python /home/admin/mtr/script_for_cron.py -j python_test3 -m 12 -a ' --short_python3 -v ' -s python_test3 -M 0 -S 0 -U 100,100,120 import MySQLdb succeeded Import error (python version) python version = 3 warning , we can't find thcl infos in json_data warning , we can't find pdt infos in json_data list_job_run_as_list : ['mask_detection', 'datou', 'CacheModelData_queries', 'CachePhotoData_queries', 'test_fork', 'prepare_maskdata', 'portfolio_queries', 'sla_mensuel'] python version used : 3 liste_fichiers : [('tests/mask_test', True, 'Test mask-detection ', 'mask_detection'), ('tests/datou_test', True, 'Datou All Test', 'datou', 'all'), ('mtr/database_queries/CacheModelData_queries', True, 'Test Cache Model Data', 'CacheModelData_queries'), ('tests/cache_photo_data_test', True, 'Test local_cache_photo ', 'CachePhotoData_queries'), ('mtr/mask_rcnn/prepare_maskdata', True, 'test prepare mask data', 'prepare_maskdata', 'all'), ('mtr/database_queries/portfolio_queries', True, 'test portfolio queries', 'portfolio_queries'), ('prod/memo/memo', True, 'SLA Mensuel', 'sla_mensuel', 'all')] #&_# BEGIN OF TEST : tests/mask_test #&_# /home/admin/workarea/git/Velours/python/tests/mask_test.py Test mask-detection python version used : 3 ############################### TEST memory used ################################ free memory at begining : begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 3337 run mask_detect Inside batchDatouExec : verbose : False # 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 ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! List Step Type Loaded in datou : mask_detect list_input_json : [] origin BFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 time to download the photos : 0.11569929122924805 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 : False number of steps : 1 step1:mask_detect Tue May 13 18:35:28 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 : 3337 max_wait_temp : 1 max_wait : 0 gpu_flag : 0 /home/admin/workarea/git/Velours/python/tests/python_tests.py:11: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses import imp 2025-05-13 18:35:31.818409: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2025-05-13 18:35:31.843112: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493065000 Hz 2025-05-13 18:35:31.844853: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f035c000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-05-13 18:35:31.844890: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-05-13 18:35:31.847717: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-05-13 18:35:32.091956: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7a211b0 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-05-13 18:35:32.092011: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-05-13 18:35:32.092902: 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 2025-05-13 18:35:32.093290: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-05-13 18:35:32.095873: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-05-13 18:35:32.099678: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-05-13 18:35:32.100419: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-05-13 18:35:32.105053: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-05-13 18:35:32.107306: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-05-13 18:35:32.114514: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-05-13 18:35:32.115781: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-05-13 18:35:32.115897: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-05-13 18:35:32.116513: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-05-13 18:35:32.116529: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-05-13 18:35:32.116539: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-05-13 18:35:32.117514: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 2885 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. Inside mask_sub_process Inside mask_detect About to load cache.load_thcl_param To do loadFromThcl(), then load ParamDescType : thcl454 thcls : [{'id': 454, 'mtr_user_id': 31, 'name': 'mask_coco_origin', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'backgroud,person,bicycle,car,motorcycle,airplane,bus,train,truck,boat,trafficlight,firehydrant,stopsign,parkingmeter,bench,bird,cat,dog,horse,sheep,cow,elephant,bear,zebra,giraffe,backpack,umbrella,handbag,tie,suitcase,frisbee,skis,snowboard,sportsball,kite,baseballbat,baseballglove,skateboard,surfboard,tennisracket,bottle,wineglass,cup,fork,knife,spoon,bowl,banana,apple,sandwich,orange,broccoli,carrot,hotdog,pizza,donut,cake,chair,couch,pottedplant,bed,diningtable,toilet,tv,laptop,mouse,remote,keyboard,cellphone,microwave,oven,toaster,sink,refrigerator,book,clock,vase,scissors,teddybear,hairdrier,toothbrush', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 445, 'photo_desc_type': 3473, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0'}] thcl {'id': 454, 'mtr_user_id': 31, 'name': 'mask_coco_origin', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'backgroud,person,bicycle,car,motorcycle,airplane,bus,train,truck,boat,trafficlight,firehydrant,stopsign,parkingmeter,bench,bird,cat,dog,horse,sheep,cow,elephant,bear,zebra,giraffe,backpack,umbrella,handbag,tie,suitcase,frisbee,skis,snowboard,sportsball,kite,baseballbat,baseballglove,skateboard,surfboard,tennisracket,bottle,wineglass,cup,fork,knife,spoon,bowl,banana,apple,sandwich,orange,broccoli,carrot,hotdog,pizza,donut,cake,chair,couch,pottedplant,bed,diningtable,toilet,tv,laptop,mouse,remote,keyboard,cellphone,microwave,oven,toaster,sink,refrigerator,book,clock,vase,scissors,teddybear,hairdrier,toothbrush', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 445, 'photo_desc_type': 3473, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0'} Update svm_hashtag_type_desc : 3473 FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (3473, 'mask_coco_origin', 16384, 25088, 'mask_coco_origin', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 1, datetime.datetime(2018, 3, 19, 10, 42, 21), datetime.datetime(2018, 3, 19, 10, 42, 21)) {'thcl': {'id': 454, 'mtr_user_id': 31, 'name': 'mask_coco_origin', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'backgroud,person,bicycle,car,motorcycle,airplane,bus,train,truck,boat,trafficlight,firehydrant,stopsign,parkingmeter,bench,bird,cat,dog,horse,sheep,cow,elephant,bear,zebra,giraffe,backpack,umbrella,handbag,tie,suitcase,frisbee,skis,snowboard,sportsball,kite,baseballbat,baseballglove,skateboard,surfboard,tennisracket,bottle,wineglass,cup,fork,knife,spoon,bowl,banana,apple,sandwich,orange,broccoli,carrot,hotdog,pizza,donut,cake,chair,couch,pottedplant,bed,diningtable,toilet,tv,laptop,mouse,remote,keyboard,cellphone,microwave,oven,toaster,sink,refrigerator,book,clock,vase,scissors,teddybear,hairdrier,toothbrush', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 445, 'photo_desc_type': 3473, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0'}, 'list_hashtags': ['backgroud', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sportsball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush'], 'list_hashtags_csv': 'backgroud,person,bicycle,car,motorcycle,airplane,bus,train,truck,boat,trafficlight,firehydrant,stopsign,parkingmeter,bench,bird,cat,dog,horse,sheep,cow,elephant,bear,zebra,giraffe,backpack,umbrella,handbag,tie,suitcase,frisbee,skis,snowboard,sportsball,kite,baseballbat,baseballglove,skateboard,surfboard,tennisracket,bottle,wineglass,cup,fork,knife,spoon,bowl,banana,apple,sandwich,orange,broccoli,carrot,hotdog,pizza,donut,cake,chair,couch,pottedplant,bed,diningtable,toilet,tv,laptop,mouse,remote,keyboard,cellphone,microwave,oven,toaster,sink,refrigerator,book,clock,vase,scissors,teddybear,hairdrier,toothbrush', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 445, 'svm_hashtag_type_desc': 3473, 'photo_desc_type': 3473, 'pb_hashtag_id_or_classifier': 0} list_class_names : ['backgroud', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sportsball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush'] 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 mask_coco_origin NUM_CLASSES 81 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 2025-05-13 18:35:32.752706: 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 2025-05-13 18:35:32.752796: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-05-13 18:35:32.752825: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-05-13 18:35:32.752852: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-05-13 18:35:32.752878: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-05-13 18:35:32.752904: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-05-13 18:35:32.752945: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-05-13 18:35:32.752972: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-05-13 18:35:32.754441: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-05-13 18:35:32.755833: 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 2025-05-13 18:35:32.755886: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-05-13 18:35:32.755914: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-05-13 18:35:32.755939: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-05-13 18:35:32.755964: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-05-13 18:35:32.755989: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-05-13 18:35:32.756014: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-05-13 18:35:32.756039: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-05-13 18:35:32.757493: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-05-13 18:35:32.757532: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-05-13 18:35:32.757547: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-05-13 18:35:32.757562: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-05-13 18:35:32.759199: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 2885 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. 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 : mask_coco_origin model_type : mask_rcnn list file need : ['mask_model.h5'] file exist in s3 : ['mask_model.h5'] file manque in s3 : [] 2025-05-13 18:35:41.249436: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-05-13 18:35:41.453640: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-05-13 18:35:42.824102: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:42.824764: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.09G (2241213184 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:42.825835: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.06GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-05-13 18:35:42.826416: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:42.826432: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.06GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-05-13 18:35:42.833487: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:42.833509: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.06GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-05-13 18:35:42.834058: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:42.834073: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.06GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-05-13 18:35:42.840609: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:42.840632: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 466.56MiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-05-13 18:35:42.841222: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:42.841239: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 466.56MiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-05-13 18:35:42.872121: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:42.872174: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.06GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-05-13 18:35:42.872727: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:42.872742: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.06GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-05-13 18:35:42.878522: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:42.878557: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 243.25MiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-05-13 18:35:42.879129: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:42.879147: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 243.25MiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-05-13 18:35:42.912885: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:42.913461: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:42.915363: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:42.915960: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:42.959682: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:42.960290: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:42.962480: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:42.963059: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:42.971205: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:42.971824: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:42.976332: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:42.976934: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:42.987627: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:42.988227: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:42.989766: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:42.990359: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:42.995851: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:42.996448: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:42.998143: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:42.998715: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.004520: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.005121: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.006728: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.007350: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.033611: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.034222: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.034779: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.035378: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.039029: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.039633: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.055081: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.055690: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.056309: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.056904: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.069217: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.069820: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.070405: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.071008: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.075265: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.075864: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.080336: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.080895: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.092663: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.093222: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.097246: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.097801: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.098350: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.098914: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.119960: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.120550: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.121116: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.121665: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.122249: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.122804: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.137628: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.138189: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.173656: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.173729: W tensorflow/core/kernels/gpu_utils.cc:49] Failed to allocate memory for convolution redzone checking; skipping this check. This is benign and only means that we won't check cudnn for out-of-bounds reads and writes. This message will only be printed once. 2025-05-13 18:35:43.174675: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.175607: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.183084: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.184015: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.184949: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.185863: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.194488: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.195461: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.211761: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.212756: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.213721: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.214667: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.219123: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.219977: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.220572: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.221161: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.222159: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.232270: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.232864: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.243051: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.243651: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.244252: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.244842: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.245441: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:35:43.246030: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory local folder : /data/models_weight/mask_coco_origin /data/models_weight/mask_coco_origin/mask_model.h5 size_local : 257557808 size in s3 : 257557808 create time local : 2021-08-09 05:27:17 create time in s3 : 2021-08-06 19:45:17 mask_model.h5 already exist and didn't need to update list_images length : 1 NEW PHOTO Processing 1 images image shape: (480, 640, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 89) min: 0.00000 max: 640.00000 nb d'objets trouves : 5 Detection mask done ! Trying to reset tf kernel 3823375 begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 2144 tf kernel not reseted sub process len(results) : 1 len(list_Values) 0 None max_time_sub_proc : 3600 parent process len(results) : 1 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 : 3337 list_Values should be empty [] To do loadFromThcl(), then load ParamDescType : thcl454 Catched exception ! Connect or reconnect ! thcls : [{'id': 454, 'mtr_user_id': 31, 'name': 'mask_coco_origin', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'backgroud,person,bicycle,car,motorcycle,airplane,bus,train,truck,boat,trafficlight,firehydrant,stopsign,parkingmeter,bench,bird,cat,dog,horse,sheep,cow,elephant,bear,zebra,giraffe,backpack,umbrella,handbag,tie,suitcase,frisbee,skis,snowboard,sportsball,kite,baseballbat,baseballglove,skateboard,surfboard,tennisracket,bottle,wineglass,cup,fork,knife,spoon,bowl,banana,apple,sandwich,orange,broccoli,carrot,hotdog,pizza,donut,cake,chair,couch,pottedplant,bed,diningtable,toilet,tv,laptop,mouse,remote,keyboard,cellphone,microwave,oven,toaster,sink,refrigerator,book,clock,vase,scissors,teddybear,hairdrier,toothbrush', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 445, 'photo_desc_type': 3473, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0'}] thcl {'id': 454, 'mtr_user_id': 31, 'name': 'mask_coco_origin', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'backgroud,person,bicycle,car,motorcycle,airplane,bus,train,truck,boat,trafficlight,firehydrant,stopsign,parkingmeter,bench,bird,cat,dog,horse,sheep,cow,elephant,bear,zebra,giraffe,backpack,umbrella,handbag,tie,suitcase,frisbee,skis,snowboard,sportsball,kite,baseballbat,baseballglove,skateboard,surfboard,tennisracket,bottle,wineglass,cup,fork,knife,spoon,bowl,banana,apple,sandwich,orange,broccoli,carrot,hotdog,pizza,donut,cake,chair,couch,pottedplant,bed,diningtable,toilet,tv,laptop,mouse,remote,keyboard,cellphone,microwave,oven,toaster,sink,refrigerator,book,clock,vase,scissors,teddybear,hairdrier,toothbrush', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 445, 'photo_desc_type': 3473, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0'} Update svm_hashtag_type_desc : 3473 ['backgroud', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sportsball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush'] time for calcul the mask position with numpy : 0.0005388259887695312 nb_pixel_total : 15551 time to create 1 rle with old method : 0.018198251724243164 length of segment : 256 time for calcul the mask position with numpy : 0.0027816295623779297 nb_pixel_total : 145330 time to create 1 rle with old method : 0.18774890899658203 length of segment : 371 time for calcul the mask position with numpy : 0.0002143383026123047 nb_pixel_total : 14254 time to create 1 rle with old method : 0.016396045684814453 length of segment : 151 time for calcul the mask position with numpy : 0.000110626220703125 nb_pixel_total : 5613 time to create 1 rle with old method : 0.006890535354614258 length of segment : 48 time for calcul the mask position with numpy : 5.4836273193359375e-05 nb_pixel_total : 1824 time to create 1 rle with old method : 0.0023221969604492188 length of segment : 39 time spent for convertir_results : 0.9814708232879639 time spend for datou_step_exec : 18.579670429229736 time spend to save output : 3.8623809814453125e-05 total time spend for step 1 : 18.57970905303955 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : False eke 12-6-18 : saveMask need to be cleaned for new output ! Number saved : None batch 1 Loaded 3331 chid ids of type : 445 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 0 begin to insert list_values into mtr_datou_result : length of list_values in save_final : 1 time used for this insertion : 0.014794588088989258 save missing photos in datou_result : After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : {'957285035': [[(957285035, 492601069, 445, 0, 186, 22, 282, 0.99548894, [(140, 26, 6), (135, 27, 15), (133, 28, 18), (131, 29, 22), (127, 30, 27), (10, 31, 1), (120, 31, 35), (8, 32, 13), (27, 32, 3), (115, 32, 41), (7, 33, 52), (109, 33, 48), (6, 34, 70), (103, 34, 55), (5, 35, 154), (4, 36, 155), (3, 37, 156), (3, 38, 156), (3, 39, 156), (2, 40, 157), (2, 41, 157), (2, 42, 157), (2, 43, 157), (2, 44, 157), (2, 45, 157), (1, 46, 158), (1, 47, 158), (1, 48, 158), (1, 49, 157), (1, 50, 157), (1, 51, 156), (1, 52, 156), (1, 53, 155), (1, 54, 154), (1, 55, 152), (1, 56, 149), (1, 57, 145), (1, 58, 141), (1, 59, 136), (1, 60, 133), (1, 61, 130), (1, 62, 127), (1, 63, 126), (1, 64, 124), (1, 65, 123), (1, 66, 121), (1, 67, 120), (1, 68, 118), (1, 69, 117), (1, 70, 116), (1, 71, 115), (1, 72, 114), (1, 73, 113), (1, 74, 112), (1, 75, 111), (1, 76, 110), (1, 77, 108), (1, 78, 108), (1, 79, 107), (1, 80, 106), (1, 81, 105), (2, 82, 104), (2, 83, 103), (2, 84, 103), (2, 85, 102), (2, 86, 102), (2, 87, 101), (2, 88, 100), (2, 89, 99), (2, 90, 99), (2, 91, 98), (2, 92, 97), (2, 93, 96), (2, 94, 95), (2, 95, 93), (2, 96, 91), (2, 97, 90), (2, 98, 89), (2, 99, 87), (2, 100, 86), (2, 101, 86), (2, 102, 85), (2, 103, 84), (2, 104, 83), (2, 105, 83), (2, 106, 82), (2, 107, 81), (2, 108, 80), (2, 109, 80), (2, 110, 79), (2, 111, 78), (2, 112, 77), (2, 113, 76), (1, 114, 76), (1, 115, 75), (1, 116, 74), (1, 117, 73), (1, 118, 72), (1, 119, 71), (1, 120, 71), (1, 121, 70), (1, 122, 69), (1, 123, 69), (1, 124, 68), (1, 125, 68), (1, 126, 67), (1, 127, 67), (1, 128, 66), (1, 129, 66), (1, 130, 66), (1, 131, 65), (1, 132, 65), (1, 133, 64), (1, 134, 63), (1, 135, 63), (1, 136, 62), (1, 137, 61), (1, 138, 60), (1, 139, 60), (1, 140, 59), (1, 141, 58), (1, 142, 58), (1, 143, 57), (1, 144, 56), (1, 145, 56), (1, 146, 55), (1, 147, 54), (1, 148, 54), (1, 149, 53), (1, 150, 52), (1, 151, 52), (1, 152, 51), (1, 153, 50), (1, 154, 49), (1, 155, 48), (1, 156, 47), (1, 157, 46), (1, 158, 45), (1, 159, 45), (1, 160, 44), (1, 161, 43), (1, 162, 42), (1, 163, 41), (1, 164, 41), (1, 165, 40), (1, 166, 40), (1, 167, 39), (1, 168, 38), (1, 169, 37), (1, 170, 36), (1, 171, 35), (1, 172, 34), (1, 173, 34), (1, 174, 33), (1, 175, 33), (1, 176, 32), (1, 177, 32), (1, 178, 32), (1, 179, 32), (1, 180, 31), (1, 181, 31), (1, 182, 31), (1, 183, 30), (1, 184, 30), (1, 185, 30), (1, 186, 29), (1, 187, 29), (1, 188, 29), (1, 189, 28), (1, 190, 28), (1, 191, 27), (1, 192, 27), (1, 193, 26), (1, 194, 26), (1, 195, 26), (1, 196, 26), (1, 197, 26), (1, 198, 26), (1, 199, 26), (1, 200, 25), (1, 201, 25), (1, 202, 25), (1, 203, 25), (1, 204, 25), (1, 205, 25), (1, 206, 25), (1, 207, 25), (1, 208, 25), (1, 209, 25), (1, 210, 25), (1, 211, 25), (1, 212, 25), (1, 213, 25), (1, 214, 25), (1, 215, 25), (1, 216, 25), (1, 217, 25), (1, 218, 25), (1, 219, 25), (1, 220, 24), (1, 221, 24), (1, 222, 24), (1, 223, 24), (1, 224, 24), (1, 225, 24), (1, 226, 25), (1, 227, 25), (1, 228, 25), (2, 229, 24), (2, 230, 24), (2, 231, 24), (2, 232, 23), (2, 233, 23), (2, 234, 23), (2, 235, 23), (2, 236, 23), (2, 237, 23), (2, 238, 23), (2, 239, 23), (2, 240, 23), (2, 241, 23), (2, 242, 23), (2, 243, 23), (2, 244, 23), (2, 245, 23), (2, 246, 23), (2, 247, 23), (2, 248, 23), (2, 249, 24), (2, 250, 24), (2, 251, 23), (2, 252, 23), (2, 253, 23), (2, 254, 23), (2, 255, 23), (2, 256, 23), (2, 257, 23), (2, 258, 23), (2, 259, 23), (2, 260, 23), (2, 261, 23), (3, 262, 22), (3, 263, 22), (3, 264, 22), (3, 265, 22), (4, 266, 21), (4, 267, 21), (5, 268, 20), (5, 269, 20), (6, 270, 19), (7, 271, 17), (8, 272, 16), (8, 273, 16), (9, 274, 13), (11, 275, 9), (15, 276, 2)], ['16,276,8,273,2,261,2,229,1,228,1,114,2,113,2,82,1,81,1,46,3,37,8,32,20,32,21,33,58,33,59,34,75,34,76,35,102,35,114,33,120,31,130,30,135,27,145,26,152,29,158,35,158,48,154,54,141,58,128,61,119,67,105,81,103,86,96,94,89,98,81,109,71,119,65,132,60,138,52,151,45,158,40,166,34,172,29,188,26,193,25,200,25,219,24,232,24,270,23,273']), (957285035, 492601069, 445, 29, 591, 24, 419, 0.99237627, [(315, 37, 25), (272, 38, 86), (253, 39, 130), (238, 40, 151), (199, 41, 196), (189, 42, 213), (180, 43, 238), (175, 44, 250), (172, 45, 257), (169, 46, 265), (166, 47, 274), (162, 48, 284), (159, 49, 294), (157, 50, 304), (155, 51, 311), (153, 52, 317), (151, 53, 323), (149, 54, 330), (148, 55, 334), (146, 56, 337), (144, 57, 341), (142, 58, 344), (140, 59, 347), (138, 60, 350), (136, 61, 353), (134, 62, 356), (132, 63, 358), (130, 64, 361), (128, 65, 364), (126, 66, 367), (124, 67, 370), (122, 68, 373), (120, 69, 376), (118, 70, 379), (117, 71, 381), (115, 72, 385), (114, 73, 387), (113, 74, 389), (112, 75, 391), (112, 76, 393), (111, 77, 395), (110, 78, 397), (109, 79, 399), (109, 80, 400), (108, 81, 402), (107, 82, 404), (107, 83, 404), (106, 84, 406), (105, 85, 408), (105, 86, 409), (104, 87, 410), (104, 88, 411), (103, 89, 413), (102, 90, 415), (101, 91, 417), (100, 92, 420), (98, 93, 423), (97, 94, 426), (96, 95, 428), (94, 96, 431), (93, 97, 433), (92, 98, 435), (91, 99, 437), (90, 100, 439), (89, 101, 441), (89, 102, 441), (89, 103, 442), (89, 104, 443), (89, 105, 444), (89, 106, 444), (89, 107, 445), (89, 108, 446), (89, 109, 447), (89, 110, 448), (89, 111, 449), (89, 112, 450), (89, 113, 451), (89, 114, 453), (89, 115, 454), (89, 116, 455), (88, 117, 456), (88, 118, 457), (87, 119, 459), (87, 120, 459), (86, 121, 461), (85, 122, 462), (85, 123, 463), (84, 124, 464), (84, 125, 465), (83, 126, 466), (82, 127, 468), (82, 128, 468), (81, 129, 470), (80, 130, 471), (78, 131, 473), (76, 132, 476), (75, 133, 477), (73, 134, 480), (71, 135, 482), (70, 136, 484), (68, 137, 486), (67, 138, 488), (65, 139, 490), (64, 140, 492), (63, 141, 493), (61, 142, 496), (60, 143, 497), (59, 144, 499), (58, 145, 501), (58, 146, 501), (57, 147, 503), (57, 148, 504), (57, 149, 505), (56, 150, 507), (56, 151, 507), (55, 152, 509), (55, 153, 510), (54, 154, 511), (54, 155, 512), (54, 156, 513), (53, 157, 514), (53, 158, 514), (52, 159, 515), (52, 160, 516), (52, 161, 516), (51, 162, 517), (51, 163, 517), (50, 164, 518), (50, 165, 518), (49, 166, 519), (49, 167, 520), (48, 168, 521), (48, 169, 521), (47, 170, 522), (47, 171, 522), (46, 172, 523), (46, 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(39, 298, 399), (39, 299, 397), (41, 300, 394), (42, 301, 392), (43, 302, 389), (44, 303, 387), (45, 304, 385), (46, 305, 382), (47, 306, 380), (47, 307, 378), (48, 308, 376), (49, 309, 373), (50, 310, 370), (51, 311, 368), (51, 312, 367), (52, 313, 365), (54, 314, 362), (55, 315, 360), (56, 316, 359), (58, 317, 356), (61, 318, 352), (64, 319, 349), (67, 320, 345), (70, 321, 341), (73, 322, 338), (75, 323, 335), (78, 324, 332), (80, 325, 329), (82, 326, 327), (84, 327, 324), (86, 328, 322), (88, 329, 320), (90, 330, 317), (93, 331, 314), (96, 332, 311), (99, 333, 307), (102, 334, 304), (105, 335, 300), (108, 336, 297), (111, 337, 294), (113, 338, 291), (115, 339, 289), (117, 340, 286), (119, 341, 283), (121, 342, 281), (123, 343, 278), (125, 344, 275), (127, 345, 272), (129, 346, 269), (132, 347, 266), (135, 348, 262), (138, 349, 258), (141, 350, 255), (143, 351, 252), (145, 352, 250), (147, 353, 247), (149, 354, 245), (151, 355, 242), (152, 356, 241), (154, 357, 239), (156, 358, 237), 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['321,407,296,403,263,401,215,388,206,382,178,371,168,363,140,349,110,336,90,330,77,323,56,316,39,299,31,273,31,236,34,199,58,145,79,131,89,116,89,101,104,88,115,72,159,49,180,43,199,41,237,41,272,38,339,37,382,39,402,43,460,50,481,55,543,116,556,143,566,156,568,167,566,186,554,199,548,216,528,235,496,256,471,275,460,281,414,315,403,339,392,355,389,371,383,385,369,400,358,405']), (957285035, 492601069, 445, 485, 636, 23, 174, 0.9711336, [(540, 24, 21), (626, 24, 3), (531, 25, 49), (594, 25, 40), (527, 26, 107), (523, 27, 111), (520, 28, 114), (517, 29, 118), (516, 30, 119), (515, 31, 120), (513, 32, 122), (512, 33, 123), (510, 34, 125), (509, 35, 126), (507, 36, 128), (506, 37, 129), (504, 38, 131), (503, 39, 132), (501, 40, 134), (500, 41, 135), (499, 42, 136), (498, 43, 137), (497, 44, 138), (496, 45, 139), (496, 46, 139), (495, 47, 140), (495, 48, 140), (494, 49, 141), (493, 50, 142), (492, 51, 143), (491, 52, 144), (491, 53, 144), (490, 54, 145), (490, 55, 145), (490, 56, 145), 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['598,172,591,172,586,170,578,168,573,164,573,162,568,152,568,149,566,145,566,136,565,132,561,125,560,121,556,116,547,109,543,108,536,104,531,99,527,97,491,62,490,54,495,48,496,45,501,40,514,32,517,29,531,25,539,25,540,24,560,24,561,25,579,25,580,26,593,26,594,25,633,25,634,29,634,56,635,57,635,111,634,112,634,129,632,134,629,138,623,141,619,145,617,149,611,155,608,161,604,166']), (957285035, 492601069, 445, 280, 481, 2, 55, 0.82978296, [(292, 3, 128), (284, 4, 146), (282, 5, 151), (281, 6, 154), (281, 7, 156), (281, 8, 157), (281, 9, 158), (281, 10, 160), (281, 11, 162), (281, 12, 165), (281, 13, 167), (281, 14, 169), (281, 15, 171), (281, 16, 173), (281, 17, 174), (281, 18, 175), (281, 19, 177), (281, 20, 178), (281, 21, 179), (281, 22, 180), (281, 23, 181), (281, 24, 182), (281, 25, 183), (281, 26, 184), (281, 27, 185), (281, 28, 185), (281, 29, 185), (282, 30, 185), (283, 31, 27), (337, 31, 131), (371, 32, 97), (401, 33, 68), (409, 34, 61), (419, 35, 52), (424, 36, 48), (429, 37, 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(474, 33, 36), (475, 34, 33), (475, 35, 32), (476, 36, 30), (476, 37, 29), (477, 38, 26), (478, 39, 23), (479, 40, 20), (480, 41, 17), (488, 42, 5)], ['492,42,488,42,487,41,480,41,476,37,475,34,473,32,469,25,465,21,461,20,457,16,457,10,463,10,464,9,466,9,470,12,474,13,476,11,480,10,482,8,500,8,501,9,524,9,525,10,528,10,532,12,539,12,542,15,545,15,545,19,535,20,534,21,529,21,525,23,523,23,513,30,512,30,504,37,496,41,493,41'])], 'temp/1747154128_3823001_957285035_a42482e51c93c8025d243dd179aee85b.jpg']} free memory after detection : begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 3337 ############################### TEST detect object ################################ run mask_detect Inside batchDatouExec : verbose : False # 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 ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! List Step Type Loaded in datou : mask_detect list_input_json : [] origin BFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 time to download the photos : 0.11167359352111816 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 : False number of steps : 1 step1:mask_detect Tue May 13 18:35:49 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec 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 : 3337 max_wait_temp : 1 max_wait : 0 gpu_flag : 0 2025-05-13 18:35:52.057559: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2025-05-13 18:35:52.083167: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493065000 Hz 2025-05-13 18:35:52.085197: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f035c000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-05-13 18:35:52.085254: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-05-13 18:35:52.089690: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-05-13 18:35:52.333455: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x8189ee0 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-05-13 18:35:52.333527: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-05-13 18:35:52.334869: 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 2025-05-13 18:35:52.335405: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-05-13 18:35:52.338611: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-05-13 18:35:52.341491: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-05-13 18:35:52.341998: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-05-13 18:35:52.344802: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-05-13 18:35:52.346196: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-05-13 18:35:52.351302: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-05-13 18:35:52.352618: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-05-13 18:35:52.352726: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-05-13 18:35:52.353307: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-05-13 18:35:52.353323: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-05-13 18:35:52.353333: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-05-13 18:35:52.354313: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 2885 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. 2025-05-13 18:35:52.437772: 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 2025-05-13 18:35:52.437906: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-05-13 18:35:52.437933: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-05-13 18:35:52.437957: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-05-13 18:35:52.437980: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-05-13 18:35:52.438003: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-05-13 18:35:52.438026: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-05-13 18:35:52.438049: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-05-13 18:35:52.439225: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-05-13 18:35:52.440364: 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 2025-05-13 18:35:52.440438: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-05-13 18:35:52.440460: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-05-13 18:35:52.440479: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-05-13 18:35:52.440498: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-05-13 18:35:52.440517: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-05-13 18:35:52.440536: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-05-13 18:35:52.440555: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-05-13 18:35:52.441395: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-05-13 18:35:52.441430: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-05-13 18:35:52.441439: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-05-13 18:35:52.441447: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-05-13 18:35:52.442340: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 2885 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 FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (3473, 'mask_coco_origin', 16384, 25088, 'mask_coco_origin', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 1, datetime.datetime(2018, 3, 19, 10, 42, 21), datetime.datetime(2018, 3, 19, 10, 42, 21)) {'thcl': {'id': 454, 'mtr_user_id': 31, 'name': 'mask_coco_origin', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'backgroud,person,bicycle,car,motorcycle,airplane,bus,train,truck,boat,trafficlight,firehydrant,stopsign,parkingmeter,bench,bird,cat,dog,horse,sheep,cow,elephant,bear,zebra,giraffe,backpack,umbrella,handbag,tie,suitcase,frisbee,skis,snowboard,sportsball,kite,baseballbat,baseballglove,skateboard,surfboard,tennisracket,bottle,wineglass,cup,fork,knife,spoon,bowl,banana,apple,sandwich,orange,broccoli,carrot,hotdog,pizza,donut,cake,chair,couch,pottedplant,bed,diningtable,toilet,tv,laptop,mouse,remote,keyboard,cellphone,microwave,oven,toaster,sink,refrigerator,book,clock,vase,scissors,teddybear,hairdrier,toothbrush', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 445, 'photo_desc_type': 3473, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0'}, 'list_hashtags': ['backgroud', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sportsball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush'], 'list_hashtags_csv': 'backgroud,person,bicycle,car,motorcycle,airplane,bus,train,truck,boat,trafficlight,firehydrant,stopsign,parkingmeter,bench,bird,cat,dog,horse,sheep,cow,elephant,bear,zebra,giraffe,backpack,umbrella,handbag,tie,suitcase,frisbee,skis,snowboard,sportsball,kite,baseballbat,baseballglove,skateboard,surfboard,tennisracket,bottle,wineglass,cup,fork,knife,spoon,bowl,banana,apple,sandwich,orange,broccoli,carrot,hotdog,pizza,donut,cake,chair,couch,pottedplant,bed,diningtable,toilet,tv,laptop,mouse,remote,keyboard,cellphone,microwave,oven,toaster,sink,refrigerator,book,clock,vase,scissors,teddybear,hairdrier,toothbrush', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 445, 'svm_hashtag_type_desc': 3473, 'photo_desc_type': 3473, 'pb_hashtag_id_or_classifier': 0} list_class_names : ['backgroud', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sportsball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush'] 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 mask_coco_origin NUM_CLASSES 81 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 : mask_coco_origin model_type : mask_rcnn list file need : ['mask_model.h5'] file exist in s3 : ['mask_model.h5'] file manque in s3 : [] 2025-05-13 18:36:00.260403: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-05-13 18:36:00.456965: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-05-13 18:36:01.836841: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:01.837985: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.09G (2241213184 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:01.838094: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.06GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-05-13 18:36:01.839298: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:01.839362: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.06GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-05-13 18:36:01.849855: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:01.849967: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.06GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-05-13 18:36:01.851073: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:01.851119: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.06GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-05-13 18:36:01.859851: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:01.859971: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 466.56MiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-05-13 18:36:01.860722: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:01.860762: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 466.56MiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-05-13 18:36:01.905810: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:01.906006: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.06GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-05-13 18:36:01.907303: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:01.907376: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.06GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-05-13 18:36:01.915688: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:01.915810: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 243.25MiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-05-13 18:36:01.916954: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:01.917008: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 243.25MiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-05-13 18:36:01.962758: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:01.963679: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:01.965978: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:01.966788: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.012308: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.012920: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.015245: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.015884: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.024206: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.024822: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.030080: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.030695: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.043874: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.044545: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.046331: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.046935: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.053006: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.053597: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.055443: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.056081: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.062132: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.062725: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.064421: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.065013: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.093652: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.094259: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.094833: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.095457: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.099161: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.099772: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.115868: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.116467: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.117042: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.117628: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.130226: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.130830: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.131480: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.132117: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.136612: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.137211: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.141967: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.142542: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.154545: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.155170: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.159333: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.159962: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.160581: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.161164: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.182389: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.183001: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.183664: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.184289: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.184909: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.185528: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.201053: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.201639: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.225055: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.225133: W tensorflow/core/kernels/gpu_utils.cc:49] Failed to allocate memory for convolution redzone checking; skipping this check. This is benign and only means that we won't check cudnn for out-of-bounds reads and writes. This message will only be printed once. 2025-05-13 18:36:02.226141: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.227145: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.234456: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.235207: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.235908: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.236603: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.245350: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.246052: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.262177: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.263015: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.263814: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.264580: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.269050: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.269838: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.270595: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.271405: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.272639: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.283029: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.283676: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.294389: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.295048: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.295673: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.296294: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.296935: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:02.297560: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.32G (2490236928 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory local folder : /data/models_weight/mask_coco_origin /data/models_weight/mask_coco_origin/mask_model.h5 size_local : 257557808 size in s3 : 257557808 create time local : 2021-08-09 05:27:17 create time in s3 : 2021-08-06 19:45:17 mask_model.h5 already exist and didn't need to update list_images length : 1 NEW PHOTO Processing 1 images image shape: (720, 1280, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 89) min: 0.00000 max: 1280.00000 nb d'objets trouves : 4 Detection mask done ! Trying to reset tf kernel 3824257 begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 2144 tf kernel not reseted sub process len(results) : 1 len(list_Values) 0 None max_time_sub_proc : 3600 parent process len(results) : 1 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 : 3337 list_Values should be empty [] ['backgroud', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sportsball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush'] time for calcul the mask position with numpy : 0.0024671554565429688 nb_pixel_total : 16902 time to create 1 rle with old method : 0.04560542106628418 length of segment : 107 time for calcul the mask position with numpy : 0.03651165962219238 nb_pixel_total : 480738 time to create 1 rle with new method : 0.03206968307495117 length of segment : 632 time for calcul the mask position with numpy : 0.0004470348358154297 nb_pixel_total : 36642 time to create 1 rle with old method : 0.04290199279785156 length of segment : 133 time for calcul the mask position with numpy : 0.00021076202392578125 nb_pixel_total : 4794 time to create 1 rle with old method : 0.008965492248535156 length of segment : 51 time spent for convertir_results : 0.3682742118835449 time spend for datou_step_exec : 16.61359691619873 time spend to save output : 3.7670135498046875e-05 total time spend for step 1 : 16.61363458633423 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : False eke 12-6-18 : saveMask need to be cleaned for new output ! Catched exception ! Connect or reconnect ! Number saved : None batch 1 Loaded 427 chid ids of type : 445 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 0 begin to insert list_values into mtr_datou_result : length of list_values in save_final : 1 time used for this insertion : 0.019812345504760742 save missing photos in datou_result : After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : {'917855882': [[(917855882, 492601069, 445, 1092, 1280, 0, 108, 0.9988374, [(1205, 1, 58), (1165, 2, 105), (1159, 3, 113), (1149, 4, 124), (1113, 5, 161), (1100, 6, 174), (1097, 7, 177), (1095, 8, 179), (1095, 9, 179), (1095, 10, 179), (1095, 11, 179), (1095, 12, 179), (1095, 13, 179), (1095, 14, 178), (1095, 15, 178), (1095, 16, 178), (1095, 17, 178), (1095, 18, 177), (1095, 19, 177), (1095, 20, 177), (1095, 21, 177), (1095, 22, 177), (1095, 23, 178), (1095, 24, 178), (1095, 25, 178), (1095, 26, 179), (1095, 27, 179), (1095, 28, 180), (1095, 29, 181), (1095, 30, 182), (1095, 31, 183), (1095, 32, 183), (1095, 33, 184), (1095, 34, 184), (1096, 35, 183), (1096, 36, 183), (1096, 37, 184), (1097, 38, 183), (1097, 39, 183), (1097, 40, 183), (1098, 41, 182), (1098, 42, 182), (1098, 43, 182), (1099, 44, 181), (1099, 45, 181), (1099, 46, 181), (1100, 47, 180), (1100, 48, 180), (1101, 49, 179), (1101, 50, 179), (1102, 51, 178), (1102, 52, 178), (1103, 53, 177), (1103, 54, 177), (1104, 55, 176), (1104, 56, 176), (1104, 57, 176), (1104, 58, 176), (1105, 59, 175), (1105, 60, 175), (1105, 61, 175), (1105, 62, 175), (1105, 63, 175), (1106, 64, 174), (1106, 65, 174), (1106, 66, 174), (1106, 67, 174), (1106, 68, 174), (1106, 69, 174), (1106, 70, 174), (1106, 71, 174), (1106, 72, 174), (1106, 73, 174), (1107, 74, 173), (1107, 75, 173), (1107, 76, 173), (1107, 77, 173), (1107, 78, 173), (1107, 79, 173), (1108, 80, 172), (1108, 81, 172), (1109, 82, 171), (1110, 83, 170), (1110, 84, 170), (1111, 85, 169), (1112, 86, 168), (1113, 87, 166), (1114, 88, 165), (1115, 89, 164), (1117, 90, 162), (1120, 91, 159), (1138, 92, 141), (1146, 93, 133), (1154, 94, 125), (1167, 95, 112), (1177, 96, 102), (1183, 97, 95), (1185, 98, 93), (1187, 99, 90), (1188, 100, 55), (1264, 100, 12), (1190, 101, 50), (1191, 102, 46), (1194, 103, 40), (1197, 104, 34), (1202, 105, 25), (1207, 106, 16)], ['1222,106,1207,106,1206,105,1197,104,1191,102,1182,96,1176,95,1167,95,1166,94,1154,94,1153,93,1146,93,1145,92,1137,91,1120,91,1115,89,1110,84,1107,79,1106,73,1106,64,1104,55,1099,46,1095,34,1095,8,1100,6,1112,6,1113,5,1148,5,1149,4,1158,4,1165,2,1204,2,1205,1,1262,1,1269,2,1273,5,1273,13,1271,18,1271,22,1273,27,1277,31,1279,37,1279,86,1278,87,1278,96,1275,100,1264,100,1263,99,1243,99,1230,104']), (917855882, 492601069, 445, 52, 1128, 16, 668, 0.9977469, [(711, 22, 21), (925, 22, 47), (608, 23, 146), (894, 23, 103), (598, 24, 234), (850, 24, 158), (590, 25, 427), (582, 26, 444), (575, 27, 458), (569, 28, 466), (565, 29, 472), (560, 30, 480), (556, 31, 486), (550, 32, 495), (544, 33, 503), (538, 34, 512), (532, 35, 520), (527, 36, 527), (523, 37, 534), (518, 38, 541), (514, 39, 548), (510, 40, 554), (506, 41, 561), (503, 42, 566), (499, 43, 572), (496, 44, 577), (493, 45, 582), (490, 46, 586), (488, 47, 590), (487, 48, 592), (485, 49, 595), (483, 50, 598), (482, 51, 600), (481, 52, 602), (480, 53, 603), (479, 54, 605), (478, 55, 606), (476, 56, 608), (475, 57, 610), (474, 58, 611), (473, 59, 613), (472, 60, 614), (470, 61, 616), (469, 62, 618), (468, 63, 619), (466, 64, 621), (465, 65, 623), (464, 66, 624), (462, 67, 626), (461, 68, 628), (459, 69, 630), (458, 70, 631), (456, 71, 633), (455, 72, 635), (453, 73, 637), (452, 74, 638), (451, 75, 639), (450, 76, 640), (448, 77, 642), (447, 78, 643), (446, 79, 644), (445, 80, 645), (444, 81, 646), (442, 82, 648), (441, 83, 649), (440, 84, 650), (439, 85, 651), (438, 86, 652), (437, 87, 653), (436, 88, 654), (435, 89, 655), (434, 90, 656), (433, 91, 657), (432, 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0, 54, 0.9392232, [(414, 0, 7), (441, 0, 60), (508, 0, 28), (402, 1, 142), (401, 2, 146), (402, 3, 145), (404, 4, 143), (406, 5, 140), (408, 6, 137), (410, 7, 134), (411, 8, 132), (412, 9, 130), (413, 10, 127), (414, 11, 125), (415, 12, 123), (415, 13, 122), (416, 14, 120), (417, 15, 117), (417, 16, 116), (418, 17, 114), (418, 18, 113), (418, 19, 111), (418, 20, 109), (419, 21, 107), (419, 22, 105), (419, 23, 103), (419, 24, 102), (419, 25, 100), (420, 26, 97), (420, 27, 95), (420, 28, 94), (421, 29, 91), (421, 30, 90), (422, 31, 88), (422, 32, 88), (422, 33, 87), (423, 34, 84), (423, 35, 82), (423, 36, 81), (424, 37, 79), (424, 38, 77), (424, 39, 75), (424, 40, 73), (424, 41, 71), (425, 42, 67), (425, 43, 66), (426, 44, 62), (426, 45, 6), (433, 45, 52), (443, 46, 30), (450, 47, 1)], ['450,47,449,46,443,46,442,45,426,45,424,41,424,37,423,36,422,31,419,25,419,21,418,20,418,17,417,15,409,6,402,3,402,1,413,1,414,0,420,0,421,1,440,1,441,0,500,0,501,1,507,1,508,0,535,0,536,1,543,1,546,2,546,4,542,8,530,18,527,19,525,21,522,22,520,24,512,28,508,33,505,34,502,37,494,41,492,41,490,43,488,43,484,45,473,45,472,46,451,46'])], 'temp/1747154149_3823001_917855882_da0fa7b7e6b5b551fe26c0ba8713276d.jpg']} ############################### TEST POLYGON ################################ Inside batchDatouExec : verbose : False # 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 ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! List Step Type Loaded in datou : mask_detect list_input_json : [] origin BFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 time to download the photos : 0.13967347145080566 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 : False number of steps : 1 step1:mask_detect Tue May 13 18:36:07 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 : 2922 max_wait_temp : 1 max_wait : 0 gpu_flag : 0 2025-05-13 18:36:10.266754: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2025-05-13 18:36:10.295464: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493065000 Hz 2025-05-13 18:36:10.297491: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f035c000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-05-13 18:36:10.297525: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-05-13 18:36:10.301668: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-05-13 18:36:10.439087: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x89814f0 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-05-13 18:36:10.439146: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-05-13 18:36:10.440236: 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 2025-05-13 18:36:10.440718: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-05-13 18:36:10.444170: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-05-13 18:36:10.447356: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-05-13 18:36:10.447773: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-05-13 18:36:10.451248: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-05-13 18:36:10.452903: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-05-13 18:36:10.457818: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-05-13 18:36:10.458859: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-05-13 18:36:10.458966: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-05-13 18:36:10.459547: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-05-13 18:36:10.459566: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-05-13 18:36:10.459576: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-05-13 18:36:10.460464: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 2086 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. 2025-05-13 18:36:10.548101: 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 2025-05-13 18:36:10.548305: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-05-13 18:36:10.548338: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-05-13 18:36:10.548368: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-05-13 18:36:10.548407: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-05-13 18:36:10.548438: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-05-13 18:36:10.548482: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-05-13 18:36:10.548523: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-05-13 18:36:10.549659: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-05-13 18:36:10.550864: 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 2025-05-13 18:36:10.550928: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-05-13 18:36:10.550955: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-05-13 18:36:10.550977: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-05-13 18:36:10.550998: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-05-13 18:36:10.551020: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-05-13 18:36:10.551041: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-05-13 18:36:10.551079: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-05-13 18:36:10.552073: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-05-13 18:36:10.552123: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-05-13 18:36:10.552137: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-05-13 18:36:10.552151: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-05-13 18:36:10.553328: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 2086 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 FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (3473, 'mask_coco_origin', 16384, 25088, 'mask_coco_origin', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 1, datetime.datetime(2018, 3, 19, 10, 42, 21), datetime.datetime(2018, 3, 19, 10, 42, 21)) {'thcl': {'id': 454, 'mtr_user_id': 31, 'name': 'mask_coco_origin', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'backgroud,person,bicycle,car,motorcycle,airplane,bus,train,truck,boat,trafficlight,firehydrant,stopsign,parkingmeter,bench,bird,cat,dog,horse,sheep,cow,elephant,bear,zebra,giraffe,backpack,umbrella,handbag,tie,suitcase,frisbee,skis,snowboard,sportsball,kite,baseballbat,baseballglove,skateboard,surfboard,tennisracket,bottle,wineglass,cup,fork,knife,spoon,bowl,banana,apple,sandwich,orange,broccoli,carrot,hotdog,pizza,donut,cake,chair,couch,pottedplant,bed,diningtable,toilet,tv,laptop,mouse,remote,keyboard,cellphone,microwave,oven,toaster,sink,refrigerator,book,clock,vase,scissors,teddybear,hairdrier,toothbrush', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 445, 'photo_desc_type': 3473, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0'}, 'list_hashtags': ['backgroud', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sportsball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush'], 'list_hashtags_csv': 'backgroud,person,bicycle,car,motorcycle,airplane,bus,train,truck,boat,trafficlight,firehydrant,stopsign,parkingmeter,bench,bird,cat,dog,horse,sheep,cow,elephant,bear,zebra,giraffe,backpack,umbrella,handbag,tie,suitcase,frisbee,skis,snowboard,sportsball,kite,baseballbat,baseballglove,skateboard,surfboard,tennisracket,bottle,wineglass,cup,fork,knife,spoon,bowl,banana,apple,sandwich,orange,broccoli,carrot,hotdog,pizza,donut,cake,chair,couch,pottedplant,bed,diningtable,toilet,tv,laptop,mouse,remote,keyboard,cellphone,microwave,oven,toaster,sink,refrigerator,book,clock,vase,scissors,teddybear,hairdrier,toothbrush', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 445, 'svm_hashtag_type_desc': 3473, 'photo_desc_type': 3473, 'pb_hashtag_id_or_classifier': 0} list_class_names : ['backgroud', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sportsball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush'] 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 mask_coco_origin NUM_CLASSES 81 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 : mask_coco_origin model_type : mask_rcnn list file need : ['mask_model.h5'] file exist in s3 : ['mask_model.h5'] file manque in s3 : [] 2025-05-13 18:36:20.369444: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-05-13 18:36:20.553566: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-05-13 18:36:21.942069: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.06GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-05-13 18:36:21.942154: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.06GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-05-13 18:36:21.951022: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.06GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-05-13 18:36:21.951046: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.06GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-05-13 18:36:22.005390: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.06GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-05-13 18:36:22.005456: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.06GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-05-13 18:36:22.052895: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.09GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-05-13 18:36:22.052966: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.09GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-05-13 18:36:22.111985: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.15GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-05-13 18:36:22.112048: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.15GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-05-13 18:36:22.113732: W tensorflow/core/common_runtime/bfc_allocator.cc:311] Garbage collection: deallocate free memory regions (i.e., allocations) so that we can re-allocate a larger region to avoid OOM due to memory fragmentation. If you see this message frequently, you are running near the threshold of the available device memory and re-allocation may incur great performance overhead. You may try smaller batch sizes to observe the performance impact. Set TF_ENABLE_GPU_GARBAGE_COLLECTION=false if you'd like to disable this feature. 2025-05-13 18:36:22.132849: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.54G (1652424704 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:22.133822: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.38G (1487182336 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-05-13 18:36:22.134787: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.25G (1338464256 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory local folder : /data/models_weight/mask_coco_origin /data/models_weight/mask_coco_origin/mask_model.h5 size_local : 257557808 size in s3 : 257557808 create time local : 2021-08-09 05:27:17 create time in s3 : 2021-08-06 19:45:17 mask_model.h5 already exist and didn't need to update list_images length : 1 NEW PHOTO Processing 1 images image shape: (2448, 2448, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 89) min: 0.00000 max: 2448.00000 nb d'objets trouves : 1 Detection mask done ! Trying to reset tf kernel 3825405 begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 11 tf kernel not reseted sub process len(results) : 1 len(list_Values) 0 None max_time_sub_proc : 3600 parent process len(results) : 1 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 : 2354 list_Values should be empty [] ['backgroud', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sportsball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush'] time for calcul the mask position with numpy : 0.86328125 nb_pixel_total : 3690323 time to create 1 rle with new method : 0.48927879333496094 length of segment : 2035 time spent for convertir_results : 2.3428409099578857 time spend for datou_step_exec : 20.961238384246826 time spend to save output : 5.507469177246094e-05 total time spend for step 1 : 20.9612934589386 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : False eke 12-6-18 : saveMask need to be cleaned for new output ! Catched exception ! Connect or reconnect ! Number saved : None batch 1 Loaded 722 chid ids of type : 445 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++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RLEs to save : 0 begin to insert list_values into mtr_datou_result : length of list_values in save_final : 1 time used for this insertion : 0.01426076889038086 save missing photos in datou_result : After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : {'917877156': [[(917877156, 492601069, 445, 3, 2264, 122, 2233, 0.9846028, [(520, 124, 446), (1152, 124, 272), (500, 125, 949), (480, 126, 993), (462, 127, 1034), (444, 128, 1098), (429, 129, 1151), (415, 130, 1174), (401, 131, 1196), (388, 132, 1217), (376, 133, 1237), (366, 134, 1255), (363, 135, 1265), (360, 136, 1275), (358, 137, 1284), (355, 138, 1294), (353, 139, 1302), (351, 140, 1309), (348, 141, 1317), (346, 142, 1323), (344, 143, 1329), (342, 144, 1335), (340, 145, 1341), (339, 146, 1346), (337, 147, 1352), (335, 148, 1357), (333, 149, 1363), (332, 150, 1367), (330, 151, 1372), (329, 152, 1376), (327, 153, 1381), (326, 154, 1385), (324, 155, 1390), (323, 156, 1394), (321, 157, 1399), (320, 158, 1402), (319, 159, 1406), (318, 160, 1410), (316, 161, 1414), (315, 162, 1418), (314, 163, 1421), (313, 164, 1425), (311, 165, 1429), (310, 166, 1432), (309, 167, 1436), (307, 168, 1440), (306, 169, 1443), (304, 170, 1447), (303, 171, 1450), (301, 172, 1455), (300, 173, 1458), (298, 174, 1463), (296, 175, 1467), (294, 176, 1472), (293, 177, 1476), (291, 178, 1480), (289, 179, 1485), (287, 180, 1490), (284, 181, 1496), (282, 182, 1502), (279, 183, 1508), (276, 184, 1514), (274, 185, 1520), (271, 186, 1527), (268, 187, 1534), (265, 188, 1541), (263, 189, 1547), (260, 190, 1554), (257, 191, 1561), (254, 192, 1570), (252, 193, 1578), (249, 194, 1588), (246, 195, 1597), (243, 196, 1606), (240, 197, 1615), (238, 198, 1623), (235, 199, 1632), (232, 200, 1641), (229, 201, 1650), (226, 202, 1659), (224, 203, 1667), (221, 204, 1676), (218, 205, 1683), (215, 206, 1688), (212, 207, 1693), (209, 208, 1698), (206, 209, 1703), (204, 210, 1707), (202, 211, 1710), (200, 212, 1714), (199, 213, 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: 3683980 proportion of common points : 0.9977480130921283 [('test release memory', 'SUCCESS', True), ('test detect objet', 'SUCCESS', True), ('test polygone', 'SUCCESS', True)] res_total : True #&_# TEST SUCCEEDED #&_# : tests/mask_test #&_# /home/admin/workarea/git/Velours/python/tests/python_tests.py refs/heads/master_6b55ca732dc5789dd54794d418371b3abe63c01d SQL :INSERT INTO MTRAdmin.monitor_sys (name, type, server, version_code, result_str, result_bool, lien , test_group ,test_name) VALUES ('python_test3','1','marlene','refs/heads/master_6b55ca732dc5789dd54794d418371b3abe63c01d','{"mask_detection": "success"}','1','http://marlene.fotonower-preprod.com/job/2025/May/13052025/python_test3//data_2/data_log/job/2025/May/13052025/python_test3/log-python3----short_python3--v--marlene-18:35:02.txt','mask_detection','unknown'); #&_# END OF TEST #&_# : tests/mask_test #&_# #&_# BEGIN OF TEST : tests/datou_test #&_# /home/admin/workarea/git/Velours/python/tests/datou_test.py Datou All Test python version used : 3 ############################### TEST sam ################################ TEST SAM Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=4573 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=4573 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 4573 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=4573 # 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 ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! no param json to modify List Step Type Loaded in datou : sam list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT photo_id, url FROM MTRBack.photos ph WHERE photo_id IN (1189321094) Found this number of photos: 1 ##### Call download_photos : nb_thread : 5 begin to download photo : 1189321094 download finish for photo 1189321094 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 ##### After load_data_input time to download the photos : 0.18040108680725098 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! WARNING : we have an input that is not a photo, we should get rid of it Calling datou_exec Inside datou_exec : verbose : True number of steps : 1 step1:sam Tue May 13 18:36:34 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 After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1747154193_3823001_1189321094_9626af7f95d010f2a4fd524688d4ea22_76896585.png': 1189321094} map_photo_id_path_extension : {1189321094: {'path': 'temp/1747154193_3823001_1189321094_9626af7f95d010f2a4fd524688d4ea22_76896585.png', 'extension': 'png'}} map_subphoto_mainphoto : {} Beginning of datou step sam ! pht : 4677 Inside sam : nb paths : 1 (640, 960, 3) ERROR in datou_step_exec, will save and exit ! CUDA out of memory. Tried to allocate 768.00 MiB (GPU 0; 10.76 GiB total capacity; 443.59 MiB already allocated; 331.88 MiB free; 498.00 MiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF File "/home/admin/workarea/git/Velours/python/mtr/datou/datou_lib.py", line 2329, in datou_exec output = datou_step_exec(sNext, args, cache, context, map_info, verbose, mtr_user_id) File "/home/admin/workarea/git/Velours/python/mtr/datou/datou_lib.py", line 2430, in datou_step_exec return lib_process.datou_step_sam(param, json_param, args, cache, context, map_info, verbose) File "/home/admin/workarea/git/Velours/python/mtr/datou/lib_step_exec/lib_step_process.py", line 396, in datou_step_sam masks = mask_generator.generate(image) File "/home/admin/.local/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context return func(*args, **kwargs) File "/home/admin/workarea/install/segment-anything/segment_anything/automatic_mask_generator.py", line 163, in generate mask_data = self._generate_masks(image) File "/home/admin/workarea/install/segment-anything/segment_anything/automatic_mask_generator.py", line 206, in _generate_masks crop_data = self._process_crop(image, crop_box, layer_idx, orig_size) File "/home/admin/workarea/install/segment-anything/segment_anything/automatic_mask_generator.py", line 236, in _process_crop self.predictor.set_image(cropped_im) File "/home/admin/workarea/install/segment-anything/segment_anything/predictor.py", line 60, in set_image self.set_torch_image(input_image_torch, image.shape[:2]) File "/home/admin/.local/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context return func(*args, **kwargs) File "/home/admin/workarea/install/segment-anything/segment_anything/predictor.py", line 89, in set_torch_image self.features = self.model.image_encoder(input_image) File "/home/admin/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl return forward_call(*input, **kwargs) File "/home/admin/workarea/install/segment-anything/segment_anything/modeling/image_encoder.py", line 112, in forward x = blk(x) File "/home/admin/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl return forward_call(*input, **kwargs) File "/home/admin/workarea/install/segment-anything/segment_anything/modeling/image_encoder.py", line 174, in forward x = self.attn(x) File "/home/admin/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl return forward_call(*input, **kwargs) File "/home/admin/workarea/install/segment-anything/segment_anything/modeling/image_encoder.py", line 231, in forward attn = (q * self.scale) @ k.transpose(-2, -1) [1189321094] map_info['map_portfolio_photo'] : {} final : True mtd_id 4573 list_pids : [1189321094] begin to insert list_values into mtr_datou_result : length of list_values in save_final : 1 insert ignore into MTRPhoto.mtr_datou_result (mtd_id, mtr_portfolio_id,mtr_photo_id,result,result_long,result_double,hashtag_id,proba, mtr_current_id) values (%s,%s,%s,%s,%s,%s,%s,%s,%s) on duplicate key update mtr_portfolio_id = mtr_portfolio_id list_values : [('4573', None, '1189321094', "[>, , , , , 'CUDA out of memory. Tried to allocate 768.00 MiB (GPU 0; 10.76 GiB total capacity; 443.59 MiB already allocated; 331.88 MiB free; 498.00 MiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF']", '-1', '-1.0', '501120777', '1.0', None)] time used for this insertion : 0.013545751571655273 save_final ERROR in last step sam, CUDA out of memory. Tried to allocate 768.00 MiB (GPU 0; 10.76 GiB total capacity; 443.59 MiB already allocated; 331.88 MiB free; 498.00 MiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF time spend for datou_step_exec : 6.420525789260864 time spend to save output : 0.016118526458740234 total time spend for step 0 : 6.4366443157196045 need to delete datou_research and reload, so keep current state 1 need to delete datou_research and reload, so keep current state 1 need to delete datou_research and reload, so keep current state 1 caffe_path_current : About to save ! 2 After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : None ERROR nb objects espect : 98 nb_objects detect : 0 ERROR sam FAILED ############################### TEST frcnn ################################ test frcnn Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=4184 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=4184 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 4184 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=4184 # 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 ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! no param json to modify List Step Type Loaded in datou : frcnn list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT photo_id, url FROM MTRBack.photos ph WHERE photo_id IN (917754606) Found this number of photos: 1 ##### Call download_photos : nb_thread : 5 begin to download photo : 917754606 download finish for photo 917754606 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 ##### After load_data_input time to download the photos : 0.14192748069763184 #### fin chargement data Blocking on flush ? No conitnuing 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 : True number of steps : 1 step1:frcnn Tue May 13 18:36:40 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 After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1747154200_3823001_917754606_35f3c9ae49686a6be16030c6ec25c9ee.jpg': 917754606} map_photo_id_path_extension : {917754606: {'path': 'temp/1747154200_3823001_917754606_35f3c9ae49686a6be16030c6ec25c9ee.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} Beginning of datou step Faster rcnn ! classes : ['background', 'plaque'] pht : 4370 caffemodel_name (should be vgg16_immat_307 but not used because net loaded outside in the fonction) : {'id': 3375, 'mtr_user_id': 31, 'name': 'detection_plaque_valcor_010622', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,plaque', 'svm_portfolios_learning': '0,0', 'photo_hashtag_type': 4370, 'photo_desc_type': 5676, 'type_classification': 'caffe_faster_rcnn', 'hashtag_id_list': '0,0'} To loadFromThcl() model_param file didn't exist model_name : detection_plaque_valcor_010622 model_type : caffe_faster_rcnn list file need : ['caffemodel', 'test.prototxt'] file exist in s3 : ['caffemodel', 'test.prototxt'] file manque in s3 : [] WARNING: Logging before InitGoogleLogging() is written to STDERR F0513 18:36:42.985919 3823001 syncedmem.cpp:71] Check failed: error == cudaSuccess (2 vs. 0) out of memory *** Check failure stack trace: *** Command terminated by signal 6 34.97user 27.40system 1:17.31elapsed 80%CPU (0avgtext+0avgdata 3577452maxresident)k 3030512inputs+4616outputs (5598major+3062809minor)pagefaults 0swaps