https://github.com/onome-joseph/license-plate-recognition
License Plate Recognition system capable of detecting license plates from images and videos, extracting the license plate text, and displaying it.
https://github.com/onome-joseph/license-plate-recognition
computer-vision easyocr license-plate-recognition tracking-by-detection yolov8
Last synced: 23 days ago
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License Plate Recognition system capable of detecting license plates from images and videos, extracting the license plate text, and displaying it.
- Host: GitHub
- URL: https://github.com/onome-joseph/license-plate-recognition
- Owner: Onome-Joseph
- License: mit
- Created: 2025-01-26T00:02:07.000Z (3 months ago)
- Default Branch: main
- Last Pushed: 2025-01-29T12:29:20.000Z (3 months ago)
- Last Synced: 2025-02-12T06:39:09.035Z (3 months ago)
- Topics: computer-vision, easyocr, license-plate-recognition, tracking-by-detection, yolov8
- Language: Jupyter Notebook
- Homepage:
- Size: 48.7 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# License Plate Recognition Model
This project implements a **License Plate Recognition Model** capable of detecting license plates from images and videos, extracting the license plate text, and displaying it. The model is specifically programmed for the **United Kingdom license plate format** but can be easily reconfigured to work with other countries' formats.
## Detected output with displayed license plate text
https://github.com/user-attachments/assets/aa586775-a2fe-4ecf-9e13-374165c7b35a
## Key Features
- **Accurate Detection**: Identifies license plates in images and videos with high precision.
- **Text Extraction**: Extracts and displays license plate text from detected plates.
- **Configurable**: Supports reconfiguration for other countries' license plate formats.
- **Data Scrapping**: Saves every license plate detected image and detected frames of a video in '.csv' file.
## Applications
1. **Traffic Management**:
- Automate traffic law enforcement through real-time monitoring.
- Identify vehicles for toll collection or congestion charging.
2. **Security and Surveillance**:
- Enhance security at gated communities, offices, or parking lots by recording license plate data.
- Integrate with surveillance systems for law enforcement.
3. **Fleet Management**:
- Monitor and manage vehicle fleets for logistics and transportation businesses.
---
4 **Scalability**: Easily adaptable to diverse geographic regions and plate formats.
5 **Cost-Effectiveness**: Reduces the need for manual labor and improves operational productivity.
## Future Enhancements
1. Integrate with a database to fetch detailed vehicle records for detected license plates.
2. Support real-time updates for license plate recognition in live video feeds.
## Installation and Usage
1. Clone the repository:
```bash
git clone https://github.com/Onome-Joseph/license-plate-recognition.git
```
2. Install the required dependencies:
```bash
pip install -r requirements.txt
```
3. Run the Jupyter Notebook:
- Upload your image or video files.
- Configure the parameters as needed for your use case.
- Execute the model to detect and extract license plate details.
- The link to get the sample images and videos I used can be found [Here](https://drive.google.com/drive/folders/1ckYl_E4b_STk0cKndk92Qrzzo9yDML1p?usp=drive_link)
## Contributions
Contributions are welcome! Feel free to fork the repository, suggest improvements, or report issues.