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pytorch implementation of openpose including Hand and Body Pose Estimation.
| Date | Stars |
|---|---|
| 2026-07-24 | 2318 |
| 2026-07-25 | 2318 |
| 2026-07-28 | 2318 |
| 2026-07-30 | 2318 |
| 2026-08-06 | 2318 |
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## pytorch-openpose
pytorch implementation of [openpose](https://github.com/CMU-Perceptual-Computing-Lab/openpose) including **Body and Hand Pose Estimation**, and the pytorch model is directly converted from [openpose](https://github.com/CMU-Perceptual-Computing-Lab/openpose) caffemodel by [caffemodel2pytorch](https://github.com/vadimkantorov/caffemodel2pytorch). You could implement face keypoint detection in the same way if you are interested in. Pay attention to that the face keypoint detector was trained using the procedure described in [Simon et al. 2017] for hands.
openpose detects hand by the result of body pose estimation, please refer to the code of [handDetector.cpp](https://github.com/CMU-Perceptual-Computing-Lab/openpose/blob/master/src/openpose/hand/handDetector.cpp).
In the paper, it states as:
```
This is an important detail: to use the keypoint detector in any practical situation,
we need a way to generate this bounding box.
We directly use the body pose estimation models from [29] and [4],
and use the wrist and elbow position to approximate the hand location,
assuming the hand extends 0.15 times the length of the forearm in the same direction.
```
If anybody wants a pure python wrapper, please refer to my [pytorch implementation](https://github.com/Hzzone/pytorch-openpose) of openpose, maybe it helps you to implement a standalone hand keypoint detector.
Don't be mean to star this repo if it helps your research.
### Getting Started
#### Install Requriements
Create a python 3.7 environement, eg:
conda create -n pytorch-openpose python=3.7
conda activate pytorch-openpose
Install pytorch by following the quick start guide here (use pip) https://download.pytorch.org/whl/torch_stable.html
Install other requirements with pip
pip install -r requirements.txt
#### Download the Models
* [dropbox](https://www.dropbox.com/sh/7xbup2qsn7vvjxo/AABWFksdlgOMXR_r5v3RwKRYa?dl=0)
* [baiduyun](https://pan.baidu.com/s/1IlkvuSi0ocNckwbnUe7j-g)
* [google drive](https://drive.google.com/drive/folders/1JsvI4M4ZTg98fmnCZLFM-3TeovnCRElG?usp=sharing)
`*.pth` files are pytorch model, you could also download caffemodel file if you want to use caffe as backend.
Download the pytorch models and put them in a directory named `model` in the project root directory
#### Run the Demo
Run:
python demo_camera.py
to run a demo with a feed from your webcam or run
python demo.py
to use a image from the images folder or run
python demo_video.py <video-file>
to process a video file (requires [ffmpeg-python][ffmpeg]).
[ffmpeg]: https://pypi.org/project/ffmpeg-python/
### Todo list
- [x] convert caffemodel to pytorch.
- [x] Body Pose Estimation.
- [x] Hand Pose Estimation.
- [ ] Performance test.
- [ ] Speed up.
### Demo
#### Skeleton
#### Body Pose Estimation
#### Hand Pose Estimation
#### Body + Hand
#### Video Body
Attribution: [this video](https://www.youtube.com/watch?v=kc-e129SBb4).
#### Video Hand
Attribution: [this video](https://www.youtube.com/watch?v=yOAmYSW3WyU).
### Citation
Please cite these papers in your publications if it helps your research (the face keypoint detector was trained using the procedure described in [Simon et al. 2017] for hands):
```
@inproceedings{cao2017realtime,
author = {Zhe Cao and Tomas Simon and Shih-En Wei and Yaser Sheikh},
booktitle = {CVPR},
title = {Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields},
year = {2017}
}
@inproceedings{simon2017hand,
author = {Tomas Simon and Hanbyul Joo and Iain Matthews and Yaser Sheikh},
booktitle = {CVPR},
title = {Hand Keypoint Detection in Single Images using Multiview Bootstrapping},
year = {2017}
}
@inproceedings{wei2016cpm,
author = {Shih-En Wei and Varun Ramakrishna andExcerpt of 4,118 characters
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Gavia Gray · Cerebras Systems · Canada
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:ab165e8f7d11b8ba, topic:pose-estimation, desc:pose estimation, readme:pose estimation
matched fp:ab165e8f7d11b8ba, topic:pytorch