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facebookresearch / Detectron

FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.
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yaml.constructor.ConstructorError: could not determine a constructor for the tag ... #988

Closed yakupakkaya closed 4 years ago

yakupakkaya commented 4 years ago

I changed requirements.txt to install pyyaml 3.12 as suggested in similar issues but when I run python3 tools/test_net.py --cfg '/tmp/detectron/configs/2020.yaml' TEST.WEIGHTS '/tmp/detectron-output/train/Mini_Train/generalized_rcnn/model_final.pkl' NUM_GPUS 1

command, I am still getting the same error.

nvcc: NVIDIA (R) Cuda compiler driver Copyright (c) 2005-2019 NVIDIA Corporation Built on Sun_Jul_28_19:07:16_PDT_2019 Cuda compilation tools, release 10.1, V10.1.243

Thu Mar 26 18:53:21 2020 +-----------------------------------------------------------------------------+ | NVIDIA-SMI 418.87.01 Driver Version: 418.87.01 CUDA Version: 10.1 | |-------------------------------+----------------------+----------------------+ | GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC | | Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. | |===============================+======================+======================| | 0 Tesla K80 Off | 00000000:00:04.0 Off | 0 | | N/A 74C P0 93W / 149W | 0MiB / 11441MiB | 100% Default | +-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+ | Processes: GPU Memory | | GPU PID Type Process name Usage | |=============================================================================| | No running processes found | +-----------------------------------------------------------------------------+

Found Detectron ops lib: /home/msi/.local/lib/python3.5/site-packages/torch/lib/libcaffe2_detectron_ops_gpu.so [E init_intrinsics_check.cc:43] CPU feature avx is present on your machine, but the Caffe2 binary is not compiled with it. It means you may not get the full speed of your CPU. [E init_intrinsics_check.cc:43] CPU feature avx2 is present on your machine, but the Caffe2 binary is not compiled with it. It means you may not get the full speed of your CPU. [E init_intrinsics_check.cc:43] CPU feature fma is present on your machine, but the Caffe2 binary is not compiled with it. It means you may not get the full speed of your CPU. INFO test_net.py: 98: Called with args: INFO test_net.py: 99: Namespace(cfg_file='/tmp/detectron/configs/2020.yaml', multi_gpu_testing=False, opts=['TEST.WEIGHTS', '/tmp/detectron-output/train/Mini_Train/generalized_rcnn/model_final.pkl', 'NUM_GPUS', '1'], range=None, vis=False, wait=True) INFO test_net.py: 105: Testing with config: INFO test_net.py: 106: {'BBOX_XFORM_CLIP': 4.135166556742356, 'CLUSTER': {'ON_CLUSTER': False}, 'DATA_LOADER': {'BLOBS_QUEUE_CAPACITY': 8, 'MINIBATCH_QUEUE_SIZE': 64, 'NUM_THREADS': 4}, 'DEDUP_BOXES': 0.0625, 'DOWNLOAD_CACHE': '/tmp/detectron-download-cache', 'EPS': 1e-14, 'EXPECTED_RESULTS': [], 'EXPECTED_RESULTS_ATOL': 0.005, 'EXPECTED_RESULTS_EMAIL': '', 'EXPECTED_RESULTS_RTOL': 0.1, 'EXPECTED_RESULTS_SIGMA_TOL': 4, 'FAST_RCNN': {'CONV_HEAD_DIM': 256, 'MLP_HEAD_DIM': 1024, 'NUM_STACKED_CONVS': 4, 'ROI_BOX_HEAD': 'fast_rcnn_heads.add_roi_Xconv1fc_gn_head', 'ROI_XFORM_METHOD': 'RoIAlign', 'ROI_XFORM_RESOLUTION': 7, 'ROI_XFORM_SAMPLING_RATIO': 2}, 'FPN': {'COARSEST_STRIDE': 32, 'DIM': 256, 'EXTRA_CONV_LEVELS': False, 'FPN_ON': True, 'MULTILEVEL_ROIS': True, 'MULTILEVEL_RPN': True, 'ROI_CANONICAL_LEVEL': 4, 'ROI_CANONICAL_SCALE': 224, 'ROI_MAX_LEVEL': 5, 'ROI_MIN_LEVEL': 2, 'RPN_ANCHOR_START_SIZE': 32, 'RPN_ASPECT_RATIOS': (0.5, 1, 2), 'RPN_MAX_LEVEL': 6, 'RPN_MIN_LEVEL': 2, 'USE_GN': True, 'ZERO_INIT_LATERAL': False}, 'GROUP_NORM': {'DIM_PER_GP': -1, 'EPSILON': 1e-05, 'NUM_GROUPS': 32}, 'KRCNN': {'CONV_HEAD_DIM': 256, 'CONV_HEAD_KERNEL': 3, 'CONV_INIT': 'GaussianFill', 'DECONV_DIM': 256, 'DECONV_KERNEL': 4, 'DILATION': 1, 'HEATMAP_SIZE': -1, 'INFERENCE_MIN_SIZE': 0, 'KEYPOINT_CONFIDENCE': 'bbox', 'LOSS_WEIGHT': 1.0, 'MIN_KEYPOINT_COUNT_FOR_VALID_MINIBATCH': 20, 'NMS_OKS': False, 'NORMALIZE_BY_VISIBLE_KEYPOINTS': True, 'NUM_KEYPOINTS': -1, 'NUM_STACKED_CONVS': 8, 'ROI_KEYPOINTS_HEAD': '', 'ROI_XFORM_METHOD': 'RoIAlign', 'ROI_XFORM_RESOLUTION': 7, 'ROI_XFORM_SAMPLING_RATIO': 0, 'UP_SCALE': -1, 'USE_DECONV': False, 'USE_DECONV_OUTPUT': False}, 'MATLAB': 'matlab', 'MEMONGER': True, 'MEMONGER_SHARE_ACTIVATIONS': False, 'MODEL': {'BBOX_REG_WEIGHTS': (10.0, 10.0, 5.0, 5.0), 'CLS_AGNOSTIC_BBOX_REG': False, 'CONV_BODY': 'FPN.add_fpn_ResNet50_conv5_body', 'EXECUTION_TYPE': 'dag', 'FASTER_RCNN': True, 'KEYPOINTS_ON': False, 'MASK_ON': True, 'NUM_CLASSES': 3, 'RPN_ONLY': False, 'TYPE': 'generalized_rcnn'}, 'MRCNN': {'CLS_SPECIFIC_MASK': True, 'CONV_INIT': 'MSRAFill', 'DILATION': 1, 'DIM_REDUCED': 256, 'RESOLUTION': 28, 'ROI_MASK_HEAD': 'mask_rcnn_heads.mask_rcnn_fcn_head_v1up4convs_gn', 'ROI_XFORM_METHOD': 'RoIAlign', 'ROI_XFORM_RESOLUTION': 14, 'ROI_XFORM_SAMPLING_RATIO': 2, 'THRESH_BINARIZE': 0.5, 'UPSAMPLE_RATIO': 1, 'USE_FC_OUTPUT': False, 'WEIGHT_LOSS_MASK': 1.0}, 'NUM_GPUS': 1, 'OUTPUT_DIR': '.', 'PIXEL_MEANS': array([[[102.9801, 115.9465, 122.7717]]]), 'RESNETS': {'NUM_GROUPS': 1, 'RES5_DILATION': 1, 'SHORTCUT_FUNC': 'basic_gn_shortcut', 'STEM_FUNC': 'basic_gn_stem', 'STRIDE_1X1': False, 'TRANS_FUNC': 'bottleneck_gn_transformation', 'WIDTH_PER_GROUP': 64}, 'RETINANET': {'ANCHOR_SCALE': 4, 'ASPECT_RATIOS': (0.5, 1.0, 2.0), 'BBOX_REG_BETA': 0.11, 'BBOX_REG_WEIGHT': 1.0, 'CLASS_SPECIFIC_BBOX': False, 'INFERENCE_TH': 0.05, 'LOSS_ALPHA': 0.25, 'LOSS_GAMMA': 2.0, 'NEGATIVE_OVERLAP': 0.4, 'NUM_CONVS': 4, 'POSITIVE_OVERLAP': 0.5, 'PRE_NMS_TOP_N': 1000, 'PRIOR_PROB': 0.01, 'RETINANET_ON': False, 'SCALES_PER_OCTAVE': 3, 'SHARE_CLS_BBOX_TOWER': False, 'SOFTMAX': False}, 'RFCN': {'PS_GRID_SIZE': 3}, 'RNG_SEED': 3, 'ROOT_DIR': '/tmp/detectron', 'RPN': {'ASPECT_RATIOS': (0.5, 1, 2), 'RPN_ON': True, 'SIZES': (64, 128, 256, 512), 'STRIDE': 16}, 'SOLVER': {'BASE_LR': 0.01, 'GAMMA': 0.1, 'LOG_LR_CHANGE_THRESHOLD': 1.1, 'LRS': [], 'LR_POLICY': 'steps_with_decay', 'MAX_ITER': 200, 'MOMENTUM': 0.9, 'SCALE_MOMENTUM': True, 'SCALE_MOMENTUM_THRESHOLD': 1.1, 'STEPS': [0, 50, 150], 'STEP_SIZE': 30000, 'WARM_UP_FACTOR': 0.3333333333333333, 'WARM_UP_ITERS': 500, 'WARM_UP_METHOD': 'linear', 'WEIGHT_DECAY': 0.0001, 'WEIGHT_DECAY_GN': 0.0}, 'TEST': {'BBOX_AUG': {'AREA_TH_HI': 32400, 'AREA_TH_LO': 2500, 'ASPECT_RATIOS': (), 'ASPECT_RATIO_H_FLIP': False, 'COORD_HEUR': 'UNION', 'ENABLED': False, 'H_FLIP': False, 'MAX_SIZE': 4000, 'SCALES': (), 'SCALE_H_FLIP': False, 'SCALE_SIZE_DEP': False, 'SCORE_HEUR': 'UNION'}, 'BBOX_REG': True, 'BBOX_VOTE': {'ENABLED': False, 'SCORING_METHOD': 'ID', 'SCORING_METHOD_BETA': 1.0, 'VOTE_TH': 0.8}, 'CLASS_SPECIFIC_AR': False, 'COMPETITION_MODE': True, 'DATASETS': ('Lytica_Mini_Ev',), 'DETECTIONS_PER_IM': 100, 'FORCE_JSON_DATASET_EVAL': True, 'GENERATE_PROPOSALS_ON_GPU': False, 'KPS_AUG': {'AREA_TH': 32400, 'ASPECT_RATIOS': (), 'ASPECT_RATIO_H_FLIP': False, 'ENABLED': False, 'HEUR': 'HM_AVG', 'H_FLIP': False, 'MAX_SIZE': 4000, 'SCALES': (), 'SCALE_H_FLIP': False, 'SCALE_SIZE_DEP': False}, 'MASK_AUG': {'AREA_TH': 32400, 'ASPECT_RATIOS': (), 'ASPECT_RATIO_H_FLIP': False, 'ENABLED': False, 'HEUR': 'SOFT_AVG', 'H_FLIP': False, 'MAX_SIZE': 4000, 'SCALES': (), 'SCALE_H_FLIP': False, 'SCALE_SIZE_DEP': False}, 'MAX_SIZE': 2000, 'NMS': 0.5, 'PRECOMPUTED_PROPOSALS': False, 'PROPOSAL_FILES': (), 'PROPOSAL_LIMIT': 2000, 'RPN_MIN_SIZE': 0, 'RPN_NMS_THRESH': 0.7, 'RPN_POST_NMS_TOP_N': 1000, 'RPN_PRE_NMS_TOP_N': 1000, 'SCALE': 1200, 'SCORE_THRESH': 0.1, 'SOFT_NMS': {'ENABLED': False, 'METHOD': 'linear', 'SIGMA': 0.5}, 'WEIGHTS': '/tmp/detectron-output/train/Lytica_Mini_Train/generalized_rcnn/model_final.pkl'}, 'TRAIN': {'ASPECT_GROUPING': True, 'AUTO_RESUME': True, 'BATCH_SIZE_PER_IM': 128, 'BBOX_THRESH': 0.5, 'BG_THRESH_HI': 0.5, 'BG_THRESH_LO': 0.0, 'COPY_WEIGHTS': False, 'CROWD_FILTER_THRESH': 0.7, 'DATASETS': ('Lytica_Mini_Train',), 'FG_FRACTION': 0.25, 'FG_THRESH': 0.5, 'FREEZE_AT': 2, 'FREEZE_CONV_BODY': False, 'GENERATE_PROPOSALS_ON_GPU': False, 'GT_MIN_AREA': -1, 'IMS_PER_BATCH': 1, 'MAX_SIZE': 2000, 'PROPOSAL_FILES': (), 'RPN_BATCH_SIZE_PER_IM': 256, 'RPN_FG_FRACTION': 0.5, 'RPN_MIN_SIZE': 0, 'RPN_NEGATIVE_OVERLAP': 0.3, 'RPN_NMS_THRESH': 0.7, 'RPN_POSITIVE_OVERLAP': 0.7, 'RPN_POST_NMS_TOP_N': 2000, 'RPN_PRE_NMS_TOP_N': 2000, 'RPN_STRADDLE_THRESH': 0, 'SCALES': (1200,), 'SNAPSHOT_ITERS': 4000, 'USE_FLIPPED': True, 'WEIGHTS': 'models/R-50-GN.pkl'}, 'USE_NCCL': False, 'VIS': False, 'VIS_TH': 0.9} loading annotations into memory... Done (t=0.00s) creating index... index created! loading annotations into memory... Done (t=0.00s) creating index... index created! WARNING cnn.py: 25: [====DEPRECATE WARNING====]: you are creating an object from CNNModelHelper class which will be deprecated soon. Please use ModelHelper object with brew module. For more information, please refer to caffe2.ai and python/brew.py, python/brew_test.py for more information. INFO net.py: 60: Loading weights from: /tmp/detectron-output/train/Lytica_Mini_Train/generalized_rcnn/model_final.pkl Traceback (most recent call last): File "tools/test_net.py", line 116, in check_expected_results=True, File "/tmp/detectron/detectron/core/test_engine.py", line 127, in run_inference all_results = result_getter() File "/tmp/detectron/detectron/core/test_engine.py", line 107, in result_getter multi_gpu=multi_gpu_testing File "/tmp/detectron/detectron/core/test_engine.py", line 158, in test_net_on_dataset weights_file, dataset_name, proposal_file, output_dir, gpu_id=gpu_id File "/tmp/detectron/detectron/core/test_engine.py", line 234, in test_net model = initialize_model_from_cfg(weights_file, gpu_id=gpu_id) File "/tmp/detectron/detectron/core/test_engine.py", line 329, in initialize_model_from_cfg model, weights_file, gpu_id=gpu_id, File "/tmp/detectron/detectron/utils/net.py", line 65, in initialize_gpu_from_weights_file saved_cfg = load_cfg(src_blobs['cfg']) File "/tmp/detectron/detectron/core/config.py", line 1145, in load_cfg return envu.yaml.safe_load(cfg_to_load) File "/home/msi/.local/lib/python3.5/site-packages/yaml/init.py", line 94, in safe_load return load(stream, SafeLoader) File "/home/msi/.local/lib/python3.5/site-packages/yaml/init.py", line 72, in load return loader.get_single_data() File "/home/msi/.local/lib/python3.5/site-packages/yaml/constructor.py", line 37, in get_single_data return self.construct_document(node) File "/home/msi/.local/lib/python3.5/site-packages/yaml/constructor.py", line 41, in construct_document data = self.construct_object(node) File "/home/msi/.local/lib/python3.5/site-packages/yaml/constructor.py", line 86, in construct_object data = constructor(self, node) File "/home/msi/.local/lib/python3.5/site-packages/yaml/constructor.py", line 414, in construct_undefined node.start_mark) yaml.constructor.ConstructorError: could not determine a constructor for the tag 'tag:yaml.org,2002:python/object/new:detectron.utils.collections.AttrDict' in "", line 1, column 1: !!python/object/new:detectron.ut ...

harshsp31 commented 3 years ago

How did you solve this issue? @yakupakkaya

yakupakkaya commented 3 years ago

I added safe expression to yaml_loader (I don't remember exactly where) before changing the YAML version to 3.12. Changing it back solved my issue. It has been a long time though, might not remember the details.