AI-basketball-analysis VS dupver

Source code: https://github.com/chonyy/AI-basketball-analysis

I built an app to visualize and analyze basketball shots and shooting pose with machine learning.

https://github.com/chonyy/AI-basketball-analysis

The result is pretty nice. However, the only problem is the slow inference speed. I'm now refactoring the project structure and changing the model to a much faster YOLO model.

Thanks for asking! This is not a noob question.

I would say that the similar workflow could be applied to any ball-related sports. The object detection and the tracking algorithm is basically the same. Then, you could add any sport-specific feature!

For example, I have used a similar method to build AI Basketball Analysis.

https://github.com/chonyy/AI-basketball-analysis

I work with a lot of uncompressed structured binary files so I finally broke down and wrote my own system based on the Restic chunker: https://github.com/akbarnes/dupver

I wound up writing dupver https://github.com/akbarnes/dupver after getting frustrated with the lack of versioning tools for binary files. One neat thing about .docx files and their ilk is that they are "just" zip files so it isn't hard to add special handling to pull out their contents and run deduplication over that.

DupVer https://github.com/akbarnes/dupver is a deduplicating version control system for large binary files. It's designed to keep state in a repository on the local machine separate from the working directory so it plays nice with cloud synchronization software.

I started it after constant headaches involving Git LFS and the corporate proxy. It's based around the Restic chunker library, with inspiration from both the Duplicacy backup software and Boar, another binary version control system for large binary files.

https://github.com/akbarnes/dupver