Check out my article on this blog spot, it talks about building a face recognition system that actually works in production — not a demo, not a toy, something you can put on an Android tablet mounted on a warehouse wall and walk away.

It covers the full pipeline:

Finding the face with a lightweight RFB-320 model (1.27 MB, runs on CPU)

Anti-spoofing to stop print and replay attacks (0.1 threshold, 13.9 MB model)

FaceNet-style 128-dim embeddings with L2 normalization