Book Image

OpenCV Computer Vision with Python

By : Joseph Howse
Book Image

OpenCV Computer Vision with Python

By: Joseph Howse

Overview of this book

<p>OpenCV Computer Vision with Python shows you how to use the Python bindings for OpenCV. By following clear and concise examples, you will develop a computer vision application that tracks faces in live video and applies special effects to them. If you have always wanted to learn which version of these bindings to use, how to integrate with cross-platform Kinect drivers, and how to efficiently process image data with NumPy and SciPy, then this book is for you.</p> <p>This book has practical, project-based tutorials for Python developers and hobbyists who want to get started with computer vision with OpenCV and Python. It is a hands-on guide that covers the fundamental tasks of computer vision, capturing, filtering, and analyzing images, with step-by-step instructions for writing both an application and reusable library classes.</p>

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OpenCV Computer Vision with Python
Joseph Howse
Apr, 2013 | 122 pages
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Table of Contents (14 chapters)
OpenCV Computer Vision with Python
OpenCV Computer Vision with Python
Credits
Credits
About the Author
About the Author
About the Reviewers
About the Reviewers
www.PacktPub.com
www.PacktPub.com
Preface
Preface
Free Chapter
1
Setting up OpenCV
Setting up OpenCV
Choosing and using the right setup tools
Running samples
Finding documentation, help, and updates
Summary
2
Handling Files, Cameras, and GUIs
Handling Files, Cameras, and GUIs
Basic I/O scripts
Project concept
An object-oriented design
Summary
3
Filtering Images
Filtering Images
Creating modules
Channel mixing – seeing in Technicolor
Curves – bending color space
Highlighting edges
Custom kernels – getting convoluted
Modifying the application
Summary
4
Tracking Faces with Haar Cascades
Tracking Faces with Haar Cascades
Conceptualizing Haar cascades
Getting Haar cascade data
Creating modules
Defining a face as a hierarchy of rectangles
Tracing, cutting, and pasting rectangles
Adding more utility functions
Tracking faces
Modifying the application
Summary
5
Detecting Foreground/Background Regions and Depth
Detecting Foreground/Background Regions and Depth
Creating modules
Capturing frames from a depth camera
Creating a mask from a disparity map
Masking a copy operation
Modifying the application
Summary
Integrating with Pygame
Integrating with Pygame
Installing Pygame
Documentation and tutorials
Subclassing managers.WindowManager
Modifying the application
Further uses of Pygame
Summary
Generating Haar Cascades for Custom Targets
Generating Haar Cascades for Custom Targets
Gathering positive and negative training images
Finding the training executables
Creating the training sets and cascade
Testing and improving <cascade>
Summary
Index
Index

Chapter 2. Handling Files, Cameras, and GUIs

This chapter introduces OpenCV's I/O functionality. We also discuss a project concept 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 I/O capabilities and design patterns, we are building 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 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.

Note

All the finished code for this chapter can be downloaded from my website: http://nummist.com/opencv/3923_02.zip.

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