Doc Scan

Doc Scan is a Python-based project for image processing and computer vision tasks. It leverages OpenCV for image manipulation and FastAPI for providing a web-based API to process images.

It's not a production suited project but still... :D

Features

• Pre-Processing:

  • Resizing, denoising, edge detection, HSV filtering, GrabCut segmentation, and morphological operations.
  • Thresholding using Otsu's method.

• Processing:

  • Corner detection using Hough Line Transform and Contour-based methods.
  • Perspective transformation for bird's-eye view extraction.

• Post-Processing:

  • Image enhancement, filtering, sharpening, and cleaning.

• FastAPI Integration:

  • Provides an API endpoint to process uploaded images and return results.

Installation

1. Clone the repository:

   git clone https://github.com/AmirKafi/Doc-Scan.git
   cd OpenCV-Prac

2. Install dependencies:

   pip install -r requirements.txt

3. Ensure you have Python 3.10 or higher installed.

Usage

Running the FastAPI Server

1. Start the server:

   uvicorn app:app --host 0.0.0.0 --port 8000

2. Access the API at http://localhost:8000.

3. Use the /process-image endpoint to upload an image and process it.

Example API Request

• Endpoint: /process-image
• Method: POST
• Request: Upload an image file.
• Response: Processed image as a downloadable file.

Running Individual Scripts

• Use the modules in the pre_processors, processors, and PostProcessor directories for specific image processing tasks.

Project Structure

OpenCV-Prac/
├── app.py                     # FastAPI application
├── requirements.txt           # Python dependencies
├── vercel.json                # Vercel deployment configuration
├── PostProcessor/             # Post-processing modules
├── pre_processors/            # Pre-processing modules
├── processors/                # Processing modules
├── static/                    # Static files (e.g., favicon)
└── README.md                  # Project documentation

Deployment

This project can be deployed on Vercel using the provided vercel.json configuration.

Contributing

Contributions are welcome! Please follow these steps:

1. Fork the repository.
2. Create a new branch for your feature or bug fix.
3. Submit a pull request with a detailed description of your changes.

License

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

Acknowledgments

• OpenCV for the computer vision library.
• FastAPI for the web framework.
• scikit-learn for clustering algorithms.

Contact

For any questions or feedback, feel free to reach out to the project maintainer.