This project is an implementation of the FaceNet: A Unified Embedding for Face Recognition and Clustering, utilizing TensorFlow for the machine learning architecture. The core idea behind this system is to enable secure user authentication through facial recognition.
The system leverages the power of deep learning to extract facial features and create a unique embedding for each user's face. This embedding serves as a digital fingerprint, allowing for accurate identification and verification during the authentication process.
- Face Recognition: Utilizes TensorFlow to implement the Facenet model for facial feature extraction.
- User Authentication: Authenticates users by comparing their facial embeddings against stored profiles.
- Secure Storage: Safely stores user facial data and corresponding embeddings for privacy and security.
- Refer to requirements.txt
This project is licensed under the MIT License. See the LICENSE file for details.