mittalsaurab/real-time-yoga

Code repo for Real-time Yoga recognition using deep learning, NCAA, Springer, 2019

Yoga Recognition

Code repo for Real-time Yoga recognition using deep learning, NCAA, Springer, 2019

Paper:

https://link.springer.com/article/10.1007/s00521-019-04232-7

Weights and converted training files:

https://drive.google.com/drive/folders/1rxPzNUl585lmWYeKMpEhIbz6Gx8liHx5?usp=sharing

Video files used to train the model:

https://archive.org/details/YogaVidCollected

Sample videos of real time operation

https://drive.google.com/drive/folders/1Xc0h5e6ntYcYL13JCwfHP1PuwtrBKbpM

To run it on your system-

1. Install and setup openpose https://github.com/CMU-Perceptual-Computing-Lab/openpose
2. Run the open pose on webcam mode and direct the results to \output
3. Run prediction and write output to file python predictSeq.py > export.txt or Run prediction and show output on terminal python predictSeq.py

Feel free to adjust predictSeq.py input folder and the weights. Contact me for any issues not resolved by adjusting file paths.

You can also use the video files in your project.

Please cite as:

Yadav, S. K., Singh, A., Gupta, A., & Raheja, J. L. (2019). Real-time Yoga recognition using deep learning. Neural Computing and Applications, 31(12), 9349-9361.

Bibtex

@article{yadav2019real, title={Real-time Yoga recognition using deep learning}, author={Yadav, Santosh Kumar and Singh, Amitojdeep and Gupta, Abhishek and Raheja, Jagdish Lal}, journal={Neural Computing and Applications}, volume={31}, number={12}, pages={9349--9361}, year={2019}, publisher={Springer} }