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 : 0.1476595401763916 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 Thu Feb 27 06:35:27 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 2025-02-27 06:35:30.173750: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2025-02-27 06:35:30.207067: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493065000 Hz 2025-02-27 06:35:30.209046: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f9cd4000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-02-27 06:35:30.209094: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-02-27 06:35:30.213488: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-02-27 06:35:30.474167: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x43705210 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-02-27 06:35:30.474236: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-02-27 06:35:30.475267: 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 2025-02-27 06:35:30.475779: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-27 06:35:30.479220: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-02-27 06:35:30.482413: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-02-27 06:35:30.483015: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-02-27 06:35:30.486000: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-02-27 06:35:30.487537: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-02-27 06:35:30.492654: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-02-27 06:35:30.493841: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-02-27 06:35:30.493942: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-27 06:35:30.494532: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-02-27 06:35:30.494549: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-02-27 06:35:30.494560: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-02-27 06:35:30.495567: 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 2025-02-27 06:35:31.146501: 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 2025-02-27 06:35:31.146609: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-27 06:35:31.146638: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-02-27 06:35:31.146664: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-02-27 06:35:31.146688: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-02-27 06:35:31.146712: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-02-27 06:35:31.146754: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-02-27 06:35:31.146779: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-02-27 06:35:31.148126: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-02-27 06:35:31.149580: 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 2025-02-27 06:35:31.149646: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-27 06:35:31.149670: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-02-27 06:35:31.149691: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-02-27 06:35:31.149711: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-02-27 06:35:31.149731: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-02-27 06:35:31.149751: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-02-27 06:35:31.149772: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-02-27 06:35:31.150816: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-02-27 06:35:31.150859: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-02-27 06:35:31.150869: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-02-27 06:35:31.150879: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-02-27 06:35:31.152006: 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 : [] 2025-02-27 06:35:39.291649: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-02-27 06:35:39.467749: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-02-27 06:35:41.203368: 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. 2025-02-27 06:35:41.203463: 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. 2025-02-27 06:35:41.209984: 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. 2025-02-27 06:35:41.210013: 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. 2025-02-27 06:35:41.261840: 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. 2025-02-27 06:35:41.261915: 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. 2025-02-27 06:35:41.304218: 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. 2025-02-27 06:35:41.304254: 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. 2025-02-27 06:35:41.356080: 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. 2025-02-27 06:35:41.356134: 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. 2025-02-27 06:35:41.358408: 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 2025-02-27 06:35:41.358904: 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 2025-02-27 06:35:41.358918: 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. 2025-02-27 06:35:41.375968: 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 2025-02-27 06:35:41.376583: 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 2025-02-27 06:35:41.385977: 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 2025-02-27 06:35:41.387046: 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 2025-02-27 06:35:41.392900: 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 2025-02-27 06:35:41.393568: 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 2025-02-27 06:35:41.406805: 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 2025-02-27 06:35:41.407841: 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 2025-02-27 06:35:41.410099: 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 2025-02-27 06:35:41.410703: 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 2025-02-27 06:35:41.417525: 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 2025-02-27 06:35:41.418128: 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 2025-02-27 06:35:41.420099: 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 2025-02-27 06:35:41.420678: 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 2025-02-27 06:35:41.427774: 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 2025-02-27 06:35:41.428368: 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 2025-02-27 06:35:41.430117: 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 2025-02-27 06:35:41.430687: 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 2025-02-27 06:35:41.461657: 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 2025-02-27 06:35:41.462270: 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 2025-02-27 06:35:41.462831: 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 2025-02-27 06:35:41.463421: 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 2025-02-27 06:35:41.467204: 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 2025-02-27 06:35:41.467806: 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 2025-02-27 06:35:41.484013: 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 2025-02-27 06:35:41.484636: 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 2025-02-27 06:35:41.485212: 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 2025-02-27 06:35:41.485787: 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 2025-02-27 06:35:41.498591: 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 2025-02-27 06:35:41.499263: 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 2025-02-27 06:35:41.499856: 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 2025-02-27 06:35:41.500585: 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 2025-02-27 06:35:41.505189: 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 2025-02-27 06:35:41.505744: 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 2025-02-27 06:35:41.510541: 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 2025-02-27 06:35:41.511129: 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 2025-02-27 06:35:41.523410: 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 2025-02-27 06:35:41.524020: 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 2025-02-27 06:35:41.528246: 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 2025-02-27 06:35:41.528838: 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 2025-02-27 06:35:41.550263: 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 2025-02-27 06:35:41.550940: 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 2025-02-27 06:35:41.551562: 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 2025-02-27 06:35:41.552158: 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 2025-02-27 06:35:41.552747: 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 2025-02-27 06:35:41.553347: 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 2025-02-27 06:35:41.593686: 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 2025-02-27 06:35:41.593759: 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. 2025-02-27 06:35:41.594342: 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 2025-02-27 06:35:41.594894: 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 2025-02-27 06:35:41.602426: 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 2025-02-27 06:35:41.603049: 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 2025-02-27 06:35:41.611414: 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 2025-02-27 06:35:41.612036: 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 2025-02-27 06:35:41.627923: 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 2025-02-27 06:35:41.628566: 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 2025-02-27 06:35:41.629173: 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 2025-02-27 06:35:41.629719: 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 2025-02-27 06:35:41.633909: 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 2025-02-27 06:35:41.634466: 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 2025-02-27 06:35:41.635035: 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 2025-02-27 06:35:41.635642: 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 2025-02-27 06:35:41.636876: 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 2025-02-27 06:35:41.646961: 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 2025-02-27 06:35:41.647561: 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 2025-02-27 06:35:41.658075: 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 2025-02-27 06:35:41.658712: 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 2025-02-27 06:35:41.659418: 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 2025-02-27 06:35:41.660077: 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 2025-02-27 06:35:41.660713: 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 2025-02-27 06:35:41.661430: 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 2300193 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 : 0.0005767345428466797 nb_pixel_total : 15552 time to create 1 rle with old method : 0.018796205520629883 length of segment : 256 time for calcul the mask position with numpy : 0.0049250125885009766 nb_pixel_total : 145336 time to create 1 rle with old method : 0.16326665878295898 length of segment : 371 time for calcul the mask position with numpy : 0.00046706199645996094 nb_pixel_total : 14255 time to create 1 rle with old method : 0.02047443389892578 length of segment : 151 time for calcul the mask position with numpy : 0.00024628639221191406 nb_pixel_total : 5613 time to create 1 rle with old method : 0.0072743892669677734 length of segment : 48 time for calcul the mask position with numpy : 0.00011730194091796875 nb_pixel_total : 1825 time to create 1 rle with old method : 0.002576112747192383 length of segment : 39 time spent for convertir_results : 1.0064918994903564 time spend for datou_step_exec : 18.588662147521973 time spend to save output : 5.555152893066406e-05 total time spend for step 1 : 18.588717699050903 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 3296 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 : 0.1312553882598877 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, 0.9954934, [(140, 26, 6), (135, 27, 15), (133, 28, 18), (131, 29, 22), (126, 30, 28), (10, 31, 1), (120, 31, 35), (8, 32, 13), (27, 32, 3), (115, 32, 41), (7, 33, 52), (109, 33, 48), (6, 34, 70), (103, 34, 55), (5, 35, 154), (4, 36, 155), (3, 37, 156), (3, 38, 156), (3, 39, 156), (2, 40, 157), (2, 41, 157), (2, 42, 157), (2, 43, 157), (2, 44, 157), (2, 45, 157), (1, 46, 158), (1, 47, 158), (1, 48, 158), (1, 49, 157), (1, 50, 157), (1, 51, 156), (1, 52, 156), (1, 53, 155), (1, 54, 154), (1, 55, 152), (1, 56, 149), (1, 57, 145), (1, 58, 141), (1, 59, 136), (1, 60, 133), (1, 61, 130), (1, 62, 127), (1, 63, 126), (1, 64, 124), (1, 65, 123), (1, 66, 121), (1, 67, 120), (1, 68, 118), (1, 69, 117), (1, 70, 116), (1, 71, 115), (1, 72, 114), (1, 73, 113), (1, 74, 112), (1, 75, 111), (1, 76, 110), (1, 77, 108), (1, 78, 108), (1, 79, 107), (1, 80, 106), (1, 81, 105), (2, 82, 104), (2, 83, 103), (2, 84, 103), (2, 85, 102), (2, 86, 102), (2, 87, 101), (2, 88, 100), (2, 89, 99), (2, 90, 99), (2, 91, 98), (2, 92, 97), (2, 93, 96), (2, 94, 95), (2, 95, 93), (2, 96, 91), (2, 97, 90), (2, 98, 89), (2, 99, 87), (2, 100, 86), (2, 101, 86), (2, 102, 85), (2, 103, 84), (2, 104, 83), (2, 105, 83), (2, 106, 82), (2, 107, 81), (2, 108, 80), (2, 109, 80), (2, 110, 79), (2, 111, 78), (2, 112, 77), (2, 113, 76), (1, 114, 76), (1, 115, 75), (1, 116, 74), (1, 117, 73), (1, 118, 72), (1, 119, 71), (1, 120, 71), (1, 121, 70), (1, 122, 69), (1, 123, 69), (1, 124, 68), (1, 125, 68), (1, 126, 67), (1, 127, 67), (1, 128, 66), (1, 129, 66), (1, 130, 66), (1, 131, 65), (1, 132, 65), (1, 133, 64), (1, 134, 63), (1, 135, 63), (1, 136, 62), (1, 137, 61), (1, 138, 60), (1, 139, 60), (1, 140, 59), (1, 141, 58), (1, 142, 58), (1, 143, 57), (1, 144, 56), (1, 145, 56), (1, 146, 55), (1, 147, 54), (1, 148, 54), (1, 149, 53), (1, 150, 52), (1, 151, 52), (1, 152, 51), (1, 153, 50), (1, 154, 49), (1, 155, 48), (1, 156, 47), (1, 157, 46), (1, 158, 45), (1, 159, 45), (1, 160, 44), (1, 161, 43), (1, 162, 42), (1, 163, 41), (1, 164, 41), (1, 165, 40), (1, 166, 40), (1, 167, 39), (1, 168, 38), (1, 169, 37), (1, 170, 36), (1, 171, 35), (1, 172, 34), (1, 173, 34), (1, 174, 33), (1, 175, 33), (1, 176, 32), (1, 177, 32), (1, 178, 32), (1, 179, 32), (1, 180, 31), (1, 181, 31), (1, 182, 31), (1, 183, 30), (1, 184, 30), (1, 185, 30), (1, 186, 29), (1, 187, 29), (1, 188, 29), (1, 189, 28), (1, 190, 28), (1, 191, 27), (1, 192, 27), (1, 193, 26), (1, 194, 26), (1, 195, 26), (1, 196, 26), (1, 197, 26), (1, 198, 26), (1, 199, 26), (1, 200, 25), (1, 201, 25), (1, 202, 25), (1, 203, 25), (1, 204, 25), (1, 205, 25), (1, 206, 25), (1, 207, 25), (1, 208, 25), (1, 209, 25), (1, 210, 25), (1, 211, 25), (1, 212, 25), (1, 213, 25), (1, 214, 25), (1, 215, 25), (1, 216, 25), (1, 217, 25), (1, 218, 25), (1, 219, 25), (1, 220, 24), (1, 221, 24), (1, 222, 24), (1, 223, 24), (1, 224, 24), (1, 225, 24), (1, 226, 25), (1, 227, 25), (1, 228, 25), (2, 229, 24), (2, 230, 24), (2, 231, 24), (2, 232, 23), (2, 233, 23), (2, 234, 23), (2, 235, 23), (2, 236, 23), (2, 237, 23), (2, 238, 23), (2, 239, 23), (2, 240, 23), (2, 241, 23), (2, 242, 23), (2, 243, 23), (2, 244, 23), (2, 245, 23), (2, 246, 23), (2, 247, 23), (2, 248, 23), (2, 249, 24), (2, 250, 24), (2, 251, 23), (2, 252, 23), (2, 253, 23), (2, 254, 23), (2, 255, 23), (2, 256, 23), (2, 257, 23), (2, 258, 23), (2, 259, 23), (2, 260, 23), (2, 261, 23), (3, 262, 22), (3, 263, 22), (3, 264, 22), (3, 265, 22), (4, 266, 21), (4, 267, 21), (5, 268, 20), (5, 269, 20), (6, 270, 19), (7, 271, 17), (8, 272, 16), (8, 273, 16), (9, 274, 13), (11, 275, 9), (15, 276, 2)], ['16,276,8,273,2,261,2,229,1,228,1,114,2,113,2,82,1,81,1,46,3,37,8,32,20,32,21,33,58,33,59,34,75,34,76,35,102,35,114,33,120,31,130,30,135,27,145,26,152,29,158,35,158,48,154,54,141,58,128,61,119,67,105,81,103,86,96,94,89,98,81,109,71,119,65,132,60,138,52,151,45,158,40,166,34,172,29,188,26,193,25,200,25,226,24,232,24,270,23,273']), (957285035, 492601069, 445, 29, 591, 24, 419, 0.99238366, [(315, 37, 25), (272, 38, 86), (253, 39, 130), (238, 40, 151), (199, 41, 196), (189, 42, 213), (180, 43, 238), (175, 44, 250), (172, 45, 257), (169, 46, 265), (166, 47, 274), (162, 48, 284), (159, 49, 294), (157, 50, 304), (155, 51, 311), (153, 52, 317), (151, 53, 323), (149, 54, 330), (148, 55, 334), (146, 56, 337), (144, 57, 341), (142, 58, 344), (140, 59, 347), (138, 60, 350), (136, 61, 353), (134, 62, 356), (132, 63, 358), (130, 64, 361), (128, 65, 364), (126, 66, 367), (124, 67, 370), (122, 68, 373), (120, 69, 376), (118, 70, 379), (117, 71, 381), (115, 72, 385), (114, 73, 387), (113, 74, 389), (112, 75, 391), (112, 76, 393), (111, 77, 395), (110, 78, 397), (109, 79, 399), (109, 80, 400), (108, 81, 402), (107, 82, 404), (107, 83, 404), (106, 84, 406), (105, 85, 408), (105, 86, 409), (104, 87, 410), (104, 88, 411), (103, 89, 413), (102, 90, 415), (101, 91, 417), (100, 92, 420), (98, 93, 423), (97, 94, 426), (96, 95, 428), (94, 96, 431), (93, 97, 433), (92, 98, 435), (91, 99, 437), (90, 100, 439), (89, 101, 441), (89, 102, 441), (89, 103, 442), (89, 104, 443), (89, 105, 444), (89, 106, 444), (89, 107, 445), (89, 108, 446), (89, 109, 447), (89, 110, 448), (89, 111, 449), (89, 112, 450), (89, 113, 451), (89, 114, 453), (89, 115, 454), (89, 116, 455), (88, 117, 456), (88, 118, 457), (87, 119, 459), (87, 120, 459), (86, 121, 461), (85, 122, 462), (85, 123, 463), (84, 124, 464), (84, 125, 465), (83, 126, 466), (82, 127, 468), (82, 128, 468), (81, 129, 470), (80, 130, 471), (78, 131, 473), (76, 132, 476), (75, 133, 477), (73, 134, 480), (71, 135, 482), (70, 136, 484), (68, 137, 486), (67, 138, 488), (65, 139, 490), (64, 140, 492), (63, 141, 493), (61, 142, 496), (60, 143, 497), (59, 144, 499), (58, 145, 501), (58, 146, 501), (57, 147, 503), (57, 148, 504), (56, 149, 506), (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), (51, 161, 517), (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), 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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)], ['492,42,488,42,487,41,480,41,476,37,475,34,473,32,469,25,465,21,461,20,457,16,457,10,466,9,470,12,474,13,476,11,480,10,482,8,500,8,501,9,524,9,525,10,528,10,532,12,539,12,542,15,545,15,545,19,535,20,534,21,529,21,525,23,523,23,513,30,512,30,504,37,496,41,493,41'])], 'temp/1740634527_2299934_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 : 0.2611110210418701 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 Thu Feb 27 06:35:49 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Beginning of datou step mask_detect ! save_polygon : True begin detect begin to check gpu status inside check gpu memory l 3637 free memory gpu now : 2743 max_wait_temp : 1 max_wait : 0 gpu_flag : 0 2025-02-27 06:35:52.024762: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2025-02-27 06:35:52.051348: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493065000 Hz 2025-02-27 06:35:52.052984: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f9cd4000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-02-27 06:35:52.053007: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-02-27 06:35:52.056085: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-02-27 06:35:52.331805: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x43284bc0 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-02-27 06:35:52.331857: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-02-27 06:35:52.332415: 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 2025-02-27 06:35:52.332799: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-27 06:35:52.334848: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-02-27 06:35:52.337012: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-02-27 06:35:52.337336: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-02-27 06:35:52.339756: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-02-27 06:35:52.340914: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-02-27 06:35:52.345599: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-02-27 06:35:52.346756: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-02-27 06:35:52.346878: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-27 06:35:52.347462: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-02-27 06:35:52.347482: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-02-27 06:35:52.347494: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-02-27 06:35:52.348492: 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. 2025-02-27 06:35:52.433165: 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 2025-02-27 06:35:52.433349: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-27 06:35:52.433384: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-02-27 06:35:52.433413: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-02-27 06:35:52.433441: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-02-27 06:35:52.433478: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-02-27 06:35:52.433503: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-02-27 06:35:52.433532: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-02-27 06:35:52.434520: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-02-27 06:35:52.435706: 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 2025-02-27 06:35:52.435756: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-27 06:35:52.435790: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-02-27 06:35:52.435824: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-02-27 06:35:52.435847: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-02-27 06:35:52.435870: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-02-27 06:35:52.435889: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-02-27 06:35:52.435916: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-02-27 06:35:52.436828: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-02-27 06:35:52.436879: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-02-27 06:35:52.436890: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-02-27 06:35:52.436901: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-02-27 06:35:52.437808: 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 : [] 2025-02-27 06:36:00.385916: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-02-27 06:36:00.599353: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-02-27 06:36:02.143587: 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. 2025-02-27 06:36:02.143650: 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. 2025-02-27 06:36:02.150178: 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. 2025-02-27 06:36:02.150216: 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. 2025-02-27 06:36:02.208702: 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. 2025-02-27 06:36:02.208778: 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. 2025-02-27 06:36:02.254237: 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. 2025-02-27 06:36:02.254295: 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. 2025-02-27 06:36:02.307261: 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. 2025-02-27 06:36:02.307341: 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. 2025-02-27 06:36:02.309846: 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 2025-02-27 06:36:02.310431: 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 2025-02-27 06:36:02.310445: 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. 2025-02-27 06:36:02.328834: 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 2025-02-27 06:36:02.330033: 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 2025-02-27 06:36:02.338448: 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 2025-02-27 06:36:02.339260: 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 2025-02-27 06:36:02.344208: 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 2025-02-27 06:36:02.345005: 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 2025-02-27 06:36:02.356329: 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 2025-02-27 06:36:02.356977: 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 2025-02-27 06:36:02.358684: 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 2025-02-27 06:36:02.359399: 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 2025-02-27 06:36:02.365441: 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 2025-02-27 06:36:02.366079: 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 2025-02-27 06:36:02.367854: 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 2025-02-27 06:36:02.368449: 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 2025-02-27 06:36:02.374421: 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 2025-02-27 06:36:02.375118: 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 2025-02-27 06:36:02.376773: 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 2025-02-27 06:36:02.377378: 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 2025-02-27 06:36:02.405688: 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 2025-02-27 06:36:02.406347: 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 2025-02-27 06:36:02.407013: 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 2025-02-27 06:36:02.407636: 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 2025-02-27 06:36:02.411785: 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 2025-02-27 06:36:02.412460: 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 2025-02-27 06:36:02.429304: 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 2025-02-27 06:36:02.429910: 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 2025-02-27 06:36:02.430484: 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 2025-02-27 06:36:02.431097: 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 2025-02-27 06:36:02.443754: 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 2025-02-27 06:36:02.444386: 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 2025-02-27 06:36:02.445000: 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 2025-02-27 06:36:02.445613: 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 2025-02-27 06:36:02.450116: 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 2025-02-27 06:36:02.450738: 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 2025-02-27 06:36:02.455642: 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 2025-02-27 06:36:02.456287: 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 2025-02-27 06:36:02.468517: 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 2025-02-27 06:36:02.469146: 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 2025-02-27 06:36:02.473398: 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 2025-02-27 06:36:02.474016: 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 2025-02-27 06:36:02.495183: 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 2025-02-27 06:36:02.495804: 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 2025-02-27 06:36:02.496411: 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 2025-02-27 06:36:02.496997: 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 2025-02-27 06:36:02.497572: 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 2025-02-27 06:36:02.498143: 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 2025-02-27 06:36:02.536872: 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 2025-02-27 06:36:02.536942: 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. 2025-02-27 06:36:02.537957: 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 2025-02-27 06:36:02.539038: 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 2025-02-27 06:36:02.546924: 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 2025-02-27 06:36:02.547709: 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 2025-02-27 06:36:02.556529: 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 2025-02-27 06:36:02.557099: 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 2025-02-27 06:36:02.573492: 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 2025-02-27 06:36:02.574047: 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 2025-02-27 06:36:02.574608: 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 2025-02-27 06:36:02.575173: 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 2025-02-27 06:36:02.593846: 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 2025-02-27 06:36:02.595669: 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 2025-02-27 06:36:02.596975: 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 2025-02-27 06:36:02.597764: 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 2025-02-27 06:36:02.599033: 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 2025-02-27 06:36:02.609398: 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 2025-02-27 06:36:02.610298: 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 2025-02-27 06:36:02.620585: 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 2025-02-27 06:36:02.621161: 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 2025-02-27 06:36:02.621745: 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 2025-02-27 06:36:02.622303: 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 2025-02-27 06:36:02.622872: 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 2025-02-27 06:36:02.623453: 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 2301517 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 : 2498 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 : 0.0010666847229003906 nb_pixel_total : 16902 time to create 1 rle with old method : 0.023778438568115234 length of segment : 107 time for calcul the mask position with numpy : 0.028066396713256836 nb_pixel_total : 480752 time to create 1 rle with new method : 0.0307159423828125 length of segment : 632 time for calcul the mask position with numpy : 0.0009987354278564453 nb_pixel_total : 36584 time to create 1 rle with old method : 0.04180717468261719 length of segment : 132 time for calcul the mask position with numpy : 0.00011038780212402344 nb_pixel_total : 4794 time to create 1 rle with old method : 0.006028413772583008 length of segment : 51 time spent for convertir_results : 0.32491111755371094 time spend for datou_step_exec : 16.921549081802368 time spend to save output : 4.1961669921875e-05 total time spend for step 1 : 16.92159104347229 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 : 0.01796269416809082 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, 0.99883765, [(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, 0.9977449, [(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), (544, 33, 503), (538, 34, 512), (532, 35, 520), (527, 36, 527), (523, 37, 534), (518, 38, 541), (514, 39, 548), (510, 40, 554), (506, 41, 561), (503, 42, 566), (499, 43, 572), (496, 44, 577), (493, 45, 582), (491, 46, 585), (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), (372, 112, 718), (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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['450,47,449,46,443,46,442,45,426,45,424,41,424,37,423,36,422,31,419,25,419,21,418,20,418,17,417,15,409,6,402,3,402,1,413,1,414,0,420,0,421,1,440,1,441,0,500,0,501,1,507,1,508,0,535,0,536,1,543,1,546,2,546,4,542,8,530,18,527,19,525,21,522,22,520,24,512,28,508,33,505,34,502,37,494,41,492,41,490,43,488,43,484,45,473,45,472,46,451,46'])], 'temp/1740634549_2299934_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 : 0.1669635772705078 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 Thu Feb 27 06:36:08 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 havn't enough memory gpu , need / 3000 l 3632 free memory gpu now : 1944 wait 20 seconds l 3637 free memory gpu now : 1944 max_wait_temp : 1 max_wait : 0 gpu_flag : 0 2025-02-27 06:36:31.277024: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2025-02-27 06:36:31.303274: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493065000 Hz 2025-02-27 06:36:31.305284: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f9cd8000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-02-27 06:36:31.305311: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-02-27 06:36:31.308791: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-02-27 06:36:31.490071: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x43a06780 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-02-27 06:36:31.490134: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-02-27 06:36:31.490971: 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 2025-02-27 06:36:31.491582: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-27 06:36:31.494892: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-02-27 06:36:31.498252: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-02-27 06:36:31.498994: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-02-27 06:36:31.501816: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-02-27 06:36:31.503032: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-02-27 06:36:31.507720: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-02-27 06:36:31.508926: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-02-27 06:36:31.509044: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-27 06:36:31.509597: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-02-27 06:36:31.509614: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-02-27 06:36:31.509623: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-02-27 06:36:31.510514: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 1171 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. 2025-02-27 06:36:31.615088: 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 2025-02-27 06:36:31.615260: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-27 06:36:31.615288: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-02-27 06:36:31.615316: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-02-27 06:36:31.615341: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-02-27 06:36:31.615384: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-02-27 06:36:31.615407: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-02-27 06:36:31.615431: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-02-27 06:36:31.616439: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-02-27 06:36:31.617537: 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 2025-02-27 06:36:31.617584: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-27 06:36:31.617603: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-02-27 06:36:31.617622: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-02-27 06:36:31.617641: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-02-27 06:36:31.617659: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-02-27 06:36:31.617675: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-02-27 06:36:31.617694: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-02-27 06:36:31.618433: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-02-27 06:36:31.618472: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-02-27 06:36:31.618482: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-02-27 06:36:31.618492: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-02-27 06:36:31.619364: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 1171 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 : [] 2025-02-27 06:36:41.566800: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-02-27 06:36:41.767579: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-02-27 06:36:43.601554: 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. 2025-02-27 06:36:43.901978: 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. 2025-02-27 06:36:43.909920: 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. 2025-02-27 06:36:43.910016: 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. 2025-02-27 06:36:43.917109: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 512.00M (536870912 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:43.917156: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 466.56MiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-02-27 06:36:43.917628: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 512.00M (536870912 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:43.917644: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 466.56MiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-02-27 06:36:43.948776: 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. 2025-02-27 06:36:43.948866: 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. 2025-02-27 06:36:43.954793: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 512.00M (536870912 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:43.954825: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 243.25MiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-02-27 06:36:43.955323: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 512.00M (536870912 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:43.955345: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 243.25MiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-02-27 06:36:43.996225: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 512.00M (536870912 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:43.997258: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 512.00M (536870912 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.053246: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 512.00M (536870912 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.054108: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 512.00M (536870912 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.059612: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 512.00M (536870912 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.060456: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 512.00M (536870912 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.072780: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.073333: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.074871: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.075404: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.082463: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.083062: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.088926: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.089474: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.091017: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.091522: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.118391: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.118911: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.119376: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.119853: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.123344: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.123808: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.139219: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.139738: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.140232: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.140694: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.152864: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.153360: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.161438: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.161930: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.173861: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.174328: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.178385: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.178855: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.199980: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.200479: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.200984: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.201475: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.201979: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.202467: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.236013: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.236101: 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. 2025-02-27 06:36:44.237014: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.237926: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.246128: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.247096: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.255635: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.256195: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.271636: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.272194: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.272705: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.273195: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.277453: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.277995: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.278489: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.279009: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.280135: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.290578: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.291232: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.301557: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.302075: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.302576: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.303088: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.303591: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-02-27 06:36:44.304079: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 660.88M (692977664 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 2303814 begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 355 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 : 1550 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 : 0.19141340255737305 nb_pixel_total : 3693225 time to create 1 rle with new method : 0.722341775894165 length of segment : 2042 time spent for convertir_results : 2.033848524093628 time spend for datou_step_exec : 42.11889672279358 time spend to save output : 3.838539123535156e-05 total time spend for step 1 : 42.118935108184814 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 : 0.030121326446533203 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, 7, 2268, 118, 2241, 0.98499554, [(675, 120, 112), (520, 121, 482), (1050, 121, 381), (502, 122, 948), (486, 123, 982), (470, 124, 1015), (455, 125, 1046), (442, 126, 1092), (429, 127, 1136), (417, 128, 1168), (405, 129, 1187), (394, 130, 1205), (383, 131, 1223), (373, 132, 1239), (368, 133, 1250), (366, 134, 1258), (363, 135, 1267), (361, 136, 1274), (359, 137, 1281), (357, 138, 1288), (355, 139, 1295), (353, 140, 1302), (351, 141, 1309), (349, 142, 1315), (347, 143, 1320), (345, 144, 1326), (343, 145, 1331), (342, 146, 1335), (340, 147, 1340), (338, 148, 1346), (337, 149, 1349), (335, 150, 1354), (334, 151, 1358), (332, 152, 1363), (331, 153, 1366), (330, 154, 1370), (328, 155, 1375), (327, 156, 1378), (326, 157, 1381), (325, 158, 1385), (323, 159, 1390), (322, 160, 1393), (321, 161, 1397), (319, 162, 1402), (318, 163, 1406), (317, 164, 1410), (315, 165, 1415), (314, 166, 1419), (312, 167, 1424), (310, 168, 1429), (309, 169, 1434), (307, 170, 1439), (305, 171, 1444), (304, 172, 1448), (302, 173, 1453), (300, 174, 1458), (298, 175, 1463), (296, 176, 1469), (294, 177, 1474), (292, 178, 1480), (289, 179, 1487), (286, 180, 1493), (283, 181, 1500), (280, 182, 1508), (278, 183, 1514), (275, 184, 1521), (272, 185, 1529), (269, 186, 1536), (266, 187, 1544), (263, 188, 1552), (260, 189, 1561), (257, 190, 1569), (254, 191, 1579), (251, 192, 1588), (248, 193, 1597), (245, 194, 1606), (242, 195, 1615), (240, 196, 1623), (237, 197, 1631), (234, 198, 1640), (231, 199, 1648), (228, 200, 1657), (225, 201, 1665), (222, 202, 1673), (219, 203, 1682), (216, 204, 1689), (213, 205, 1694), (210, 206, 1699), (208, 207, 1702), (206, 208, 1706), (204, 209, 1710), (203, 210, 1712), (201, 211, 1716), (199, 212, 1719), (198, 213, 1721), (196, 214, 1725), (195, 215, 1727), (193, 216, 1730), (192, 217, 1733), (191, 218, 1735), (189, 219, 1738), (188, 220, 1740), (187, 221, 1742), (186, 222, 1744), (185, 223, 1746), (183, 224, 1749), (182, 225, 1751), (181, 226, 1753), (180, 227, 1755), (179, 228, 1757), (178, 229, 1759), (177, 230, 1761), (176, 231, 1762), (176, 232, 1763), (175, 233, 1765), (174, 234, 1767), (173, 235, 1768), (172, 236, 1770), (171, 237, 1772), (170, 238, 1774), (169, 239, 1775), (168, 240, 1777), (167, 241, 1779), (166, 242, 1781), (165, 243, 1783), (164, 244, 1785), (163, 245, 1787), (162, 246, 1789), (161, 247, 1791), (159, 248, 1794), (158, 249, 1796), (157, 250, 1798), (156, 251, 1800), (154, 252, 1803), (153, 253, 1805), (152, 254, 1807), (151, 255, 1809), (149, 256, 1812), (148, 257, 1815), (146, 258, 1818), (145, 259, 1820), (143, 260, 1823), (142, 261, 1826), (140, 262, 1829), (138, 263, 1833), (137, 264, 1835), (135, 265, 1839), (133, 266, 1842), (132, 267, 1845), (130, 268, 1849), (128, 269, 1852), (126, 270, 1856), (125, 271, 1859), (124, 272, 1862), (122, 273, 1865), (121, 274, 1868), (120, 275, 1871), (119, 276, 1873), (118, 277, 1876), (116, 278, 1879), (115, 279, 1881), (114, 280, 1884), (113, 281, 1886), (112, 282, 1888), (111, 283, 1890), (110, 284, 1892), (109, 285, 1895), (108, 286, 1897), (108, 287, 1898), (107, 288, 1900), (106, 289, 1902), (105, 290, 1904), (104, 291, 1906), (103, 292, 1908), (103, 293, 1909), (102, 294, 1910), (101, 295, 1912), (101, 296, 1913), (100, 297, 1915), (99, 298, 1917), (99, 299, 1918), (98, 300, 1919), (97, 301, 1921), (97, 302, 1922), (96, 303, 1924), (95, 304, 1925), (95, 305, 1926), (94, 306, 1928), (94, 307, 1928), (93, 308, 1930), (93, 309, 1930), (93, 310, 1931), (93, 311, 1931), (92, 312, 1933), (92, 313, 1933), (92, 314, 1934), (92, 315, 1934), (91, 316, 1936), (91, 317, 1936), (91, 318, 1937), (91, 319, 1937), (90, 320, 1939), (90, 321, 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380, 2005), (72, 381, 2006), (72, 382, 2007), (71, 383, 2009), (71, 384, 2009), (71, 385, 2010), (70, 386, 2012), (70, 387, 2012), (70, 388, 2013), (70, 389, 2013), (69, 390, 2015), (69, 391, 2015), (69, 392, 2016), (68, 393, 2017), (68, 394, 2018), (68, 395, 2019), (67, 396, 2020), (67, 397, 2021), (67, 398, 2021), (66, 399, 2023), (66, 400, 2023), (65, 401, 2025), (65, 402, 2025), (65, 403, 2026), (64, 404, 2027), (64, 405, 2028), (64, 406, 2028), (63, 407, 2030), (63, 408, 2030), (63, 409, 2031), (62, 410, 2032), (62, 411, 2033), (61, 412, 2034), (61, 413, 2034), (61, 414, 2035), (60, 415, 2036), (60, 416, 2037), (59, 417, 2038), (59, 418, 2039), (58, 419, 2040), (58, 420, 2041), (58, 421, 2041), (57, 422, 2042), (57, 423, 2043), (56, 424, 2044), (56, 425, 2045), (55, 426, 2046), (55, 427, 2047), (54, 428, 2048), (54, 429, 2048), (53, 430, 2050), (53, 431, 2050), (52, 432, 2052), (52, 433, 2052), (51, 434, 2053), (51, 435, 2054), (50, 436, 2055), (50, 437, 2055), (49, 438, 2057), 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['1001,2150,936,2144,763,2090,694,2075,619,2040,365,1986,215,1963,128,1971,54,1825,39,1677,39,1454,29,1243,27,757,21,696,27,543,39,458,93,308,116,278,210,206,291,179,373,132,520,121,1430,121,1584,128,1663,142,1768,178,1904,204,2021,306,2076,379,2148,535,2168,614,2165,833,2128,914,2112,994,2078,1072,2031,1132,1997,1214,1967,1255,1931,1368,1879,1444,1846,1670,1780,1868,1756,1920,1662,2015,1582,2015,1497,2039,1420,2046,1339,2070,1177,2101,1097,2141'])], 'temp/1740634567_2299934_917877156_a9c2d4b99270c9302def4ed40606e685.jpg']} nb pixel non reg : 3692295 nb pixel common : 3690329 proportion of common points : 0.9994675398363349 [('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/27022025/python_test3//data_2/data_log/job/2025/February/27022025/python_test3/log-python3----short_python3--v--marlene-06:35:00.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 : 0.23969817161560059 #### 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 Thu Feb 27 06:36:58 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1740634618_2299934_1189321094_9626af7f95d010f2a4fd524688d4ea22_76896585.png': 1189321094} map_photo_id_path_extension : {1189321094: {'path': 'temp/1740634618_2299934_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 16.00 MiB (GPU 0; 10.76 GiB total capacity; 485.94 MiB already allocated; 32.88 MiB free; 530.00 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 16.00 MiB (GPU 0; 10.76 GiB total capacity; 485.94 MiB already allocated; 32.88 MiB free; 530.00 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 : 0.027525663375854492 save_final ERROR in last step sam, CUDA out of memory. Tried to allocate 16.00 MiB (GPU 0; 10.76 GiB total capacity; 485.94 MiB already allocated; 32.88 MiB free; 530.00 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 : 7.531125783920288 time spend to save output : 0.09711194038391113 total time spend for step 0 : 7.628237724304199 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 : 0.11628437042236328 #### 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 Thu Feb 27 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 After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1740634626_2299934_917754606_35f3c9ae49686a6be16030c6ec25c9ee.jpg': 917754606} map_photo_id_path_extension : {917754606: {'path': 'temp/1740634626_2299934_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 E0227 06:37:07.738729 2299934 common.cpp:114] Cannot create Cublas handle. Cublas won't be available. F0227 06:37:07.818006 2299934 syncedmem.hpp:22] Check failed: error == cudaSuccess (2 vs. 0) out of memory *** Check failure stack trace: *** Command terminated by signal 6 37.33user 25.83system 1:43.44elapsed 61%CPU (0avgtext+0avgdata 2868188maxresident)k 2606408inputs+4664outputs (6643major+2933756minor)pagefaults 0swaps