Welcome to the Automatic Number Plate Recognition (ANPR) project! This repository showcases a state-of-the-art ANPR system using the powerful YOLOv8 model. Trained meticulously for 100 epochs on a dataset of 5000 images with precise annotations, this project aims to deliver high accuracy and reliability in detecting and reading vehicle number plates. All training was conducted on Google Colab, leveraging its robust computational resources. Additionally, Tesseract OCR has been integrated for the optical character recognition (OCR) part of the pipeline, ensuring accurate text extraction from the detected number plates. The main.py script included in this repository allows you to test the model locally on your machine. Dive into this project to explore cutting-edge technology in action and see how machine learning can transform everyday tasks. Let's make number plate recognition seamless and efficient! 🚀✨
To get started with the ANPR project, follow these steps:
Clone this repository to your local machine. Install the necessary Python packages by running the following command:
pip install -r requirements.txtEnsure you have Tesseract installed on your machine.