OpenPose
1.0.0rc2
OpenPose: A Real-Time Multi-Person Key-Point Detection And Multi-Threading C++ Library
|
**Linux ** |
---|
![Build Status](https://travis-ci.org/CMU-Perceptual-Computing-Lab/openpose.svg?branch=master) |
OpenPose represents the first real-time multi-person system to jointly detect human body, hand, and facial keypoints (in total 130 keypoints) on single images.
<img src="doc/media/pose_face_hands.gif", width="480">
Functionality:
<img src="doc/media/dance.gif", width="360">
<img src="doc/media/pose_face.gif", width="360">
<img src="doc/media/pose_hands.gif", width="360">
See doc/installation.md for instructions on how to build from source or how to download our portable binaries.
Most users do not need the OpenPose C++ API, but they can simply use the basic Demo and/or OpenPose Wrapper.
./build/examples/openpose/openpose.bin –video examples/media/video.avi :: Windows - Portable Demo bin\OpenPoseDemo.exe –video examples\media\video.avi ```
Wrapper
tutorial on examples/tutorial_wrapper/. You can create your custom code on examples/user_code/ and quickly compile it by using make all
in the OpenPose folder (assuming Makefile installer).Output (format, keypoint index ordering, etc.) in doc/output.md.
Check the OpenPose Benchmark and some hints to speed up OpenPose on doc/installation.md#faq.
Our library is open source for research purposes, and we want to continuously improve it! So please, let us know if...
Just comment on GitHub or make a pull request and we will answer as soon as possible! Send us an email if you use the library to make a cool demo or YouTube video!
OpenPose is authored by Gines Hidalgo, Zhe Cao, Tomas Simon, Shih-En Wei, Hanbyul Joo, and Yaser Sheikh. Currently, it is being maintained by Gines Hidalgo, Bikramjot Hanzra, and Yaadhav Raaj. The original CVPR 2017 repo includes Matlab and Python versions, as well as the training code. The body pose estimation work is based on the original ECCV 2016 demo.
In addition, OpenPose would not be possible without the CMU Panoptic Studio dataset.
We would also like to thank all the people who helped OpenPose in any way. The main contributors are listed in doc/contributors.md.
Please cite these papers in your publications if it helps your research (the face keypoint detector was trained using the same procedure described in [Simon et al. 2017]):
@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} }
OpenPose is freely available for free non-commercial use, and may be redistributed under these conditions. Please, see the [license](LICENSE) for further details. Interested in a commercial license? Check this link. For commercial queries, contact Yaser Sheikh.