Build a Deep Facial Recognition App // Part 2 Collecting Data // Deep Learning Project Tutorial

PodAn September 17, 2021

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 2 you'll go through:
1. Collecting Negative images from Labelled Faces in the wild
2. Resizing OpenCV Output Frames for Image Collection
3. Collecting Positive and Anchor Images

Get the code: https://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
0:28 - What's Covered
1:45 - Whiteboard Session
7:34 - Collect LFW Data
12:20 - Moving Images
19:38 - Access Webcam with OpenCV
27:14 - Changing OpenCV Frame Size
32:43 - Saving Images
43:16 - Wrap Up

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

Happy coding!
Nick

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