Real-Time Object Detection 🎥🤖 A browser-based object detection system that uses your webcam and TensorFlow.js to identify objects in real-time.

✨ Features Real-time detection using webcam

80+ object types (person, phone, cup, laptop, etc.)

Visual bounding boxes with labels

Live statistics (FPS, confidence scores)

Snapshot capture 📸

Mobile-friendly design

No installation needed - runs in browser

🚀 Quick Start Clone the repo

bash git clone https://github.com/nbolok-code/real-time-object-detection.git Open index.html in your browser

Allow camera permissions when prompted

Click "Detect Objects" to start

Or try the Live Demo

🛠️ Tech Stack TensorFlow.js - Machine learning

COCO-SSD Model - Object detection

WebRTC - Camera access

Canvas API - Real-time drawing

Vanilla JavaScript - No frameworks needed

📁 Project Structure text real-time-object-detection/ ├── index.html # Main application ├── app.js # Core logic ├── README.md # This file └── LICENSE # MIT License 🎮 How to Use Start Camera → Allow webcam access

Detect Objects → Watch AI identify things

Take Snapshot → Save detection as image

Stop → End session

🔧 How It Works Browser captures webcam video

TensorFlow.js processes each frame

COCO-SSD model identifies objects

Results displayed with bounding boxes

All processing happens locally

🤝 Contributing Contributions welcome! Feel free to submit issues and pull requests.

Fork the project

Create your feature branch (git checkout -b feature/AmazingFeature)

Commit changes (git commit -m 'Add some feature')

Push to branch (git push origin feature/AmazingFeature)

Open a Pull Request

📄 License MIT License - see LICENSE file for details.

🙏 Acknowledgments TensorFlow.js

COCO-SSD Model

Inspired by Google's Teachable Machine

📞 Contact N Bolok - GitHub Profile

Project Link: https://github.com/nbolok-code/real-time-object-detection