zaino
AI-basketball-analysis
zaino | AI-basketball-analysis | |
---|---|---|
1 | 12 | |
7 | 923 | |
- | - | |
6.0 | 0.0 | |
10 months ago | about 1 year ago | |
TypeScript | Python | |
MIT License | GNU General Public License v3.0 or later |
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zaino
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Ask HN: Show me your Half Baked project
I am currently building a (open-source) hiking and mountaineering equipment management web app.
An early prototype is at https://www.zaino.io . It's a bit rough around the edges (does not work on mobiles, not a lot of features, some UX issues probably) but core functionality should work.
Code, docs, issues are at https://github.com/igor-krupenja/zaino
AI-basketball-analysis
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[P] Basketball Shots Detection and Shooting Pose Analysis (Open Source)
Source code: https://github.com/chonyy/AI-basketball-analysis
- Show HN: Visualizing Basketball Trajectory and Analyzing Shooting Pose
- Automatically Overlaying Baseball Pitch Motion and Trajectory in Realtime (Open Source)
- Show HN: AI Basketball Analysis Web App and API
- Show HN: Visualize and Analyze Basketball Shots and Shooting Pose with ML
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Ask HN: Show me your Half Baked project
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.
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Show HN: Automatic Baseball Pitching Motion and Trajectory Overlay in Realtime
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
- Show HN: AI Basketball Analysis in Realtime
- Show HN: AI Basketball Visualization
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