License Plate Recognition using YOLO and OCR

📌 Overview

This project implements an Automatic License Plate Recognition (ALPR) system using YOLO (You Only Look Once) for object detection and OCR (Optical Character Recognition) for text extraction. The system detects vehicle license plates in images or video streams and extracts the plate numbers.

🚀 Features

• Detects license plates in real-time using YOLO.
• Extracts plate numbers using OCR (Tesseract/ EasyOCR).
• Supports video and image input.
• Exports results in a structured format (JSON, CSV).
• Can be integrated with security and traffic monitoring systems.

📂 Project Structure

📦 license-plate-recognition
├── 📂 models          # Pre-trained YOLO models
├── 📂 datasets        # Sample images/videos for testing
├── 📂 output          # Detected results and logs
├── detect.py         # Main script for license plate detection
├── ocr.py            # OCR processing script
├── requirements.txt  # Required dependencies
└── README.md         # Project documentation

🛠️ Model Details

• YOLOv5/YOLOv8 is used for license plate detection.
• Tesseract OCR/EasyOCR is used for text extraction.
• Pretrained models are included in the models/ directory or can be downloaded from external sources.

🎯 Applications

• Automatic Toll Collection 🚗
• Parking Lot Management 🅿️
• Traffic Law Enforcement 🚦
• Smart City Surveillance 🏙️

📜 License

This project is licensed under the MIT License - see the LICENSE file for details.

🤝 Contributing

Feel free to submit issues, fork the repository, and create pull requests!

📧 Contact

For questions or collaboration opportunities, contact: [email protected]