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

Testing
Training

Require

Pytorch
Caffe 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 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.
CVPR'17, Realtime Multi-Person Pose Estimation.

Network Architecture

testing architecture
training architecture

Citation

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

@InProceedings{cao2017realtime,
  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}
  }

JDwangmo/pytorch_Realtime_Multi-Person_Pose_Estimation