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Modern Computer Vision with PyTorch

You're reading from   Modern Computer Vision with PyTorch Explore deep learning concepts and implement over 50 real-world image applications

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Product type Paperback
Published in Nov 2020
Publisher Packt
ISBN-13 9781839213472
Length 824 pages
Edition 1st Edition
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Authors (2):
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Yeshwanth Reddy Yeshwanth Reddy
Author Profile Icon Yeshwanth Reddy
Yeshwanth Reddy
V Kishore Ayyadevara V Kishore Ayyadevara
Author Profile Icon V Kishore Ayyadevara
V Kishore Ayyadevara
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Toc

Table of Contents (25) Chapters Close

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. Training with Minimal Data Points 19. Combining Computer Vision and NLP Techniques 20. Combining Computer Vision and Reinforcement Learning 21. Moving a Model to Production 22. Using OpenCV Utilities for Image Analysis 23. Other Books You May Enjoy Appendix

Representing an image

A digital image file (typically associated with the extension "JPEG" or "PNG") is comprised of an array of pixels. A pixel is the smallest constituting element of an image. In a grayscale image, each pixel is a scalar (single) value between 0 and 255 – 0 is black, 255 is white, and anything in between is gray (the smaller the pixel value, the darker the pixel is). On the other hand, the pixels in color images are three-dimensional vectors that correspond to the scalar values that can be found in its red, green, and blue channels.

An image has height x width x c pixels, where height is the number of rows of pixels, width is the number of columns of pixels, and c is the number of channels. c is 3 for color images (one channel each for the red, green, and blue intensities of the image) and 1 for grayscale images. An example grayscale image containing 3 x 3 pixels and their corresponding scalar values is shown here:

Again, a pixel value of...

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