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| # Number Plate Detection using YOLO and Gradio | |
| This repository contains code and resources for number plate detection using YOLO (You Only Look Once) object detection algorithm and Gradio for building a user-friendly interface. | |
| ## Table of Contents | |
| - [Introduction](#introduction) | |
| - [Installation](#installation) | |
| - [Usage](#usage) | |
| - [Contributing](#contributing) | |
| - [License](#license) | |
| ## Introduction | |
| Number plate detection is an important task in various applications such as traffic surveillance, parking management, and law enforcement. This project utilizes the YOLO algorithm, a state-of-the-art object detection model, to detect number plates in images or videos. Gradio, a Python library, is used to create a simple and interactive user interface for easy testing and deployment. | |
| ## Installation | |
| To use this project, follow these steps: | |
| 1. Clone the repository: `git clone https://github.com/yuval728/number-plate-detection.git` | |
| 2. Install the required dependencies: `pip install -r requirements.txt` | |
| ## Usage | |
| 1. Run the `app/app.py` script. | |
| 2. Open your web browser and navigate to `http://localhost:7860`. | |
| 3. Upload an image or video file to detect number plates. | |
| 4. View the detected number plates and their bounding boxes. | |
| ## Contributing | |
| Contributions are welcome! If you have any ideas, suggestions, or bug reports, please open an issue or submit a pull request. | |
| ## License | |
| This project is licensed under the [MIT License](LICENSE). | |