Uploaded September 2021 | Updated September 2026, 2 hours 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 3 you'll go through:
1. Scaling and Resizing Images as part of a Deep Learning pipeline
2. Loading and labelling images using the Tensorflow Dataloader
3. Splitting data pipelines into training and testing partitions

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
3:19 - Loading Image paths into tf.data
10:19 - Loading, Scaling and Resizing Images in a pipeline
16:51 - Creating Positive and Negative Samples
25:21 - Caching, Batching and Splitting the Pipeline

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!