Computer Vision Detection and Blur OCR Plate using YOLO

Welcome to the computervison-detection-and-blur-ocr-plate-yolo repository. This project leverages the YOLO (You Only Look Once) model for detecting and blurring OCR plates in images. It is designed to protect privacy by ensuring that sensitive information on vehicle license plates is obscured.

Table of Contents

• Introduction
• Features
• Installation
• Usage
• Project Structure
• Contributing
• License

Introduction

This repository contains a computer vision application that detects vehicle license plates using the YOLO model and applies a blurring effect to obscure the detected plates. This can be useful for maintaining privacy in images and videos where license plates are visible.

Features

• License Plate Detection: Uses YOLO model to detect license plates in images.
• Blur Functionality: Applies a blurring effect to the detected license plates to obscure them.
• High Accuracy: Utilizes state-of-the-art YOLO model for robust detection.

Installation

To set up this project, follow these steps:

1. Clone the repository:

   git clone https://github.com/DominikRoczan/computervison-detection-and-blur-ocr-plate-yolo.git
   cd computervison-detection-and-blur-ocr-plate-yolo

2. Create and activate a virtual environment (optional but recommended):

   python -m venv venv
   source venv/bin/activate  # On Windows use `venv\Scripts\activate`

3. Install the required packages:

   pip install -r requirements.txt

Usage

To use the application, follow these steps:

1. Prepare your images: Place the images you want to process in the input directory.

2. Run the detection and blurring script:

   python blur_license_plates.py

3. Output: The processed images with blurred license plates will be saved in the output directory.

Project Structure