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A library for electronic Know Your Customer (eKYC) verification

Project description

Juara eKYC Library

Juara eKYC is a Python library for electronic Know Your Customer (eKYC) verification, including document verification, face processing, liveness detection, and face matching.

Features

  • Document verification
  • Face processing
  • Liveness check
  • Face matching
  • Flask-based API for eKYC verification

Prerequisites

  • Python 3.7+
  • OpenCV
  • NumPy
  • scikit-learn
  • deepface
  • paddleocr
  • Flask
  • dlib

Installation

For Windows Users:

  1. Ensure you have CMake installed. You can download it from cmake.org.

  2. Uninstall any previous versions:

    pip uninstall ekyc
    
  3. Clear pip cache:

    pip cache purge
    
  4. Install the package:

    pip install path/to/ekyc-0.0.4-py3-none-any.whl
    

    Note: This will automatically install the correct dlib version for your Python installation.

  5. You may need to install PaddleOCR and PaddlePaddle separately:

    pip install paddlepaddle
    pip install paddleocr
    

For Other Operating Systems:

You can install the eKYC library using pip:

pip install juara_ekyc

Usage

Here's a basic example of how to use the Juara eKYC library:

python from juara_ekyc import process_id_verification result, message = process_id_verification('path/to/image.jpg') print(f"Verification result: {result}") print(f"Message: {message}")

Development

  1. Clone the repository:

    git clone https://github.com/yourusername/juara_ekyc.git
    cd juara_ekyc
    
  2. Create a virtual environment:

    python -m venv venv
    source venv/bin/activate  # On Windows use `venv\Scripts\activate`
    
  3. Install the development dependencies:

    pip install -r requirements.txt
    
  4. Run the tests:

    python -m unittest discover tests
    

Contributing

Contributions 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.

Project details


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