Traccc

A tool to track sports balls, and add interesting visual effects. It's very fun to apply to juggling 🤹 and sports 🏐🏀 videos .

Running this project is fairly demanding. A GPU is very helpful for running the neural networks for ball detection quickly, but it isn't required. At minimum: 10GB disk space.

🔥 Application Quickstart 🔥

For Windows users, see the Windows Installation Guide. For MacOS users, see the MacOS Installation Guide.

After installation, you can refer to the User Guide for an overview of all the software has to offer.

🖥️ The CLI pipeline 🖥️

This project also features a full command line interface (CLI). This can be used inside the running docker container. Before starting the pipeline, determine a name for your project. For the following examples, I'll be using yellowball

1. Detect all the sports balls in the video, frame by frame

py3 detect.py yellowball 

2. Track the sports balls through sequential frames, using the detections

py3 track.py yellowball 

3. Visualize the motion of the balls, using the tracks

py3 draw.py yellowball --effect red_dot

All of the above commands will have multiple options. You can see what the options do using the -h (help) option, such as:

py3 detect.py -h

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📝 Contributing 📝

Contributions are welcome! Open an issue or a pull request, and I'll get to it when I can. Adding new effects is an easy contribution to make.

TODO

• Custom train a NN for sports balls only.
• Video "upload" and download in the GUI.