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'),
    ])