Using Qt Widgets Application
projects allows the creation of flexible and powerful GUIs by using the Qt Creator Design mode, or manually modifying the GUI files (*.ui
) in a text editor. Up until now and throughout the chapters of this book, we relied on Qt Widgets applications as the basis for the GUIs that we created, and as we learned in Chapter 3, Creating a Comprehensive Qt+OpenCV Project, we use style sheets to effectively alter the look and feel of our Qt applications. But apart from Qt Widgets applications and using QtWidgets
and QtGui
modules, there is another approach to the creation of GUIs that is offered by the Qt Framework. This approach is based on the QtQuick
module and the QML language, and it allows the creation of far more flexible (in terms of the look, feel, animations, effects, and so on) GUIs and with much more ease. Applications created by using this approach are referred to as Qt Quick applications. Note that in more recent Qt versions...
Computer Vision with OpenCV 3 and Qt5
By :
Computer Vision with OpenCV 3 and Qt5
By:
Overview of this book
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, and how 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.
Table of Contents (19 chapters)
Title Page
Dedication
Packt Upsell
Foreword
Contributors
Preface
Free Chapter
Introduction to OpenCV and Qt
Creating Our First Qt and OpenCV Project
Creating a Comprehensive Qt+OpenCV Project
Mat and QImage
The Graphics View Framework
Image Processing in OpenCV
Features and Descriptors
Multithreading
Video Analysis
Debugging and Testing
Linking and Deployment
Qt Quick Applications
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Customer Reviews