pytorch-openpose

Warning: This implementation is customized to support training, and some behaviors are different from the original pytorch-openpose.

The PyTorch models are converted from official OpenPose caffemodels by caffemodel2pytorch.

Getting Started

Install Requriements

Create a python 3.7 environement, e.g.:

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
• baiduyun
• google drive

*.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

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{wei2016cpm,
  author = {Shih-En Wei and Varun Ramakrishna and Takeo Kanade and Yaser Sheikh},
  booktitle = {CVPR},
  title = {Convolutional pose machines},
  year = {2016}
}