学习OpenCV——行人识别&人脸识别(总算运行出来了)

转自：http://blog.csdn.net/sangni007/article/details/7453987

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