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Computer Vision with OpenCV 3 and Qt5

Computer Vision with OpenCV 3 and Qt5

By : Amin Ahmadi Tazehkandi
4.5 (11)
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Computer Vision with OpenCV 3 and Qt5

Computer Vision with OpenCV 3 and Qt5

4.5 (11)
By: Amin Ahmadi Tazehkandi

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)
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Reading images using OpenCV

Now that we have learned all about the Mat class in OpenCV, we can move on to learn how to read images and fill a Mat class with an image to further process it. As you have seen briefly in the previous chapters, the imread function can be used to read images from the disk. Here's an example:

    Mat image = imread("c:/dev/test.jpg", IMREAD_GRAYSCALE | 
IMREAD_IGNORE_ORIENTATION);

imread simply takes a C++ std::string class as the first parameter and an ImreadModes flag as the second parameter. If for any reason the image cannot be read, then it returns an empty Mat class (data == NULL), otherwise, it returns a Mat class filled with the image pixels with the type and color specified in the second parameter. Depending on the availability of some image types in the platform, imread can read the following image types:

  • Windows bitmaps...
Visually different images
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