Vehicle-Plate-Recognition

Project: Vehicle Plate Recognition

Install

This project requires Python and the following Python libraries installed:

• NumPy
• Pandas
• matplotlib
• scikit-learn
• YOLO v8
• YOLO v9
• EasyOcr

You must also install software to run and execute a Google Colab.

Code

Template code is provided in the Licence_Plate_Detection_YOLO_V8.ipynb notebook file and licence_plate_using_YOLO_V9.ipynb.

Run

In a terminal or command window, navigate to the top-level project directory Licence_Plate_Detection_YOLO_V8.ipynb/ (that contains this README) and also licence_plate_using_YOLO_V9.ipynband run one of the following commands:

ipython notebook Licence_Plate_Detection_YOLO_V8.ipynb

or

ipython notebook licence_plate_using_YOLO_V9.ipynb

or

jupyter notebook Licence_Plate_Detection_YOLO_V8.ipynb

or

jupyter notebook licence_plate_using_YOLO_V9.ipynb

or open with Jupyter Lab

jupyter lab

This will open the Jupyter Notebook software and project file in your browser.

Data

Dataset used: https://universe.roboflow.com/mochoye/license-plate-detector-ogxxg Features

• Result: Vehicle number plates are recognized using YOLO v8 and YOLO v9 models along with Easyocr.