学习OpenCV——行人检测&人脸检测(总算运行出来了)

之前运行haar特征的adaboost算法人脸检测一直出错，加上今天的HOG&SVM行人检测程序，一直报错。

今天总算发现自己犯了多么白痴的错误——是因为外部依赖项lib文件没有添加完整，想一头囊死啊

做程序一定要心如止水！！！ 仔细查找！！！

1.人脸识别程序：

#include "cv.h"
#include "highgui.h"

#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>
using namespace std;

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

void detect_and_draw( IplImage* image );

const char* cascade_name =
"G:/OpenCV2.3.1/data/haarcascades/haarcascade_frontalface_alt.xml";
/* "haarcascade_profileface.xml";*/

int main()
{
    CvCapture* capture = 0;

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

    if( !cascade )
    {
        fprintf( stderr, "ERROR: Could not load classifier cascade/n" );
        //fprintf( stderr,
            //"Usage: facedetect --cascade=/"<cascade_path>"/[filename|camera_index]/n" );
        return -1;
    }
    storage = cvCreateMemStorage(0);


    cvNamedWindow( "result", 1 );


    const char* filename = "H:/test/face05.jpg";
    IplImage* image = cvLoadImage(filename );

    if( image )
    {
        detect_and_draw( image );
        cvWaitKey(0);
        cvReleaseImage( &image );
    }

    cvDestroyWindow("result");
    cvWaitKey(0);
    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 );
        }
    }

    cvShowImage( "result", img );
    cvReleaseImage( &gray );
    cvReleaseImage( &small_img );
}

2.行人检测程序

#include <cv.h>
#include <highgui.h>
#include <string>
#include <iostream>
#include <algorithm>
#include <iterator>

#include <stdio.h>
#include <string.h>
#include <ctype.h>

using namespace cv;
using namespace std;

void help()
{
    printf(
            "
Demonstrate the use of the HoG descriptor using
"
            "  HOGDescriptor::hog.setSVMDetector(HOGDescriptor::getDefaultPeopleDetector());
"
            "Usage:
"
            "./peopledetect (<image_filename> | <image_list>.txt)

");
}

int main(int argc, char** argv)
{
    Mat img;
    FILE* f = 0;
    char _filename[1024];

    if( argc == 1 )
    {
        printf("Usage: peopledetect (<image_filename> | <image_list>.txt)
");
        return 0;
    }

    img = imread(argv[1]);

    if( img.data )
    {
        strcpy(_filename, argv[1]);
    }
    else
    {
        f = fopen(argv[1], "rt");
        if(!f)
        {
            fprintf( stderr, "ERROR: the specified file could not be loaded
");
            return -1;
        }
    }

    HOGDescriptor hog;
    hog.setSVMDetector(HOGDescriptor::getDefaultPeopleDetector());//得到检测器
    namedWindow("people detector", 1);

    for(;;)
    {
        char* filename = _filename;
        if(f)
        {
            if(!fgets(filename, (int)sizeof(_filename)-2, f))
                break;
            //while(*filename && isspace(*filename))
            //  ++filename;
            if(filename[0] == '#')
                continue;
            int l = strlen(filename);
            while(l > 0 && isspace(filename[l-1]))
                --l;
            filename[l] = '';
            img = imread(filename);
        }
        printf("%s:
", filename);
        if(!img.data)
            continue;

        fflush(stdout);
        vector<Rect> found, found_filtered;
        double t = (double)getTickCount();
        // run the detector with default parameters. to get a higher hit-rate
        // (and more false alarms, respectively), decrease the hitThreshold and
        // groupThreshold (set groupThreshold to 0 to turn off the grouping completely).
        hog.detectMultiScale(img, found, 0, Size(8,8), Size(32,32), 1.05, 2);
        t = (double)getTickCount() - t;
        printf("tdetection time = %gms
", t*1000./cv::getTickFrequency());
        size_t i, j;
        for( i = 0; i < found.size(); i++ )
        {
            Rect r = found[i];
            for( j = 0; j < found.size(); j++ )
                if( j != i && (r & found[j]) == r)
                    break;
            if( j == found.size() )
                found_filtered.push_back(r);
        }
        for( i = 0; i < found_filtered.size(); i++ )
        {
            Rect r = found_filtered[i];
            // the HOG detector returns slightly larger rectangles than the real objects.
            // so we slightly shrink the rectangles to get a nicer output.
            r.x += cvRound(r.width*0.1);
            r.width = cvRound(r.width*0.8);
            r.y += cvRound(r.height*0.07);
            r.height = cvRound(r.height*0.8);
            rectangle(img, r.tl(), r.br(), cv::Scalar(0,255,0), 3);
        }
        imshow("people detector", img);
        int c = waitKey(0) & 255;
        if( c == 'q' || c == 'Q' || !f)
            break;
    }
    if(f)
        fclose(f);
    return 0;
}

注意：可能会出现tbb_debug.dll的问题，在G:OpenCV2.3.1uildcommon bbia32vc10中找到tbb.dll改名为tbb_debug.dll 加到程序绝对目录下即可

还有其他的解决方式：http://blog.csdn.net/scut1135/article/details/7329398

from: http://blog.csdn.net/yangtrees/article/details/7453987