https://github.com/wahidpanda/car_number_plate_tracking
Tracking Cars Number plate using Yolo V8 Model
https://github.com/wahidpanda/car_number_plate_tracking
Last synced: 4 months ago
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Tracking Cars Number plate using Yolo V8 Model
- Host: GitHub
- URL: https://github.com/wahidpanda/car_number_plate_tracking
- Owner: wahidpanda
- Created: 2024-03-14T05:07:29.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-03-14T05:17:28.000Z (over 1 year ago)
- Last Synced: 2025-03-15T05:26:40.364Z (7 months ago)
- Language: Python
- Size: 1.05 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
**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**
1. Real-time detection and tracking of car number plates
2. Integration with existing surveillance systems
3. Customizable for specific use cases
4. 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)
1. Install dependencies: pip install -r requirements.txt
2. Download pre-trained YOLOv8 weights: [Link to weights]
3. Run the project: python main.py
**Usage**
1. Configure input sources (webcam, video file, or live stream).
2. Run the project using the installation steps mentioned above.
3. 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.**
1. Create a new branch: git checkout -b feature_branch.
2. Make your changes and commit them: git commit -m 'Add new feature'.
3. Push to the branch: git push origin feature_branch.
4. Submit a pull request.
**License**
This project is licensed under the MIT License.