opencv 图片中的 人脸检测

#include <opencv\cv.h>
#include <opencv\highgui.h>
#include <opencv\cxcore.h>
#include <stdio.h>

#include "opencv2/objdetect/objdetect.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/ml/ml.hpp"
#include <iostream>

using namespace std;

using namespace cv;

void detectAndDraw( Mat& img,

CascadeClassifier& cascade, CascadeClassifier& nestedCascade,

double scale);

String cascadeName = "haarcascade_frontalface_alt2.xml";//人脸的训练数据

//String nestedCascadeName = "./haarcascade_eye_tree_eyeglasses.xml";//人眼的训练数据

String nestedCascadeName = "haarcascade_eye.xml";//人眼的训练数据

int main( int argc, const char** argv )

{

Mat image;

CascadeClassifier cascade, nestedCascade;//创建级联分类器对象

double scale = 1.3;

image = imread( "lena.jpg", 1 );//读入lena图片

//image = imread("people_with_hands.png",1);

namedWindow( "result", 1 );//opencv2.0以后用namedWindow函数会自动销毁窗口

if( !cascade.load( cascadeName ) )//从指定的文件目录中加载级联分类器

{

cerr << "ERROR: Could not load classifier cascade" << endl;

return 0;

}

if( !nestedCascade.load( nestedCascadeName ) )

{

cerr << "WARNING: Could not load classifier cascade for nested objects" << endl;

return 0;

}

if( !image.empty() )//读取图片数据不能为空

{

detectAndDraw( image, cascade, nestedCascade, scale );

waitKey(0);

}

return 0;

}

void detectAndDraw( Mat& img,

CascadeClassifier& cascade, CascadeClassifier& nestedCascade,

double scale)

{

int i = 0;

double t = 0;

vector<Rect> faces;

const static Scalar colors[] =  { CV_RGB(0,0,255),

CV_RGB(0,128,255),

CV_RGB(0,255,255),

CV_RGB(0,255,0),

CV_RGB(255,128,0),

CV_RGB(255,255,0),

CV_RGB(255,0,0),

CV_RGB(255,0,255)} ;//用不同的颜色表示不同的人脸

Mat gray, smallImg( cvRound (img.rows/scale), cvRound(img.cols/scale), CV_8UC1 );//将图片缩小，加快检测速度

cvtColor( img, gray, CV_BGR2GRAY );//因为用的是类haar特征，所以都是基于灰度图像的，这里要转换成灰度图像

resize( gray, smallImg, smallImg.size(), 0, 0, INTER_LINEAR );//将尺寸缩小到1/scale,用线性插值

equalizeHist( smallImg, smallImg );//直方图均衡

t = (double)cvGetTickCount();//用来计算算法执行时间

//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, 2, 0

//|CV_HAAR_FIND_BIGGEST_OBJECT

//|CV_HAAR_DO_ROUGH_SEARCH

|CV_HAAR_SCALE_IMAGE

,

Size(30, 30) );

t = (double)cvGetTickCount() - t;//相减为算法执行的时间

printf( "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%8];

int radius;

center.x = cvRound((r->x + r->width*0.5)*scale);//还原成原来的大小

center.y = cvRound((r->y + r->height*0.5)*scale);

radius = cvRound((r->width + r->height)*0.25*scale);

circle( img, center, radius, color, 3, 8, 0 );

//检测人眼，在每幅人脸图上画出人眼

if( nestedCascade.empty() )

continue;

smallImgROI = smallImg(*r);

//和上面的函数功能一样

nestedCascade.detectMultiScale( smallImgROI, nestedObjects,

1.1, 2, 0

//|CV_HAAR_FIND_BIGGEST_OBJECT

//|CV_HAAR_DO_ROUGH_SEARCH

//|CV_HAAR_DO_CANNY_PRUNING

|CV_HAAR_SCALE_IMAGE

,

Size(30, 30) );

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, 3, 8, 0 );//将眼睛也画出来，和对应人脸的图形是一样的

}

}

cv::imshow( "result", img );

}