https://github.com/minar09/openpose-pytorch
openpose implementation in pytorch
https://github.com/minar09/openpose-pytorch
body estimation openpose pose pose-estimation pose-keypoints pytorch
Last synced: about 1 year ago
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openpose implementation in pytorch
- Host: GitHub
- URL: https://github.com/minar09/openpose-pytorch
- Owner: minar09
- Created: 2020-03-27T04:33:06.000Z (about 6 years ago)
- Default Branch: master
- Last Pushed: 2022-10-16T05:47:54.000Z (over 3 years ago)
- Last Synced: 2025-03-25T06:51:15.331Z (over 1 year ago)
- Topics: body, estimation, openpose, pose, pose-estimation, pose-keypoints, pytorch
- Language: Jupyter Notebook
- Homepage: https://github.com/Hzzone/pytorch-openpose
- Size: 2.88 MB
- Stars: 6
- Watchers: 2
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
## Disclaimer
This is a slightly modified version [pytorch-openpose](https://github.com/Hzzone/pytorch-openpose) github repository. Modifications are:
#### 1) demo_body.py:
pose estimation of human body only, and saving them into .json files.
## 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.
### Model Download
* [dropbox](https://www.dropbox.com/sh/7xbup2qsn7vvjxo/AABWFksdlgOMXR_r5v3RwKRYa?dl=0)
`*.pth` files are pytorch model, you could also download caffemodel file if you want to use caffe as backend.
### 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
### 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 and Takeo Kanade and Yaser Sheikh},
booktitle = {CVPR},
title = {Convolutional pose machines},
year = {2016}
}
```