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Computer Vision with OpenCV 3 and Qt5电子书

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23人正在读 | 0人评论 6.2

作       者:Amin Ahmadi Tazehkandi

出  版  社:Packt Publishing

出版时间:2018-01-02

字       数:59.3万

所属分类: 进口书 > 外文原版书 > 电脑/网络

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Blend the power of Qt with OpenCV to build cross-platform computer vision applications About This Book ? Start creating robust applications with the power of OpenCV and Qt combined ? Learn from scratch how to develop cross-platform computer vision applications ? Accentuate your OpenCV applications by developing them with Qt Who This Book Is For This book is for readers interested in building computer vision applications. Intermediate knowledge of C++ programming is expected. Even though no knowledge of Qt5 and OpenCV 3 is assumed, if you’re familiar with these frameworks, you’ll benefit. What You Will Learn ? Get an introduction to Qt IDE and SDK ? Be introduced to OpenCV and see how to communicate between OpenCV and Qt ? Understand how to create UI using Qt Widgets ? Know to develop cross-platform applications using OpenCV 3 and Qt 5 ? Explore the multithreaded application development features of Qt5 ? Improve OpenCV 3 application development using Qt5 ? Build, test, and deploy Qt and OpenCV apps, either dynamically or statically ? See Computer Vision technologies such as filtering and transformation of images, detecting and matching objects, template matching, object tracking, video and motion analysis, and much more ? Be introduced to QML and Qt Quick for iOS and Android application development In Detail Developers have been using OpenCV library to develop computer vision applications for a long time. However, they now need a more effective tool to get the job done and in a much better and modern way. Qt is one of the major frameworks available for this task at the moment. This book will teach you to develop applications with the combination of OpenCV 3 and Qt5. This book will teach you to create cross-platform computer vision applications. We’ll begin by introducing Qt, its IDE, and its SDK. Next you’ll learn how to use the OpenCV API to integrate both tools, and see how to configure Qt to use OpenCV. You’ll go on to build a full-fledged computer vision application throughout the book. Later, you’ll create a stunning UI application using the Qt widgets technology, where you’ll display the images after they are processed in an efficient way. At the end of the book, you’ll learn how to convert OpenCV Mat to Qt QImage. You’ll also see how to efficiently process images to filter them, transform them, detect or track objects as well as analyze video. You’ll become better at developing OpenCV applications. Style and approach This book will help you understand and create cross-platform and multithreaded computer vision applications with the help of OpenCV 3 and Qt5, using a plugin-based and modular application development approach.
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Title Page

Copyright and Credits

Computer Vision with OpenCV 3 and Qt5

Dedication

Packt Upsell

Why subscribe?

PacktPub.com

Foreword

Contributors

About the author

About the reviewers

Packt is searching for authors like you

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

Introduction to OpenCV and Qt

What is required?

Introduction to Qt

Qt Essentials

Qt Add-Ons

Value-Add Modules

Technology Preview Modules

Platforms supported by Qt

Qt Creator

Introduction to OpenCV

Main modules

Extra modules

Installing Qt

Preparing for Qt installation

Where to get it?

How to install?

Windows users

macOS users

Linux users

Testing Qt installation

Installing OpenCV

Preparing for an OpenCV build

Where to get OpenCV?

How to build?

Configuring OpenCV installation

Testing OpenCV installation

Summary

Creating Our First Qt and OpenCV Project

What is Qt Creator?

A tour of the IDE

Qt Creator modes

The Welcome mode

Projects

Examples

Tutorials

Edit mode

Design mode

Designing user interfaces

Hello Qt and OpenCV

Writing the code for a Qt project

Help mode

The Qt Creator Options window

Summary

Creating a Comprehensive Qt+OpenCV Project

Behind the scenes

The qmake tool

Meta-Object Compiler (moc)

User Interface Compiler (uic)

Design patterns

Qt Resource System

Styling applications

Selector types

Sub-controls

Pseudo-states

Cascading

Multi-language support

Creating and using plugins

The interface

The plugin

The plugin loader and user

Creating the foundations

Summary

Mat and QImage

All about the Mat class

Constructors, properties, and methods

The Mat_<_Tp> class

Matx< _Tp, m, n >

The UMat class

InputArray, OutputArry, InputOutputArray

Reading images using OpenCV

Writing images using OpenCV

Reading and writing videos in OpenCV

The HighGUI module in OpenCV

Image and video handling in Qt

The QImage class

The QPixmap class

The QImageReader and QImageWriter classes

The QPainter class

Camera and video handling in Qt

Summary

The Graphics View Framework

The Scene-View-Item architecture

The Scene, QGraphicsScene

The Items, QGraphicsItem

The View, QGraphicsView

Summary

Image Processing in OpenCV

Image filtering

Filtering functions in OpenCV

Image transformation capabilities

Geometric transformations

Miscellaneous transformations

Colors and color spaces

Image thresholding

Discrete Fourier transform

Drawing in OpenCV

Template matching

Summary

Features and Descriptors

Base of all algorithms – the Algorithm class

The 2D Features Framework

Detecting features

KAZE and AKAZE

The BRISK class

FAST

GFTT (Good Features to Track)

ORB

Extracting and matching descriptors

How to choose an algorithm

Accuracy

Speed

Resource usage

Availability

Summary

Multithreading

Multithreading in Qt

Low-level multithreading using QThread

Subclassing QThread

Using the moveToThread function

Thread synchronization tools

Mutexes

Read-write locks

Semaphores

Wait conditions

High-level multithreading using QtConcurrent

Summary

Video Analysis

Understanding histograms

Understanding back-projection images

Histogram comparison

Histogram equalization

MeanShift and CamShift

Background/foreground detection

Summary

Debugging and Testing

Debugging with Qt Creator

Getting started with the debugging mode

Qt Test Framework

Creating a Unit Test

Data-driven testing

Benchmarking

GUI testing

testcase projects

Summary

Linking and Deployment

The build process, behind the scenes

Preprocessing

Compiling

Linking

Building OpenCV static libraries

Building Qt static libraries

Deploying Qt+OpenCV applications

Deploying using static linking

Deploying using dynamic linking

Qt Installer Framework

Summary

Qt Quick Applications

Introduction to QML

User interaction and scripting in QML

Using Qt Quick Designer

Structure of a Qt Quick Application

Integrating C++ and QML codes

Qt and OpenCV apps on Android and iOS

Summary

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