| backend_args = dict(backend='local') | |
| codec = dict( | |
| heatmap_size=( | |
| 72, | |
| 96, | |
| ), | |
| input_size=( | |
| 288, | |
| 384, | |
| ), | |
| sigma=3, | |
| type='MSRAHeatmap', | |
| unbiased=True) | |
| data_mode = 'topdown' | |
| dataset_type = 'CocoDataset' | |
| default_scope = 'mmpose' | |
| model = dict( | |
| backbone=dict( | |
| extra=dict( | |
| stage1=dict( | |
| block='BOTTLENECK', | |
| num_blocks=(4, ), | |
| num_branches=1, | |
| num_channels=(64, ), | |
| num_modules=1), | |
| stage2=dict( | |
| block='BASIC', | |
| num_blocks=( | |
| 4, | |
| 4, | |
| ), | |
| num_branches=2, | |
| num_channels=( | |
| 48, | |
| 96, | |
| ), | |
| num_modules=1), | |
| stage3=dict( | |
| block='BASIC', | |
| num_blocks=( | |
| 4, | |
| 4, | |
| 4, | |
| ), | |
| num_branches=3, | |
| num_channels=( | |
| 48, | |
| 96, | |
| 192, | |
| ), | |
| num_modules=4), | |
| stage4=dict( | |
| block='BASIC', | |
| num_blocks=( | |
| 4, | |
| 4, | |
| 4, | |
| 4, | |
| ), | |
| num_branches=4, | |
| num_channels=( | |
| 48, | |
| 96, | |
| 192, | |
| 384, | |
| ), | |
| num_modules=3)), | |
| in_channels=3, | |
| init_cfg=dict( | |
| checkpoint= | |
| '/scratch/users/yonigoz/mmpose_data/ckpts/hrnet/td-hm_hrnet-w48_dark-8xb32-210e_coco-384x288-39c3c381_20220916.pth', | |
| prefix='backbone', | |
| type='Pretrained'), | |
| type='HRNet'), | |
| data_preprocessor=dict( | |
| bgr_to_rgb=True, | |
| mean=[ | |
| 123.675, | |
| 116.28, | |
| 103.53, | |
| ], | |
| std=[ | |
| 58.395, | |
| 57.12, | |
| 57.375, | |
| ], | |
| type='PoseDataPreprocessor'), | |
| head=dict( | |
| decoder=dict( | |
| heatmap_size=( | |
| 72, | |
| 96, | |
| ), | |
| input_size=( | |
| 288, | |
| 384, | |
| ), | |
| sigma=3, | |
| type='MSRAHeatmap', | |
| unbiased=True), | |
| deconv_out_channels=None, | |
| in_channels=48, | |
| loss=dict(type='KeypointMSELoss', use_target_weight=True), | |
| out_channels=52, | |
| type='HeatmapHead'), | |
| test_cfg=dict(flip_mode='heatmap', flip_test=True, shift_heatmap=True), | |
| type='TopdownPoseEstimator') | |
| test_dataloader = dict( | |
| batch_size=32, | |
| dataset=dict( | |
| data_mode='topdown', | |
| data_prefix=dict(img=''), | |
| data_root='', | |
| pipeline=[ | |
| dict(type='LoadImage'), | |
| dict(type='GetBBoxCenterScale'), | |
| dict(input_size=( | |
| 288, | |
| 384, | |
| ), type='TopdownAffine'), | |
| dict(type='PackPoseInputs'), | |
| ], | |
| test_mode=True, | |
| type='CocoDataset', | |
| used_data_keys=[ | |
| 'nose', | |
| 'left_eye', | |
| 'right_eye', | |
| 'left_ear', | |
| 'right_ear', | |
| 'left_shoulder', | |
| 'right_shoulder', | |
| 'left_elbow', | |
| 'right_elbow', | |
| 'left_wrist', | |
| 'right_wrist', | |
| 'left_hip', | |
| 'right_hip', | |
| 'left_knee', | |
| 'right_knee', | |
| 'left_ankle', | |
| 'right_ankle', | |
| 'sternum', | |
| 'rshoulder', | |
| 'lshoulder', | |
| 'r_lelbow', | |
| 'l_lelbow', | |
| 'r_melbow', | |
| 'l_melbow', | |
| 'r_lwrist', | |
| 'l_lwrist', | |
| 'r_mwrist', | |
| 'l_mwrist', | |
| 'r_ASIS', | |
| 'l_ASIS', | |
| 'r_PSIS', | |
| 'l_PSIS', | |
| 'r_knee', | |
| 'l_knee', | |
| 'r_mknee', | |
| 'l_mknee', | |
| 'r_ankle', | |
| 'l_ankle', | |
| 'r_mankle', | |
| 'l_mankle', | |
| 'r_5meta', | |
| 'l_5meta', | |
| 'r_toe', | |
| 'l_toe', | |
| 'r_big_toe', | |
| 'l_big_toe', | |
| 'l_calc', | |
| 'r_calc', | |
| 'C7', | |
| 'L2', | |
| 'T11', | |
| 'T6', | |
| ]), | |
| drop_last=False, | |
| num_workers=4, | |
| persistent_workers=True, | |
| sampler=dict(round_up=False, shuffle=False, type='DefaultSampler')) | |
| visualizer = dict( | |
| name='visualizer', | |
| type='PoseLocalVisualizer', | |
| vis_backends=[ | |
| dict(type='LocalVisBackend'), | |
| ]) | |