You're reading from Modern Computer Vision with PyTorch A practical roadmap from deep learning fundamentals to advanced applications and Generative AI

Product type Paperback

Published in Jun 2024

Publisher Packt

ISBN-13 9781803231334

Length 746 pages

Edition 2nd Edition

Languages

Python

Tools

PyTorch

Concepts

Computer Vision

Authors (2):

V Kishore Ayyadevara

Yeshwanth Reddy

View More author details

Table of Contents (26) Chapters

Preface

1. Section 1: Fundamentals of Deep Learning for Computer Vision

2. Artificial Neural Network Fundamentals FREE CHAPTER

3. PyTorch Fundamentals

4. Building a Deep Neural Network with PyTorch

5. Section 2: Object Classification and Detection

6. Introducing Convolutional Neural Networks

7. Transfer Learning for Image Classification

8. Practical Aspects of Image Classification

9. Basics of Object Detection

10. Advanced Object Detection

11. Image Segmentation

12. Applications of Object Detection and Segmentation

13. Section 3: Image Manipulation

14. Autoencoders and Image Manipulation

15. Image Generation Using GANs

16. Advanced GANs to Manipulate Images

17. Section 4: Combining Computer Vision with Other Techniques

18. Combining Computer Vision and Reinforcement Learning

19. Combining Computer Vision and NLP Techniques

20. Foundation Models in Computer Vision

21. Applications of Stable Diffusion

22. Moving a Model to Production

23. Other Books You May Enjoy

24. Index

Appendix

Understanding region proposals

Imagine a hypothetical scenario where the image of interest contains a person and sky in the background. Let’s assume there is little change in the pixel intensity of the background (sky) and a considerable change in the pixel intensity of the foreground (the person).

Just from the preceding description itself, we can conclude that there are two primary regions here – the person and the sky. Furthermore, within the region of the image of a person, the pixels corresponding to hair will have a different intensity to the pixels corresponding to the face, establishing that there can be multiple sub-regions within a region.

Region proposal is a technique that helps identify islands of regions where the pixels are similar to one another. Generating a region proposal comes in handy for object detection where we must identify the locations of objects present in an image. Additionally, given that a region proposal generates a proposal for...