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 : 2743 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 : 0.13369989395141602 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 Fri Feb 21 06:35:29 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 : 2743 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 2025-02-21 06:35:32.761067: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2025-02-21 06:35:32.795156: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493065000 Hz 2025-02-21 06:35:32.797723: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f374c000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-02-21 06:35:32.797790: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-02-21 06:35:32.803616: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-02-21 06:35:33.094279: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x3e24c780 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-02-21 06:35:33.094336: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-02-21 06:35:33.095410: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-02-21 06:35:33.095886: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-21 06:35:33.098556: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-02-21 06:35:33.117488: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-02-21 06:35:33.118130: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-02-21 06:35:33.151322: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-02-21 06:35:33.157061: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-02-21 06:35:33.215783: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-02-21 06:35:33.217448: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-02-21 06:35:33.217978: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-21 06:35:33.218788: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-02-21 06:35:33.218812: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-02-21 06:35:33.218827: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-02-21 06:35:33.220642: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 2291 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 2025-02-21 06:35:33.897584: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-02-21 06:35:33.897704: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-21 06:35:33.897722: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-02-21 06:35:33.897736: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-02-21 06:35:33.897751: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-02-21 06:35:33.897765: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-02-21 06:35:33.897803: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-02-21 06:35:33.897819: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-02-21 06:35:33.898579: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-02-21 06:35:33.899766: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-02-21 06:35:33.899815: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-21 06:35:33.899831: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-02-21 06:35:33.899845: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-02-21 06:35:33.899860: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-02-21 06:35:33.899874: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-02-21 06:35:33.899888: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-02-21 06:35:33.899902: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-02-21 06:35:33.900687: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-02-21 06:35:33.900733: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-02-21 06:35:33.900744: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-02-21 06:35:33.900753: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-02-21 06:35:33.901565: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 2291 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 : [] 2025-02-21 06:35:42.649352: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-02-21 06:35:42.880204: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-02-21 06:35:44.717750: 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. 2025-02-21 06:35:44.721400: 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. 2025-02-21 06:35:44.728555: 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. 2025-02-21 06:35:44.728607: 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. 2025-02-21 06:35:44.803196: 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. 2025-02-21 06:35:44.803273: 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. 2025-02-21 06:35:44.848169: 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. 2025-02-21 06:35:44.848233: 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. 2025-02-21 06:35:44.900695: 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. 2025-02-21 06:35:44.900756: 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. 2025-02-21 06:35:44.903305: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1330511872 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:44.903892: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.11G (1197460736 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:44.903910: 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. 2025-02-21 06:35:44.919870: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:44.920544: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:44.928983: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:44.929583: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:44.934732: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:44.935356: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:44.947516: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:44.948122: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:44.949704: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:44.950273: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:44.957804: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:44.958396: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:44.960146: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:44.960722: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:44.966592: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:44.967204: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:44.968786: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:44.969353: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.000461: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.001086: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.001652: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.002216: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.007100: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.007701: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.029150: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.029790: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.030356: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.030957: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.044639: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.045255: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.045861: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.046432: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.051468: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.052058: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.056820: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.057411: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.069468: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.070093: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.074374: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.074980: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.096155: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.096778: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.097371: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.097938: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.098501: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.099070: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.151431: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.151514: 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. 2025-02-21 06:35:45.152276: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.152991: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.160405: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.161055: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.169609: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.170545: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.208678: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.209307: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.209924: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.210495: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.214580: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.215164: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.215736: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.216298: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.218119: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.227434: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.228010: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.238276: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.238885: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.239485: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.240046: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.240618: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:35:45.241194: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 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 1332585 begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 1550 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 : 2743 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 : 0.0007786750793457031 nb_pixel_total : 15555 time to create 1 rle with old method : 0.02044391632080078 length of segment : 256 time for calcul the mask position with numpy : 0.003076791763305664 nb_pixel_total : 145328 time to create 1 rle with old method : 0.16967272758483887 length of segment : 371 time for calcul the mask position with numpy : 0.000286102294921875 nb_pixel_total : 14255 time to create 1 rle with old method : 0.01671290397644043 length of segment : 151 time for calcul the mask position with numpy : 0.00016498565673828125 nb_pixel_total : 5613 time to create 1 rle with old method : 0.0070209503173828125 length of segment : 48 time for calcul the mask position with numpy : 8.487701416015625e-05 nb_pixel_total : 1824 time to create 1 rle with old method : 0.0024292469024658203 length of segment : 39 time spent for convertir_results : 1.7073302268981934 time spend for datou_step_exec : 21.08576011657715 time spend to save output : 5.435943603515625e-05 total time spend for step 1 : 21.085814476013184 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 3278 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 : 0.019365549087524414 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, 0.99549603, [(140, 26, 6), (135, 27, 15), (133, 28, 18), (131, 29, 22), (126, 30, 28), (10, 31, 1), (120, 31, 35), (8, 32, 13), (26, 32, 4), (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, 46), (1, 159, 45), (1, 160, 44), (1, 161, 43), (1, 162, 42), (1, 163, 42), (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)], ['16,276,8,273,2,261,2,229,1,228,1,114,2,113,2,82,1,81,1,46,3,37,8,32,29,32,30,33,58,33,59,34,75,34,76,35,102,35,114,33,120,31,130,30,135,27,145,26,152,29,158,35,158,48,154,54,141,58,128,61,119,67,105,81,103,86,96,94,89,98,81,109,71,119,65,132,60,138,52,151,42,162,40,166,34,172,29,188,26,193,25,200,25,219,24,232,24,270,23,273']), (957285035, 492601069, 445, 29, 591, 24, 419, 0.9923753, [(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, 310), (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, 516), (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, 173, 523), (46, 174, 523), (45, 175, 524), (45, 176, 523), 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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/1740116129_1332300_957285035_a42482e51c93c8025d243dd179aee85b.jpg']} free memory after detection : begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 2743 ############################### 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 : 0.12494826316833496 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 Fri Feb 21 06:36:35 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec 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 : 2743 max_wait_temp : 1 max_wait : 0 gpu_flag : 0 2025-02-21 06:36:38.589128: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2025-02-21 06:36:38.615138: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493065000 Hz 2025-02-21 06:36:38.617215: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f3750000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-02-21 06:36:38.617281: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-02-21 06:36:38.621215: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-02-21 06:36:38.884619: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x3e5b6c40 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-02-21 06:36:38.884675: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-02-21 06:36:38.885710: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-02-21 06:36:38.886564: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-21 06:36:38.892324: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-02-21 06:36:38.899945: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-02-21 06:36:38.901330: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-02-21 06:36:38.907242: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-02-21 06:36:38.909428: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-02-21 06:36:38.955649: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-02-21 06:36:38.956954: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-02-21 06:36:38.957410: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-21 06:36:38.958062: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-02-21 06:36:38.958081: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-02-21 06:36:38.958093: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-02-21 06:36:38.959531: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 2291 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:41:00.0, compute capability: 7.5) WARNING:tensorflow:From /home/admin/workarea/git/Velours/python/mtr/mask_rcnn/mask_detection.py:69: The name tf.keras.backend.set_session is deprecated. Please use tf.compat.v1.keras.backend.set_session instead. 2025-02-21 06:36:39.096373: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-02-21 06:36:39.096502: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-21 06:36:39.096524: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-02-21 06:36:39.096543: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-02-21 06:36:39.096561: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-02-21 06:36:39.096592: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-02-21 06:36:39.096610: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-02-21 06:36:39.096629: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-02-21 06:36:39.097382: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-02-21 06:36:39.098279: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-02-21 06:36:39.098309: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-21 06:36:39.098325: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-02-21 06:36:39.098340: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-02-21 06:36:39.098355: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-02-21 06:36:39.098370: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-02-21 06:36:39.098385: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-02-21 06:36:39.098400: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-02-21 06:36:39.099152: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-02-21 06:36:39.099186: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-02-21 06:36:39.099194: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-02-21 06:36:39.099201: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-02-21 06:36:39.099992: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 2291 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 : [] 2025-02-21 06:36:46.636311: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-02-21 06:36:46.819432: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-02-21 06:36:48.385567: 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. 2025-02-21 06:36:48.385644: 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. 2025-02-21 06:36:48.392441: 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. 2025-02-21 06:36:48.392465: 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. 2025-02-21 06:36:48.442582: 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. 2025-02-21 06:36:48.442639: 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. 2025-02-21 06:36:48.484622: 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. 2025-02-21 06:36:48.484653: 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. 2025-02-21 06:36:48.535772: 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. 2025-02-21 06:36:48.535802: 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. 2025-02-21 06:36:48.538108: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1330511872 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.538615: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.11G (1197460736 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.538629: 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. 2025-02-21 06:36:48.555787: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.556427: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.565646: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.566714: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.571786: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.572329: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.584909: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.585442: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.586953: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.587625: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.594662: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.595253: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.596882: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.597412: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.602961: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.603510: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.604992: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.605523: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.632059: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.632598: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.633121: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.633644: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.637769: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.638300: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.655154: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.655691: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.656216: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.656740: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.669561: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.670099: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.670628: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.671203: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.675841: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.676425: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.681044: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.681584: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.693815: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.694350: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.698445: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.699011: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.719804: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.720339: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.720878: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.721402: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.721947: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.722477: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.763485: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.763561: 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. 2025-02-21 06:36:48.764650: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.765730: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.772934: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.773641: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.781699: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.782234: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.801955: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.802682: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.803422: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.804048: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.808014: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.808546: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.809089: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.809612: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.810827: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.820744: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.821274: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.831418: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.831947: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.832479: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.833002: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.833532: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:36:48.834055: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 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 1335827 begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 1550 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 : 2743 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 : 0.0006482601165771484 nb_pixel_total : 16902 time to create 1 rle with old method : 0.022507190704345703 length of segment : 107 time for calcul the mask position with numpy : 0.01940608024597168 nb_pixel_total : 480755 time to create 1 rle with new method : 0.03445744514465332 length of segment : 632 time for calcul the mask position with numpy : 0.0005266666412353516 nb_pixel_total : 36583 time to create 1 rle with old method : 0.04042816162109375 length of segment : 132 time for calcul the mask position with numpy : 9.679794311523438e-05 nb_pixel_total : 4793 time to create 1 rle with old method : 0.005530595779418945 length of segment : 51 time spent for convertir_results : 0.30199623107910156 time spend for datou_step_exec : 17.113559007644653 time spend to save output : 6.079673767089844e-05 total time spend for step 1 : 17.113619804382324 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 400 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 : 0.012727499008178711 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, 0.9988385, [(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, 0.997741, [(711, 22, 21), (926, 22, 46), (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), (545, 33, 502), (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), (449, 76, 641), (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, 92, 658), (431, 93, 659), (430, 94, 660), (429, 95, 661), (428, 96, 662), (427, 97, 663), (425, 98, 665), (423, 99, 667), (421, 100, 669), (419, 101, 671), (417, 102, 673), (413, 103, 677), (410, 104, 680), (405, 105, 685), (401, 106, 689), (397, 107, 693), (392, 108, 698), (387, 109, 703), (382, 110, 708), (377, 111, 713), (373, 112, 717), (368, 113, 722), (365, 114, 725), (361, 115, 729), (358, 116, 732), (356, 117, 734), (353, 118, 737), (351, 119, 739), (348, 120, 742), (346, 121, 744), (344, 122, 746), (341, 123, 749), (338, 124, 752), (335, 125, 755), (331, 126, 759), (327, 127, 763), (323, 128, 767), (319, 129, 770), (314, 130, 775), (308, 131, 781), (303, 132, 786), (294, 133, 795), (286, 134, 803), (279, 135, 810), (273, 136, 816), (267, 137, 822), (262, 138, 827), (258, 139, 831), (255, 140, 834), (252, 141, 837), (250, 142, 839), (247, 143, 842), (245, 144, 844), (242, 145, 847), (240, 146, 849), (237, 147, 852), (233, 148, 856), (230, 149, 859), (226, 150, 863), (220, 151, 869), (213, 152, 876), 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['449,46,443,46,442,45,426,45,424,41,424,37,423,36,422,31,420,28,420,25,419,24,419,21,418,20,418,17,417,15,409,6,402,3,402,1,413,1,414,0,420,0,421,1,440,1,441,0,500,0,501,1,507,1,508,0,535,0,536,1,543,1,546,2,546,4,542,8,530,18,527,19,525,21,522,22,520,24,512,28,508,33,505,34,502,37,494,41,492,41,490,43,488,43,484,45,473,45,472,46'])], 'temp/1740116195_1332300_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 : 0.17285537719726562 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 Fri Feb 21 06:37:06 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec 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 : 2743 max_wait_temp : 1 max_wait : 0 gpu_flag : 0 2025-02-21 06:37:09.279456: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2025-02-21 06:37:09.307143: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493065000 Hz 2025-02-21 06:37:09.309064: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f3750000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-02-21 06:37:09.309113: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-02-21 06:37:09.312938: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-02-21 06:37:09.571719: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x3f28bc20 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-02-21 06:37:09.571783: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-02-21 06:37:09.572831: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-02-21 06:37:09.588460: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-21 06:37:09.592473: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-02-21 06:37:09.595457: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-02-21 06:37:09.596232: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-02-21 06:37:09.599038: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-02-21 06:37:09.600345: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-02-21 06:37:09.605801: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-02-21 06:37:09.607092: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-02-21 06:37:09.607195: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-21 06:37:09.607804: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-02-21 06:37:09.607819: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-02-21 06:37:09.607828: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-02-21 06:37:09.608693: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 2291 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:41:00.0, compute capability: 7.5) WARNING:tensorflow:From /home/admin/workarea/git/Velours/python/mtr/mask_rcnn/mask_detection.py:69: The name tf.keras.backend.set_session is deprecated. Please use tf.compat.v1.keras.backend.set_session instead. 2025-02-21 06:37:09.690783: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-02-21 06:37:09.690964: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-21 06:37:09.690996: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-02-21 06:37:09.691022: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-02-21 06:37:09.691046: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-02-21 06:37:09.691070: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-02-21 06:37:09.691110: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-02-21 06:37:09.691135: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-02-21 06:37:09.692105: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-02-21 06:37:09.693144: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-02-21 06:37:09.693183: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-21 06:37:09.693209: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-02-21 06:37:09.693229: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-02-21 06:37:09.693249: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-02-21 06:37:09.693269: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-02-21 06:37:09.693289: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-02-21 06:37:09.693309: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-02-21 06:37:09.694255: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-02-21 06:37:09.694294: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-02-21 06:37:09.694305: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-02-21 06:37:09.694315: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-02-21 06:37:09.695332: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 2291 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 : [] 2025-02-21 06:37:17.399557: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-02-21 06:37:17.591842: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-02-21 06:37:18.945822: 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. 2025-02-21 06:37:18.945885: 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. 2025-02-21 06:37:18.952416: 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. 2025-02-21 06:37:18.952444: 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. 2025-02-21 06:37:19.002967: 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. 2025-02-21 06:37:19.003040: 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. 2025-02-21 06:37:19.044903: 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. 2025-02-21 06:37:19.044935: 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. 2025-02-21 06:37:19.096051: 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. 2025-02-21 06:37:19.096101: 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. 2025-02-21 06:37:19.098397: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1330511872 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.098917: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.11G (1197460736 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.098932: 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. 2025-02-21 06:37:19.116458: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.117490: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.125497: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.126574: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.130653: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.131201: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.141478: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.141996: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.143460: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.143977: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.149386: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.149905: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.151534: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.152074: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.157596: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.158153: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.159688: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.160249: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.186227: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.186756: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.187316: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.187873: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.191323: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.191883: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.207081: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.207647: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.208182: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.208694: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.220778: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.221297: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.221852: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.222372: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.226706: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.227284: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.231879: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.232409: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.244622: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.245143: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.249244: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.249761: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.271166: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.271777: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.272356: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.272945: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.273549: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.274120: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.312360: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.312428: 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. 2025-02-21 06:37:19.313459: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.314487: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.322043: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.322572: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.331045: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.331607: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.347016: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.347604: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.348169: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.348692: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.353053: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.353574: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.354106: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.354622: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.355531: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.370432: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.370969: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.381755: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.382277: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.382821: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.383386: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.383951: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-21 06:37:19.384485: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.74G (1867382784 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 1337277 begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 1550 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 : 2743 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 : 0.15158724784851074 nb_pixel_total : 3696939 time to create 1 rle with new method : 0.5427036285400391 length of segment : 2044 time spent for convertir_results : 2.33833646774292 time spend for datou_step_exec : 18.70655369758606 time spend to save output : 4.1961669921875e-05 total time spend for step 1 : 18.70659565925598 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 719 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 : 0.11296677589416504 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, 0, 2279, 103, 2222, 0.981974, [(1250, 110, 26), (653, 111, 287), (1203, 111, 134), (615, 112, 374), (1083, 112, 344), (525, 113, 909), (518, 114, 922), (512, 115, 934), (505, 116, 948), (499, 117, 959), (493, 118, 971), (487, 119, 983), (481, 120, 994), (476, 121, 1004), (471, 122, 1014), (465, 123, 1024), (461, 124, 1033), (456, 125, 1042), (451, 126, 1052), (447, 127, 1061), (443, 128, 1075), (439, 129, 1088), (435, 130, 1101), (431, 131, 1114), (427, 132, 1126), (423, 133, 1139), (420, 134, 1150), (416, 135, 1161), (413, 136, 1172), (410, 137, 1180), (407, 138, 1186), (403, 139, 1193), (400, 140, 1200), (398, 141, 1205), (395, 142, 1211), (392, 143, 1217), (389, 144, 1224), (385, 145, 1231), (382, 146, 1238), (379, 147, 1245), (376, 148, 1251), (372, 149, 1259), (368, 150, 1267), (365, 151, 1275), (363, 152, 1281), (361, 153, 1287), (358, 154, 1295), (356, 155, 1302), (353, 156, 1310), (350, 157, 1318), (348, 158, 1325), (345, 159, 1333), (342, 160, 1341), (339, 161, 1350), (336, 162, 1358), (333, 163, 1367), (330, 164, 1376), (327, 165, 1385), (324, 166, 1395), (321, 167, 1404), (318, 168, 1414), (314, 169, 1426), (311, 170, 1436), (307, 171, 1448), (303, 172, 1461), (300, 173, 1472), (296, 174, 1485), (292, 175, 1497), (288, 176, 1510), (284, 177, 1523), (281, 178, 1535), (277, 179, 1548), (274, 180, 1559), (271, 181, 1567), (268, 182, 1574), (266, 183, 1580), (263, 184, 1588), (260, 185, 1595), (258, 186, 1600), (255, 187, 1607), (253, 188, 1613), (250, 189, 1619), (248, 190, 1625), (246, 191, 1630), (243, 192, 1636), (241, 193, 1641), (239, 194, 1646), (237, 195, 1651), (235, 196, 1656), (233, 197, 1661), (231, 198, 1665), (229, 199, 1670), (227, 200, 1674), (225, 201, 1679), (224, 202, 1682), (222, 203, 1686), (220, 204, 1691), (218, 205, 1695), (217, 206, 1697), (215, 207, 1700), (214, 208, 1703), (212, 209, 1706), (210, 210, 1709), (209, 211, 1711), (208, 212, 1714), (206, 213, 1717), (205, 214, 1719), (203, 215, 1722), (202, 216, 1724), (201, 217, 1726), (199, 218, 1729), (198, 219, 1731), (197, 220, 1732), (196, 221, 1734), (194, 222, 1737), (193, 223, 1739), (192, 224, 1741), (190, 225, 1744), (189, 226, 1746), (188, 227, 1748), (186, 228, 1751), (185, 229, 1753), (183, 230, 1756), (182, 231, 1758), (181, 232, 1761), (179, 233, 1764), (178, 234, 1766), (176, 235, 1769), (175, 236, 1771), (173, 237, 1774), (172, 238, 1776), (170, 239, 1780), (169, 240, 1782), (167, 241, 1785), (166, 242, 1787), (164, 243, 1791), (163, 244, 1793), (161, 245, 1796), (160, 246, 1799), (158, 247, 1802), (156, 248, 1805), (155, 249, 1808), (153, 250, 1811), (151, 251, 1814), (150, 252, 1817), (148, 253, 1820), (146, 254, 1824), (145, 255, 1826), (143, 256, 1830), (141, 257, 1834), (140, 258, 1836), (138, 259, 1840), (136, 260, 1843), (134, 261, 1847), (133, 262, 1850), (131, 263, 1854), (129, 264, 1857), (127, 265, 1861), (125, 266, 1865), (123, 267, 1869), (122, 268, 1872), (120, 269, 1875), (119, 270, 1878), (118, 271, 1880), (117, 272, 1882), (115, 273, 1886), (114, 274, 1888), (113, 275, 1890), (112, 276, 1892), (111, 277, 1894), (110, 278, 1896), (109, 279, 1899), (108, 280, 1901), (107, 281, 1903), (106, 282, 1905), (106, 283, 1906), (105, 284, 1907), (104, 285, 1909), (103, 286, 1911), (102, 287, 1913), (101, 288, 1915), (101, 289, 1916), (100, 290, 1918), (99, 291, 1919), (99, 292, 1920), (98, 293, 1921), (98, 294, 1922), (97, 295, 1923), (97, 296, 1924), (97, 297, 1924), (96, 298, 1926), (96, 299, 1926), (95, 300, 1928), (95, 301, 1928), (95, 302, 1929), (94, 303, 1930), (94, 304, 1931), (94, 305, 1931), (93, 306, 1933), (93, 307, 1933), (92, 308, 1935), (92, 309, 1935), (92, 310, 1936), (91, 311, 1937), (91, 312, 1938), (91, 313, 1938), (90, 314, 1940), (90, 315, 1940), (89, 316, 1942), (89, 317, 1942), (89, 318, 1943), (88, 319, 1944), (88, 320, 1945), (88, 321, 1946), (87, 322, 1947), (87, 323, 1948), (87, 324, 1948), (86, 325, 1950), (86, 326, 1950), (86, 327, 1951), (85, 328, 1952), (85, 329, 1953), (84, 330, 1954), (84, 331, 1955), (84, 332, 1955), (83, 333, 1957), (83, 334, 1957), (83, 335, 1958), (82, 336, 1959), (82, 337, 1960), (82, 338, 1961), (81, 339, 1962), (81, 340, 1963), (81, 341, 1963), (80, 342, 1965), (80, 343, 1965), (80, 344, 1966), (79, 345, 1967), (79, 346, 1968), (79, 347, 1968), (78, 348, 1970), (78, 349, 1971), (78, 350, 1971), (77, 351, 1973), (77, 352, 1973), (77, 353, 1974), (76, 354, 1975), (76, 355, 1976), (76, 356, 1977), (75, 357, 1978), (75, 358, 1979), (75, 359, 1979), (75, 360, 1980), (74, 361, 1981), (74, 362, 1982), (74, 363, 1983), (73, 364, 1984), (73, 365, 1985), (73, 366, 1985), (72, 367, 1987), (72, 368, 1988), (72, 369, 1988), (72, 370, 1989), (71, 371, 1991), (71, 372, 1992), (71, 373, 1993), (71, 374, 1993), (70, 375, 1995), (70, 376, 1996), (70, 377, 1997), (70, 378, 1998), (69, 379, 2000), (69, 380, 2001), (69, 381, 2002), (69, 382, 2003), (68, 383, 2005), (68, 384, 2006), (68, 385, 2007), (67, 386, 2010), (67, 387, 2011), (67, 388, 2012), (67, 389, 2013), (66, 390, 2015), (66, 391, 2016), (66, 392, 2017), (65, 393, 2019), (65, 394, 2020), (65, 395, 2021), (65, 396, 2022), (64, 397, 2023), (64, 398, 2024), (64, 399, 2025), (63, 400, 2027), (63, 401, 2028), (63, 402, 2029), (62, 403, 2030), (62, 404, 2031), (62, 405, 2032), (62, 406, 2033), (61, 407, 2034), (61, 408, 2035), (61, 409, 2036), (60, 410, 2038), (60, 411, 2038), (60, 412, 2039), (59, 413, 2040), (59, 414, 2041), (59, 415, 2042), (58, 416, 2043), (58, 417, 2044), (57, 418, 2046), (57, 419, 2046), (57, 420, 2047), (56, 421, 2048), (56, 422, 2049), (56, 423, 2049), (55, 424, 2051), (55, 425, 2051), (55, 426, 2052), (54, 427, 2053), (54, 428, 2054), (53, 429, 2055), (53, 430, 2056), (53, 431, 2056), (52, 432, 2058), (52, 433, 2058), (51, 434, 2060), (51, 435, 2060), (51, 436, 2061), (50, 437, 2062), (50, 438, 2063), (49, 439, 2064), (49, 440, 2064), (48, 441, 2066), (48, 442, 2066), (48, 443, 2067), (47, 444, 2068), (47, 445, 2068), (47, 446, 2068), (47, 447, 2068), (46, 448, 2070), (46, 449, 2070), (46, 450, 2070), (46, 451, 2070), (46, 452, 2070), (45, 453, 2072), (45, 454, 2072), (45, 455, 2072), (45, 456, 2072), (44, 457, 2074), (44, 458, 2074), (44, 459, 2074), (44, 460, 2074), (43, 461, 2076), (43, 462, 2076), (43, 463, 2076), (43, 464, 2076), (42, 465, 2077), (42, 466, 2078), (42, 467, 2078), (42, 468, 2078), (41, 469, 2079), (41, 470, 2080), (41, 471, 2080), (41, 472, 2080), (40, 473, 2081), (40, 474, 2082), (40, 475, 2082), (40, 476, 2082), (39, 477, 2083), (39, 478, 2084), (39, 479, 2084), (39, 480, 2084), (38, 481, 2085), (38, 482, 2086), (38, 483, 2086), (38, 484, 2086), (37, 485, 2087), (37, 486, 2088), (37, 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['937,2141,855,2123,777,2093,650,2058,528,2013,367,1982,205,1965,122,1970,88,1911,51,1806,40,1658,44,1591,39,1419,29,1275,30,910,21,612,36,489,97,295,120,269,250,189,416,135,525,113,1426,112,1569,134,1747,171,1832,180,1910,204,2017,290,2059,369,2114,443,2163,646,2152,822,2127,898,2119,974,2093,1050,2039,1123,2011,1192,1974,1242,1939,1350,1886,1426,1848,1654,1800,1806,1759,1913,1731,1957,1668,2011,1585,2014,1506,2049,1409,2057,1263,2079,1099,2136'])], 'temp/1740116226_1332300_917877156_a9c2d4b99270c9302def4ed40606e685.jpg']} nb pixel non reg : 3692295 nb pixel common : 3677640 proportion of common points : 0.9960309238563008 [('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_3bb8fc9eb89f6e73213a93d2f1429765ec1e113a 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_3bb8fc9eb89f6e73213a93d2f1429765ec1e113a','{"mask_detection": "success"}','1','http://marlene.fotonower-preprod.com/job/2025/February/21022025/python_test3//data_2/data_log/job/2025/February/21022025/python_test3/log-python3----short_python3--v--marlene-06:35:01.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 : 0.3064408302307129 #### 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 Fri Feb 21 06:41:31 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1740116491_1332300_1189321094_9626af7f95d010f2a4fd524688d4ea22_76896585.png': 1189321094} map_photo_id_path_extension : {1189321094: {'path': 'temp/1740116491_1332300_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; 508.88 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; 508.88 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 : 0.01420283317565918 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; 508.88 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 : 7.587748289108276 time spend to save output : 0.04800295829772949 total time spend for step 0 : 7.635751247406006 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 : 0.12598538398742676 #### 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 Fri Feb 21 06:41:39 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/1740116499_1332300_917754606_35f3c9ae49686a6be16030c6ec25c9ee.jpg': 917754606} map_photo_id_path_extension : {917754606: {'path': 'temp/1740116499_1332300_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 F0221 06:41:41.871237 1332300 syncedmem.cpp:71] Check failed: error == cudaSuccess (2 vs. 0) out of memory *** Check failure stack trace: *** Command terminated by signal 6 34.20user 26.57system 6:15.94elapsed 16%CPU (0avgtext+0avgdata 3582536maxresident)k 5783848inputs+4696outputs (21076major+2991468minor)pagefaults 0swaps