👁️ VisionTrack

AI-powered desktop application for real-time object detection, tracking, and counting using YOLOv8, OpenCV, and CustomTkinter.

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📌 Overview

VisionTrack is a desktop computer vision application that performs real-time object detection, multi-object tracking, and object counting across images, videos, webcam streams, and batch image collections.

Unlike command-line AI tools, VisionTrack provides a modern graphical interface that allows users to run deep-learning models with just a few clicks.

It is designed for students, researchers, and developers who need an intuitive computer vision application without requiring command-line interaction.

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✨ Features

• 🖼 Image object detection
• 🎥 Video detection & tracking
• 📷 Live webcam detection
• 🔢 Polygon ROI object counting
• 🖱 Interactive object selection
• 📂 Batch image processing
• 🎯 Confidence threshold adjustment
• 🏷 Class filtering
• 💾 Export annotated images & videos
• 🌙 Dark/Light mode
• ⚡ Modern desktop GUI

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🖼 Application Screenshots

Main Interface

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Media Selection

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Object Detection

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Multi-Object Tracking

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🧠 Methodology

The application follows a simple computer vision pipeline.

1. Load media (image/video/webcam)
2. Preprocess frame
3. Run YOLOv8 inference
4. Track detected objects
5. Count objects inside ROI
6. Display results
7. Export annotated output

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🤖 Detection Model

VisionTrack uses YOLOv8n, a lightweight object detection model from Ultralytics.

Why YOLOv8?

• Fast inference
• High detection accuracy
• Lightweight
• Real-time performance
• CPU-friendly

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🚀 Performance

Metric	Value
Detection Accuracy	~92%
Webcam FPS	~24 FPS
Batch Processing	100+ images
Hardware	Intel i5, 8 GB RAM
GPU Required	❌ No

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🛠 Tech Stack

Language

• Python

AI

• YOLOv8
• OpenCV

GUI

• CustomTkinter

Image Processing

• Pillow (PIL)

Optional Module

• FER (Emotion Recognition)

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📁 Project Structure

VisionTrack
│
├── assets/
├── models/
├── output/
├── utils/
├── app.py
├── requirements.txt
└── README.md

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⚙ Installation

Clone the repository

git clone https://github.com/Maryam024/VisionTrack.git

cd VisionTrack

Create virtual environment

python -m venv venv

Windows

venv\Scripts\activate

Install dependencies

pip install -r requirements.txt

Run

python app.py

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🎯 Detection Modes

📷 Webcam Detection

Detect objects in real time from a webcam.

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🎥 Video Detection

Analyze recorded videos frame by frame.

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🖼 Image Detection

Detect multiple objects in static images.

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📂 Batch Processing

Process hundreds of images automatically.

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🔢 Object Counting

Count objects entering user-defined polygon regions.

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💡 Future Improvements

• Instance Segmentation
• Pose Estimation
• GPU Acceleration
• Multi-camera Support
• CSV Export
• Custom YOLO Models
• Object Re-identification

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👩‍💻 Author

Maryam Zaheer

• AI/ML Engineer
• Full-Stack Developer
• Computer Vision Enthusiast

Portfolio: https://www.maryam-dev.me

LinkedIn: https://linkedin.com/in/maryam-zaheer4