openpifpaf
AI-basketball-analysis
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| openpifpaf | AI-basketball-analysis | |
|---|---|---|
| 1 | 12 | |
| 1,127 | 923 | |
| 0.9% | - | |
| 4.4 | 0.0 | |
| 4 months ago | 12 months ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | 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.
openpifpaf
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Human Pose Estimation Recommendation
OpenPifPaf is decent, easier to install on newer systems than OpenPose imo.
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?
mmpose - OpenMMLab Pose Estimation Toolbox and Benchmark.
Deep-SORT-YOLOv4 - People detection and optional tracking with Tensorflow backend.
AlphaPose - Real-Time and Accurate Full-Body Multi-Person Pose Estimation&Tracking System
go-live - 🗂️ go-live is an ultra-light server utility that serves files, HTML or anything else, over HTTP.
lightweight-human-pose-estimation.pytorch - Fast and accurate human pose estimation in PyTorch. Contains implementation of "Real-time 2D Multi-Person Pose Estimation on CPU: Lightweight OpenPose" paper.
veems - An open-source platform for online video.
posenet-python - A Python port of Google TensorFlow.js PoseNet (Real-time Human Pose Estimation)
FastMOT - High-performance multiple object tracking based on YOLO, Deep SORT, and KLT 🚀
tensorflow_Realtime_Multi-Person_Pose_Estimation - Multi-Person Pose Estimation project for Tensorflow 2.0 with a small and fast model based on MobilenetV3
SynthDet - SynthDet - An end-to-end object detection pipeline using synthetic data
kapao - KAPAO is an efficient single-stage human pose estimation model that detects keypoints and poses as objects and fuses the detections to predict human poses.
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