Lebanese License Plate Recognition System

Overview

This project implements an automated system for real-time detection and recognition of new Lebanese license plates. It integrates state-of-the-art technologies: YOLOv8 for detection and PaddleOCR for optical character recognition.

Demo

Watch the full demo of the license plate recognition system in action here:

Getting Started

Prerequisites

Python 3.x
OpenCV library
Ultralytics YOLOv8
PaddlePaddle PaddleOCR

Installation

Clone this repository and install the required dependencies.

Step 1: Clone the repository

To get started, clone this repository to your local machine using the following command:

git clone https://github.com/Ghantoos7/AutoVision-Plate-Recognition.git

Step 2: Navigate to the project directory

Change into the project directory with:

cd AutoVision-Plate-Recognition

Step 3: Install the dependencies

Install all the necessary dependencies by running:

pip install -r requirements.txt

Usage

To process an image or video, use the following command:

python recognize.py your_file_path

The script accepts the path to the source image or video file and processes it to output the detection and recognition results or if you put 0 it will use your camera for real time detection and recognition.

Examples

Processed images and videos will be saved with "_processed" appended to the original file name.

Example Images

Original Image	Processed Image

Results

the model has achieved an impressive 95% accuracy in real-world conditions.

Confusion Matrix

Precision-Recall Curve

Contributing

Contributions to this project are welcome! Please consider the following steps:

Fork the project
Create your feature branch (git checkout -b feature/AmazingFeature)
Commit your changes (git commit -m 'Add some AmazingFeature')
Push to the branch (git push origin feature/AmazingFeature)
Open a pull request

License

Distributed under the MIT License. See LICENSE for more information.

License

Ghantoos7/AutoVision-Plate-Recognition

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