This project is designed to display how we can utilize deep learning methods for Sports Data Analytics.

Fast Volleyball Tracking Inference: Real-time volleyball ball detection and tracking at 100 FPS on CPU (Intel i5-10400F). Powered by an optimized ONNX model, outputs ball coordinates to CSV, with optional video visualization. Ideal for sports analytics and computer vision research.

A test simulation of all projects and models from time to time.

Cricket Ball Trajectory Detection And Prediction

LBW Detection in Cricket: A Deep Dive with OpenCV & NumPy

Tool for multi-view camera calibration - Ball detection and tracking.

Intelligent Snooker Video Analyzer turns ordinary snooker footage into professional-grade insights. It automatically detects every shot, tracks cue ball path, and generates cinematic highlights in seconds. Built for clubs, academies, and passionate players, it delivers instant real-time playback and highlights share

🏀 BasketballDetector implementation using a segmentation approach

WASB-SBDT-FPFilter 是一个可配置、工程化的体育球（网球/足球/羽毛球/排球/篮球）检测与跟踪基线实现，基于 WASB。仓库包含评估代码、示例数据、预训练权重、FP（假阳性）过滤训练与推理工具、交互式 patch 标注工具，并新增了一个一键式端到端推理 Pipeline（WASB 检测 → FP 过滤 → 可视化）。支持通过 Hydra 配置灵活定制，适合研究与工程化部署场景。

A robot made to balance a ball on a platform. The platform is controlled by two servo motors, and the ball's position is detected using a camera. A Raspberry Pi is the brain of the project, and calculates the incline of the plane needed to get the ball to the desired position.

Simple controller using trained NN for ball detection with gazebo, ROS, and Matlab Simulink.