TraBasT-SportTech

TraBasT (Tracked Basketball Training) is a university project of the Sport-Tech course in University of Trento.

The concept behind this project is to use motion capture to track basketball players movement during a free throw. The final goal is to help amateur players learn and improve their free throws by comparing their free throw motions against a gold standard and giving them performance-based feedback.

Data

We have already included some data in the code/Data folder. If you want to add your own data for analysis, place it in the Data folder. Make sure it is in CSV format and organized in the same way as the files already in the folder.

Starting the Project

Getting started with this project is very straightforward:

1. (Optional) Use a virtual environment to manage dependencies. To create and activate a virtual environment on Windows, run:

   • Create the virtual environment (you can personalize the environment name, e.g., my_env):

     python -m venv name_env  # You can personalize the environment name

   • Activate the virtual environment:

     .\name_env\Scripts\activate

   For Linux or macOS, refer to the official guide for installing and using virtual environments.

   Alternatively, you can install the dependencies directly on your system.

2. Install the required libraries specified in requirements.txt by running the following command:

   pip install -r requirements.txt

3. Navigate to the code/main.py file and run it:

   python main.py

After running main.py, an interactive menu will appear. The menu is very user-friendly and will guide you through the next steps. You can choose to:

• Track the movement of a single player.
• Compare the free throws of two players. In this case, the second player/file selected will be treated as the gold standard, while the first will be the player you want to evaluate.

After selecting the two-player option, you will receive an evaluation of the player.

Then, you will be asked if you want to save the video that will be displayed. You can change the frames per second (FPS) of the saved video by modifying the FPS variable at the top of the plotter.py file.

Finally, the video will be displayed.

Additional Notes

• Ensure that Python is installed on your system (recommended version: >=3.8).
• If you encounter issues with the packages or running the code, verify that all dependencies listed in requirements.txt have been correctly installed.

Report

The report (a brief explanation of the project and its conceptualization) can be read here