Real-time IoT Vehicle Counting & Tracking System using YOLOv8 and ByteTrack. Optimized for Raspberry Pi (NCNN) with live data sync to Firebase Firestore.
AI 기반 항공 운항 안전/활주로 위험감지 서비스
This is the pipeline 2 for player detection in football match.
Real-time face detection system for security checkpoints
Real Time Radar with car Tracking and Speed Estimation + support for live video streaming and video download
🚗 Count vehicles in videos using a YOLOv8-based program for efficient traffic monitoring and real-time vehicle tracking.
This is the pipeline 1 for player detection in football match. (gpu recommended)
A project that utilizes deep learning and computer vision for cost-effective football match analysis. By applying YOLO for object detection and auto-homography for field mapping.
A state-of-the-art object detection system, built on the YOLOv5 framework, is employed to individually recognize and monitor players, the ball, sideline referees, and the goalkeeper in real-time using a television broadcast camera feed. The Bytetrack technology is integrated to augment and refine the model's performance! ⚽
ExplainableTrack — an explainable, interpretable toolkit for object tracking with visualizations.
Vehicle detection and lane-wise traffic analysis on prerecorded videos using YOLOv8 and ByteTrack
ByteTrack: Multi-Object Tracking by Associating Every Detection Box | Face Tracking using ByTrack and UniFace
This repository houses a simple native plugin for the Unity game engine, built in Visual Studio, that leverages the ByteTrack-Eigen library to perform real-time object tracking.
KickSense is an advanced computer-vision system built using YOLOv8 and DeepSORT to detect, track, and analyze football players in real-time. It identifies players, referees, goalkeepers, and the ball, assigns unique tracking IDs, draws dynamic elliptical markers, and automatically performs team classification using jersey-based appearance features.
Computer Vision Social Distance Control
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