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

Channel	Publish Date	Thumbnail & View Count	Download Video
	Publish Date not found	0 Views	View on YouTube Download Video

Have you ever wanted to implement facial recognition or authentication in your application?

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

In part 2 you will go through:
1. Collecting negative images of labeled faces in the wild
2. Resize OpenCV output frames for image collection
3. Collect positive and anchor images

Get the code: https://github.com/nicknochnack/FaceRecognition

Links
Paper: https://www.cs.cmu.edu/rsalakhu/papers/oneshot1.pdf
Tagged faces in the wild: http://vis-www.cs.umass.edu/lfw/

Chapters:
0:00 – Start
0:28 – What is covered
1:45 – Whiteboard session
7:34 – Collect LFW data
12:20 – Moving images
19:38 – Access webcam with OpenCV
27:14 – Change OpenCV frame size
32:43 – Save 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

Ps Let me know how it goes and leave a comment if you need any help!