Real-Time Object Detection and Tracking System

This project implements a real-time object detection and tracking system using YOLOv8 and OpenCV. It can detect and track multiple objects in a video stream, with features like object counting and trajectory visualization.

Features

• Real-time object detection using YOLOv8
• Multiple object tracking
• Object counting
• Trajectory visualization
• Support for both webcam and video file input
• Configurable detection confidence threshold

Requirements

• Python 3.8+
• OpenCV
• PyTorch
• Ultralytics (YOLOv8)
• NumPy

Installation

1. Clone this repository
2. Install the required packages:

pip install -r requirements.txt

Usage

Run the main script:

python object_detection.py

By default, the program uses your webcam. To use a video file, modify the source in the script.

Project Structure

• object_detection.py: Main script for object detection and tracking
• utils.py: Helper functions and utilities
• requirements.txt: Project dependencies
• README.md: Project documentation

Technical Details

• Uses YOLOv8 for state-of-the-art object detection
• Implements a custom tracking algorithm for object persistence
• Optimized for real-time performance
• Supports multiple object classes from COCO dataset

Future Improvements

• Add support for custom object detection models
• Implement object classification
• Add GUI for parameter configuration
• Support for multiple camera inputs
• Export tracking data to CSV/JSON