We have come a long way since the start of our computer vision journey with OpenCV 3 and Qt5 Frameworks. We can now very easily install these powerful frameworks and configure a computer running a Windows, macOS, or Linux operating system so that we can design and build computer vision applications. Over the course of the previous chapters, we learned how to use the Qt plugin system to build modular and plugin-based applications. We learned how to style our apps using Qt Style Sheets and also make them support multiple languages by using the internationalization technologies in Qt. We built powerful graphics viewer applications using the Qt Graphics View Framework. The classes in this framework helped us deal with displaying graphical items much more efficiently and with much more flexibility. We were able to build graphics viewers that could zoom in and out of images without having to deal with the source image itself (thanks to the Scene-View-Item Architecture...
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.
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