Feature Request: Implement Face Liveliness and Anti-Spoofing Mechanism

[pratikwayal01]

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Pull Request Title:

Add Face Liveness Detection System Using Profile and Blink Detection
Issue Number - #135

Description:

This pull request implements a Face Liveness Detection System that leverages profile detection and blink detection techniques. The goal is to verify whether a user is physically present during the authentication process by analyzing their facial features and eye blinks.

Changes Made:

• Implemented profile detection using Haar Cascade classifiers for frontal and profile face detection.
• Integrated blink detection using Dlib's shape predictor to calculate the Eye Aspect Ratio (EAR).
• Developed a user interface that prompts users to turn their faces and blink.
• Added a README file explaining the methodology, how to run the main file, and project structure.
• Included a requirements.txt file with necessary dependencies.

Methodology:

1. Profile Detection: Utilizes Haar Cascade classifiers to detect frontal and profile faces.
2. Blink Detection: Employs Dlib's shape predictor to monitor eye blinks based on the EAR threshold.
3. User Interaction: Prompts the user for specific actions (turning and blinking) to confirm liveness.

How to Test:

1. Ensure the necessary XML and DAT files are placed in the dataset/ directory.
2. Run the main.py file to initiate the detection process.
3. Follow the prompts on the screen for liveness detection.

[github-actions]

Thank you for submitting your pull request! 🙌 We'll review it as soon as possible. In the meantime, please ensure that your changes align with our CONTRIBUTING.md. If there are any specific instructions or feedback regarding your PR, we'll provide them here. Thanks again for your contribution! 😊

[UppuluriKalyani]

@pratikwayal01 can you please show results here and also attach in readme file.