Car Number Plate Tracking using YOLOv8
Overview Car Number Plate Tracking using YOLOv8 is a project aimed at leveraging advanced computer vision techniques to track car number plates in real-time. By utilizing YOLOv8, an efficient and accurate object detection algorithm, this project offers a robust solution for various applications such as traffic management, security surveillance, and parking lot monitoring.
Features
- Real-time detection and tracking of car number plates
- Integration with existing surveillance systems
- Customizable for specific use cases
- Easy to deploy and use
Installation **To run the project locally, follow these steps: ** **Clone the repository: **git clone (https://github.com/wahidpanda/Car_Number_Plate_Tracking/tree/main)
- Install dependencies: pip install -r requirements.txt
- Download pre-trained YOLOv8 weights: [Link to weights]
- Run the project: python main.py
Usage
- Configure input sources (webcam, video file, or live stream).
- Run the project using the installation steps mentioned above.
- View the output with real-time car number plate detection and tracking. Contributing Contributions are welcome! If you'd like to contribute to this project, please follow these guidelines:
Fork the repository.
- Create a new branch: git checkout -b feature_branch.
- Make your changes and commit them: git commit -m 'Add new feature'.
- Push to the branch: git push origin feature_branch.
- Submit a pull request.
License This project is licensed under the MIT License.