Uploaded September 2021 | Updated September 2026, 1 hour ago

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Ever wanted to implement facial recognition or verification into your application?

In this series you'll learn how to build a deep facial recognition application to authenticate into an application. You'll start off by building a model using Deep Learning with Tensorflow which replicates what is shown in the paper titled Siamese Neural Networks for One-shot Image Recognition. Once that's all trained you'll be able to integrate it into a Kivy app and actually authenticate!

In Part 4 you'll go through:
1. Creating an Image Embedding Model
2. Building an L1 Distance Layer
3. Combining models to Create a Siamese Neural Network

Get the code: github.com/nicknochnack/FaceRecognition

Links
Paper: https://www.cs.cmu.edu/~rsalakhu/papers/oneshot1.pdf
Labelled Faces in the Wild: http://vis-www.cs.umass.edu/lfw/

Chapters:
0:00 - Start
0:30 - Gameplan
1:59 - Tutorial Kickoff
3:07 - Create an Embedding Layer with Tensorflow
28:11 - Build a custom L1 Distance Keras Layer
35:35 - Use the Keras Functional API to make a Siamese Model

Oh, and don't forget to connect with me!
LinkedIn: bit.ly/324Epgo
Facebook: bit.ly/3mB1sZD
GitHub: bit.ly/3mDJllD
Patreon: bit.ly/2OCn3UW
Join the Discussion on Discord: bit.ly/3dQiZsV

Happy coding!
Nick

P.s. Let me know how you go and drop a comment if you need a hand!