python /home/admin/mtr/script_for_cron.py -j coverage -m 9 -a '' -s coverage -M 0 -S 0 -U 100,100,120 import MySQLdb succeeded root_folder /data_4/data_log/job/2026/February/15022026/coverage/ git_velours : /home/admin/workarea/git/Velours/ out_folder_name htmlcov output_folder /data_4/data_log/job/2026/February/15022026/coverage/htmlcov new path : /data_4/data_log/job/2026/February/15022026/coverage/ command : coverage3 run /home/admin/workarea/git/Velours/python/tests/python_tests.py --short_python3 `cat ~/.fotonower_pass/bdd.py.pass` cat: /home/admin/.fotonower_pass/bdd.py.pass: Aucun fichier ou dossier de ce type 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 python version used : 3 #&_# 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 : 2143 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 : 0.12437319755554199 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 Sun Feb 15 05:20:29 2026 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 : 2143 wait 20 seconds l 3637 free memory gpu now : 2143 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 2026-02-15 05:20:53.684576: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2026-02-15 05:20:53.714658: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493010000 Hz 2026-02-15 05:20:53.716950: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7fb6f8000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2026-02-15 05:20:53.717004: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2026-02-15 05:20:53.721407: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2026-02-15 05:20:53.891355: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0xd40acb0 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2026-02-15 05:20:53.891406: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2026-02-15 05:20:53.892759: 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 2026-02-15 05:20:53.893203: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2026-02-15 05:20:53.896535: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2026-02-15 05:20:53.915758: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2026-02-15 05:20:53.916376: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2026-02-15 05:20:53.947465: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2026-02-15 05:20:53.951961: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2026-02-15 05:20:54.008967: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2026-02-15 05:20:54.010233: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2026-02-15 05:20:54.010684: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2026-02-15 05:20:54.011352: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2026-02-15 05:20:54.011372: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2026-02-15 05:20:54.011384: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2026-02-15 05:20:54.012866: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 1767 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 2026-02-15 05:20:55.050365: 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 2026-02-15 05:20:55.050451: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2026-02-15 05:20:55.050472: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2026-02-15 05:20:55.050491: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2026-02-15 05:20:55.050509: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2026-02-15 05:20:55.050527: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2026-02-15 05:20:55.050544: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2026-02-15 05:20:55.050562: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2026-02-15 05:20:55.051492: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2026-02-15 05:20:55.052466: 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 2026-02-15 05:20:55.052501: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2026-02-15 05:20:55.052520: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2026-02-15 05:20:55.052538: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2026-02-15 05:20:55.052556: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2026-02-15 05:20:55.052573: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2026-02-15 05:20:55.052591: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2026-02-15 05:20:55.052608: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2026-02-15 05:20:55.053523: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2026-02-15 05:20:55.053556: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2026-02-15 05:20:55.053566: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2026-02-15 05:20:55.053576: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2026-02-15 05:20:55.054555: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 1767 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 : [] 2026-02-15 05:21:04.029427: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2026-02-15 05:21:04.224875: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2026-02-15 05:21:06.213926: 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. 2026-02-15 05:21:06.214024: 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. 2026-02-15 05:21:06.220647: 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. 2026-02-15 05:21:06.220676: 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. 2026-02-15 05:21:06.270338: 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. 2026-02-15 05:21:06.270409: 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. 2026-02-15 05:21:06.311928: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.09GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2026-02-15 05:21:06.311953: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.09GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2026-02-15 05:21:06.362829: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.15GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2026-02-15 05:21:06.362857: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.15GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2026-02-15 05:21:06.364520: W tensorflow/core/common_runtime/bfc_allocator.cc:311] Garbage collection: deallocate free memory regions (i.e., allocations) so that we can re-allocate a larger region to avoid OOM due to memory fragmentation. If you see this message frequently, you are running near the threshold of the available device memory and re-allocation may incur great performance overhead. You may try smaller batch sizes to observe the performance impact. Set TF_ENABLE_GPU_GARBAGE_COLLECTION=false if you'd like to disable this feature. 2026-02-15 05:21:06.388115: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.389051: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.10G (1185310464 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.389951: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.398805: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.399599: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.404419: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.404915: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.416599: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.417090: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.418520: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.419008: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.427336: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.428324: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.430573: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.431501: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.437150: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.437705: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.439255: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.439792: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.467179: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.467747: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.468232: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.468715: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.472900: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.473393: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.489761: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.490259: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.490806: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.491353: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.504039: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.504536: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.505023: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.505508: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.509807: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.510325: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.514833: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.515374: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.527276: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.527813: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.531821: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.532310: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.552705: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.553194: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.553869: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.554445: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.554963: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.555446: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.598724: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.598810: 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. 2026-02-15 05:21:06.599789: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.600771: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.607954: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.608674: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.616688: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.617172: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.643729: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.644317: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.644864: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.645360: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.649221: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.649712: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.650197: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.650698: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.651982: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.661553: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.662040: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.672032: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.672517: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.673004: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.673483: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.673969: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:06.674464: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 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 2058549 begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 950 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 : 2143 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'] DEBUG bbox = [22, 0, 282, 186] DEBUG masks shape = (480, 640) time for calcul the mask position with numpy : 0.000621795654296875 nb_pixel_total : 15561 time to create 1 rle with old method : 0.03384828567504883 length of segment : 256 DEBUG bbox = [24, 29, 419, 591] DEBUG masks shape = (480, 640) time for calcul the mask position with numpy : 0.002704620361328125 nb_pixel_total : 145322 time to create 1 rle with old method : 0.30352163314819336 length of segment : 371 DEBUG bbox = [23, 485, 174, 636] DEBUG masks shape = (480, 640) time for calcul the mask position with numpy : 0.0002353191375732422 nb_pixel_total : 14257 time to create 1 rle with old method : 0.030121803283691406 length of segment : 151 DEBUG bbox = [2, 280, 55, 481] DEBUG masks shape = (480, 640) time for calcul the mask position with numpy : 0.00011539459228515625 nb_pixel_total : 5613 time to create 1 rle with old method : 0.012546062469482422 length of segment : 48 DEBUG bbox = [6, 456, 45, 547] DEBUG masks shape = (480, 640) time for calcul the mask position with numpy : 5.9604644775390625e-05 nb_pixel_total : 1825 time to create 1 rle with old method : 0.004235982894897461 length of segment : 39 time spent for convertir_results : 1.3085379600524902 time spend for datou_step_exec : 41.72027921676636 time spend to save output : 6.890296936035156e-05 total time spend for step 1 : 41.72034811973572 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 3424 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 : 0.021184444427490234 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, 0.99552095, [(139, 26, 7), (135, 27, 15), (133, 28, 18), (131, 29, 22), (126, 30, 28), (10, 31, 1), (120, 31, 35), (8, 32, 14), (25, 32, 6), (115, 32, 41), (7, 33, 53), (108, 33, 49), (6, 34, 71), (102, 34, 56), (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)], ['16,276,8,273,2,261,2,229,1,228,1,114,2,113,2,82,1,81,1,46,3,37,8,32,30,32,31,33,59,33,60,34,76,34,77,35,101,35,108,33,114,33,120,31,130,30,135,27,145,26,152,29,158,35,158,48,154,54,141,58,128,61,119,67,105,81,103,86,96,94,89,98,81,109,71,119,65,132,60,138,52,151,45,158,40,166,34,172,29,188,26,193,25,200,25,219,24,270,23,273']), (957285035, 492601069, 445, 29, 591, 24, 419, 0.9923701, [(316, 37, 21), (272, 38, 86), (253, 39, 130), (238, 40, 151), (199, 41, 196), (189, 42, 213), (180, 43, 238), (176, 44, 249), (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), (150, 54, 329), (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), (86, 122, 461), (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), (77, 132, 475), (75, 133, 477), (73, 134, 480), (72, 135, 481), (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), (59, 145, 500), (58, 146, 501), (58, 147, 502), (57, 148, 504), (57, 149, 505), (56, 150, 507), (56, 151, 507), (55, 152, 509), (55, 153, 510), (54, 154, 511), (54, 155, 512), (54, 156, 513), (53, 157, 514), (53, 158, 514), (52, 159, 516), (52, 160, 516), (52, 161, 516), (51, 162, 517), (51, 163, 517), (50, 164, 518), (50, 165, 518), 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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/1771129229_2058237_957285035_a42482e51c93c8025d243dd179aee85b.jpg']} free memory after detection : begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 2143 ############################### 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 : 0.3286397457122803 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 Sun Feb 15 05:21:14 2026 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 : 2143 wait 20 seconds l 3637 free memory gpu now : 2143 max_wait_temp : 1 max_wait : 0 gpu_flag : 0 2026-02-15 05:21:37.802435: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2026-02-15 05:21:37.826516: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493010000 Hz 2026-02-15 05:21:37.828576: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7fb6f8000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2026-02-15 05:21:37.828609: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2026-02-15 05:21:37.832055: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2026-02-15 05:21:37.966592: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0xcb08710 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2026-02-15 05:21:37.966635: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2026-02-15 05:21:37.967502: 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 2026-02-15 05:21:37.967876: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2026-02-15 05:21:37.970751: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2026-02-15 05:21:37.976598: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2026-02-15 05:21:37.977071: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2026-02-15 05:21:37.980108: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2026-02-15 05:21:37.981301: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2026-02-15 05:21:37.986186: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2026-02-15 05:21:37.987315: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2026-02-15 05:21:37.987388: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2026-02-15 05:21:37.987939: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2026-02-15 05:21:37.987953: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2026-02-15 05:21:37.987960: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2026-02-15 05:21:37.988771: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 1767 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. 2026-02-15 05:21:38.094060: 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 2026-02-15 05:21:38.094159: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2026-02-15 05:21:38.094187: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2026-02-15 05:21:38.094211: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2026-02-15 05:21:38.094249: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2026-02-15 05:21:38.094310: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2026-02-15 05:21:38.094338: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2026-02-15 05:21:38.094362: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2026-02-15 05:21:38.095302: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2026-02-15 05:21:38.096416: 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 2026-02-15 05:21:38.096454: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2026-02-15 05:21:38.096476: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2026-02-15 05:21:38.096497: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2026-02-15 05:21:38.096517: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2026-02-15 05:21:38.096537: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2026-02-15 05:21:38.096558: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2026-02-15 05:21:38.096578: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2026-02-15 05:21:38.097500: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2026-02-15 05:21:38.097535: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2026-02-15 05:21:38.097545: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2026-02-15 05:21:38.097555: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2026-02-15 05:21:38.098565: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 1767 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 : [] 2026-02-15 05:21:46.061315: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2026-02-15 05:21:46.228439: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2026-02-15 05:21:47.494439: 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. 2026-02-15 05:21:47.494502: 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. 2026-02-15 05:21:47.500973: 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. 2026-02-15 05:21:47.500995: 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. 2026-02-15 05:21:47.551019: 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. 2026-02-15 05:21:47.551093: 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. 2026-02-15 05:21:47.593093: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.09GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2026-02-15 05:21:47.593119: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.09GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2026-02-15 05:21:47.644875: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.15GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2026-02-15 05:21:47.644928: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.15GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2026-02-15 05:21:47.646649: W tensorflow/core/common_runtime/bfc_allocator.cc:311] Garbage collection: deallocate free memory regions (i.e., allocations) so that we can re-allocate a larger region to avoid OOM due to memory fragmentation. If you see this message frequently, you are running near the threshold of the available device memory and re-allocation may incur great performance overhead. You may try smaller batch sizes to observe the performance impact. Set TF_ENABLE_GPU_GARBAGE_COLLECTION=false if you'd like to disable this feature. 2026-02-15 05:21:47.663832: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.664794: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.10G (1185310464 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.665724: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.674177: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.674889: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.680250: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.681174: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.694072: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.694626: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.696286: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.696818: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.703223: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.703757: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.705596: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.706128: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.712654: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.713158: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.714768: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.715253: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.746063: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.746585: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.747077: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.747565: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.751471: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.751961: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.768220: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.768713: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.769198: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.769681: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.781872: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.782378: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.782872: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.783361: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.787451: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.787942: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.792320: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.792812: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.804479: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.804968: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.808937: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.809429: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.830166: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.830677: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.831182: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.831669: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.832155: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.832641: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.864825: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.864905: 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. 2026-02-15 05:21:47.865898: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.866873: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.874403: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.875144: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.883599: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.884094: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.899250: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.899978: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.900478: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.900978: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.904947: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.905440: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.905939: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.906448: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.907438: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.917818: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.918521: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.928839: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.929350: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.929846: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.930355: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.930895: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:21:47.931425: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 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 2059029 begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 950 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 : 2143 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'] DEBUG bbox = [0, 1092, 108, 1280] DEBUG masks shape = (720, 1280) time for calcul the mask position with numpy : 0.000667572021484375 nb_pixel_total : 16903 time to create 1 rle with old method : 0.04135704040527344 length of segment : 107 DEBUG bbox = [0, 50, 672, 1144] DEBUG masks shape = (720, 1280) time for calcul the mask position with numpy : 0.017290830612182617 nb_pixel_total : 483335 time to create 1 rle with new method : 0.03339672088623047 length of segment : 633 DEBUG bbox = [0, 0, 116, 438] DEBUG masks shape = (720, 1280) time for calcul the mask position with numpy : 0.0004851818084716797 nb_pixel_total : 36580 time to create 1 rle with old method : 0.07842278480529785 length of segment : 132 DEBUG bbox = [0, 390, 54, 550] DEBUG masks shape = (720, 1280) time for calcul the mask position with numpy : 9.989738464355469e-05 nb_pixel_total : 4793 time to create 1 rle with old method : 0.01070094108581543 length of segment : 51 time spent for convertir_results : 0.44277501106262207 time spend for datou_step_exec : 36.836552143096924 time spend to save output : 4.00543212890625e-05 total time spend for step 1 : 36.83659219741821 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 447 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 : 0.016302108764648438 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, 0.9988362, [(1205, 1, 58), (1164, 2, 106), (1159, 3, 113), (1149, 4, 124), (1113, 5, 161), (1100, 6, 174), (1097, 7, 177), (1095, 8, 179), (1095, 9, 179), (1095, 10, 179), (1095, 11, 179), (1095, 12, 179), (1095, 13, 179), (1095, 14, 178), (1095, 15, 178), (1095, 16, 178), (1095, 17, 178), (1095, 18, 177), (1095, 19, 177), (1095, 20, 177), (1095, 21, 177), (1095, 22, 177), (1095, 23, 178), (1095, 24, 178), (1095, 25, 178), (1095, 26, 179), (1095, 27, 179), (1095, 28, 180), (1095, 29, 181), (1095, 30, 182), (1095, 31, 183), (1095, 32, 183), (1095, 33, 184), (1095, 34, 184), (1096, 35, 183), (1096, 36, 183), (1096, 37, 184), (1097, 38, 183), (1097, 39, 183), (1097, 40, 183), (1098, 41, 182), (1098, 42, 182), (1098, 43, 182), (1099, 44, 181), (1099, 45, 181), (1099, 46, 181), (1100, 47, 180), (1100, 48, 180), (1101, 49, 179), (1101, 50, 179), (1102, 51, 178), (1102, 52, 178), (1103, 53, 177), (1103, 54, 177), (1104, 55, 176), (1104, 56, 176), (1104, 57, 176), (1104, 58, 176), (1105, 59, 175), (1105, 60, 175), (1105, 61, 175), (1105, 62, 175), (1105, 63, 175), (1106, 64, 174), (1106, 65, 174), (1106, 66, 174), (1106, 67, 174), (1106, 68, 174), (1106, 69, 174), (1106, 70, 174), (1106, 71, 174), (1106, 72, 174), (1106, 73, 174), (1107, 74, 173), (1107, 75, 173), (1107, 76, 173), (1107, 77, 173), (1107, 78, 173), (1107, 79, 173), (1108, 80, 172), (1108, 81, 172), (1109, 82, 171), (1110, 83, 170), (1110, 84, 170), (1111, 85, 169), (1112, 86, 168), (1113, 87, 166), (1114, 88, 165), (1115, 89, 164), (1117, 90, 162), (1120, 91, 159), (1138, 92, 141), (1146, 93, 133), (1154, 94, 125), (1167, 95, 112), (1177, 96, 102), (1183, 97, 95), (1185, 98, 93), (1187, 99, 90), (1188, 100, 55), (1264, 100, 12), (1190, 101, 50), (1191, 102, 46), (1194, 103, 40), (1197, 104, 34), (1202, 105, 25), (1207, 106, 16)], ['1222,106,1207,106,1206,105,1197,104,1191,102,1182,96,1176,95,1167,95,1166,94,1154,94,1153,93,1146,93,1145,92,1137,91,1120,91,1115,89,1110,84,1107,79,1106,73,1106,64,1104,55,1099,46,1095,34,1095,8,1100,6,1112,6,1113,5,1148,5,1149,4,1158,4,1164,2,1204,2,1205,1,1262,1,1269,2,1273,5,1273,13,1271,18,1271,22,1273,27,1277,31,1279,37,1279,86,1278,87,1278,96,1275,100,1264,100,1263,99,1243,99,1230,104']), (917855882, 492601069, 445, 50, 1144, 0, 672, 0.99749446, [(962, 20, 10), (612, 21, 63), (912, 21, 100), (581, 22, 226), (861, 22, 166), (564, 23, 479), (549, 24, 500), (537, 25, 515), (533, 26, 522), 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(379, 635, 310), (383, 636, 302), (387, 637, 295), (391, 638, 287), (395, 639, 279), (400, 640, 270), (406, 641, 259), (411, 642, 249), (418, 643, 236), (430, 644, 219), (448, 645, 195), (466, 646, 170), (482, 647, 148), (499, 648, 125), (520, 649, 97), (548, 650, 35)], ['520,649,418,643,344,627,303,610,261,598,225,578,184,564,121,523,95,501,88,490,71,443,64,360,73,314,94,227,120,202,141,177,211,152,301,137,344,121,382,112,439,87,488,46,516,31,537,25,612,21,675,22,806,22,1011,21,1042,23,1070,34,1092,56,1098,100,1097,163,1088,205,1069,251,1064,279,1054,297,961,364,923,393,894,423,871,442,858,466,838,485,821,516,802,535,783,574,744,613,734,619,669,640,616,649']), (917855882, 492601069, 445, 0, 438, 0, 116, 0.9919442, [(127, 1, 140), (94, 2, 205), (59, 3, 273), (338, 3, 59), (22, 4, 380), (19, 5, 386), (16, 6, 391), (15, 7, 393), (14, 8, 395), (14, 9, 396), (13, 10, 398), (12, 11, 399), (12, 12, 399), (11, 13, 401), (10, 14, 402), (11, 15, 402), (11, 16, 403), (12, 17, 403), (12, 18, 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['344,105,330,102,319,101,307,95,300,93,293,86,284,84,261,85,244,90,204,90,203,89,175,89,160,88,140,85,125,86,83,86,56,92,36,101,25,103,8,101,6,93,11,80,11,59,12,58,12,17,10,14,16,6,22,4,58,4,59,3,93,3,94,2,126,2,127,1,266,1,267,2,298,2,299,3,396,3,406,6,416,19,420,34,420,51,411,60,405,68,402,81,404,85,401,92,386,102,365,105']), (917855882, 492601069, 445, 390, 550, 0, 54, 0.93906075, [(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), (420, 25, 99), (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)], ['449,46,443,46,442,45,426,45,424,41,424,37,423,36,422,31,420,28,420,25,419,24,419,21,418,20,418,17,417,15,409,6,402,3,402,1,413,1,414,0,420,0,421,1,440,1,441,0,500,0,501,1,507,1,508,0,535,0,536,1,543,1,546,2,546,4,542,8,530,18,527,19,525,21,522,22,520,24,512,28,508,33,505,34,502,37,494,41,492,41,490,43,488,43,484,45,473,45,472,46'])], 'temp/1771129274_2058237_917855882_da0fa7b7e6b5b551fe26c0ba8713276d.jpg']} error in position expected : (917855882, 492601069, 445, 52, 1128, 16, 668, 0.9977477) got : (917855882, 492601069, 445, 50, 1144, 0, 672, 0.99749446) 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 : 0.20397591590881348 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 Sun Feb 15 05:21:53 2026 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 : 2143 wait 20 seconds l 3637 free memory gpu now : 2143 max_wait_temp : 1 max_wait : 0 gpu_flag : 0 2026-02-15 05:22:16.809045: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2026-02-15 05:22:16.834664: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493010000 Hz 2026-02-15 05:22:16.836983: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7fb6f8000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2026-02-15 05:22:16.837048: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2026-02-15 05:22:16.840809: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2026-02-15 05:22:16.968686: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0xa5f0d80 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2026-02-15 05:22:16.968737: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2026-02-15 05:22:16.969459: 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 2026-02-15 05:22:16.969780: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2026-02-15 05:22:16.971904: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2026-02-15 05:22:16.973960: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2026-02-15 05:22:16.974258: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2026-02-15 05:22:16.976561: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2026-02-15 05:22:16.977532: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2026-02-15 05:22:16.981747: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2026-02-15 05:22:16.982756: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2026-02-15 05:22:16.982835: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2026-02-15 05:22:16.983356: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2026-02-15 05:22:16.983371: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2026-02-15 05:22:16.983380: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2026-02-15 05:22:16.984186: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 1767 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. 2026-02-15 05:22:17.091297: 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 2026-02-15 05:22:17.091451: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2026-02-15 05:22:17.091472: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2026-02-15 05:22:17.091491: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2026-02-15 05:22:17.091508: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2026-02-15 05:22:17.091526: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2026-02-15 05:22:17.091543: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2026-02-15 05:22:17.091562: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2026-02-15 05:22:17.092258: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2026-02-15 05:22:17.093131: 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 2026-02-15 05:22:17.093162: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2026-02-15 05:22:17.093178: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2026-02-15 05:22:17.093193: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2026-02-15 05:22:17.093207: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2026-02-15 05:22:17.093222: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2026-02-15 05:22:17.093236: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2026-02-15 05:22:17.093251: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2026-02-15 05:22:17.093928: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2026-02-15 05:22:17.093960: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2026-02-15 05:22:17.093968: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2026-02-15 05:22:17.093975: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2026-02-15 05:22:17.094774: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 1767 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 : [] 2026-02-15 05:22:26.300734: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2026-02-15 05:22:26.471255: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2026-02-15 05:22:27.631891: 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. 2026-02-15 05:22:27.631956: 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. 2026-02-15 05:22:27.638392: 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. 2026-02-15 05:22:27.638417: 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. 2026-02-15 05:22:27.689901: 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. 2026-02-15 05:22:27.689948: 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. 2026-02-15 05:22:27.729802: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.09GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2026-02-15 05:22:27.729841: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.09GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2026-02-15 05:22:27.776335: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.15GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2026-02-15 05:22:27.776372: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.15GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2026-02-15 05:22:27.777855: W tensorflow/core/common_runtime/bfc_allocator.cc:311] Garbage collection: deallocate free memory regions (i.e., allocations) so that we can re-allocate a larger region to avoid OOM due to memory fragmentation. If you see this message frequently, you are running near the threshold of the available device memory and re-allocation may incur great performance overhead. You may try smaller batch sizes to observe the performance impact. Set TF_ENABLE_GPU_GARBAGE_COLLECTION=false if you'd like to disable this feature. 2026-02-15 05:22:27.795334: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.796259: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.10G (1185310464 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.797154: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.805206: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.806099: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.810487: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.810971: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.822095: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.822617: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.824159: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.824649: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.830442: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.830980: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.832645: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.833148: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.839140: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.839674: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.841189: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.841676: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.869828: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.870332: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.870818: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.871301: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.874902: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.875390: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.891980: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.892471: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.892953: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.893432: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.907117: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.907603: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.908084: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.908563: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.913023: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.913509: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.918161: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.918857: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.931364: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.931854: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.935920: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.936411: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.957415: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.957905: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.958412: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.958900: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.959385: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.959871: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.991584: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.991627: 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. 2026-02-15 05:22:27.992134: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:27.992632: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:28.000417: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:28.000908: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:28.008797: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:28.009286: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:28.024360: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:28.025342: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:28.026427: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:28.027325: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:28.031280: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:28.031764: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:28.032242: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:28.032718: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:28.033579: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:28.043716: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:28.044200: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:28.054627: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:28.055201: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:28.055753: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:28.056292: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:28.056824: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-15 05:22:28.057342: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.23G (1317011456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory local folder : /data/models_weight/mask_coco_origin /data/models_weight/mask_coco_origin/mask_model.h5 size_local : 257557808 size in s3 : 257557808 create time local : 2021-08-09 05:27:17 create time in s3 : 2021-08-06 19:45:17 mask_model.h5 already exist and didn't need to update list_images length : 1 NEW PHOTO Processing 1 images image shape: (2448, 2448, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 89) min: 0.00000 max: 2448.00000 nb d'objets trouves : 1 Detection mask done ! Trying to reset tf kernel 2059568 begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 950 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 : 2143 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'] DEBUG bbox = [103, 11, 2256, 2268] DEBUG masks shape = (2448, 2448) time for calcul the mask position with numpy : 0.2843332290649414 nb_pixel_total : 3697586 time to create 1 rle with new method : 0.3696432113647461 length of segment : 2054 time spent for convertir_results : 1.9088423252105713 time spend for datou_step_exec : 39.89156651496887 time spend to save output : 5.888938903808594e-05 total time spend for step 1 : 39.89162540435791 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 726 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 : 0.01807570457458496 save missing photos in datou_result : After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : {'917877156': [[(917877156, 492601069, 445, 11, 2268, 103, 2256, 0.9864405, [(1254, 110, 15), (660, 111, 235), (1208, 111, 123), (606, 112, 371), (1108, 112, 315), (529, 113, 901), (522, 114, 915), (514, 115, 929), (507, 116, 943), (501, 117, 955), (494, 118, 967), (488, 119, 979), (482, 120, 990), (476, 121, 1001), (470, 122, 1012), (465, 123, 1022), (459, 124, 1033), (454, 125, 1042), (449, 126, 1051), (444, 127, 1064), (440, 128, 1077), (435, 129, 1091), (430, 130, 1105), (426, 131, 1118), (422, 132, 1130), (418, 133, 1142), (414, 134, 1154), (410, 135, 1165), (406, 136, 1177), (402, 137, 1184), (399, 138, 1191), (395, 139, 1198), (392, 140, 1204), (389, 141, 1210), (386, 142, 1217), (382, 143, 1224), (379, 144, 1230), (376, 145, 1236), (373, 146, 1243), (371, 147, 1248), (369, 148, 1254), (367, 149, 1260), (365, 150, 1266), (363, 151, 1272), (361, 152, 1278), (359, 153, 1284), (356, 154, 1291), (354, 155, 1298), (352, 156, 1304), (349, 157, 1312), (347, 158, 1319), (344, 159, 1327), (342, 160, 1334), (339, 161, 1342), (337, 162, 1350), (334, 163, 1358), (331, 164, 1367), (328, 165, 1376), (325, 166, 1385), (322, 167, 1395), (319, 168, 1404), (316, 169, 1414), (312, 170, 1426), (309, 171, 1436), (305, 172, 1448), (302, 173, 1459), (298, 174, 1472), (294, 175, 1484), (290, 176, 1497), (287, 177, 1509), (283, 178, 1522), (280, 179, 1534), (277, 180, 1547), (273, 181, 1556), (270, 182, 1564), (267, 183, 1572), (264, 184, 1580), (261, 185, 1587), (258, 186, 1594), (255, 187, 1601), (252, 188, 1609), (249, 189, 1615), (246, 190, 1622), (244, 191, 1628), (241, 192, 1635), (238, 193, 1641), (236, 194, 1646), (233, 195, 1653), (231, 196, 1658), (228, 197, 1664), (226, 198, 1669), (224, 199, 1674), (221, 200, 1680), (219, 201, 1685), (217, 202, 1689), (215, 203, 1692), (213, 204, 1696), (211, 205, 1699), (210, 206, 1701), (208, 207, 1705), (207, 208, 1707), (205, 209, 1710), (204, 210, 1712), (203, 211, 1714), (201, 212, 1717), (200, 213, 1719), (199, 214, 1722), (198, 215, 1724), (197, 216, 1726), (195, 217, 1729), (194, 218, 1730), (193, 219, 1732), (192, 220, 1734), (191, 221, 1736), (190, 222, 1738), (189, 223, 1740), (188, 224, 1742), (187, 225, 1743), (186, 226, 1745), (185, 227, 1747), (184, 228, 1749), (182, 229, 1752), (181, 230, 1754), (180, 231, 1756), (179, 232, 1758), (178, 233, 1760), (176, 234, 1763), (175, 235, 1765), (174, 236, 1768), (172, 237, 1771), (171, 238, 1773), (170, 239, 1775), (168, 240, 1778), (167, 241, 1780), (165, 242, 1783), (164, 243, 1786), (163, 244, 1788), (161, 245, 1791), (159, 246, 1795), (158, 247, 1797), (156, 248, 1800), (155, 249, 1803), (153, 250, 1806), (151, 251, 1810), (150, 252, 1812), (148, 253, 1816), (146, 254, 1819), (144, 255, 1823), (143, 256, 1825), (141, 257, 1829), (139, 258, 1833), (137, 259, 1836), (135, 260, 1840), (133, 261, 1844), (131, 262, 1848), (130, 263, 1851), (128, 264, 1855), (127, 265, 1858), (126, 266, 1861), (124, 267, 1864), (123, 268, 1867), (122, 269, 1869), (121, 270, 1871), (120, 271, 1874), (119, 272, 1876), (118, 273, 1878), (117, 274, 1880), (116, 275, 1883), (115, 276, 1885), (114, 277, 1887), (113, 278, 1889), (112, 279, 1891), (111, 280, 1893), (110, 281, 1895), (110, 282, 1896), (109, 283, 1898), (108, 284, 1900), (107, 285, 1902), (107, 286, 1903), (106, 287, 1904), (105, 288, 1906), (104, 289, 1908), (104, 290, 1909), (103, 291, 1911), (102, 292, 1912), (102, 293, 1913), (101, 294, 1915), (101, 295, 1915), (100, 296, 1917), (100, 297, 1917), (100, 298, 1918), (99, 299, 1919), (99, 300, 1920), (99, 301, 1920), (98, 302, 1922), (98, 303, 1922), (98, 304, 1923), (98, 305, 1923), (97, 306, 1925), (97, 307, 1925), (97, 308, 1926), (96, 309, 1927), (96, 310, 1928), (96, 311, 1928), (95, 312, 1930), (95, 313, 1930), (95, 314, 1931), (94, 315, 1932), (94, 316, 1933), (94, 317, 1934), (93, 318, 1935), (93, 319, 1936), (93, 320, 1936), (92, 321, 1938), (92, 322, 1938), (92, 323, 1939), (91, 324, 1941), (91, 325, 1941), (91, 326, 1942), (91, 327, 1942), (90, 328, 1944), (90, 329, 1945), (90, 330, 1945), (89, 331, 1947), (89, 332, 1948), (89, 333, 1948), (88, 334, 1950), (88, 335, 1950), (88, 336, 1951), (87, 337, 1953), (87, 338, 1953), (87, 339, 1954), (86, 340, 1956), (86, 341, 1957), (86, 342, 1957), (85, 343, 1959), (85, 344, 1960), (85, 345, 1960), (84, 346, 1962), (84, 347, 1963), (84, 348, 1964), (83, 349, 1965), (83, 350, 1966), (83, 351, 1967), (82, 352, 1969), (82, 353, 1969), (82, 354, 1970), (81, 355, 1972), (81, 356, 1973), (80, 357, 1975), (80, 358, 1975), (80, 359, 1976), (79, 360, 1978), (79, 361, 1979), (79, 362, 1980), (78, 363, 1982), (78, 364, 1983), (78, 365, 1984), (77, 366, 1985), (77, 367, 1986), (77, 368, 1987), (76, 369, 1989), (76, 370, 1990), (76, 371, 1991), (75, 372, 1993), (75, 373, 1994), (75, 374, 1995), (74, 375, 1997), (74, 376, 1997), (74, 377, 1998), (73, 378, 2000), (73, 379, 2001), (73, 380, 2002), (72, 381, 2004), (72, 382, 2004), (71, 383, 2006), (71, 384, 2007), (71, 385, 2008), (70, 386, 2009), (70, 387, 2010), (70, 388, 2011), (69, 389, 2012), (69, 390, 2013), (68, 391, 2015), (68, 392, 2015), (68, 393, 2016), (67, 394, 2018), (67, 395, 2018), (66, 396, 2020), (66, 397, 2021), (66, 398, 2021), (65, 399, 2023), (65, 400, 2024), (64, 401, 2025), (64, 402, 2026), (63, 403, 2027), (63, 404, 2028), (62, 405, 2029), (62, 406, 2030), (62, 407, 2031), (61, 408, 2032), (61, 409, 2033), (60, 410, 2034), (60, 411, 2035), (59, 412, 2036), (59, 413, 2037), (58, 414, 2038), (58, 415, 2039), (57, 416, 2040), (57, 417, 2041), (56, 418, 2042), (55, 419, 2044), (55, 420, 2044), (54, 421, 2046), (54, 422, 2046), (53, 423, 2048), (53, 424, 2048), (52, 425, 2049), (51, 426, 2051), (51, 427, 2051), 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['1011,2151,942,2142,697,2073,618,2039,371,1984,231,1965,132,1973,55,1832,53,1755,39,1683,39,1468,30,1302,30,902,23,646,40,448,110,281,211,205,444,127,529,113,660,111,1422,112,1582,136,1723,169,1823,180,1903,201,1998,275,2088,400,2143,525,2167,604,2172,672,2165,833,2129,910,2114,987,2084,1064,2031,1133,2015,1178,1958,1274,1930,1370,1878,1447,1845,1677,1789,1847,1763,1905,1706,1984,1663,2016,1582,2017,1497,2036,1418,2041,1260,2085,1174,2102,1099,2138'])], 'temp/1771129313_2058237_917877156_a9c2d4b99270c9302def4ed40606e685.jpg']} nb pixel non reg : 3692295 nb pixel common : 3683673 proportion of common points : 0.9976648669729802 #&_# TEST FAILED #&_# : tests/mask_test #&_# #&_# 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 : 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 : sam 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 : 0.22945475578308105 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 : False number of steps : 1 step1:sam Sun Feb 15 05:22:40 2026 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 sam ! Inside sam : nb paths : 1 (640, 960, 3) ERROR in datou_step_exec, will save and exit ! CUDA out of memory. Tried to allocate 768.00 MiB (GPU 0; 10.76 GiB total capacity; 443.59 MiB already allocated; 660.00 MiB free; 498.00 MiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF File "/home/admin/workarea/git/Velours/python/mtr/datou/datou_lib.py", line 2339, 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 2440, in datou_step_exec return lib_process.datou_step_sam(param, json_param, args, cache, context, map_info, verbose) File "/home/admin/workarea/git/Velours/python/mtr/datou/lib_step_exec/lib_step_process.py", line 396, in datou_step_sam masks = mask_generator.generate(image) File "/home/admin/.local/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context return func(*args, **kwargs) File "/home/admin/workarea/install/segment-anything/segment_anything/automatic_mask_generator.py", line 163, in generate mask_data = self._generate_masks(image) File "/home/admin/workarea/install/segment-anything/segment_anything/automatic_mask_generator.py", line 206, in _generate_masks crop_data = self._process_crop(image, crop_box, layer_idx, orig_size) File "/home/admin/workarea/install/segment-anything/segment_anything/automatic_mask_generator.py", line 236, in _process_crop self.predictor.set_image(cropped_im) File "/home/admin/workarea/install/segment-anything/segment_anything/predictor.py", line 60, in set_image self.set_torch_image(input_image_torch, image.shape[:2]) File "/home/admin/.local/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context return func(*args, **kwargs) File "/home/admin/workarea/install/segment-anything/segment_anything/predictor.py", line 89, in set_torch_image self.features = self.model.image_encoder(input_image) File "/home/admin/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl return forward_call(*input, **kwargs) File "/home/admin/workarea/install/segment-anything/segment_anything/modeling/image_encoder.py", line 112, in forward x = blk(x) File "/home/admin/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl return forward_call(*input, **kwargs) File "/home/admin/workarea/install/segment-anything/segment_anything/modeling/image_encoder.py", line 174, in forward x = self.attn(x) File "/home/admin/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl return forward_call(*input, **kwargs) File "/home/admin/workarea/install/segment-anything/segment_anything/modeling/image_encoder.py", line 231, in forward attn = (q * self.scale) @ k.transpose(-2, -1) [1189321094] begin to insert list_values into mtr_datou_result : length of list_values in save_final : 1 time used for this insertion : 0.020833253860473633 save_final ERROR in last step sam, CUDA out of memory. Tried to allocate 768.00 MiB (GPU 0; 10.76 GiB total capacity; 443.59 MiB already allocated; 660.00 MiB free; 498.00 MiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF time spend for datou_step_exec : 9.929118871688843 time spend to save output : 0.02404046058654785 total time spend for step 0 : 9.95315933227539 need to delete datou_research and reload, so keep current state 1 need to delete datou_research and reload, so keep current state 1 need to delete datou_research and reload, so keep current state 1 caffe_path_current : About to save ! 2 After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : None ERROR nb objects espect : 98 nb_objects detect : 0 ERROR sam FAILED ############################### TEST frcnn ################################ 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 : frcnn 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 : 0.16946911811828613 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:frcnn Sun Feb 15 05:22:50 2026 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 Faster rcnn ! 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 : [] [libprotobuf ERROR google/protobuf/text_format.cc:307] Error parsing text-format caffe.NetParameter: 325:21: Message type "caffe.LayerParameter" has no field named "roi_pooling_param". WARNING: Logging before InitGoogleLogging() is written to STDERR F0215 05:22:52.141729 2058237 upgrade_proto.cpp:90] Check failed: ReadProtoFromTextFile(param_file, param) Failed to parse NetParameter file: /data/models_weight/detection_plaque_valcor_010622/test.prototxt *** Check failure stack trace: *** Aborted (core dumped) No data to report. No data to report. ret : 34304 command : coverage3 html -i --omit=/usr/local/lib/python3.8/dist-packages/*,/home/admin/.local/lib/python3.8/site-packages/*,/usr/lib/python3/dist-packages/* -d htmlcov ret : 256 command : coverage3 report -i -m ret : 256 39.40user 22.79system 2:26.71elapsed 42%CPU (0avgtext+0avgdata 2963904maxresident)k 3858960inputs+4800outputs (12472major+3060008minor)pagefaults 0swaps