Vehicle Tracking and Counting with YOLOv8 and ByteTrack

This project demonstrates vehicle tracking and counting using YOLOv8 and ByteTrack. The combined approach offers high accuracy and robustness in real-time vehicle detection, tracking, and counting tasks.

Table of Contents

• Vehicle Tracking and Counting with YOLOv8 and ByteTrack
  • Table of Contents
  • Introduction
    • ByteTrack
  • Features
  • Requirements
  • Installation
  • Usage
  • Demo

Introduction

Vehicle tracking and counting are essential tasks in traffic management, surveillance, and smart city applications. This project leverages the capabilities of YOLOv8 and ByteTrack to achieve real-time and accurate vehicle detection, tracking, and counting.

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ByteTrack

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Features

• Real-time vehicle detection using YOLOv8
• Multi-object tracking with ByteTrack
• Vehicle counting and analysis
• User-friendly interface

Requirements

• Python 3.x
• PyTorch
• Supervision
• Ultralytics - YOLO

Installation

Clone the repository and install the required packages:

git clone https://github.com/VuBacktracking/yolo-bytetrack-vehicle-tracking.git

Setup virtual enviroment

python3 -m venv my_venv
source my_venv/bin/activate

Install the requirements

pip install -r requirements.txt

Usage

Run the main.py

python3 main.py

Demo

vehicle-counting-result.mp4