OpenCV实例：对实时视频做人脸检测

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我是靠谱客的博主天真铃铛，最近开发中收集的这篇文章主要介绍OpenCV实例：对实时视频做人脸检测，觉得挺不错的，现在分享给大家，希望可以做个参考。

概述

OpenCV的人脸检测主要是调用训练好的cascade（Haar分类器）来进行模式匹配。

1. 新建项目

启动Code::Blocks，选择File->New->Project, 项目类型选择:Console Application,项目名为：MyFace，其他按默认选择。

2. 代码

打开main.cpp文件，输入以下代码：

#include <iostream>

using namespace std;

#include <videoInput.h>
#include <opencv2/opencv.hpp>

#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <assert.h>
#include <math.h>
#include <float.h>
#include <limits.h>
#include <time.h>
#include <ctype.h>

static CvMemStorage* storage = 0;
static CvHaarClassifierCascade* cascade = 0;

void detect_and_draw(IplImage* image);
const char* cascade_name = "haarcascade_frontalface_alt.xml";

int main(int argc, char** argv)
{
int width = 640;
int height = 400;

    videoInput video;//创建视频捕获对象
    video.setupDevice(0, width, height);//配置设备
    //video.showSettingsWindow(0);//该语句可以显示视频设置窗口，可以去掉

IplImage* frame, *frame_copy = 0;

int optlen = strlen("--cascade=");
const char* input_name;

    if(argc > 1 && strncmp(argv[1], "--cascade=", optlen) == 0)
    {
        cascade_name = argv[1] + optlen;
        input_name = argc > 2 ? argv[2] : 0;
    }
    else
    {
        input_name = argc > 1 ? argv[1] : 0;
    }

cascade = (CvHaarClassifierCascade*) cvLoad(cascade_name, 0, 0, 0);

    if(!cascade)
    {
        fprintf(stderr, "ERROR: Could not load classifier cascade/n");
        fprintf(stderr, "Usage: myface --cascade=/"<cascade_path>/" [filename]/n");
        return -1;
    }

    storage = cvCreateMemStorage(0);
    cvNamedWindow("result", 1);
    frame = cvCreateImage(cvSize(width,height), IPL_DEPTH_8U, 3);

    for(;;)
    {
        if(video.isFrameNew(0))
        {
            video.getPixels(0, (unsigned char *)frame->imageData, false, true);//获取一帧
        }

        if(!frame)
            break;
        if(!frame_copy)
            frame_copy = cvCreateImage(cvSize(frame->width, frame->height), IPL_DEPTH_8U, frame->nChannels);
        if(frame->origin == IPL_ORIGIN_TL)
            cvCopy(frame, frame_copy, 0);
        else
            cvFlip(frame, frame_copy, 0);

detect_and_draw(frame_copy);

        if(cvWaitKey(10) >= 0)
            break;
    }

cvReleaseImage(&frame_copy);
cvReleaseImage(&frame);

return 0;
}

void detect_and_draw( IplImage* img )
{
    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}}
    };

    double scale = 1.3;
    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 );
    int i;

    cvCvtColor( img, gray, CV_BGR2GRAY );
    cvResize( gray, small_img, CV_INTER_LINEAR );
    cvEqualizeHist( small_img, small_img );
    cvClearMemStorage( storage );

    if( cascade )
    {
        double t = (double)cvGetTickCount();
        CvSeq* faces = cvHaarDetectObjects( small_img, cascade, storage,
                                            1.1, 2, 0/*CV_HAAR_DO_CANNY_PRUNING*/,
                                            cvSize(30, 30) );
        t = (double)cvGetTickCount() - t;
        printf( "detection time = %gms/n", t/((double)cvGetTickFrequency()*1000.) );
        for( i = 0; i < (faces ? faces->total : 0); i++ )
        {
            CvRect* r = (CvRect*)cvGetSeqElem( faces, 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 );
        }
    }