README.md~

# pytorch_Realtime_Multi-Person_Pose_Estimation
This is a pytorch version of Realtime_Multi-Person_Pose_Estimation, origin code is here https://github.com/ZheC/Realtime_Multi-Person_Pose_Estimation 

## Introduction
Code repo for reproducing 2017 CVPR Oral paper using pytorch.  

## Results

<p align="left">
<img src="https://github.com/tensorboy/pytorch_Realtime_Multi-Person_Pose_Estimation/blob/master/readme/result1.gif", width="720">
</p>

<p align="left">
<img src="https://github.com/tensorboy/pytorch_Realtime_Multi-Person_Pose_Estimation/blob/master/readme/result2.gif", width="720">
</p>

## Contents
1. [Testing](#testing)
2. [Training](#training)

## Require
1. [Pytorch](http://pytorch.org/)
2. [Caffe](http://caffe.berkeleyvision.org/) is required if you want convert caffe model to a pytorch model.

## Testing
- `cd model; sh get_model.sh` to download caffe model or download converted pytorch model(https://www.dropbox.com/s/ae071mfm2qoyc8v/pose_model.pth?dl=0).
- `cd caffe_to_pytorch; python convert.py` to convert a trained caffe model to pytorch model. The converted model have relative error less than 1e-6, and will be located in `./model` after convert.
- `python picture_demo.py` to run the picture demo.
- `python web_demo.py` to run the web demo.

## Training
- `cd training; bash getData.sh` to obtain the COCO images in `dataset/COCO/images/`, keypoints annotations in `dataset/COCO/annotations/` and [COCO official toolbox](https://github.com/pdollar/coco) in `dataset/COCO/coco/ . 
- `cd training/dataset/COCO/coco/PythonAPI; sudo python setup.py install` to install pycocotools . 


## Related repository
- CVPR'16, [Convolutional Pose Machines](https://github.com/shihenw/convolutional-pose-machines-release).
- CVPR'17, [Realtime Multi-Person Pose Estimation](https://github.com/ZheC/Realtime_Multi-Person_Pose_Estimation).

### Network Architecture
- testing architecture
![Teaser?](https://github.com/tensorboy/pytorch_Realtime_Multi-Person_Pose_Estimation/blob/master/readme/pose.png)

- training architecture
![Teaser?](https://github.com/tensorboy/pytorch_Realtime_Multi-Person_Pose_Estimation/blob/master/readme/training_structure.png)

## Citation
Please cite the paper in your publications if it helps your research:    

    @InProceedings{cao2016realtime,
      title = {Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields},
      author = {Zhe Cao and Tomas Simon and Shih-En Wei and Yaser Sheikh},
      booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
      year = {2017}
      }