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/12022026/coverage/ git_velours : /home/admin/workarea/git/Velours/ out_folder_name htmlcov output_folder /data_4/data_log/job/2026/February/12022026/coverage/htmlcov new path : /data_4/data_log/job/2026/February/12022026/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 : 2161 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 : 0.13855600357055664 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : False number of steps : 1 step1:mask_detect Thu Feb 12 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 : 2161 wait 20 seconds l 3637 free memory gpu now : 2161 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 2026-02-12 05:20:54.130962: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2026-02-12 05:20:54.162424: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493010000 Hz 2026-02-12 05:20:54.165021: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7fb164000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2026-02-12 05:20:54.165081: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2026-02-12 05:20:54.170657: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2026-02-12 05:20:54.343652: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x6bcdfe0 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2026-02-12 05:20:54.343716: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2026-02-12 05:20:54.345160: 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 2026-02-12 05:20:54.345677: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2026-02-12 05:20:54.348965: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2026-02-12 05:20:54.368227: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2026-02-12 05:20:54.368902: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2026-02-12 05:20:54.404240: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2026-02-12 05:20:54.410522: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2026-02-12 05:20:54.475186: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2026-02-12 05:20:54.476869: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2026-02-12 05:20:54.477457: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2026-02-12 05:20:54.478366: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2026-02-12 05:20:54.478398: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2026-02-12 05:20:54.478416: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2026-02-12 05:20:54.480400: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 1785 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 2026-02-12 05:20:55.779563: 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 2026-02-12 05:20:55.779696: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2026-02-12 05:20:55.779720: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2026-02-12 05:20:55.779746: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2026-02-12 05:20:55.779769: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2026-02-12 05:20:55.779791: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2026-02-12 05:20:55.779815: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2026-02-12 05:20:55.779839: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2026-02-12 05:20:55.780816: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2026-02-12 05:20:55.782139: 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 2026-02-12 05:20:55.782181: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2026-02-12 05:20:55.782204: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2026-02-12 05:20:55.782226: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2026-02-12 05:20:55.782247: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2026-02-12 05:20:55.782268: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2026-02-12 05:20:55.782302: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2026-02-12 05:20:55.782324: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2026-02-12 05:20:55.783272: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2026-02-12 05:20:55.783323: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2026-02-12 05:20:55.783335: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2026-02-12 05:20:55.783346: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2026-02-12 05:20:55.784373: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 1785 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 : [] 2026-02-12 05:21:05.558832: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2026-02-12 05:21:05.750725: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2026-02-12 05:21:07.468752: 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. 2026-02-12 05:21:07.468827: 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. 2026-02-12 05:21:07.475225: 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. 2026-02-12 05:21:07.475249: 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. 2026-02-12 05:21:07.523502: 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. 2026-02-12 05:21:07.523551: 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. 2026-02-12 05:21:07.564012: 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. 2026-02-12 05:21:07.564043: 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. 2026-02-12 05:21:07.612334: 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. 2026-02-12 05:21:07.612360: 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. 2026-02-12 05:21:07.613897: 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. 2026-02-12 05:21:07.631234: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.632146: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.12G (1202356224 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.633070: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.641511: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.642468: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.647035: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.647531: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.659134: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.659690: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.661242: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.661742: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.669344: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.669846: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.671582: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.672086: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.678294: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.678813: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.680416: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.680913: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.710752: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.711314: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.711818: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.712315: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.716577: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.717080: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.735920: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.736474: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.736969: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.737472: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.751511: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.752014: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.752511: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.753007: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.757361: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.757871: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.762338: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.762897: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.774775: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.775335: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.779419: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.779977: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.800497: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.801016: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.801583: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.802133: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.802691: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.803242: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.846817: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.846899: 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. 2026-02-12 05:21:07.847915: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.848956: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.856073: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.856589: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.864485: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.865024: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.885724: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.886448: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.887154: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.887832: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.891983: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.892670: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.893348: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.894023: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.895584: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.905016: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.905551: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.915620: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.916126: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.916631: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.917127: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.917636: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:07.918186: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 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 3052664 begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 968 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 : 2161 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 : 0.0005109310150146484 nb_pixel_total : 15553 time to create 1 rle with old method : 0.032756805419921875 length of segment : 256 DEBUG bbox = [24, 29, 419, 591] DEBUG masks shape = (480, 640) time for calcul the mask position with numpy : 0.0024666786193847656 nb_pixel_total : 145332 time to create 1 rle with old method : 0.2931966781616211 length of segment : 371 DEBUG bbox = [23, 485, 174, 636] DEBUG masks shape = (480, 640) time for calcul the mask position with numpy : 0.00022673606872558594 nb_pixel_total : 14255 time to create 1 rle with old method : 0.02929830551147461 length of segment : 151 DEBUG bbox = [2, 280, 55, 481] DEBUG masks shape = (480, 640) time for calcul the mask position with numpy : 0.0001246929168701172 nb_pixel_total : 5614 time to create 1 rle with old method : 0.012414216995239258 length of segment : 48 DEBUG bbox = [6, 456, 45, 547] DEBUG masks shape = (480, 640) time for calcul the mask position with numpy : 6.723403930664062e-05 nb_pixel_total : 1825 time to create 1 rle with old method : 0.004098653793334961 length of segment : 39 time spent for convertir_results : 1.2946422100067139 time spend for datou_step_exec : 42.72919964790344 time spend to save output : 4.315376281738281e-05 total time spend for step 1 : 42.72924280166626 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 : 0.02051091194152832 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, 0.9954921, [(140, 26, 6), (135, 27, 15), (133, 28, 18), (131, 29, 22), (126, 30, 28), (10, 31, 1), (120, 31, 35), (8, 32, 13), (27, 32, 3), (115, 32, 41), (7, 33, 52), (109, 33, 48), (6, 34, 70), (103, 34, 55), (5, 35, 154), (4, 36, 155), (3, 37, 156), (3, 38, 156), (3, 39, 156), (2, 40, 157), (2, 41, 157), (2, 42, 157), (2, 43, 157), (2, 44, 157), (2, 45, 157), (1, 46, 158), (1, 47, 158), (1, 48, 158), (1, 49, 157), (1, 50, 157), (1, 51, 156), (1, 52, 156), (1, 53, 155), (1, 54, 154), (1, 55, 152), (1, 56, 149), (1, 57, 145), (1, 58, 141), (1, 59, 137), (1, 60, 133), (1, 61, 130), (1, 62, 127), (1, 63, 126), (1, 64, 124), (1, 65, 123), (1, 66, 121), (1, 67, 120), (1, 68, 118), (1, 69, 117), (1, 70, 116), (1, 71, 115), (1, 72, 114), (1, 73, 113), (1, 74, 112), (1, 75, 111), (1, 76, 110), (1, 77, 108), (1, 78, 108), (1, 79, 107), (1, 80, 106), (1, 81, 105), (2, 82, 104), (2, 83, 103), (2, 84, 103), (2, 85, 102), (2, 86, 102), (2, 87, 101), (2, 88, 100), (2, 89, 99), (2, 90, 99), (2, 91, 98), (2, 92, 97), (2, 93, 96), (2, 94, 95), (2, 95, 93), (2, 96, 91), (2, 97, 90), (2, 98, 89), (2, 99, 87), (2, 100, 86), (2, 101, 86), (2, 102, 85), (2, 103, 84), (2, 104, 83), (2, 105, 83), (2, 106, 82), (2, 107, 81), (2, 108, 80), (2, 109, 80), (2, 110, 79), (2, 111, 78), (2, 112, 77), (2, 113, 76), (1, 114, 76), (1, 115, 75), (1, 116, 74), (1, 117, 73), (1, 118, 72), (1, 119, 71), (1, 120, 71), (1, 121, 70), (1, 122, 69), (1, 123, 69), (1, 124, 68), (1, 125, 68), (1, 126, 67), (1, 127, 67), (1, 128, 66), (1, 129, 66), (1, 130, 66), (1, 131, 65), (1, 132, 65), (1, 133, 64), (1, 134, 63), (1, 135, 63), (1, 136, 62), (1, 137, 61), (1, 138, 60), (1, 139, 60), (1, 140, 59), (1, 141, 58), (1, 142, 58), (1, 143, 57), (1, 144, 56), (1, 145, 56), (1, 146, 55), (1, 147, 54), (1, 148, 54), (1, 149, 53), (1, 150, 52), (1, 151, 52), (1, 152, 51), (1, 153, 50), (1, 154, 49), (1, 155, 48), (1, 156, 47), (1, 157, 46), (1, 158, 45), (1, 159, 45), (1, 160, 44), (1, 161, 43), (1, 162, 42), (1, 163, 41), (1, 164, 41), (1, 165, 40), (1, 166, 40), (1, 167, 39), (1, 168, 38), (1, 169, 37), (1, 170, 36), (1, 171, 35), (1, 172, 34), (1, 173, 34), (1, 174, 33), (1, 175, 33), (1, 176, 32), (1, 177, 32), (1, 178, 32), (1, 179, 32), (1, 180, 31), (1, 181, 31), (1, 182, 31), (1, 183, 30), (1, 184, 30), (1, 185, 30), (1, 186, 29), (1, 187, 29), (1, 188, 29), (1, 189, 28), (1, 190, 28), (1, 191, 27), (1, 192, 27), (1, 193, 26), (1, 194, 26), (1, 195, 26), (1, 196, 26), (1, 197, 26), (1, 198, 26), (1, 199, 26), (1, 200, 25), (1, 201, 25), (1, 202, 25), (1, 203, 25), (1, 204, 25), (1, 205, 25), (1, 206, 25), (1, 207, 25), (1, 208, 25), (1, 209, 25), (1, 210, 25), (1, 211, 25), (1, 212, 25), (1, 213, 25), (1, 214, 25), (1, 215, 25), (1, 216, 25), (1, 217, 25), (1, 218, 25), (1, 219, 25), (1, 220, 24), (1, 221, 24), (1, 222, 24), (1, 223, 24), (1, 224, 24), (1, 225, 24), (1, 226, 25), (1, 227, 25), (1, 228, 25), (2, 229, 24), (2, 230, 24), (2, 231, 24), (2, 232, 23), (2, 233, 23), (2, 234, 23), (2, 235, 23), (2, 236, 23), (2, 237, 23), (2, 238, 23), (2, 239, 23), (2, 240, 23), (2, 241, 23), (2, 242, 23), (2, 243, 23), (2, 244, 23), (2, 245, 23), (2, 246, 23), (2, 247, 23), (2, 248, 23), (2, 249, 24), (2, 250, 24), (2, 251, 23), (2, 252, 23), (2, 253, 23), (2, 254, 23), (2, 255, 23), (2, 256, 23), (2, 257, 23), (2, 258, 23), (2, 259, 23), (2, 260, 23), (2, 261, 23), (3, 262, 22), (3, 263, 22), (3, 264, 22), (3, 265, 22), (4, 266, 21), (4, 267, 21), (5, 268, 20), (5, 269, 20), (6, 270, 19), (7, 271, 17), (8, 272, 16), (8, 273, 16), (9, 274, 13), (11, 275, 9), (15, 276, 2)], ['16,276,8,273,2,261,2,229,1,228,1,114,2,113,2,82,1,81,1,46,3,37,8,32,20,32,21,33,58,33,59,34,75,34,76,35,102,35,120,31,130,30,135,27,145,26,152,29,158,35,158,48,154,54,149,56,138,58,128,61,119,67,105,81,103,86,96,94,89,98,81,109,71,119,65,132,60,138,52,151,45,158,40,166,34,172,29,188,26,193,25,200,25,219,24,232,24,270,23,273']), (957285035, 492601069, 445, 29, 591, 24, 419, 0.9923746, [(315, 37, 25), (272, 38, 86), (253, 39, 130), (238, 40, 151), (199, 41, 196), (189, 42, 213), (180, 43, 238), (175, 44, 250), (172, 45, 257), (169, 46, 265), (166, 47, 274), (162, 48, 284), (159, 49, 294), (157, 50, 304), (155, 51, 311), (153, 52, 317), (151, 53, 323), (149, 54, 330), (148, 55, 334), (146, 56, 337), (144, 57, 341), (142, 58, 344), (140, 59, 347), (138, 60, 350), (136, 61, 353), (134, 62, 356), (132, 63, 358), (130, 64, 361), (128, 65, 364), (126, 66, 367), (124, 67, 370), (122, 68, 373), (120, 69, 376), (118, 70, 379), (117, 71, 381), (115, 72, 385), (114, 73, 387), (113, 74, 389), (112, 75, 391), (112, 76, 393), (111, 77, 395), (110, 78, 397), (109, 79, 399), (109, 80, 400), (108, 81, 402), (107, 82, 404), (107, 83, 404), (106, 84, 406), (105, 85, 408), (105, 86, 409), (104, 87, 410), (104, 88, 411), (103, 89, 413), (102, 90, 415), (101, 91, 417), (100, 92, 420), (98, 93, 423), (97, 94, 426), (96, 95, 428), (94, 96, 431), (93, 97, 433), (92, 98, 435), (91, 99, 437), (90, 100, 439), (89, 101, 441), (89, 102, 441), (89, 103, 442), (89, 104, 443), (89, 105, 444), (89, 106, 444), (89, 107, 445), (89, 108, 446), (89, 109, 447), (89, 110, 448), (89, 111, 449), (89, 112, 450), (89, 113, 451), (89, 114, 453), (89, 115, 454), (89, 116, 455), (88, 117, 456), (88, 118, 457), (87, 119, 459), (87, 120, 459), (86, 121, 461), (85, 122, 462), (85, 123, 463), (84, 124, 464), (84, 125, 465), (83, 126, 466), (82, 127, 468), (82, 128, 468), (81, 129, 470), (80, 130, 471), (78, 131, 473), (76, 132, 476), (75, 133, 477), (73, 134, 480), (71, 135, 482), (70, 136, 484), (68, 137, 486), (67, 138, 488), (65, 139, 490), (64, 140, 492), (62, 141, 494), (61, 142, 496), (60, 143, 497), (59, 144, 499), (58, 145, 501), (58, 146, 501), (57, 147, 503), (57, 148, 504), (56, 149, 506), (56, 150, 507), (56, 151, 507), (55, 152, 509), (55, 153, 510), (54, 154, 511), (54, 155, 512), (54, 156, 513), (53, 157, 514), (53, 158, 514), (52, 159, 515), (52, 160, 516), (51, 161, 517), (51, 162, 517), (51, 163, 517), (50, 164, 518), (50, 165, 518), (49, 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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/1770870029_3052451_957285035_a42482e51c93c8025d243dd179aee85b.jpg']} free memory after detection : begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 2161 ############################### 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 : 0.2063429355621338 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : False number of steps : 1 step1:mask_detect Thu Feb 12 05:21:15 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 : 2161 wait 20 seconds l 3637 free memory gpu now : 2161 max_wait_temp : 1 max_wait : 0 gpu_flag : 0 2026-02-12 05:21:38.850490: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2026-02-12 05:21:38.874518: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493010000 Hz 2026-02-12 05:21:38.876578: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7fb170000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2026-02-12 05:21:38.876638: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2026-02-12 05:21:38.880597: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2026-02-12 05:21:39.003909: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x6a4cca0 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2026-02-12 05:21:39.003963: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2026-02-12 05:21:39.004968: 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 2026-02-12 05:21:39.005405: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2026-02-12 05:21:39.008757: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2026-02-12 05:21:39.011751: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2026-02-12 05:21:39.012180: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2026-02-12 05:21:39.015010: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2026-02-12 05:21:39.016432: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2026-02-12 05:21:39.021520: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2026-02-12 05:21:39.022507: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2026-02-12 05:21:39.022604: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2026-02-12 05:21:39.023146: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2026-02-12 05:21:39.023163: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2026-02-12 05:21:39.023172: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2026-02-12 05:21:39.023978: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 1785 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. 2026-02-12 05:21:39.134317: 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 2026-02-12 05:21:39.134464: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2026-02-12 05:21:39.134493: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2026-02-12 05:21:39.134519: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2026-02-12 05:21:39.134564: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2026-02-12 05:21:39.134591: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2026-02-12 05:21:39.134616: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2026-02-12 05:21:39.134642: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2026-02-12 05:21:39.135620: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2026-02-12 05:21:39.136741: 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 2026-02-12 05:21:39.136786: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2026-02-12 05:21:39.136813: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2026-02-12 05:21:39.136837: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2026-02-12 05:21:39.136861: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2026-02-12 05:21:39.136886: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2026-02-12 05:21:39.136910: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2026-02-12 05:21:39.136934: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2026-02-12 05:21:39.137894: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2026-02-12 05:21:39.137933: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2026-02-12 05:21:39.137945: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2026-02-12 05:21:39.137955: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2026-02-12 05:21:39.138975: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 1785 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 : [] 2026-02-12 05:21:48.301246: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2026-02-12 05:21:48.470302: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2026-02-12 05:21:49.682876: 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. 2026-02-12 05:21:49.682961: 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. 2026-02-12 05:21:49.689659: 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. 2026-02-12 05:21:49.689684: 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. 2026-02-12 05:21:49.749991: 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. 2026-02-12 05:21:49.750108: 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. 2026-02-12 05:21:49.794850: 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. 2026-02-12 05:21:49.794893: 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. 2026-02-12 05:21:49.847680: 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. 2026-02-12 05:21:49.847717: 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. 2026-02-12 05:21:49.849424: 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. 2026-02-12 05:21:49.867859: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:49.868842: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.12G (1202356224 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:49.869861: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:49.879318: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:49.879887: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:49.885110: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:49.885678: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:49.898707: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:49.899271: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:49.901121: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:49.901743: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:49.908634: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:49.909183: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:49.911135: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:49.911703: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:49.918772: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:49.919407: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:49.921147: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:49.921680: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:49.950696: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:49.951259: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:49.951792: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:49.952339: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:49.956022: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:49.956572: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:49.972707: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:49.973287: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:49.973834: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:49.974392: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:49.986837: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:49.987399: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:49.987942: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:49.988484: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:49.993028: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:49.993573: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:49.998362: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:49.998910: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:50.011134: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:50.011695: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:50.015862: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:50.016416: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:50.037563: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:50.038114: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:50.038706: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:50.039252: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:50.039795: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:50.040335: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:50.082629: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:50.082724: 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. 2026-02-12 05:21:50.083764: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:50.084847: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:50.092056: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:50.092603: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:50.100803: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:50.101396: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:50.117294: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:50.117910: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:50.118521: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:50.119112: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:50.123270: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:50.123859: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:50.124459: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:50.124981: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:50.126062: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:50.136187: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:50.136766: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:50.147129: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:50.147704: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:50.148247: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:50.148804: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:50.149402: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:21:50.149937: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 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 3053248 begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 968 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 : 2161 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 : 0.0004115104675292969 nb_pixel_total : 16902 time to create 1 rle with old method : 0.035892486572265625 length of segment : 107 DEBUG bbox = [16, 52, 668, 1128] DEBUG masks shape = (720, 1280) time for calcul the mask position with numpy : 0.021692752838134766 nb_pixel_total : 480751 time to create 1 rle with new method : 0.02887725830078125 length of segment : 632 DEBUG bbox = [0, 0, 116, 440] DEBUG masks shape = (720, 1280) time for calcul the mask position with numpy : 0.0004394054412841797 nb_pixel_total : 36641 time to create 1 rle with old method : 0.07880973815917969 length of segment : 133 DEBUG bbox = [0, 390, 54, 550] DEBUG masks shape = (720, 1280) time for calcul the mask position with numpy : 0.00012969970703125 nb_pixel_total : 4791 time to create 1 rle with old method : 0.01114797592163086 length of segment : 51 time spent for convertir_results : 0.4286494255065918 time spend for datou_step_exec : 38.174476623535156 time spend to save output : 4.100799560546875e-05 total time spend for step 1 : 38.17451763153076 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 : 0.015689849853515625 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, 0.99883634, [(1205, 1, 58), (1165, 2, 105), (1159, 3, 113), (1149, 4, 124), (1113, 5, 161), (1100, 6, 174), (1097, 7, 177), (1095, 8, 179), (1095, 9, 179), (1095, 10, 179), (1095, 11, 179), (1095, 12, 179), (1095, 13, 179), (1095, 14, 178), (1095, 15, 178), (1095, 16, 178), (1095, 17, 178), (1095, 18, 177), (1095, 19, 177), (1095, 20, 177), (1095, 21, 177), (1095, 22, 177), (1095, 23, 178), (1095, 24, 178), (1095, 25, 178), (1095, 26, 179), (1095, 27, 179), (1095, 28, 180), (1095, 29, 181), (1095, 30, 182), (1095, 31, 183), (1095, 32, 183), (1095, 33, 184), (1095, 34, 184), (1096, 35, 183), (1096, 36, 183), (1096, 37, 184), (1097, 38, 183), (1097, 39, 183), (1097, 40, 183), (1098, 41, 182), (1098, 42, 182), (1098, 43, 182), (1099, 44, 181), (1099, 45, 181), (1099, 46, 181), (1100, 47, 180), (1100, 48, 180), (1101, 49, 179), (1101, 50, 179), (1102, 51, 178), (1102, 52, 178), (1103, 53, 177), (1103, 54, 177), (1104, 55, 176), (1104, 56, 176), (1104, 57, 176), (1104, 58, 176), (1105, 59, 175), (1105, 60, 175), (1105, 61, 175), (1105, 62, 175), (1105, 63, 175), (1106, 64, 174), (1106, 65, 174), (1106, 66, 174), (1106, 67, 174), (1106, 68, 174), (1106, 69, 174), (1106, 70, 174), (1106, 71, 174), (1106, 72, 174), (1106, 73, 174), (1107, 74, 173), (1107, 75, 173), (1107, 76, 173), (1107, 77, 173), (1107, 78, 173), (1107, 79, 173), (1108, 80, 172), (1108, 81, 172), (1109, 82, 171), (1110, 83, 170), (1110, 84, 170), (1111, 85, 169), (1112, 86, 168), (1113, 87, 166), (1114, 88, 165), (1115, 89, 164), (1117, 90, 162), (1120, 91, 159), (1138, 92, 141), (1146, 93, 133), (1154, 94, 125), (1167, 95, 112), (1177, 96, 102), (1183, 97, 95), (1185, 98, 93), (1187, 99, 90), (1188, 100, 55), (1264, 100, 12), (1190, 101, 50), (1191, 102, 46), (1194, 103, 40), (1197, 104, 34), (1202, 105, 25), (1207, 106, 16)], ['1222,106,1207,106,1206,105,1197,104,1191,102,1182,96,1176,95,1167,95,1166,94,1154,94,1153,93,1146,93,1145,92,1137,91,1120,91,1115,89,1110,84,1107,79,1106,73,1106,64,1104,55,1099,46,1095,34,1095,8,1100,6,1112,6,1113,5,1148,5,1149,4,1158,4,1165,2,1204,2,1205,1,1262,1,1269,2,1273,5,1273,13,1271,18,1271,22,1273,27,1277,31,1279,37,1279,86,1278,87,1278,96,1275,100,1264,100,1263,99,1243,99,1230,104']), (917855882, 492601069, 445, 52, 1128, 16, 668, 0.9977487, [(711, 22, 22), (925, 22, 47), (608, 23, 146), (894, 23, 103), (598, 24, 234), (850, 24, 158), (590, 25, 427), (582, 26, 444), (575, 27, 458), (569, 28, 466), (565, 29, 472), (560, 30, 480), (556, 31, 486), (550, 32, 495), (544, 33, 503), (538, 34, 512), (532, 35, 520), (527, 36, 527), (523, 37, 534), (518, 38, 541), (514, 39, 548), (510, 40, 554), (506, 41, 561), (503, 42, 566), (499, 43, 572), (496, 44, 577), (493, 45, 582), (491, 46, 585), (488, 47, 590), (487, 48, 592), (485, 49, 595), (483, 50, 598), (482, 51, 600), (481, 52, 602), (480, 53, 603), (479, 54, 605), (478, 55, 606), (476, 56, 608), (475, 57, 610), (474, 58, 611), (473, 59, 613), (472, 60, 614), (470, 61, 616), (469, 62, 618), (468, 63, 619), (466, 64, 621), (465, 65, 623), (464, 66, 624), (462, 67, 626), (461, 68, 628), (459, 69, 630), (458, 70, 631), (456, 71, 633), (455, 72, 635), (453, 73, 637), (452, 74, 638), (451, 75, 639), (450, 76, 640), (448, 77, 642), (447, 78, 643), (446, 79, 644), (445, 80, 645), (444, 81, 646), (442, 82, 648), (441, 83, 649), (440, 84, 650), (439, 85, 651), (438, 86, 652), (437, 87, 653), (436, 88, 654), (435, 89, 655), (434, 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(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)], ['449,46,443,46,442,45,426,45,424,41,424,37,423,36,422,31,420,28,420,25,419,24,419,21,418,20,418,17,417,15,409,6,402,3,402,1,414,1,415,0,419,0,420,1,440,1,441,0,500,0,501,1,507,1,508,0,535,0,536,1,543,1,546,2,546,4,542,8,530,18,527,19,525,21,522,22,520,24,512,28,508,33,505,34,502,37,494,41,492,41,490,43,488,43,484,45,473,45,472,46'])], 'temp/1770870075_3052451_917855882_da0fa7b7e6b5b551fe26c0ba8713276d.jpg']} ############################### TEST POLYGON ################################ Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! List Step Type Loaded in datou : mask_detect list_input_json : [] origin BFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 time to download the photos : 0.18040013313293457 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : False number of steps : 1 step1:mask_detect Thu Feb 12 05:21:55 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 : 2161 wait 20 seconds l 3637 free memory gpu now : 2161 max_wait_temp : 1 max_wait : 0 gpu_flag : 0 2026-02-12 05:22:18.808597: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2026-02-12 05:22:18.834505: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493010000 Hz 2026-02-12 05:22:18.836567: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7fb168000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2026-02-12 05:22:18.836610: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2026-02-12 05:22:18.840110: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2026-02-12 05:22:18.952766: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x6bcbb10 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2026-02-12 05:22:18.952812: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2026-02-12 05:22:18.953787: 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 2026-02-12 05:22:18.954168: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2026-02-12 05:22:18.957066: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2026-02-12 05:22:18.959592: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2026-02-12 05:22:18.960071: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2026-02-12 05:22:18.963147: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2026-02-12 05:22:18.964742: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2026-02-12 05:22:18.969653: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2026-02-12 05:22:18.970632: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2026-02-12 05:22:18.970701: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2026-02-12 05:22:18.971214: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2026-02-12 05:22:18.971230: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2026-02-12 05:22:18.971239: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2026-02-12 05:22:18.972072: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 1785 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. 2026-02-12 05:22:19.079049: 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 2026-02-12 05:22:19.079139: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2026-02-12 05:22:19.079163: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2026-02-12 05:22:19.079198: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2026-02-12 05:22:19.079221: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2026-02-12 05:22:19.079241: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2026-02-12 05:22:19.079262: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2026-02-12 05:22:19.079283: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2026-02-12 05:22:19.080215: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2026-02-12 05:22:19.081188: 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 2026-02-12 05:22:19.081226: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2026-02-12 05:22:19.081248: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2026-02-12 05:22:19.081268: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2026-02-12 05:22:19.081288: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2026-02-12 05:22:19.081308: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2026-02-12 05:22:19.081327: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2026-02-12 05:22:19.081348: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2026-02-12 05:22:19.082270: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2026-02-12 05:22:19.082337: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2026-02-12 05:22:19.082348: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2026-02-12 05:22:19.082358: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2026-02-12 05:22:19.083336: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 1785 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 : [] 2026-02-12 05:22:30.093279: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2026-02-12 05:22:30.241834: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2026-02-12 05:22:31.371513: 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. 2026-02-12 05:22:31.371557: 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. 2026-02-12 05:22:31.377951: 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. 2026-02-12 05:22:31.377973: 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. 2026-02-12 05:22:31.425927: 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. 2026-02-12 05:22:31.425973: 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. 2026-02-12 05:22:31.467406: 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. 2026-02-12 05:22:31.467445: 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. 2026-02-12 05:22:31.518315: 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. 2026-02-12 05:22:31.518341: 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. 2026-02-12 05:22:31.519977: 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. 2026-02-12 05:22:31.543767: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.544669: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.12G (1202356224 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.545590: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.552693: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.553374: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.557694: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.558435: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.568579: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.569086: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.570572: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.571131: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.576400: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.576929: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.578499: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.579054: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.584458: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.584985: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.586438: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.586944: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.612397: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.612936: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.613437: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.613937: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.617297: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.617808: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.632770: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.633281: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.633784: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.634305: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.646375: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.646883: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.647385: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.647885: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.651949: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.652454: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.656920: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.657475: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.669582: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.670098: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.674188: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.674698: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.695418: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.695973: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.696541: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.697072: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.697576: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.698077: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.734602: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.734647: 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. 2026-02-12 05:22:31.735601: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.736588: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.744028: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.745014: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.752990: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.753493: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.767681: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.768386: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.769075: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.769750: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.773952: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.774672: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.775287: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.775835: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.776684: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.786986: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.787539: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.797653: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.798166: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.798701: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.799210: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.799722: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2026-02-12 05:22:31.800226: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.24G (1335951360 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 3053846 begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 968 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 : 2161 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, 0, 2222, 2279] DEBUG masks shape = (2448, 2448) time for calcul the mask position with numpy : 0.1742558479309082 nb_pixel_total : 3697244 time to create 1 rle with new method : 0.4215888977050781 length of segment : 2044 time spent for convertir_results : 1.9411194324493408 time spend for datou_step_exec : 42.06798315048218 time spend to save output : 4.7206878662109375e-05 total time spend for step 1 : 42.06803035736084 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 : 0.02339792251586914 save missing photos in datou_result : After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : {'917877156': [[(917877156, 492601069, 445, 0, 2279, 103, 2222, 0.9818688, [(1250, 110, 26), (652, 111, 289), (1203, 111, 134), (614, 112, 376), (1082, 112, 345), (525, 113, 909), (518, 114, 922), (511, 115, 936), (505, 116, 948), (498, 117, 960), (492, 118, 972), (487, 119, 983), (481, 120, 994), (476, 121, 1004), (470, 122, 1015), (465, 123, 1025), (460, 124, 1034), (456, 125, 1042), (451, 126, 1052), (447, 127, 1061), (442, 128, 1076), (438, 129, 1089), (434, 130, 1102), (430, 131, 1115), (427, 132, 1127), (423, 133, 1139), (419, 134, 1151), (416, 135, 1162), (413, 136, 1172), (409, 137, 1181), (406, 138, 1187), (403, 139, 1193), (400, 140, 1200), (397, 141, 1206), (394, 142, 1212), (391, 143, 1219), (388, 144, 1225), (385, 145, 1231), (382, 146, 1238), (379, 147, 1245), (375, 148, 1253), (372, 149, 1260), (368, 150, 1268), (365, 151, 1275), (363, 152, 1281), (360, 153, 1289), (358, 154, 1295), (355, 155, 1303), (353, 156, 1310), (350, 157, 1318), (348, 158, 1325), (345, 159, 1333), (342, 160, 1341), (339, 161, 1350), (336, 162, 1358), (333, 163, 1367), (330, 164, 1376), (327, 165, 1385), (324, 166, 1395), (321, 167, 1405), (317, 168, 1415), (314, 169, 1426), (311, 170, 1436), (307, 171, 1448), (303, 172, 1461), (299, 173, 1473), (296, 174, 1485), (292, 175, 1497), (288, 176, 1510), (284, 177, 1523), (280, 178, 1536), (277, 179, 1548), (274, 180, 1559), (271, 181, 1567), (268, 182, 1574), (266, 183, 1580), (263, 184, 1588), (260, 185, 1595), (258, 186, 1600), (255, 187, 1607), (253, 188, 1613), (250, 189, 1619), (248, 190, 1625), (245, 191, 1631), (243, 192, 1636), (241, 193, 1641), (239, 194, 1646), (237, 195, 1651), (235, 196, 1656), (233, 197, 1661), (231, 198, 1665), (229, 199, 1670), (227, 200, 1674), (225, 201, 1679), (223, 202, 1683), (222, 203, 1686), (220, 204, 1691), (218, 205, 1695), (217, 206, 1697), (215, 207, 1700), (213, 208, 1704), (212, 209, 1706), (210, 210, 1709), (209, 211, 1711), (207, 212, 1715), (206, 213, 1717), (205, 214, 1719), (203, 215, 1722), (202, 216, 1724), (201, 217, 1726), (199, 218, 1729), (198, 219, 1731), (197, 220, 1732), (195, 221, 1735), (194, 222, 1737), (193, 223, 1739), (192, 224, 1741), (190, 225, 1744), (189, 226, 1746), (187, 227, 1749), (186, 228, 1751), (185, 229, 1753), (183, 230, 1756), (182, 231, 1758), (180, 232, 1762), (179, 233, 1764), (178, 234, 1766), (176, 235, 1769), (175, 236, 1771), (173, 237, 1774), (172, 238, 1776), (170, 239, 1780), (169, 240, 1782), (167, 241, 1785), (166, 242, 1787), (164, 243, 1791), (163, 244, 1793), (161, 245, 1796), (159, 246, 1799), (158, 247, 1802), (156, 248, 1805), (155, 249, 1808), (153, 250, 1811), (151, 251, 1814), (150, 252, 1817), (148, 253, 1820), (146, 254, 1824), (145, 255, 1826), (143, 256, 1830), (141, 257, 1834), (140, 258, 1836), (138, 259, 1840), (136, 260, 1843), (134, 261, 1847), (132, 262, 1851), (131, 263, 1854), (129, 264, 1857), (127, 265, 1861), (125, 266, 1865), (123, 267, 1869), (122, 268, 1872), (120, 269, 1875), (119, 270, 1878), (118, 271, 1880), (117, 272, 1882), (115, 273, 1886), (114, 274, 1888), (113, 275, 1890), (112, 276, 1892), (111, 277, 1894), (110, 278, 1896), (109, 279, 1898), (108, 280, 1901), (107, 281, 1903), (106, 282, 1905), (105, 283, 1906), (105, 284, 1907), (104, 285, 1909), (103, 286, 1911), (102, 287, 1913), (101, 288, 1915), (101, 289, 1916), (100, 290, 1917), (99, 291, 1919), (99, 292, 1920), (98, 293, 1921), (98, 294, 1922), (97, 295, 1923), (97, 296, 1924), (97, 297, 1924), (96, 298, 1926), (96, 299, 1926), (95, 300, 1928), (95, 301, 1928), (95, 302, 1929), (94, 303, 1930), (94, 304, 1931), (94, 305, 1931), (93, 306, 1933), (93, 307, 1933), (92, 308, 1935), (92, 309, 1935), (92, 310, 1936), (91, 311, 1937), (91, 312, 1938), (91, 313, 1938), (90, 314, 1940), (90, 315, 1940), (89, 316, 1942), (89, 317, 1942), (89, 318, 1943), (88, 319, 1944), (88, 320, 1945), (88, 321, 1945), (87, 322, 1947), (87, 323, 1948), (87, 324, 1948), (86, 325, 1950), (86, 326, 1950), (85, 327, 1952), (85, 328, 1952), (85, 329, 1953), (84, 330, 1954), (84, 331, 1955), (84, 332, 1955), (83, 333, 1957), (83, 334, 1957), (83, 335, 1958), (82, 336, 1959), (82, 337, 1960), (82, 338, 1960), (81, 339, 1962), (81, 340, 1963), (81, 341, 1963), (80, 342, 1965), (80, 343, 1965), (80, 344, 1966), (79, 345, 1967), (79, 346, 1968), (79, 347, 1968), (78, 348, 1970), (78, 349, 1971), (78, 350, 1971), (77, 351, 1973), (77, 352, 1973), (77, 353, 1974), (76, 354, 1975), (76, 355, 1976), (76, 356, 1976), (75, 357, 1978), (75, 358, 1979), (75, 359, 1979), (74, 360, 1981), (74, 361, 1981), (74, 362, 1982), (74, 363, 1983), (73, 364, 1984), (73, 365, 1985), (73, 366, 1985), (72, 367, 1987), (72, 368, 1988), (72, 369, 1988), (72, 370, 1989), (71, 371, 1991), (71, 372, 1992), (71, 373, 1993), (71, 374, 1993), (70, 375, 1995), (70, 376, 1996), (70, 377, 1997), (70, 378, 1998), (69, 379, 2000), (69, 380, 2001), (69, 381, 2002), (68, 382, 2004), (68, 383, 2005), (68, 384, 2006), (68, 385, 2007), (67, 386, 2009), (67, 387, 2011), (67, 388, 2012), (67, 389, 2013), (66, 390, 2015), (66, 391, 2016), (66, 392, 2017), (65, 393, 2019), (65, 394, 2020), (65, 395, 2021), (65, 396, 2022), (64, 397, 2023), (64, 398, 2024), (64, 399, 2025), (63, 400, 2027), (63, 401, 2028), (63, 402, 2029), (62, 403, 2030), (62, 404, 2031), (62, 405, 2032), (61, 406, 2034), (61, 407, 2034), (61, 408, 2035), (61, 409, 2036), (60, 410, 2037), (60, 411, 2038), (60, 412, 2039), (59, 413, 2040), (59, 414, 2041), (58, 415, 2043), (58, 416, 2043), (58, 417, 2044), (57, 418, 2046), (57, 419, 2046), (57, 420, 2047), (56, 421, 2048), (56, 422, 2049), (56, 423, 2049), (55, 424, 2051), (55, 425, 2051), (54, 426, 2053), (54, 427, 2053), (54, 428, 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['936,2141,854,2123,758,2087,665,2063,447,1996,204,1964,122,1970,88,1911,51,1806,51,1725,40,1659,44,1590,40,1441,29,1278,29,887,19,682,29,525,47,447,99,291,223,202,419,134,525,113,652,111,1426,112,1584,136,1653,155,1832,180,1910,204,2018,292,2059,369,2114,443,2166,665,2152,822,2127,898,2119,974,2093,1050,2046,1108,2007,1199,1959,1275,1939,1350,1886,1426,1847,1658,1772,1887,1727,1962,1668,2011,1585,2014,1507,2049,1430,2054,1259,2080,1094,2137'])], 'temp/1770870115_3052451_917877156_a9c2d4b99270c9302def4ed40606e685.jpg']} nb pixel non reg : 3692295 nb pixel common : 3678237 proportion of common points : 0.9961926119121034 #&_# TEST SUCCEEDED #&_# : 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 : 0.1884620189666748 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 Thu Feb 12 05:22:45 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; 678.06 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 : 0.022536039352416992 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; 678.06 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 : 9.066059350967407 time spend to save output : 0.0380094051361084 total time spend for step 0 : 9.104068756103516 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 : 0.12766075134277344 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 Thu Feb 12 05:22:54 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 F0212 05:22:55.675274 3052451 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 39.33user 26.19system 2:30.16elapsed 43%CPU (0avgtext+0avgdata 2955988maxresident)k 4014008inputs+4816outputs (13355major+2794125minor)pagefaults 0swaps