0.03497743606567383 length of segment : 318 time for calcul the mask position with numpy : 0.0005176067352294922 nb_pixel_total : 16977 time to create 1 rle with old method : 0.021449565887451172 length of segment : 356 time for calcul the mask position with numpy : 0.001809835433959961 nb_pixel_total : 47801 time to create 1 rle with old method : 0.05475449562072754 length of segment : 326 time for calcul the mask position with numpy : 0.0007615089416503906 nb_pixel_total : 26963 time to create 1 rle with old method : 0.030546903610229492 length of segment : 326 time for calcul the mask position with numpy : 0.0018634796142578125 nb_pixel_total : 72063 time to create 1 rle with old method : 0.10836029052734375 length of segment : 338 time for calcul the mask position with numpy : 0.001062631607055664 nb_pixel_total : 23228 time to create 1 rle with old method : 0.03101515769958496 length of segment : 218 time for calcul the mask position with numpy : 0.004845619201660156 nb_pixel_total : 158352 time to create 1 rle with new method : 0.007913589477539062 length of segment : 422 time for calcul the mask position with numpy : 0.0006399154663085938 nb_pixel_total : 25146 time to create 1 rle with old method : 0.04095745086669922 length of segment : 215 time for calcul the mask position with numpy : 0.006287097930908203 nb_pixel_total : 176225 time to create 1 rle with new method : 0.009209871292114258 length of segment : 869 time for calcul the mask position with numpy : 0.0006685256958007812 nb_pixel_total : 14640 time to create 1 rle with old method : 0.016751766204833984 length of segment : 143 time for calcul the mask position with numpy : 0.0025250911712646484 nb_pixel_total : 68605 time to create 1 rle with old method : 0.07782149314880371 length of segment : 795 time for calcul the mask position with numpy : 0.0005249977111816406 nb_pixel_total : 19682 time to create 1 rle with old method : 0.02271270751953125 length of segment : 228 time for calcul the mask position with numpy : 0.0010564327239990234 nb_pixel_total : 25381 time to create 1 rle with old method : 0.0283963680267334 length of segment : 245 time for calcul the mask position with numpy : 0.0034356117248535156 nb_pixel_total : 126158 time to create 1 rle with old method : 0.14839911460876465 length of segment : 501 time for calcul the mask position with numpy : 0.0018570423126220703 nb_pixel_total : 80156 time to create 1 rle with old method : 0.09418630599975586 length of segment : 247 time for calcul the mask position with numpy : 0.003795146942138672 nb_pixel_total : 77672 time to create 1 rle with old method : 0.08930850028991699 length of segment : 343 time for calcul the mask position with numpy : 0.02550983428955078 nb_pixel_total : 389611 time to create 1 rle with new method : 0.02518916130065918 length of segment : 645 time for calcul the mask position with numpy : 0.010329008102416992 nb_pixel_total : 159295 time to create 1 rle with new method : 0.01606011390686035 length of segment : 684 time for calcul the mask position with numpy : 0.002184152603149414 nb_pixel_total : 44865 time to create 1 rle with old method : 0.05273866653442383 length of segment : 248 time for calcul the mask position with numpy : 0.0029325485229492188 nb_pixel_total : 55593 time to create 1 rle with old method : 0.06189393997192383 length of segment : 431 time for calcul the mask position with numpy : 0.00048613548278808594 nb_pixel_total : 13497 time to create 1 rle with old method : 0.016132831573486328 length of segment : 361 time for calcul the mask position with numpy : 0.0023539066314697266 nb_pixel_total : 39681 time to create 1 rle with old method : 0.04517531394958496 length of segment : 383 time for calcul the mask position with numpy : 0.0004143714904785156 nb_pixel_total : 11104 time to create 1 rle with old method : 0.01310873031616211 length of segment : 131 time for calcul the mask position with numpy : 0.0009353160858154297 nb_pixel_total : 15659 time to create 1 rle with old method : 0.01877760887145996 length of segment : 208 time for calcul the mask position with numpy : 0.00193023681640625 nb_pixel_total : 51422 time to create 1 rle with old method : 0.05600857734680176 length of segment : 293 time for calcul the mask position with numpy : 0.0005269050598144531 nb_pixel_total : 19003 time to create 1 rle with old method : 0.021782398223876953 length of segment : 279 time for calcul the mask position with numpy : 0.0010449886322021484 nb_pixel_total : 23135 time to create 1 rle with old method : 0.025600671768188477 length of segment : 199 time for calcul the mask position with numpy : 0.0011925697326660156 nb_pixel_total : 24434 time to create 1 rle with old method : 0.026193857192993164 length of segment : 263 time for calcul the mask position with numpy : 0.0033473968505859375 nb_pixel_total : 73558 time to create 1 rle with old method : 0.08206439018249512 length of segment : 346 time for calcul the mask position with numpy : 0.000993490219116211 nb_pixel_total : 14436 time to create 1 rle with old method : 0.015579462051391602 length of segment : 175 time for calcul the mask position with numpy : 0.0028853416442871094 nb_pixel_total : 73641 time to create 1 rle with old method : 0.08150148391723633 length of segment : 386 time for calcul the mask position with numpy : 0.004551887512207031 nb_pixel_total : 106763 time to create 1 rle with old method : 0.11683177947998047 length of segment : 497 time for calcul the mask position with numpy : 0.0021462440490722656 nb_pixel_total : 78018 time to create 1 rle with old method : 0.08750343322753906 length of segment : 416 time for calcul the mask position with numpy : 0.0034356117248535156 nb_pixel_total : 81054 time to create 1 rle with old method : 0.08949160575866699 length of segment : 428 time for calcul the mask position with numpy : 0.0016613006591796875 nb_pixel_total : 27648 time to create 1 rle with old method : 0.03150534629821777 length of segment : 251 time for calcul the mask position with numpy : 0.0029392242431640625 nb_pixel_total : 40159 time to create 1 rle with old method : 0.0457758903503418 length of segment : 254 time for calcul the mask position with numpy : 0.009144783020019531 nb_pixel_total : 203581 time to create 1 rle with new method : 0.00919795036315918 length of segment : 853 time for calcul the mask position with numpy : 0.0020227432250976562 nb_pixel_total : 40622 time to create 1 rle with old method : 0.045694828033447266 length of segment : 346 time for calcul the mask position with numpy : 0.0004143714904785156 nb_pixel_total : 14054 time to create 1 rle with old method : 0.016200780868530273 length of segment : 149 time for calcul the mask position with numpy : 0.00912165641784668 nb_pixel_total : 190045 time to create 1 rle with new method : 0.011836767196655273 length of segment : 626 time for calcul the mask position with numpy : 0.0002655982971191406 nb_pixel_total : 8425 time to create 1 rle with old method : 0.009867191314697266 length of segment : 79 time for calcul the mask position with numpy : 0.006015777587890625 nb_pixel_total : 201294 time to create 1 rle with new method : 0.009190797805786133 length of segment : 687 time for calcul the mask position with numpy : 0.0024809837341308594 nb_pixel_total : 20923 time to create 1 rle with old method : 0.02535390853881836 length of segment : 463 time spent for convertir_results : 34.311209201812744 Inside saveOutput : final : False verbose : 0 eke 12-6-18 : saveMask need to be cleaned for new output ! Number saved : None batch 1 Loaded 850 chid ids of type : 3594 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 16600 save missing photos in datou_result : time spend for datou_step_exec : 179.47612023353577 time spend to save output : 3.7046024799346924 total time spend for step 1 : 183.18072271347046 step2:crop_condition Sat Feb 1 02:13:36 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! 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 : 12 ! batch 1 Loaded 850 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 ! Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! 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Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! map_result returned by crop_photo_return_map_crop : length : 630 About to insert : list_path_to_insert length 630 new photo from crops ! About to upload 630 photos upload in portfolio : 3736932 init cache_photo without model_param we have 630 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1738372520_2654573 we have uploaded 630 photos in the portfolio 3736932 time of upload the photos Elapsed time : 152.47409296035767 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 Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! map_result returned by crop_photo_return_map_crop : length : 89 About to insert : list_path_to_insert length 89 new photo from crops ! About to upload 89 photos upload in portfolio : 3736932 init cache_photo without model_param we have 89 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1738372697_2654573 we have uploaded 89 photos in the portfolio 3736932 time of upload the photos Elapsed time : 20.306326150894165 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 ! 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/1738372719_2654573 we have uploaded 2 photos in the portfolio 3736932 time of upload the photos Elapsed time : 0.7464475631713867 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 ! Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! map_result returned by crop_photo_return_map_crop : length : 69 About to insert : list_path_to_insert length 69 new photo from crops ! About to upload 69 photos upload in portfolio : 3736932 init cache_photo without model_param we have 69 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1738372792_2654573 we have uploaded 69 photos in the portfolio 3736932 time of upload the photos Elapsed time : 24.33455491065979 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 ! Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! map_result returned by crop_photo_return_map_crop : length : 31 About to insert : list_path_to_insert length 31 new photo from crops ! About to upload 31 photos upload in portfolio : 3736932 init cache_photo without model_param we have 31 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1738372824_2654573 we have uploaded 31 photos in the portfolio 3736932 time of upload the photos Elapsed time : 7.267431974411011 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 ! 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/1738372835_2654573 we have uploaded 2 photos in the portfolio 3736932 time of upload the photos Elapsed time : 0.9093060493469238 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 ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! map_result returned by crop_photo_return_map_crop : length : 16 About to insert : list_path_to_insert length 16 new photo from crops ! About to upload 16 photos upload in portfolio : 3736932 init cache_photo without model_param we have 16 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1738372844_2654573 we have uploaded 16 photos in the portfolio 3736932 time of upload the photos Elapsed time : 3.971219301223755 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 Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : crop_condition we use saveGeneral [1333348189, 1333348185, 1333348179, 1333348016, 1333347989, 1333347939, 1333347927, 1333347884, 1333347719, 1333347695, 1333347643, 1333347642] Looping around the photos to save general results len do output : 839 /1333551952Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333551953Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333551954Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333551955Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333551956Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333551957Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333551958Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333551959Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333551960Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333551961Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333551962Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333551963Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333551964Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333551965Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333551966Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333551967Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333551968Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333551969Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333551970Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333551971Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333551972Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333551973Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333551974Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333551975Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333551976Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333551977Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333551978Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333551979Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333551980Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333551981Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333551982Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333551984Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333551986Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333551987Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333551988Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333551989Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333551990Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333551991Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333551992Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333551993Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333551994Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333551995Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333551996Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333551997Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333551998Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333551999Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552000Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552001Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552002Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552003Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552004Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552005Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552006Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552007Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552008Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552009Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552010Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552011Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552012Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552013Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552015Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552016Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552017Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552018Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552019Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552020Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552021Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552022Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552023Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552024Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552025Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552026Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552027Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552028Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552029Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552030Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552031Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552032Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552033Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552034Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552035Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552036Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552037Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552038Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552039Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552040Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552041Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552042Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552043Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552044Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552045Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552046Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552047Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552048Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552049Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552050Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552051Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552052Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552053Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552055Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552056Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552057Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552058Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552060Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552061Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552062Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552063Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552064Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552065Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552066Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552067Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552068Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552069Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552070Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552071Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552072Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552073Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552074Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552075Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552076Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552077Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552078Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552079Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552080Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552081Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552082Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552083Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552084Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552085Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552086Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552087Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552088Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552089Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552090Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552091Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552092Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552093Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552094Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552095Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552096Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552097Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552099Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552100Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552103Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552107Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552111Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552115Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552119Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552123Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552128Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552131Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552135Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552140Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552144Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552148Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552152Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552156Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552158Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552160Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552162Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552164Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552166Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552168Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552170Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552172Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552174Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552176Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552178Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552180Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552183Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552186Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552188Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552190Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552192Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552195Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552197Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552199Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552202Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552204Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552206Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552208Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552210Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552212Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552214Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552216Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552218Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552220Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552224Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552226Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552228Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552230Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552232Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552234Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552236Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552238Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552240Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552242Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552244Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552246Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552248Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552250Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552252Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552254Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552256Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552258Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552260Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552262Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552264Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552266Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552268Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552270Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552272Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552274Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552276Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552279Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552281Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552283Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552285Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552287Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552289Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552291Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552293Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552295Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552297Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552299Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552301Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552303Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552305Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552307Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552309Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552311Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552313Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552315Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552317Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552319Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552321Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552323Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552325Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552327Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552329Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552332Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552334Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552336Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552338Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552340Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552342Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552344Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552346Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552348Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552350Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552352Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552354Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552356Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552358Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552360Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552362Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552364Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552366Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552368Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552370Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552372Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552374Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552377Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552379Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552381Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552383Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552386Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552388Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552390Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552392Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552394Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552396Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552398Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552400Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552402Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552404Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552406Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552408Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1333552410Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . 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('3318', None, None, None, None, None, None, None, '2535942') ('3318', '20128891', '1333348189', None, None, None, None, None, '2535942') ('3318', None, None, None, None, None, None, None, '2535942') ('3318', '20128891', '1333348185', None, None, None, None, None, '2535942') ('3318', None, None, None, None, None, None, None, '2535942') ('3318', '20128891', '1333348179', None, None, None, None, None, '2535942') ('3318', None, None, None, None, None, None, None, '2535942') ('3318', '20128891', '1333348016', None, None, None, None, None, '2535942') ('3318', None, None, None, None, None, None, None, '2535942') ('3318', '20128891', '1333347989', None, None, None, None, None, '2535942') ('3318', None, None, None, None, None, None, None, '2535942') ('3318', '20128891', '1333347939', None, None, None, None, None, '2535942') ('3318', None, None, None, None, None, None, None, '2535942') ('3318', '20128891', '1333347927', None, None, None, None, None, '2535942') ('3318', None, None, None, None, None, None, None, '2535942') ('3318', '20128891', '1333347884', None, None, None, None, None, '2535942') ('3318', None, None, None, None, None, None, None, '2535942') ('3318', '20128891', '1333347719', None, None, None, None, None, '2535942') ('3318', None, None, None, None, None, None, None, '2535942') ('3318', '20128891', '1333347695', None, None, None, None, None, '2535942') ('3318', None, None, None, None, None, None, None, '2535942') ('3318', '20128891', '1333347643', None, None, None, None, None, '2535942') ('3318', None, None, None, None, None, None, None, '2535942') ('3318', '20128891', '1333347642', None, None, None, None, None, '2535942') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 2529 time used for this insertion : 0.24829339981079102 save_final save missing photos in datou_result : time spend for datou_step_exec : 432.18229246139526 time spend to save output : 0.268218994140625 total time spend for step 2 : 432.4505114555359 step3:rle_unique_nms_with_priority Sat Feb 1 02:20:48 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed 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 VR 22-3-18 : For now we do not clean correctly the datou structure Begin step rle-unique-nms batch 1 Loaded 850 chid ids of type : 3594 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++nb_obj : 39 nb_hashtags : 6 time to prepare the origin masks : 7.944004774093628 time for calcul the mask position with numpy : 0.7399580478668213 nb_pixel_total : 5779089 time to create 1 rle with new method : 1.3111004829406738 time for calcul the mask position with numpy : 0.03472447395324707 nb_pixel_total : 31807 time to create 1 rle with old method : 0.04446983337402344 time for calcul the mask position with numpy : 0.02953195571899414 nb_pixel_total : 8270 time to create 1 rle with old method : 0.009597063064575195 time for calcul the mask position with numpy : 0.029669761657714844 nb_pixel_total : 23216 time to create 1 rle with old method : 0.026429414749145508 time for calcul the mask position with numpy : 0.031099319458007812 nb_pixel_total : 25151 time to create 1 rle with old method : 0.02956390380859375 time for calcul the mask position with numpy : 0.029549598693847656 nb_pixel_total : 9142 time to create 1 rle with old method : 0.011022567749023438 time for calcul the mask position with numpy : 0.03153085708618164 nb_pixel_total : 8140 time to create 1 rle with old method : 0.012175559997558594 time for calcul the mask position with numpy : 0.030167341232299805 nb_pixel_total : 30529 time to create 1 rle with old method : 0.03471875190734863 time for calcul the mask position with numpy : 0.029134511947631836 nb_pixel_total : 9456 time to create 1 rle with old method : 0.01105356216430664 time for calcul the mask position with numpy : 0.02916884422302246 nb_pixel_total : 4165 time to create 1 rle with old method : 0.004994630813598633 time for calcul the mask position with numpy : 0.029469966888427734 nb_pixel_total : 12391 time to create 1 rle with old method : 0.01416015625 time for calcul the mask position with numpy : 0.03040933609008789 nb_pixel_total : 15236 time to create 1 rle with old method : 0.02466583251953125 time for calcul the mask position with numpy : 0.03283071517944336 nb_pixel_total : 23950 time to create 1 rle with old method : 0.028699874877929688 time for calcul the mask position with numpy : 0.03391408920288086 nb_pixel_total : 20974 time to create 1 rle with old method : 0.02485489845275879 time for calcul the mask position with numpy : 0.029395103454589844 nb_pixel_total : 24079 time to create 1 rle with old method : 0.029870271682739258 time for calcul the mask position with numpy : 0.030301332473754883 nb_pixel_total : 33193 time to create 1 rle with old method : 0.06348586082458496 time for calcul the mask position with numpy : 0.030060768127441406 nb_pixel_total : 21327 time to create 1 rle with old method : 0.024669885635375977 time for calcul the mask position with numpy : 0.029734373092651367 nb_pixel_total : 14197 time to create 1 rle with old method : 0.017050743103027344 time for calcul the mask position with numpy : 0.03023076057434082 nb_pixel_total : 79695 time to create 1 rle with old method : 0.08981108665466309 time for calcul the mask position with numpy : 0.031206846237182617 nb_pixel_total : 145901 time to create 1 rle with old method : 0.1694631576538086 time for calcul the mask position with numpy : 0.03121495246887207 nb_pixel_total : 3298 time to create 1 rle with old method : 0.005427360534667969 time for calcul the mask position with numpy : 0.03966259956359863 nb_pixel_total : 5464 time to create 1 rle with old method : 0.008881330490112305 time for calcul the mask position with numpy : 0.03857088088989258 nb_pixel_total : 9883 time to create 1 rle with old method : 0.011105537414550781 time for calcul the mask position with numpy : 0.02933359146118164 nb_pixel_total : 3512 time to create 1 rle with old method : 0.004145622253417969 time for calcul the mask position with numpy : 0.032956838607788086 nb_pixel_total : 70379 time to create 1 rle with old method : 0.08475446701049805 time for calcul the mask position with numpy : 0.0322108268737793 nb_pixel_total : 17359 time to create 1 rle with old method : 0.020573854446411133 time for calcul the mask position with numpy : 0.029569387435913086 nb_pixel_total : 58413 time to create 1 rle with old method : 0.07219576835632324 time for calcul the mask position with numpy : 0.032355546951293945 nb_pixel_total : 13666 time to create 1 rle with old method : 0.015651464462280273 time for calcul the mask position with numpy : 0.029326438903808594 nb_pixel_total : 25724 time to create 1 rle with old method : 0.028980016708374023 time for calcul the mask position with numpy : 0.02995467185974121 nb_pixel_total : 79852 time to create 1 rle with old method : 0.0894010066986084 time for calcul the mask position with numpy : 0.032389163970947266 nb_pixel_total : 12938 time to create 1 rle with old method : 0.014957427978515625 time for calcul the mask position with numpy : 0.029094934463500977 nb_pixel_total : 661 time to create 1 rle with old method : 0.0016396045684814453 time for calcul the mask position with numpy : 0.03813624382019043 nb_pixel_total : 18076 time to create 1 rle with old method : 0.021445512771606445 time for calcul the mask position with numpy : 0.029271364212036133 nb_pixel_total : 31065 time to create 1 rle with old method : 0.03635358810424805 time for calcul the mask position with numpy : 0.02968621253967285 nb_pixel_total : 85 time to create 1 rle with old method : 0.0005443096160888672 time for calcul the mask position with numpy : 0.031151771545410156 nb_pixel_total : 4221 time to create 1 rle with old method : 0.004977703094482422 time for calcul the mask position with numpy : 0.030605792999267578 nb_pixel_total : 4498 time to create 1 rle with old method : 0.0063037872314453125 time for calcul the mask position with numpy : 0.03211498260498047 nb_pixel_total : 280317 time to create 1 rle with new method : 1.5934488773345947 time for calcul the mask position with numpy : 0.030184268951416016 nb_pixel_total : 90921 time to create 1 rle with old method : 0.10607767105102539 create new chi : 6.143934488296509 time to delete rle : 0.016093015670776367 batch 1 Loaded 79 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 282 TO DO : save crop sub photo not yet done ! save time : 0.3077247142791748 nb_obj : 42 nb_hashtags : 5 time to prepare the origin masks : 7.263979434967041 time for calcul the mask position with numpy : 1.3680462837219238 nb_pixel_total : 5087333 time to create 1 rle with new method : 0.7375261783599854 time for calcul the mask position with numpy : 0.030759572982788086 nb_pixel_total : 29284 time to create 1 rle with old method : 0.036417245864868164 time for calcul the mask position with numpy : 0.035597801208496094 nb_pixel_total : 79992 time to create 1 rle with old method : 0.10673403739929199 time for calcul the mask position with numpy : 0.03988957405090332 nb_pixel_total : 194504 time to create 1 rle with new method : 0.4559011459350586 time for calcul the mask position with numpy : 0.029314041137695312 nb_pixel_total : 12602 time to create 1 rle with old method : 0.014946222305297852 time for calcul the mask position with numpy : 0.029422760009765625 nb_pixel_total : 70962 time to create 1 rle with old method : 0.07950401306152344 time for calcul the mask position with numpy : 0.030084848403930664 nb_pixel_total : 237836 time to create 1 rle with new method : 0.8500611782073975 time for calcul the mask position with numpy : 0.02783823013305664 nb_pixel_total : 17570 time to create 1 rle with old method : 0.02058887481689453 time for calcul the mask position with numpy : 0.02912116050720215 nb_pixel_total : 34375 time to create 1 rle with old method : 0.0412442684173584 time for calcul the mask position with numpy : 0.03245806694030762 nb_pixel_total : 39202 time to create 1 rle with old method : 0.04579615592956543 time for calcul the mask position with numpy : 0.029428482055664062 nb_pixel_total : 7164 time to create 1 rle with old method : 0.008234262466430664 time for calcul the mask position with numpy : 0.02945685386657715 nb_pixel_total : 12684 time to create 1 rle with old method : 0.015118837356567383 time for calcul the mask position with numpy : 0.029155254364013672 nb_pixel_total : 1457 time to create 1 rle with old method : 0.0017745494842529297 time for calcul the mask position with numpy : 0.02884817123413086 nb_pixel_total : 3739 time to create 1 rle with old method : 0.005122661590576172 time for calcul the mask position with numpy : 0.029790639877319336 nb_pixel_total : 171926 time to create 1 rle with new method : 0.6749427318572998 time for calcul the mask position with numpy : 0.029385089874267578 nb_pixel_total : 16269 time to create 1 rle with old method : 0.018166780471801758 time for calcul the mask position with numpy : 0.029251575469970703 nb_pixel_total : 41855 time to create 1 rle with old method : 0.04656076431274414 time for calcul the mask position with numpy : 0.02947402000427246 nb_pixel_total : 42025 time to create 1 rle with old method : 0.04950118064880371 time for calcul the mask position with numpy : 0.029784202575683594 nb_pixel_total : 92011 time to create 1 rle with old method : 0.1080479621887207 time for calcul the mask position with numpy : 0.031064510345458984 nb_pixel_total : 49498 time to create 1 rle with old method : 0.05815458297729492 time for calcul the mask position with numpy : 0.02927422523498535 nb_pixel_total : 11554 time to create 1 rle with old method : 0.013803720474243164 time for calcul the mask position with numpy : 0.02927398681640625 nb_pixel_total : 23998 time to create 1 rle with old method : 0.026980161666870117 time for calcul the mask position with numpy : 0.029392242431640625 nb_pixel_total : 163 time to create 1 rle with old method : 0.0003743171691894531 time for calcul the mask position with numpy : 0.028858661651611328 nb_pixel_total : 6789 time to create 1 rle with old method : 0.008049964904785156 time for calcul the mask position with numpy : 0.029222488403320312 nb_pixel_total : 58991 time to create 1 rle with old method : 0.06908130645751953 time for calcul the mask position with numpy : 0.029503345489501953 nb_pixel_total : 16868 time to create 1 rle with old method : 0.019034862518310547 time for calcul the mask position with numpy : 0.029475927352905273 nb_pixel_total : 263 time to create 1 rle with old method : 0.0005211830139160156 time for calcul the mask position with numpy : 0.02948594093322754 nb_pixel_total : 19262 time to create 1 rle with old method : 0.028048276901245117 time for calcul the mask position with numpy : 0.02930450439453125 nb_pixel_total : 148 time to create 1 rle with old method : 0.00038743019104003906 time for calcul the mask position with numpy : 0.029679536819458008 nb_pixel_total : 21609 time to create 1 rle with old method : 0.024857044219970703 time for calcul the mask position with numpy : 0.0343625545501709 nb_pixel_total : 348078 time to create 1 rle with new method : 0.5251119136810303 time for calcul the mask position with numpy : 0.029203176498413086 nb_pixel_total : 16878 time to create 1 rle with old method : 0.01943516731262207 time for calcul the mask position with numpy : 0.029752492904663086 nb_pixel_total : 1269 time to create 1 rle with old method : 0.0016155242919921875 time for calcul the mask position with numpy : 0.029609203338623047 nb_pixel_total : 63 time to create 1 rle with old method : 0.0001423358917236328 time for calcul the mask position with numpy : 0.02935957908630371 nb_pixel_total : 6052 time to create 1 rle with old method : 0.006806612014770508 time for calcul the mask position with numpy : 0.029631614685058594 nb_pixel_total : 278 time to create 1 rle with old method : 0.0004458427429199219 time for calcul the mask position with numpy : 0.029727697372436523 nb_pixel_total : 12978 time to create 1 rle with old method : 0.015650033950805664 time for calcul the mask position with numpy : 0.030432701110839844 nb_pixel_total : 196411 time to create 1 rle with new method : 0.6899592876434326 time for calcul the mask position with numpy : 0.029956579208374023 nb_pixel_total : 10687 time to create 1 rle with old method : 0.0127410888671875 time for calcul the mask position with numpy : 0.02963876724243164 nb_pixel_total : 32734 time to create 1 rle with old method : 0.03787684440612793 time for calcul the mask position with numpy : 0.029473304748535156 nb_pixel_total : 15326 time to create 1 rle with old method : 0.018242835998535156 time for calcul the mask position with numpy : 0.029304981231689453 nb_pixel_total : 7553 time to create 1 rle with old method : 0.009057283401489258 create new chi : 7.68734335899353 time to delete rle : 0.0031766891479492188 batch 1 Loaded 92 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 2654 TO DO : save crop sub photo not yet done ! save time : 0.38939785957336426 nb_obj : 48 nb_hashtags : 6 time to prepare the origin masks : 7.7953572273254395 time for calcul the mask position with numpy : 1.2288093566894531 nb_pixel_total : 5634940 time to create 1 rle with new method : 0.7451732158660889 time for calcul the mask position with numpy : 0.0642857551574707 nb_pixel_total : 30905 time to create 1 rle with old method : 0.0382540225982666 time for calcul the mask position with numpy : 0.02912139892578125 nb_pixel_total : 14469 time to create 1 rle with old method : 0.016323089599609375 time for calcul the mask position with numpy : 0.02902841567993164 nb_pixel_total : 25113 time to create 1 rle with old method : 0.027652263641357422 time for calcul the mask position with numpy : 0.029171228408813477 nb_pixel_total : 41471 time to create 1 rle with old method : 0.04744410514831543 time for calcul the mask position with numpy : 0.02967691421508789 nb_pixel_total : 13138 time to create 1 rle with old method : 0.015628576278686523 time for calcul the mask position with numpy : 0.030815601348876953 nb_pixel_total : 16870 time to create 1 rle with old method : 0.019743919372558594 time for calcul the mask position with numpy : 0.02998661994934082 nb_pixel_total : 9508 time to create 1 rle with old method : 0.010689735412597656 time for calcul the mask position with numpy : 0.030168771743774414 nb_pixel_total : 97685 time to create 1 rle with old method : 0.11070704460144043 time for calcul the mask position with numpy : 0.02898383140563965 nb_pixel_total : 13340 time to create 1 rle with old method : 0.014962196350097656 time for calcul the mask position with numpy : 0.029459238052368164 nb_pixel_total : 18993 time to create 1 rle with old method : 0.02336883544921875 time for calcul the mask position with numpy : 0.032258033752441406 nb_pixel_total : 4504 time to create 1 rle with old method : 0.00520014762878418 time for calcul the mask position with numpy : 0.029300451278686523 nb_pixel_total : 12494 time to create 1 rle with old method : 0.014693498611450195 time for calcul the mask position with numpy : 0.029567956924438477 nb_pixel_total : 33058 time to create 1 rle with old method : 0.039467811584472656 time for calcul the mask position with numpy : 0.02939128875732422 nb_pixel_total : 26991 time to create 1 rle with old method : 0.030331850051879883 time for calcul the mask position with numpy : 0.0296475887298584 nb_pixel_total : 18553 time to create 1 rle with old method : 0.022248029708862305 time for calcul the mask position with numpy : 0.029619216918945312 nb_pixel_total : 46722 time to create 1 rle with old method : 0.05267500877380371 time for calcul the mask position with numpy : 0.029400110244750977 nb_pixel_total : 30209 time to create 1 rle with old method : 0.03445029258728027 time for calcul the mask position with numpy : 0.029268980026245117 nb_pixel_total : 7551 time to create 1 rle with old method : 0.008961915969848633 time for calcul the mask position with numpy : 0.029178142547607422 nb_pixel_total : 13676 time to create 1 rle with old method : 0.015552997589111328 time for calcul the mask position with numpy : 0.029190540313720703 nb_pixel_total : 8171 time to create 1 rle with old method : 0.009215116500854492 time for calcul the mask position with numpy : 0.02956557273864746 nb_pixel_total : 18512 time to create 1 rle with old method : 0.02189469337463379 time for calcul the mask position with numpy : 0.029458045959472656 nb_pixel_total : 16380 time to create 1 rle with old method : 0.018500328063964844 time for calcul the mask position with numpy : 0.030279874801635742 nb_pixel_total : 16558 time to create 1 rle with old method : 0.026311635971069336 time for calcul the mask position with numpy : 0.034001827239990234 nb_pixel_total : 48616 time to create 1 rle with old method : 0.05917549133300781 time for calcul the mask position with numpy : 0.030071020126342773 nb_pixel_total : 24031 time to create 1 rle with old method : 0.027509689331054688 time for calcul the mask position with numpy : 0.029604673385620117 nb_pixel_total : 21654 time to create 1 rle with old method : 0.025746822357177734 time for calcul the mask position with numpy : 0.029579639434814453 nb_pixel_total : 19865 time to create 1 rle with old method : 0.022323131561279297 time for calcul the mask position with numpy : 0.02912759780883789 nb_pixel_total : 4959 time to create 1 rle with old method : 0.005903005599975586 time for calcul the mask position with numpy : 0.02886509895324707 nb_pixel_total : 38024 time to create 1 rle with old method : 0.04179692268371582 time for calcul the mask position with numpy : 0.02976536750793457 nb_pixel_total : 45294 time to create 1 rle with old method : 0.05053377151489258 time for calcul the mask position with numpy : 0.03049468994140625 nb_pixel_total : 48453 time to create 1 rle with old method : 0.055084228515625 time for calcul the mask position with numpy : 0.028946876525878906 nb_pixel_total : 6747 time to create 1 rle with old method : 0.00762629508972168 time for calcul the mask position with numpy : 0.029238224029541016 nb_pixel_total : 16573 time to create 1 rle with old method : 0.01912236213684082 time for calcul the mask position with numpy : 0.02908468246459961 nb_pixel_total : 39351 time to create 1 rle with old method : 0.04359698295593262 time for calcul the mask position with numpy : 0.02905750274658203 nb_pixel_total : 39016 time to create 1 rle with old method : 0.044302940368652344 time for calcul the mask position with numpy : 0.028942108154296875 nb_pixel_total : 29103 time to create 1 rle with old method : 0.03297305107116699 time for calcul the mask position with numpy : 0.03043675422668457 nb_pixel_total : 172128 time to create 1 rle with new method : 0.5985305309295654 time for calcul the mask position with numpy : 0.030440568923950195 nb_pixel_total : 31798 time to create 1 rle with old method : 0.03787994384765625 time for calcul the mask position with numpy : 0.030306339263916016 nb_pixel_total : 99027 time to create 1 rle with old method : 0.11730718612670898 time for calcul the mask position with numpy : 0.0320887565612793 nb_pixel_total : 23975 time to create 1 rle with old method : 0.041368961334228516 time for calcul the mask position with numpy : 0.032984256744384766 nb_pixel_total : 16399 time to create 1 rle with old method : 0.018527984619140625 time for calcul the mask position with numpy : 0.029660940170288086 nb_pixel_total : 49829 time to create 1 rle with old method : 0.05555534362792969 time for calcul the mask position with numpy : 0.029576778411865234 nb_pixel_total : 22012 time to create 1 rle with old method : 0.024886369705200195 time for calcul the mask position with numpy : 0.029991865158081055 nb_pixel_total : 19654 time to create 1 rle with old method : 0.024609804153442383 time for calcul the mask position with numpy : 0.03452563285827637 nb_pixel_total : 4108 time to create 1 rle with old method : 0.005008220672607422 time for calcul the mask position with numpy : 0.030441761016845703 nb_pixel_total : 24115 time to create 1 rle with old method : 0.03168082237243652 time for calcul the mask position with numpy : 0.03150534629821777 nb_pixel_total : 35698 time to create 1 rle with old method : 0.04700183868408203 create new chi : 5.664581060409546 time to delete rle : 0.007526397705078125 batch 1 Loaded 95 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! save time : 0.36545610427856445 nb_obj : 60 nb_hashtags : 6 time to prepare the origin masks : 7.917041778564453 time for calcul the mask position with numpy : 0.4074125289916992 nb_pixel_total : 6057194 time to create 1 rle with new method : 0.5840063095092773 time for calcul the mask position with numpy : 0.029520034790039062 nb_pixel_total : 6325 time to create 1 rle with old method : 0.00722813606262207 time for calcul the mask position with numpy : 0.02972722053527832 nb_pixel_total : 25547 time to create 1 rle with old method : 0.02977299690246582 time for calcul the mask position with numpy : 0.029448747634887695 nb_pixel_total : 4235 time to create 1 rle with old method : 0.0049054622650146484 time for calcul the mask position with numpy : 0.029709339141845703 nb_pixel_total : 23633 time to create 1 rle with old method : 0.0284121036529541 time for calcul the mask position with numpy : 0.03058910369873047 nb_pixel_total : 28644 time to create 1 rle with old method : 0.04547739028930664 time for calcul the mask position with numpy : 0.032764434814453125 nb_pixel_total : 15849 time to create 1 rle with old method : 0.01828908920288086 time for calcul the mask position with numpy : 0.029066085815429688 nb_pixel_total : 18287 time to create 1 rle with old method : 0.02057790756225586 time for calcul the mask position with numpy : 0.028972148895263672 nb_pixel_total : 23397 time to create 1 rle with old method : 0.026130199432373047 time for calcul the mask position with numpy : 0.029232263565063477 nb_pixel_total : 17543 time to create 1 rle with old method : 0.0201871395111084 time for calcul the mask position with numpy : 0.02959609031677246 nb_pixel_total : 14051 time to create 1 rle with old method : 0.01664566993713379 time for calcul the mask position with numpy : 0.029719829559326172 nb_pixel_total : 26743 time to create 1 rle with old method : 0.030237913131713867 time for calcul the mask position with numpy : 0.029957294464111328 nb_pixel_total : 48700 time to create 1 rle with old method : 0.0590057373046875 time for calcul the mask position with numpy : 0.02961277961730957 nb_pixel_total : 13798 time to create 1 rle with old method : 0.015490531921386719 time for calcul the mask position with numpy : 0.02930593490600586 nb_pixel_total : 13575 time to create 1 rle with old method : 0.015491008758544922 time for calcul the mask position with numpy : 0.03021526336669922 nb_pixel_total : 21102 time to create 1 rle with old method : 0.025534391403198242 time for calcul the mask position with numpy : 0.03005838394165039 nb_pixel_total : 20877 time to create 1 rle with old method : 0.023918628692626953 time for calcul the mask position with numpy : 0.030187129974365234 nb_pixel_total : 20867 time to create 1 rle with old method : 0.02393817901611328 time for calcul the mask position with numpy : 0.02951359748840332 nb_pixel_total : 11126 time to create 1 rle with old method : 0.013145685195922852 time for calcul the mask position with numpy : 0.029313325881958008 nb_pixel_total : 10687 time to create 1 rle with old method : 0.014429330825805664 time for calcul the mask position with numpy : 0.030715465545654297 nb_pixel_total : 24459 time to create 1 rle with old method : 0.0390934944152832 time for calcul the mask position with numpy : 0.033390045166015625 nb_pixel_total : 39853 time to create 1 rle with old method : 0.05802559852600098 time for calcul the mask position with numpy : 0.030832529067993164 nb_pixel_total : 15358 time to create 1 rle with old method : 0.018688201904296875 time for calcul the mask position with numpy : 0.030164241790771484 nb_pixel_total : 29660 time to create 1 rle with old method : 0.035513877868652344 time for calcul the mask position with numpy : 0.02984619140625 nb_pixel_total : 11318 time to create 1 rle with old method : 0.013155937194824219 time for calcul the mask position with numpy : 0.030414581298828125 nb_pixel_total : 37515 time to create 1 rle with old method : 0.044713497161865234 time for calcul the mask position with numpy : 0.02972102165222168 nb_pixel_total : 14794 time to create 1 rle with old method : 0.01683330535888672 time for calcul the mask position with numpy : 0.029919147491455078 nb_pixel_total : 27543 time to create 1 rle with old method : 0.03102421760559082 time for calcul the mask position with numpy : 0.03571581840515137 nb_pixel_total : 7099 time to create 1 rle with old method : 0.00807952880859375 time for calcul the mask position with numpy : 0.03050518035888672 nb_pixel_total : 14001 time to create 1 rle with old method : 0.01718306541442871 time for calcul the mask position with numpy : 0.029567718505859375 nb_pixel_total : 7714 time to create 1 rle with old method : 0.009356975555419922 time for calcul the mask position with numpy : 0.031302452087402344 nb_pixel_total : 3992 time to create 1 rle with old method : 0.004716396331787109 time for calcul the mask position with numpy : 0.030188798904418945 nb_pixel_total : 6693 time to create 1 rle with old method : 0.009084701538085938 time for calcul the mask position with numpy : 0.03706812858581543 nb_pixel_total : 6167 time to create 1 rle with old method : 0.009657144546508789 time for calcul the mask position with numpy : 0.04026460647583008 nb_pixel_total : 11312 time to create 1 rle with old method : 0.01801133155822754 time for calcul the mask position with numpy : 0.039972782135009766 nb_pixel_total : 19075 time to create 1 rle with old method : 0.02415180206298828 time for calcul the mask position with numpy : 0.03110527992248535 nb_pixel_total : 4220 time to create 1 rle with old method : 0.00506138801574707 time for calcul the mask position with numpy : 0.029238224029541016 nb_pixel_total : 16441 time to create 1 rle with old method : 0.019672393798828125 time for calcul the mask position with numpy : 0.029147624969482422 nb_pixel_total : 8119 time to create 1 rle with old method : 0.009536981582641602 time for calcul the mask position with numpy : 0.02933955192565918 nb_pixel_total : 8254 time to create 1 rle with old method : 0.010082483291625977 time for calcul the mask position with numpy : 0.029186725616455078 nb_pixel_total : 11620 time to create 1 rle with old method : 0.013463497161865234 time for calcul the mask position with numpy : 0.029591798782348633 nb_pixel_total : 44129 time to create 1 rle with old method : 0.05373525619506836 time for calcul the mask position with numpy : 0.033679962158203125 nb_pixel_total : 4857 time to create 1 rle with old method : 0.00796651840209961 time for calcul the mask position with numpy : 0.030787229537963867 nb_pixel_total : 8766 time to create 1 rle with old method : 0.010484933853149414 time for calcul the mask position with numpy : 0.02924489974975586 nb_pixel_total : 12385 time to create 1 rle with old method : 0.014948844909667969 time for calcul the mask position with numpy : 0.029208660125732422 nb_pixel_total : 4431 time to create 1 rle with old method : 0.005052804946899414 time for calcul the mask position with numpy : 0.029507875442504883 nb_pixel_total : 34961 time to create 1 rle with old method : 0.04208040237426758 time for calcul the mask position with numpy : 0.029247045516967773 nb_pixel_total : 3045 time to create 1 rle with old method : 0.0034716129302978516 time for calcul the mask position with numpy : 0.029105424880981445 nb_pixel_total : 4165 time to create 1 rle with old method : 0.004785060882568359 time for calcul the mask position with numpy : 0.029187440872192383 nb_pixel_total : 3704 time to create 1 rle with old method : 0.004296541213989258 time for calcul the mask position with numpy : 0.029416322708129883 nb_pixel_total : 4964 time to create 1 rle with old method : 0.00598597526550293 time for calcul the mask position with numpy : 0.029537200927734375 nb_pixel_total : 65460 time to create 1 rle with old method : 0.07636833190917969 time for calcul the mask position with numpy : 0.030086755752563477 nb_pixel_total : 24736 time to create 1 rle with old method : 0.02810955047607422 time for calcul the mask position with numpy : 0.029479503631591797 nb_pixel_total : 10839 time to create 1 rle with old method : 0.013057947158813477 time for calcul the mask position with numpy : 0.029273033142089844 nb_pixel_total : 11298 time to create 1 rle with old method : 0.012812614440917969 time for calcul the mask position with numpy : 0.02935504913330078 nb_pixel_total : 14115 time to create 1 rle with old method : 0.016046762466430664 time for calcul the mask position with numpy : 0.029475927352905273 nb_pixel_total : 12455 time to create 1 rle with old method : 0.014177799224853516 time for calcul the mask position with numpy : 0.02933049201965332 nb_pixel_total : 682 time to create 1 rle with old method : 0.001024484634399414 time for calcul the mask position with numpy : 0.029451608657836914 nb_pixel_total : 13134 time to create 1 rle with old method : 0.015411615371704102 time for calcul the mask position with numpy : 0.029600858688354492 nb_pixel_total : 24727 time to create 1 rle with old method : 0.029932260513305664 create new chi : 4.073068857192993 time to delete rle : 0.004424333572387695 batch 1 Loaded 119 chid ids of type : 3594 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 151 TO DO : save crop sub photo not yet done ! save time : 0.20658659934997559 nb_obj : 64 nb_hashtags : 5 time to prepare the origin masks : 7.768002986907959 time for calcul the mask position with numpy : 1.0863251686096191 nb_pixel_total : 5489862 time to create 1 rle with new method : 0.6665465831756592 time for calcul the mask position with numpy : 0.02934432029724121 nb_pixel_total : 8169 time to create 1 rle with old method : 0.009762287139892578 time for calcul the mask position with numpy : 0.029271364212036133 nb_pixel_total : 13148 time to create 1 rle with old method : 0.015413999557495117 time for calcul the mask position with numpy : 0.029400110244750977 nb_pixel_total : 49445 time to create 1 rle with old method : 0.05559968948364258 time for calcul the mask position with numpy : 0.028636693954467773 nb_pixel_total : 21302 time to create 1 rle with old method : 0.024813413619995117 time for calcul the mask position with numpy : 0.02957749366760254 nb_pixel_total : 32189 time to create 1 rle with old method : 0.03821921348571777 time for calcul the mask position with numpy : 0.029448986053466797 nb_pixel_total : 8653 time to create 1 rle with old method : 0.010353803634643555 time for calcul the mask position with numpy : 0.0292813777923584 nb_pixel_total : 5727 time to create 1 rle with old method : 0.0065898895263671875 time for calcul the mask position with numpy : 0.028231143951416016 nb_pixel_total : 6073 time to create 1 rle with old method : 0.006632804870605469 time for calcul the mask position with numpy : 0.028626680374145508 nb_pixel_total : 30948 time to create 1 rle with old method : 0.03522014617919922 time for calcul the mask position with numpy : 0.027724504470825195 nb_pixel_total : 15581 time to create 1 rle with old method : 0.0166015625 time for calcul the mask position with numpy : 0.031058549880981445 nb_pixel_total : 49325 time to create 1 rle with old method : 0.055021047592163086 time for calcul the mask position with numpy : 0.030353546142578125 nb_pixel_total : 51379 time to create 1 rle with old method : 0.05721473693847656 time for calcul the mask position with numpy : 0.029758930206298828 nb_pixel_total : 76396 time to create 1 rle with old method : 0.08421850204467773 time for calcul the mask position with numpy : 0.028295040130615234 nb_pixel_total : 250 time to create 1 rle with old method : 0.0004940032958984375 time for calcul the mask position with numpy : 0.028672456741333008 nb_pixel_total : 25132 time to create 1 rle with old method : 0.028435707092285156 time for calcul the mask position with numpy : 0.027984142303466797 nb_pixel_total : 20622 time to create 1 rle with old method : 0.022182941436767578 time for calcul the mask position with numpy : 0.02681422233581543 nb_pixel_total : 6308 time to create 1 rle with old method : 0.006730318069458008 time for calcul the mask position with numpy : 0.027533769607543945 nb_pixel_total : 8067 time to create 1 rle with old method : 0.008971214294433594 time for calcul the mask position with numpy : 0.02714395523071289 nb_pixel_total : 22631 time to create 1 rle with old method : 0.02362513542175293 time for calcul the mask position with numpy : 0.028989791870117188 nb_pixel_total : 11676 time to create 1 rle with old method : 0.013181924819946289 time for calcul the mask position with numpy : 0.028356552124023438 nb_pixel_total : 6212 time to create 1 rle with old method : 0.007305145263671875 time for calcul the mask position with numpy : 0.027481555938720703 nb_pixel_total : 12697 time to create 1 rle with old method : 0.013770341873168945 time for calcul the mask position with numpy : 0.027893781661987305 nb_pixel_total : 18096 time to create 1 rle with old method : 0.028656005859375 time for calcul the mask position with numpy : 0.03306007385253906 nb_pixel_total : 45029 time to create 1 rle with old method : 0.05898594856262207 time for calcul the mask position with numpy : 0.029774904251098633 nb_pixel_total : 13983 time to create 1 rle with old method : 0.015940189361572266 time for calcul the mask position with numpy : 0.029826879501342773 nb_pixel_total : 2376 time to create 1 rle with old method : 0.0027887821197509766 time for calcul the mask position with numpy : 0.029580354690551758 nb_pixel_total : 24976 time to create 1 rle with old method : 0.027800798416137695 time for calcul the mask position with numpy : 0.02805304527282715 nb_pixel_total : 13370 time to create 1 rle with old method : 0.01485896110534668 time for calcul the mask position with numpy : 0.02931070327758789 nb_pixel_total : 17090 time to create 1 rle with old method : 0.019193410873413086 time for calcul the mask position with numpy : 0.029560089111328125 nb_pixel_total : 88239 time to create 1 rle with old method : 0.10138893127441406 time for calcul the mask position with numpy : 0.02970123291015625 nb_pixel_total : 51388 time to create 1 rle with old method : 0.05752921104431152 time for calcul the mask position with numpy : 0.029429197311401367 nb_pixel_total : 20083 time to create 1 rle with old method : 0.022644519805908203 time for calcul the mask position with numpy : 0.029157400131225586 nb_pixel_total : 14024 time to create 1 rle with old method : 0.01644301414489746 time for calcul the mask position with numpy : 0.029764413833618164 nb_pixel_total : 25436 time to create 1 rle with old method : 0.02864861488342285 time for calcul the mask position with numpy : 0.027948379516601562 nb_pixel_total : 11049 time to create 1 rle with old method : 0.012148141860961914 time for calcul the mask position with numpy : 0.02791428565979004 nb_pixel_total : 15723 time to create 1 rle with old method : 0.017130613327026367 time for calcul the mask position with numpy : 0.028561830520629883 nb_pixel_total : 12221 time to create 1 rle with old method : 0.013367414474487305 time for calcul the mask position with numpy : 0.028089523315429688 nb_pixel_total : 20381 time to create 1 rle with old method : 0.022237539291381836 time for calcul the mask position with numpy : 0.029040098190307617 nb_pixel_total : 10947 time to create 1 rle with old method : 0.01195836067199707 time for calcul the mask position with numpy : 0.030152320861816406 nb_pixel_total : 12448 time to create 1 rle with old method : 0.014858245849609375 time for calcul the mask position with numpy : 0.03150439262390137 nb_pixel_total : 14217 time to create 1 rle with old method : 0.017086505889892578 time for calcul the mask position with numpy : 0.03115677833557129 nb_pixel_total : 22535 time to create 1 rle with old method : 0.03632164001464844 time for calcul the mask position with numpy : 0.03641915321350098 nb_pixel_total : 115080 time to create 1 rle with old method : 0.12987852096557617 time for calcul the mask position with numpy : 0.029835939407348633 nb_pixel_total : 32468 time to create 1 rle with old method : 0.03861856460571289 time for calcul the mask position with numpy : 0.0295865535736084 nb_pixel_total : 12355 time to create 1 rle with old method : 0.013643980026245117 time for calcul the mask position with numpy : 0.029332399368286133 nb_pixel_total : 29869 time to create 1 rle with old method : 0.03335881233215332 time for calcul the mask position with numpy : 0.02961421012878418 nb_pixel_total : 5425 time to create 1 rle with old method : 0.006479740142822266 time for calcul the mask position with numpy : 0.029248952865600586 nb_pixel_total : 54605 time to create 1 rle with old method : 0.0912466049194336 time for calcul the mask position with numpy : 0.040282249450683594 nb_pixel_total : 8505 time to create 1 rle with old method : 0.013131380081176758 time for calcul the mask position with numpy : 0.040461063385009766 nb_pixel_total : 49673 time to create 1 rle with old method : 0.056659698486328125 time for calcul the mask position with numpy : 0.028891324996948242 nb_pixel_total : 164 time to create 1 rle with old method : 0.0003771781921386719 time for calcul the mask position with numpy : 0.030087947845458984 nb_pixel_total : 18932 time to create 1 rle with old method : 0.022241592407226562 time for calcul the mask position with numpy : 0.02950882911682129 nb_pixel_total : 362 time to create 1 rle with old method : 0.001495361328125 time for calcul the mask position with numpy : 0.032921552658081055 nb_pixel_total : 25202 time to create 1 rle with old method : 0.038736581802368164 time for calcul the mask position with numpy : 0.02983403205871582 nb_pixel_total : 156433 time to create 1 rle with new method : 0.6138088703155518 time for calcul the mask position with numpy : 0.029523849487304688 nb_pixel_total : 18736 time to create 1 rle with old method : 0.021448850631713867 time for calcul the mask position with numpy : 0.029215574264526367 nb_pixel_total : 11423 time to create 1 rle with old method : 0.012941598892211914 time for calcul the mask position with numpy : 0.03188514709472656 nb_pixel_total : 16932 time to create 1 rle with old method : 0.020344018936157227 time for calcul the mask position with numpy : 0.029436588287353516 nb_pixel_total : 21534 time to create 1 rle with old method : 0.024324417114257812 time for calcul the mask position with numpy : 0.029421329498291016 nb_pixel_total : 5928 time to create 1 rle with old method : 0.007730722427368164 time for calcul the mask position with numpy : 0.03238844871520996 nb_pixel_total : 10026 time to create 1 rle with old method : 0.011619806289672852 time for calcul the mask position with numpy : 0.030910491943359375 nb_pixel_total : 15700 time to create 1 rle with old method : 0.01776266098022461 time for calcul the mask position with numpy : 0.029608964920043945 nb_pixel_total : 15485 time to create 1 rle with old method : 0.017733335494995117 create new chi : 6.006871223449707 time to delete rle : 0.004489421844482422 batch 1 Loaded 131 chid ids of type : 3594 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 1081 TO DO : save crop sub photo not yet done ! save time : 0.3596189022064209 nb_obj : 38 nb_hashtags : 4 time to prepare the origin masks : 7.68462061882019 time for calcul the mask position with numpy : 0.5362181663513184 nb_pixel_total : 4798310 time to create 1 rle with new method : 0.7513198852539062 time for calcul the mask position with numpy : 0.02870011329650879 nb_pixel_total : 16407 time to create 1 rle with old method : 0.01946854591369629 time for calcul the mask position with numpy : 0.03332042694091797 nb_pixel_total : 471490 time to create 1 rle with new method : 0.5701439380645752 time for calcul the mask position with numpy : 0.03054332733154297 nb_pixel_total : 185765 time to create 1 rle with new method : 0.39095044136047363 time for calcul the mask position with numpy : 0.029774904251098633 nb_pixel_total : 20689 time to create 1 rle with old method : 0.023592233657836914 time for calcul the mask position with numpy : 0.028928279876708984 nb_pixel_total : 7641 time to create 1 rle with old method : 0.008597373962402344 time for calcul the mask position with numpy : 0.02918100357055664 nb_pixel_total : 35304 time to create 1 rle with old method : 0.050745248794555664 time for calcul the mask position with numpy : 0.033709049224853516 nb_pixel_total : 41001 time to create 1 rle with old method : 0.0517885684967041 time for calcul the mask position with numpy : 0.029167890548706055 nb_pixel_total : 3990 time to create 1 rle with old method : 0.004759788513183594 time for calcul the mask position with numpy : 0.03114461898803711 nb_pixel_total : 18299 time to create 1 rle with old method : 0.021682262420654297 time for calcul the mask position with numpy : 0.028375625610351562 nb_pixel_total : 25029 time to create 1 rle with old method : 0.027544260025024414 time for calcul the mask position with numpy : 0.0280764102935791 nb_pixel_total : 31593 time to create 1 rle with old method : 0.03709864616394043 time for calcul the mask position with numpy : 0.027311086654663086 nb_pixel_total : 8542 time to create 1 rle with old method : 0.009387493133544922 time for calcul the mask position with numpy : 0.028666019439697266 nb_pixel_total : 47670 time to create 1 rle with old method : 0.055117130279541016 time for calcul the mask position with numpy : 0.028415679931640625 nb_pixel_total : 26912 time to create 1 rle with old method : 0.03194069862365723 time for calcul the mask position with numpy : 0.028698444366455078 nb_pixel_total : 55540 time to create 1 rle with old method : 0.06058168411254883 time for calcul the mask position with numpy : 0.028555631637573242 nb_pixel_total : 27870 time to create 1 rle with old method : 0.0413966178894043 time for calcul the mask position with numpy : 0.03294634819030762 nb_pixel_total : 10185 time to create 1 rle with old method : 0.016667842864990234 time for calcul the mask position with numpy : 0.0292055606842041 nb_pixel_total : 48260 time to create 1 rle with old method : 0.05416250228881836 time for calcul the mask position with numpy : 0.028783082962036133 nb_pixel_total : 186234 time to create 1 rle with new method : 0.6548881530761719 time for calcul the mask position with numpy : 0.02993941307067871 nb_pixel_total : 44395 time to create 1 rle with old method : 0.050591468811035156 time for calcul the mask position with numpy : 0.03324484825134277 nb_pixel_total : 96796 time to create 1 rle with old method : 0.11088299751281738 time for calcul the mask position with numpy : 0.02965259552001953 nb_pixel_total : 76 time to create 1 rle with old method : 0.00012946128845214844 time for calcul the mask position with numpy : 0.031771183013916016 nb_pixel_total : 20039 time to create 1 rle with old method : 0.02305150032043457 time for calcul the mask position with numpy : 0.029668092727661133 nb_pixel_total : 85907 time to create 1 rle with old method : 0.10743951797485352 time for calcul the mask position with numpy : 0.029618263244628906 nb_pixel_total : 71251 time to create 1 rle with old method : 0.08175349235534668 time for calcul the mask position with numpy : 0.03003978729248047 nb_pixel_total : 66462 time to create 1 rle with old method : 0.07640910148620605 time for calcul the mask position with numpy : 0.03073740005493164 nb_pixel_total : 9319 time to create 1 rle with old method : 0.011301040649414062 time for calcul the mask position with numpy : 0.03036189079284668 nb_pixel_total : 9321 time to create 1 rle with old method : 0.016978979110717773 time for calcul the mask position with numpy : 0.029049396514892578 nb_pixel_total : 18444 time to create 1 rle with old method : 0.022160053253173828 time for calcul the mask position with numpy : 0.029076099395751953 nb_pixel_total : 41202 time to create 1 rle with old method : 0.044696807861328125 time for calcul the mask position with numpy : 0.029149770736694336 nb_pixel_total : 8966 time to create 1 rle with old method : 0.010774374008178711 time for calcul the mask position with numpy : 0.029749631881713867 nb_pixel_total : 72821 time to create 1 rle with old method : 0.0805823802947998 time for calcul the mask position with numpy : 0.029770612716674805 nb_pixel_total : 271116 time to create 1 rle with new method : 0.5240633487701416 time for calcul the mask position with numpy : 0.029599905014038086 nb_pixel_total : 70686 time to create 1 rle with old method : 0.07966876029968262 time for calcul the mask position with numpy : 0.029703378677368164 nb_pixel_total : 12760 time to create 1 rle with old method : 0.014444828033447266 time for calcul the mask position with numpy : 0.029271364212036133 nb_pixel_total : 3834 time to create 1 rle with old method : 0.0045299530029296875 time for calcul the mask position with numpy : 0.028867244720458984 nb_pixel_total : 80114 time to create 1 rle with old method : 0.09392046928405762 create new chi : 6.038776397705078 time to delete rle : 0.003313779830932617 batch 1 Loaded 75 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! save time : 0.17126822471618652 nb_obj : 11 nb_hashtags : 4 time to prepare the origin masks : 6.71083927154541 time for calcul the mask position with numpy : 0.03639411926269531 nb_pixel_total : 24315 time to create 1 rle with old method : 0.02758336067199707 time for calcul the mask position with numpy : 0.03387141227722168 nb_pixel_total : 18341 time to create 1 rle with old method : 0.0204315185546875 time for calcul the mask position with numpy : 0.030402183532714844 nb_pixel_total : 18706 time to create 1 rle with old method : 0.020915746688842773 time for calcul the mask position with numpy : 0.02808547019958496 nb_pixel_total : 38 time to create 1 rle with old method : 0.00021457672119140625 time for calcul the mask position with numpy : 0.2190103530883789 nb_pixel_total : 2811150 time to create 1 rle with new method : 0.7828116416931152 time for calcul the mask position with numpy : 0.03876066207885742 nb_pixel_total : 174441 time to create 1 rle with new method : 0.5547976493835449 time for calcul the mask position with numpy : 0.0345911979675293 nb_pixel_total : 326 time to create 1 rle with old method : 0.0008947849273681641 time for calcul the mask position with numpy : 0.03682732582092285 nb_pixel_total : 236729 time to create 1 rle with new method : 0.5756015777587891 time for calcul the mask position with numpy : 0.0348968505859375 nb_pixel_total : 252044 time to create 1 rle with new method : 0.7010433673858643 time for calcul the mask position with numpy : 0.037041664123535156 nb_pixel_total : 250489 time to create 1 rle with new method : 0.5817153453826904 time for calcul the mask position with numpy : 0.27129292488098145 nb_pixel_total : 3263661 time to create 1 rle with new method : 1.2659757137298584 create new chi : 5.533597230911255 time to delete rle : 0.0020754337310791016 batch 1 Loaded 22 chid ids of type : 3594 +++++++++++++Number RLEs to save : 194 TO DO : save crop sub photo not yet done ! save time : 0.20375895500183105 nb_obj : 50 nb_hashtags : 5 time to prepare the origin masks : 8.112801790237427 time for calcul the mask position with numpy : 0.4969453811645508 nb_pixel_total : 4850440 time to create 1 rle with new method : 0.6860644817352295 time for calcul the mask position with numpy : 0.029680490493774414 nb_pixel_total : 19002 time to create 1 rle with old method : 0.02261495590209961 time for calcul the mask position with numpy : 0.030248641967773438 nb_pixel_total : 73654 time to create 1 rle with old method : 0.08559799194335938 time for calcul the mask position with numpy : 0.029095888137817383 nb_pixel_total : 20629 time to create 1 rle with old method : 0.027266740798950195 time for calcul the mask position with numpy : 0.030447006225585938 nb_pixel_total : 3972 time to create 1 rle with old method : 0.005217313766479492 time for calcul the mask position with numpy : 0.02952885627746582 nb_pixel_total : 78107 time to create 1 rle with old method : 0.08780860900878906 time for calcul the mask position with numpy : 0.0289156436920166 nb_pixel_total : 71440 time to create 1 rle with old method : 0.08209061622619629 time for calcul the mask position with numpy : 0.030271053314208984 nb_pixel_total : 142409 time to create 1 rle with old method : 0.16060996055603027 time for calcul the mask position with numpy : 0.04055070877075195 nb_pixel_total : 10454 time to create 1 rle with old method : 0.013309001922607422 time for calcul the mask position with numpy : 0.033280134201049805 nb_pixel_total : 72593 time to create 1 rle with old method : 0.08618378639221191 time for calcul the mask position with numpy : 0.029902219772338867 nb_pixel_total : 57200 time to create 1 rle with old method : 0.06614542007446289 time for calcul the mask position with numpy : 0.030336618423461914 nb_pixel_total : 34584 time to create 1 rle with old method : 0.043662071228027344 time for calcul the mask position with numpy : 0.029724597930908203 nb_pixel_total : 76561 time to create 1 rle with old method : 0.08613467216491699 time for calcul the mask position with numpy : 0.0292665958404541 nb_pixel_total : 30604 time to create 1 rle with old method : 0.03461718559265137 time for calcul the mask position with numpy : 0.030937671661376953 nb_pixel_total : 16944 time to create 1 rle with old method : 0.021874666213989258 time for calcul the mask position with numpy : 0.030726909637451172 nb_pixel_total : 53304 time to create 1 rle with old method : 0.06219339370727539 time for calcul the mask position with numpy : 0.029575347900390625 nb_pixel_total : 92339 time to create 1 rle with old method : 0.10410690307617188 time for calcul the mask position with numpy : 0.034258365631103516 nb_pixel_total : 58741 time to create 1 rle with old method : 0.07682991027832031 time for calcul the mask position with numpy : 0.030872583389282227 nb_pixel_total : 1405 time to create 1 rle with old method : 0.0019390583038330078 time for calcul the mask position with numpy : 0.02910304069519043 nb_pixel_total : 12801 time to create 1 rle with old method : 0.014505386352539062 time for calcul the mask position with numpy : 0.02935957908630371 nb_pixel_total : 44468 time to create 1 rle with old method : 0.05453348159790039 time for calcul the mask position with numpy : 0.032909393310546875 nb_pixel_total : 5413 time to create 1 rle with old method : 0.009005546569824219 time for calcul the mask position with numpy : 0.03311443328857422 nb_pixel_total : 101275 time to create 1 rle with old method : 0.13068747520446777 time for calcul the mask position with numpy : 0.0309906005859375 nb_pixel_total : 31486 time to create 1 rle with old method : 0.0350949764251709 time for calcul the mask position with numpy : 0.030962467193603516 nb_pixel_total : 178769 time to create 1 rle with new method : 0.6582682132720947 time for calcul the mask position with numpy : 0.029607295989990234 nb_pixel_total : 16700 time to create 1 rle with old method : 0.021126508712768555 time for calcul the mask position with numpy : 0.0334165096282959 nb_pixel_total : 101747 time to create 1 rle with old method : 0.11426997184753418 time for calcul the mask position with numpy : 0.029349088668823242 nb_pixel_total : 9049 time to create 1 rle with old method : 0.010892391204833984 time for calcul the mask position with numpy : 0.02943897247314453 nb_pixel_total : 18435 time to create 1 rle with old method : 0.021222591400146484 time for calcul the mask position with numpy : 0.03051900863647461 nb_pixel_total : 11997 time to create 1 rle with old method : 0.014628887176513672 time for calcul the mask position with numpy : 0.0311126708984375 nb_pixel_total : 6978 time to create 1 rle with old method : 0.008301496505737305 time for calcul the mask position with numpy : 0.03138446807861328 nb_pixel_total : 12993 time to create 1 rle with old method : 0.01595139503479004 time for calcul the mask position with numpy : 0.031118392944335938 nb_pixel_total : 61462 time to create 1 rle with old method : 0.07372832298278809 time for calcul the mask position with numpy : 0.03050971031188965 nb_pixel_total : 94315 time to create 1 rle with old method : 0.10796713829040527 time for calcul the mask position with numpy : 0.029210329055786133 nb_pixel_total : 433 time to create 1 rle with old method : 0.0007777214050292969 time for calcul the mask position with numpy : 0.029218673706054688 nb_pixel_total : 32449 time to create 1 rle with old method : 0.036806344985961914 time for calcul the mask position with numpy : 0.029305219650268555 nb_pixel_total : 57543 time to create 1 rle with old method : 0.06512975692749023 time for calcul the mask position with numpy : 0.029132604598999023 nb_pixel_total : 361 time to create 1 rle with old method : 0.0006992816925048828 time for calcul the mask position with numpy : 0.03205418586730957 nb_pixel_total : 283556 time to create 1 rle with new method : 0.7474536895751953 time for calcul the mask position with numpy : 0.028597593307495117 nb_pixel_total : 62104 time to create 1 rle with old method : 0.07237982749938965 time for calcul the mask position with numpy : 0.028063297271728516 nb_pixel_total : 1688 time to create 1 rle with old method : 0.0019767284393310547 time for calcul the mask position with numpy : 0.03225278854370117 nb_pixel_total : 51 time to create 1 rle with old method : 0.0001468658447265625 time for calcul the mask position with numpy : 0.028156757354736328 nb_pixel_total : 5738 time to create 1 rle with old method : 0.006990909576416016 time for calcul the mask position with numpy : 0.0285794734954834 nb_pixel_total : 28238 time to create 1 rle with old method : 0.030823230743408203 time for calcul the mask position with numpy : 0.028744935989379883 nb_pixel_total : 81002 time to create 1 rle with old method : 0.08987092971801758 time for calcul the mask position with numpy : 0.029363393783569336 nb_pixel_total : 10625 time to create 1 rle with old method : 0.011992692947387695 time for calcul the mask position with numpy : 0.029407501220703125 nb_pixel_total : 52 time to create 1 rle with old method : 0.0001480579376220703 time for calcul the mask position with numpy : 0.029405593872070312 nb_pixel_total : 6687 time to create 1 rle with old method : 0.007816314697265625 time for calcul the mask position with numpy : 0.030728578567504883 nb_pixel_total : 3770 time to create 1 rle with old method : 0.004530906677246094 time for calcul the mask position with numpy : 0.02967667579650879 nb_pixel_total : 3673 time to create 1 rle with old method : 0.004410982131958008 create new chi : 6.227858304977417 time to delete rle : 0.008695840835571289 batch 1 Loaded 105 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 1044 TO DO : save crop sub photo not yet done ! save time : 0.27527713775634766 nb_obj : 18 nb_hashtags : 4 time to prepare the origin masks : 6.964434862136841 time for calcul the mask position with numpy : 0.3528015613555908 nb_pixel_total : 5468891 time to create 1 rle with new method : 0.8216328620910645 time for calcul the mask position with numpy : 0.038533687591552734 nb_pixel_total : 282388 time to create 1 rle with new method : 0.5399637222290039 time for calcul the mask position with numpy : 0.03837776184082031 nb_pixel_total : 7911 time to create 1 rle with old method : 0.009447813034057617 time for calcul the mask position with numpy : 0.03452754020690918 nb_pixel_total : 2367 time to create 1 rle with old method : 0.0028057098388671875 time for calcul the mask position with numpy : 0.03619813919067383 nb_pixel_total : 17891 time to create 1 rle with old method : 0.021117687225341797 time for calcul the mask position with numpy : 0.034536123275756836 nb_pixel_total : 23109 time to create 1 rle with old method : 0.026772737503051758 time for calcul the mask position with numpy : 0.03510165214538574 nb_pixel_total : 168349 time to create 1 rle with new method : 0.7204978466033936 time for calcul the mask position with numpy : 0.034483909606933594 nb_pixel_total : 6834 time to create 1 rle with old method : 0.007669210433959961 time for calcul the mask position with numpy : 0.0379791259765625 nb_pixel_total : 58125 time to create 1 rle with old method : 0.06595182418823242 time for calcul the mask position with numpy : 0.03476405143737793 nb_pixel_total : 30068 time to create 1 rle with old method : 0.034497976303100586 time for calcul the mask position with numpy : 0.036035776138305664 nb_pixel_total : 104222 time to create 1 rle with old method : 0.11664605140686035 time for calcul the mask position with numpy : 0.037169694900512695 nb_pixel_total : 119524 time to create 1 rle with old method : 0.13960528373718262 time for calcul the mask position with numpy : 0.05120992660522461 nb_pixel_total : 40602 time to create 1 rle with old method : 0.04416918754577637 time for calcul the mask position with numpy : 0.036126136779785156 nb_pixel_total : 219072 time to create 1 rle with new method : 0.8195576667785645 time for calcul the mask position with numpy : 0.03006291389465332 nb_pixel_total : 16664 time to create 1 rle with old method : 0.019421100616455078 time for calcul the mask position with numpy : 0.026947975158691406 nb_pixel_total : 296575 time to create 1 rle with new method : 0.4140164852142334 time for calcul the mask position with numpy : 0.02913045883178711 nb_pixel_total : 28293 time to create 1 rle with old method : 0.03283238410949707 time for calcul the mask position with numpy : 0.03407692909240723 nb_pixel_total : 131121 time to create 1 rle with old method : 0.1557755470275879 time for calcul the mask position with numpy : 0.0357060432434082 nb_pixel_total : 28234 time to create 1 rle with old method : 0.040390729904174805 create new chi : 5.157921075820923 time to delete rle : 0.004321575164794922 batch 1 Loaded 37 chid ids of type : 3594 ++++++++++++++++++++++++++++++++Number RLEs to save : 15094 TO DO : save crop sub photo not yet done ! save time : 1.9500889778137207 nb_obj : 17 nb_hashtags : 4 time to prepare the origin masks : 7.5541675090789795 time for calcul the mask position with numpy : 0.9781498908996582 nb_pixel_total : 6088548 time to create 1 rle with new method : 0.4647519588470459 time for calcul the mask position with numpy : 0.030483007431030273 nb_pixel_total : 97660 time to create 1 rle with old method : 0.10908985137939453 time for calcul the mask position with numpy : 0.029033184051513672 nb_pixel_total : 24425 time to create 1 rle with old method : 0.027540206909179688 time for calcul the mask position with numpy : 0.029651880264282227 nb_pixel_total : 128244 time to create 1 rle with old method : 0.16594195365905762 time for calcul the mask position with numpy : 0.03048419952392578 nb_pixel_total : 5445 time to create 1 rle with old method : 0.007074594497680664 time for calcul the mask position with numpy : 0.032256364822387695 nb_pixel_total : 10652 time to create 1 rle with old method : 0.012163400650024414 time for calcul the mask position with numpy : 0.02983379364013672 nb_pixel_total : 9577 time to create 1 rle with old method : 0.010812520980834961 time for calcul the mask position with numpy : 0.02938675880432129 nb_pixel_total : 108756 time to create 1 rle with old method : 0.1203761100769043 time for calcul the mask position with numpy : 0.02910780906677246 nb_pixel_total : 94125 time to create 1 rle with old method : 0.10357046127319336 time for calcul the mask position with numpy : 0.029056310653686523 nb_pixel_total : 21221 time to create 1 rle with old method : 0.024536848068237305 time for calcul the mask position with numpy : 0.02918410301208496 nb_pixel_total : 28026 time to create 1 rle with old method : 0.03138995170593262 time for calcul the mask position with numpy : 0.02935957908630371 nb_pixel_total : 85691 time to create 1 rle with old method : 0.09525203704833984 time for calcul the mask position with numpy : 0.02935624122619629 nb_pixel_total : 16191 time to create 1 rle with old method : 0.01848292350769043 time for calcul the mask position with numpy : 0.029937744140625 nb_pixel_total : 115516 time to create 1 rle with old method : 0.12894654273986816 time for calcul the mask position with numpy : 0.029727697372436523 nb_pixel_total : 165790 time to create 1 rle with new method : 0.8241617679595947 time for calcul the mask position with numpy : 0.028867483139038086 nb_pixel_total : 36816 time to create 1 rle with old method : 0.04162001609802246 time for calcul the mask position with numpy : 0.027657508850097656 nb_pixel_total : 13557 time to create 1 rle with old method : 0.014803171157836914 create new chi : 3.7381396293640137 time to delete rle : 0.001840829849243164 batch 1 Loaded 33 chid ids of type : 3594 +++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! save time : 0.11793828010559082 nb_obj : 23 nb_hashtags : 4 time to prepare the origin masks : 7.407617568969727 time for calcul the mask position with numpy : 0.3912849426269531 nb_pixel_total : 5833637 time to create 1 rle with new method : 0.7391319274902344 time for calcul the mask position with numpy : 0.031230926513671875 nb_pixel_total : 16978 time to create 1 rle with old method : 0.021091699600219727 time for calcul the mask position with numpy : 0.029612064361572266 nb_pixel_total : 18902 time to create 1 rle with old method : 0.02402782440185547 time for calcul the mask position with numpy : 0.04363274574279785 nb_pixel_total : 10537 time to create 1 rle with old method : 0.019929170608520508 time for calcul the mask position with numpy : 0.04305100440979004 nb_pixel_total : 16162 time to create 1 rle with old method : 0.025934696197509766 time for calcul the mask position with numpy : 0.04124593734741211 nb_pixel_total : 27204 time to create 1 rle with old method : 0.0325927734375 time for calcul the mask position with numpy : 0.031128883361816406 nb_pixel_total : 10412 time to create 1 rle with old method : 0.01193380355834961 time for calcul the mask position with numpy : 0.02767634391784668 nb_pixel_total : 3237 time to create 1 rle with old method : 0.003893613815307617 time for calcul the mask position with numpy : 0.027927160263061523 nb_pixel_total : 68633 time to create 1 rle with old method : 0.07741665840148926 time for calcul the mask position with numpy : 0.027864694595336914 nb_pixel_total : 120122 time to create 1 rle with old method : 0.13191914558410645 time for calcul the mask position with numpy : 0.02900218963623047 nb_pixel_total : 176232 time to create 1 rle with new method : 0.8430576324462891 time for calcul the mask position with numpy : 0.02851080894470215 nb_pixel_total : 66927 time to create 1 rle with old method : 0.07729792594909668 time for calcul the mask position with numpy : 0.027626514434814453 nb_pixel_total : 14640 time to create 1 rle with old method : 0.016610383987426758 time for calcul the mask position with numpy : 0.028142213821411133 nb_pixel_total : 3632 time to create 1 rle with old method : 0.004255533218383789 time for calcul the mask position with numpy : 0.028379201889038086 nb_pixel_total : 23227 time to create 1 rle with old method : 0.025265932083129883 time for calcul the mask position with numpy : 0.027077198028564453 nb_pixel_total : 25594 time to create 1 rle with old method : 0.027504444122314453 time for calcul the mask position with numpy : 0.02704024314880371 nb_pixel_total : 26960 time to create 1 rle with old method : 0.028354406356811523 time for calcul the mask position with numpy : 0.026912689208984375 nb_pixel_total : 50730 time to create 1 rle with old method : 0.05376791954040527 time for calcul the mask position with numpy : 0.028923749923706055 nb_pixel_total : 47797 time to create 1 rle with old method : 0.05164289474487305 time for calcul the mask position with numpy : 0.02761387825012207 nb_pixel_total : 26414 time to create 1 rle with old method : 0.028184175491333008 time for calcul the mask position with numpy : 0.029136180877685547 nb_pixel_total : 72066 time to create 1 rle with old method : 0.07912874221801758 time for calcul the mask position with numpy : 0.02830791473388672 nb_pixel_total : 158367 time to create 1 rle with new method : 0.6639382839202881 time for calcul the mask position with numpy : 0.028522968292236328 nb_pixel_total : 231830 time to create 1 rle with new method : 0.8117818832397461 create new chi : 4.989210844039917 time to delete rle : 0.0035965442657470703 batch 1 Loaded 45 chid ids of type : 3594 ++++++++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! save time : 0.14447832107543945 nb_obj : 32 nb_hashtags : 7 time to prepare the origin masks : 7.698800563812256 time for calcul the mask position with numpy : 1.0193212032318115 nb_pixel_total : 4763612 time to create 1 rle with new method : 0.6333754062652588 time for calcul the mask position with numpy : 0.032375335693359375 nb_pixel_total : 15657 time to create 1 rle with old method : 0.01847386360168457 time for calcul the mask position with numpy : 0.029617786407470703 nb_pixel_total : 51433 time to create 1 rle with old method : 0.06270313262939453 time for calcul the mask position with numpy : 0.033725738525390625 nb_pixel_total : 126163 time to create 1 rle with old method : 0.15381884574890137 time for calcul the mask position with numpy : 0.035567283630371094 nb_pixel_total : 80163 time to create 1 rle with old method : 0.09897589683532715 time for calcul the mask position with numpy : 0.02923440933227539 nb_pixel_total : 78016 time to create 1 rle with old method : 0.08638238906860352 time for calcul the mask position with numpy : 0.029621601104736328 nb_pixel_total : 7354 time to create 1 rle with old method : 0.008289337158203125 time for calcul the mask position with numpy : 0.028571367263793945 nb_pixel_total : 12399 time to create 1 rle with old method : 0.01385498046875 time for calcul the mask position with numpy : 0.03185772895812988 nb_pixel_total : 389577 time to create 1 rle with new method : 0.4011554718017578 time for calcul the mask position with numpy : 0.03076004981994629 nb_pixel_total : 159261 time to create 1 rle with new method : 0.5930595397949219 time for calcul the mask position with numpy : 0.02853083610534668 nb_pixel_total : 24436 time to create 1 rle with old method : 0.028090476989746094 time for calcul the mask position with numpy : 0.029384374618530273 nb_pixel_total : 16638 time to create 1 rle with old method : 0.019158363342285156 time for calcul the mask position with numpy : 0.028448820114135742 nb_pixel_total : 14438 time to create 1 rle with old method : 0.016811370849609375 time for calcul the mask position with numpy : 0.02823185920715332 nb_pixel_total : 73688 time to create 1 rle with old method : 0.0823061466217041 time for calcul the mask position with numpy : 0.028017282485961914 nb_pixel_total : 203669 time to create 1 rle with new method : 0.6637759208679199 time for calcul the mask position with numpy : 0.029815673828125 nb_pixel_total : 77668 time to create 1 rle with old method : 0.09637761116027832 time for calcul the mask position with numpy : 0.030007362365722656 nb_pixel_total : 177163 time to create 1 rle with new method : 0.782250165939331 time for calcul the mask position with numpy : 0.02980947494506836 nb_pixel_total : 40152 time to create 1 rle with old method : 0.046227216720581055 time for calcul the mask position with numpy : 0.03175926208496094 nb_pixel_total : 23140 time to create 1 rle with old method : 0.02611374855041504 time for calcul the mask position with numpy : 0.030701637268066406 nb_pixel_total : 189740 time to create 1 rle with new method : 0.9923055171966553 time for calcul the mask position with numpy : 0.029352664947509766 nb_pixel_total : 73571 time to create 1 rle with old method : 0.08369064331054688 time for calcul the mask position with numpy : 0.03191852569580078 nb_pixel_total : 27640 time to create 1 rle with old method : 0.03350567817687988 time for calcul the mask position with numpy : 0.02986454963684082 nb_pixel_total : 41267 time to create 1 rle with old method : 0.04972672462463379 time for calcul the mask position with numpy : 0.02996540069580078 nb_pixel_total : 14056 time to create 1 rle with old method : 0.01691293716430664 time for calcul the mask position with numpy : 0.03012537956237793 nb_pixel_total : 81055 time to create 1 rle with old method : 0.1017158031463623 time for calcul the mask position with numpy : 0.03461623191833496 nb_pixel_total : 106770 time to create 1 rle with old method : 0.1271991729736328 time for calcul the mask position with numpy : 0.02918720245361328 nb_pixel_total : 44861 time to create 1 rle with old method : 0.0512690544128418 time for calcul the mask position with numpy : 0.03060626983642578 nb_pixel_total : 39675 time to create 1 rle with old method : 0.04562115669250488 time for calcul the mask position with numpy : 0.028691530227661133 nb_pixel_total : 10839 time to create 1 rle with old method : 0.012244701385498047 time for calcul the mask position with numpy : 0.028775930404663086 nb_pixel_total : 55619 time to create 1 rle with old method : 0.061933279037475586 time for calcul the mask position with numpy : 0.02948737144470215 nb_pixel_total : 25382 time to create 1 rle with old method : 0.029448509216308594 time for calcul the mask position with numpy : 0.029859066009521484 nb_pixel_total : 5138 time to create 1 rle with old method : 0.0059661865234375 create new chi : 7.586185693740845 time to delete rle : 0.00532984733581543 batch 1 Loaded 64 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! save time : 0.16528582572937012 map_output_result : {1333348189: (0.0, 'Should be the crop_list due to order', 0.0), 1333348185: (0.0, 'Should be the crop_list due to order', 0.0), 1333348179: (0.0, 'Should be the crop_list due to order', 0.0), 1333348016: (0.0, 'Should be the crop_list due to order', 0.0), 1333347989: (0.0, 'Should be the crop_list due to order', 0.0), 1333347939: (0.0, 'Should be the crop_list due to order', 0.0), 1333347927: (0.0, 'Should be the crop_list due to order', 0.0), 1333347884: (0.0, 'Should be the crop_list due to order', 0.0), 1333347719: (0.0, 'Should be the crop_list due to order', 0.0), 1333347695: (0.0, 'Should be the crop_list due to order', 0.0), 1333347643: (0.0, 'Should be the crop_list due to order', 0.0), 1333347642: (0.0, 'Should be the crop_list due to order', 0.0)} 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 [1333348189, 1333348185, 1333348179, 1333348016, 1333347989, 1333347939, 1333347927, 1333347884, 1333347719, 1333347695, 1333347643, 1333347642] Looping around the photos to save general results len do output : 12 /1333348189.Didn't retrieve data . /1333348185.Didn't retrieve data . /1333348179.Didn't retrieve data . /1333348016.Didn't retrieve data . /1333347989.Didn't retrieve data . /1333347939.Didn't retrieve data . /1333347927.Didn't retrieve data . /1333347884.Didn't retrieve data . /1333347719.Didn't retrieve data . /1333347695.Didn't retrieve data . /1333347643.Didn't retrieve data . /1333347642.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, '2535942') ('3318', '20128891', '1333348189', None, None, None, None, None, '2535942') ('3318', None, None, None, None, None, None, None, '2535942') ('3318', '20128891', '1333348185', None, None, None, None, None, '2535942') ('3318', None, None, None, None, None, None, None, '2535942') ('3318', '20128891', '1333348179', None, None, None, None, None, '2535942') ('3318', None, None, None, None, None, None, None, '2535942') ('3318', '20128891', '1333348016', None, None, None, None, None, '2535942') ('3318', None, None, None, None, None, None, None, '2535942') ('3318', '20128891', '1333347989', None, None, None, None, None, '2535942') ('3318', None, None, None, None, None, None, None, '2535942') ('3318', '20128891', '1333347939', None, None, None, None, None, '2535942') ('3318', None, None, None, None, None, None, None, '2535942') ('3318', '20128891', '1333347927', None, None, None, None, None, '2535942') ('3318', None, None, None, None, None, None, None, '2535942') ('3318', '20128891', '1333347884', None, None, None, None, None, '2535942') ('3318', None, None, None, None, None, None, None, '2535942') ('3318', '20128891', '1333347719', None, None, None, None, None, '2535942') ('3318', None, None, None, None, None, None, None, '2535942') ('3318', '20128891', '1333347695', None, None, None, None, None, '2535942') ('3318', None, None, None, None, None, None, None, '2535942') ('3318', '20128891', '1333347643', None, None, None, None, None, '2535942') ('3318', None, None, None, None, None, None, None, '2535942') ('3318', '20128891', '1333347642', None, None, None, None, None, '2535942') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 36 time used for this insertion : 0.016025066375732422 save_final save missing photos in datou_result : time spend for datou_step_exec : 166.92712330818176 time spend to save output : 0.016438007354736328 total time spend for step 3 : 166.9435613155365 step4:ventilate_hashtags_in_portfolio Sat Feb 1 02:23:35 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure beginning of datou step ventilate_hashtags_in_portfolio : To implement ! Iterating over portfolio : 20128891 get user id for portfolio 20128891 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`=20128891 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('environnement','flou','mal_croppe','background','autre','pehd','pet_fonce','metal','papier','pet_clair','carton')) 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`=20128891 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('environnement','flou','mal_croppe','background','autre','pehd','pet_fonce','metal','papier','pet_clair','carton')) AND mptpi.`min_score`=0.5 To do Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") To do ! Use context local managing function ! SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=20128891 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('environnement','flou','mal_croppe','background','autre','pehd','pet_fonce','metal','papier','pet_clair','carton')) AND mptpi.`min_score`=0.5 To do lien utilise dans velours : https://www.fotonower.com/velours/20129128,20129129,20129130,20129131,20129132,20129133,20129134,20129135,20129136,20129137,20129138?tags=environnement,flou,mal_croppe,background,autre,pehd,pet_fonce,metal,papier,pet_clair,carton Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : ventilate_hashtags_in_portfolio we use saveGeneral [1333348189, 1333348185, 1333348179, 1333348016, 1333347989, 1333347939, 1333347927, 1333347884, 1333347719, 1333347695, 1333347643, 1333347642] Looping around the photos to save general results len do output : 1 /20128891. 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, '2535942') ('3318', '20128891', '1333348189', None, None, None, None, None, '2535942') ('3318', None, None, None, None, None, None, None, '2535942') ('3318', '20128891', '1333348185', None, None, None, None, None, '2535942') ('3318', None, None, None, None, None, None, None, '2535942') ('3318', '20128891', '1333348179', None, None, None, None, None, '2535942') ('3318', None, None, None, None, None, None, None, '2535942') ('3318', '20128891', '1333348016', None, None, None, None, None, '2535942') ('3318', None, None, None, None, None, None, None, '2535942') ('3318', '20128891', '1333347989', None, None, None, None, None, '2535942') ('3318', None, None, None, None, None, None, None, '2535942') ('3318', '20128891', '1333347939', None, None, None, None, None, '2535942') ('3318', None, None, None, None, None, None, None, '2535942') ('3318', '20128891', '1333347927', None, None, None, None, None, '2535942') ('3318', None, None, None, None, None, None, None, '2535942') ('3318', '20128891', '1333347884', None, None, None, None, None, '2535942') ('3318', None, None, None, None, None, None, None, '2535942') ('3318', '20128891', '1333347719', None, None, None, None, None, '2535942') ('3318', None, None, None, None, None, None, None, '2535942') ('3318', '20128891', '1333347695', None, None, None, None, None, '2535942') ('3318', None, None, None, None, None, None, None, '2535942') ('3318', '20128891', '1333347643', None, None, None, None, None, '2535942') ('3318', None, None, None, None, None, None, None, '2535942') ('3318', '20128891', '1333347642', None, None, None, None, None, '2535942') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 13 time used for this insertion : 0.13749289512634277 save_final save missing photos in datou_result : time spend for datou_step_exec : 1.600327968597412 time spend to save output : 0.13776040077209473 total time spend for step 4 : 1.7380883693695068 step5:final Sat Feb 1 02:23:37 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 : {1333348189: ('0.2539790962198923',), 1333348185: ('0.2539790962198923',), 1333348179: ('0.2539790962198923',), 1333348016: ('0.2539790962198923',), 1333347989: ('0.2539790962198923',), 1333347939: ('0.2539790962198923',), 1333347927: ('0.2539790962198923',), 1333347884: ('0.2539790962198923',), 1333347719: ('0.2539790962198923',), 1333347695: ('0.2539790962198923',), 1333347643: ('0.2539790962198923',), 1333347642: ('0.2539790962198923',)} new output for save of step final : {1333348189: ('0.2539790962198923',), 1333348185: ('0.2539790962198923',), 1333348179: ('0.2539790962198923',), 1333348016: ('0.2539790962198923',), 1333347989: ('0.2539790962198923',), 1333347939: ('0.2539790962198923',), 1333347927: ('0.2539790962198923',), 1333347884: ('0.2539790962198923',), 1333347719: ('0.2539790962198923',), 1333347695: ('0.2539790962198923',), 1333347643: ('0.2539790962198923',), 1333347642: ('0.2539790962198923',)} [1333348189, 1333348185, 1333348179, 1333348016, 1333347989, 1333347939, 1333347927, 1333347884, 1333347719, 1333347695, 1333347643, 1333347642] Looping around the photos to save general results len do output : 12 /1333348189.Didn't retrieve data . /1333348185.Didn't retrieve data . /1333348179.Didn't retrieve data . /1333348016.Didn't retrieve data . /1333347989.Didn't retrieve data . /1333347939.Didn't retrieve data . /1333347927.Didn't retrieve data . /1333347884.Didn't retrieve data . /1333347719.Didn't retrieve data . /1333347695.Didn't retrieve data . /1333347643.Didn't retrieve data . /1333347642.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, '2535942') ('3318', '20128891', '1333348189', None, None, None, None, None, '2535942') ('3318', None, None, None, None, None, None, None, '2535942') ('3318', '20128891', '1333348185', None, None, None, None, None, '2535942') ('3318', None, None, None, None, None, None, None, '2535942') ('3318', '20128891', '1333348179', None, None, None, None, None, '2535942') ('3318', None, None, None, None, None, None, None, '2535942') ('3318', '20128891', '1333348016', None, None, None, None, None, '2535942') ('3318', None, None, None, None, None, None, None, '2535942') ('3318', '20128891', '1333347989', None, None, None, None, None, '2535942') ('3318', None, None, None, None, None, None, None, '2535942') ('3318', '20128891', '1333347939', None, None, None, None, None, '2535942') ('3318', None, None, None, None, None, None, None, '2535942') ('3318', '20128891', '1333347927', None, None, None, None, None, '2535942') ('3318', None, None, None, None, None, None, None, '2535942') ('3318', '20128891', '1333347884', None, None, None, None, None, '2535942') ('3318', None, None, None, None, None, None, None, '2535942') ('3318', '20128891', '1333347719', None, None, None, None, None, '2535942') ('3318', None, None, None, None, None, None, None, '2535942') ('3318', '20128891', '1333347695', None, None, None, None, None, '2535942') ('3318', None, None, None, None, None, None, None, '2535942') ('3318', '20128891', '1333347643', None, None, None, None, None, '2535942') ('3318', None, None, None, None, None, None, None, '2535942') ('3318', '20128891', '1333347642', None, None, None, None, None, '2535942') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 36 time used for this insertion : 0.016799449920654297 save_final save missing photos in datou_result : time spend for datou_step_exec : 0.144148588180542 time spend to save output : 0.017377853393554688 total time spend for step 5 : 0.16152644157409668 step6:blur_detection Sat Feb 1 02:23:37 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/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e.jpg resize: (2160, 3264) 1333348189 -5.977352812792872 treat image : temp/1738372229_2654573_1333348185_f2d424fa38d9fa76ed64cc159e7c3745.jpg resize: (2160, 3264) 1333348185 -5.853923864676999 treat image : temp/1738372229_2654573_1333348179_3b56bb17ff49acba70056938957f6662.jpg resize: (2160, 3264) 1333348179 -6.846812316847188 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6.jpg resize: (2160, 3264) 1333348016 -7.154786306586481 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256.jpg resize: (2160, 3264) 1333347989 -6.980874791851019 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f.jpg resize: (2160, 3264) 1333347939 -6.1774910421618126 treat image : temp/1738372229_2654573_1333347927_60c57d7afcc133119c0c5db747539889.jpg resize: (2160, 3264) 1333347927 -3.162609669829571 treat image : temp/1738372229_2654573_1333347884_03e7636a354a16105d0fed840241ed97.jpg resize: (2160, 3264) 1333347884 -5.443506037319138 treat image : temp/1738372229_2654573_1333347719_1bbdb60064be87d7e08ddf3aad907c20.jpg resize: (2160, 3264) 1333347719 -4.954225884510779 treat image : temp/1738372229_2654573_1333347695_fe5bb2210598f5c1651db0167f7781da.jpg resize: (2160, 3264) 1333347695 -5.13467706629257 treat image : temp/1738372229_2654573_1333347643_d03d7c60aa08e60b1d89507044772de3.jpg resize: (2160, 3264) 1333347643 -2.788454300495292 treat image : temp/1738372229_2654573_1333347642_d35e5f20eb4796bd26f0cc46c0694c70.jpg resize: (2160, 3264) 1333347642 -6.351268514444442 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647984857_0.png resize: (159, 191) 1333551952 -3.188296149695921 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647988023_0.png resize: (159, 191) 1333551953 -3.188296149695921 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647984856_0.png resize: (123, 130) 1333551954 -3.8541758430868556 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647988019_0.png resize: (123, 130) 1333551955 -3.8541758430868556 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647988026_0.png resize: (136, 141) 1333551956 -3.8048558309922917 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647984884_0.png resize: (136, 141) 1333551957 -3.8048558309922917 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647984867_0.png resize: (269, 127) 1333551958 -3.803065379457792 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647988021_0.png resize: (269, 127) 1333551959 -3.803065379457792 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647984881_0.png resize: (210, 203) 1333551960 -3.38116888393081 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3648057271_0.png resize: (210, 203) 1333551961 -3.3153889472339046 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647988037_0.png resize: (210, 203) 1333551962 -3.38116888393081 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647984877_0.png resize: (166, 98) 1333551963 -4.430406199767077 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647988014_0.png resize: (166, 98) 1333551964 -4.430406199767077 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647984870_0.png resize: (198, 159) 1333551965 -4.354086695838499 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647988013_0.png resize: (198, 159) 1333551966 -4.354086695838499 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647984890_0.png resize: (230, 116) 1333551967 -3.940503461550069 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647988022_0.png resize: (230, 116) 1333551968 -3.940503461550069 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647984876_0.png resize: (135, 76) 1333551969 -4.0426246824120895 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647988015_0.png resize: (135, 76) 1333551970 -4.0426246824120895 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647984858_0.png resize: (455, 315) 1333551971 -4.166652062585255 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647984869_0.png resize: (113, 54) 1333551972 -3.946404923985442 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647988039_0.png resize: (109, 185) 1333551973 -3.6556091553867094 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647984875_0.png resize: (109, 185) 1333551974 -3.6556091553867094 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647988044_0.png resize: (113, 54) 1333551975 -3.946404923985442 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647988027_0.png resize: (455, 315) 1333551976 -4.166652062585255 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647984861_0.png resize: (215, 225) 1333551977 -2.8674225398500166 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647988024_0.png resize: (215, 225) 1333551978 -2.8674225398500166 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647984889_0.png resize: (65, 81) 1333551979 -1.2860576266734902 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647988029_0.png resize: (65, 81) 1333551980 -1.564745032630204 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647984865_0.png resize: (167, 112) 1333551981 -3.1223444049178943 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647988031_0.png resize: (167, 112) 1333551982 -3.1223444049178943 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647984885_0.png resize: (90, 91) 1333551984 -2.8226171307938834 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647988030_0.png resize: (90, 91) 1333551986 -2.8226171307938834 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647988043_0.png resize: (77, 72) 1333551987 -3.236105183940368 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647984887_0.png resize: (77, 72) 1333551988 -3.236105183940368 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647984871_0.png resize: (221, 205) 1333551989 -3.63558782366759 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647988016_0.png resize: (221, 205) 1333551990 -3.63558782366759 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647984860_0.png resize: (160, 211) 1333551991 -3.21447948372489 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647988012_0.png resize: (160, 211) 1333551992 -3.21447948372489 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647984891_0.png resize: (159, 192) 1333551993 -3.2328767861441814 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647988025_0.png resize: (159, 192) 1333551994 -3.2328767861441814 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647984866_0.png resize: (433, 416) 1333551995 -4.316244089564295 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647988028_0.png resize: (433, 416) 1333551996 -4.316244089564295 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647984862_0.png resize: (208, 121) 1333551997 -4.052893872520666 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647988034_0.png resize: (208, 121) 1333551998 -4.052893872520666 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647988017_0.png resize: (142, 109) 1333551999 -3.458359202563764 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647984873_0.png resize: (142, 109) 1333552000 -3.458359202563764 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647984883_0.png resize: (99, 90) 1333552001 -3.5659618631123675 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647988040_0.png resize: (77, 89) 1333552002 -1.6365360704605236 treat image : 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temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647988018_0.png resize: (51, 100) 1333552009 -1.110195481689399 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647984880_0.png resize: (147, 110) 1333552010 -2.61438593358203 treat image : temp/1738372229_2654573_1333348189_9a01f438c16285db32ed788460a5da6e_rle_crop_3647988032_0.png resize: (142, 110) 1333552011 -2.9755966791859283 treat image : temp/1738372229_2654573_1333348185_f2d424fa38d9fa76ed64cc159e7c3745_rle_crop_3647984905_0.png resize: (123, 161) 1333552012 -1.4337167881261552 treat image : temp/1738372229_2654573_1333348185_f2d424fa38d9fa76ed64cc159e7c3745_rle_crop_3647988078_0.png resize: (123, 161) 1333552013 -1.4337167881261552 treat image : temp/1738372229_2654573_1333348185_f2d424fa38d9fa76ed64cc159e7c3745_rle_crop_3647984921_0.png resize: (428, 156) 1333552015 -4.351251681325576 treat image : temp/1738372229_2654573_1333348185_f2d424fa38d9fa76ed64cc159e7c3745_rle_crop_3647988080_0.png resize: (428, 156) 1333552016 -4.351251681325576 treat image : temp/1738372229_2654573_1333348185_f2d424fa38d9fa76ed64cc159e7c3745_rle_crop_3647984902_0.png resize: (96, 113) 1333552017 -1.4141957303437231 treat image : temp/1738372229_2654573_1333348185_f2d424fa38d9fa76ed64cc159e7c3745_rle_crop_3647988099_0.png resize: (96, 113) 1333552018 -1.4141957303437231 treat image : temp/1738372229_2654573_1333348185_f2d424fa38d9fa76ed64cc159e7c3745_rle_crop_3647984906_0.png resize: (222, 249) 1333552019 -3.781160896431101 treat image : temp/1738372229_2654573_1333348185_f2d424fa38d9fa76ed64cc159e7c3745_rle_crop_3647984923_0.png resize: (367, 213) 1333552020 -3.91238081224315 treat image : temp/1738372229_2654573_1333348185_f2d424fa38d9fa76ed64cc159e7c3745_rle_crop_3647988072_0.png resize: (367, 213) 1333552021 -3.91238081224315 treat image : temp/1738372229_2654573_1333348185_f2d424fa38d9fa76ed64cc159e7c3745_rle_crop_3647984912_0.png resize: (98, 181) 1333552022 -4.20388347350919 treat image : temp/1738372229_2654573_1333348185_f2d424fa38d9fa76ed64cc159e7c3745_rle_crop_3647988096_0.png resize: (98, 180) 1333552023 -4.205215319357844 treat image : temp/1738372229_2654573_1333348185_f2d424fa38d9fa76ed64cc159e7c3745_rle_crop_3647988097_0.png resize: (222, 249) 1333552024 -3.7428011396360588 treat image : temp/1738372229_2654573_1333348185_f2d424fa38d9fa76ed64cc159e7c3745_rle_crop_3647984908_0.png resize: (177, 115) 1333552025 -2.4706898060549687 treat image : temp/1738372229_2654573_1333348185_f2d424fa38d9fa76ed64cc159e7c3745_rle_crop_3647988075_0.png resize: (177, 115) 1333552026 -2.4706898060549687 treat image : temp/1738372229_2654573_1333348185_f2d424fa38d9fa76ed64cc159e7c3745_rle_crop_3647984895_0.png resize: (222, 324) 1333552027 -4.853398915739093 treat image : temp/1738372229_2654573_1333348185_f2d424fa38d9fa76ed64cc159e7c3745_rle_crop_3647988086_0.png resize: (222, 324) 1333552028 -4.853398915739093 treat image : temp/1738372229_2654573_1333348185_f2d424fa38d9fa76ed64cc159e7c3745_rle_crop_3647984919_0.png resize: (50, 53) 1333552029 -3.1085326778408136 treat image : temp/1738372229_2654573_1333348185_f2d424fa38d9fa76ed64cc159e7c3745_rle_crop_3647988074_0.png resize: (98, 112) 1333552030 -1.100250059616219 treat image : temp/1738372229_2654573_1333348185_f2d424fa38d9fa76ed64cc159e7c3745_rle_crop_3647984898_0.png resize: (98, 112) 1333552031 -1.100250059616219 treat image : temp/1738372229_2654573_1333348185_f2d424fa38d9fa76ed64cc159e7c3745_rle_crop_3647988076_0.png resize: (49, 49) 1333552032 -2.90384336680099 treat image : temp/1738372229_2654573_1333348185_f2d424fa38d9fa76ed64cc159e7c3745_rle_crop_3647984892_0.png resize: (480, 1148) 1333552033 -2.0650380935927712 treat image : 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temp/1738372229_2654573_1333348185_f2d424fa38d9fa76ed64cc159e7c3745_rle_crop_3647988069_0.png resize: (356, 426) 1333552040 -2.599714586491787 treat image : temp/1738372229_2654573_1333348185_f2d424fa38d9fa76ed64cc159e7c3745_rle_crop_3647984907_0.png resize: (165, 117) 1333552041 -0.04702902614369665 treat image : temp/1738372229_2654573_1333348185_f2d424fa38d9fa76ed64cc159e7c3745_rle_crop_3647988068_0.png resize: (165, 117) 1333552042 -0.04702902614369665 treat image : temp/1738372229_2654573_1333348185_f2d424fa38d9fa76ed64cc159e7c3745_rle_crop_3647984917_0.png resize: (121, 99) 1333552043 -4.0862002871664895 treat image : temp/1738372229_2654573_1333348185_f2d424fa38d9fa76ed64cc159e7c3745_rle_crop_3648057280_0.png resize: (126, 93) 1333552044 -4.032380955966812 treat image : temp/1738372229_2654573_1333348185_f2d424fa38d9fa76ed64cc159e7c3745_rle_crop_3647988093_0.png resize: (121, 99) 1333552045 -4.0862002871664895 treat image : 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temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647985005_0.png resize: (104, 117) 1333552236 -3.617314377758724 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647988200_0.png resize: (104, 117) 1333552238 -3.617314377758724 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647985019_0.png resize: (212, 266) 1333552240 -5.137784511839754 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647988192_0.png resize: (212, 266) 1333552242 -5.137784511839754 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647985024_0.png resize: (109, 179) 1333552244 -5.016550918234887 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647984987_0.png resize: (215, 195) 1333552246 -3.063794100508822 treat image : 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temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647988169_0.png resize: (236, 144) 1333552334 -4.9871398034343395 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647985017_0.png resize: (196, 103) 1333552336 -4.5597823556755905 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647988194_0.png resize: (308, 154) 1333552338 -4.943367694205601 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647988177_0.png resize: (196, 103) 1333552340 -4.5597823556755905 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647984974_0.png resize: (76, 144) 1333552342 -4.32519059736686 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647988217_0.png resize: (76, 144) 1333552344 -4.32519059736686 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647984991_0.png resize: (97, 58) 1333552346 -3.113103450009627 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647988203_0.png resize: (97, 58) 1333552348 -3.113103450009627 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647985020_0.png resize: (178, 95) 1333552350 -4.368695243852451 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647988221_0.png resize: (178, 95) 1333552352 -4.368695243852451 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647984981_0.png resize: (112, 56) 1333552354 -2.8969528936744084 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647988209_0.png resize: (112, 56) 1333552356 -2.8969528936744084 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647984982_0.png resize: (134, 259) 1333552358 -4.131945350717541 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647988181_0.png resize: (134, 259) 1333552360 -4.131945350717541 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647984995_0.png resize: (183, 72) 1333552362 -3.922896330755596 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647984993_0.png resize: (275, 482) 1333552364 -5.114251464749125 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647988210_0.png resize: (183, 72) 1333552366 -3.922896330755596 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647988218_0.png resize: (275, 482) 1333552368 -5.114251464749125 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647988223_0.png resize: (151, 111) 1333552370 -4.136407540582621 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647985002_0.png resize: (151, 111) 1333552372 -4.136407540582621 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3648057282_0.png resize: (151, 102) 1333552374 -4.111339458700626 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647984980_0.png resize: (134, 108) 1333552377 -2.9000880034093415 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647988186_0.png resize: (134, 108) 1333552379 -2.9000880034093415 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647985009_0.png resize: (127, 150) 1333552381 -4.5961625530038654 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647988224_0.png resize: (127, 150) 1333552383 -4.5961625530038654 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647984984_0.png resize: (193, 119) 1333552386 -4.362761244271216 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647985000_0.png resize: (59, 115) 1333552388 -5.01818316153068 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647988207_0.png resize: (193, 119) 1333552390 -4.362761244271216 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647988216_0.png resize: (57, 113) 1333552392 -5.051531966896393 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647984986_0.png resize: (211, 165) 1333552394 -5.092227217867545 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647988171_0.png resize: (211, 165) 1333552396 -5.092227217867545 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647988204_0.png resize: (165, 130) 1333552398 -4.771068483828934 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647985011_0.png resize: (165, 130) 1333552400 -4.771068483828934 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647984994_0.png resize: (228, 222) 1333552402 -4.648540878073904 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647988220_0.png resize: (228, 222) 1333552404 -2.850133995627435 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647984976_0.png resize: (67, 89) 1333552406 -4.49215467994873 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647988215_0.png resize: (67, 89) 1333552408 -4.49215467994873 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647985027_0.png resize: (65, 115) 1333552410 -3.123338042731152 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647988212_0.png resize: (65, 115) 1333552412 -3.123338042731152 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647985004_0.png resize: (70, 79) 1333552414 -3.150639989689868 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647988170_0.png resize: (70, 79) 1333552416 -3.150639989689868 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647985031_0.png resize: (221, 236) 1333552418 -4.033220883141303 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647988190_0.png resize: (221, 236) 1333552420 -4.033220883141303 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647985015_0.png resize: (273, 248) 1333552422 -5.241251935022352 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647988179_0.png resize: (273, 248) 1333552424 -5.241251935022352 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647984983_0.png resize: (235, 181) 1333552426 -3.699758651386635 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647988219_0.png resize: (235, 181) 1333552428 -3.699758651386635 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647985026_0.png resize: (84, 45) 1333552430 -2.488276439599986 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647988214_0.png resize: (84, 45) 1333552432 -2.488276439599986 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647984999_0.png resize: (145, 216) 1333552434 -4.72789584319119 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647985025_0.png resize: (233, 135) 1333552436 -4.398990966614331 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647988187_0.png resize: (145, 216) 1333552438 -4.72789584319119 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647988202_0.png resize: (233, 135) 1333552440 -4.398990966614331 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647984989_0.png resize: (131, 159) 1333552442 -5.0823405064199925 treat image : temp/1738372229_2654573_1333348016_f72a2dcd7619523ff11e69c83f8492d6_rle_crop_3647988173_0.png resize: (131, 159) 1333552444 -5.0823405064199925 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647985046_0.png resize: (242, 189) 1333552446 -4.142999537094028 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647985088_0.png resize: (671, 280) 1333552448 -4.436410252210268 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647988231_0.png resize: (242, 189) 1333552450 -4.142999537094028 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647985035_0.png resize: (387, 290) 1333552452 -3.666869313958557 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647988268_0.png resize: (670, 280) 1333552454 -4.201311849357345 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647988239_0.png resize: (387, 290) 1333552456 -3.666869313958557 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647985041_0.png resize: (273, 148) 1333552458 -3.990068279134082 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3648057283_0.png resize: (268, 147) 1333552460 -3.9720507692988667 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647988277_0.png resize: (273, 148) 1333552462 -3.990068279134082 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647985089_0.png resize: (142, 131) 1333552464 -4.756318608230342 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647988284_0.png resize: (142, 131) 1333552466 -4.756318608230342 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3648057286_0.png resize: (172, 219) 1333552468 -2.814603632948532 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647985067_0.png resize: (175, 218) 1333552470 -2.8939086505596774 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647988240_0.png resize: (175, 218) 1333552472 -2.8937292110016006 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647985057_0.png resize: (155, 206) 1333552474 -4.109978593052559 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647988241_0.png resize: (155, 206) 1333552477 -4.109978593052559 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647985042_0.png resize: (265, 287) 1333552479 -4.913959793054878 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647988256_0.png resize: (265, 287) 1333552481 -4.913959793054878 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647985084_0.png resize: (103, 154) 1333552483 -2.154767026527783 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647988245_0.png resize: (103, 154) 1333552485 -2.154767026527783 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647988276_0.png resize: (135, 193) 1333552487 -2.969095278094877 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647985053_0.png resize: (135, 193) 1333552489 -2.969095278094877 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647985080_0.png resize: (210, 165) 1333552491 -3.470381888587511 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647988263_0.png resize: (210, 165) 1333552493 -3.470381888587511 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647985061_0.png resize: (115, 180) 1333552495 -2.8173843204632534 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647988286_0.png resize: (115, 180) 1333552497 -2.8173843204632534 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647985074_0.png resize: (291, 291) 1333552499 -3.8709025951677596 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647988275_0.png resize: (231, 330) 1333552501 -4.567741421727905 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3648057285_0.png resize: (229, 317) 1333552503 -4.537395276831899 treat image : 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temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647985090_0.png resize: (160, 153) 1333552515 -4.528683383745293 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647985071_0.png resize: (269, 162) 1333552516 -4.006690492747187 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647988269_0.png resize: (269, 162) 1333552517 -4.006690492747187 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647988261_0.png resize: (160, 153) 1333552519 -4.569926548595104 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647985068_0.png resize: (251, 155) 1333552520 -4.486973070220087 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647988257_0.png resize: (249, 151) 1333552521 -4.518114238788003 treat image : 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temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647985060_0.png resize: (148, 148) 1333552535 -3.558123972299923 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647985047_0.png resize: (149, 179) 1333552536 -3.7800463927655605 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647988247_0.png resize: (148, 148) 1333552537 -3.558123972299923 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647985032_0.png resize: (234, 182) 1333552538 -3.4059396019022046 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647988230_0.png resize: (149, 179) 1333552539 -3.7800463927655605 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647988271_0.png resize: (234, 182) 1333552540 -3.4059396019022046 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647985065_0.png resize: (111, 85) 1333552541 -4.2620323039137675 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647988242_0.png resize: (111, 85) 1333552542 -4.2620323039137675 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647985082_0.png resize: (157, 242) 1333552543 -3.469598754082192 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647988285_0.png resize: (157, 242) 1333552544 -3.469598754082192 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647985040_0.png resize: (73, 95) 1333552545 -1.1983528256176588 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647988283_0.png resize: (73, 95) 1333552546 -1.1983528256176588 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647985069_0.png resize: (304, 269) 1333552547 -4.632251898689828 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647988229_0.png resize: (304, 269) 1333552548 -4.632251898689828 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647985073_0.png resize: (240, 178) 1333552549 -4.565129587208625 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3648057287_0.png resize: (246, 177) 1333552550 -4.614744096782814 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647985063_0.png resize: (72, 122) 1333552551 -2.722799510068186 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647988252_0.png resize: (240, 178) 1333552552 -4.565129587208625 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647988246_0.png resize: (72, 122) 1333552553 -2.722799510068186 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647985049_0.png resize: (85, 104) 1333552554 -4.522300294822293 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647988233_0.png resize: (85, 104) 1333552555 -4.522300294822293 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647985081_0.png resize: (164, 121) 1333552556 -2.473314936410682 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647988258_0.png resize: (164, 121) 1333552557 -2.473314936410682 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647985058_0.png resize: (186, 117) 1333552558 -4.030700442510607 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647988264_0.png resize: (186, 117) 1333552559 -4.030700442510607 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647985038_0.png resize: (179, 104) 1333552560 -4.162403422544173 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647988270_0.png resize: (179, 104) 1333552561 -4.162403422544173 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647985062_0.png resize: (332, 126) 1333552562 -4.214604303293481 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647988279_0.png resize: (332, 126) 1333552563 -4.214604303293481 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647985075_0.png resize: (477, 438) 1333552565 -1.6043377587352927 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647988278_0.png resize: (477, 438) 1333552566 -1.6043377587352927 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647985033_0.png resize: (108, 207) 1333552567 -4.980007467483519 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647988236_0.png resize: (108, 207) 1333552568 -4.980007467483519 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647985086_0.png resize: (267, 295) 1333552569 -4.569630648425098 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647988281_0.png resize: (267, 281) 1333552570 -4.164459057660607 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647985072_0.png resize: (188, 106) 1333552571 -5.306817574701146 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647988253_0.png resize: (188, 106) 1333552572 -5.306817574701146 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647985055_0.png resize: (195, 228) 1333552573 -4.9631823562042845 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647988235_0.png resize: (195, 228) 1333552574 -4.9631823562042845 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647985037_0.png resize: (249, 132) 1333552575 -4.33712841225678 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647988282_0.png resize: (249, 132) 1333552576 -4.33712841225678 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647985048_0.png resize: (118, 107) 1333552577 -2.998698897756031 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647988243_0.png resize: (118, 107) 1333552578 -2.998698897756031 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647985085_0.png resize: (155, 130) 1333552579 -3.6587484541184385 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647988250_0.png resize: (155, 130) 1333552580 -3.6587484541184385 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647988280_0.png resize: (152, 102) 1333552581 -3.0996343945162996 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647985083_0.png resize: (152, 102) 1333552582 -3.0996343945162996 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647988274_0.png resize: (100, 110) 1333552583 -3.952488035760536 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647985044_0.png resize: (100, 110) 1333552584 -3.952488035760536 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647985043_0.png resize: (134, 243) 1333552585 -3.712527294760128 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647988267_0.png resize: (134, 243) 1333552586 -3.712527294760128 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647985036_0.png resize: (366, 207) 1333552587 -5.438162446585864 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647988237_0.png resize: (366, 207) 1333552588 -5.438162446585864 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647985045_0.png resize: (236, 196) 1333552590 -4.420455016387417 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647988259_0.png resize: (236, 196) 1333552591 -4.420455016387417 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647985034_0.png resize: (193, 118) 1333552592 -4.58974667965828 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647988248_0.png resize: (193, 118) 1333552593 -4.58974667965828 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647988227_0.png resize: (128, 69) 1333552594 -1.364944057418907 treat image : temp/1738372229_2654573_1333347989_509ea1dcedaf9561d9b73ea6a11ec256_rle_crop_3647985091_0.png resize: (128, 69) 1333552595 -1.364944057418907 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647985102_0.png resize: (921, 920) 1333552596 -3.6925299573607777 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647988294_0.png resize: (921, 920) 1333552597 -3.6925299573607777 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647985114_0.png resize: (142, 544) 1333552598 -3.5948908164952416 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647988318_0.png resize: (142, 544) 1333552599 -3.5948908164952416 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647985093_0.png resize: (281, 421) 1333552600 -4.047871960144216 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647988315_0.png resize: (247, 97) 1333552602 -4.304966926633341 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647985094_0.png resize: (247, 97) 1333552603 -4.304966926633341 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647988307_0.png resize: (281, 421) 1333552604 -4.047871960144216 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647985115_0.png resize: (59, 84) 1333552605 -0.9844582279373851 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647988328_0.png resize: (59, 84) 1333552606 -0.9844582279373851 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647985092_0.png resize: (113, 178) 1333552607 -3.7460654881656716 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647988327_0.png resize: (113, 178) 1333552608 -3.7460654881656716 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647985098_0.png resize: (71, 164) 1333552609 -4.231637299874246 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647988323_0.png resize: (71, 164) 1333552610 -4.231637299874246 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647985105_0.png resize: (198, 231) 1333552611 -4.5701179607462326 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647988308_0.png resize: (198, 231) 1333552612 -4.5701179607462326 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647985112_0.png resize: (326, 358) 1333552613 -3.415300579375072 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647985108_0.png resize: (166, 128) 1333552614 -3.752131780827999 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647988293_0.png resize: (166, 128) 1333552615 -3.752131780827999 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647988326_0.png resize: (326, 358) 1333552616 -3.4046900646814646 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647985095_0.png resize: (155, 176) 1333552617 -4.222507930202347 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647988321_0.png resize: (155, 176) 1333552618 -4.222507930202347 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647985100_0.png resize: (157, 217) 1333552619 -3.9758080202744526 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647988301_0.png resize: (157, 217) 1333552620 -3.9758080202744526 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647985104_0.png resize: (340, 141) 1333552621 -3.7256225191448884 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647988298_0.png resize: (340, 141) 1333552622 -3.7246936913539583 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647985097_0.png resize: (310, 194) 1333552623 -3.2361969080255975 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647988299_0.png resize: (310, 194) 1333552624 -3.2361969080255975 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647985107_0.png resize: (208, 166) 1333552625 -3.73816647988626 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647988302_0.png resize: (208, 166) 1333552626 -3.73816647988626 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647985109_0.png resize: (100, 120) 1333552627 -2.9159757345606665 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647988319_0.png resize: (100, 120) 1333552628 -2.9159757345606665 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647985120_0.png resize: (330, 184) 1333552629 -3.7302851777200416 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647988303_0.png resize: (330, 184) 1333552630 -3.7302851777200416 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647985101_0.png resize: (133, 103) 1333552631 -2.6067068639624833 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647988320_0.png resize: (133, 103) 1333552632 -2.6067068639624833 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647985126_0.png resize: (108, 108) 1333552633 -2.040550944027084 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647988304_0.png resize: (108, 108) 1333552634 -2.040550944027084 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647985125_0.png resize: (377, 545) 1333552635 -3.743831373806132 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647988316_0.png resize: (377, 545) 1333552636 -3.743831373806132 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647985123_0.png resize: (258, 307) 1333552637 -4.7233730029560785 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647988312_0.png resize: (258, 307) 1333552638 -4.7233730029560785 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647985111_0.png resize: (237, 183) 1333552639 -4.994426717491463 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647988296_0.png resize: (237, 183) 1333552640 -4.994426717491463 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647985106_0.png resize: (340, 394) 1333552641 -5.1570086625983125 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647988313_0.png resize: (340, 394) 1333552642 -5.1570086625983125 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647985110_0.png resize: (117, 113) 1333552643 -3.906605114412111 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647988309_0.png resize: (117, 113) 1333552645 -3.906605114412111 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647985119_0.png resize: (77, 88) 1333552646 -4.599552489495491 treat image : temp/1738372229_2654573_1333347939_25ac195c65c7eb21f84e56b48f92b61f_rle_crop_3647988314_0.png resize: (9, 20) ERROR in datou_step_exec, will save and exit ! float division by zero File "/home/admin/workarea/git/Velours/python/mtr/datou/datou_lib.py", line 2329, in datou_exec output = datou_step_exec(sNext, args, cache, context, map_info, verbose, mtr_user_id) File "/home/admin/workarea/git/Velours/python/mtr/datou/datou_lib.py", line 2530, in datou_step_exec return lib_process.datou_step_exec_blur_detection(param, json_param, args, context, map_info, verbose) File "/home/admin/workarea/git/Velours/python/mtr/datou/lib_step_exec/lib_step_process.py", line 1153, in datou_step_exec_blur_detection score = dbi.calcul_score_blur_detection(img_path, a, b, c, seuil_ratio, crop) File "/home/admin/workarea/git/Velours/python/mtr/datou/detect_blur_image.py", line 81, in calcul_score_blur_detection ratio = float(k)/((x-20)*(y-20)) [1333348189, 1333348185, 1333348179, 1333348016, 1333347989, 1333347939, 1333347927, 1333347884, 1333347719, 1333347695, 1333347643, 1333347642] begin to insert list_values into mtr_datou_result : length of list_values in save_final : 12 time used for this insertion : 0.017223596572875977 save_final ERROR in last step blur_detection, float division by zero time spend for datou_step_exec : 49.18807506561279 time spend to save output : 0.02406620979309082 total time spend for step 5 : 49.212141275405884 caffe_path_current : About to save ! 2 After save, about to update current ! ret : 2 len(input) + len(total_photo_id_missing) : 12 set_done_treatment 450.55user 175.50system 14:01.11elapsed 74%CPU (0avgtext+0avgdata 9516600maxresident)k 1251992inputs+423456outputs (45975major+37940311minor)pagefaults 0swaps