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(
			"\nDemonstrate the use of the HoG descriptor using\n"
			"  HOGDescriptor::hog.setSVMDetector(HOGDescriptor::getDefaultPeopleDetector());\n"
			"Usage:\n"
			"./peopledetect (<image_filename> | <image_list>.txt)\n\n");
}

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)\n");
        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\n");
		    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] = '\0';
		    img = imread(filename);
	    }
	    printf("%s:\n", 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\n", 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:\OpenCV2.3.1\build\common\tbb\ia32\vc10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