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:
-
Ensure you have CMake installed. You can download it from cmake.org.
-
Uninstall any previous versions:
pip uninstall ekyc
-
Clear pip cache:
pip cache purge
-
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.
-
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
-
Clone the repository:
git clone https://github.com/yourusername/juara_ekyc.git cd juara_ekyc
-
Create a virtual environment:
python -m venv venv source venv/bin/activate # On Windows use `venv\Scripts\activate`
-
Install the development dependencies:
pip install -r requirements.txt
-
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.
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