AkshaySatasiya/Tennis-Match-Analysis
This project integrates machine learning, computer vision, and deep learning to analyze tennis. Using YOLO, it detects players and balls, with trackers for smooth tracking. It also employs a custom CNN to identify court points.
This tool helps tennis players, coaches, and enthusiasts analyze match videos to understand player and ball movements. It takes a tennis match video as input and outputs detailed visualizations of player trajectories, ball speed, shot placements, and overall match statistics on a 'mini court.' This is ideal for anyone looking to optimize training strategies, improve individual skills, or gain deeper insights into tennis matches.
No commits in the last 6 months.
Use this if you need to break down tennis match footage to understand player movement, ball trajectory, and overall match dynamics.
Not ideal if you're looking for real-time analysis of a live match or advanced shot classification beyond basic tracking.
Stars
7
Forks
3
Language
Jupyter Notebook
License
—
Category
Last pushed
Apr 01, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/AkshaySatasiya/Tennis-Match-Analysis"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
roboflow/sports
computer vision and sports
chonyy/AI-basketball-analysis
:basketball::robot::basketball: AI web app and API to analyze basketball shots and shooting pose.
mradovic38/football_analysis
A comprehensive tool for processing and analyzing video footage, producing detailed insights...
KieDani/UpliftingTableTennis
Official implementation of the paper "Uplifting Table Tennis: A Robust, Real-World Application...
wmcnally/deep-darts
DeepDarts is the first deep learning-based automatic scoring system for steel-tip darts. It...