copycat
AI-basketball-analysis
| copycat | AI-basketball-analysis | |
|---|---|---|
| 1 | 12 | |
| 6 | 923 | |
| - | - | |
| 0.0 | 0.0 | |
| 5 months ago | about 1 year ago | |
| Shell | Python | |
| MIT License | GNU General Public License v3.0 or later |
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copycat
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Ask HN: Show me your Half Baked project
A very simple web application (aimed at being self-hosted) to collect videos for watching them (repeatedly) later: https://github.com/tomszilagyi/copycat
It invokes youtube-dl under the hood, but the user can add videos (to be downloaded) via the browser. It is quite usable as is, but pretty slim on features. Maybe someone here wants to take it further.
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?
pcopy - pcopy is a temporary file host, nopaste and clipboard across machines. It can be used from the Web UI, via a CLI or without a client by using curl.
Deep-SORT-YOLOv4 - People detection and optional tracking with Tensorflow backend.
hacn - A "monad" or DSL for creating React components using Fable and F# computation expressions
openpifpaf - Official implementation of "OpenPifPaf: Composite Fields for Semantic Keypoint Detection and Spatio-Temporal Association" in PyTorch.
go-live - 🗂️ go-live is an ultra-light server utility that serves files, HTML or anything else, over HTTP.
veems - An open-source platform for online video.
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
hof - Framework that joins data models, schemas, code generation, and a task engine. Language and technology agnostic.
live_data
human-detection - yolov3 tensorflow object detection and report human movements in persian