A mobile app that analyzes user golf swings and provides advice on how to improve their swing, as well as some shot metrics to help them track their progress.
Built using Flutter. Can be loaded onto an Android or iOS device following Flutter documentation.
Built using Python and TensorFlow MoveNet for pose estimation, OpenCV for golf ball tracking, and Flask for server capabilities.
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├── archive # Old code that might be useful at some point.
├── assets # Sample images/videos used to test the system.
├── data_extraction # Module providing functionality to extract data out of video/images (i.e. golf ball coordinates, player positioning).
├── metrics # Module responsible for swing metric calculations and feedback generation.
├── static # Used by application.
└── tests # Unit tests.
- Have Python 3.8 or 3.9 installed.
- Install poetry: https://python-poetry.org/docs/
- Create a virtual environment:
virtualenv env/ - Activate the virtual environment:
source env/bin/activate(on Linux) or.\env\Scripts\activate(on Windows) - Install dependencies:
poetry install - Run the server:
flask run --host=0.0.0.0 --port=5000