qt+halcon实战

本文主要是介绍qt+halcon实战，希望对大家解决编程问题提供一定的参考价值，需要的开发者们随着小编来一起学习吧！

注意建QT工程项目用的是MSVC，如果选成MinGW,则会报错

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INCLUDEPATH += $$PWD/include
INCLUDEPATH += $$PWD/include/halconcppLIBS += $$PWD/lib/x64-win64/halconcpp.lib
LIBS += $$PWD/lib/x64-win64/halcon.lib

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#include "halconcpp/HalconCpp.h"
#include "Halcon.h"
#include "HDevThread.h"using namespace HalconCpp;

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#include "mainwindow.h"
#include "ui_mainwindow.h"
#include "QDebug"
#include "QFileDialog"
MainWindow::MainWindow(QWidget *parent): QMainWindow(parent), ui(new Ui::MainWindow)
{ui->setupUi(this);Hlong windID=(Hlong)this->ui->graphicsView->winId();qDebug()<<ui->graphicsView->width()<< " : "<<ui->graphicsView->height();HalconCpp::OpenWindow(0,0,ui->graphicsView->width(),ui->graphicsView->height() ,windID, "visible" , "red",&hv_WindowHandle);SetPart(hv_WindowHandle,0,0,960,1280);SetDraw(hv_WindowHandle,"margin");SetColor(hv_WindowHandle,"red");
}MainWindow::~MainWindow()
{delete ui;
}void MainWindow::on_pushButton_clicked()
{QString path=QFileDialog::getOpenFileName(this,"Select Imagee","","(*.png *.bmp)");qDebug()<<path;if(path=="")return;HTuple h01=HTuple(path.toLatin1().data());// Local iconic variablesHObject  ho_Image, ho_Region, ho_ConnectedRegions;HObject  ho_SelectedConnectedRegions, ho_ImageReduced, ho_DerivGaussImage;HObject  ho_DerivGaussRegion, ho_DerivGaussConnectedRegions;HObject  ho_SelectedDerivGaussConnectedRegions, ho_RegionFillUp;HObject  ho_RegionDifference, ho_ResultConnectedRegions;HObject  ho_DefectResult;// Local control variablesHTuple  hv_ImageFiles, hv_Index;//关闭程序计数器,图形变量,窗口图形更新//  dev_update_off();//Image Acquisition 01: Code generated by Image Acquisition 01hv_ImageFiles = HTuple();hv_ImageFiles[0] = "1.bmp";HTuple end_val8 = (hv_ImageFiles.TupleLength())-1;HTuple step_val8 = 1;for (hv_Index=0; hv_Index.Continue(end_val8, step_val8); hv_Index += step_val8){qDebug()<<"hhhhh  001";//读取一张图像//ReadImage(&ho_Image, HTuple(hv_ImageFiles[hv_Index]));ReadImage(&ho_Image, h01);qDebug()<<"hhhhh  002";//分割出环形区域Threshold(ho_Image, &ho_Region, 100, 255);qDebug()<<"hhhhh  003";//对区域进行连通处理Connection(ho_Region, &ho_ConnectedRegions);qDebug()<<"hhhhh  004";//过滤出圆环区域SelectShape(ho_ConnectedRegions, &ho_SelectedConnectedRegions, (HTuple("area").Append("circularity")),"and", (HTuple(40000).Append(0.6)), (HTuple(99999).Append(1)));qDebug()<<"hhhhh  005";//将圆环区域中的图像剪切出来ReduceDomain(ho_Image, ho_SelectedConnectedRegions, &ho_ImageReduced);qDebug()<<"hhhhh  006";//将图像和高斯导数进行卷积运算DerivateGauss(ho_ImageReduced, &ho_DerivGaussImage, 1.5, "gradient");qDebug()<<"hhhhh  007";//分割出图像中的轮廓Threshold(ho_DerivGaussImage, &ho_DerivGaussRegion, 9, 50);qDebug()<<"hhhhh  008";//对轮廓区域进行连通处理Connection(ho_DerivGaussRegion, &ho_DerivGaussConnectedRegions);qDebug()<<"hhhhh  009";//获取的轮廓区域SelectShapeStd(ho_DerivGaussConnectedRegions, &ho_SelectedDerivGaussConnectedRegions,"max_area", 70);qDebug()<<"hhhhh  010";//填充该轮廓区域FillUp(ho_SelectedDerivGaussConnectedRegions, &ho_RegionFillUp);qDebug()<<"hhhhh  011";//求轮廓区域和填充的轮廓区域之间的补集区域Difference(ho_RegionFillUp, ho_SelectedDerivGaussConnectedRegions, &ho_RegionDifference);//对补集区域进行连通处理Connection(ho_RegionDifference, &ho_ResultConnectedRegions);qDebug()<<"hhhhh  012";//获取缺陷区域SelectShape(ho_ResultConnectedRegions, &ho_DefectResult, "area", "and", 50, 999);qDebug()<<"hhhhh  013";//显示图像if (HDevWindowStack::IsOpen()){DispObj(ho_Image, HDevWindowStack::GetActive());qDebug()<<"hhhhh  014";}DispObj(ho_Image, hv_WindowHandle);//显示缺陷区域DispObj(ho_DefectResult, hv_WindowHandle);qDebug()<<"hhhhh  0 66666";// stop(); only in hdevelop}}

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运行结果:

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下面是Halcon导出QT可以使用的c++脚本

FR：徐海涛(hunkxu)

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