此节介绍的架构模式（MVC），将联合使用模型-视图-控制器（Model-View-Controller）三个模式以及其他的类。其清晰地分离程序中的逻辑部分与用户交互部分。此节将使用MVC模式构建一个基于QT的图形界面应用程序。
模型包含关于应用程序的信息，它拥有所有由应用程序处理的数据。当出现新的数据，它将告知控制器，后者要求视图来显示结果。通常模型将集合多个算法，它们很有可能按照策略模式进行实现。
视图职责之一是发送用户的命令到控制器。当新数据可用时，它会刷新自己以显示新的信息。
控制器将视图和模型桥接在一起。接收视图的请求，并转化为模型中的合适方法。它也会在模型更改状态时，得到通知，并请求视图刷新以显示新的信息。
本模型使用ColorDetector类，包含应用程序的逻辑和底层数据。然后实现一个控制器即ColorDetectController类。MVC架构下，用户界面只是简单地调用控制器方法，不包含任何应用数据，也没实现任何应用逻辑。因此，容易替换接口。
#include <QApplication>
#include "mainwindow.h"
int main(int argc, char *argv[])
{
QApplication a(argc, argv);
MainWindow w;
w.show();
return a.exec();
}
main.cpp
#include "mainwindow.h"
#include "ui_mainwindow.h"
MainWindow::MainWindow(QWidget *parent) :
QMainWindow(parent),
ui(new Ui::MainWindow)
{
ui->setupUi(this);
//select color
connect(ui->pushButton_color, SIGNAL(clicked()), this, SLOT(setColor()));
connect(ui->actionChoose_Color, SIGNAL(triggered()), this, SLOT(setColor()));
//open image
connect(ui->pushButton_openImage, SIGNAL(clicked()), this, SLOT(setImage()));
connect(ui->actionOpen_Image, SIGNAL(triggered()), this, SLOT(setImage()));
//process Color Detection
connect(ui->pushButton_process, SIGNAL(clicked()), this, SLOT(processColorDetection()));
connect(ui->actionProcess, SIGNAL(triggered()), this, SLOT(processColorDetection()));
}
MainWindow::~MainWindow()
{
delete ui;
}
void MainWindow::changeEvent(QEvent *e)
{
QMainWindow::changeEvent(e);
switch (e->type()) {
case QEvent::LanguageChange:
ui->retranslateUi(this);
break;
default:
break;
}
}
void MainWindow::setImage()
{
QFileDialog::Options options;
QString selectedFilter;
QString fileName = QFileDialog::getOpenFileName(this,
tr("Open Image Files"),
"",
tr("Image files (*.jpg *.jpeg *.png *.gif *.bmp)"),
&selectedFilter,
options);
if (!fileName.isEmpty()){
//在Qt的应用程序中定义的fileName是QString类型，而cout只能输出String类型
//要将QString类型转换为String类型
cv::Mat img_mat = cv::imread(fileName.toStdString(),1); //0 for grayscale
displayMat(img_mat);
}
//Set Filename
ColorDetectController::getInstance()->setInputImage(fileName.toStdString());
}
//Convert cv::Mat to QImage and display
void MainWindow::displayMat(const cv::Mat& image){
//BGR openCV Mat to QImage
QImage img_qt = QImage((const unsigned char*)image.data,image.cols, image.rows, image.step, QImage::Format_RGB888);
//For Binary Images
if (img_qt.isNull()){
//ColorTable for Binary Images
QVector<QRgb> colorTable;
for (int i = 0; i < 256; i++)
colorTable.push_back(qRgb(i, i, i));
img_qt = QImage((const unsigned char*)image.data,image.cols, image.rows, QImage::Format_Indexed8);
img_qt.setColorTable(colorTable);
}
//Display the QImage in the Label
//简单地转换一下为Image对象，rgbSwapped是为了显示效果色彩好一些。
QPixmap img_pix = QPixmap::fromImage(img_qt.rgbSwapped()); //BGR to RGB
// pix = pix.scaled(width*2,height*2,Qt::KeepAspectRatio);
// 将图片的宽和高都扩大两倍，并且在给定的矩形内保持宽高的比值
this->ui->label->setPixmap(img_pix.scaled(ui->label->size(), Qt::KeepAspectRatio));
}
void MainWindow::on_verticalSlider_Threshold_valueChanged(int value)
{
QString cdt("Color Distance Threshold: ");
cdt.append(QString::number(value));
this->ui->label_2->setText(cdt);
}
void MainWindow::setColor()
{
QColor color = QColorDialog::getColor(Qt::green, this); //打开颜色对话框时，默认是Qt::white
if (color.isValid()) {
ColorDetectController::getInstance()->setTargetColor(color.red(),color.green(),color.blue());
}
}
void MainWindow::processColorDetection()
{
ColorDetectController::getInstance()->setColorDistanceThreshold(ui->verticalSlider_Threshold->value());
ColorDetectController::getInstance()->process();
cv::Mat resulting = ColorDetectController::getInstance()->getLastResult();
if (!resulting.empty())
displayMat(resulting);
}
mainwindow.cpp
#ifndef MAINWINDOW_H
#define MAINWINDOW_H
#include <QMainWindow>
#include <QFileDialog>
#include <QColorDialog>
//OpenCV
#include "cv.h"
#include "highgui.h"
//color detector, controller
#include "colorDetectController.h"
#include "colordetector.h"
namespace Ui {
class MainWindow;
}
class MainWindow : public QMainWindow {
Q_OBJECT
public:
MainWindow(QWidget *parent = 0);
~MainWindow();
protected:
void changeEvent(QEvent *e);
void displayMat(const cv::Mat& img);
//Main Image
//cv::Mat img_mat;
private:
Ui::MainWindow *ui;
private slots:
void on_pushButton_color_clicked();
void processColorDetection();
void on_verticalSlider_Threshold_valueChanged(int value);
void setColor();
void setImage();
};
#endif // MAINWINDOW_H
mainwindow.h
#include "colorDetectController.h" ColorDetectController *ColorDetectController::singleton=0;
colorDetectController.cpp
#if !defined CD_CNTRLLR
#define CD_CNTRLLR
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include "colordetector.h"
class ColorDetectController {
private:
static ColorDetectController *singleton; // pointer to the singleton
ColorDetector *cdetect;
// The image to be processed
cv::Mat image;
cv::Mat result;
public:
ColorDetectController() { // private constructor
//setting up the application
cdetect= new ColorDetector();
}
// Sets the color distance threshold
void setColorDistanceThreshold(int distance) {
cdetect->setColorDistanceThreshold(distance);
}
// Gets the color distance threshold
int getColorDistanceThreshold() const {
return cdetect->getColorDistanceThreshold();
}
// Sets the color to be detected
void setTargetColor(unsigned char red, unsigned char green, unsigned char blue) {
cdetect->setTargetColor(red,green,blue);
}
// Gets the color to be detected
void getTargetColor(unsigned char &red, unsigned char &green, unsigned char &blue) const {
cv::Vec3b color= cdetect->getTargetColor();
red= color[2];
green= color[1];
blue= color[0];
}
// Sets the input image. Reads it from file.
bool setInputImage(std::string filename) {
image= cv::imread(filename);
if (!image.data)
return false;
else
return true;
}
// Returns the current input image.
const cv::Mat getInputImage() const {
return image;
}
// Performs image processing.
void process() {
result= cdetect->process(image);
}
// Returns the image result from the latest processing.
const cv::Mat getLastResult() const {
return result;
}
// Deletes all processor objects created by the controller.
~ColorDetectController() {
delete cdetect;
}
// Singleton static members
static ColorDetectController *getInstance() {
if (singleton == 0)
singleton= new ColorDetectController;
return singleton;
}
// Releases the singleton instance of this controller.
static void destroy() {
if (singleton != 0) {
delete singleton;
singleton= 0;
}
}
};
colorDetectController.h
#include "colordetector.h"
cv::Mat ColorDetector::process(const cv::Mat &image) {
// re-allocate binary map if necessary
// same size as input image, but 1-channel
result.create(image.rows,image.cols,CV_8U);
// re-allocate intermediate image if necessary
converted.create(image.rows,image.cols,image.type());
// Converting to Lab color space
cv::cvtColor(image, converted, CV_BGR2Lab);
// get the iterators
cv::Mat_<cv::Vec3b>::iterator it= converted.begin<cv::Vec3b>();
cv::Mat_<cv::Vec3b>::iterator itend= converted.end<cv::Vec3b>();
cv::Mat_<uchar>::iterator itout= result.begin<uchar>();
// for each pixel
for ( ; it!= itend; ++it, ++itout) {
// process each pixel ---------------------
// compute distance from target color
if (getDistance(*it)<minDist) {
*itout= 255;
} else {
*itout= 0;
}
// end of pixel processing ----------------
}
return result;
}
colordetector.cpp
#if !defined COLORDETECT
#define COLORDETECT
#include <opencv2/core/core.hpp>
#include <opencv2/imgproc/imgproc.hpp>
class ColorDetector {
private:
// minimum acceptable distance
int minDist;
// target color
cv::Vec3b target;
// image containing resulting binary map
cv::Mat result;
// image containing color converted image
cv::Mat converted;
// inline private member function
// Computes the distance from target color.
int getDistance(const cv::Vec3b& color) const {
// return static_cast<int>(cv::norm<int,3>(cv::Vec3i(color[0]-target[0],color[1]-target[1],color[2]-target[2])));
return abs(color[0]-target[0])+
abs(color[1]-target[1])+
abs(color[2]-target[2]);
}
public:
// empty constructor
ColorDetector() : minDist(100) {
// default parameter initialization here
target[0]= target[1]= target[2]= 0;
}
// Getters and setters
// Sets the color distance threshold.
// Threshold must be positive, otherwise distance threshold
// is set to 0.
void setColorDistanceThreshold(int distance) {
if (distance<0)
distance=0;
minDist= distance;
}
// Gets the color distance threshold
int getColorDistanceThreshold() const {
return minDist;
}
// Sets the color to be detected
void setTargetColor(unsigned char red, unsigned char green, unsigned char blue) {
cv::Mat tmp(1,1,CV_8UC3); //创建一个一行一列有三通道像素
tmp.at<cv::Vec3b>(0,0)[0]= blue;
tmp.at<cv::Vec3b>(0,0)[1]= green;
tmp.at<cv::Vec3b>(0,0)[2]= red;
// Converting the target to Lab color space
cv::cvtColor(tmp, tmp, CV_BGR2Lab); //使用/usr/local/lib/libopencv_imgproc.so
target= tmp.at<cv::Vec3b>(0,0);
}
// Sets the color to be detected
void setTargetColor(cv::Vec3b color) {
cv::Mat tmp(1,1,CV_8UC3);
tmp.at<cv::Vec3b>(0,0)= color;
// Converting the target to Lab color space
cv::cvtColor(tmp, tmp, CV_BGR2Lab);
target= tmp.at<cv::Vec3b>(0,0);
}
// Gets the color to be detected
cv::Vec3b getTargetColor() const {
return target;
}
// Processes the image. Returns a 1-channel binary image.
cv::Mat process(const cv::Mat &image);
};
#endif
colordetector.h
时间： 2024-10-01 19:42:33