Apart from everything we have seen up until now throughout this book, there is another side to the computer vision story, and that is dealing with videos, cameras, and essentially real-time processing of the input frames. It is one of the most popular computer vision topics and for good reason, since it can power live machines or devices that monitor their surroundings for objects of interest, movements, patterns, colors, and so on. All of the algorithms and classes that we have learned about, especially in Chapter 6, Image Processing in OpenCV and Chapter 7, Features and Descriptors, were meant to work with a single image, and for this same reason they can be easily applied to individual video frames in the exact same way. We only need to make sure individual frames are correctly read (for instance using the cv::VideoCapture class) into cv::Mat class instances...
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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 (14 chapters)
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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