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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

Product type Paperback

Published in Feb 2021

Publisher Packt

ISBN-13 9781838829131

Length 542 pages

Edition 1st Edition

Languages

Python

Tools

OpenCV

Concepts

Computer Vision

Author (1):

Jesús Martínez

View More author details

Table of Contents (14) Chapters

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

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Technical requirements

Given the complexity of object detectors, having access to a Graphics Processing Unit (GPU) is a great idea. There are many cloud providers you can use to run the recipes in this chapter, my favorite being FloydHub, but you can use whichever you like the most! Of course, do keep in mind of the fees if you don't want any surprises! In the Getting ready sections, you'll find the preparatory steps for each recipe. The code for this chapter is available at https://github.com/PacktPublishing/Tensorflow-2.0-Computer-Vision-Cookbook/tree/master/ch9.

Check out the following link to see the Code in Action video:

https://bit.ly/39wInla.

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Authors (1)

Martinez

Martinez

Emilio Rodriguez Martinez is a senior software engineer who has been working on highly demanding JavaScript projects since 2010. He transitioned from web development positions into mobile development, first with hybrid technologies such as Cordova and then with native JavaScript solutions such as Titanium. In 2015, he focused on the development and maintenance of several apps built in React Native, some of which were featured in Apple's App Store as the top apps of the week. He is also an active contributor to React Native's codebase and Stack Overflow, where he provides advice on React and React Native questions.

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