def METHOD_NAME():
    """Visualize the demo images.
    Using mmdet to detect the human.
    """
    parser = ArgumentParser()
    parser.add_argument('det_config', help='Config file for detection')
    parser.add_argument('det_checkpoint', help='Checkpoint file for detection')
    parser.add_argument('pose_config', help='Config file for pose')
    parser.add_argument('pose_checkpoint', help='Checkpoint file for pose')
    parser.add_argument('--input', type=str, help='input Image file')
    parser.add_argument(
        '--device', default='cuda:0', help='Device used for inference')
    parser.add_argument(
        '--det-cat-id',
        type=int,
        default=0,
        help='Category id for bounding box detection model')
    parser.add_argument(
        '--bbox-thr',
        type=float,
        default=0.4,
        help='Bounding box score threshold')
    parser.add_argument(
        '--nms-thr',
        type=float,
        default=0.3,
        help='IoU threshold for bounding box NMS')
    parser.add_argument(
        '--kpt-thr', type=float, default=0.4, help='Keypoint score threshold')
    assert has_mmdet, 'Please install mmdet to run the demo.'
    args = parser.parse_args()
    assert args.input != ''
    assert args.det_config is not None
    assert args.det_checkpoint is not None
    # build detector
    detector = init_detector(
        args.det_config, args.det_checkpoint, device=args.device)
    # build pose estimator
    pose_estimator = init_pose_estimator(
        args.pose_config,
        args.pose_checkpoint,
        device=args.device,
        cfg_options=dict(model=dict(test_cfg=dict(output_heatmaps=False))))
    input_type = mimetypes.guess_type(args.input)[0].split('/')[0]
    if input_type == 'image':
        mmpose_to_openpose_visualization(args, args.input, detector,
                                         pose_estimator)