Professional applications never end up being professional because of some random circumstances. They are designed like this from the very beginning. Of course, it is easier said than done, but it's still quite easy if you already know the golden rule of how to create applications that can be easily extended, maintained, scaled, and customized. The golden rule here is just one simple concept, which fortunately Qt framework already has the means to implement, and that is building applications in a modular fashion. Note that modular in this sense doesn't just mean libraries or different source code modules, but modular in the sense that each of the responsibilities and capabilities of the application is created and built independently of the others. This is, in fact, exactly the way Qt and OpenCV themselves are created. An application that is modularized can be extended very easily, even by different developers from different backgrounds...
Computer Vision with OpenCV 3 and Qt5
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Computer Vision with OpenCV 3 and Qt5
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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.
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Current Title:
Computer Vision with OpenCV 3 and Qt5
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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