Facekeeper - Face Encoding Generator

A simple tool to capture and encode human faces into 128-dimensional numpy arrays for use in facial recognition applications.

Overview

This program provides a user-friendly way to:

• Capture face images through a camera
• Process and validate face quality
• Generate standardized 128-D face encodings
• Store encodings with associated names
• Preview and verify captured faces
• Export encodings for use in other applications
• Scare your friends who don't know how to use this program or what it does

The face encodings are generated using dlib's deep learning model and can be used for:

• Face verification/matching
• Identity management systems
• Access control applications
• Custom facial recognition projects

Features

• Live camera preview with face detection
• Quality checks for optimal face capture
• Multiple sample collection for accuracy
• Both GUI and CLI interfaces
• Configurable capture parameters
• Secure local storage of encodings
• Export options for encoded data

Setup

1. Install required dependencies:

pip install -r requirements.txt

2. Download dlib models:

python setup.download_models.py

3. Run the program:

python main.py

The program focuses on generating high-quality, consistent face encodings that can be reliably used for facial recognition tasks in other applications. Totally open source and free, let me know if you have any questions or suggestions.