This project implements face recognition for a transaction system using Keras, OpenCV, data augmentation, and OTP verification with Django as the backend.
The Face Recognition Transaction System is designed to enhance security and convenience in financial transactions by implementing a face recognition system. This system verifies the identity of users through their facial features and integrates OTP (One Time Password) verification for additional security.
- Face recognition using Keras and OpenCV.
- Data augmentation techniques for improving model performance.
- OTP verification for secure transactions.
- User-friendly interface for seamless interaction.
- User perform curd operations to manage their profile
-
Clone the repository:
git clone https://github.com/kashishsinghyadav/Face-Recogination-for-transaction-system
-
Install the required dependencies:
pip install -r requirements.txt
-
Download the pre-trained model weights for face recognition.
-
Apply database migrations:
python manage.py migrate
-
Run the Django server:
python manage.py runserver
- Launch the Django server.
- Register your face by following the instructions.
- Initiate a transaction.
- The system will verify your identity through face recognition.
- Enter the OTP received on your registered device to complete the transaction.
Contributions are welcome! Please feel free to fork the repository and submit pull requests to suggest improvements or add new features.
This project is licensed under the MIT License - see the LICENSE file for details.
For any inquiries or support, please contact kashish . k