GymTracker is a web-based application, developed as part of a university project, that uses pre-trained TensorFlow.js pose detection models to track your movements and help optimize your workouts.
During the development and testing phase, prototype force plates were also integrated to monitor force distribution during selected exercises. However, the application is fully functional without the use of force plates.
Developed by: Marcus Gustafsson, Stephanie Källberg, Saad Ezeldin, Nnamdi Ronald Onuigbo, and Rami Jbara.
Before you start, make sure the following software is installed on your computer:
To check if you already have these installed, run the following commands in your Terminal/Command Prompt:
node -v
yarn -v
python -VInstallation Follow these steps to set up and run the GymTracker application locally:
git clone https://github.com/your-username/GymTracker.git
cd GymTracker/GymTracker_app/Applicationrm -rf .cache dist node_modulesyarn build-depyarnyarn watchThe application will be running at http://localhost:1234/?model=movenet.
macOS If you encounter issues during installation, try removing the following files from the Application folder:
rm yarn.lock package-lock.json node_modulesFor Windows or Linux users, you may need to install Visual Studio with the "Desktop development with C++" workload enabled. You can follow the instructions here: https://learn.microsoft.com/en-us/cpp/build/vscpp-step-0-installation?view=msvc-170
All credits for resources used in this project go to their original creators. This project is for educational and portfolio purposes only, and will not be used for commercial purposes.
If you are the author of any of the used assets and would like them removed or credited differently, please contact me.