AhmAshraf1/ACLPR

Object Detection project using YOLOv11 and EasyOCR to detect license car plates in Egypt , cropping them in images and processing videos and recognize Arabic letters and numbers with a web app for Interactive UI for users # Arabic Car License Plate Detection and Recognition This project implements a deep learning-based system for detecting and recognizing Arabic car license plates. The system can handle both images and video inputs, making it versatile for real-world applications. It is built using YOLOv11 (You Only Look Once) for object detection and OpenCV for image processing, with a focus on detecting license plates and recognizing Arabic numbers and alphabets with both YOLOv11 and EasyOCR. ## Features - **Car Plate Detection**: Detects license plates from images and videos using a trained YOLO model. - **Arabic Characters Recognition**: Recognizes Arabic letters and numbers on detected license plates. - **Video Processing**: Annotates video frames with bounding boxes for plates, letters, and numbers, and displays the processed video with these annotations. - **Image Processing**: Handles both full images of cars and cropped license plate images. - **Streamlit Deployment**: The system can be deployed as a web application using Streamlit for real-time plate detection and recognition. ## Pipeline The pipeline of the project is as follows: ## Project Structure The project is divided into two main sections: 1. **Detection**: Detects the car plate in images or video frames. If the input is an image of a car, it will crop the plate using YOLOv11 and pass it to the next stage. 2. **Recognition**: If the input is a cropped car plate image or the plate detected from the first stage, it recognizes the Arabic characters (numbers and letters) using YOLOv11 & EasyOCR. ## Installation ### Prerequisites - Python - Streamlit - OpenCV (cv2) - YOLO - EasyOCR ### Install Dependencies 1. Clone the repository: ```bash git clone github.com cd sic-dl-Arabic-Car-License ``` 2. Install the required packages: ```bash pip install -r requirements.txt ``` ## Usage ### Running the App Locally 1. To start the Streamlit web application, run the followi …