evo-client-nuxt
AI-basketball-analysis
evo-client-nuxt | AI-basketball-analysis | |
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3 | 12 | |
5 | 923 | |
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0.0 | 0.0 | |
about 1 year ago | about 1 year ago | |
Vue | Python | |
MIT License | GNU General Public License v3.0 or later |
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evo-client-nuxt
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I brought back the web interface for Evo car share. You can once again find available evos from the comfort of your web browser.
You can go here to report an issue or request a feature
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Ask HN: Show me your Half Baked project
I'm building an unauthorized web interface for a car share service I use. They discontinued theirs in favour of their terrible mobile apps. I just finished the API client in TypeScript, now I'm on to the UI.
I RE'd the API calls using an android emulator and mitmproxy. It has been a ton of fun. If ur in Vancouver and use evo, you may be interested. If you work for vulog, look away!
https://github.com/jeremy21212121/evo-client-nuxt
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
What are some alternatives?
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Deep-SORT-YOLOv4 - People detection and optional tracking with Tensorflow backend.
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openpifpaf - Official implementation of "OpenPifPaf: Composite Fields for Semantic Keypoint Detection and Spatio-Temporal Association" in PyTorch.
pyodide - Pyodide is a Python distribution for the browser and Node.js based on WebAssembly
go-live - 🗂️ go-live is an ultra-light server utility that serves files, HTML or anything else, over HTTP.
dflex - The sophisticated Drag and Drop library you've been waiting for 🥳
veems - An open-source platform for online video.
pastty - Copy and paste across devices
FastMOT - High-performance multiple object tracking based on YOLO, Deep SORT, and KLT 🚀
SynthDet - SynthDet - An end-to-end object detection pipeline using synthetic data