AI-basketball-analysis
FastMOT
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| AI-basketball-analysis | FastMOT | |
|---|---|---|
| 12 | 2 | |
| 922 | 1,095 | |
| - | - | |
| 0.0 | 0.0 | |
| 12 months ago | about 2 years ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | MIT License |
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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.
- Show HN: AI Basketball Analysis in Realtime
- Show HN: AI Basketball Visualization
FastMOT
- Does Multi Object Tracking work better (precision/recall) on videos than jury rigging a SOTA image object detection to work on videos?
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Assign ID and track moving object with optical flow
On failure, you can try using a re-identification methods like FastReid: https://github.com/JDAI-CV/fast-reid in combination with your detector. A good pipeline that combines everything you seem to need is here: https://github.com/GeekAlexis/FastMOT. It uses a combination of Yolov4 (detector) + Kalman filters, Optical flow (tracker) and FastReid (re-identification)
What are some alternatives?
Deep-SORT-YOLOv4 - People detection and optional tracking with Tensorflow backend.
multi-object-tracker - Multi-object trackers in Python
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.
ByteTrack - [ECCV 2022] ByteTrack: Multi-Object Tracking by Associating Every Detection Box
veems - An open-source platform for online video.
fast-reid - SOTA Re-identification Methods and Toolbox
SynthDet - SynthDet - An end-to-end object detection pipeline using synthetic data
TFJS-object-detection - Real-time custom object detection in the browser using tensorflow.js
live_data
zero-shot-object-tracking - Object tracking implemented with the Roboflow Inference API, DeepSort, and OpenAI CLIP.