Object Tracking and Counting System

A computer vision solution for tracking and counting objects crossing a defined line

Object Tracking Demo

How It Works

  • 1.

    Objects are detected using YOLOv11 neural network

  • 2.

    Object tracking with ByteTrack algorithm assigns unique IDs

  • 3.

    Virtual counting line is defined in the frame

  • 4.

    Objects are counted when their trajectory crosses the line

  • 5.

    Directional counting (in/out) with trajectory analysis

Key Features

  • Accurate tracking in crowded scenes

  • Multi-class object detection and classification

  • Real-time processing with optimized inference

  • Handles occlusions and complex scenarios

  • Customizable counting zones and visualization

Applications

Retail Analytics

Track customer flow and traffic patterns in stores to optimize layout and staffing.

Industrial Automation

Count products on conveyor belts for quality control and inventory management.

Smart Cities

Monitor pedestrian and vehicle traffic at intersections and public spaces.

Technical Specifications

Technologies Used

  • Python 3.8+
  • YOLOv11 for object detection
  • ByteTrack for object tracking
  • PyTorch 2.0
  • OpenCV for image processing

Performance Metrics

  • 95%+ counting accuracy in standard conditions
  • 30+ FPS on NVIDIA RTX GPUs
  • Supports multiple camera inputs
  • Cloud or edge deployment options