Our movement estimation interface allows users to perform classifications on human body movement data using a standard desktop webcamera.
Python, JavaScript, C++, Arduino & Arduino Cam, and OpenCV
Before you begin, ensure you have met the following requirements:
To contribute to <project_name>, follow these steps:
- Fork this repository.
- Create a branch:
git checkout -b <branch_name>. - Make your changes and commit them:
git commit -m '<commit_message>' - Push to the original branch:
git push origin <project_name>/<location> - Create the pull request.
Alternatively see the GitHub documentation on creating a pull request.
Thanks to the following people who have contributed to this project:
If you wish to contact us you can reach us at tasha_kim@brown.edu and jatrindo@gmail.com.
This project uses the following license: <license_name>.
07/01: Use Posenet to output array of body-part coordinates.
07/02: Confirmed method of logging Posenet data to a csv file, + time coordinates.
07/03: Made organization repository and made two separate forks on our own GitHub accounts.
07/04: Finished JavaScript script that extracts relevant data from web browser running Posenet.
07/06: Completed data pipeline using R. Plotted some movement data.
07/07: Updated the p5 web editor script, runs in browser. Next goal: Algos.
07/12~: Performing EDA on pose_class_data.