This Flutter project implements face authentication using the FaceNet512 model, storing face data (as Float32 arrays) and names in Firebase Firestore.

• FaceNet512 Model: Utilizes the FaceNet512 model to encode facial features.
• Firebase Firestore Integration: Stores face data (as a Float32 array of length 512) and corresponding names (as strings) in Firestore.
• Face Data Loading: Loads all face data from Firestore upon app launch.
• Face Data Storage: Allows users to capture their face and store the data in Firestore.
• Face Prediction: Predicts the user's identity by comparing the captured face data with the stored data using cosine similarity.

• camera: ^0.10.5+5
• google_mlkit_face_detection: ^0.9.0
• image: ^3.0.2
• tflite_flutter: ^0.10.3
• cloud_firestore: ^4.13.2
• firebase_core: ^2.23.0

This application aims to assist in mobile face authentication purposes, leveraging advanced face recognition technology and cloud storage.

I hope this project helps you in implementing mobile face authentication functionalities efficiently.