#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/core/core.hpp>
#include <opencv2/objdetect/objdetect.hpp> using namespace cv;
using namespace std; void detectAndDraw( Mat& img, CascadeClassifier& cascade,
CascadeClassifier& nestedCascade,
double scale, bool tryflip ); int main()
{
//VideoCapture cap(0); //打开默认摄像头
//if(!cap.isOpened())
//{
// return -1;
//}
Mat frame;
Mat edges; CascadeClassifier cascade, nestedCascade;
bool stop = false;
//训练好的文件名称，放置在可执行文件同目录下
cascade.load("D:\\opencv\\sources\\data\\haarcascades\\haarcascade_frontalface_alt.xml");
nestedCascade.load("D:\\opencv\\sources\\data\\haarcascades\\haarcascade_eye.xml");
frame = imread("E:\\tmpimg\\hezhao.jpg");
detectAndDraw( frame, cascade, nestedCascade,, );
waitKey();
//while(!stop)
//{
// cap>>frame;
// detectAndDraw( frame, cascade, nestedCascade,2,0 );
// if(waitKey(30) >=0)
// stop = true;
//}
return ;
}
void detectAndDraw( Mat& img, CascadeClassifier& cascade,
CascadeClassifier& nestedCascade,
double scale, bool tryflip )
{
int i = ;
double t = ;
//建立用于存放人脸的向量容器
vector<Rect> faces, faces2;
//定义一些颜色，用来标示不同的人脸
const static Scalar colors[] = {
CV_RGB(,,),
CV_RGB(,,),
CV_RGB(,,),
CV_RGB(,,),
CV_RGB(,,),
CV_RGB(,,),
CV_RGB(,,),
CV_RGB(,,)} ;
//建立缩小的图片，加快检测速度
//nt cvRound (double value) 对一个double型的数进行四舍五入，并返回一个整型数！
Mat gray, smallImg( cvRound (img.rows/scale), cvRound(img.cols/scale), CV_8UC1 );
//转成灰度图像，Harr特征基于灰度图
cvtColor( img, gray, CV_BGR2GRAY );
imshow("灰度",gray);
//改变图像大小，使用双线性差值
resize( gray, smallImg, smallImg.size(), , , INTER_LINEAR );
imshow("缩小尺寸",smallImg);
//变换后的图像进行直方图均值化处理
equalizeHist( smallImg, smallImg );
imshow("直方图均值处理",smallImg);
//程序开始和结束插入此函数获取时间，经过计算求得算法执行时间
t = (double)cvGetTickCount();
//检测人脸
//detectMultiScale函数中smallImg表示的是要检测的输入图像为smallImg，faces表示检测到的人脸目标序列，1.1表示
//每次图像尺寸减小的比例为1.1，2表示每一个目标至少要被检测到3次才算是真的目标(因为周围的像素和不同的窗口大
//小都可以检测到人脸),CV_HAAR_SCALE_IMAGE表示不是缩放分类器来检测，而是缩放图像，Size(30, 30)为目标的
//最小最大尺寸
cascade.detectMultiScale( smallImg, faces,
1.1, ,
//|CV_HAAR_FIND_BIGGEST_OBJECT
//|CV_HAAR_DO_ROUGH_SEARCH
|CV_HAAR_SCALE_IMAGE
,Size(, ));
//如果使能，翻转图像继续检测
if( tryflip )
{
flip(smallImg, smallImg, );
imshow("反转图像",smallImg);
cascade.detectMultiScale( smallImg, faces2,
1.1, ,
//|CV_HAAR_FIND_BIGGEST_OBJECT
//|CV_HAAR_DO_ROUGH_SEARCH
|CV_HAAR_SCALE_IMAGE
,Size(, ) );
for( vector<Rect>::const_iterator r = faces2.begin(); r != faces2.end(); r++ )
{
faces.push_back(Rect(smallImg.cols - r->x - r->width, r->y, r->width, r->height));
}
}
t = (double)cvGetTickCount() - t;
// qDebug( "detection time = %g ms\n", t/((double)cvGetTickFrequency()*1000.) );
for( vector<Rect>::const_iterator r = faces.begin(); r != faces.end(); r++, i++ )
{
Mat smallImgROI;
vector<Rect> nestedObjects;
Point center;
Scalar color = colors[i%];
int radius; double aspect_ratio = (double)r->width/r->height;
if( 0.75 < aspect_ratio && aspect_ratio < 1.3 )
{
//标示人脸时在缩小之前的图像上标示，所以这里根据缩放比例换算回去
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);
circle( img, center, radius, color, , , );
}
else
rectangle( img, cvPoint(cvRound(r->x*scale), cvRound(r->y*scale)),
cvPoint(cvRound((r->x + r->width-)*scale), cvRound((r->y + r->height-)*scale)),
color, , , );
if( nestedCascade.empty() )
continue;
smallImgROI = smallImg(*r);
//同样方法检测人眼
nestedCascade.detectMultiScale( smallImgROI, nestedObjects,
1.1, ,
//|CV_HAAR_FIND_BIGGEST_OBJECT
//|CV_HAAR_DO_ROUGH_SEARCH
//|CV_HAAR_DO_CANNY_PRUNING
|CV_HAAR_SCALE_IMAGE
,Size(, ) );
for( vector<Rect>::const_iterator nr = nestedObjects.begin(); nr != nestedObjects.end(); nr++ )
{
center.x = cvRound((r->x + nr->x + nr->width*0.5)*scale);
center.y = cvRound((r->y + nr->y + nr->height*0.5)*scale);
radius = cvRound((nr->width + nr->height)*0.25*scale);
circle( img, center, radius, color, , , );
}
}
imshow( "识别结果", img );
}
opencv 连接器配置
[debug]
opencv_ml2413d.lib
opencv_calib3d2413d.lib
opencv_contrib2413d.lib
opencv_core2413d.lib
opencv_features2d2413d.lib
opencv_flann2413d.lib
opencv_gpu2413d.lib
opencv_highgui2413d.lib
opencv_imgproc2413d.lib
opencv_legacy2413d.lib
opencv_objdetect2413d.lib
opencv_ts2413d.lib
opencv_video2413d.lib
opencv_nonfree2413d.lib
opencv_ocl2413d.lib
opencv_photo2413d.lib
opencv_stitching2413d.lib
opencv_superres2413d.lib
opencv_videostab2413d.lib [release]
opencv_ml2413.lib
opencv_calib3d2413.lib
opencv_contrib2413.lib
opencv_core2413.lib
opencv_features2d2413.lib
opencv_flann2413.lib
opencv_gpu2413.lib
opencv_highgui2413.lib
opencv_imgproc2413.lib
opencv_legacy2413.lib
opencv_objdetect2413.lib
opencv_ts2413.lib
opencv_video2413.lib
opencv_nonfree2413.lib
opencv_ocl2413.lib
opencv_photo2413.lib
opencv_stitching2413.lib
opencv_superres2413.lib
opencv_videostab2413.lib // 根据你的版本批量替换2413版本号