OpenCV 3.x with Python By Example - Second Edition电子书

Title Page

Copyright and Credits

OpenCV 3.x with Python By Example Second Edition

Contributors

About the authors

About the reviewer

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Why subscribe?

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Preface

Who this book is for

What this book covers

To get the most out of this book

Download the example code files

Download the color images

Conventions used

Get in touch

Reviews

Applying Geometric Transformations to Images

Installing OpenCV-Python

Windows

macOS X

Linux (for Ubuntu)

Virtual environments

Troubleshooting

OpenCV documentation

Reading, displaying, and saving images

What just happened?

Loading and saving an image

Changing image format

Image color spaces

Converting color spaces

What just happened?

Splitting image channels

Merging image channels

Image translation

What just happened?

Image rotation

What just happened?

Image scaling

What just happened?

Affine transformations

What just happened?

Projective transformations

What just happened?

Image warping

Summary

Detecting Edges and Applying Image Filters

2D convolution

Blurring

Size of the kernel versus blurriness

Motion blur

Under the hood

Sharpening

Understanding the pattern

Embossing

Edge detection

Erosion and dilation

Afterthought

Creating a vignette filter

What's happening underneath?

How do we move the focus around?

Enhancing the contrast in an image

How do we handle color images?

Summary

Cartoonizing an Image

Accessing the webcam

Under the hood

Extending capture options

Keyboard inputs

Interacting with the application

Mouse inputs

What's happening underneath?

Interacting with a live video stream

How did we do it?

Cartoonizing an image

Deconstructing the code

Summary

Detecting and Tracking Different Body Parts

Using Haar cascades to detect things

What are integral images?

Detecting and tracking faces

Understanding it better

Fun with faces

Under the hood

Removing the alpha channel from the overlay image

Detecting eyes

Afterthought

Fun with eyes

Positioning the sunglasses

Detecting ears

Detecting a mouth

It's time for a moustache

Detecting pupils

Deconstructing the code

Summary

Extracting Features from an Image

Why do we care about keypoints?

What are keypoints?

Detecting the corners

Good features to track

Scale-invariant feature transform (SIFT)

Speeded-up robust features (SURF)

Features from accelerated segment test (FAST)

Binary robust independent elementary features (BRIEF)

Oriented FAST and Rotated BRIEF (ORB)

Summary

Seam Carving

Why do we care about seam carving?

How does it work?

How do we define interesting?

How do we compute the seams?

Can we expand an image?

Can we remove an object completely?

How did we do it?

Summary

Detecting Shapes and Segmenting an Image

Contour analysis and shape matching

Approximating a contour

Identifying a pizza with a slice taken out

How to censor a shape?

What is image segmentation?

How does it work?

Watershed algorithm

Summary

Object Tracking

Frame differencing

Colorspace based tracking

Building an interactive object tracker

Feature-based tracking

Background subtraction

Summary

Object Recognition

Object detection versus object recognition

What is a dense feature detector?

What is a visual dictionary?

What is supervised and unsupervised learning?

What are support vector machines?

What if we cannot separate the data with simple straight lines?

How do we actually implement this?

What happened inside the code?

How did we build the trainer?

Summary

Augmented Reality

What is the premise of augmented reality?

What does an augmented reality system look like?

Geometric transformations for augmented reality

What is pose estimation?

How to track planar objects

What happened inside the code?

How to augment our reality

Mapping coordinates from 3D to 2D

How to overlay 3D objects on a video

Let's look at the code

Let's add some movements

Summary

Machine Learning by an Artificial Neural Network

Machine learning (ML) versus artificial neural network (ANN)

How does ANN work?

How to define multi-layer perceptrons (MLP)

How to implement an ANN-MLP classifier?

Evaluate a trained network

Classifying images

Summary

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