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Learning OpenCV 3 Computer Vision with Python (Update)

You're reading from   Learning OpenCV 3 Computer Vision with Python (Update) Unleash the power of computer vision with Python using OpenCV

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Product type Paperback
Published in Sep 2015
Publisher
ISBN-13 9781785283840
Length 266 pages
Edition 1st Edition
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Toc

Table of Contents (11) Chapters Close

Preface 1. Setting Up OpenCV FREE CHAPTER 2. Handling Files, Cameras, and GUIs 3. Processing Images with OpenCV 3 4. Depth Estimation and Segmentation 5. Detecting and Recognizing Faces 6. Retrieving Images and Searching Using Image Descriptors 7. Detecting and Recognizing Objects 8. Tracking Objects 9. Neural Networks with OpenCV – an Introduction Index

Chapter 2. Handling Files, Cameras, and GUIs

Installing OpenCV and running samples is fun, but at this stage, we want to try it out ourselves. This chapter introduces OpenCV's I/O functionality. We also discuss the concept of a project and the beginnings of an object-oriented design for this project, which we will flesh out in subsequent chapters.

By starting with a look at the I/O capabilities and design patterns, we will build our project in the same way we would make a sandwich: from the outside in. Bread slices and spread, or endpoints and glue, come before fillings or algorithms. We choose this approach because computer vision is mostly extroverted—it contemplates the real world outside our computer—and we want to apply all our subsequent algorithmic work to the real world through a common interface.

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