Linux 下 QT 配合 OpenCV 完成图像处理 (实现基本的人脸检测)
作者:DS小龙哥
- 2022 年 7 月 15 日
本文字数:3491 字
阅读完需:约 11 分钟
一、环境介绍
ubuntu 版本: VM 虚拟机运行 ubuntu18.04 64 位
OpenCV 版本: 3.4.9
QT 版本: 5.12
二、建立 QT 工程加入 OpenCV 依赖库
下面编写例子很简单,使用 OpenCV 自带的分类器,检测一张图中的人脸,并圈出来。
opencv 源码自带的人脸检测分类器目录:opencv-3.4.9/data/haarcascades_cuda/haarcascade_frontalface_alt2.xml
xxx.pro 工程文件代码:
QT += core gui
greaterThan(QT_MAJOR_VERSION, 4): QT += widgets
CONFIG += c++11
# The following define makes your compiler emit warnings if you use
# any Qt feature that has been marked deprecated (the exact warnings
# depend on your compiler). Please consult the documentation of the
# deprecated API in order to know how to port your code away from it.
DEFINES += QT_DEPRECATED_WARNINGS
# You can also make your code fail to compile if it uses deprecated APIs.
# In order to do so, uncomment the following line.
# You can also select to disable deprecated APIs only up to a certain version of Qt.
#DEFINES += QT_DISABLE_DEPRECATED_BEFORE=0x060000 # disables all the APIs deprecated before Qt 6.0.0
SOURCES += \
main.cpp \
widget.cpp
HEADERS += \
widget.h
FORMS += \
widget.ui
# Default rules for deployment.
qnx: target.path = /tmp/$${TARGET}/bin
else: unix:!android: target.path = /opt/$${TARGET}/bin
!isEmpty(target.path): INSTALLS += target
#linu平台的路径设置
linux {
#添加opencv头文件的路径,需要根据自己的头文件路径进行修改
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.so
LIBS+=/home/wbyq/work_pc/opencv-3.4.9/_install/install/lib/libopencv_core.so
LIBS+=/home/wbyq/work_pc/opencv-3.4.9/_install/install/lib/libopencv_dnn.so
LIBS+=/home/wbyq/work_pc/opencv-3.4.9/_install/install/lib/libopencv_features2d.so
LIBS+=/home/wbyq/work_pc/opencv-3.4.9/_install/install/lib/libopencv_flann.so
LIBS+=/home/wbyq/work_pc/opencv-3.4.9/_install/install/lib/libopencv_highgui.so
LIBS+=/home/wbyq/work_pc/opencv-3.4.9/_install/install/lib/libopencv_imgcodecs.so
LIBS+=/home/wbyq/work_pc/opencv-3.4.9/_install/install/lib/libopencv_imgproc.so
LIBS+=/home/wbyq/work_pc/opencv-3.4.9/_install/install/lib/libopencv_ml.so
LIBS+=/home/wbyq/work_pc/opencv-3.4.9/_install/install/lib/libopencv_objdetect.so
LIBS+=/home/wbyq/work_pc/opencv-3.4.9/_install/install/lib/libopencv_photo.so
LIBS+=/home/wbyq/work_pc/opencv-3.4.9/_install/install/lib/libopencv_shape.so
LIBS+=/home/wbyq/work_pc/opencv-3.4.9/_install/install/lib/libopencv_stitching.so
LIBS+=/home/wbyq/work_pc/opencv-3.4.9/_install/install/lib/libopencv_superres.so
LIBS+=/home/wbyq/work_pc/opencv-3.4.9/_install/install/lib/libopencv_videoio.so
LIBS+=/home/wbyq/work_pc/opencv-3.4.9/_install/install/lib/libopencv_video.so
}
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widget.cpp 文件代码:
#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;
}
//分类器的路径
#define source_xml_addr "/home/wbyq/work_pc/opencv-3.4.9/data/haarcascades_cuda/haarcascade_frontalface_alt2.xml"
//将要检测的图片路径
#define source_pix_addr "/mnt/hgfs/linux-share-dir/1.jpg"
//人脸检测代码
void Widget::opencv_face()
{
static CvMemStorage* storage = 0;
static CvHaarClassifierCascade* cascade = 0;
fprintf( stderr, "start------------------------------>1 \n" );
const char*cascade_name =source_xml_addr;
//加载分类器
cascade = (CvHaarClassifierCascade*)cvLoad( cascade_name, 0, 0, 0 );
if( !cascade )
{
fprintf( stderr, "ERROR: Could not load classifier cascade\n" );
return ;
}
//创建内存空间
storage = cvCreateMemStorage(0);
//加载需要检测的图片
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}}
};//Just some pretty colors to draw with
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); //直方图均衡
cvClearMemStorage(storage);
double t = (double)cvGetTickCount();
CvSeq* objects = cvHaarDetectObjects(small_img,
cascade,
storage,
1.1,
2,
0/*CV_HAAR_DO_CANNY_PRUNING*/,
cvSize(30,30));
t = (double)cvGetTickCount() - t;
fprintf( stderr, "start------------------------------>3 \n" );
//遍历找到对象和周围画盒
for(int i=0;i<(objects->total);++i)
{
CvRect* r=(CvRect*)cvGetSeqElem(objects,i);
cvRectangle(img, cvPoint(r->x*scale,r->y*scale), cvPoint((r->x+r->width)*scale,(r->y+r->height)*scale), colors[i%8]);
}
fprintf( stderr, "start------------------------------>4 \n" );
for( int i = 0; i < (objects? objects->total : 0); i++ )
{
CvRect* r = (CvRect*)cvGetSeqElem( objects, i );
CvPoint center;
int radius;
center.x = cvRound((r->x + r->width*0.5)*scale);
center.y = cvRound((r->y + r->height*0.5)*scale);
radius = cvRound((r->width + r->height)*0.25*scale);
cvCircle( img, center, radius, colors[i%8], 3, 8, 0 );
}
show_face(img); //显示检测的结果
cvReleaseImage(&gray);
cvReleaseImage(&small_img);
//释放图片
cvReleaseImage( &img );
}
//显示检测的结果
void Widget::show_face(IplImage* img)
{
/*将opecv的图片转为qimage格式*/
uchar *imgData=(uchar *)img->imageData;
QImage my_image(imgData,img->width,img->height,QImage::Format_RGB888);
my_image =my_image.rgbSwapped(); //BGR格式转RGB
QPixmap my_pix; //创建画图类
my_pix.convertFromImage(my_image);
/*在控件上显示*/
ui->label_display_face->setPixmap(my_pix);
}
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widget.h 文件代码:
#ifndef WIDGET_H
#define WIDGET_H
#include <QWidget>
//opencv include
#include <cv.h>
#include <cxcore.h>
#include <highgui.h>
QT_BEGIN_NAMESPACE
namespace Ui { class Widget; }
QT_END_NAMESPACE
class Widget : public QWidget
{
Q_OBJECT
public:
Widget(QWidget *parent = nullptr);
void opencv_face();
~Widget();
void show_face(IplImage* img);
private:
Ui::Widget *ui;
};
#endif // WIDGET_H
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运行代码检测结果如下:
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发布于: 刚刚阅读数: 4
版权声明: 本文为 InfoQ 作者【DS小龙哥】的原创文章。
原文链接:【http://xie.infoq.cn/article/96a0aa64912c356841d6030d0】。文章转载请联系作者。
DS小龙哥
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之所以觉得累,是因为说的比做的多。 2022.01.06 加入
熟悉C/C++、51单片机、STM32、Linux应用开发、Linux驱动开发、音视频开发、QT开发. 目前已经完成的项目涉及音视频、物联网、智能家居、工业控制领域
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