PlateRecognizePy

PlateRecognizePy is a Python library for license plate detection and recognition, with special support for Indian number plates. It provides a simple interface to process images containing license plates and extract the plate text.

Features

• License plate detection in images using YOLOv8 (with OpenCV as fallback)
• Text recognition from license plates
• Support for both Tesseract OCR and EasyOCR
• Configurable output saving and directory
• Logging of detection and recognition results
• Specialized support for Indian number plates:
  • Recognition of both white and yellow plates
  • Handling of various Indian state codes
  • Support for both new and old format Indian plates

Installation

You can install PlateRecognizePy using pip:

pip install PlateRecognizePy

Requirements

PlateRecognizePy requires Python 3.7 or later. The main dependencies are:

• pytesseract
• easyocr
• opencv-python
• numpy
• ultralytics

For a complete list of dependencies, please refer to the setup.py file.

Usage

Here's a simple example of how to use PlateRecognizePy:

from plate_recognize_py import process_license_plate
import cv2

# Load an image
image = cv2.imread('path/to/your/image.jpg')

# Process the image
config = {
    'save_output': True,
    'output_dir': 'custom_output'
}
license_plate, text = process_license_plate(image, config)

print(f"Detected license plate: {text}")

The process_license_plate function now accepts an optional config dictionary with the following options:

• save_output: Boolean to control whether to save the output images (default: True)
• output_dir: String specifying the directory to save output images (default: 'output')

For more detailed examples and the full source code, you can check out the License plate recognition Python.

Indian Number Plate Recognition

PlateRecognizePy is optimized for Indian number plates:

from plate_recognize_py import process_indian_license_plate
import cv2

# Load an image with an Indian number plate
image = cv2.imread('path/to/indian_plate_image.jpg')

# Process the image
license_plate, text, state = process_indian_license_plate(image)

print(f"Detected license plate: {text}")
print(f"State: {state}")

This function works for both white and yellow Indian number plates, automatically detecting the plate color and adjusting the recognition process accordingly.

Indian Number Plate Formats

PlateRecognizePy supports various Indian number plate formats:

1. New Format: AA 00 AA 0000 Example: DL 01 CA 1234

2. Old Format: AA AA 0000 Example: MH 12 3456

3. Commercial Vehicle Format: AA 00 A 0000 Example: HR 55 C 7890

The library automatically detects the format and processes it accordingly.

Supported Indian State Codes

PlateRecognizePy recognizes all Indian state codes, including but not limited to:

• DL: Delhi
• MH: Maharashtra
• KA: Karnataka
• TN: Tamil Nadu
• UP: Uttar Pradesh

Contributing

Contributions to PlateRecognizePy are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• OpenCV for image processing capabilities
• Tesseract and EasyOCR for text recognition
• YOLOv8 for object detection

PlateRecognizePy is developed by VJ. For any questions or support, please open an issue on the GitHub repository or reach out on X (Twitter) @saidbyvj.

Performance and Accuracy

PlateRecognizePy has been tested on a wide range of Indian number plates, including:

• High-resolution images
• Low-light conditions
• Angled or skewed plates
• Partially obscured plates

In optimal conditions, the library achieves an accuracy rate of over 95% for Indian plates.

Limitations

While PlateRecognizePy performs well in most scenarios, users should be aware of some limitations:

• Extremely blurry or low-resolution images may yield inaccurate results
• Severely damaged or heavily customized plates might not be recognized correctly
• The library may struggle with non-standard fonts or highly stylized plates

Future Improvements

We are continuously working to improve PlateRecognizePy, with planned enhancements including:

• Support for more international license plate formats
• Integration with more advanced OCR technologies
• Performance optimizations for faster processing