一、环境概述
在虚拟机上运行的Ubuntu 18.04 64位操作系统搭配了OpenCV 3.4.9和QT 5.12版本。关于在Ubuntu上编译OpenCV的详细步骤，请参考链接：https://www.php.cn/link/1c1f1beef683946794edf22079849283。
二、创建QT工程并集成OpenCV库
以下提供了一个简单的示例，利用OpenCV内置的分类器对图像进行人脸检测并标记。
OpenCV源码中的人脸检测分类器位于：opencv-3.4.9/data/haarcascades_cuda/haarcascade_frontalface_alt2.xml。
xxx.pro项目文件如下：
QT += core guigreaterThan(QT_MAJOR_VERSION, 4): QT += widgetsCONFIG += c++11DEFINES += QT_DEPRECATED_WARNINGS
SOURCES += main.cpp widget.cpp
HEADERS += widget.h
FORMS += widget.ui
qnx: target.path = /tmp/$${TARGET}/binelse: unix:!android: target.path = /opt/$${TARGET}/bin!isEmpty(target.path): INSTALLS += target
linux {INCLUDEPATH += /home/wbyq/work_pc/opencv-3.4.9/_install/install/include /home/wbyq/work_pc/opencv-3.4.9/_install/install/include/opencv /home/wbyq/work_pc/opencv-3.4.9/_install/install/include/opencv2
LIBS += /home/wbyq/work_pc/opencv-3.4.9/_install/install/lib/libopencv_calib3d.soLIBS += /home/wbyq/work_pc/opencv-3.4.9/_install/install/lib/libopencv_core.soLIBS += /home/wbyq/work_pc/opencv-3.4.9/_install/install/lib/libopencv_dnn.soLIBS += /home/wbyq/work_pc/opencv-3.4.9/_install/install/lib/libopencv_features2d.soLIBS += /home/wbyq/work_pc/opencv-3.4.9/_install/install/lib/libopencv_flann.soLIBS += /home/wbyq/work_pc/opencv-3.4.9/_install/install/lib/libopencv_highgui.soLIBS += /home/wbyq/work_pc/opencv-3.4.9/_install/install/lib/libopencv_imgcodecs.soLIBS += /home/wbyq/work_pc/opencv-3.4.9/_install/install/lib/libopencv_imgproc.soLIBS += /home/wbyq/work_pc/opencv-3.4.9/_install/install/lib/libopencv_ml.soLIBS += /home/wbyq/work_pc/opencv-3.4.9/_install/install/lib/libopencv_objdetect.soLIBS += /home/wbyq/work_pc/opencv-3.4.9/_install/install/lib/libopencv_photo.soLIBS += /home/wbyq/work_pc/opencv-3.4.9/_install/install/lib/libopencv_shape.soLIBS += /home/wbyq/work_pc/opencv-3.4.9/_install/install/lib/libopencv_stitching.soLIBS += /home/wbyq/work_pc/opencv-3.4.9/_install/install/lib/libopencv_superres.soLIBS += /home/wbyq/work_pc/opencv-3.4.9/_install/install/lib/libopencv_videoio.soLIBS += /home/wbyq/work_pc/opencv-3.4.9/_install/install/lib/libopencv_video.so}
widget.cpp文件内容如下：
#include "widget.h"include "ui_widget.h"
Widget::Widget(QWidget *parent): QWidget(parent), ui(new Ui::Widget){ui->setupUi(this);opencv_face();}
Widget::~Widget(){delete ui;}
define source_xml_addr "/home/wbyq/work_pc/opencv-3.4.9/data/haarcascades_cuda/haarcascade_frontalface_alt2.xml"
define source_pix_addr "/mnt/hgfs/linux-share-dir/1.jpg"
void Widget::opencv_face(){static CvMemStorage storage = 0;static CvHaarClassifierCascade cascade = 0;fprintf( stderr, "start------------------------------>1 n" );const char cascade_name = source_xml_addr;cascade = (CvHaarClassifierCascade)cvLoad( cascade_name, 0, 0, 0 );if( !cascade ){fprintf( stderr, "ERROR: Could not load classifier cascaden" );return ;}storage = cvCreateMemStorage(0);const char filename = source_pix_addr;IplImage img = cvLoadImage( filename, 1 );if(img == nullptr ){fprintf( stderr, "jpg load error! n" );return;}fprintf( stderr, "start------------------------------>2 n" );double scale = 1.2;static CvScalar colors[] = {{{0,0,255}},{{0,128,255}},{{0,255,255}},{{0,255,0}},{{255,128,0}},{{255,255,0}},{{255,0,0}},{{255,0,255}}};IplImage gray = cvCreateImage(cvSize(img->width,img->height),8,1);IplImage small_img = cvCreateImage(cvSize(cvRound(img->width/scale),cvRound(img->height/scale)),8,1);cvCvtColor(img,gray, CV_BGR2GRAY);cvResize(gray, small_img, CV_INTER_LINEAR);cvEqualizeHist(small_img,small_img);cvClearMemStorage(storage);double t = (double)cvGetTickCount();CvSeq objects = cvHaarDetectObjects(small_img,cascade,storage,1.1,2,0,cvSize(30,30));t = (double)cvGetTickCount() - t;fprintf( stderr, "start------------------------------>3 n" );for(int i=0; i total; ++i){CvRect r = (CvRect)cvGetSeqElem(objects,i);cvRectangle(img, cvPoint(r->xscale,r->yscale), cvPoint((r->x+r->width)scale,(r->y+r->height)scale), colors[i%8]);}fprintf( stderr, "start------------------------------>4 n" );for( int i = 0; i total; i++ ){CvRect r = (CvRect)cvGetSeqElem( objects, i );CvPoint center;int radius;center.x = cvRound((r->x + r->width0.5)scale);center.y = cvRound((r->y + r->height0.5)scale);radius = cvRound((r->width + r->height)0.25*scale);cvCircle( img, center, radius, colors[i%8], 3, 8, 0 );}show_face(img);cvReleaseImage(&gray);cvReleaseImage(&small_img);cvReleaseImage( &img );}
void Widget::show_face(IplImage img){uchar imgData = (uchar *)img->imageData;QImage my_image(imgData,img->width,img->height,QImage::Format_RGB888);my_image = my_image.rgbSwapped();QPixmap my_pix;my_pix.convertFromImage(my_image);ui->label_display_face->setPixmap(my_pix);}
widget.h文件内容如下：
#ifndef WIDGET_Hdefine WIDGET_H
include
include
include
include
QT_BEGIN_NAMESPACEnamespace Ui { class Widget; }QT_END_NAMESPACE
class Widget : public QWidget{Q_OBJECT
public:Widget(QWidget parent = nullptr);~Widget();void opencv_face();void show_face(IplImage img);
private:Ui::Widget *ui;};
endif // WIDGET_H
运行上述代码后，人脸检测结果展示如下：
以上就是Linux下QT配合OpenCV完成图像处理(实现基本的人脸检测)的详细内容，更多请关注创想鸟其它相关文章！
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