Mastering Qt 5 by Lazar Guillaume & Penea Robin

Author:Lazar, Guillaume & Penea, Robin
Language: eng
Format: epub
Publisher: Packt Publishing
Published: 2016-12-15T05:00:00+00:00

Implementing your OpenCV filters

Now that your development environment is ready, we can begin the fun part! We will implement three filters using OpenCV:

FilterOriginal: This filter does nothing and returns the same picture (lazy!)

FilterGrayscale: This filter converts a picture from color to grayscale

FilterBlur: This filter smoothes the picture

The parent class of all these filters is Filter. Here is this abstract class:

//Filter.h class Filter { public: Filter(); virtual ~Filter(); virtualQImage process(constQImage& image) = 0; }; //Filter.cpp Filter::Filter() {} Filter::~Filter() {}

As you can see, process() is a pure abstract method. All filters will implement a specific behavior with this function. Let's begin with the simple FilterOriginal class. Here is FilterOriginal.h:

class FilterOriginal : public Filter { public: FilterOriginal(); ~FilterOriginal(); QImageprocess(constQImage& image) override; };

This class inherits Filter and we override the process() function. The implementation is also really simple. Fill FilterOriginal.cpp with the following:

FilterOriginal::FilterOriginal() : Filter() { } FilterOriginal::~FilterOriginal() { } QImageFilterOriginal::process(constQImage& image) { return image; }

No modification is performed; we return the same picture. Now that the filter structure is clear, we can create FilterGrayscale. The .h/.cpp files are close to FilterOriginalFilter, so let's jump to the process() function of FilterGrayscale.cpp:

QImageFilterGrayscale::process(constQImage& image) { // QImage => cv::mat cv::Mattmp(image.height(), image.width(), CV_8UC4, (uchar*)image.bits(), image.bytesPerLine()); cv::MatresultMat; cv::cvtColor(tmp, resultMat, CV_BGR2GRAY); // cv::mat =>QImage QImageresultImage((constuchar *) resultMat.data, resultMat.cols, resultMat.rows, resultMat.step, QImage::Format_Grayscale8); returnresultImage.copy(); }

In the Qt framework, we use the QImage class to manipulate pictures. In the OpenCV world, we use the Mat class, so the first step is to create a correct Mat object from the QImage source. OpenCV and Qt both handle many image formats. An image format describes the data bytes organization with information such as the following:

Channel count: A grayscale picture only needs one channel (white intensity), while a color picture requires three channels (red, green, and blue). You will even need four channels to handle the opacity (alpha) pixel information.

Bit depth: The number of bits used to store a pixel color.

Channel order: The most common orders are RGB and BGR. Alpha can be placed before or after the color information.

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