Video to 3DPose and Bvh motion file
This project integrates some project working, example as VideoPose3D,video-to-pose3D , video2bvh, AlphaPose, Higher-HRNet-Human-Pose-Estimation,openpose, thanks for the mentioned above project.
The project extracted the 2d joint key point from the video by using AlphaPose,HRNet and so on. Then transform the 2d point to the 3D joint point by using VideoPose3D. Finally We convert the 3d joint point to the bvh motion file.
Environment
- Windows 10
- Anaconda
- Python > 3.6
Dependencies
You can refer to the project dependencies of video-to-pose3D for setting.
This is the dependencies of the project of video-to-pose3D, and modifyed by me to solve some bug.
- Packages
- Pytorch > 1.1.0 (I use the Pytorch1.1.0 - GPU)
- torchsample
- ffmpeg (note:you must copy the ffmpeg.exe to the directory of python install)
- tqdm
- pillow
- scipy
- pandas
- h5py
- visdom
- nibabel
- opencv-python (install with pip)
- matplotlib
- 2D Joint detectors
- Alphapose (Recommended)
- Download duc_se.pth from (Google Drive | Baidu pan),
place to
./joints_detectors/Alphapose/models/sppe - Download yolov3-spp.weights from (Google Drive | Baidu pan),
place to
./joints_detectors/Alphapose/models/yolo
- Download duc_se.pth from (Google Drive | Baidu pan),
place to
- HR-Net (Bad 3d joints performance in my testing environment)
- Download pose_hrnet* from Google Drive,
place to
./joints_detectors/hrnet/models/pytorch/pose_coco/ - Download yolov3.weights from here,
place to
./joints_detectors/hrnet/lib/detector/yolo
- Download pose_hrnet* from Google Drive,
place to
- Alphapose (Recommended)
- 3D Joint detectors
- Download pretrained_h36m_detectron_coco.bin from here,
place it into
./checkpointfolder - 2D Pose trackers (Optional)
- PoseFlow (Recommended)
No extra dependences
- LightTrack (Bad 2d tracking performance in my testing environment)
- See original README, and perform same get started step on
./pose_trackers/lighttrack
How to Use it
Please place your video to the .\outputs\inputvideo, and setting the path to the videopose.py, like this
inference_video('outputs/inputvideo/kunkun_cut.mp4', 'alpha_pose')
Waiting some minute, you can see the output video in the \outputs\outputvideo directory,and the bvh file in the \outputs\outputvideo\alpha_pose_kunkun_cut\bvh directory.