vs13 opencv3.0 人脸检测

背景：使用opencv3.0进行人脸识别的第一步：完成人脸的检测
环境：vs2013,opencv3.0 alpha版
代码：由/source/samples/cpp/facedetect.cpp下更改而来

#include "opencv2/objdetect.hpp"
#include "opencv2/imgcodecs.hpp"
#include "opencv2/videoio.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/core/utility.hpp"

#include "opencv2/videoio/videoio_c.h"
#include "opencv2/highgui/highgui_c.h"

#include <cctype>
#include <iostream>
#include <iterator>
#include <stdio.h>

using namespace std;
using namespace cv;

static void help()
{
    cout << "\nThis program demonstrates the cascade recognizer. Now you can use Haar or LBP features.\n"
        "This classifier can recognize many kinds of rigid objects, once the appropriate classifier is trained.\n"
        "It‘s most known use is for faces.\n"
        "Usage:\n"
        "./facedetect [--cascade=<cascade_path> this is the primary trained classifier such as frontal face]\n"
        "   [--nested-cascade[=nested_cascade_path this an optional secondary classifier such as eyes]]\n"
        "   [--scale=<image scale greater or equal to 1, try 1.3 for example>]\n"
        "   [--try-flip]\n"
        "   [filename|camera_index]\n\n"
        "see facedetect.cmd for one call:\n"
        "./facedetect --cascade=\"../../data/haarcascades/haarcascade_frontalface_alt.xml\" --nested-cascade=\"../../data/haarcascades/haarcascade_eye.xml\" --scale=1.3\n\n"
        "During execution:\n\tHit any key to quit.\n"
        "\tUsing OpenCV version " << CV_VERSION << "\n" << endl;
}

void detectAndDraw(Mat& img, CascadeClassifier& cascade,
    CascadeClassifier& nestedCascade,
    double scale, bool tryflip);

//要使用到的两个cascade文件,用于联合检测人脸,opencv自带了多个xml文件，在opencv安装目录下的/source/data/haarcascades/ 文件夹内
string cascadeName = "C:\\opencv\\sources\\data\\haarcascades\\haarcascade_frontalface_alt.xml";

string nestedCascadeName = "C:\\opencv\\sources\\data\\haarcascades\\haarcascade_eye_tree_eyeglasses.xml";//检测眼睛

int main()
{
    CvCapture* capture = 0;
    Mat frame, frameCopy, image;
    CascadeClassifier cascade, nestedCascade;
    char *srcImageFile = "C:\\facetest\\psb.webp (59).jpg";//测试图片
    double scale = 1;
    if (!cascade.load(cascadeName))//载入cascade文件
    {
        cerr << "ERROR: Could not load classifier cascade" << endl;
        help();
        return -1;
    }
    image = imread(srcImageFile);


    cvNamedWindow("result", 1);

    cout << "In image read" << endl;
    if (!image.empty())
        {
            detectAndDraw(image, cascade, nestedCascade, scale, 0);//检测人脸
            waitKey(0);
        }
    cvDestroyWindow("result");
    return 0;
}

void detectAndDraw(Mat& img, CascadeClassifier& cascade,
    CascadeClassifier& nestedCascade,
    double scale, bool tryflip)
{
    int i = 0;
    double t = 0;
    vector<Rect> faces, faces2;
    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) };//用于画线
    Mat gray, smallImg(cvRound(img.rows / scale), cvRound(img.cols / scale), CV_8UC1);

    cvtColor(img, gray, COLOR_BGR2GRAY);
    resize(gray, smallImg, smallImg.size(), 0, 0, INTER_LINEAR);
    equalizeHist(smallImg, smallImg);

    t = (double)cvGetTickCount();
    cascade.detectMultiScale(smallImg, faces,
        1.1, 2, 0
        //|CASCADE_FIND_BIGGEST_OBJECT
        //|CASCADE_DO_ROUGH_SEARCH
        | CASCADE_SCALE_IMAGE
        ,
        Size(30, 30));
    if (tryflip)
    {
        flip(smallImg, smallImg, 1);
        cascade.detectMultiScale(smallImg, faces2,
            1.1, 2, 0
            //|CASCADE_FIND_BIGGEST_OBJECT
            //|CASCADE_DO_ROUGH_SEARCH
            | CASCADE_SCALE_IMAGE
            ,
            Size(30, 30));
        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;
    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;

        double aspect_ratio = (double)r->width / r->height;
        if (0.75 < aspect_ratio && aspect_ratio < 1.3)
        {
            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, 3, 8, 0);
        }
        else
            rectangle(img, cvPoint(cvRound(r->x*scale), cvRound(r->y*scale)),
            cvPoint(cvRound((r->x + r->width - 1)*scale), cvRound((r->y + r->height - 1)*scale)),
            color, 3, 8, 0);
        if (nestedCascade.empty())
            continue;
        smallImgROI = smallImg(*r);
        nestedCascade.detectMultiScale(smallImgROI, nestedObjects,
            1.1, 2, 0
            //|CASCADE_FIND_BIGGEST_OBJECT
            //|CASCADE_DO_ROUGH_SEARCH
            //|CASCADE_DO_CANNY_PRUNING
            | CASCADE_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);
        }
    }
    cv::imshow("result", img);
}

运行一发：