python /home/admin/mtr/script_for_cron.py -j default -m 20 -a 'python3 ~/workarea/git/Velours/python/prod/datou.py -j batch_current -C 3784180' -s carac_3318 -M 0 -S 0 -U 100,80,95 import MySQLdb succeeded Import error (python version) ['/Users/moilerat/Documents/Fotonower/install/caffe/distribute/python', '/home/admin/workarea/git/Velours/python/prod', '/home/admin/workarea/install/darknet', '/home/admin/workarea/git/Velours/python', '/home/admin/workarea/install/caffe_frcnn_python3/py-faster-rcnn/caffe-fast-rcnn/python', '/home/admin/mtr/.credentials', '/home/admin/workarea/install/caffe/python', '/home/admin/workarea/install/caffe_frcnn/py-faster-rcnn/tools', '/home/admin/workarea/git/fotonowerpip', '/home/admin/workarea/install/segment-anything', '/home/admin/workarea/git/pyfvs', '/home/admin/workarea/git/apy', '/usr/lib/python38.zip', '/usr/lib/python3.8', '/usr/lib/python3.8/lib-dynload', '/home/admin/.local/lib/python3.8/site-packages', '/usr/local/lib/python3.8/dist-packages', '/usr/lib/python3/dist-packages'] process id : 359586 load datou : 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) 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 : step 0 init_dummy_multi_datou is not linked in the step_by_step architecture ! WARNING : step 1294 init_dummy_multi_datou is not linked in the step_by_step architecture ! 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 ! 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 : (photo_id, hashtag_id, score_max) was removed should we ? (x0, y0, x1, y1) was removed should we ? chemin de la photo was removed should we ? (photo_id, hashtag_id, score_max) was removed should we ? (x0, y0, x1, y1) was removed should we ? chemin de la photo was removed should we ? load thcls load pdts 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 : ['3784180'] with mtr_portfolio_ids : ['27268302'] and first list_photo_ids : [] new path : /proc/359586/ 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 , BFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 16 ; length of list_pids : 16 ; length of list_args : 16 time to download the photos : 3.481722831726074 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : 0 number of steps : 10 step1:mask_detect Tue Sep 30 16:59:50 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 : 10582 max_wait_temp : 1 max_wait : 0 gpu_flag : 0 2025-09-30 16:59:53.415580: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2025-09-30 16:59:53.440567: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3492910000 Hz 2025-09-30 16:59:53.442294: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f1714000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-09-30 16:59:53.442339: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-09-30 16:59:53.445777: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-09-30 16:59:53.593542: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x3d076d60 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-09-30 16:59:53.593590: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-09-30 16:59:53.595083: 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 2025-09-30 16:59:53.595757: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-09-30 16:59:53.603131: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-09-30 16:59:53.608488: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-09-30 16:59:53.609650: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-09-30 16:59:53.621663: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-09-30 16:59:53.623474: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-09-30 16:59:53.641733: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-09-30 16:59:53.643454: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-09-30 16:59:53.643518: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-09-30 16:59:53.644697: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-09-30 16:59:53.644718: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-09-30 16:59:53.644728: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-09-30 16:59:53.646397: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 9801 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. 2025-09-30 16:59:54.116111: 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 2025-09-30 16:59:54.116215: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-09-30 16:59:54.116243: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-09-30 16:59:54.116269: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-09-30 16:59:54.116292: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-09-30 16:59:54.116316: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-09-30 16:59:54.116356: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-09-30 16:59:54.116385: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-09-30 16:59:54.118473: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-09-30 16:59:54.120162: 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 2025-09-30 16:59:54.120213: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-09-30 16:59:54.120242: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-09-30 16:59:54.120269: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-09-30 16:59:54.120295: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-09-30 16:59:54.120321: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-09-30 16:59:54.120380: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-09-30 16:59:54.120414: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-09-30 16:59:54.122025: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-09-30 16:59:54.122049: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-09-30 16:59:54.122057: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-09-30 16:59:54.122064: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-09-30 16:59:54.123265: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 9801 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 : [] 2025-09-30 17:00:04.469403: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-09-30 17:00:04.669082: 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 : 16 NEW PHOTO Processing 1 images image shape: (2160, 3840, 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: 3840.00000 nb d'objets trouves : 27 NEW PHOTO Processing 1 images image shape: (2160, 3840, 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: 3840.00000 nb d'objets trouves : 22 NEW PHOTO Processing 1 images image shape: (2160, 3840, 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: 3840.00000 nb d'objets trouves : 25 NEW PHOTO Processing 1 images image shape: (2160, 3840, 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: 3840.00000 nb d'objets trouves : 18 NEW PHOTO Processing 1 images image shape: (2160, 3840, 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: 3840.00000 nb d'objets trouves : 21 NEW PHOTO Processing 1 images image shape: (2160, 3840, 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: 3840.00000 nb d'objets trouves : 28 NEW PHOTO Processing 1 images image shape: (2160, 3840, 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: 3840.00000 nb d'objets trouves : 24 NEW PHOTO Processing 1 images image shape: (2160, 3840, 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: 3840.00000 nb d'objets trouves : 15 NEW PHOTO Processing 1 images image shape: (2160, 3840, 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: 3840.00000 nb d'objets trouves : 28 NEW PHOTO Processing 1 images image shape: (2160, 3840, 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: 3840.00000 nb d'objets trouves : 27 NEW PHOTO Processing 1 images image shape: (2160, 3840, 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: 3840.00000 nb d'objets trouves : 18 NEW PHOTO Processing 1 images image shape: (2160, 3840, 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: 3840.00000 nb d'objets trouves : 20 NEW PHOTO Processing 1 images image shape: (2160, 3840, 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: 3840.00000 nb d'objets trouves : 24 NEW PHOTO Processing 1 images image shape: (2160, 3840, 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: 3840.00000 nb d'objets trouves : 17 NEW PHOTO Processing 1 images image shape: (2160, 3840, 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: 3840.00000 nb d'objets trouves : 18 NEW PHOTO Processing 1 images image shape: (2160, 3840, 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: 3840.00000 nb d'objets trouves : 19 Detection mask done ! Trying to reset tf kernel 359662 begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 5290 tf kernel not reseted sub process len(results) : 16 len(list_Values) 0 None max_time_sub_proc : 3600 parent process len(results) : 16 len(list_Values) 0 process is alive finish correctly or not : True after detect begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 10582 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 : 0.015558242797851562 nb_pixel_total : 385683 time to create 1 rle with new method : 0.027249574661254883 length of segment : 641 time for calcul the mask position with numpy : 0.0019097328186035156 nb_pixel_total : 124089 time to create 1 rle with old method : 0.12911772727966309 length of segment : 425 time for calcul the mask position with numpy : 0.0005123615264892578 nb_pixel_total : 21849 time to create 1 rle with old method : 0.023534297943115234 length of segment : 231 time for calcul the mask position with numpy : 0.0008263587951660156 nb_pixel_total : 55612 time to create 1 rle with old method : 0.05940866470336914 length of segment : 223 time for calcul the mask position with numpy : 0.0002257823944091797 nb_pixel_total : 10862 time to create 1 rle with old method : 0.012316703796386719 length of segment : 92 time for calcul the mask position with numpy : 0.00021314620971679688 nb_pixel_total : 13783 time to create 1 rle with old method : 0.01580667495727539 length of segment : 111 time for calcul the mask position with numpy : 0.00025010108947753906 nb_pixel_total : 14447 time to create 1 rle with old method : 0.015809059143066406 length of segment : 143 time for calcul the mask position with numpy : 0.00023508071899414062 nb_pixel_total : 14122 time to create 1 rle with old method : 0.015794754028320312 length of segment : 119 time for calcul the mask position with numpy : 0.0013575553894042969 nb_pixel_total : 82115 time to create 1 rle with old method : 0.08803534507751465 length of segment : 531 time for calcul the mask position with numpy : 0.00022077560424804688 nb_pixel_total : 6965 time to create 1 rle with old method : 0.010202884674072266 length of segment : 118 time for calcul the mask position with numpy : 0.0001709461212158203 nb_pixel_total : 8949 time to create 1 rle with old method : 0.009895801544189453 length of segment : 122 time for calcul the mask position with numpy : 0.004122018814086914 nb_pixel_total : 310627 time to create 1 rle with new method : 0.014943599700927734 length of segment : 907 time for calcul the mask position with numpy : 0.00033545494079589844 nb_pixel_total : 14346 time to create 1 rle with old method : 0.015677690505981445 length of segment : 174 time for calcul the mask position with numpy : 0.45560503005981445 nb_pixel_total : 4677288 time to create 1 rle with new method : 0.8806502819061279 length of segment : 2076 time for calcul the mask position with numpy : 0.0014615058898925781 nb_pixel_total : 94232 time to create 1 rle with old method : 0.09728693962097168 length of segment : 357 time for calcul the mask position with numpy : 0.0026111602783203125 nb_pixel_total : 198864 time to create 1 rle with new method : 0.009867668151855469 length of segment : 432 time for calcul the mask position with numpy : 0.00033473968505859375 nb_pixel_total : 16025 time to create 1 rle with old method : 0.017462968826293945 length of segment : 90 time for calcul the mask position with numpy : 0.0007081031799316406 nb_pixel_total : 33582 time to create 1 rle with old method : 0.03692150115966797 length of segment : 253 time for calcul the mask position with numpy : 0.0015614032745361328 nb_pixel_total : 91251 time to create 1 rle with old method : 0.10339784622192383 length of segment : 278 time for calcul the mask position with numpy : 0.0002529621124267578 nb_pixel_total : 7890 time to create 1 rle with old method : 0.00880289077758789 length of segment : 88 time for calcul the mask position with numpy : 0.0008559226989746094 nb_pixel_total : 47513 time to create 1 rle with old method : 0.05140829086303711 length of segment : 278 time for calcul the mask position with numpy : 0.0004284381866455078 nb_pixel_total : 18086 time to create 1 rle with old method : 0.01994037628173828 length of segment : 169 time for calcul the mask position with numpy : 0.0007894039154052734 nb_pixel_total : 33733 time to create 1 rle with old method : 0.035414934158325195 length of segment : 468 time for calcul the mask position with numpy : 0.0006132125854492188 nb_pixel_total : 30081 time to create 1 rle with old method : 0.03219890594482422 length of segment : 175 time for calcul the mask position with numpy : 0.0009677410125732422 nb_pixel_total : 48387 time to create 1 rle with old method : 0.0574495792388916 length of segment : 208 time for calcul the mask position with numpy : 0.0014615058898925781 nb_pixel_total : 41322 time to create 1 rle with old method : 0.04520726203918457 length of segment : 294 time for calcul the mask position with numpy : 0.003230571746826172 nb_pixel_total : 116110 time to create 1 rle with old method : 0.13428473472595215 length of segment : 312 time for calcul the mask position with numpy : 0.002162933349609375 nb_pixel_total : 64751 time to create 1 rle with old method : 0.07238411903381348 length of segment : 222 time for calcul the mask position with numpy : 0.0028257369995117188 nb_pixel_total : 108719 time to create 1 rle with old method : 0.11974859237670898 length of segment : 297 time for calcul the mask position with numpy : 0.001508474349975586 nb_pixel_total : 50898 time to create 1 rle with old method : 0.052457332611083984 length of segment : 303 time for calcul the mask position with numpy : 0.0029823780059814453 nb_pixel_total : 51560 time to create 1 rle with old method : 0.06205177307128906 length of segment : 498 time for calcul the mask position with numpy : 0.001962900161743164 nb_pixel_total : 65742 time to create 1 rle with old method : 0.06746602058410645 length of segment : 242 time for calcul the mask position with numpy : 0.0020530223846435547 nb_pixel_total : 54349 time to create 1 rle with old method : 0.05831766128540039 length of segment : 187 time for calcul the mask position with numpy : 0.0017685890197753906 nb_pixel_total : 31489 time to create 1 rle with old method : 0.03700375556945801 length of segment : 266 time for calcul the mask position with numpy : 0.0070383548736572266 nb_pixel_total : 278173 time to create 1 rle with new method : 0.011927604675292969 length of segment : 552 time for calcul the mask position with numpy : 0.0010919570922851562 nb_pixel_total : 42874 time to create 1 rle with old method : 0.04697370529174805 length of segment : 175 time for calcul the mask position with numpy : 0.0020694732666015625 nb_pixel_total : 52854 time to create 1 rle with old method : 0.058089494705200195 length of segment : 281 time for calcul the mask position with numpy : 0.001718282699584961 nb_pixel_total : 80478 time to create 1 rle with old method : 0.09003710746765137 length of segment : 247 time for calcul the mask position with numpy : 0.0036363601684570312 nb_pixel_total : 149890 time to create 1 rle with old method : 0.16489720344543457 length of segment : 490 time for calcul the mask position with numpy : 0.008556604385375977 nb_pixel_total : 247130 time to create 1 rle with new method : 0.011690855026245117 length of segment : 485 time for calcul the mask position with numpy : 0.0010302066802978516 nb_pixel_total : 27751 time to create 1 rle with old method : 0.031613826751708984 length of segment : 254 time for calcul the mask position with numpy : 0.0014314651489257812 nb_pixel_total : 43982 time to create 1 rle with old method : 0.04975605010986328 length of segment : 285 time for calcul the mask position with numpy : 0.0036249160766601562 nb_pixel_total : 115253 time to create 1 rle with old method : 0.14568305015563965 length of segment : 477 time for calcul the mask position with numpy : 0.003339052200317383 nb_pixel_total : 71361 time to create 1 rle with old method : 0.07854795455932617 length of segment : 335 time for calcul the mask position with numpy : 0.0010607242584228516 nb_pixel_total : 38287 time to create 1 rle with old method : 0.043099403381347656 length of segment : 148 time for calcul the mask position with numpy : 0.0002791881561279297 nb_pixel_total : 5814 time to create 1 rle with old method : 0.0065424442291259766 length of segment : 78 time for calcul the mask position with numpy : 0.00485992431640625 nb_pixel_total : 195568 time to create 1 rle with new method : 0.00849294662475586 length of segment : 398 time for calcul the mask position with numpy : 0.0006589889526367188 nb_pixel_total : 25734 time to create 1 rle with old method : 0.029587745666503906 length of segment : 233 time for calcul the mask position with numpy : 0.002032756805419922 nb_pixel_total : 59913 time to create 1 rle with old method : 0.06496763229370117 length of segment : 565 time for calcul the mask position with numpy : 0.0012576580047607422 nb_pixel_total : 32343 time to create 1 rle with old method : 0.03608441352844238 length of segment : 128 time for calcul the mask position with numpy : 0.003971099853515625 nb_pixel_total : 139036 time to create 1 rle with old method : 0.15235614776611328 length of segment : 666 time for calcul the mask position with numpy : 0.0003426074981689453 nb_pixel_total : 11458 time to create 1 rle with old method : 0.013004064559936523 length of segment : 154 time for calcul the mask position with numpy : 0.0043544769287109375 nb_pixel_total : 184852 time to create 1 rle with new method : 0.0069730281829833984 length of segment : 519 time for calcul the mask position with numpy : 0.0032198429107666016 nb_pixel_total : 122818 time to create 1 rle with old method : 0.13127994537353516 length of segment : 611 time for calcul the mask position with numpy : 0.0017063617706298828 nb_pixel_total : 57910 time to create 1 rle with old method : 0.06474924087524414 length of segment : 322 time for calcul the mask position with numpy : 0.002912282943725586 nb_pixel_total : 104968 time to create 1 rle with old method : 0.14113545417785645 length of segment : 402 time for calcul the mask position with numpy : 0.0011954307556152344 nb_pixel_total : 40045 time to create 1 rle with old method : 0.0456995964050293 length of segment : 314 time for calcul the mask position with numpy : 0.007210493087768555 nb_pixel_total : 251421 time to create 1 rle with new method : 0.012141942977905273 length of segment : 725 time for calcul the mask position with numpy : 0.0019676685333251953 nb_pixel_total : 53020 time to create 1 rle with old method : 0.06083273887634277 length of segment : 304 time for calcul the mask position with numpy : 0.00575566291809082 nb_pixel_total : 193491 time to create 1 rle with new method : 0.00824427604675293 length of segment : 444 time for calcul the mask position with numpy : 0.00092315673828125 nb_pixel_total : 30185 time to create 1 rle with old method : 0.03335905075073242 length of segment : 191 time for calcul the mask position with numpy : 0.0009205341339111328 nb_pixel_total : 49907 time to create 1 rle with old method : 0.05515289306640625 length of segment : 259 time for calcul the mask position with numpy : 0.002569437026977539 nb_pixel_total : 75364 time to create 1 rle with old method : 0.08151102066040039 length of segment : 448 time for calcul the mask position with numpy : 0.0018093585968017578 nb_pixel_total : 60922 time to create 1 rle with old method : 0.0669701099395752 length of segment : 395 time for calcul the mask position with numpy : 0.0011012554168701172 nb_pixel_total : 29603 time to create 1 rle with old method : 0.03359484672546387 length of segment : 251 time for calcul the mask position with numpy : 0.0005283355712890625 nb_pixel_total : 12259 time to create 1 rle with old method : 0.0143280029296875 length of segment : 126 time for calcul the mask position with numpy : 0.0008690357208251953 nb_pixel_total : 22769 time to create 1 rle with old method : 0.025272130966186523 length of segment : 233 time for calcul the mask position with numpy : 0.0007932186126708984 nb_pixel_total : 23428 time to create 1 rle with old method : 0.02747941017150879 length of segment : 158 time for calcul the mask position with numpy : 0.0006108283996582031 nb_pixel_total : 18950 time to create 1 rle with old method : 0.021611928939819336 length of segment : 222 time for calcul the mask position with numpy : 0.00047659873962402344 nb_pixel_total : 15510 time to create 1 rle with old method : 0.017714738845825195 length of segment : 116 time for calcul the mask position with numpy : 0.0006158351898193359 nb_pixel_total : 20631 time to create 1 rle with old method : 0.023898839950561523 length of segment : 173 time for calcul the mask position with numpy : 0.0006561279296875 nb_pixel_total : 22359 time to create 1 rle with old method : 0.028069257736206055 length of segment : 161 time for calcul the mask position with numpy : 0.002397775650024414 nb_pixel_total : 94286 time to create 1 rle with old method : 0.10448598861694336 length of segment : 677 time for calcul the mask position with numpy : 0.001180410385131836 nb_pixel_total : 27448 time to create 1 rle with old method : 0.031768798828125 length of segment : 273 time for calcul the mask position with numpy : 0.0005593299865722656 nb_pixel_total : 14295 time to create 1 rle with old method : 0.016718149185180664 length of segment : 162 time for calcul the mask position with numpy : 0.004721879959106445 nb_pixel_total : 193431 time to create 1 rle with new method : 0.008763313293457031 length of segment : 529 time for calcul the mask position with numpy : 0.0009284019470214844 nb_pixel_total : 28415 time to create 1 rle with old method : 0.032928466796875 length of segment : 245 time for calcul the mask position with numpy : 0.0016820430755615234 nb_pixel_total : 89833 time to create 1 rle with old method : 0.10226607322692871 length of segment : 367 time for calcul the mask position with numpy : 0.0010597705841064453 nb_pixel_total : 27669 time to create 1 rle with old method : 0.03159499168395996 length of segment : 255 time for calcul the mask position with numpy : 0.0025789737701416016 nb_pixel_total : 86227 time to create 1 rle with old method : 0.09460997581481934 length of segment : 504 time for calcul the mask position with numpy : 0.0003654956817626953 nb_pixel_total : 7267 time to create 1 rle with old method : 0.008351564407348633 length of segment : 141 time for calcul the mask position with numpy : 0.016089916229248047 nb_pixel_total : 692869 time to create 1 rle with new method : 0.04201698303222656 length of segment : 944 time for calcul the mask position with numpy : 0.003847360610961914 nb_pixel_total : 102427 time to create 1 rle with old method : 0.1164250373840332 length of segment : 430 time for calcul the mask position with numpy : 0.00036597251892089844 nb_pixel_total : 10415 time to create 1 rle with old method : 0.012325048446655273 length of segment : 101 time for calcul the mask position with numpy : 0.0005178451538085938 nb_pixel_total : 8094 time to create 1 rle with old method : 0.009305000305175781 length of segment : 136 time for calcul the mask position with numpy : 0.0013196468353271484 nb_pixel_total : 29241 time to create 1 rle with old method : 0.03299379348754883 length of segment : 285 time for calcul the mask position with numpy : 0.002273082733154297 nb_pixel_total : 81128 time to create 1 rle with old method : 0.09246087074279785 length of segment : 316 time for calcul the mask position with numpy : 0.0023620128631591797 nb_pixel_total : 57655 time to create 1 rle with old method : 0.06813311576843262 length of segment : 509 time for calcul the mask position with numpy : 0.0023832321166992188 nb_pixel_total : 82728 time to create 1 rle with old method : 0.09209132194519043 length of segment : 338 time for calcul the mask position with numpy : 0.0007371902465820312 nb_pixel_total : 27095 time to create 1 rle with old method : 0.03099846839904785 length of segment : 200 time for calcul the mask position with numpy : 0.0013251304626464844 nb_pixel_total : 48228 time to create 1 rle with old method : 0.06254339218139648 length of segment : 202 time for calcul the mask position with numpy : 0.005059719085693359 nb_pixel_total : 121287 time to create 1 rle with old method : 0.15355944633483887 length of segment : 556 time for calcul the mask position with numpy : 0.0005700588226318359 nb_pixel_total : 12935 time to create 1 rle with old method : 0.021588563919067383 length of segment : 107 time for calcul the mask position with numpy : 0.0005359649658203125 nb_pixel_total : 12784 time to create 1 rle with old method : 0.014834165573120117 length of segment : 129 time for calcul the mask position with numpy : 0.0034008026123046875 nb_pixel_total : 112432 time to create 1 rle with old method : 0.12407851219177246 length of segment : 434 time for calcul the mask position with numpy : 0.0003325939178466797 nb_pixel_total : 15402 time to create 1 rle with old method : 0.017870426177978516 length of segment : 131 time for calcul the mask position with numpy : 0.0024335384368896484 nb_pixel_total : 95581 time to create 1 rle with old method : 0.10768318176269531 length of segment : 343 time for calcul the mask position with numpy : 0.0008745193481445312 nb_pixel_total : 22411 time to create 1 rle with old method : 0.025705337524414062 length of segment : 185 time for calcul the mask position with numpy : 0.0013909339904785156 nb_pixel_total : 44180 time to create 1 rle with old method : 0.05040764808654785 length of segment : 284 time for calcul the mask position with numpy : 0.0005202293395996094 nb_pixel_total : 16592 time to create 1 rle with old method : 0.018963336944580078 length of segment : 147 time for calcul the mask position with numpy : 0.0009067058563232422 nb_pixel_total : 33497 time to create 1 rle with old method : 0.03796792030334473 length of segment : 221 time for calcul the mask position with numpy : 0.0002868175506591797 nb_pixel_total : 15956 time to create 1 rle with old method : 0.01792740821838379 length of segment : 143 time for calcul the mask position with numpy : 0.008917093276977539 nb_pixel_total : 217960 time to create 1 rle with new method : 0.013935327529907227 length of segment : 912 time for calcul the mask position with numpy : 0.0018796920776367188 nb_pixel_total : 65861 time to create 1 rle with old method : 0.07293272018432617 length of segment : 394 time for calcul the mask position with numpy : 0.0021605491638183594 nb_pixel_total : 74260 time to create 1 rle with old method : 0.08504438400268555 length of segment : 492 time for calcul the mask position with numpy : 0.0016398429870605469 nb_pixel_total : 59407 time to create 1 rle with old method : 0.06728625297546387 length of segment : 294 time for calcul the mask position with numpy : 0.002324819564819336 nb_pixel_total : 53741 time to create 1 rle with old method : 0.06140923500061035 length of segment : 360 time for calcul the mask position with numpy : 0.0012433528900146484 nb_pixel_total : 40610 time to create 1 rle with old method : 0.04597020149230957 length of segment : 238 time for calcul the mask position with numpy : 0.0017478466033935547 nb_pixel_total : 73648 time to create 1 rle with old method : 0.09943294525146484 length of segment : 344 time for calcul the mask position with numpy : 0.0019185543060302734 nb_pixel_total : 51330 time to create 1 rle with old method : 0.058503150939941406 length of segment : 372 time for calcul the mask position with numpy : 0.006561756134033203 nb_pixel_total : 227146 time to create 1 rle with new method : 0.011394739151000977 length of segment : 508 time for calcul the mask position with numpy : 0.003100156784057617 nb_pixel_total : 104046 time to create 1 rle with old method : 0.11710715293884277 length of segment : 412 time for calcul the mask position with numpy : 0.0008394718170166016 nb_pixel_total : 20845 time to create 1 rle with old method : 0.023111820220947266 length of segment : 231 time for calcul the mask position with numpy : 0.0011608600616455078 nb_pixel_total : 42159 time to create 1 rle with old method : 0.04683494567871094 length of segment : 246 time for calcul the mask position with numpy : 0.0006325244903564453 nb_pixel_total : 20304 time to create 1 rle with old method : 0.022706270217895508 length of segment : 167 time for calcul the mask position with numpy : 0.0010666847229003906 nb_pixel_total : 28975 time to create 1 rle with old method : 0.032099008560180664 length of segment : 209 time for calcul the mask position with numpy : 0.0006203651428222656 nb_pixel_total : 26307 time to create 1 rle with old method : 0.029811620712280273 length of segment : 194 time for calcul the mask position with numpy : 0.000926971435546875 nb_pixel_total : 34213 time to create 1 rle with old method : 0.03802847862243652 length of segment : 229 time for calcul the mask position with numpy : 0.0012009143829345703 nb_pixel_total : 33173 time to create 1 rle with old method : 0.0362238883972168 length of segment : 251 time for calcul the mask position with numpy : 0.0007431507110595703 nb_pixel_total : 26003 time to create 1 rle with old method : 0.02939128875732422 length of segment : 157 time for calcul the mask position with numpy : 0.000995635986328125 nb_pixel_total : 25730 time to create 1 rle with old method : 0.02849745750427246 length of segment : 190 time for calcul the mask position with numpy : 0.0009534358978271484 nb_pixel_total : 38935 time to create 1 rle with old method : 0.04492545127868652 length of segment : 206 time for calcul the mask position with numpy : 0.0038826465606689453 nb_pixel_total : 167823 time to create 1 rle with new method : 0.005549907684326172 length of segment : 514 time for calcul the mask position with numpy : 0.0012054443359375 nb_pixel_total : 36636 time to create 1 rle with old method : 0.043135643005371094 length of segment : 173 time for calcul the mask position with numpy : 0.0009202957153320312 nb_pixel_total : 33309 time to create 1 rle with old method : 0.03700447082519531 length of segment : 253 time for calcul the mask position with numpy : 0.000579833984375 nb_pixel_total : 18029 time to create 1 rle with old method : 0.02013421058654785 length of segment : 128 time for calcul the mask position with numpy : 0.0025527477264404297 nb_pixel_total : 99684 time to create 1 rle with old method : 0.1098778247833252 length of segment : 386 time for calcul the mask position with numpy : 0.0032007694244384766 nb_pixel_total : 154033 time to create 1 rle with new method : 0.0039370059967041016 length of segment : 474 time for calcul the mask position with numpy : 0.003110647201538086 nb_pixel_total : 140654 time to create 1 rle with old method : 0.15816926956176758 length of segment : 304 time for calcul the mask position with numpy : 0.00042319297790527344 nb_pixel_total : 14939 time to create 1 rle with old method : 0.017462491989135742 length of segment : 175 time for calcul the mask position with numpy : 0.0007698535919189453 nb_pixel_total : 25641 time to create 1 rle with old method : 0.028655529022216797 length of segment : 128 time for calcul the mask position with numpy : 0.0006842613220214844 nb_pixel_total : 21549 time to create 1 rle with old method : 0.024599552154541016 length of segment : 194 time for calcul the mask position with numpy : 0.0006411075592041016 nb_pixel_total : 22517 time to create 1 rle with old method : 0.026042461395263672 length of segment : 139 time for calcul the mask position with numpy : 0.0009024143218994141 nb_pixel_total : 27517 time to create 1 rle with old method : 0.0446925163269043 length of segment : 181 time for calcul the mask position with numpy : 0.0016014575958251953 nb_pixel_total : 66164 time to create 1 rle with old method : 0.07250547409057617 length of segment : 372 time for calcul the mask position with numpy : 0.004580259323120117 nb_pixel_total : 218889 time to create 1 rle with new method : 0.006842613220214844 length of segment : 505 time for calcul the mask position with numpy : 0.3466227054595947 nb_pixel_total : 4301512 time to create 1 rle with new method : 0.6836371421813965 length of segment : 2642 time for calcul the mask position with numpy : 0.0014700889587402344 nb_pixel_total : 54580 time to create 1 rle with old method : 0.061727046966552734 length of segment : 305 time for calcul the mask position with numpy : 0.0004622936248779297 nb_pixel_total : 16261 time to create 1 rle with old method : 0.019154787063598633 length of segment : 95 time for calcul the mask position with numpy : 0.0007882118225097656 nb_pixel_total : 23887 time to create 1 rle with old method : 0.02689051628112793 length of segment : 166 time for calcul the mask position with numpy : 0.0013890266418457031 nb_pixel_total : 64821 time to create 1 rle with old method : 0.07135987281799316 length of segment : 249 time for calcul the mask position with numpy : 0.003920078277587891 nb_pixel_total : 137351 time to create 1 rle with old method : 0.15059137344360352 length of segment : 547 time for calcul the mask position with numpy : 0.0008862018585205078 nb_pixel_total : 42866 time to create 1 rle with old method : 0.0484771728515625 length of segment : 158 time spent for convertir_results : 19.161787271499634 Inside saveOutput : final : False verbose : 0 eke 12-6-18 : saveMask need to be cleaned for new output ! Number saved : None batch 1 Loaded 143 chid ids of type : 3594 Number RLEs to save : 47443 save missing photos in datou_result : time spend for datou_step_exec : 86.3174500465393 time spend to save output : 5.089879512786865 total time spend for step 1 : 91.40732955932617 step2:crop_condition Tue Sep 30 17:01:21 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! 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 : 16 ! batch 1 Loaded 143 chid ids of type : 3594 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ begin to crop the class : papier param for this class : {'min_score': 0.7} filtre for class : papier hashtag_id of this class : 492668766 we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! map_result returned by crop_photo_return_map_crop : length : 44 About to insert : list_path_to_insert length 44 new photo from crops ! About to upload 44 photos upload in portfolio : 3736932 init cache_photo without model_param we have 44 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1759244498_359586 INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244507), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302361_caa1d21076ce801265ffe1196d1b1d80_rle_crop_3981095786_0.png', 0, 316, 514, 0, 1759244507,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244507), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302361_caa1d21076ce801265ffe1196d1b1d80_rle_crop_3981095782_0.png', 0, 184, 83, 0, 1759244507,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244507), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302361_caa1d21076ce801265ffe1196d1b1d80_rle_crop_3981095783_0.png', 0, 162, 111, 0, 1759244507,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244507), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302361_caa1d21076ce801265ffe1196d1b1d80_rle_crop_3981095780_0.png', 0, 130, 203, 0, 1759244507,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244507), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302357_ce78121a78f3d76800b7c71d3ed11b3b_rle_crop_3981095795_0.png', 0, 234, 213, 0, 1759244507,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244507), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302345_18ef46a11ab875d6338afbd6ab25fa4a_rle_crop_3981095803_0.png', 0, 176, 294, 0, 1759244507,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244507), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302319_50da8176754b972256fdd310af4e25aa_rle_crop_3981095816_0.png', 0, 461, 444, 0, 1759244507,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244507), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302319_50da8176754b972256fdd310af4e25aa_rle_crop_3981095812_0.png', 0, 745, 546, 0, 1759244507,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244507), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302319_50da8176754b972256fdd310af4e25aa_rle_crop_3981095811_0.png', 0, 227, 248, 0, 1759244507,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244507), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302319_50da8176754b972256fdd310af4e25aa_rle_crop_3981095814_0.png', 0, 537, 281, 0, 1759244507,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244507), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302302_e0d3c06db129da79f8ad80350c8f0577_rle_crop_3981095817_0.png', 0, 733, 483, 0, 1759244507,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244507), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302302_e0d3c06db129da79f8ad80350c8f0577_rle_crop_3981095825_0.png', 0, 225, 231, 0, 1759244507,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244507), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302302_e0d3c06db129da79f8ad80350c8f0577_rle_crop_3981095821_0.png', 0, 598, 335, 0, 1759244507,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244507), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302286_4ce84dcd8ab6d33803d5875471b522b9_rle_crop_3981095828_0.png', 0, 401, 538, 0, 1759244507,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244507), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302286_4ce84dcd8ab6d33803d5875471b522b9_rle_crop_3981095830_0.png', 0, 543, 478, 0, 1759244507,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244507), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302286_4ce84dcd8ab6d33803d5875471b522b9_rle_crop_3981095829_0.png', 0, 106, 154, 0, 1759244507,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244507), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302286_4ce84dcd8ab6d33803d5875471b522b9_rle_crop_3981095837_0.png', 0, 802, 375, 0, 1759244507,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244507), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302286_4ce84dcd8ab6d33803d5875471b522b9_rle_crop_3981095827_0.png', 0, 376, 122, 0, 1759244507,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244507), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302079_07022de81d7c5fd5889a36c7d151c632_rle_crop_3981095852_0.png', 0, 161, 162, 0, 1759244507,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244507), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302079_07022de81d7c5fd5889a36c7d151c632_rle_crop_3981095851_0.png', 0, 314, 211, 0, 1759244507,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244507), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302079_07022de81d7c5fd5889a36c7d151c632_rle_crop_3981095854_0.png', 0, 223, 223, 0, 1759244507,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244507), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302050_6b7e9a2de9ba085cde9b70c45023d640_rle_crop_3981095865_0.png', 0, 257, 500, 0, 1759244507,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244507), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302050_6b7e9a2de9ba085cde9b70c45023d640_rle_crop_3981095866_0.png', 0, 337, 333, 0, 1759244507,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244507), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302050_6b7e9a2de9ba085cde9b70c45023d640_rle_crop_3981095857_0.png', 0, 217, 502, 0, 1759244507,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244507), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302050_6b7e9a2de9ba085cde9b70c45023d640_rle_crop_3981095863_0.png', 0, 186, 285, 0, 1759244507,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244507), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302050_6b7e9a2de9ba085cde9b70c45023d640_rle_crop_3981095860_0.png', 0, 423, 398, 0, 1759244507,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244507), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302050_6b7e9a2de9ba085cde9b70c45023d640_rle_crop_3981095861_0.png', 0, 153, 96, 0, 1759244507,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244507), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302050_6b7e9a2de9ba085cde9b70c45023d640_rle_crop_3981095862_0.png', 0, 104, 136, 0, 1759244507,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244507), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302050_6b7e9a2de9ba085cde9b70c45023d640_rle_crop_3981095858_0.png', 0, 84, 141, 0, 1759244507,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244507), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302018_ccf36b9aba9c06d80ab85f52789a2795_rle_crop_3981095868_0.png', 0, 325, 191, 0, 1759244507,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244507), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302018_ccf36b9aba9c06d80ab85f52789a2795_rle_crop_3981095878_0.png', 0, 197, 221, 0, 1759244507,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244507), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386301983_b1ae4982d7372426325a6e09a54e1a65_rle_crop_3981095881_0.png', 0, 281, 389, 0, 1759244507,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244507), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386301983_b1ae4982d7372426325a6e09a54e1a65_rle_crop_3981095882_0.png', 0, 327, 426, 0, 1759244507,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244507), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386301953_3d192aa38bce05f090a0633230dd4bdf_rle_crop_3981095886_0.png', 0, 252, 323, 0, 1759244507,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244507), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386301953_3d192aa38bce05f090a0633230dd4bdf_rle_crop_3981095884_0.png', 0, 352, 328, 0, 1759244507,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244507), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386301925_a479eb7b704c59d507f8361a441478c6_rle_crop_3981095891_0.png', 0, 238, 245, 0, 1759244507,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244507), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386301925_a479eb7b704c59d507f8361a441478c6_rle_crop_3981095889_0.png', 0, 448, 412, 0, 1759244507,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244507), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386301925_a479eb7b704c59d507f8361a441478c6_rle_crop_3981095896_0.png', 0, 240, 242, 0, 1759244507,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244507), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386301882_1222513e42333942b0dfb98b088e45cd_rle_crop_3981095901_0.png', 0, 359, 165, 0, 1759244507,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244507), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386301882_1222513e42333942b0dfb98b088e45cd_rle_crop_3981095900_0.png', 0, 496, 511, 0, 1759244507,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244507), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386301882_1222513e42333942b0dfb98b088e45cd_rle_crop_3981095904_0.png', 0, 460, 377, 0, 1759244507,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244507), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386301877_629ff193e5587e28dbb01b1d4b49e62a_rle_crop_3981095911_0.png', 0, 237, 178, 0, 1759244507,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244507), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386301877_629ff193e5587e28dbb01b1d4b49e62a_rle_crop_3981095907_0.png', 0, 196, 175, 0, 1759244507,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244507), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386301860_814c16b7b8fa744b39a1ad6a523f8d17_rle_crop_3981095920_0.png', 0, 375, 155, 0, 1759244507,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 44 photos in the portfolio 3736932 time of upload the photos Elapsed time : 14.77797269821167 we have finished the crop for the class : papier begin to crop the class : carton param for this class : {'min_score': 0.7} filtre for class : carton hashtag_id of this class : 492774966 we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! map_result returned by crop_photo_return_map_crop : length : 17 About to insert : list_path_to_insert length 17 new photo from crops ! About to upload 17 photos upload in portfolio : 3736932 init cache_photo without model_param we have 17 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1759244519_359586 INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244522), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302357_ce78121a78f3d76800b7c71d3ed11b3b_rle_crop_3981095800_0.png', 0, 157, 407, 0, 1759244522,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244522), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302357_ce78121a78f3d76800b7c71d3ed11b3b_rle_crop_3981095793_0.png', 0, 619, 431, 0, 1759244522,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244522), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302345_18ef46a11ab875d6338afbd6ab25fa4a_rle_crop_3981095808_0.png', 0, 292, 466, 0, 1759244522,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244522), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302345_18ef46a11ab875d6338afbd6ab25fa4a_rle_crop_3981095801_0.png', 0, 253, 168, 0, 1759244522,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244522), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302302_e0d3c06db129da79f8ad80350c8f0577_rle_crop_3981095826_0.png', 0, 154, 556, 0, 1759244522,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244522), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302302_e0d3c06db129da79f8ad80350c8f0577_rle_crop_3981095818_0.png', 0, 160, 254, 0, 1759244522,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244522), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302302_e0d3c06db129da79f8ad80350c8f0577_rle_crop_3981095822_0.png', 0, 343, 133, 0, 1759244522,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244522), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302286_4ce84dcd8ab6d33803d5875471b522b9_rle_crop_3981095834_0.png', 0, 265, 237, 0, 1759244522,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244522), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302079_07022de81d7c5fd5889a36c7d151c632_rle_crop_3981095853_0.png', 0, 514, 526, 0, 1759244522,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244522), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302050_6b7e9a2de9ba085cde9b70c45023d640_rle_crop_3981095867_0.png', 0, 189, 200, 0, 1759244522,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244522), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302018_ccf36b9aba9c06d80ab85f52789a2795_rle_crop_3981095877_0.png', 0, 137, 144, 0, 1759244522,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244522), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386301925_a479eb7b704c59d507f8361a441478c6_rle_crop_3981095892_0.png', 0, 158, 167, 0, 1759244522,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244522), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386301925_a479eb7b704c59d507f8361a441478c6_rle_crop_3981095890_0.png', 0, 146, 231, 0, 1759244522,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244522), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386301925_a479eb7b704c59d507f8361a441478c6_rle_crop_3981095899_0.png', 0, 292, 188, 0, 1759244522,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244522), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386301882_1222513e42333942b0dfb98b088e45cd_rle_crop_3981095905_0.png', 0, 413, 469, 0, 1759244522,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244522), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386301877_629ff193e5587e28dbb01b1d4b49e62a_rle_crop_3981095910_0.png', 0, 214, 135, 0, 1759244522,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244522), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386301860_814c16b7b8fa744b39a1ad6a523f8d17_rle_crop_3981095917_0.png', 0, 218, 144, 0, 1759244522,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 17 photos in the portfolio 3736932 time of upload the photos Elapsed time : 5.479099988937378 we have finished the crop for the class : carton begin to crop the class : metal param for this class : {'min_score': 0.7} filtre for class : metal hashtag_id of this class : 492628673 we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! map_result returned by crop_photo_return_map_crop : length : 14 About to insert : list_path_to_insert length 14 new photo from crops ! About to upload 14 photos upload in portfolio : 3736932 init cache_photo without model_param we have 14 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1759244528_359586 INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244532), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302361_caa1d21076ce801265ffe1196d1b1d80_rle_crop_3981095787_0.png', 0, 85, 116, 0, 1759244532,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244532), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302361_caa1d21076ce801265ffe1196d1b1d80_rle_crop_3981095790_0.png', 0, 116, 173, 0, 1759244532,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244532), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302361_caa1d21076ce801265ffe1196d1b1d80_rle_crop_3981095785_0.png', 0, 161, 116, 0, 1759244532,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244532), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302361_caa1d21076ce801265ffe1196d1b1d80_rle_crop_3981095784_0.png', 0, 129, 141, 0, 1759244532,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244532), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302357_ce78121a78f3d76800b7c71d3ed11b3b_rle_crop_3981095799_0.png', 0, 167, 169, 0, 1759244532,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244532), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302302_e0d3c06db129da79f8ad80350c8f0577_rle_crop_3981095823_0.png', 0, 102, 78, 0, 1759244532,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244532), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302286_4ce84dcd8ab6d33803d5875471b522b9_rle_crop_3981095838_0.png', 0, 203, 187, 0, 1759244532,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244532), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302284_b3ec7232402b94d0d364bb11e2dffa46_rle_crop_3981095845_0.png', 0, 202, 156, 0, 1759244532,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244532), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302284_b3ec7232402b94d0d364bb11e2dffa46_rle_crop_3981095843_0.png', 0, 127, 119, 0, 1759244532,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244532), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302284_b3ec7232402b94d0d364bb11e2dffa46_rle_crop_3981095846_0.png', 0, 143, 190, 0, 1759244532,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244532), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302018_ccf36b9aba9c06d80ab85f52789a2795_rle_crop_3981095879_0.png', 0, 137, 140, 0, 1759244532,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244532), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302018_ccf36b9aba9c06d80ab85f52789a2795_rle_crop_3981095876_0.png', 0, 267, 224, 0, 1759244532,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244532), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386301925_a479eb7b704c59d507f8361a441478c6_rle_crop_3981095894_0.png', 0, 173, 193, 0, 1759244532,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244532), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386301925_a479eb7b704c59d507f8361a441478c6_rle_crop_3981095897_0.png', 0, 213, 154, 0, 1759244532,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 14 photos in the portfolio 3736932 time of upload the photos Elapsed time : 5.094716310501099 we have finished the crop for the class : metal begin to crop the class : pet_clair param for this class : {'min_score': 0.7} filtre for class : pet_clair hashtag_id of this class : 2107755846 we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! map_result returned by crop_photo_return_map_crop : length : 54 About to insert : list_path_to_insert length 54 new photo from crops ! About to upload 54 photos upload in portfolio : 3736932 init cache_photo without model_param we have 54 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1759244592_359586 INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302361_caa1d21076ce801265ffe1196d1b1d80_rle_crop_3981095791_0.png', 0, 2547, 1935, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302361_caa1d21076ce801265ffe1196d1b1d80_rle_crop_3981095778_0.png', 0, 861, 612, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302361_caa1d21076ce801265ffe1196d1b1d80_rle_crop_3981095789_0.png', 0, 566, 695, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302361_caa1d21076ce801265ffe1196d1b1d80_rle_crop_3981095781_0.png', 0, 363, 205, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302361_caa1d21076ce801265ffe1196d1b1d80_rle_crop_3981095779_0.png', 0, 405, 413, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302357_ce78121a78f3d76800b7c71d3ed11b3b_rle_crop_3981095798_0.png', 0, 266, 230, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302357_ce78121a78f3d76800b7c71d3ed11b3b_rle_crop_3981095796_0.png', 0, 439, 278, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302357_ce78121a78f3d76800b7c71d3ed11b3b_rle_crop_3981095797_0.png', 0, 110, 88, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302357_ce78121a78f3d76800b7c71d3ed11b3b_rle_crop_3981095794_0.png', 0, 235, 86, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302357_ce78121a78f3d76800b7c71d3ed11b3b_rle_crop_3981095792_0.png', 0, 352, 357, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302345_18ef46a11ab875d6338afbd6ab25fa4a_rle_crop_3981095809_0.png', 0, 380, 224, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302345_18ef46a11ab875d6338afbd6ab25fa4a_rle_crop_3981095802_0.png', 0, 327, 208, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302345_18ef46a11ab875d6338afbd6ab25fa4a_rle_crop_3981095810_0.png', 0, 522, 165, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302345_18ef46a11ab875d6338afbd6ab25fa4a_rle_crop_3981095805_0.png', 0, 414, 219, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302345_18ef46a11ab875d6338afbd6ab25fa4a_rle_crop_3981095804_0.png', 0, 500, 312, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302345_18ef46a11ab875d6338afbd6ab25fa4a_rle_crop_3981095806_0.png', 0, 415, 295, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302345_18ef46a11ab875d6338afbd6ab25fa4a_rle_crop_3981095807_0.png', 0, 203, 303, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302319_50da8176754b972256fdd310af4e25aa_rle_crop_3981095813_0.png', 0, 276, 172, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302319_50da8176754b972256fdd310af4e25aa_rle_crop_3981095815_0.png', 0, 488, 208, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302302_e0d3c06db129da79f8ad80350c8f0577_rle_crop_3981095820_0.png', 0, 454, 386, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302302_e0d3c06db129da79f8ad80350c8f0577_rle_crop_3981095819_0.png', 0, 235, 285, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302302_e0d3c06db129da79f8ad80350c8f0577_rle_crop_3981095824_0.png', 0, 647, 397, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302286_4ce84dcd8ab6d33803d5875471b522b9_rle_crop_3981095840_0.png', 0, 310, 340, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302286_4ce84dcd8ab6d33803d5875471b522b9_rle_crop_3981095835_0.png', 0, 482, 719, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302286_4ce84dcd8ab6d33803d5875471b522b9_rle_crop_3981095833_0.png', 0, 450, 320, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302286_4ce84dcd8ab6d33803d5875471b522b9_rle_crop_3981095839_0.png', 0, 245, 259, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302286_4ce84dcd8ab6d33803d5875471b522b9_rle_crop_3981095831_0.png', 0, 250, 610, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302286_4ce84dcd8ab6d33803d5875471b522b9_rle_crop_3981095836_0.png', 0, 225, 296, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302284_b3ec7232402b94d0d364bb11e2dffa46_rle_crop_3981095841_0.png', 0, 238, 390, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302079_07022de81d7c5fd5889a36c7d151c632_rle_crop_3981095855_0.png', 0, 292, 365, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302079_07022de81d7c5fd5889a36c7d151c632_rle_crop_3981095850_0.png', 0, 372, 390, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302050_6b7e9a2de9ba085cde9b70c45023d640_rle_crop_3981095859_0.png', 0, 1146, 765, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302018_ccf36b9aba9c06d80ab85f52789a2795_rle_crop_3981095874_0.png', 0, 344, 338, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302018_ccf36b9aba9c06d80ab85f52789a2795_rle_crop_3981095869_0.png', 0, 445, 481, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302018_ccf36b9aba9c06d80ab85f52789a2795_rle_crop_3981095872_0.png', 0, 502, 376, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302018_ccf36b9aba9c06d80ab85f52789a2795_rle_crop_3981095873_0.png', 0, 140, 130, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302018_ccf36b9aba9c06d80ab85f52789a2795_rle_crop_3981095870_0.png', 0, 162, 107, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386301983_b1ae4982d7372426325a6e09a54e1a65_rle_crop_3981095883_0.png', 0, 246, 293, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386301953_3d192aa38bce05f090a0633230dd4bdf_rle_crop_3981095885_0.png', 0, 237, 210, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386301953_3d192aa38bce05f090a0633230dd4bdf_rle_crop_3981095888_0.png', 0, 642, 508, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386301953_3d192aa38bce05f090a0633230dd4bdf_rle_crop_3981095887_0.png', 0, 328, 373, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386301925_a479eb7b704c59d507f8361a441478c6_rle_crop_3981095893_0.png', 0, 247, 199, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386301925_a479eb7b704c59d507f8361a441478c6_rle_crop_3981095898_0.png', 0, 240, 190, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386301882_1222513e42333942b0dfb98b088e45cd_rle_crop_3981095902_0.png', 0, 172, 252, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386301882_1222513e42333942b0dfb98b088e45cd_rle_crop_3981095903_0.png', 0, 195, 128, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386301877_629ff193e5587e28dbb01b1d4b49e62a_rle_crop_3981095914_0.png', 0, 2785, 1827, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386301877_629ff193e5587e28dbb01b1d4b49e62a_rle_crop_3981095912_0.png', 0, 224, 364, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386301877_629ff193e5587e28dbb01b1d4b49e62a_rle_crop_3981095909_0.png', 0, 151, 194, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386301877_629ff193e5587e28dbb01b1d4b49e62a_rle_crop_3981095906_0.png', 0, 666, 270, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386301877_629ff193e5587e28dbb01b1d4b49e62a_rle_crop_3981095908_0.png', 0, 271, 128, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386301877_629ff193e5587e28dbb01b1d4b49e62a_rle_crop_3981095913_0.png', 0, 545, 505, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386301860_814c16b7b8fa744b39a1ad6a523f8d17_rle_crop_3981095918_0.png', 0, 323, 247, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386301860_814c16b7b8fa744b39a1ad6a523f8d17_rle_crop_3981095919_0.png', 0, 403, 543, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244606), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386301860_814c16b7b8fa744b39a1ad6a523f8d17_rle_crop_3981095916_0.png', 0, 225, 95, 0, 1759244606,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 54 photos in the portfolio 3736932 time of upload the photos Elapsed time : 19.63597083091736 we have finished the crop for the class : pet_clair begin to crop the class : autre param for this class : {'min_score': 0.7} filtre for class : autre hashtag_id of this class : 494826614 we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! map_result returned by crop_photo_return_map_crop : length : 11 About to insert : list_path_to_insert length 11 new photo from crops ! About to upload 11 photos upload in portfolio : 3736932 init cache_photo without model_param we have 11 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1759244616_359586 INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244618), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302361_caa1d21076ce801265ffe1196d1b1d80_rle_crop_3981095788_0.png', 0, 91, 122, 0, 1759244618,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244618), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302284_b3ec7232402b94d0d364bb11e2dffa46_rle_crop_3981095842_0.png', 0, 176, 251, 0, 1759244618,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244618), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302284_b3ec7232402b94d0d364bb11e2dffa46_rle_crop_3981095847_0.png', 0, 156, 111, 0, 1759244618,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244618), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302284_b3ec7232402b94d0d364bb11e2dffa46_rle_crop_3981095849_0.png', 0, 223, 137, 0, 1759244618,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244618), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302284_b3ec7232402b94d0d364bb11e2dffa46_rle_crop_3981095848_0.png', 0, 158, 172, 0, 1759244618,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244618), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302284_b3ec7232402b94d0d364bb11e2dffa46_rle_crop_3981095844_0.png', 0, 121, 233, 0, 1759244618,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244618), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302050_6b7e9a2de9ba085cde9b70c45023d640_rle_crop_3981095864_0.png', 0, 325, 316, 0, 1759244618,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244618), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302018_ccf36b9aba9c06d80ab85f52789a2795_rle_crop_3981095875_0.png', 0, 178, 178, 0, 1759244618,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244618), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302018_ccf36b9aba9c06d80ab85f52789a2795_rle_crop_3981095871_0.png', 0, 118, 128, 0, 1759244618,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244618), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386301925_a479eb7b704c59d507f8361a441478c6_rle_crop_3981095895_0.png', 0, 208, 229, 0, 1759244618,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244618), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386301860_814c16b7b8fa744b39a1ad6a523f8d17_rle_crop_3981095915_0.png', 0, 286, 281, 0, 1759244618,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 11 photos in the portfolio 3736932 time of upload the photos Elapsed time : 3.9519717693328857 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 begin to crop the class : pet_fonce param for this class : {'min_score': 0.7} filtre for class : pet_fonce hashtag_id of this class : 2107755900 we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! map_result returned by crop_photo_return_map_crop : length : 3 About to insert : list_path_to_insert length 3 new photo from crops ! About to upload 3 photos upload in portfolio : 3736932 init cache_photo without model_param we have 3 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1759244624_359586 INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244624), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302286_4ce84dcd8ab6d33803d5875471b522b9_rle_crop_3981095832_0.png', 0, 231, 322, 0, 1759244624,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244624), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302079_07022de81d7c5fd5889a36c7d151c632_rle_crop_3981095856_0.png', 0, 183, 255, 0, 1759244624,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244624), 0.0, 0.0, 14, '', 0, 0, '1759244386_359586_1386302018_ccf36b9aba9c06d80ab85f52789a2795_rle_crop_3981095880_0.png', 0, 488, 749, 0, 1759244624,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 3 photos in the portfolio 3736932 time of upload the photos Elapsed time : 1.3713922500610352 we have finished the crop for the class : pet_fonce delete rles from all chi we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : crop_condition we use saveGeneral [1386302361, 1386302357, 1386302345, 1386302319, 1386302302, 1386302286, 1386302284, 1386302079, 1386302050, 1386302018, 1386301983, 1386301953, 1386301925, 1386301882, 1386301877, 1386301860] Looping around the photos to save general results len do output : 143 /1386982872Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982873Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982874Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982875Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982876Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982877Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982879Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982880Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982881Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982882Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982883Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982884Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982885Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982886Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982887Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982888Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982889Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982890Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982891Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982892Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982893Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982894Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982895Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982896Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982897Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982898Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982899Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982900Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982901Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982902Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982903Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982904Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982905Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982906Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982907Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982908Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982909Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982910Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982911Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982912Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982913Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982914Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982915Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982916Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982920Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982921Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982922Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982923Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982924Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982925Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982926Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982927Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982928Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982929Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982930Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982931Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982933Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982934Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982935Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982936Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982937Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982966Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982967Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982968Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982969Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982970Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982971Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982972Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982973Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982974Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982975Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982976Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982977Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982978Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386982979Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983406Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983407Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983408Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983409Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983410Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983411Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983412Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983413Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983414Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983416Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983417Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983418Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983419Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983420Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983421Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983422Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983423Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983424Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983425Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983427Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983428Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983429Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983430Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983431Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983432Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983433Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983434Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983435Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983437Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983438Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983439Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983440Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983441Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983442Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983443Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983444Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983445Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983446Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983447Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983448Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983449Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983450Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983451Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983452Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983453Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983454Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983455Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983456Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983457Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983458Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983459Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983460Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983461Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983463Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983469Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983470Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983471Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983472Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983474Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983475Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983476Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983477Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983478Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983479Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983480Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983483Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983484Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983485Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . before output type Here is an output not treated by saveGeneral : Here is an output not treated by saveGeneral : Here is an output not treated by saveGeneral : Managing all output in save final without adding information in the mtr_datou_result ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302361', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302357', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302345', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302319', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302302', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302286', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302284', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302079', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302050', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302018', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386301983', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386301953', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386301925', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386301882', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386301877', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386301860', None, None, None, None, None, '3784180') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 445 time used for this insertion : 0.05044865608215332 save_final save missing photos in datou_result : time spend for datou_step_exec : 143.46201515197754 time spend to save output : 0.05464744567871094 total time spend for step 2 : 143.51666259765625 step3:rle_unique_nms_with_priority Tue Sep 30 17:03:45 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array VR 22-3-18 : For now we do not clean correctly the datou structure Begin step rle-unique-nms batch 1 Loaded 143 chid ids of type : 3594 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++nb_obj : 14 nb_hashtags : 4 time to prepare the origin masks : 5.3923821449279785 time for calcul the mask position with numpy : 0.3226289749145508 nb_pixel_total : 3543304 time to create 1 rle with new method : 0.8456475734710693 time for calcul the mask position with numpy : 0.3331286907196045 nb_pixel_total : 3720620 time to create 1 rle with new method : 0.6463491916656494 time for calcul the mask position with numpy : 0.02476215362548828 nb_pixel_total : 14346 time to create 1 rle with old method : 0.01538705825805664 time for calcul the mask position with numpy : 0.02593708038330078 nb_pixel_total : 277654 time to create 1 rle with new method : 0.6157815456390381 time for calcul the mask position with numpy : 0.0257718563079834 nb_pixel_total : 8949 time to create 1 rle with old method : 0.010313272476196289 time for calcul the mask position with numpy : 0.02494215965270996 nb_pixel_total : 6965 time to create 1 rle with old method : 0.007573366165161133 time for calcul the mask position with numpy : 0.02416825294494629 nb_pixel_total : 82115 time to create 1 rle with old method : 0.08974432945251465 time for calcul the mask position with numpy : 0.03369927406311035 nb_pixel_total : 14122 time to create 1 rle with old method : 0.016036272048950195 time for calcul the mask position with numpy : 0.024414539337158203 nb_pixel_total : 14447 time to create 1 rle with old method : 0.016063451766967773 time for calcul the mask position with numpy : 0.024901628494262695 nb_pixel_total : 13783 time to create 1 rle with old method : 0.015458345413208008 time for calcul the mask position with numpy : 0.024071455001831055 nb_pixel_total : 10862 time to create 1 rle with old method : 0.012026309967041016 time for calcul the mask position with numpy : 0.025218486785888672 nb_pixel_total : 55612 time to create 1 rle with old method : 0.060875654220581055 time for calcul the mask position with numpy : 0.023858070373535156 nb_pixel_total : 21849 time to create 1 rle with old method : 0.023847103118896484 time for calcul the mask position with numpy : 0.02442479133605957 nb_pixel_total : 124089 time to create 1 rle with old method : 0.13706564903259277 time for calcul the mask position with numpy : 0.027093887329101562 nb_pixel_total : 385683 time to create 1 rle with new method : 0.763404130935669 create new chi : 4.3748085498809814 time to delete rle : 0.07376527786254883 batch 1 Loaded 29 chid ids of type : 3594 ++++++++++++++++++++Number RLEs to save : 12842 TO DO : save crop sub photo not yet done ! save time : 1.4333338737487793 nb_obj : 9 nb_hashtags : 4 time to prepare the origin masks : 4.225660085678101 time for calcul the mask position with numpy : 0.966400146484375 nb_pixel_total : 7753224 time to create 1 rle with new method : 1.044543743133545 time for calcul the mask position with numpy : 0.02587580680847168 nb_pixel_total : 33733 time to create 1 rle with old method : 0.038004398345947266 time for calcul the mask position with numpy : 0.024799346923828125 nb_pixel_total : 18086 time to create 1 rle with old method : 0.019945144653320312 time for calcul the mask position with numpy : 0.024895668029785156 nb_pixel_total : 47513 time to create 1 rle with old method : 0.05307722091674805 time for calcul the mask position with numpy : 0.026981592178344727 nb_pixel_total : 7890 time to create 1 rle with old method : 0.008527278900146484 time for calcul the mask position with numpy : 0.025590181350708008 nb_pixel_total : 91251 time to create 1 rle with old method : 0.09885478019714355 time for calcul the mask position with numpy : 0.023874759674072266 nb_pixel_total : 33582 time to create 1 rle with old method : 0.03656435012817383 time for calcul the mask position with numpy : 0.02391672134399414 nb_pixel_total : 16025 time to create 1 rle with old method : 0.0176393985748291 time for calcul the mask position with numpy : 0.026126384735107422 nb_pixel_total : 198864 time to create 1 rle with new method : 0.5986392498016357 time for calcul the mask position with numpy : 0.027546167373657227 nb_pixel_total : 94232 time to create 1 rle with old method : 0.12738704681396484 create new chi : 3.3090550899505615 time to delete rle : 0.001277923583984375 batch 1 Loaded 19 chid ids of type : 3594 +++++++++++Number RLEs to save : 6986 TO DO : save crop sub photo not yet done ! save time : 0.8649594783782959 nb_obj : 10 nb_hashtags : 3 time to prepare the origin masks : 4.79314661026001 time for calcul the mask position with numpy : 0.5781574249267578 nb_pixel_total : 7662481 time to create 1 rle with new method : 0.6974928379058838 time for calcul the mask position with numpy : 0.024102449417114258 nb_pixel_total : 54349 time to create 1 rle with old method : 0.058246612548828125 time for calcul the mask position with numpy : 0.02551889419555664 nb_pixel_total : 65742 time to create 1 rle with old method : 0.07113504409790039 time for calcul the mask position with numpy : 0.0365755558013916 nb_pixel_total : 51560 time to create 1 rle with old method : 0.05573844909667969 time for calcul the mask position with numpy : 0.03245663642883301 nb_pixel_total : 50898 time to create 1 rle with old method : 0.05423331260681152 time for calcul the mask position with numpy : 0.02471613883972168 nb_pixel_total : 108719 time to create 1 rle with old method : 0.11607670783996582 time for calcul the mask position with numpy : 0.024018526077270508 nb_pixel_total : 64751 time to create 1 rle with old method : 0.06788206100463867 time for calcul the mask position with numpy : 0.024814605712890625 nb_pixel_total : 116110 time to create 1 rle with old method : 0.12365961074829102 time for calcul the mask position with numpy : 0.025116682052612305 nb_pixel_total : 41322 time to create 1 rle with old method : 0.04458451271057129 time for calcul the mask position with numpy : 0.0241851806640625 nb_pixel_total : 48387 time to create 1 rle with old method : 0.05074286460876465 time for calcul the mask position with numpy : 0.023437023162841797 nb_pixel_total : 30081 time to create 1 rle with old method : 0.031987667083740234 create new chi : 2.2571585178375244 time to delete rle : 0.001111745834350586 batch 1 Loaded 21 chid ids of type : 3594 +++++++++++Number RLEs to save : 7636 TO DO : save crop sub photo not yet done ! save time : 0.9670965671539307 nb_obj : 6 nb_hashtags : 2 time to prepare the origin masks : 2.2120749950408936 time for calcul the mask position with numpy : 0.6559417247772217 nb_pixel_total : 7658642 time to create 1 rle with new method : 0.6262781620025635 time for calcul the mask position with numpy : 0.025578737258911133 nb_pixel_total : 149890 time to create 1 rle with old method : 0.16527175903320312 time for calcul the mask position with numpy : 0.02470707893371582 nb_pixel_total : 80478 time to create 1 rle with old method : 0.08720135688781738 time for calcul the mask position with numpy : 0.025308847427368164 nb_pixel_total : 52854 time to create 1 rle with old method : 0.05742335319519043 time for calcul the mask position with numpy : 0.02662038803100586 nb_pixel_total : 42874 time to create 1 rle with old method : 0.04624676704406738 time for calcul the mask position with numpy : 0.025786161422729492 nb_pixel_total : 278173 time to create 1 rle with new method : 0.8017504215240479 time for calcul the mask position with numpy : 0.025240421295166016 nb_pixel_total : 31489 time to create 1 rle with old method : 0.03447723388671875 create new chi : 2.697096824645996 time to delete rle : 0.0008881092071533203 batch 1 Loaded 13 chid ids of type : 3594 +++++++Number RLEs to save : 6182 TO DO : save crop sub photo not yet done ! save time : 0.7943847179412842 nb_obj : 10 nb_hashtags : 4 time to prepare the origin masks : 4.288910388946533 time for calcul the mask position with numpy : 0.6030635833740234 nb_pixel_total : 7463607 time to create 1 rle with new method : 0.6142418384552002 time for calcul the mask position with numpy : 0.02389669418334961 nb_pixel_total : 59913 time to create 1 rle with old method : 0.09099125862121582 time for calcul the mask position with numpy : 0.028202295303344727 nb_pixel_total : 25734 time to create 1 rle with old method : 0.0284731388092041 time for calcul the mask position with numpy : 0.02636551856994629 nb_pixel_total : 195568 time to create 1 rle with new method : 1.2363510131835938 time for calcul the mask position with numpy : 0.027020692825317383 nb_pixel_total : 5814 time to create 1 rle with old method : 0.006646633148193359 time for calcul the mask position with numpy : 0.028305768966674805 nb_pixel_total : 38287 time to create 1 rle with old method : 0.04598116874694824 time for calcul the mask position with numpy : 0.0294189453125 nb_pixel_total : 71361 time to create 1 rle with old method : 0.08146095275878906 time for calcul the mask position with numpy : 0.027766704559326172 nb_pixel_total : 115253 time to create 1 rle with old method : 0.126922607421875 time for calcul the mask position with numpy : 0.026243925094604492 nb_pixel_total : 43982 time to create 1 rle with old method : 0.050872087478637695 time for calcul the mask position with numpy : 0.025595664978027344 nb_pixel_total : 27751 time to create 1 rle with old method : 0.0338132381439209 time for calcul the mask position with numpy : 0.028815269470214844 nb_pixel_total : 247130 time to create 1 rle with new method : 0.7060625553131104 create new chi : 4.00014853477478 time to delete rle : 0.0014846324920654297 batch 1 Loaded 21 chid ids of type : 3594 +++++++++++++++Number RLEs to save : 8676 TO DO : save crop sub photo not yet done ! save time : 1.0615942478179932 nb_obj : 14 nb_hashtags : 5 time to prepare the origin masks : 6.055694818496704 time for calcul the mask position with numpy : 0.3948354721069336 nb_pixel_total : 6947582 time to create 1 rle with new method : 0.7793917655944824 time for calcul the mask position with numpy : 0.024324893951416016 nb_pixel_total : 75364 time to create 1 rle with old method : 0.08375859260559082 time for calcul the mask position with numpy : 0.025392770767211914 nb_pixel_total : 49907 time to create 1 rle with old method : 0.05607032775878906 time for calcul the mask position with numpy : 0.030314207077026367 nb_pixel_total : 30185 time to create 1 rle with old method : 0.03412580490112305 time for calcul the mask position with numpy : 0.02847743034362793 nb_pixel_total : 193491 time to create 1 rle with new method : 0.782686710357666 time for calcul the mask position with numpy : 0.0245053768157959 nb_pixel_total : 53020 time to create 1 rle with old method : 0.05912303924560547 time for calcul the mask position with numpy : 0.025419950485229492 nb_pixel_total : 251421 time to create 1 rle with new method : 0.5224857330322266 time for calcul the mask position with numpy : 0.02442145347595215 nb_pixel_total : 40045 time to create 1 rle with old method : 0.04323530197143555 time for calcul the mask position with numpy : 0.0257720947265625 nb_pixel_total : 104968 time to create 1 rle with old method : 0.11562728881835938 time for calcul the mask position with numpy : 0.024936676025390625 nb_pixel_total : 57910 time to create 1 rle with old method : 0.06325602531433105 time for calcul the mask position with numpy : 0.025538921356201172 nb_pixel_total : 122818 time to create 1 rle with old method : 0.13262581825256348 time for calcul the mask position with numpy : 0.024402618408203125 nb_pixel_total : 184852 time to create 1 rle with new method : 0.7270066738128662 time for calcul the mask position with numpy : 0.025228023529052734 nb_pixel_total : 11458 time to create 1 rle with old method : 0.012715816497802734 time for calcul the mask position with numpy : 0.025462627410888672 nb_pixel_total : 139036 time to create 1 rle with old method : 0.151519775390625 time for calcul the mask position with numpy : 0.02503657341003418 nb_pixel_total : 32343 time to create 1 rle with old method : 0.035854339599609375 create new chi : 4.474909067153931 time to delete rle : 0.0019762516021728516 batch 1 Loaded 29 chid ids of type : 3594 +++++++++++++++++++++Number RLEs to save : 13134 TO DO : save crop sub photo not yet done ! save time : 1.458583116531372 nb_obj : 9 nb_hashtags : 3 time to prepare the origin masks : 3.838409662246704 time for calcul the mask position with numpy : 0.706118106842041 nb_pixel_total : 8067969 time to create 1 rle with new method : 0.80812668800354 time for calcul the mask position with numpy : 0.041253089904785156 nb_pixel_total : 22359 time to create 1 rle with old method : 0.02480459213256836 time for calcul the mask position with numpy : 0.04562830924987793 nb_pixel_total : 20631 time to create 1 rle with old method : 0.022661685943603516 time for calcul the mask position with numpy : 0.04059767723083496 nb_pixel_total : 15510 time to create 1 rle with old method : 0.017578601837158203 time for calcul the mask position with numpy : 0.04092693328857422 nb_pixel_total : 18950 time to create 1 rle with old method : 0.020841121673583984 time for calcul the mask position with numpy : 0.03980541229248047 nb_pixel_total : 23428 time to create 1 rle with old method : 0.025606632232666016 time for calcul the mask position with numpy : 0.039266109466552734 nb_pixel_total : 22769 time to create 1 rle with old method : 0.02514171600341797 time for calcul the mask position with numpy : 0.03554654121398926 nb_pixel_total : 12259 time to create 1 rle with old method : 0.15959739685058594 time for calcul the mask position with numpy : 0.028360843658447266 nb_pixel_total : 29603 time to create 1 rle with old method : 0.032834768295288086 time for calcul the mask position with numpy : 0.02831888198852539 nb_pixel_total : 60922 time to create 1 rle with old method : 0.07063055038452148 create new chi : 2.2985472679138184 time to delete rle : 0.0009822845458984375 batch 1 Loaded 19 chid ids of type : 3594 +++++++++Number RLEs to save : 5830 TO DO : save crop sub photo not yet done ! save time : 0.7455325126647949 nb_obj : 7 nb_hashtags : 4 time to prepare the origin masks : 3.4143974781036377 time for calcul the mask position with numpy : 0.6171302795410156 nb_pixel_total : 7819023 time to create 1 rle with new method : 0.8219025135040283 time for calcul the mask position with numpy : 0.023073673248291016 nb_pixel_total : 27669 time to create 1 rle with old method : 0.02911067008972168 time for calcul the mask position with numpy : 0.023364543914794922 nb_pixel_total : 89833 time to create 1 rle with old method : 0.09464025497436523 time for calcul the mask position with numpy : 0.02460193634033203 nb_pixel_total : 28415 time to create 1 rle with old method : 0.031302452087402344 time for calcul the mask position with numpy : 0.025539159774780273 nb_pixel_total : 193431 time to create 1 rle with new method : 0.5690770149230957 time for calcul the mask position with numpy : 0.024901390075683594 nb_pixel_total : 14295 time to create 1 rle with old method : 0.01545262336730957 time for calcul the mask position with numpy : 0.02434682846069336 nb_pixel_total : 27448 time to create 1 rle with old method : 0.0299227237701416 time for calcul the mask position with numpy : 0.029587268829345703 nb_pixel_total : 94286 time to create 1 rle with old method : 0.09933233261108398 create new chi : 2.550558090209961 time to delete rle : 0.0012862682342529297 batch 1 Loaded 15 chid ids of type : 3594 ++++++++++++++Number RLEs to save : 7176 TO DO : save crop sub photo not yet done ! save time : 0.9534094333648682 nb_obj : 11 nb_hashtags : 4 time to prepare the origin masks : 4.706707000732422 time for calcul the mask position with numpy : 0.5713019371032715 nb_pixel_total : 7109254 time to create 1 rle with new method : 0.842475175857544 time for calcul the mask position with numpy : 0.024016857147216797 nb_pixel_total : 27095 time to create 1 rle with old method : 0.029801607131958008 time for calcul the mask position with numpy : 0.027158260345458984 nb_pixel_total : 82728 time to create 1 rle with old method : 0.08877372741699219 time for calcul the mask position with numpy : 0.024944543838500977 nb_pixel_total : 57655 time to create 1 rle with old method : 0.06275296211242676 time for calcul the mask position with numpy : 0.025450944900512695 nb_pixel_total : 81128 time to create 1 rle with old method : 0.08732223510742188 time for calcul the mask position with numpy : 0.02521204948425293 nb_pixel_total : 29241 time to create 1 rle with old method : 0.03205108642578125 time for calcul the mask position with numpy : 0.025803089141845703 nb_pixel_total : 8094 time to create 1 rle with old method : 0.00892186164855957 time for calcul the mask position with numpy : 0.025069236755371094 nb_pixel_total : 10415 time to create 1 rle with old method : 0.011528968811035156 time for calcul the mask position with numpy : 0.024913787841796875 nb_pixel_total : 102427 time to create 1 rle with old method : 0.11051440238952637 time for calcul the mask position with numpy : 0.028157472610473633 nb_pixel_total : 692869 time to create 1 rle with new method : 0.7068490982055664 time for calcul the mask position with numpy : 0.02669072151184082 nb_pixel_total : 7267 time to create 1 rle with old method : 0.008157014846801758 time for calcul the mask position with numpy : 0.026949644088745117 nb_pixel_total : 86227 time to create 1 rle with old method : 0.09294939041137695 create new chi : 3.007723331451416 time to delete rle : 0.0017058849334716797 batch 1 Loaded 23 chid ids of type : 3594 ++++++++++++Number RLEs to save : 9968 TO DO : save crop sub photo not yet done ! save time : 1.1669158935546875 nb_obj : 13 nb_hashtags : 6 time to prepare the origin masks : 6.433282136917114 time for calcul the mask position with numpy : 0.6338982582092285 nb_pixel_total : 7536840 time to create 1 rle with new method : 0.8874948024749756 time for calcul the mask position with numpy : 0.04369711875915527 nb_pixel_total : 217960 time to create 1 rle with new method : 0.6920452117919922 time for calcul the mask position with numpy : 0.0421144962310791 nb_pixel_total : 5017 time to create 1 rle with old method : 0.005624055862426758 time for calcul the mask position with numpy : 0.043413639068603516 nb_pixel_total : 33497 time to create 1 rle with old method : 0.03729057312011719 time for calcul the mask position with numpy : 0.04084062576293945 nb_pixel_total : 16592 time to create 1 rle with old method : 0.01829218864440918 time for calcul the mask position with numpy : 0.04078936576843262 nb_pixel_total : 44180 time to create 1 rle with old method : 0.04943490028381348 time for calcul the mask position with numpy : 0.04178428649902344 nb_pixel_total : 22411 time to create 1 rle with old method : 0.02513909339904785 time for calcul the mask position with numpy : 0.042826175689697266 nb_pixel_total : 95581 time to create 1 rle with old method : 0.11287140846252441 time for calcul the mask position with numpy : 0.04684877395629883 nb_pixel_total : 14656 time to create 1 rle with old method : 0.016316652297973633 time for calcul the mask position with numpy : 0.04114890098571777 nb_pixel_total : 112432 time to create 1 rle with old method : 0.12149238586425781 time for calcul the mask position with numpy : 0.03949332237243652 nb_pixel_total : 12784 time to create 1 rle with old method : 0.014116287231445312 time for calcul the mask position with numpy : 0.04126620292663574 nb_pixel_total : 12935 time to create 1 rle with old method : 0.014095783233642578 time for calcul the mask position with numpy : 0.04037666320800781 nb_pixel_total : 121287 time to create 1 rle with old method : 0.13207316398620605 time for calcul the mask position with numpy : 0.03869271278381348 nb_pixel_total : 48228 time to create 1 rle with old method : 0.05459856986999512 create new chi : 3.4349920749664307 time to delete rle : 0.0027191638946533203 batch 1 Loaded 27 chid ids of type : 3594 ++++++++++++++++++Number RLEs to save : 9511 TO DO : save crop sub photo not yet done ! save time : 1.1387906074523926 nb_obj : 3 nb_hashtags : 2 time to prepare the origin masks : 1.9546642303466797 time for calcul the mask position with numpy : 0.8083903789520264 nb_pixel_total : 8094872 time to create 1 rle with new method : 0.9604198932647705 time for calcul the mask position with numpy : 0.04424619674682617 nb_pixel_total : 59407 time to create 1 rle with old method : 0.06635355949401855 time for calcul the mask position with numpy : 0.02910304069519043 nb_pixel_total : 74260 time to create 1 rle with old method : 0.09075736999511719 time for calcul the mask position with numpy : 0.031067848205566406 nb_pixel_total : 65861 time to create 1 rle with old method : 0.07475900650024414 create new chi : 2.1525633335113525 time to delete rle : 0.0007805824279785156 batch 1 Loaded 7 chid ids of type : 3594 ++++++Number RLEs to save : 4520 TO DO : save crop sub photo not yet done ! save time : 0.6367127895355225 nb_obj : 5 nb_hashtags : 2 time to prepare the origin masks : 2.272230386734009 time for calcul the mask position with numpy : 0.4184849262237549 nb_pixel_total : 7847925 time to create 1 rle with new method : 1.0755157470703125 time for calcul the mask position with numpy : 0.04572892189025879 nb_pixel_total : 227146 time to create 1 rle with new method : 0.8066432476043701 time for calcul the mask position with numpy : 0.042185306549072266 nb_pixel_total : 51330 time to create 1 rle with old method : 0.05684828758239746 time for calcul the mask position with numpy : 0.03608059883117676 nb_pixel_total : 73648 time to create 1 rle with old method : 0.0820915699005127 time for calcul the mask position with numpy : 0.0302731990814209 nb_pixel_total : 40610 time to create 1 rle with old method : 0.04374384880065918 time for calcul the mask position with numpy : 0.04118680953979492 nb_pixel_total : 53741 time to create 1 rle with old method : 0.06240391731262207 create new chi : 2.8216254711151123 time to delete rle : 0.0012650489807128906 batch 1 Loaded 11 chid ids of type : 3594 +++++++++Number RLEs to save : 5804 TO DO : save crop sub photo not yet done ! save time : 0.7483537197113037 nb_obj : 11 nb_hashtags : 5 time to prepare the origin masks : 5.767414808273315 time for calcul the mask position with numpy : 0.6395859718322754 nb_pixel_total : 7893710 time to create 1 rle with new method : 1.1539537906646729 time for calcul the mask position with numpy : 0.04341697692871094 nb_pixel_total : 38935 time to create 1 rle with old method : 0.04328107833862305 time for calcul the mask position with numpy : 0.04108428955078125 nb_pixel_total : 25730 time to create 1 rle with old method : 0.028741836547851562 time for calcul the mask position with numpy : 0.04116201400756836 nb_pixel_total : 26003 time to create 1 rle with old method : 0.028996944427490234 time for calcul the mask position with numpy : 0.040604591369628906 nb_pixel_total : 33173 time to create 1 rle with old method : 0.03704333305358887 time for calcul the mask position with numpy : 0.03982186317443848 nb_pixel_total : 34213 time to create 1 rle with old method : 0.03823280334472656 time for calcul the mask position with numpy : 0.025272846221923828 nb_pixel_total : 26307 time to create 1 rle with old method : 0.0294036865234375 time for calcul the mask position with numpy : 0.025416135787963867 nb_pixel_total : 28975 time to create 1 rle with old method : 0.03197288513183594 time for calcul the mask position with numpy : 0.025361061096191406 nb_pixel_total : 20304 time to create 1 rle with old method : 0.0245816707611084 time for calcul the mask position with numpy : 0.025216102600097656 nb_pixel_total : 42159 time to create 1 rle with old method : 0.04708600044250488 time for calcul the mask position with numpy : 0.027575016021728516 nb_pixel_total : 20845 time to create 1 rle with old method : 0.02546405792236328 time for calcul the mask position with numpy : 0.028450489044189453 nb_pixel_total : 104046 time to create 1 rle with old method : 0.11441159248352051 create new chi : 2.6528308391571045 time to delete rle : 0.0012509822845458984 batch 1 Loaded 23 chid ids of type : 3594 +++++++++++Number RLEs to save : 7144 TO DO : save crop sub photo not yet done ! save time : 0.9224574565887451 nb_obj : 6 nb_hashtags : 3 time to prepare the origin masks : 3.4053914546966553 time for calcul the mask position with numpy : 0.49944138526916504 nb_pixel_total : 7784886 time to create 1 rle with new method : 0.8796403408050537 time for calcul the mask position with numpy : 0.03605914115905762 nb_pixel_total : 154033 time to create 1 rle with new method : 0.7243223190307617 time for calcul the mask position with numpy : 0.024778127670288086 nb_pixel_total : 99684 time to create 1 rle with old method : 0.10833191871643066 time for calcul the mask position with numpy : 0.024240970611572266 nb_pixel_total : 18029 time to create 1 rle with old method : 0.022496461868286133 time for calcul the mask position with numpy : 0.02725672721862793 nb_pixel_total : 33309 time to create 1 rle with old method : 0.03562641143798828 time for calcul the mask position with numpy : 0.0296328067779541 nb_pixel_total : 36636 time to create 1 rle with old method : 0.05019497871398926 time for calcul the mask position with numpy : 0.033179283142089844 nb_pixel_total : 167823 time to create 1 rle with new method : 0.7500367164611816 create new chi : 3.340122699737549 time to delete rle : 0.0016314983367919922 batch 1 Loaded 13 chid ids of type : 3594 ++++++Number RLEs to save : 6016 TO DO : save crop sub photo not yet done ! save time : 0.8000972270965576 nb_obj : 9 nb_hashtags : 3 time to prepare the origin masks : 3.699876070022583 time for calcul the mask position with numpy : 0.400313138961792 nb_pixel_total : 3616006 time to create 1 rle with new method : 0.8989794254302979 time for calcul the mask position with numpy : 0.19743013381958008 nb_pixel_total : 4140524 time to create 1 rle with new method : 1.3267056941986084 time for calcul the mask position with numpy : 0.027367591857910156 nb_pixel_total : 218889 time to create 1 rle with new method : 0.9114363193511963 time for calcul the mask position with numpy : 0.024083375930786133 nb_pixel_total : 66164 time to create 1 rle with old method : 0.06951117515563965 time for calcul the mask position with numpy : 0.02561640739440918 nb_pixel_total : 27517 time to create 1 rle with old method : 0.029677867889404297 time for calcul the mask position with numpy : 0.025153636932373047 nb_pixel_total : 22517 time to create 1 rle with old method : 0.024354219436645508 time for calcul the mask position with numpy : 0.02557659149169922 nb_pixel_total : 21549 time to create 1 rle with old method : 0.02292633056640625 time for calcul the mask position with numpy : 0.024418115615844727 nb_pixel_total : 25641 time to create 1 rle with old method : 0.02795886993408203 time for calcul the mask position with numpy : 0.025153160095214844 nb_pixel_total : 14939 time to create 1 rle with old method : 0.015706300735473633 time for calcul the mask position with numpy : 0.026135683059692383 nb_pixel_total : 140654 time to create 1 rle with old method : 0.1517479419708252 create new chi : 4.377427577972412 time to delete rle : 0.0018706321716308594 batch 1 Loaded 19 chid ids of type : 3594 ++++++++++++Number RLEs to save : 10560 TO DO : save crop sub photo not yet done ! save time : 1.2678570747375488 nb_obj : 6 nb_hashtags : 4 time to prepare the origin masks : 4.757150411605835 time for calcul the mask position with numpy : 0.6892001628875732 nb_pixel_total : 7954634 time to create 1 rle with new method : 0.5138859748840332 time for calcul the mask position with numpy : 0.027901887893676758 nb_pixel_total : 42866 time to create 1 rle with old method : 0.048197031021118164 time for calcul the mask position with numpy : 0.027158737182617188 nb_pixel_total : 137351 time to create 1 rle with old method : 0.15074682235717773 time for calcul the mask position with numpy : 0.027614116668701172 nb_pixel_total : 64821 time to create 1 rle with old method : 0.07872962951660156 time for calcul the mask position with numpy : 0.027786731719970703 nb_pixel_total : 23887 time to create 1 rle with old method : 0.038137197494506836 time for calcul the mask position with numpy : 0.025765180587768555 nb_pixel_total : 16261 time to create 1 rle with old method : 0.01833200454711914 time for calcul the mask position with numpy : 0.025650978088378906 nb_pixel_total : 54580 time to create 1 rle with old method : 0.05982041358947754 create new chi : 1.805518388748169 time to delete rle : 0.0008282661437988281 batch 1 Loaded 13 chid ids of type : 3594 ++++++Number RLEs to save : 5200 TO DO : save crop sub photo not yet done ! save time : 0.7075409889221191 map_output_result : {1386302361: (0.0, 'Should be the crop_list due to order', 0), 1386302357: (0.0, 'Should be the crop_list due to order', 0), 1386302345: (0.0, 'Should be the crop_list due to order', 0), 1386302319: (0.0, 'Should be the crop_list due to order', 0), 1386302302: (0.0, 'Should be the crop_list due to order', 0), 1386302286: (0.0, 'Should be the crop_list due to order', 0), 1386302284: (0.0, 'Should be the crop_list due to order', 0), 1386302079: (0.0, 'Should be the crop_list due to order', 0), 1386302050: (0.0, 'Should be the crop_list due to order', 0), 1386302018: (0.0, 'Should be the crop_list due to order', 0), 1386301983: (0.0, 'Should be the crop_list due to order', 0), 1386301953: (0.0, 'Should be the crop_list due to order', 0), 1386301925: (0.0, 'Should be the crop_list due to order', 0), 1386301882: (0.0, 'Should be the crop_list due to order', 0), 1386301877: (0.0, 'Should be the crop_list due to order', 0), 1386301860: (0.0, 'Should be the crop_list due to order', 0)} End step rle-unique-nms Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : rle_unique_nms_with_priority we use saveGeneral [1386302361, 1386302357, 1386302345, 1386302319, 1386302302, 1386302286, 1386302284, 1386302079, 1386302050, 1386302018, 1386301983, 1386301953, 1386301925, 1386301882, 1386301877, 1386301860] Looping around the photos to save general results len do output : 16 /1386302361.Didn't retrieve data . /1386302357.Didn't retrieve data . /1386302345.Didn't retrieve data . /1386302319.Didn't retrieve data . /1386302302.Didn't retrieve data . /1386302286.Didn't retrieve data . /1386302284.Didn't retrieve data . /1386302079.Didn't retrieve data . /1386302050.Didn't retrieve data . /1386302018.Didn't retrieve data . /1386301983.Didn't retrieve data . /1386301953.Didn't retrieve data . /1386301925.Didn't retrieve data . /1386301882.Didn't retrieve data . /1386301877.Didn't retrieve data . /1386301860.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, '3784180') ('3318', '27268302', '1386302361', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302357', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302345', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302319', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302302', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302286', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302284', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302079', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302050', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302018', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386301983', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386301953', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386301925', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386301882', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386301877', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386301860', None, None, None, None, None, '3784180') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 48 time used for this insertion : 0.042490243911743164 save_final save missing photos in datou_result : time spend for datou_step_exec : 134.90200448036194 time spend to save output : 0.043647050857543945 total time spend for step 3 : 134.94565153121948 step4:ventilate_hashtags_in_portfolio Tue Sep 30 17:06:00 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed 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 : 27268302 get user id for portfolio 27268302 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`=27268302 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('flou','papier','carton','environnement','pet_clair','pet_fonce','autre','mal_croppe','background','pehd','metal')) AND mptpi.`min_score`=0.5 To do To do SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=27268302 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('flou','papier','carton','environnement','pet_clair','pet_fonce','autre','mal_croppe','background','pehd','metal')) AND mptpi.`min_score`=0.5 To do Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") To do ! Use context local managing function ! SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=27268302 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('flou','papier','carton','environnement','pet_clair','pet_fonce','autre','mal_croppe','background','pehd','metal')) AND mptpi.`min_score`=0.5 To do lien utilise dans velours : https://marlene.fotonower.com/velours/27356995,27356996,27356997,27356998,27356999,27357000,27357001,27357002,27357003,27357004,27357005?tags=flou,papier,carton,environnement,pet_clair,pet_fonce,autre,mal_croppe,background,pehd,metal Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : ventilate_hashtags_in_portfolio we use saveGeneral [1386302361, 1386302357, 1386302345, 1386302319, 1386302302, 1386302286, 1386302284, 1386302079, 1386302050, 1386302018, 1386301983, 1386301953, 1386301925, 1386301882, 1386301877, 1386301860] Looping around the photos to save general results len do output : 1 /27268302. 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, '3784180') ('3318', '27268302', '1386302361', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302357', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302345', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302319', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302302', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302286', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302284', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302079', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302050', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302018', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386301983', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386301953', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386301925', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386301882', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386301877', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386301860', None, None, None, None, None, '3784180') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 17 time used for this insertion : 0.03745436668395996 save_final save missing photos in datou_result : time spend for datou_step_exec : 5.6988866329193115 time spend to save output : 0.03803706169128418 total time spend for step 4 : 5.736923694610596 step5:final Tue Sep 30 17:06:05 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 : {1386302361: ('0.13530545458381554',), 1386302357: ('0.13530545458381554',), 1386302345: ('0.13530545458381554',), 1386302319: ('0.13530545458381554',), 1386302302: ('0.13530545458381554',), 1386302286: ('0.13530545458381554',), 1386302284: ('0.13530545458381554',), 1386302079: ('0.13530545458381554',), 1386302050: ('0.13530545458381554',), 1386302018: ('0.13530545458381554',), 1386301983: ('0.13530545458381554',), 1386301953: ('0.13530545458381554',), 1386301925: ('0.13530545458381554',), 1386301882: ('0.13530545458381554',), 1386301877: ('0.13530545458381554',), 1386301860: ('0.13530545458381554',)} new output for save of step final : {1386302361: ('0.13530545458381554',), 1386302357: ('0.13530545458381554',), 1386302345: ('0.13530545458381554',), 1386302319: ('0.13530545458381554',), 1386302302: ('0.13530545458381554',), 1386302286: ('0.13530545458381554',), 1386302284: ('0.13530545458381554',), 1386302079: ('0.13530545458381554',), 1386302050: ('0.13530545458381554',), 1386302018: ('0.13530545458381554',), 1386301983: ('0.13530545458381554',), 1386301953: ('0.13530545458381554',), 1386301925: ('0.13530545458381554',), 1386301882: ('0.13530545458381554',), 1386301877: ('0.13530545458381554',), 1386301860: ('0.13530545458381554',)} [1386302361, 1386302357, 1386302345, 1386302319, 1386302302, 1386302286, 1386302284, 1386302079, 1386302050, 1386302018, 1386301983, 1386301953, 1386301925, 1386301882, 1386301877, 1386301860] Looping around the photos to save general results len do output : 16 /1386302361.Didn't retrieve data . /1386302357.Didn't retrieve data . /1386302345.Didn't retrieve data . /1386302319.Didn't retrieve data . /1386302302.Didn't retrieve data . /1386302286.Didn't retrieve data . /1386302284.Didn't retrieve data . /1386302079.Didn't retrieve data . /1386302050.Didn't retrieve data . /1386302018.Didn't retrieve data . /1386301983.Didn't retrieve data . /1386301953.Didn't retrieve data . /1386301925.Didn't retrieve data . /1386301882.Didn't retrieve data . /1386301877.Didn't retrieve data . /1386301860.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, '3784180') ('3318', '27268302', '1386302361', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302357', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302345', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302319', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302302', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302286', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302284', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302079', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302050', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302018', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386301983', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386301953', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386301925', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386301882', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386301877', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386301860', None, None, None, None, None, '3784180') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 48 time used for this insertion : 0.03679943084716797 save_final save missing photos in datou_result : time spend for datou_step_exec : 0.3759462833404541 time spend to save output : 0.03750491142272949 total time spend for step 5 : 0.4134511947631836 step6:blur_detection Tue Sep 30 17:06:06 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/1759244386_359586_1386302361_caa1d21076ce801265ffe1196d1b1d80.jpg resize: (2160, 3840) 1386302361 -5.788193087064078 treat image : temp/1759244386_359586_1386302357_ce78121a78f3d76800b7c71d3ed11b3b.jpg resize: (2160, 3840) 1386302357 -6.556976304811067 treat image : temp/1759244386_359586_1386302345_18ef46a11ab875d6338afbd6ab25fa4a.jpg resize: (2160, 3840) 1386302345 -7.0153097181104584 treat image : temp/1759244386_359586_1386302319_50da8176754b972256fdd310af4e25aa.jpg resize: (2160, 3840) 1386302319 -7.232537838607711 treat image : temp/1759244386_359586_1386302302_e0d3c06db129da79f8ad80350c8f0577.jpg resize: (2160, 3840) 1386302302 -7.155046829820226 treat image : temp/1759244386_359586_1386302286_4ce84dcd8ab6d33803d5875471b522b9.jpg resize: (2160, 3840) 1386302286 -6.938881854184758 treat image : temp/1759244386_359586_1386302284_b3ec7232402b94d0d364bb11e2dffa46.jpg resize: (2160, 3840) 1386302284 -7.067196778924721 treat image : temp/1759244386_359586_1386302079_07022de81d7c5fd5889a36c7d151c632.jpg resize: (2160, 3840) 1386302079 -6.95983035955159 treat image : temp/1759244386_359586_1386302050_6b7e9a2de9ba085cde9b70c45023d640.jpg resize: (2160, 3840) 1386302050 -6.912786490374688 treat image : temp/1759244386_359586_1386302018_ccf36b9aba9c06d80ab85f52789a2795.jpg resize: (2160, 3840) 1386302018 -7.030209321471857 treat image : temp/1759244386_359586_1386301983_b1ae4982d7372426325a6e09a54e1a65.jpg resize: (2160, 3840) 1386301983 -6.988856939969375 treat image : temp/1759244386_359586_1386301953_3d192aa38bce05f090a0633230dd4bdf.jpg resize: (2160, 3840) 1386301953 -7.107402108477322 treat image : temp/1759244386_359586_1386301925_a479eb7b704c59d507f8361a441478c6.jpg resize: (2160, 3840) 1386301925 -7.078922471874244 treat image : temp/1759244386_359586_1386301882_1222513e42333942b0dfb98b088e45cd.jpg resize: (2160, 3840) 1386301882 -6.993507044028771 treat image : temp/1759244386_359586_1386301877_629ff193e5587e28dbb01b1d4b49e62a.jpg resize: (2160, 3840) 1386301877 -4.02740905689293 treat image : temp/1759244386_359586_1386301860_814c16b7b8fa744b39a1ad6a523f8d17.jpg resize: (2160, 3840) 1386301860 -6.281932836273739 treat image : temp/1759244386_359586_1386302361_caa1d21076ce801265ffe1196d1b1d80_rle_crop_3981095786_0.png resize: (514, 316) 1386982872 -4.905977388472405 treat image : temp/1759244386_359586_1386302361_caa1d21076ce801265ffe1196d1b1d80_rle_crop_3981095782_0.png resize: (83, 184) 1386982873 -4.479979010029508 treat image : temp/1759244386_359586_1386302361_caa1d21076ce801265ffe1196d1b1d80_rle_crop_3981095783_0.png resize: (111, 162) 1386982874 -3.7849862321411525 treat image : temp/1759244386_359586_1386302361_caa1d21076ce801265ffe1196d1b1d80_rle_crop_3981095780_0.png resize: (203, 130) 1386982875 -4.5538530231266705 treat image : temp/1759244386_359586_1386302357_ce78121a78f3d76800b7c71d3ed11b3b_rle_crop_3981095795_0.png resize: (213, 234) 1386982876 -4.2260834867818495 treat image : temp/1759244386_359586_1386302345_18ef46a11ab875d6338afbd6ab25fa4a_rle_crop_3981095803_0.png resize: (294, 176) 1386982877 -4.230997182809044 treat image : temp/1759244386_359586_1386302319_50da8176754b972256fdd310af4e25aa_rle_crop_3981095816_0.png resize: (444, 461) 1386982879 -5.67413315300035 treat image : temp/1759244386_359586_1386302319_50da8176754b972256fdd310af4e25aa_rle_crop_3981095812_0.png resize: (546, 745) 1386982880 -4.320131344156762 treat image : temp/1759244386_359586_1386302319_50da8176754b972256fdd310af4e25aa_rle_crop_3981095811_0.png resize: (248, 227) 1386982881 -4.474390791688472 treat image : temp/1759244386_359586_1386302319_50da8176754b972256fdd310af4e25aa_rle_crop_3981095814_0.png resize: (281, 537) 1386982882 -2.69348996804005 treat image : temp/1759244386_359586_1386302302_e0d3c06db129da79f8ad80350c8f0577_rle_crop_3981095817_0.png resize: (483, 733) 1386982883 -4.809263362958022 treat image : temp/1759244386_359586_1386302302_e0d3c06db129da79f8ad80350c8f0577_rle_crop_3981095825_0.png resize: (231, 225) 1386982884 -4.285457948484243 treat image : temp/1759244386_359586_1386302302_e0d3c06db129da79f8ad80350c8f0577_rle_crop_3981095821_0.png resize: (335, 598) 1386982885 -3.7631463263326768 treat image : temp/1759244386_359586_1386302286_4ce84dcd8ab6d33803d5875471b522b9_rle_crop_3981095828_0.png resize: (538, 401) 1386982886 -3.384279433059311 treat image : temp/1759244386_359586_1386302286_4ce84dcd8ab6d33803d5875471b522b9_rle_crop_3981095830_0.png resize: (478, 543) 1386982887 -5.3036592409210845 treat image : temp/1759244386_359586_1386302286_4ce84dcd8ab6d33803d5875471b522b9_rle_crop_3981095829_0.png resize: (154, 106) 1386982888 -3.67590065445124 treat image : temp/1759244386_359586_1386302286_4ce84dcd8ab6d33803d5875471b522b9_rle_crop_3981095837_0.png resize: (375, 802) 1386982889 -4.56287781743341 treat image : temp/1759244386_359586_1386302286_4ce84dcd8ab6d33803d5875471b522b9_rle_crop_3981095827_0.png resize: (122, 376) 1386982890 -5.088395897512055 treat image : temp/1759244386_359586_1386302079_07022de81d7c5fd5889a36c7d151c632_rle_crop_3981095852_0.png resize: (162, 161) 1386982891 -3.0510622198406283 treat image : temp/1759244386_359586_1386302079_07022de81d7c5fd5889a36c7d151c632_rle_crop_3981095851_0.png resize: (211, 314) 1386982892 -3.149161852993631 treat image : temp/1759244386_359586_1386302079_07022de81d7c5fd5889a36c7d151c632_rle_crop_3981095854_0.png resize: (223, 223) 1386982893 -4.2144601215299 treat image : temp/1759244386_359586_1386302050_6b7e9a2de9ba085cde9b70c45023d640_rle_crop_3981095865_0.png resize: (500, 257) 1386982894 -4.436007041622754 treat image : temp/1759244386_359586_1386302050_6b7e9a2de9ba085cde9b70c45023d640_rle_crop_3981095866_0.png resize: (333, 337) 1386982895 -4.8090436101723775 treat image : temp/1759244386_359586_1386302050_6b7e9a2de9ba085cde9b70c45023d640_rle_crop_3981095857_0.png resize: (502, 217) 1386982896 -3.8865105192431897 treat image : temp/1759244386_359586_1386302050_6b7e9a2de9ba085cde9b70c45023d640_rle_crop_3981095863_0.png resize: (285, 186) 1386982897 -4.707517363022529 treat image : temp/1759244386_359586_1386302050_6b7e9a2de9ba085cde9b70c45023d640_rle_crop_3981095860_0.png resize: (398, 423) 1386982898 -3.650656197015261 treat image : temp/1759244386_359586_1386302050_6b7e9a2de9ba085cde9b70c45023d640_rle_crop_3981095861_0.png resize: (96, 153) 1386982899 -4.002870089089444 treat image : temp/1759244386_359586_1386302050_6b7e9a2de9ba085cde9b70c45023d640_rle_crop_3981095862_0.png resize: (136, 104) 1386982900 -4.66481246801736 treat image : temp/1759244386_359586_1386302050_6b7e9a2de9ba085cde9b70c45023d640_rle_crop_3981095858_0.png resize: (141, 84) 1386982901 -3.9726411186372332 treat image : temp/1759244386_359586_1386302018_ccf36b9aba9c06d80ab85f52789a2795_rle_crop_3981095868_0.png resize: (191, 325) 1386982902 -5.227024250990893 treat image : temp/1759244386_359586_1386302018_ccf36b9aba9c06d80ab85f52789a2795_rle_crop_3981095878_0.png resize: (221, 197) 1386982903 -4.763017429973382 treat image : temp/1759244386_359586_1386301983_b1ae4982d7372426325a6e09a54e1a65_rle_crop_3981095881_0.png resize: (389, 281) 1386982904 -3.4363091023911463 treat image : temp/1759244386_359586_1386301983_b1ae4982d7372426325a6e09a54e1a65_rle_crop_3981095882_0.png resize: (426, 327) 1386982905 -4.211033334811863 treat image : temp/1759244386_359586_1386301953_3d192aa38bce05f090a0633230dd4bdf_rle_crop_3981095886_0.png resize: (323, 252) 1386982906 -3.176680931144602 treat image : temp/1759244386_359586_1386301953_3d192aa38bce05f090a0633230dd4bdf_rle_crop_3981095884_0.png resize: (328, 352) 1386982907 -4.595931422827029 treat image : temp/1759244386_359586_1386301925_a479eb7b704c59d507f8361a441478c6_rle_crop_3981095891_0.png resize: (245, 238) 1386982908 -4.0794056456502945 treat image : temp/1759244386_359586_1386301925_a479eb7b704c59d507f8361a441478c6_rle_crop_3981095889_0.png resize: (412, 448) 1386982909 -4.635442929451139 treat image : temp/1759244386_359586_1386301925_a479eb7b704c59d507f8361a441478c6_rle_crop_3981095896_0.png resize: (242, 240) 1386982910 -4.406666756102304 treat image : temp/1759244386_359586_1386301882_1222513e42333942b0dfb98b088e45cd_rle_crop_3981095901_0.png resize: (165, 359) 1386982911 -3.920196701659466 treat image : temp/1759244386_359586_1386301882_1222513e42333942b0dfb98b088e45cd_rle_crop_3981095900_0.png resize: (511, 496) 1386982912 -4.5158935434946255 treat image : temp/1759244386_359586_1386301882_1222513e42333942b0dfb98b088e45cd_rle_crop_3981095904_0.png resize: (377, 460) 1386982913 -5.310008047431368 treat image : temp/1759244386_359586_1386301877_629ff193e5587e28dbb01b1d4b49e62a_rle_crop_3981095911_0.png resize: (178, 237) 1386982914 -4.517057442564102 treat image : temp/1759244386_359586_1386301877_629ff193e5587e28dbb01b1d4b49e62a_rle_crop_3981095907_0.png resize: (175, 196) 1386982915 -3.5270926627895722 treat image : temp/1759244386_359586_1386301860_814c16b7b8fa744b39a1ad6a523f8d17_rle_crop_3981095920_0.png resize: (155, 375) 1386982916 -4.138014511817629 treat image : temp/1759244386_359586_1386302357_ce78121a78f3d76800b7c71d3ed11b3b_rle_crop_3981095800_0.png resize: (407, 157) 1386982920 -3.1259614338367148 treat image : temp/1759244386_359586_1386302357_ce78121a78f3d76800b7c71d3ed11b3b_rle_crop_3981095793_0.png resize: (431, 619) 1386982921 -2.566540972334224 treat image : temp/1759244386_359586_1386302345_18ef46a11ab875d6338afbd6ab25fa4a_rle_crop_3981095808_0.png resize: (466, 292) 1386982922 -2.7711631037077633 treat image : temp/1759244386_359586_1386302345_18ef46a11ab875d6338afbd6ab25fa4a_rle_crop_3981095801_0.png resize: (168, 253) 1386982923 -2.8718458217418013 treat image : temp/1759244386_359586_1386302302_e0d3c06db129da79f8ad80350c8f0577_rle_crop_3981095826_0.png resize: (556, 154) 1386982924 -4.946853156601584 treat image : temp/1759244386_359586_1386302302_e0d3c06db129da79f8ad80350c8f0577_rle_crop_3981095818_0.png resize: (254, 160) 1386982925 -4.297695085493904 treat image : temp/1759244386_359586_1386302302_e0d3c06db129da79f8ad80350c8f0577_rle_crop_3981095822_0.png resize: (133, 343) 1386982926 -3.077223067435558 treat image : temp/1759244386_359586_1386302286_4ce84dcd8ab6d33803d5875471b522b9_rle_crop_3981095834_0.png resize: (237, 265) 1386982927 -4.221370762378574 treat image : temp/1759244386_359586_1386302079_07022de81d7c5fd5889a36c7d151c632_rle_crop_3981095853_0.png resize: (526, 514) 1386982928 -2.943787169601316 treat image : temp/1759244386_359586_1386302050_6b7e9a2de9ba085cde9b70c45023d640_rle_crop_3981095867_0.png resize: (200, 189) 1386982929 -4.792610717626917 treat image : temp/1759244386_359586_1386302018_ccf36b9aba9c06d80ab85f52789a2795_rle_crop_3981095877_0.png resize: (144, 137) 1386982930 -4.3597064625815625 treat image : temp/1759244386_359586_1386301925_a479eb7b704c59d507f8361a441478c6_rle_crop_3981095892_0.png resize: (167, 158) 1386982931 -4.244074931490516 treat image : temp/1759244386_359586_1386301925_a479eb7b704c59d507f8361a441478c6_rle_crop_3981095890_0.png resize: (231, 146) 1386982933 -2.996436824388564 treat image : temp/1759244386_359586_1386301925_a479eb7b704c59d507f8361a441478c6_rle_crop_3981095899_0.png resize: (188, 292) 1386982934 -4.425229587848554 treat image : temp/1759244386_359586_1386301882_1222513e42333942b0dfb98b088e45cd_rle_crop_3981095905_0.png resize: (469, 413) 1386982935 -3.863016690111764 treat image : temp/1759244386_359586_1386301877_629ff193e5587e28dbb01b1d4b49e62a_rle_crop_3981095910_0.png resize: (135, 214) 1386982936 -3.7315200294085735 treat image : temp/1759244386_359586_1386301860_814c16b7b8fa744b39a1ad6a523f8d17_rle_crop_3981095917_0.png resize: (144, 218) 1386982937 -2.8719339250071343 treat image : temp/1759244386_359586_1386302361_caa1d21076ce801265ffe1196d1b1d80_rle_crop_3981095787_0.png resize: (116, 85) 1386982966 -5.6405673005992565 treat image : temp/1759244386_359586_1386302361_caa1d21076ce801265ffe1196d1b1d80_rle_crop_3981095790_0.png resize: (173, 116) 1386982967 -4.385850201976865 treat image : temp/1759244386_359586_1386302361_caa1d21076ce801265ffe1196d1b1d80_rle_crop_3981095785_0.png resize: (116, 161) 1386982968 -5.481367141385659 treat image : temp/1759244386_359586_1386302361_caa1d21076ce801265ffe1196d1b1d80_rle_crop_3981095784_0.png resize: (141, 129) 1386982969 -4.1701235362701965 treat image : temp/1759244386_359586_1386302357_ce78121a78f3d76800b7c71d3ed11b3b_rle_crop_3981095799_0.png resize: (169, 167) 1386982970 -4.00993025428276 treat image : temp/1759244386_359586_1386302302_e0d3c06db129da79f8ad80350c8f0577_rle_crop_3981095823_0.png resize: (78, 102) 1386982971 -4.662346319316291 treat image : temp/1759244386_359586_1386302286_4ce84dcd8ab6d33803d5875471b522b9_rle_crop_3981095838_0.png resize: (187, 203) 1386982972 -5.06221508449854 treat image : temp/1759244386_359586_1386302284_b3ec7232402b94d0d364bb11e2dffa46_rle_crop_3981095845_0.png resize: (156, 202) 1386982973 -3.177404286347426 treat image : temp/1759244386_359586_1386302284_b3ec7232402b94d0d364bb11e2dffa46_rle_crop_3981095843_0.png resize: (119, 127) 1386982974 -4.953476859296852 treat image : temp/1759244386_359586_1386302284_b3ec7232402b94d0d364bb11e2dffa46_rle_crop_3981095846_0.png resize: (190, 143) 1386982975 -4.532396625994858 treat image : temp/1759244386_359586_1386302018_ccf36b9aba9c06d80ab85f52789a2795_rle_crop_3981095879_0.png resize: (140, 137) 1386982976 -4.401938375251226 treat image : temp/1759244386_359586_1386302018_ccf36b9aba9c06d80ab85f52789a2795_rle_crop_3981095876_0.png resize: (224, 267) 1386982977 -4.520087757071482 treat image : temp/1759244386_359586_1386301925_a479eb7b704c59d507f8361a441478c6_rle_crop_3981095894_0.png resize: (193, 173) 1386982978 -5.361031881622853 treat image : temp/1759244386_359586_1386301925_a479eb7b704c59d507f8361a441478c6_rle_crop_3981095897_0.png resize: (154, 213) 1386982979 -3.7489123649044647 treat image : temp/1759244386_359586_1386302361_caa1d21076ce801265ffe1196d1b1d80_rle_crop_3981095791_0.png resize: (1935, 2547) 1386983406 -6.0034075383171155 treat image : temp/1759244386_359586_1386302361_caa1d21076ce801265ffe1196d1b1d80_rle_crop_3981095778_0.png resize: (612, 861) 1386983407 -6.021277470402061 treat image : temp/1759244386_359586_1386302361_caa1d21076ce801265ffe1196d1b1d80_rle_crop_3981095789_0.png resize: (695, 566) 1386983408 -6.287189677315778 treat image : temp/1759244386_359586_1386302361_caa1d21076ce801265ffe1196d1b1d80_rle_crop_3981095781_0.png resize: (205, 363) 1386983409 -4.426157500021828 treat image : temp/1759244386_359586_1386302361_caa1d21076ce801265ffe1196d1b1d80_rle_crop_3981095779_0.png resize: (413, 405) 1386983410 -3.6576654053108726 treat image : temp/1759244386_359586_1386302357_ce78121a78f3d76800b7c71d3ed11b3b_rle_crop_3981095798_0.png resize: (230, 266) 1386983411 -4.351286801537505 treat image : temp/1759244386_359586_1386302357_ce78121a78f3d76800b7c71d3ed11b3b_rle_crop_3981095796_0.png resize: (278, 439) 1386983412 -4.89120050349427 treat image : temp/1759244386_359586_1386302357_ce78121a78f3d76800b7c71d3ed11b3b_rle_crop_3981095797_0.png resize: (88, 110) 1386983413 -3.6189496611055105 treat image : temp/1759244386_359586_1386302357_ce78121a78f3d76800b7c71d3ed11b3b_rle_crop_3981095794_0.png resize: (86, 235) 1386983414 -4.31137055271041 treat image : temp/1759244386_359586_1386302357_ce78121a78f3d76800b7c71d3ed11b3b_rle_crop_3981095792_0.png resize: (357, 352) 1386983416 -5.812680898297524 treat image : temp/1759244386_359586_1386302345_18ef46a11ab875d6338afbd6ab25fa4a_rle_crop_3981095809_0.png resize: (224, 380) 1386983417 -5.1424598509146575 treat image : temp/1759244386_359586_1386302345_18ef46a11ab875d6338afbd6ab25fa4a_rle_crop_3981095802_0.png resize: (208, 327) 1386983418 -5.03577886502505 treat image : temp/1759244386_359586_1386302345_18ef46a11ab875d6338afbd6ab25fa4a_rle_crop_3981095810_0.png resize: (165, 522) 1386983419 -4.14718075850436 treat image : temp/1759244386_359586_1386302345_18ef46a11ab875d6338afbd6ab25fa4a_rle_crop_3981095805_0.png resize: (219, 414) 1386983420 -3.9536679759816633 treat image : temp/1759244386_359586_1386302345_18ef46a11ab875d6338afbd6ab25fa4a_rle_crop_3981095804_0.png resize: (312, 500) 1386983421 -4.253090350204065 treat image : temp/1759244386_359586_1386302345_18ef46a11ab875d6338afbd6ab25fa4a_rle_crop_3981095806_0.png resize: (295, 415) 1386983422 -4.919028099904816 treat image : temp/1759244386_359586_1386302345_18ef46a11ab875d6338afbd6ab25fa4a_rle_crop_3981095807_0.png resize: (303, 203) 1386983423 -5.239650168800221 treat image : temp/1759244386_359586_1386302319_50da8176754b972256fdd310af4e25aa_rle_crop_3981095813_0.png resize: (172, 276) 1386983424 -4.540522712047569 treat image : temp/1759244386_359586_1386302319_50da8176754b972256fdd310af4e25aa_rle_crop_3981095815_0.png resize: (208, 488) 1386983425 -3.568043590705948 treat image : temp/1759244386_359586_1386302302_e0d3c06db129da79f8ad80350c8f0577_rle_crop_3981095820_0.png resize: (386, 454) 1386983427 -4.833068460437159 treat image : temp/1759244386_359586_1386302302_e0d3c06db129da79f8ad80350c8f0577_rle_crop_3981095819_0.png resize: (285, 235) 1386983428 -4.327753802483202 treat image : temp/1759244386_359586_1386302302_e0d3c06db129da79f8ad80350c8f0577_rle_crop_3981095824_0.png resize: (397, 647) 1386983429 -4.186146750001262 treat image : temp/1759244386_359586_1386302286_4ce84dcd8ab6d33803d5875471b522b9_rle_crop_3981095840_0.png resize: (340, 310) 1386983430 -5.403819503366766 treat image : temp/1759244386_359586_1386302286_4ce84dcd8ab6d33803d5875471b522b9_rle_crop_3981095835_0.png resize: (719, 482) 1386983431 -5.922173586696497 treat image : temp/1759244386_359586_1386302286_4ce84dcd8ab6d33803d5875471b522b9_rle_crop_3981095833_0.png resize: (320, 450) 1386983432 -5.262392725390514 treat image : temp/1759244386_359586_1386302286_4ce84dcd8ab6d33803d5875471b522b9_rle_crop_3981095839_0.png resize: (259, 245) 1386983433 -5.174486642690474 treat image : temp/1759244386_359586_1386302286_4ce84dcd8ab6d33803d5875471b522b9_rle_crop_3981095831_0.png resize: (610, 250) 1386983434 -4.8685334844319295 treat image : temp/1759244386_359586_1386302286_4ce84dcd8ab6d33803d5875471b522b9_rle_crop_3981095836_0.png resize: (296, 225) 1386983435 -4.824810872890071 treat image : temp/1759244386_359586_1386302284_b3ec7232402b94d0d364bb11e2dffa46_rle_crop_3981095841_0.png resize: (390, 238) 1386983437 -5.089341204018371 treat image : temp/1759244386_359586_1386302079_07022de81d7c5fd5889a36c7d151c632_rle_crop_3981095855_0.png resize: (365, 292) 1386983438 -4.513873858491192 treat image : temp/1759244386_359586_1386302079_07022de81d7c5fd5889a36c7d151c632_rle_crop_3981095850_0.png resize: (390, 372) 1386983439 -4.93116845230215 treat image : temp/1759244386_359586_1386302050_6b7e9a2de9ba085cde9b70c45023d640_rle_crop_3981095859_0.png resize: (765, 1146) 1386983440 -5.301287054034791 treat image : temp/1759244386_359586_1386302018_ccf36b9aba9c06d80ab85f52789a2795_rle_crop_3981095874_0.png resize: (338, 344) 1386983441 -3.6412522132754197 treat image : temp/1759244386_359586_1386302018_ccf36b9aba9c06d80ab85f52789a2795_rle_crop_3981095869_0.png resize: (481, 445) 1386983442 -4.6727576707360186 treat image : temp/1759244386_359586_1386302018_ccf36b9aba9c06d80ab85f52789a2795_rle_crop_3981095872_0.png resize: (376, 502) 1386983443 -4.187387958137083 treat image : temp/1759244386_359586_1386302018_ccf36b9aba9c06d80ab85f52789a2795_rle_crop_3981095873_0.png resize: (130, 140) 1386983444 -4.684479981999381 treat image : temp/1759244386_359586_1386302018_ccf36b9aba9c06d80ab85f52789a2795_rle_crop_3981095870_0.png resize: (107, 162) 1386983445 -3.9104493328344314 treat image : temp/1759244386_359586_1386301983_b1ae4982d7372426325a6e09a54e1a65_rle_crop_3981095883_0.png resize: (293, 246) 1386983446 -4.734451231350207 treat image : temp/1759244386_359586_1386301953_3d192aa38bce05f090a0633230dd4bdf_rle_crop_3981095885_0.png resize: (210, 237) 1386983447 -4.7313537164294495 treat image : temp/1759244386_359586_1386301953_3d192aa38bce05f090a0633230dd4bdf_rle_crop_3981095888_0.png resize: (508, 642) 1386983448 -5.52817914360963 treat image : temp/1759244386_359586_1386301953_3d192aa38bce05f090a0633230dd4bdf_rle_crop_3981095887_0.png resize: (373, 328) 1386983449 -3.736884512301739 treat image : temp/1759244386_359586_1386301925_a479eb7b704c59d507f8361a441478c6_rle_crop_3981095893_0.png resize: (199, 247) 1386983450 -4.955561371581811 treat image : temp/1759244386_359586_1386301925_a479eb7b704c59d507f8361a441478c6_rle_crop_3981095898_0.png resize: (190, 240) 1386983451 -5.0377907682541805 treat image : temp/1759244386_359586_1386301882_1222513e42333942b0dfb98b088e45cd_rle_crop_3981095902_0.png resize: (252, 172) 1386983452 -5.60000447679481 treat image : temp/1759244386_359586_1386301882_1222513e42333942b0dfb98b088e45cd_rle_crop_3981095903_0.png resize: (128, 195) 1386983453 -4.691091475662803 treat image : temp/1759244386_359586_1386301877_629ff193e5587e28dbb01b1d4b49e62a_rle_crop_3981095914_0.png resize: (1827, 2785) 1386983454 -4.233559531707441 treat image : temp/1759244386_359586_1386301877_629ff193e5587e28dbb01b1d4b49e62a_rle_crop_3981095912_0.png resize: (364, 224) 1386983455 -4.887056816337334 treat image : temp/1759244386_359586_1386301877_629ff193e5587e28dbb01b1d4b49e62a_rle_crop_3981095909_0.png resize: (194, 151) 1386983456 -4.7928105427041325 treat image : temp/1759244386_359586_1386301877_629ff193e5587e28dbb01b1d4b49e62a_rle_crop_3981095906_0.png resize: (270, 666) 1386983457 -4.623634092403419 treat image : temp/1759244386_359586_1386301877_629ff193e5587e28dbb01b1d4b49e62a_rle_crop_3981095908_0.png resize: (128, 271) 1386983458 -4.975409288930389 treat image : temp/1759244386_359586_1386301877_629ff193e5587e28dbb01b1d4b49e62a_rle_crop_3981095913_0.png resize: (505, 545) 1386983459 -3.7243812776431287 treat image : temp/1759244386_359586_1386301860_814c16b7b8fa744b39a1ad6a523f8d17_rle_crop_3981095918_0.png resize: (247, 323) 1386983460 -4.800336205639661 treat image : temp/1759244386_359586_1386301860_814c16b7b8fa744b39a1ad6a523f8d17_rle_crop_3981095919_0.png resize: (543, 403) 1386983461 -4.419995997335039 treat image : temp/1759244386_359586_1386301860_814c16b7b8fa744b39a1ad6a523f8d17_rle_crop_3981095916_0.png resize: (95, 225) 1386983463 -3.9272191600843493 treat image : temp/1759244386_359586_1386302361_caa1d21076ce801265ffe1196d1b1d80_rle_crop_3981095788_0.png resize: (122, 91) 1386983469 -4.8635835956266575 treat image : temp/1759244386_359586_1386302284_b3ec7232402b94d0d364bb11e2dffa46_rle_crop_3981095842_0.png resize: (251, 176) 1386983470 -5.35476755512034 treat image : temp/1759244386_359586_1386302284_b3ec7232402b94d0d364bb11e2dffa46_rle_crop_3981095847_0.png resize: (111, 156) 1386983471 -0.9952698700035499 treat image : temp/1759244386_359586_1386302284_b3ec7232402b94d0d364bb11e2dffa46_rle_crop_3981095849_0.png resize: (137, 223) 1386983472 -4.420793653814436 treat image : temp/1759244386_359586_1386302284_b3ec7232402b94d0d364bb11e2dffa46_rle_crop_3981095848_0.png resize: (172, 158) 1386983474 -4.099211077062377 treat image : temp/1759244386_359586_1386302284_b3ec7232402b94d0d364bb11e2dffa46_rle_crop_3981095844_0.png resize: (233, 121) 1386983475 -4.231471301015089 treat image : temp/1759244386_359586_1386302050_6b7e9a2de9ba085cde9b70c45023d640_rle_crop_3981095864_0.png resize: (316, 325) 1386983476 -3.6050198136958023 treat image : temp/1759244386_359586_1386302018_ccf36b9aba9c06d80ab85f52789a2795_rle_crop_3981095875_0.png resize: (178, 178) 1386983477 -3.61359893407303 treat image : temp/1759244386_359586_1386302018_ccf36b9aba9c06d80ab85f52789a2795_rle_crop_3981095871_0.png resize: (128, 118) 1386983478 -4.235918589254005 treat image : temp/1759244386_359586_1386301925_a479eb7b704c59d507f8361a441478c6_rle_crop_3981095895_0.png resize: (229, 208) 1386983479 -4.303308149511521 treat image : temp/1759244386_359586_1386301860_814c16b7b8fa744b39a1ad6a523f8d17_rle_crop_3981095915_0.png resize: (281, 286) 1386983480 -1.741812542788459 treat image : temp/1759244386_359586_1386302286_4ce84dcd8ab6d33803d5875471b522b9_rle_crop_3981095832_0.png resize: (322, 231) 1386983483 -4.048700709398766 treat image : temp/1759244386_359586_1386302079_07022de81d7c5fd5889a36c7d151c632_rle_crop_3981095856_0.png resize: (255, 183) 1386983484 -4.814422198385601 treat image : temp/1759244386_359586_1386302018_ccf36b9aba9c06d80ab85f52789a2795_rle_crop_3981095880_0.png resize: (749, 488) 1386983485 -4.6147720172996225 Inside saveOutput : final : False verbose : 0 begin to insert list_values into class_photo_scores : length of list_valuse in save_photo_hashtag_id_thcl_score : 159 time used for this insertion : 0.04960012435913086 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 159 time used for this insertion : 0.07796168327331543 save missing photos in datou_result : time spend for datou_step_exec : 73.69085693359375 time spend to save output : 0.14637494087219238 total time spend for step 6 : 73.83723187446594 step7:brightness Tue Sep 30 17:07:20 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure inside step calcul brightness treat image : temp/1759244386_359586_1386302361_caa1d21076ce801265ffe1196d1b1d80.jpg treat image : temp/1759244386_359586_1386302357_ce78121a78f3d76800b7c71d3ed11b3b.jpg treat image : temp/1759244386_359586_1386302345_18ef46a11ab875d6338afbd6ab25fa4a.jpg treat image : temp/1759244386_359586_1386302319_50da8176754b972256fdd310af4e25aa.jpg treat image : temp/1759244386_359586_1386302302_e0d3c06db129da79f8ad80350c8f0577.jpg treat image : temp/1759244386_359586_1386302286_4ce84dcd8ab6d33803d5875471b522b9.jpg treat image : temp/1759244386_359586_1386302284_b3ec7232402b94d0d364bb11e2dffa46.jpg treat image : temp/1759244386_359586_1386302079_07022de81d7c5fd5889a36c7d151c632.jpg treat image : temp/1759244386_359586_1386302050_6b7e9a2de9ba085cde9b70c45023d640.jpg treat image : temp/1759244386_359586_1386302018_ccf36b9aba9c06d80ab85f52789a2795.jpg treat image : 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temp/1759244386_359586_1386302284_b3ec7232402b94d0d364bb11e2dffa46_rle_crop_3981095842_0.png treat image : temp/1759244386_359586_1386302284_b3ec7232402b94d0d364bb11e2dffa46_rle_crop_3981095847_0.png treat image : temp/1759244386_359586_1386302284_b3ec7232402b94d0d364bb11e2dffa46_rle_crop_3981095849_0.png treat image : temp/1759244386_359586_1386302284_b3ec7232402b94d0d364bb11e2dffa46_rle_crop_3981095848_0.png treat image : temp/1759244386_359586_1386302284_b3ec7232402b94d0d364bb11e2dffa46_rle_crop_3981095844_0.png treat image : temp/1759244386_359586_1386302050_6b7e9a2de9ba085cde9b70c45023d640_rle_crop_3981095864_0.png treat image : temp/1759244386_359586_1386302018_ccf36b9aba9c06d80ab85f52789a2795_rle_crop_3981095875_0.png treat image : temp/1759244386_359586_1386302018_ccf36b9aba9c06d80ab85f52789a2795_rle_crop_3981095871_0.png treat image : temp/1759244386_359586_1386301925_a479eb7b704c59d507f8361a441478c6_rle_crop_3981095895_0.png treat image : temp/1759244386_359586_1386301860_814c16b7b8fa744b39a1ad6a523f8d17_rle_crop_3981095915_0.png treat image : temp/1759244386_359586_1386302286_4ce84dcd8ab6d33803d5875471b522b9_rle_crop_3981095832_0.png treat image : temp/1759244386_359586_1386302079_07022de81d7c5fd5889a36c7d151c632_rle_crop_3981095856_0.png treat image : temp/1759244386_359586_1386302018_ccf36b9aba9c06d80ab85f52789a2795_rle_crop_3981095880_0.png Inside saveOutput : final : False verbose : 0 begin to insert list_values into class_photo_scores : length of list_valuse in save_photo_hashtag_id_thcl_score : 159 time used for this insertion : 0.04316568374633789 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 159 time used for this insertion : 0.07675337791442871 save missing photos in datou_result : time spend for datou_step_exec : 20.48283076286316 time spend to save output : 0.13878297805786133 total time spend for step 7 : 20.62161374092102 step8:velours_tree Tue Sep 30 17:07:40 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 VR 22-3-18 : For now we do not clean correctly the datou structure can't find the photo_desc_type Inside saveOutput : final : False verbose : 0 ouput is None No outpout to save, returning out of save general time spend for datou_step_exec : 0.3750617504119873 time spend to save output : 0.00011372566223144531 total time spend for step 8 : 0.37517547607421875 step9:send_mail_cod Tue Sep 30 17:07:41 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 complete output_args for input 1 Inconsistent number of input and output, step which parrallelize and manage error in input by avoiding sending an output for this data can't be used in tree dependencies of input and output complete output_args for input 2 Inconsistent number of input and output, step which parrallelize and manage error in input by avoiding sending an output for this data can't be used in tree dependencies of input and output complete output_args for input 3 We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure dans la step send mail cod work_area: /home/admin in order to get the selector url, please entre the license of selector results_Auto_P27268302_30-09-2025_17_07_41.pdf 27356995 imagette273569951759244861 27356996 change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .imagette273569961759244861 27356997 change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .imagette273569971759244864 27356999 change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .imagette273569991759244866 27357000 change filename to text .change filename to text .change filename to text .imagette273570001759244868 27357001 change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .imagette273570011759244869 27357002 imagette273570021759244870 27357003 imagette273570031759244870 27357004 imagette273570041759244870 27357005 change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .imagette273570051759244870 SELECT h.hashtag,pcr.value FROM MTRUser.portfolio_carac_ratio pcr, MTRBack.hashtags h where pcr.portfolio_id=27268302 and hashtag_type = 3594 and pcr.hashtag_id = h.hashtag_id; velour_link : https://marlene.fotonower.com/velours/27356995,27356996,27356997,27356998,27356999,27357000,27357001,27357002,27357003,27357004,27357005?tags=flou,papier,carton,environnement,pet_clair,pet_fonce,autre,mal_croppe,background,pehd,metal args[1386302361] : ((1386302361, -5.788193087064078, 492609224), (1386302361, -0.9496277145278013, 501862349), '0.13530545458381554') We are sending mail with results at report@fotonower.com args[1386302357] : ((1386302357, -6.556976304811067, 492609224), (1386302357, -0.20459405071799172, 496442774), '0.13530545458381554') We are sending mail with results at report@fotonower.com args[1386302345] : ((1386302345, -7.0153097181104584, 492609224), (1386302345, 0.02464017756475171, 2107752395), '0.13530545458381554') We are sending mail with results at report@fotonower.com args[1386302319] : ((1386302319, -7.232537838607711, 492609224), (1386302319, 0.04124823197985904, 2107752395), '0.13530545458381554') We are sending mail with results at report@fotonower.com args[1386302302] : ((1386302302, -7.155046829820226, 492609224), (1386302302, 0.0694679471287354, 2107752395), '0.13530545458381554') We are sending mail with results at report@fotonower.com args[1386302286] : ((1386302286, -6.938881854184758, 492609224), (1386302286, 0.02141950872271514, 2107752395), '0.13530545458381554') We are sending mail with results at report@fotonower.com args[1386302284] : ((1386302284, -7.067196778924721, 492609224), (1386302284, 0.008583765947470663, 2107752395), '0.13530545458381554') We are sending mail with results at report@fotonower.com args[1386302079] : ((1386302079, -6.95983035955159, 492609224), (1386302079, -0.021704988065936473, 2107752395), '0.13530545458381554') We are sending mail with results at report@fotonower.com args[1386302050] : ((1386302050, -6.912786490374688, 492609224), (1386302050, 0.03628174498123924, 2107752395), '0.13530545458381554') We are sending mail with results at report@fotonower.com args[1386302018] : ((1386302018, -7.030209321471857, 492609224), (1386302018, -0.05513028407595421, 2107752395), '0.13530545458381554') We are sending mail with results at report@fotonower.com args[1386301983] : ((1386301983, -6.988856939969375, 492609224), (1386301983, -0.06158247189455771, 2107752395), '0.13530545458381554') We are sending mail with results at report@fotonower.com args[1386301953] : ((1386301953, -7.107402108477322, 492609224), (1386301953, 0.039555125143173935, 2107752395), '0.13530545458381554') We are sending mail with results at report@fotonower.com args[1386301925] : ((1386301925, -7.078922471874244, 492609224), (1386301925, -0.026948096343003453, 2107752395), '0.13530545458381554') We are sending mail with results at report@fotonower.com args[1386301882] : ((1386301882, -6.993507044028771, 492609224), (1386301882, -0.05435397011913358, 2107752395), '0.13530545458381554') We are sending mail with results at report@fotonower.com args[1386301877] : ((1386301877, -4.02740905689293, 492609224), (1386301877, -1.6822396957651966, 501862349), '0.13530545458381554') We are sending mail with results at report@fotonower.com args[1386301860] : ((1386301860, -6.281932836273739, 492609224), (1386301860, -0.2406011046694353, 496442774), '0.13530545458381554') We are sending mail with results at report@fotonower.com refus_total : 0.13530545458381554 2022-04-13 10:29:59 0 SELECT ph.photo_id,ph.url,ph.username,ph.uploaded_at,ph.text FROM MTRBack.photos_view ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=27268302 AND mpp.hide_status=0 ORDER BY mpp.order LIMIT 0, 1000 start upload file to ovh https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27268302_30-09-2025_17_07_41.pdf results_Auto_P27268302_30-09-2025_17_07_41.pdf uploaded to url https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27268302_30-09-2025_17_07_41.pdf start insert file to database insert into MTRUser.mtr_files (mtd_id,mtr_portfolio_id,text,url,format,tags,file_size,value) values ('3318','27268302','results_Auto_P27268302_30-09-2025_17_07_41.pdf','https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27268302_30-09-2025_17_07_41.pdf','pdf','','1.55','0.13530545458381554') message_in_mail: Bonjour,
Veuillez trouver ci dessous les résultats du service carac on demand pour le portfolio: https://www.fotonower.com/view/27268302

https://www.fotonower.com/image?json=false&list_photos_id=1386302361
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386302357
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386302345
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386302319
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386302302
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386302286
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386302284
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386302079
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386302050
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386302018
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386301983
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386301953
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386301925
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386301882
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386301877
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386301860
Bravo, la photo est bien prise.

Dans ces conditions,le taux de refus est: 13.53%
Veuillez trouver les photos des contaminants.

exemples de contaminants: papier: https://www.fotonower.com/view/27356996?limit=200
exemples de contaminants: carton: https://www.fotonower.com/view/27356997?limit=200
exemples de contaminants: pet_clair: https://www.fotonower.com/view/27356999?limit=200
exemples de contaminants: pet_fonce: https://www.fotonower.com/view/27357000?limit=200
exemples de contaminants: autre: https://www.fotonower.com/view/27357001?limit=200
exemples de contaminants: metal: https://www.fotonower.com/view/27357005?limit=200
Veuillez trouver le rapport en pdf:https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27268302_30-09-2025_17_07_41.pdf.

Lien vers velours :https://marlene.fotonower.com/velours/27356995,27356996,27356997,27356998,27356999,27357000,27357001,27357002,27357003,27357004,27357005?tags=flou,papier,carton,environnement,pet_clair,pet_fonce,autre,mal_croppe,background,pehd,metal.


L'équipe Fotonower 202 b'' Server: nginx Date: Tue, 30 Sep 2025 15:07:57 GMT Content-Length: 0 Connection: close X-Message-Id: yvOzc1eMRdaxHSVLPZ5JYA Access-Control-Allow-Origin: https://sendgrid.api-docs.io Access-Control-Allow-Methods: POST Access-Control-Allow-Headers: Authorization, Content-Type, On-behalf-of, x-sg-elas-acl Access-Control-Max-Age: 600 X-No-CORS-Reason: https://sendgrid.com/docs/Classroom/Basics/API/cors.html Strict-Transport-Security: max-age=31536000; includeSubDomains Content-Security-Policy: frame-ancestors 'none' Cache-Control: no-cache X-Content-Type-Options: no-sniff Referrer-Policy: strict-origin-when-cross-origin Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : send_mail_cod we use saveGeneral [1386302361, 1386302357, 1386302345, 1386302319, 1386302302, 1386302286, 1386302284, 1386302079, 1386302050, 1386302018, 1386301983, 1386301953, 1386301925, 1386301882, 1386301877, 1386301860] Looping around the photos to save general results len do output : 0 before output type Used above Managing all output in save final without adding information in the mtr_datou_result ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302361', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302357', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302345', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302319', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302302', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302286', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302284', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302079', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302050', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302018', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386301983', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386301953', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386301925', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386301882', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386301877', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386301860', None, None, None, None, None, '3784180') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 16 time used for this insertion : 0.036621809005737305 save_final save missing photos in datou_result : time spend for datou_step_exec : 16.374898195266724 time spend to save output : 0.03690385818481445 total time spend for step 9 : 16.411802053451538 step10:split_time_score Tue Sep 30 17:07:57 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! complete output_args for input 1 VR 22-3-18 : For now we do not clean correctly the datou structure begin split time score Catched exception ! Connect or reconnect ! TODO : Insert select and so on Begin split_port_in_batch_balle thcls : [{'id': 861, 'mtr_user_id': 31, 'name': 'Rungis_class_dechets_1212', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'Rungis_Aluminium,Rungis_Carton,Rungis_Papier,Rungis_Plastique_clair,Rungis_Plastique_dur,Rungis_Plastique_fonce,Rungis_Tapis_vide,Rungis_Tetrapak', 'svm_portfolios_learning': '1160730,571842,571844,571839,571933,571840,571841,572307', 'photo_hashtag_type': 999, 'photo_desc_type': 3963, 'type_classification': 'caffe', 'hashtag_id_list': '2107751280,2107750907,2107750908,2107750909,2107750910,2107750911,2107750912,2107750913'}] thcls : [{'id': 758, 'mtr_user_id': 31, 'name': 'Rungis_amount_dechets_fall_2018_v2', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': '05102018_Papier_non_papier_dense,05102018_Papier_non_papier_peu_dense,05102018_Papier_non_papier_presque_vide,05102018_Papier_non_papier_tres_dense,05102018_Papier_non_papier_tres_peu_dense', 'svm_portfolios_learning': '1108385,1108386,1108388,1108384,1108387', 'photo_hashtag_type': 856, 'photo_desc_type': 3853, 'type_classification': 'caffe', 'hashtag_id_list': '2107751013,2107751014,2107751015,2107751016,2107751017'}] (('08', 16),) ERROR counted https://github.com/fotonower/Velours/issues/663#issuecomment-421136223 {} 26092025 27268302 Nombre de photos uploadées : 16 / 23040 (0%) 26092025 27268302 Nombre de photos taguées (types de déchets): 0 / 16 (0%) 26092025 27268302 Nombre de photos taguées (volume) : 0 / 16 (0%) elapsed_time : load_data_split_time_score 4.0531158447265625e-06 elapsed_time : order_list_meta_photo_and_scores 1.0967254638671875e-05 ???????????????? elapsed_time : fill_and_build_computed_from_old_data 0.0008149147033691406 Catched exception ! Connect or reconnect ! Catched exception ! Connect or reconnect ! elapsed_time : insert_dashboard_record_day_entry 0.6604299545288086 We will return after consolidate but for now we need the day, how to get it, for now depending on the previous heavy steps Qualite : 0.01581898816307257 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27265029_26-09-2025_08_16_33.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27265029 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11449 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11452 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 11452 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11453 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11453 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11478 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11478 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11455 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11455 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11458 send_mail_cod have less inputs used (3) than in the step definition (5) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 11449 doesn't seem to be define in the database( WARNING : type of input 2 of step 11452 doesn't seem to be define in the database( WARNING : output 1 of step 11449 have datatype=2 whereas input 1 of step 11453 have datatype=7 WARNING : type of output 2 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11454 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11456 doesn't seem to be define in the database( WARNING : type of output 1 of step 11456 doesn't seem to be define in the database( WARNING : type of input 3 of step 11455 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11456 have datatype=10 whereas input 3 of step 11458 have datatype=6 WARNING : type of input 5 of step 11458 doesn't seem to be define in the database( WARNING : output 0 of step 11477 have datatype=11 whereas input 5 of step 11458 have datatype=None WARNING : output 0 of step 11456 have datatype=10 whereas input 0 of step 11477 have datatype=18 WARNING : type of input 2 of step 11478 doesn't seem to be define in the database( WARNING : output 1 of step 11454 have datatype=7 whereas input 2 of step 11478 have datatype=None WARNING : type of output 3 of step 11478 doesn't seem to be define in the database( WARNING : type of input 2 of step 11456 doesn't seem to be define in the database( WARNING : output 0 of step 11453 have datatype=1 whereas input 0 of step 11454 have datatype=2 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=27265029 AND mptpi.`type`=3726 To do Qualite : 0.046315839602623456 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27268279_30-09-2025_17_00_58.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27268279 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=27268279 AND mptpi.`type`=3594 To do Qualite : 0.13530545458381554 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27268302_30-09-2025_17_07_41.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27268302 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=27268302 AND mptpi.`type`=3594 To do Qualite : 0.04804779511299892 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27270434_26-09-2025_10_47_16.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27270434 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11449 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11452 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 11452 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11453 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11453 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11478 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11478 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11455 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11455 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11458 send_mail_cod have less inputs used (3) than in the step definition (5) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 11449 doesn't seem to be define in the database( WARNING : type of input 2 of step 11452 doesn't seem to be define in the database( WARNING : output 1 of step 11449 have datatype=2 whereas input 1 of step 11453 have datatype=7 WARNING : type of output 2 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11454 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11456 doesn't seem to be define in the database( WARNING : type of output 1 of step 11456 doesn't seem to be define in the database( WARNING : type of input 3 of step 11455 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11456 have datatype=10 whereas input 3 of step 11458 have datatype=6 WARNING : type of input 5 of step 11458 doesn't seem to be define in the database( WARNING : output 0 of step 11477 have datatype=11 whereas input 5 of step 11458 have datatype=None WARNING : output 0 of step 11456 have datatype=10 whereas input 0 of step 11477 have datatype=18 WARNING : type of input 2 of step 11478 doesn't seem to be define in the database( WARNING : output 1 of step 11454 have datatype=7 whereas input 2 of step 11478 have datatype=None WARNING : type of output 3 of step 11478 doesn't seem to be define in the database( WARNING : type of input 2 of step 11456 doesn't seem to be define in the database( WARNING : output 0 of step 11453 have datatype=1 whereas input 0 of step 11454 have datatype=2 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=27270434 AND mptpi.`type`=3726 To do Qualite : 0.014633098392367446 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27275379_26-09-2025_12_42_50.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27275379 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11449 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11452 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 11452 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11453 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11453 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11478 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11478 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11455 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11455 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11458 send_mail_cod have less inputs used (3) than in the step definition (5) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 11449 doesn't seem to be define in the database( WARNING : type of input 2 of step 11452 doesn't seem to be define in the database( WARNING : output 1 of step 11449 have datatype=2 whereas input 1 of step 11453 have datatype=7 WARNING : type of output 2 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11454 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11456 doesn't seem to be define in the database( WARNING : type of output 1 of step 11456 doesn't seem to be define in the database( WARNING : type of input 3 of step 11455 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11456 have datatype=10 whereas input 3 of step 11458 have datatype=6 WARNING : type of input 5 of step 11458 doesn't seem to be define in the database( WARNING : output 0 of step 11477 have datatype=11 whereas input 5 of step 11458 have datatype=None WARNING : output 0 of step 11456 have datatype=10 whereas input 0 of step 11477 have datatype=18 WARNING : type of input 2 of step 11478 doesn't seem to be define in the database( WARNING : output 1 of step 11454 have datatype=7 whereas input 2 of step 11478 have datatype=None WARNING : type of output 3 of step 11478 doesn't seem to be define in the database( WARNING : type of input 2 of step 11456 doesn't seem to be define in the database( WARNING : output 0 of step 11453 have datatype=1 whereas input 0 of step 11454 have datatype=2 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=27275379 AND mptpi.`type`=3726 To do Qualite : 0.00984680739461973 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27304148_27-09-2025_03_22_48.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27304148 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11449 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11452 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 11452 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11453 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11453 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11478 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11478 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11455 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11455 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11458 send_mail_cod have less inputs used (3) than in the step definition (5) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 11449 doesn't seem to be define in the database( WARNING : type of input 2 of step 11452 doesn't seem to be define in the database( WARNING : output 1 of step 11449 have datatype=2 whereas input 1 of step 11453 have datatype=7 WARNING : type of output 2 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11454 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11456 doesn't seem to be define in the database( WARNING : type of output 1 of step 11456 doesn't seem to be define in the database( WARNING : type of input 3 of step 11455 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11456 have datatype=10 whereas input 3 of step 11458 have datatype=6 WARNING : type of input 5 of step 11458 doesn't seem to be define in the database( WARNING : output 0 of step 11477 have datatype=11 whereas input 5 of step 11458 have datatype=None WARNING : output 0 of step 11456 have datatype=10 whereas input 0 of step 11477 have datatype=18 WARNING : type of input 2 of step 11478 doesn't seem to be define in the database( WARNING : output 1 of step 11454 have datatype=7 whereas input 2 of step 11478 have datatype=None WARNING : type of output 3 of step 11478 doesn't seem to be define in the database( WARNING : type of input 2 of step 11456 doesn't seem to be define in the database( WARNING : output 0 of step 11453 have datatype=1 whereas input 0 of step 11454 have datatype=2 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=27304148 AND mptpi.`type`=3726 To do Qualite : 0.019711607889653333 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27279552_26-09-2025_15_27_28.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27279552 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11449 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11452 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 11452 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11453 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11453 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11478 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11478 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11455 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11455 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11458 send_mail_cod have less inputs used (3) than in the step definition (5) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 11449 doesn't seem to be define in the database( WARNING : type of input 2 of step 11452 doesn't seem to be define in the database( WARNING : output 1 of step 11449 have datatype=2 whereas input 1 of step 11453 have datatype=7 WARNING : type of output 2 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11454 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11456 doesn't seem to be define in the database( WARNING : type of output 1 of step 11456 doesn't seem to be define in the database( WARNING : type of input 3 of step 11455 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11456 have datatype=10 whereas input 3 of step 11458 have datatype=6 WARNING : type of input 5 of step 11458 doesn't seem to be define in the database( WARNING : output 0 of step 11477 have datatype=11 whereas input 5 of step 11458 have datatype=None WARNING : output 0 of step 11456 have datatype=10 whereas input 0 of step 11477 have datatype=18 WARNING : type of input 2 of step 11478 doesn't seem to be define in the database( WARNING : output 1 of step 11454 have datatype=7 whereas input 2 of step 11478 have datatype=None WARNING : type of output 3 of step 11478 doesn't seem to be define in the database( WARNING : type of input 2 of step 11456 doesn't seem to be define in the database( WARNING : output 0 of step 11453 have datatype=1 whereas input 0 of step 11454 have datatype=2 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=27279552 AND mptpi.`type`=3726 To do Qualite : 0.02968023996498934 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27279612_26-09-2025_15_17_57.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27279612 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11449 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11452 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 11452 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11453 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11453 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11478 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11478 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11455 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11455 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11458 send_mail_cod have less inputs used (3) than in the step definition (5) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 11449 doesn't seem to be define in the database( WARNING : type of input 2 of step 11452 doesn't seem to be define in the database( WARNING : output 1 of step 11449 have datatype=2 whereas input 1 of step 11453 have datatype=7 WARNING : type of output 2 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11454 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11456 doesn't seem to be define in the database( WARNING : type of output 1 of step 11456 doesn't seem to be define in the database( WARNING : type of input 3 of step 11455 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11456 have datatype=10 whereas input 3 of step 11458 have datatype=6 WARNING : type of input 5 of step 11458 doesn't seem to be define in the database( WARNING : output 0 of step 11477 have datatype=11 whereas input 5 of step 11458 have datatype=None WARNING : output 0 of step 11456 have datatype=10 whereas input 0 of step 11477 have datatype=18 WARNING : type of input 2 of step 11478 doesn't seem to be define in the database( WARNING : output 1 of step 11454 have datatype=7 whereas input 2 of step 11478 have datatype=None WARNING : type of output 3 of step 11478 doesn't seem to be define in the database( WARNING : type of input 2 of step 11456 doesn't seem to be define in the database( WARNING : output 0 of step 11453 have datatype=1 whereas input 0 of step 11454 have datatype=2 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=27279612 AND mptpi.`type`=3726 To do find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27285549 order by id desc limit 1 Qualite : 0.01216723976040846 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27286590_26-09-2025_18_47_26.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27286590 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11449 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11452 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 11452 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11453 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11453 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11478 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11478 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11455 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11455 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11458 send_mail_cod have less inputs used (3) than in the step definition (5) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 11449 doesn't seem to be define in the database( WARNING : type of input 2 of step 11452 doesn't seem to be define in the database( WARNING : output 1 of step 11449 have datatype=2 whereas input 1 of step 11453 have datatype=7 WARNING : type of output 2 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11454 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11456 doesn't seem to be define in the database( WARNING : type of output 1 of step 11456 doesn't seem to be define in the database( WARNING : type of input 3 of step 11455 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11456 have datatype=10 whereas input 3 of step 11458 have datatype=6 WARNING : type of input 5 of step 11458 doesn't seem to be define in the database( WARNING : output 0 of step 11477 have datatype=11 whereas input 5 of step 11458 have datatype=None WARNING : output 0 of step 11456 have datatype=10 whereas input 0 of step 11477 have datatype=18 WARNING : type of input 2 of step 11478 doesn't seem to be define in the database( WARNING : output 1 of step 11454 have datatype=7 whereas input 2 of step 11478 have datatype=None WARNING : type of output 3 of step 11478 doesn't seem to be define in the database( WARNING : type of input 2 of step 11456 doesn't seem to be define in the database( WARNING : output 0 of step 11453 have datatype=1 whereas input 0 of step 11454 have datatype=2 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=27286590 AND mptpi.`type`=3726 To do Qualite : 0.01632671576748192 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27285558_26-09-2025_18_08_52.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27285558 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11449 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11452 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 11452 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11453 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11453 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11478 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11478 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11455 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11455 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11458 send_mail_cod have less inputs used (3) than in the step definition (5) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 11449 doesn't seem to be define in the database( WARNING : type of input 2 of step 11452 doesn't seem to be define in the database( WARNING : output 1 of step 11449 have datatype=2 whereas input 1 of step 11453 have datatype=7 WARNING : type of output 2 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11454 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11456 doesn't seem to be define in the database( WARNING : type of output 1 of step 11456 doesn't seem to be define in the database( WARNING : type of input 3 of step 11455 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11456 have datatype=10 whereas input 3 of step 11458 have datatype=6 WARNING : type of input 5 of step 11458 doesn't seem to be define in the database( WARNING : output 0 of step 11477 have datatype=11 whereas input 5 of step 11458 have datatype=None WARNING : output 0 of step 11456 have datatype=10 whereas input 0 of step 11477 have datatype=18 WARNING : type of input 2 of step 11478 doesn't seem to be define in the database( WARNING : output 1 of step 11454 have datatype=7 whereas input 2 of step 11478 have datatype=None WARNING : type of output 3 of step 11478 doesn't seem to be define in the database( WARNING : type of input 2 of step 11456 doesn't seem to be define in the database( WARNING : output 0 of step 11453 have datatype=1 whereas input 0 of step 11454 have datatype=2 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=27285558 AND mptpi.`type`=3726 To do Qualite : 0.07236157070172718 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27304157_27-09-2025_03_12_04.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27304157 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11449 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11452 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 11452 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11453 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11453 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11478 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11478 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11455 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11455 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11458 send_mail_cod have less inputs used (3) than in the step definition (5) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 11449 doesn't seem to be define in the database( WARNING : type of input 2 of step 11452 doesn't seem to be define in the database( WARNING : output 1 of step 11449 have datatype=2 whereas input 1 of step 11453 have datatype=7 WARNING : type of output 2 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11454 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11456 doesn't seem to be define in the database( WARNING : type of output 1 of step 11456 doesn't seem to be define in the database( WARNING : type of input 3 of step 11455 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11456 have datatype=10 whereas input 3 of step 11458 have datatype=6 WARNING : type of input 5 of step 11458 doesn't seem to be define in the database( WARNING : output 0 of step 11477 have datatype=11 whereas input 5 of step 11458 have datatype=None WARNING : output 0 of step 11456 have datatype=10 whereas input 0 of step 11477 have datatype=18 WARNING : type of input 2 of step 11478 doesn't seem to be define in the database( WARNING : output 1 of step 11454 have datatype=7 whereas input 2 of step 11478 have datatype=None WARNING : type of output 3 of step 11478 doesn't seem to be define in the database( WARNING : type of input 2 of step 11456 doesn't seem to be define in the database( WARNING : output 0 of step 11453 have datatype=1 whereas input 0 of step 11454 have datatype=2 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=27304157 AND mptpi.`type`=3726 To do Qualite : 0.10342333104543416 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27298623_27-09-2025_00_13_25.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27298623 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11449 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11452 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 11452 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11453 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11453 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11478 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11478 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11455 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11455 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11458 send_mail_cod have less inputs used (3) than in the step definition (5) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 11449 doesn't seem to be define in the database( WARNING : type of input 2 of step 11452 doesn't seem to be define in the database( WARNING : output 1 of step 11449 have datatype=2 whereas input 1 of step 11453 have datatype=7 WARNING : type of output 2 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11454 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11456 doesn't seem to be define in the database( WARNING : type of output 1 of step 11456 doesn't seem to be define in the database( WARNING : type of input 3 of step 11455 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11456 have datatype=10 whereas input 3 of step 11458 have datatype=6 WARNING : type of input 5 of step 11458 doesn't seem to be define in the database( WARNING : output 0 of step 11477 have datatype=11 whereas input 5 of step 11458 have datatype=None WARNING : output 0 of step 11456 have datatype=10 whereas input 0 of step 11477 have datatype=18 WARNING : type of input 2 of step 11478 doesn't seem to be define in the database( WARNING : output 1 of step 11454 have datatype=7 whereas input 2 of step 11478 have datatype=None WARNING : type of output 3 of step 11478 doesn't seem to be define in the database( WARNING : type of input 2 of step 11456 doesn't seem to be define in the database( WARNING : output 0 of step 11453 have datatype=1 whereas input 0 of step 11454 have datatype=2 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=27298623 AND mptpi.`type`=3726 To do Qualite : 0.10113698226431476 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27298624_27-09-2025_00_08_40.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27298624 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11449 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11452 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 11452 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11453 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11453 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11478 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11478 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11455 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11455 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11458 send_mail_cod have less inputs used (3) than in the step definition (5) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 11449 doesn't seem to be define in the database( WARNING : type of input 2 of step 11452 doesn't seem to be define in the database( WARNING : output 1 of step 11449 have datatype=2 whereas input 1 of step 11453 have datatype=7 WARNING : type of output 2 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11454 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11456 doesn't seem to be define in the database( WARNING : type of output 1 of step 11456 doesn't seem to be define in the database( WARNING : type of input 3 of step 11455 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11456 have datatype=10 whereas input 3 of step 11458 have datatype=6 WARNING : type of input 5 of step 11458 doesn't seem to be define in the database( WARNING : output 0 of step 11477 have datatype=11 whereas input 5 of step 11458 have datatype=None WARNING : output 0 of step 11456 have datatype=10 whereas input 0 of step 11477 have datatype=18 WARNING : type of input 2 of step 11478 doesn't seem to be define in the database( WARNING : output 1 of step 11454 have datatype=7 whereas input 2 of step 11478 have datatype=None WARNING : type of output 3 of step 11478 doesn't seem to be define in the database( WARNING : type of input 2 of step 11456 doesn't seem to be define in the database( WARNING : output 0 of step 11453 have datatype=1 whereas input 0 of step 11454 have datatype=2 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=27298624 AND mptpi.`type`=3726 To do NUMBER BATCH : 0 # DISPLAY ALL COLLECTED DATA : {'26092025': {'nb_upload': 16, 'nb_taggue_class': 0, 'nb_taggue_densite': 0}} Inside saveOutput : final : True verbose : 0 saveOutput not yet implemented for datou_step.type : split_time_score we use saveGeneral [1386302361, 1386302357, 1386302345, 1386302319, 1386302302, 1386302286, 1386302284, 1386302079, 1386302050, 1386302018, 1386301983, 1386301953, 1386301925, 1386301882, 1386301877, 1386301860] Looping around the photos to save general results len do output : 1 /27268302Didn't retrieve data . before output type Here is an output not treated by saveGeneral : Managing all output in save final without adding information in the mtr_datou_result ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302361', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302357', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302345', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302319', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302302', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302286', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302284', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302079', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302050', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386302018', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386301983', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386301953', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386301925', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386301882', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386301877', None, None, None, None, None, '3784180') ('3318', None, None, None, None, None, None, None, '3784180') ('3318', '27268302', '1386301860', None, None, None, None, None, '3784180') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 17 time used for this insertion : 0.03730177879333496 save_final save missing photos in datou_result : time spend for datou_step_exec : 4.746156930923462 time spend to save output : 0.03762388229370117 total time spend for step 10 : 4.783780813217163 caffe_path_current : About to save ! 2 After save, about to update current ! ret : 2 len(input) + len(total_photo_id_missing) : 16 set_done_treatment 234.69user 173.53system 8:18.37elapsed 81%CPU (0avgtext+0avgdata 6141380maxresident)k 911360inputs+301880outputs (27964major+19577597minor)pagefaults 0swaps