Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
TensorFlow 2.0 Computer Vision Cookbook

You're reading from   TensorFlow 2.0 Computer Vision Cookbook Implement machine learning solutions to overcome various computer vision challenges

Arrow left icon
Product type Paperback
Published in Feb 2021
Publisher Packt
ISBN-13 9781838829131
Length 542 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Author (1):
Arrow left icon
Jesús Martínez Jesús Martínez
Author Profile Icon Jesús Martínez
Jesús Martínez
Arrow right icon
View More author details
Toc

Table of Contents (14) Chapters Close

Preface 1. Chapter 1: Getting Started with TensorFlow 2.x for Computer Vision 2. Chapter 2: Performing Image Classification FREE CHAPTER 3. Chapter 3: Harnessing the Power of Pre-Trained Networks with Transfer Learning 4. Chapter 4: Enhancing and Styling Images with DeepDream, Neural Style Transfer, and Image Super-Resolution 5. Chapter 5: Reducing Noise with Autoencoders 6. Chapter 6: Generative Models and Adversarial Attacks 7. Chapter 7: Captioning Images with CNNs and RNNs 8. Chapter 8: Fine-Grained Understanding of Images through Segmentation 9. Chapter 9: Localizing Elements in Images with Object Detection 10. Chapter 10: Applying the Power of Deep Learning to Videos 11. Chapter 11: Streamlining Network Implementation with AutoML 12. Chapter 12: Boosting Performance 13. Other Books You May Enjoy

Chapter 10: Applying the Power of Deep Learning to Videos

Computer vision is focused on the understanding of visual data. Of course, that includes videos, which, at their core, are a sequence of images, which means we can leverage most of our knowledge regarding deep learning for image processing to videos and reap great results.

In this chapter, we'll start training a convolutional neuronal network to detect emotions in human faces, and then we'll learn how to apply it in a real-time context using our webcam.

Then, in the remaining recipes, we'll use very advanced implementations of architectures, hosted in TensorFlow Hub (TFHub), specially tailored to tackle interesting video-related problems such as action recognition, frames generation, and text-to-video retrieval.

Here are the recipes that we will be covering shortly:

  • Detecting emotions in real time
  • Recognizing actions with TensorFlow Hub
  • Generating the middle frames of a video with TensorFlow...
lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at €18.99/month. Cancel anytime