OpenCV Computer Vision with Python by Howse, Joseph -- Read -- Imperial Library of Trantor

Index

OpenCV Computer Vision with Python

Table of Contents OpenCV Computer Vision with Python Credits About the Author About the Reviewers www.PacktPub.com

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Preface

What this book covers What you need for this book Who this book is for Conventions Reader feedback Customer support

Downloading the example code Errata Piracy Questions

1. Setting up OpenCV

Choosing and using the right setup tools

Using binary installers (no support for depth cameras) Using CMake and compilers

Making the choice on Mac OS X Snow Leopard, Mac OS X Lion, or Mac OS X Mountain Lion

Making the choice on Ubuntu 12.04 LTS or Ubuntu 12.10

Making the choice on other Unix-like systems

Running samples Finding documentation, help, and updates Summary

2. Handling Files, Cameras, and GUIs

Basic I/O scripts

Reading/Writing an image file Converting between an image and raw bytes Reading/Writing a video file Capturing camera frames Displaying camera frames in a window

Project concept An object-oriented design

Summary

3. Filtering Images

Creating modules Channel mixing – seeing in Technicolor

Simulating RC color space Simulating RGV color space Simulating CMV color space

Curves – bending color space

Formulating a curve Caching and applying a curve Designing object-oriented curve filters Emulating photo films

Emulating Kodak Portra Emulating Fuji Provia Emulating Fuji Velvia Emulating cross-processing

Highlighting edges Custom kernels – getting convoluted Modifying the application Summary

4. 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

Swapping faces in one camera feed Copying faces between camera feeds

Summary

5. 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

A. Integrating with Pygame

Installing Pygame Documentation and tutorials Subclassing managers.WindowManager Modifying the application Further uses of Pygame Summary

B. Generating Haar Cascades for Custom Targets

Gathering positive and negative training images Finding the training executables

On Windows On Mac, Ubuntu, and other Unix-like systems

Creating the training sets and cascade

Creating <negative_description> Creating <positive_description> Creating <binary_description> by running <opencv_createsamples> Creating <cascade> by running <opencv_traincascade>

Testing and improving <cascade> Summary

Index