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OpenCV Text Detection (EAST text detector) πŸ”

A Python application that performs real-time text detection in images and video streams using OpenCV and the EAST text detector model.

πŸ“‹ Table of Contents

✨ Features

  • Real-time text detection in images
  • Real-time text detection in video streams and webcam
  • Support for multiple text orientations
  • Non-maximum suppression for overlapping detections
  • Adjustable confidence threshold
  • FPS counter for performance monitoring

πŸ”§ Requirements

  • Python 3.6+
  • OpenCV (cv2)
  • NumPy
  • imutils
  • Pre-trained EAST text detector model

πŸš€ Installation

  1. Clone this repository:
git clone https://github.com/gifflet/opencv-text-detection.git
cd opencv-text-detection
  1. Install the required packages:
pip install opencv-python numpy imutils
  1. Download the EAST text detector model (frozen_east_text_detection.pb)

πŸ’» Usage

Image Detection

To detect text in an image:

python text_detection.py --image path/to/image.jpg --east frozen_east_text_detection.pb

Optional arguments:

  • --min-confidence: Minimum probability to filter weak detections (default: 0.5)
  • --width: Resized image width (should be multiple of 32)
  • --height: Resized image height (should be multiple of 32)

Video/Webcam Detection

To detect text in video or webcam:

# For webcam
python text_detection_video.py --east frozen_east_text_detection.pb

# For video file
python text_detection_video.py --east frozen_east_text_detection.pb --video path/to/video.mp4

πŸ” How it Works

The application uses the EAST (Efficient and Accurate Scene Text) detector, which is a deep learning model designed for text detection. The process involves:

  1. Image preprocessing and resizing
  2. Running the EAST detector to get text predictions
  3. Decoding the predictions to get bounding box coordinates
  4. Applying non-maximum suppression to eliminate overlapping detections
  5. Drawing the results on the original image/frame

🀝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.

  1. Fork the repository
  2. Create your feature branch (git checkout -b feature/AmazingFeature)
  3. Commit your changes (git commit -m 'Add some AmazingFeature')
  4. Push to the branch (git push origin feature/AmazingFeature)
  5. Open a Pull Request

πŸ“„ License

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

πŸ™ Acknowledgments

Project based on the original work by Adrian Rosebrock from PyImageSearch (https://www.pyimagesearch.com/2018/08/20/opencv-text-detection-east-text-detector/)


Made with ❀️ by gifflet

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