mmpose-0.29.0/demo/bottom_up_video_demo.py

# Copyright (c) OpenMMLab. All rights reserved.
import os
import warnings
from argparse import ArgumentParser

import cv2
import mmcv

from mmpose.apis import (inference_bottom_up_pose_model, init_pose_model,
 vis_pose_result)
from mmpose.datasets import DatasetInfo


def main():
 """Visualize the demo images."""
 parser = ArgumentParser()
 parser.add_argument('pose_config', help='Config file for pose')
 parser.add_argument('pose_checkpoint', help='Checkpoint file for pose')
 parser.add_argument('--video-path', type=str, help='Video path')
 parser.add_argument(
 '--show',
 action='store_true',
 default=False,
 help='whether to show visualizations.')
 parser.add_argument(
 '--out-video-root',
 default='',
 help='Root of the output video file. '
 'Default not saving the visualization video.')
 parser.add_argument(
 '--device', default='cuda:0', help='Device used for inference')
 parser.add_argument(
 '--kpt-thr', type=float, default=0.3, help='Keypoint score threshold')
 parser.add_argument(
 '--pose-nms-thr',
 type=float,
 default=0.9,
 help='OKS threshold for pose NMS')
 parser.add_argument(
 '--radius',
 type=int,
 default=4,
 help='Keypoint radius for visualization')
 parser.add_argument(
 '--thickness',
 type=int,
 default=1,
 help='Link thickness for visualization')

 args = parser.parse_args()

 assert args.show or (args.out_video_root != '')

 # build the pose model from a config file and a checkpoint file
 pose_model = init_pose_model(
 args.pose_config, args.pose_checkpoint, device=args.device.lower())

 dataset = pose_model.cfg.data['test']['type']
 dataset_info = pose_model.cfg.data['test'].get('dataset_info', None)
 if dataset_info is None:
 warnings.warn(
 'Please set `dataset_info` in the config.'
 'Check https://github.com/open-mmlab/mmpose/pull/663 for details.',
 DeprecationWarning)
 assert (dataset == 'BottomUpCocoDataset')
 else:
 dataset_info = DatasetInfo(dataset_info)

 # read video
 video = mmcv.VideoReader(args.video_path)
 assert video.opened, f'Faild to load video file {args.video_path}'

 if args.out_video_root == '':
 save_out_video = False
 else:
 os.makedirs(args.out_video_root, exist_ok=True)
 save_out_video = True

 if save_out_video:
 fps = video.fps
 size = (video.width, video.height)
 fourcc = cv2.VideoWriter_fourcc(*'mp4v')
 videoWriter = cv2.VideoWriter(
 os.path.join(args.out_video_root,
 f'vis_{os.path.basename(args.video_path)}'), fourcc,
 fps, size)

 # optional
 return_heatmap = False

 # e.g. use ('backbone', ) to return backbone feature
 output_layer_names = None

 print('Running inference...')
 for _, cur_frame in enumerate(mmcv.track_iter_progress(video)):
 pose_results, _ = inference_bottom_up_pose_model(
 pose_model,
 cur_frame,
 dataset=dataset,
 dataset_info=dataset_info,
 pose_nms_thr=args.pose_nms_thr,
 return_heatmap=return_heatmap,
 outputs=output_layer_names)

 # show the results
 vis_frame = vis_pose_result(
 pose_model,
 cur_frame,
 pose_results,
 radius=args.radius,
 thickness=args.thickness,
 dataset=dataset,
 dataset_info=dataset_info,
 kpt_score_thr=args.kpt_thr,
 show=False)

 if args.show:
 cv2.imshow('Image', vis_frame)

 if save_out_video:
 videoWriter.write(vis_frame)

 if args.show and cv2.waitKey(1) & 0xFF == ord('q'):
 break

 if save_out_video:
 videoWriter.release()
 if args.show:
 cv2.destroyAllWindows()


if __name__ == '__main__':
 main()