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 : 3185 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 : 0.17315125465393066 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 Mar 20 18:35:29 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Beginning of datou step mask_detect ! save_polygon : True begin detect begin to check gpu status inside check gpu memory l 3637 free memory gpu now : 3185 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 2025-03-20 18:35:33.152907: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2025-03-20 18:35:33.187109: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493065000 Hz 2025-03-20 18:35:33.189572: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f0034000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-03-20 18:35:33.189660: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-03-20 18:35:33.196353: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-03-20 18:35:33.471904: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x15796b60 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-03-20 18:35:33.471964: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-03-20 18:35:33.473275: 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 2025-03-20 18:35:33.474311: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-03-20 18:35:33.486241: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-03-20 18:35:33.503631: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-03-20 18:35:33.504945: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-03-20 18:35:33.530218: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-03-20 18:35:33.534371: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-03-20 18:35:33.582682: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-03-20 18:35:33.584386: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-03-20 18:35:33.584949: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-03-20 18:35:33.586148: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-03-20 18:35:33.586177: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-03-20 18:35:33.586192: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-03-20 18:35:33.588118: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 2733 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 2025-03-20 18:35:34.887987: 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 2025-03-20 18:35:34.888074: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-03-20 18:35:34.888095: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-03-20 18:35:34.888114: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-03-20 18:35:34.888131: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-03-20 18:35:34.888149: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-03-20 18:35:34.888179: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-03-20 18:35:34.888198: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-03-20 18:35:34.889252: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-03-20 18:35:34.890337: 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 2025-03-20 18:35:34.890371: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-03-20 18:35:34.890387: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-03-20 18:35:34.890401: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-03-20 18:35:34.890415: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-03-20 18:35:34.890429: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-03-20 18:35:34.890452: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-03-20 18:35:34.890469: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-03-20 18:35:34.891362: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-03-20 18:35:34.891394: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-03-20 18:35:34.891403: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-03-20 18:35:34.891411: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-03-20 18:35:34.892312: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 2733 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 : [] 2025-03-20 18:35:42.650160: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-03-20 18:35:42.852098: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-03-20 18:35:44.697414: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.697473: 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. 2025-03-20 18:35:44.698024: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.698040: 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. 2025-03-20 18:35:44.704997: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.705016: 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. 2025-03-20 18:35:44.705542: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.705557: 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. 2025-03-20 18:35:44.711991: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.712011: 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. 2025-03-20 18:35:44.712537: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.712552: 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. 2025-03-20 18:35:44.742913: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.742935: 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. 2025-03-20 18:35:44.743469: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.743484: 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. 2025-03-20 18:35:44.749280: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.749302: 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. 2025-03-20 18:35:44.749889: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.749905: 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. 2025-03-20 18:35:44.783481: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.784019: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.785816: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.786348: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.829805: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.830394: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.832618: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.833152: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.840925: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.841509: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.846321: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.846921: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.859374: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.859942: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.861669: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.862251: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.868466: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.869052: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.870753: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.871352: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.877531: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.878116: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.879662: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.880243: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.906707: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.907258: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.907784: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.908307: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.912202: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.912750: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.928630: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.929157: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.929678: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.930198: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.942522: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.943057: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.943583: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.944111: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.948254: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.948782: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.953208: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.953789: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.965671: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.966205: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.970330: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.970888: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.971459: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.971988: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.993003: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.993736: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.994333: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.994921: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.995506: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:44.996081: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:45.011920: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:45.012934: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:45.042627: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:45.042668: 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. 2025-03-20 18:35:45.043738: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:45.044802: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:45.051859: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:45.052580: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:45.060948: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:45.061497: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:45.083242: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:45.084008: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:45.084573: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:45.085144: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:45.089163: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:45.089705: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:45.090241: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:45.090775: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:45.091806: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:45.101928: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:45.102482: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:45.121614: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:45.122387: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:45.123378: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:45.124602: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:45.125578: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:35:45.126535: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 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 558384 begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 1992 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 : 3185 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 : 0.0005152225494384766 nb_pixel_total : 15551 time to create 1 rle with old method : 0.016625165939331055 length of segment : 256 time for calcul the mask position with numpy : 0.002617359161376953 nb_pixel_total : 145329 time to create 1 rle with old method : 0.15396618843078613 length of segment : 371 time for calcul the mask position with numpy : 0.00021719932556152344 nb_pixel_total : 14255 time to create 1 rle with old method : 0.015923500061035156 length of segment : 151 time for calcul the mask position with numpy : 0.00011348724365234375 nb_pixel_total : 5613 time to create 1 rle with old method : 0.0068628787994384766 length of segment : 48 time for calcul the mask position with numpy : 7.462501525878906e-05 nb_pixel_total : 1825 time to create 1 rle with old method : 0.0023093223571777344 length of segment : 39 time spent for convertir_results : 2.0989675521850586 time spend for datou_step_exec : 21.213653087615967 time spend to save output : 4.1484832763671875e-05 total time spend for step 1 : 21.21369457244873 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 3316 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 : 0.3668794631958008 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, 0.99548763, [(140, 26, 6), (135, 27, 15), (133, 28, 18), (131, 29, 22), (127, 30, 27), (10, 31, 1), (120, 31, 35), (8, 32, 13), (27, 32, 3), (115, 32, 41), (7, 33, 52), (109, 33, 48), (6, 34, 70), (103, 34, 55), (5, 35, 154), (4, 36, 155), (3, 37, 156), (3, 38, 156), (3, 39, 156), (2, 40, 157), (2, 41, 157), (2, 42, 157), (2, 43, 157), (2, 44, 157), (2, 45, 157), (1, 46, 158), (1, 47, 158), (1, 48, 158), (1, 49, 157), (1, 50, 157), (1, 51, 156), (1, 52, 156), (1, 53, 155), (1, 54, 154), (1, 55, 152), (1, 56, 149), (1, 57, 145), (1, 58, 141), (1, 59, 136), (1, 60, 133), (1, 61, 130), (1, 62, 127), (1, 63, 126), (1, 64, 124), (1, 65, 123), (1, 66, 121), (1, 67, 120), (1, 68, 118), (1, 69, 117), (1, 70, 116), (1, 71, 115), (1, 72, 114), (1, 73, 113), (1, 74, 112), (1, 75, 111), (1, 76, 110), (1, 77, 108), (1, 78, 108), (1, 79, 107), (1, 80, 106), (1, 81, 105), (2, 82, 104), (2, 83, 103), (2, 84, 103), (2, 85, 102), (2, 86, 102), (2, 87, 101), (2, 88, 100), (2, 89, 99), (2, 90, 99), (2, 91, 98), (2, 92, 97), (2, 93, 96), (2, 94, 95), (2, 95, 93), (2, 96, 91), (2, 97, 90), (2, 98, 89), (2, 99, 87), (2, 100, 86), (2, 101, 86), (2, 102, 85), (2, 103, 84), (2, 104, 83), (2, 105, 83), (2, 106, 82), (2, 107, 81), (2, 108, 80), (2, 109, 80), (2, 110, 79), (2, 111, 78), (2, 112, 77), (2, 113, 76), (1, 114, 76), (1, 115, 75), (1, 116, 74), (1, 117, 73), (1, 118, 72), (1, 119, 71), (1, 120, 71), (1, 121, 70), (1, 122, 69), (1, 123, 69), (1, 124, 68), (1, 125, 68), (1, 126, 67), (1, 127, 67), (1, 128, 66), (1, 129, 66), (1, 130, 66), (1, 131, 65), (1, 132, 65), (1, 133, 64), (1, 134, 63), (1, 135, 63), (1, 136, 62), (1, 137, 61), (1, 138, 60), (1, 139, 60), (1, 140, 59), (1, 141, 58), (1, 142, 58), (1, 143, 57), (1, 144, 56), (1, 145, 56), (1, 146, 55), (1, 147, 54), (1, 148, 54), (1, 149, 53), (1, 150, 52), (1, 151, 52), (1, 152, 51), (1, 153, 50), (1, 154, 49), (1, 155, 48), (1, 156, 47), (1, 157, 46), (1, 158, 45), (1, 159, 45), (1, 160, 44), (1, 161, 43), (1, 162, 42), (1, 163, 41), (1, 164, 41), (1, 165, 40), (1, 166, 40), (1, 167, 39), (1, 168, 38), (1, 169, 37), (1, 170, 36), (1, 171, 35), (1, 172, 34), (1, 173, 34), (1, 174, 33), (1, 175, 33), (1, 176, 32), (1, 177, 32), (1, 178, 32), (1, 179, 32), (1, 180, 31), (1, 181, 31), (1, 182, 31), (1, 183, 30), (1, 184, 30), (1, 185, 30), (1, 186, 29), (1, 187, 29), (1, 188, 29), (1, 189, 28), (1, 190, 28), (1, 191, 27), (1, 192, 27), (1, 193, 26), (1, 194, 26), (1, 195, 26), (1, 196, 26), (1, 197, 26), (1, 198, 26), (1, 199, 26), (1, 200, 25), (1, 201, 25), (1, 202, 25), (1, 203, 25), (1, 204, 25), (1, 205, 25), (1, 206, 25), (1, 207, 25), (1, 208, 25), (1, 209, 25), (1, 210, 25), (1, 211, 25), (1, 212, 25), (1, 213, 25), (1, 214, 25), (1, 215, 25), (1, 216, 25), (1, 217, 25), (1, 218, 25), (1, 219, 25), (1, 220, 24), (1, 221, 24), (1, 222, 24), (1, 223, 24), (1, 224, 24), (1, 225, 24), (1, 226, 25), (1, 227, 25), (1, 228, 25), (2, 229, 24), (2, 230, 24), (2, 231, 24), (2, 232, 23), (2, 233, 23), (2, 234, 23), (2, 235, 23), (2, 236, 23), (2, 237, 23), (2, 238, 23), (2, 239, 23), (2, 240, 23), (2, 241, 23), (2, 242, 23), (2, 243, 23), (2, 244, 23), (2, 245, 23), (2, 246, 23), (2, 247, 23), (2, 248, 23), (2, 249, 24), (2, 250, 24), (2, 251, 23), (2, 252, 23), (2, 253, 23), (2, 254, 23), (2, 255, 23), (2, 256, 23), (2, 257, 23), (2, 258, 23), (2, 259, 23), (2, 260, 23), (2, 261, 23), (3, 262, 22), (3, 263, 22), (3, 264, 22), (3, 265, 22), (4, 266, 21), (4, 267, 21), (5, 268, 20), (5, 269, 20), (6, 270, 19), (7, 271, 17), (8, 272, 16), (8, 273, 16), (9, 274, 13), (11, 275, 9), (15, 276, 2)], ['16,276,8,273,2,261,2,229,1,228,1,114,2,113,2,82,1,81,1,46,3,37,8,32,20,32,21,33,58,33,59,34,75,34,76,35,102,35,114,33,120,31,130,30,135,27,145,26,152,29,158,35,158,48,154,54,141,58,128,61,119,67,105,81,103,86,96,94,89,98,81,109,71,119,65,132,60,138,52,151,45,158,40,166,34,172,29,188,26,193,25,200,25,219,24,232,24,270,23,273']), (957285035, 492601069, 445, 29, 591, 24, 419, 0.99238414, [(315, 37, 25), (272, 38, 86), (253, 39, 130), (238, 40, 151), (199, 41, 196), (189, 42, 213), (180, 43, 238), (175, 44, 250), (172, 45, 257), (169, 46, 265), (166, 47, 274), (162, 48, 284), (159, 49, 294), (157, 50, 304), (155, 51, 311), (153, 52, 317), (151, 53, 323), (149, 54, 330), (148, 55, 334), (146, 56, 337), (144, 57, 341), (142, 58, 344), (140, 59, 347), (138, 60, 350), (136, 61, 353), (134, 62, 356), (132, 63, 358), (130, 64, 361), (128, 65, 364), (126, 66, 367), (124, 67, 370), (122, 68, 373), (120, 69, 376), (118, 70, 379), (117, 71, 381), (115, 72, 385), (114, 73, 387), (113, 74, 389), (112, 75, 391), (112, 76, 393), (111, 77, 395), (110, 78, 397), (109, 79, 399), (109, 80, 400), (108, 81, 402), (107, 82, 404), (107, 83, 404), (106, 84, 406), (105, 85, 408), (105, 86, 409), (104, 87, 410), (104, 88, 411), (103, 89, 413), (102, 90, 415), (101, 91, 417), (100, 92, 420), (98, 93, 423), (97, 94, 426), (96, 95, 428), (94, 96, 431), (93, 97, 433), (92, 98, 435), (91, 99, 437), (90, 100, 439), (89, 101, 441), (89, 102, 441), (89, 103, 442), (89, 104, 443), (89, 105, 444), (89, 106, 444), (89, 107, 445), (89, 108, 446), (89, 109, 447), (89, 110, 448), (89, 111, 449), (89, 112, 450), (89, 113, 451), (89, 114, 453), (89, 115, 454), (89, 116, 455), (88, 117, 456), (88, 118, 457), (87, 119, 459), (87, 120, 459), (86, 121, 461), (85, 122, 462), (85, 123, 463), (84, 124, 464), (84, 125, 465), (83, 126, 466), (82, 127, 468), (82, 128, 468), (81, 129, 470), (80, 130, 471), (78, 131, 473), (76, 132, 476), (75, 133, 477), (73, 134, 480), (71, 135, 482), (70, 136, 484), (68, 137, 486), (67, 138, 488), (65, 139, 490), (64, 140, 492), (63, 141, 493), (61, 142, 496), (60, 143, 497), (59, 144, 499), (58, 145, 501), (58, 146, 501), (57, 147, 503), (57, 148, 504), (57, 149, 505), (56, 150, 507), (56, 151, 507), (55, 152, 509), (55, 153, 510), (54, 154, 511), (54, 155, 512), (54, 156, 513), (53, 157, 514), (53, 158, 514), (52, 159, 515), (52, 160, 516), (52, 161, 516), (51, 162, 517), (51, 163, 517), (50, 164, 518), (50, 165, 518), (49, 166, 519), (49, 167, 520), (48, 168, 521), (48, 169, 521), (47, 170, 522), (47, 171, 522), (46, 172, 523), (46, 173, 523), (46, 174, 523), 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(474, 33, 36), (475, 34, 33), (475, 35, 32), (476, 36, 30), (476, 37, 29), (477, 38, 26), (478, 39, 23), (479, 40, 20), (480, 41, 17), (488, 42, 5)], ['492,42,488,42,487,41,480,41,476,37,475,34,473,32,469,25,465,21,461,20,457,16,457,10,466,9,470,12,474,13,476,11,480,10,482,8,500,8,501,9,524,9,525,10,528,10,532,12,539,12,542,15,545,15,545,19,535,20,534,21,529,21,525,23,523,23,513,30,512,30,504,37,496,41,493,41'])], 'temp/1742492129_557939_957285035_a42482e51c93c8025d243dd179aee85b.jpg']} free memory after detection : begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 3185 ############################### 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 : 0.24479126930236816 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 Mar 20 18:35:53 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 : 3185 max_wait_temp : 1 max_wait : 0 gpu_flag : 0 2025-03-20 18:35:55.545262: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2025-03-20 18:35:55.571172: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493065000 Hz 2025-03-20 18:35:55.573260: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f0034000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-03-20 18:35:55.573312: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-03-20 18:35:55.576402: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-03-20 18:35:55.841945: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x160b1170 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-03-20 18:35:55.841991: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-03-20 18:35:55.842825: 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 2025-03-20 18:35:55.843225: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-03-20 18:35:55.845888: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-03-20 18:35:55.848409: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-03-20 18:35:55.848847: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-03-20 18:35:55.851732: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-03-20 18:35:55.852904: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-03-20 18:35:55.860944: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-03-20 18:35:55.862278: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-03-20 18:35:55.862374: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-03-20 18:35:55.863091: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-03-20 18:35:55.863114: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-03-20 18:35:55.863125: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-03-20 18:35:55.864324: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 2733 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. 2025-03-20 18:35:55.955245: 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 2025-03-20 18:35:55.955371: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-03-20 18:35:55.955397: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-03-20 18:35:55.955420: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-03-20 18:35:55.955442: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-03-20 18:35:55.955464: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-03-20 18:35:55.955485: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-03-20 18:35:55.955508: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-03-20 18:35:55.956301: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-03-20 18:35:55.957219: 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 2025-03-20 18:35:55.957252: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-03-20 18:35:55.957269: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-03-20 18:35:55.957286: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-03-20 18:35:55.957304: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-03-20 18:35:55.957336: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-03-20 18:35:55.957352: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-03-20 18:35:55.957368: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-03-20 18:35:55.958134: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-03-20 18:35:55.958167: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-03-20 18:35:55.958174: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-03-20 18:35:55.958181: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-03-20 18:35:55.958981: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 2733 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 : [] 2025-03-20 18:36:02.521359: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-03-20 18:36:02.714473: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-03-20 18:36:04.421435: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.421495: 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. 2025-03-20 18:36:04.422115: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.422132: 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. 2025-03-20 18:36:04.429315: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.429336: 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. 2025-03-20 18:36:04.429905: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.429921: 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. 2025-03-20 18:36:04.436585: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.436610: 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. 2025-03-20 18:36:04.437186: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.437202: 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. 2025-03-20 18:36:04.468595: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.468628: 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. 2025-03-20 18:36:04.469197: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.469212: 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. 2025-03-20 18:36:04.475096: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.475118: 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. 2025-03-20 18:36:04.475689: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.475705: 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. 2025-03-20 18:36:04.511008: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.511954: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.514166: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.515101: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.562114: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.563038: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.565481: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.566370: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.573800: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.574693: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.580296: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.581061: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.593726: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.594327: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.596007: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.596586: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.603017: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.603609: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.605411: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.605997: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.612741: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.613333: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.615042: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.615656: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.646706: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.647522: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.648155: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.648745: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.652636: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.653227: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.669359: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.670095: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.670803: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.671575: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.685951: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.686537: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.687089: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.687681: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.692432: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.693009: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.698035: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.698623: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.712354: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.713082: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.717413: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.717990: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.718546: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.719080: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.743439: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.744033: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.744609: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.745141: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.745671: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.746202: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.760520: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.761060: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.784300: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.784339: 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. 2025-03-20 18:36:04.785417: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.786415: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.795651: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.796552: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.808404: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.809001: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.826415: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.827038: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.827633: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.828200: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.832547: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.833251: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.833813: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.834372: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.835459: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.846640: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.847211: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.858520: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.859470: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.860090: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.860659: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.861199: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-03-20 18:36:04.861727: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.17G (2330853376 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 559324 begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 1701 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 : 2386 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 : 0.0005357265472412109 nb_pixel_total : 16881 time to create 1 rle with old method : 0.021325111389160156 length of segment : 107 time for calcul the mask position with numpy : 0.24863028526306152 nb_pixel_total : 481407 time to create 1 rle with new method : 0.030482769012451172 length of segment : 633 time for calcul the mask position with numpy : 0.0005085468292236328 nb_pixel_total : 36642 time to create 1 rle with old method : 0.04132556915283203 length of segment : 133 time for calcul the mask position with numpy : 0.00011801719665527344 nb_pixel_total : 4794 time to create 1 rle with old method : 0.005825519561767578 length of segment : 51 time spent for convertir_results : 0.5298535823822021 time spend for datou_step_exec : 15.673583269119263 time spend to save output : 6.318092346191406e-05 total time spend for step 1 : 15.673646450042725 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 404 chid ids of type : 445 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 633 begin to insert list_values into mtr_datou_result : length of list_values in save_final : 1 time used for this insertion : 0.02097344398498535 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, 0.9988607, [(1205, 1, 58), (1165, 2, 105), (1159, 3, 113), (1150, 4, 123), (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), (1095, 35, 184), (1096, 36, 183), (1096, 37, 184), (1096, 38, 184), (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), (1108, 79, 172), (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), (1118, 90, 161), (1121, 91, 158), (1142, 92, 137), (1148, 93, 131), (1156, 94, 123), (1170, 95, 109), (1179, 96, 100), (1184, 97, 94), (1186, 98, 92), (1187, 99, 90), (1189, 100, 54), (1264, 100, 12), (1190, 101, 50), (1192, 102, 45), (1194, 103, 40), (1198, 104, 33), (1202, 105, 25), (1208, 106, 15)], ['1222,106,1208,106,1194,103,1183,96,1178,95,1170,95,1169,94,1156,94,1155,93,1148,93,1141,91,1121,91,1115,89,1108,81,1106,73,1106,64,1105,63,1104,55,1099,46,1098,41,1095,35,1095,8,1100,6,1112,6,1113,5,1149,5,1150,4,1158,4,1165,2,1204,2,1205,1,1262,1,1269,2,1273,5,1273,13,1271,18,1271,22,1273,27,1277,31,1279,37,1279,86,1278,87,1278,96,1275,100,1264,100,1263,99,1243,99,1234,102,1230,104,1223,105']), (917855882, 492601069, 445, 54, 1096, 4, 668, 0.9975745, [(958, 20, 19), (942, 21, 57), (619, 22, 25), (923, 22, 87), (586, 23, 144), (897, 23, 121), (571, 24, 455), (556, 25, 479), (546, 26, 495), (537, 27, 508), (528, 28, 521), (519, 29, 533), (516, 30, 539), (513, 31, 545), (510, 32, 550), (508, 33, 555), (505, 34, 560), (503, 35, 565), (502, 36, 568), (500, 37, 572), (498, 38, 576), (497, 39, 579), (496, 40, 581), (495, 41, 583), (494, 42, 585), (492, 43, 587), (491, 44, 589), (489, 45, 592), (488, 46, 594), (486, 47, 596), (484, 48, 599), (483, 49, 600), (481, 50, 603), (479, 51, 606), (477, 52, 608), (475, 53, 611), (474, 54, 612), (472, 55, 615), (471, 56, 616), (470, 57, 618), (469, 58, 619), (468, 59, 620), (467, 60, 622), (466, 61, 623), (465, 62, 625), (464, 63, 626), (463, 64, 627), (462, 65, 628), (461, 66, 629), (460, 67, 630), (460, 68, 630), (459, 69, 631), (458, 70, 632), (457, 71, 633), (456, 72, 634), (454, 73, 636), (453, 74, 637), (452, 75, 639), (451, 76, 640), (449, 77, 642), (448, 78, 643), (447, 79, 644), (445, 80, 646), (443, 81, 648), (442, 82, 649), (441, 83, 650), (439, 84, 652), (438, 85, 653), (437, 86, 654), (436, 87, 655), (434, 88, 657), (433, 89, 658), (431, 90, 660), (429, 91, 662), (427, 92, 664), (425, 93, 666), (423, 94, 668), (421, 95, 670), (419, 96, 672), (416, 97, 675), (413, 98, 678), (410, 99, 681), (407, 100, 684), (403, 101, 689), (400, 102, 692), (397, 103, 695), (394, 104, 698), (392, 105, 700), (389, 106, 703), (387, 107, 705), (385, 108, 707), (383, 109, 709), (382, 110, 710), (380, 111, 712), (378, 112, 714), (376, 113, 716), (374, 114, 718), (371, 115, 721), (368, 116, 724), (363, 117, 729), (359, 118, 733), (354, 119, 738), (350, 120, 742), (345, 121, 747), (339, 122, 753), (334, 123, 758), (329, 124, 763), (325, 125, 767), (321, 126, 771), (318, 127, 774), (315, 128, 777), (312, 129, 780), (309, 130, 783), (306, 131, 786), (303, 132, 789), (301, 133, 791), (299, 134, 793), (296, 135, 796), (293, 136, 799), (289, 137, 803), (285, 138, 807), (280, 139, 812), (275, 140, 817), (269, 141, 823), (264, 142, 828), (257, 143, 835), (250, 144, 842), (243, 145, 849), (237, 146, 855), (230, 147, 862), (223, 148, 869), (217, 149, 875), (212, 150, 880), (207, 151, 885), (203, 152, 889), (199, 153, 893), (196, 154, 896), (193, 155, 899), (190, 156, 902), (187, 157, 905), (184, 158, 908), (182, 159, 910), (180, 160, 912), (178, 161, 914), (176, 162, 916), (173, 163, 919), (171, 164, 921), (169, 165, 923), (166, 166, 926), (164, 167, 928), (161, 168, 931), (158, 169, 934), (155, 170, 937), (152, 171, 940), (149, 172, 943), (147, 173, 945), (145, 174, 947), (143, 175, 949), (141, 176, 951), (140, 177, 952), (138, 178, 954), (137, 179, 955), (136, 180, 956), (135, 181, 957), (134, 182, 958), (133, 183, 959), (132, 184, 960), (132, 185, 960), (131, 186, 961), (130, 187, 962), (129, 188, 963), (128, 189, 964), (128, 190, 964), (127, 191, 965), (126, 192, 965), (125, 193, 966), (124, 194, 967), (124, 195, 967), (123, 196, 968), (122, 197, 969), (121, 198, 970), (120, 199, 971), (119, 200, 972), (119, 201, 972), (118, 202, 973), (117, 203, 974), (116, 204, 975), (115, 205, 975), (114, 206, 976), (113, 207, 977), (112, 208, 978), (110, 209, 980), (109, 210, 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(118, 521, 691), (119, 522, 690), (121, 523, 687), (122, 524, 685), (124, 525, 683), (125, 526, 681), (127, 527, 678), (128, 528, 677), (130, 529, 674), (131, 530, 673), (132, 531, 671), (134, 532, 668), (135, 533, 667), (137, 534, 664), (138, 535, 663), (139, 536, 661), (141, 537, 659), (142, 538, 657), (144, 539, 655), (145, 540, 653), (147, 541, 651), (149, 542, 648), (150, 543, 647), (152, 544, 644), (154, 545, 641), (156, 546, 639), (157, 547, 637), (159, 548, 634), (160, 549, 633), (162, 550, 630), (163, 551, 628), (165, 552, 625), (166, 553, 623), (168, 554, 621), (169, 555, 619), (170, 556, 617), (172, 557, 614), (173, 558, 612), (174, 559, 610), (175, 560, 608), (177, 561, 605), (178, 562, 603), (180, 563, 600), (181, 564, 598), (183, 565, 595), (186, 566, 592), (189, 567, 588), (191, 568, 585), (194, 569, 581), (197, 570, 577), (200, 571, 573), (203, 572, 570), (206, 573, 566), (208, 574, 563), (211, 575, 560), (214, 576, 556), (217, 577, 552), (219, 578, 550), (222, 579, 546), (224, 580, 543), (226, 581, 541), (228, 582, 538), (229, 583, 537), (231, 584, 534), (232, 585, 533), (234, 586, 530), (236, 587, 527), (237, 588, 525), (239, 589, 523), (241, 590, 520), (243, 591, 517), (245, 592, 514), (247, 593, 512), (249, 594, 509), (252, 595, 505), (254, 596, 502), (257, 597, 498), (260, 598, 494), (264, 599, 489), (267, 600, 485), (271, 601, 480), (274, 602, 476), (278, 603, 471), (281, 604, 467), (284, 605, 463), (287, 606, 459), (290, 607, 454), (292, 608, 451), (295, 609, 447), (297, 610, 442), (299, 611, 438), (302, 612, 433), (304, 613, 429), (306, 614, 425), (309, 615, 420), (311, 616, 415), (313, 617, 411), (316, 618, 406), (318, 619, 402), (321, 620, 397), (323, 621, 392), (326, 622, 387), (329, 623, 382), (332, 624, 376), (335, 625, 371), (339, 626, 365), (343, 627, 358), (347, 628, 352), (350, 629, 347), (354, 630, 342), (357, 631, 337), (360, 632, 332), (364, 633, 326), (369, 634, 319), (373, 635, 313), (377, 636, 306), (382, 637, 299), (387, 638, 291), (393, 639, 282), (399, 640, 273), (406, 641, 262), (419, 642, 240), (434, 643, 216), (449, 644, 192), (464, 645, 167), (478, 646, 145), (493, 647, 122), (506, 648, 101), (519, 649, 81), (546, 650, 46)], ['591,650,519,649,406,641,377,636,323,621,289,606,249,594,216,576,183,565,100,507,89,492,66,439,62,352,70,300,84,268,95,226,138,178,184,158,207,151,284,139,321,126,373,115,432,90,472,55,503,35,519,29,586,23,729,23,730,24,896,24,958,20,998,21,1040,26,1075,39,1089,62,1091,101,1091,191,1082,241,1044,302,993,337,942,379,921,391,898,420,875,435,843,466,827,500,808,521,792,549,745,606,667,641']), (917855882, 492601069, 445, 0, 440, 0, 116, 0.9919478, [(127, 1, 141), (94, 2, 206), (384, 2, 2), (59, 3, 273), (340, 3, 57), (22, 4, 381), (19, 5, 387), (16, 6, 392), (15, 7, 394), (14, 8, 396), (14, 9, 397), (13, 10, 399), (12, 11, 400), (12, 12, 400), (11, 13, 402), (10, 14, 403), (11, 15, 403), (11, 16, 404), (12, 17, 403), (12, 18, 404), (12, 19, 405), (12, 20, 405), (12, 21, 406), (12, 22, 406), (12, 23, 407), (12, 24, 407), (12, 25, 408), (12, 26, 408), (12, 27, 408), (12, 28, 408), (12, 29, 409), (12, 30, 409), (12, 31, 409), (12, 32, 409), (12, 33, 409), (12, 34, 410), (12, 35, 410), (12, 36, 410), (12, 37, 410), (12, 38, 410), (12, 39, 410), (12, 40, 410), (12, 41, 411), (12, 42, 411), (12, 43, 411), (12, 44, 411), (12, 45, 411), (12, 46, 410), (12, 47, 410), (12, 48, 410), (12, 49, 410), (12, 50, 410), (12, 51, 410), (12, 52, 409), (12, 53, 408), (12, 54, 408), (12, 55, 407), (12, 56, 406), (12, 57, 404), (12, 58, 403), (11, 59, 403), (11, 60, 402), (11, 61, 401), (11, 62, 400), (11, 63, 400), (11, 64, 399), (11, 65, 398), (11, 66, 397), (11, 67, 397), (11, 68, 396), (11, 69, 395), (11, 70, 395), (11, 71, 394), (11, 72, 394), (11, 73, 394), (11, 74, 393), (11, 75, 393), (11, 76, 393), (11, 77, 393), (11, 78, 393), (11, 79, 393), (11, 80, 392), (10, 81, 394), (10, 82, 394), (10, 83, 395), (9, 84, 396), (9, 85, 262), (279, 85, 126), (9, 86, 75), (98, 86, 28), (142, 86, 117), (292, 86, 112), (9, 87, 71), (152, 87, 103), (294, 87, 110), (8, 88, 68), (161, 88, 91), (296, 88, 107), (8, 89, 63), (176, 89, 73), (297, 89, 106), (7, 90, 61), (205, 90, 40), (298, 90, 104), (7, 91, 57), (299, 91, 103), (6, 92, 54), (300, 92, 102), (6, 93, 50), (301, 93, 100), (7, 94, 46), (303, 94, 97), (7, 95, 44), (306, 95, 92), (7, 96, 42), (308, 96, 89), (7, 97, 40), (310, 97, 86), (7, 98, 38), (312, 98, 83), (8, 99, 34), (314, 99, 79), (8, 100, 32), (317, 100, 75), (8, 101, 29), (319, 101, 71), (13, 102, 19), (324, 102, 63), (20, 103, 6), (330, 103, 51), (337, 104, 37), (344, 105, 22), (352, 106, 3)], ['344,105,319,101,301,93,291,85,259,85,244,90,205,90,204,89,176,89,161,88,141,85,126,85,125,86,98,86,84,85,56,92,36,101,26,102,8,101,6,92,11,80,11,59,12,58,12,17,10,14,16,6,22,4,58,4,59,3,93,3,94,2,126,2,127,1,267,1,268,2,331,3,396,3,407,6,411,10,419,25,421,34,421,51,410,62,404,71,402,80,404,85,401,92,394,98,386,102,365,105']), (917855882, 492601069, 445, 390, 550, 0, 54, 0.9391909, [(414, 0, 7), (441, 0, 60), (508, 0, 28), (402, 1, 142), (401, 2, 146), (402, 3, 145), (404, 4, 143), (406, 5, 140), (408, 6, 137), (410, 7, 134), (411, 8, 132), (412, 9, 130), (413, 10, 127), (414, 11, 125), (415, 12, 123), (415, 13, 122), (416, 14, 120), (417, 15, 117), (417, 16, 116), (418, 17, 114), (418, 18, 113), (418, 19, 111), (418, 20, 109), (419, 21, 107), (419, 22, 105), (419, 23, 103), (419, 24, 102), (419, 25, 100), (420, 26, 97), (420, 27, 95), (420, 28, 94), (421, 29, 91), (421, 30, 90), (422, 31, 88), (422, 32, 88), (422, 33, 87), (423, 34, 84), (423, 35, 82), (423, 36, 81), (424, 37, 79), (424, 38, 77), (424, 39, 75), (424, 40, 73), (424, 41, 71), (425, 42, 67), (425, 43, 66), (426, 44, 62), (426, 45, 6), (433, 45, 52), (443, 46, 30), (450, 47, 1)], ['450,47,449,46,443,46,442,45,426,45,424,41,424,37,423,36,422,31,419,25,419,21,418,20,418,17,417,15,409,6,402,3,402,1,413,1,414,0,420,0,421,1,440,1,441,0,500,0,501,1,507,1,508,0,535,0,536,1,543,1,546,2,546,4,542,8,530,18,527,19,525,21,522,22,520,24,512,28,508,33,505,34,502,37,494,41,492,41,490,43,488,43,484,45,473,45,472,46,451,46'])], 'temp/1742492152_557939_917855882_da0fa7b7e6b5b551fe26c0ba8713276d.jpg']} error in position expected : (917855882, 492601069, 445, 52, 1128, 16, 668, 0.9977477) got : (917855882, 492601069, 445, 54, 1096, 4, 668, 0.9975745) ERROR test detect objet FAILED ############################### 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 : 0.16124963760375977 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 Mar 20 18:36:11 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 : 2386 wait 20 seconds l 3637 free memory gpu now : 2386 max_wait_temp : 1 max_wait : 0 gpu_flag : 0 2025-03-20 18:36:35.122055: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2025-03-20 18:36:35.147198: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493065000 Hz 2025-03-20 18:36:35.149111: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f0034000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-03-20 18:36:35.149160: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-03-20 18:36:35.153229: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-03-20 18:36:35.365499: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x16d82e20 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-03-20 18:36:35.365580: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-03-20 18:36:35.366436: 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 2025-03-20 18:36:35.367797: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-03-20 18:36:35.375811: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-03-20 18:36:35.383411: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-03-20 18:36:35.384859: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-03-20 18:36:35.399516: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-03-20 18:36:35.402529: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-03-20 18:36:35.426442: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-03-20 18:36:35.428413: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-03-20 18:36:35.428589: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-03-20 18:36:35.429431: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-03-20 18:36:35.429479: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-03-20 18:36:35.429496: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-03-20 18:36:35.430951: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 509 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. 2025-03-20 18:36:35.557663: 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 2025-03-20 18:36:35.557761: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-03-20 18:36:35.557785: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-03-20 18:36:35.557807: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-03-20 18:36:35.557827: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-03-20 18:36:35.557848: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-03-20 18:36:35.557868: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-03-20 18:36:35.557889: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-03-20 18:36:35.558744: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-03-20 18:36:35.559875: 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 2025-03-20 18:36:35.559924: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-03-20 18:36:35.559946: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-03-20 18:36:35.559966: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-03-20 18:36:35.559986: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-03-20 18:36:35.560006: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-03-20 18:36:35.560026: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-03-20 18:36:35.560046: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-03-20 18:36:35.560914: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-03-20 18:36:35.560947: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-03-20 18:36:35.560957: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-03-20 18:36:35.560967: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-03-20 18:36:35.561879: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 509 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 : [] 2025-03-20 18:36:44.677269: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-03-20 18:36:44.871506: E tensorflow/stream_executor/cuda/cuda_blas.cc:238] failed to create cublas handle: CUBLAS_STATUS_NOT_INITIALIZED 2025-03-20 18:36:44.873704: E tensorflow/stream_executor/cuda/cuda_blas.cc:238] failed to create cublas handle: CUBLAS_STATUS_NOT_INITIALIZED 2025-03-20 18:36:44.885034: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-03-20 18:36:44.893441: E tensorflow/stream_executor/cuda/cuda_dnn.cc:329] Could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR 2025-03-20 18:36:44.895812: E tensorflow/stream_executor/cuda/cuda_dnn.cc:329] Could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR 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 error in detect the image : temp/1742492171_557939_917877156_a9c2d4b99270c9302def4ed40606e685.jpg 2 root error(s) found. (0) Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above. [[node conv1/convolution (defined at usr/local/lib/python3.8/dist-packages/keras/backend/tensorflow_backend.py:3007) ]] [[mrcnn_detection/ExpandDims/_52]] (1) Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above. [[node conv1/convolution (defined at usr/local/lib/python3.8/dist-packages/keras/backend/tensorflow_backend.py:3007) ]] 0 successful operations. 0 derived errors ignored. [Op:__inference_keras_scratch_graph_13584] Function call stack: keras_scratch_graph -> keras_scratch_graph Detection mask done ! Trying to reset tf kernel 561332 begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 29 tf kernel not reseted sub process len(results) : 0 len(list_Values) 0 None max_time_sub_proc : 3600 parent process len(results) : 0 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 : 886 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'] WARNING : results is empty ! time spent for convertir_results : 0.00015974044799804688 time spend for datou_step_exec : 36.68251323699951 time spend to save output : 1.9311904907226562e-05 total time spend for step 1 : 36.68253254890442 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 ! begin to insert list_values into mtr_datou_result : length of list_values in save_final : 1 Catched exception ! Connect or reconnect ! time used for this insertion : 1.1449496746063232 save missing photos in datou_result : After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : {'917877156': [[], 'temp/1742492171_557939_917877156_a9c2d4b99270c9302def4ed40606e685.jpg']} ERROR : list index out of range reconnect to base ! warning , we can't find thcl infos in json_data warning , we can't find pdt infos in json_data #&_# TEST FAILED #&_# : tests/mask_test #&_# Error : invalid literal for int() with base 10: 'list index out of range' /home/admin/workarea/git/Velours/python/tests/python_tests.py refs/heads/master_6419193983607b8ec28e462733ffc29d3101ac80 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_6419193983607b8ec28e462733ffc29d3101ac80','{"mask_detection": "fail"}','0','http://marlene.fotonower-preprod.com/job/2025/March/20032025/python_test3//data_2/data_log/job/2025/March/20032025/python_test3/log-python3----short_python3--v--marlene-18:35:02.txt','mask_detection','unknown'); #&_# END OF TEST #&_# : tests/mask_test #&_# #&_# BEGIN OF TEST : tests/datou_test #&_# /home/admin/workarea/git/Velours/python/tests/datou_test.py Datou All Test python version used : 3 ############################### TEST sam ################################ TEST SAM Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=4573 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=4573 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 4573 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=4573 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! no param json to modify List Step Type Loaded in datou : sam list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT photo_id, url FROM MTRBack.photos ph WHERE photo_id IN (1189321094) Found this number of photos: 1 ##### Call download_photos : nb_thread : 5 begin to download photo : 1189321094 download finish for photo 1189321094 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 ##### After load_data_input time to download the photos : 0.2184000015258789 #### 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 Mar 20 18:36:49 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 After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1742492209_557939_1189321094_9626af7f95d010f2a4fd524688d4ea22_76896585.png': 1189321094} map_photo_id_path_extension : {1189321094: {'path': 'temp/1742492209_557939_1189321094_9626af7f95d010f2a4fd524688d4ea22_76896585.png', 'extension': 'png'}} map_subphoto_mainphoto : {} Beginning of datou step sam ! pht : 4677 Inside sam : nb paths : 1 ERROR in datou_step_exec, will save and exit ! CUDA error: out of memory CUDA kernel errors might be asynchronously reported at some other API call,so the stacktrace below might be incorrect. For debugging consider passing CUDA_LAUNCH_BLOCKING=1. 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 367, in datou_step_sam sam.to(device=device) File "/home/admin/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 927, in to return self._apply(convert) File "/home/admin/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 579, in _apply module._apply(fn) File "/home/admin/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 579, in _apply module._apply(fn) File "/home/admin/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 579, in _apply module._apply(fn) File "/home/admin/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 602, in _apply param_applied = fn(param) File "/home/admin/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 925, in convert return t.to(device, dtype if t.is_floating_point() or t.is_complex() else None, non_blocking) [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 error: out of memory\\nCUDA kernel errors might be asynchronously reported at some other API call,so the stacktrace below might be incorrect.\\nFor debugging consider passing CUDA_LAUNCH_BLOCKING=1.']", '-1', '-1.0', '501120777', '1.0', None)] time used for this insertion : 0.024489402770996094 save_final ERROR in last step sam, CUDA error: out of memory CUDA kernel errors might be asynchronously reported at some other API call,so the stacktrace below might be incorrect. For debugging consider passing CUDA_LAUNCH_BLOCKING=1. time spend for datou_step_exec : 6.1351158618927 time spend to save output : 0.060304880142211914 total time spend for step 0 : 6.195420742034912 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 : 0.08991670608520508 #### 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 Mar 20 18:36:56 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/1742492216_557939_917754606_35f3c9ae49686a6be16030c6ec25c9ee.jpg': 917754606} map_photo_id_path_extension : {917754606: {'path': 'temp/1742492216_557939_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 E0320 18:36:57.546870 557939 common.cpp:114] Cannot create Cublas handle. Cublas won't be available. E0320 18:36:57.559324 557939 common.cpp:121] Cannot create Curand generator. Curand won't be available. F0320 18:36:57.581030 557939 syncedmem.hpp:22] Check failed: error == cudaSuccess (2 vs. 0) out of memory *** Check failure stack trace: *** Command terminated by signal 6 30.88user 20.90system 1:31.74elapsed 56%CPU (0avgtext+0avgdata 2574156maxresident)k 4373944inputs+4216outputs (15600major+2441551minor)pagefaults 0swaps