dflex
AI-basketball-analysis
| dflex | AI-basketball-analysis | |
|---|---|---|
| 129 | 12 | |
| 1,729 | 923 | |
| 0.4% | - | |
| 8.1 | 0.0 | |
| 24 days ago | almost 1 year ago | |
| TypeScript | Python | |
| MIT License | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
dflex
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Introducing DFlex - A Modern Javascript Drag and Drop Library
I'd love for you to check out the DFlex website to see examples and live demos. Let me know if you end up building something cool with DFlex! I'm always looking for feedback to help improve the library.
- Show HN: Removing esbuild reduces bundle size by 30%
- DFlex – The JavaScript Library for Modern Drag and Drop Apps
- Show HN: DFlex – JavaScript framework for modern Drag and Drop apps
- DFlex - a Javascript library for modern Drag and Drop apps. It's built with vanilla Javascript and implemented an enhanced transformation mechanism to manipulate DOM elements
- DFlex: Javascript framework for modern Drag and Drop apps
- Show HN: JavaScript Drag-N-Drop Framework for Modern Apps
- Show HN: Enable DOM reconciliation for transformed elements
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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vue-smooth-dnd - Vue wrapper components for smooth-dnd
veems - An open-source platform for online video.
roost - Proof of Concept for Eventsourced backend
FastMOT - High-performance multiple object tracking based on YOLO, Deep SORT, and KLT 🚀
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SynthDet - SynthDet - An end-to-end object detection pipeline using synthetic data