Tennis analysis using deep learning and machine learning.
You can check this blog post https://medium.com/@kosolapov.aetp/tennis-analysis-using-deep-learning-and-machine-learning-a5a74db7e2ee for more details

TrackNet was used for detecting tennis ball during the game. For more information you can check this repository: https://github.com/yastrebksv/TrackNet. There you can find pretrained weights to check the model.

CatBoostRegressor was used to predict ball's bounces during the game based on ball trajectory detected in the previous step. You can check this pretrained model: https://drive.google.com/file/d/1Eo5HDnAQE8y_FbOftKZ8pjiojwuy2BmJ/view?usp=drive_link

It was used neural network for detection 14 points of tennis court. For more information you can check this repository: https://github.com/yastrebksv/TennisCourtDetector. There you can find pretrained weights to check the model.

Prepare a video file with resolution 1280x720

1. Clone the repository https://github.com/yastrebksv/TennisProject.git
2. Run pip install -r requirements.txt to install packages required
3. Run python main.py <args>