mmaction2

算法启动

We provide a demo script to predict the skeleton-based action recognition result using a single video.

点击查看代码

python demo/demo_skeleton.py ${VIDEO_FILE} ${OUT_FILENAME} \
    [--config ${SKELETON_BASED_ACTION_RECOGNITION_CONFIG_FILE}] \
    [--checkpoint ${SKELETON_BASED_ACTION_RECOGNITION_CHECKPOINT}] \
    [--det-config ${HUMAN_DETECTION_CONFIG_FILE}] \
    [--det-checkpoint ${HUMAN_DETECTION_CHECKPOINT}] \
    [--det-score-thr ${HUMAN_DETECTION_SCORE_THRESHOLD}] \
    [--pose-config ${HUMAN_POSE_ESTIMATION_CONFIG_FILE}] \
    [--pose-checkpoint ${HUMAN_POSE_ESTIMATION_CHECKPOINT}] \
    [--label-map ${LABEL_MAP}] \
    [--device ${DEVICE}] \
    [--short-side] ${SHORT_SIDE}

点击查看代码

python demo/app.py demo/ntu_sample.avi demo/skeleton_demo.mp4 \
    --config configs/skeleton/posec3d/slowonly_r50_u48_240e_ntu120_xsub_keypoint.py \
    --checkpoint https://download.openmmlab.com/mmaction/skeleton/posec3d/slowonly_r50_u48_240e_ntu120_xsub_keypoint/slowonly_r50_u48_240e_ntu120_xsub_keypoint-6736b03f.pth \
    --det-config demo/faster_rcnn_r50_fpn_2x_coco.py \
    --det-checkpoint http://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r50_fpn_2x_coco/faster_rcnn_r50_fpn_2x_coco_bbox_mAP-0.384_20200504_210434-a5d8aa15.pth \
    --det-score-thr 0.9 \
    --pose-config demo/hrnet_w32_coco_256x192.py \
    --pose-checkpoint https://download.openmmlab.com/mmpose/top_down/hrnet/hrnet_w32_coco_256x192-c78dce93_20200708.pth \
    --label-map tools/data/skeleton/label_map_ntu120.txt