Uploaded October 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!

Get the code: github.com/nicknochnack/FaceRecognition
Final App: github.com/nicknochnack/FaceIDApp

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
0:43 - Setting Up Tensorflow and Keras for Deep Learning
24:35 - Collecting Image Samples and Using the LFW Dataset
1:08:06 - Loading Images into the Tensorflow Dataloader
1:51:25 - Building a Siamese Neural Network
2:38:55 - Building a Custom Training Loop with tf.GradientTape
3:10:00 - Testing the Model on Images
3:40:37 - Integrating with OpenCV
4:18:40 - Building the Kivy App and Integrating with Tensorflow

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!