opencv 人脸和行人识别

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：

[cpp] view plain copy print ?

1. #include "cv.h"   
2. #include "highgui.h"   
3.   
4. #include <stdio.h>   
5. #include <stdlib.h>   
6. #include <string.h>   
7. #include <assert.h>   
8. #include <math.h>   
9. #include <float.h>   
10. #include <limits.h>   
11. #include <time.h>   
12. #include <ctype.h>   
13. using namespace std;  
14.   
15. static CvMemStorage* storage = 0;  
16. static CvHaarClassifierCascade* cascade = 0;  
17.   
18. void detect_and_draw( IplImage* image );  
19.   
20. const char* cascade_name =  
21. "G:/OpenCV2.3.1/data/haarcascades/haarcascade_frontalface_alt.xml";  
22. /* "haarcascade_profileface.xml";*/  
23.   
24. int main()  
25. {  
26.     CvCapture* capture = 0;  
27.   
28.     cascade = (CvHaarClassifierCascade*)cvLoad( cascade_name, 0, 0, 0 );  
29.   
30.     if( !cascade )  
31.     {  
32.         fprintf( stderr, "ERROR: Could not load classifier cascade/n" );  
33.         //fprintf( stderr,   
34.             //"Usage: facedetect --cascade=/"<cascade_path>"/[filename|camera_index]/n" );   
35.         return -1;  
36.     }  
37.     storage = cvCreateMemStorage(0);  
38.   
39.   
40.     cvNamedWindow( "result", 1 );  
41.   
42.   
43.     const char* filename = "H:/test/face05.jpg";  
44.     IplImage* image = cvLoadImage(filename );  
45.   
46.     if( image )  
47.     {  
48.         detect_and_draw( image );  
49.         cvWaitKey(0);  
50.         cvReleaseImage( &image );  
51.     }  
52.   
53.     cvDestroyWindow("result");  
54.     cvWaitKey(0);  
55.     return 0;  
56. }  
57.   
58. void detect_and_draw( IplImage* img )  
59. {  
60.     static CvScalar colors[] =   
61.     {  
62.         {{0,0,255}},  
63.         {{0,128,255}},  
64.         {{0,255,255}},  
65.         {{0,255,0}},  
66.         {{255,128,0}},  
67.         {{255,255,0}},  
68.         {{255,0,0}},  
69.         {{255,0,255}}  
70.     };  
71.   
72.     double scale = 1.3;  
73.     IplImage* gray = cvCreateImage( cvSize(img->width,img->height), 8, 1 );  
74.     IplImage* small_img = cvCreateImage( cvSize( cvRound (img->width/scale),  
75.         cvRound (img->height/scale)),  
76.         8, 1 );  
77.     int i;  
78.   
79.     cvCvtColor( img, gray, CV_BGR2GRAY );  
80.     cvResize( gray, small_img, CV_INTER_LINEAR );  
81.     cvEqualizeHist( small_img, small_img );  
82.     cvClearMemStorage( storage );  
83.   
84.     if( cascade )  
85.     {  
86.         double t = (double)cvGetTickCount();  
87.         CvSeq* faces = cvHaarDetectObjects( small_img, cascade, storage,  
88.             1.1, 2, 0/*CV_HAAR_DO_CANNY_PRUNING*/,  
89.             cvSize(30, 30) );  
90.         t = (double)cvGetTickCount() - t;  
91.         printf( "detection time = %gms/n", t/((double)cvGetTickFrequency()*1000.) );  
92.         for( i = 0; i < (faces ? faces->total : 0); i++ )  
93.         {  
94.             CvRect* r = (CvRect*)cvGetSeqElem( faces, i );  
95.             CvPoint center;  
96.             int radius;  
97.             center.x = cvRound((r->x + r->width*0.5)*scale);  
98.             center.y = cvRound((r->y + r->height*0.5)*scale);  
99.             radius = cvRound((r->width + r->height)*0.25*scale);  
100.             cvCircle( img, center, radius, colors[i%8], 3, 8, 0 );  
101.         }  
102.     }  
103.   
104.     cvShowImage( "result", img );  
105.     cvReleaseImage( &gray );  
106.     cvReleaseImage( &small_img );  
107. }   

#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

[cpp] view plain copy print ?

1. #include <cv.h>    
2. #include <highgui.h>      
3. #include <string>    
4. #include <iostream>    
5. #include <algorithm>    
6. #include <iterator>   
7.   
8. #include <stdio.h>   
9. #include <string.h>   
10. #include <ctype.h>   
11.   
12. using namespace cv;  
13. using namespace std;  
14.   
15. void help()  
16. {  
17.     printf(  
18.             "\nDemonstrate the use of the HoG descriptor using\n"  
19.             "  HOGDescriptor::hog.setSVMDetector(HOGDescriptor::getDefaultPeopleDetector());\n"  
20.             "Usage:\n"  
21.             "./peopledetect (<image_filename> | <image_list>.txt)\n\n");  
22. }  
23.   
24. int main(int argc, char** argv)  
25. {  
26.     Mat img;  
27.     FILE* f = 0;  
28.     char _filename[1024];  
29.       
30.     if( argc == 1 )  
31.     {  
32.         printf("Usage: peopledetect (<image_filename> | <image_list>.txt)\n");  
33.         return 0;  
34.     }  
35.       
36.     img = imread(argv[1]);  
37.   
38.     if( img.data )  
39.     {  
40.         strcpy(_filename, argv[1]);  
41.     }  
42.     else  
43.     {  
44.         f = fopen(argv[1], "rt");  
45.         if(!f)  
46.         {  
47.             fprintf( stderr, "ERROR: the specified file could not be loaded\n");  
48.             return -1;  
49.         }  
50.     }  
51.   
52.     HOGDescriptor hog;  
53.     hog.setSVMDetector(HOGDescriptor::getDefaultPeopleDetector());//得到检测器   
54.     namedWindow("people detector", 1);  
55.   
56.     for(;;)  
57.     {  
58.         char* filename = _filename;  
59.         if(f)  
60.         {  
61.             if(!fgets(filename, (int)sizeof(_filename)-2, f))  
62.                 break;  
63.             //while(*filename && isspace(*filename))   
64.             //  ++filename;   
65.             if(filename[0] == '#')  
66.                 continue;  
67.             int l = strlen(filename);  
68.             while(l > 0 && isspace(filename[l-1]))  
69.                 --l;  
70.             filename[l] = '\0';  
71.             img = imread(filename);  
72.         }  
73.         printf("%s:\n", filename);  
74.         if(!img.data)  
75.             continue;  
76.           
77.         fflush(stdout);  
78.         vector<Rect> found, found_filtered;  
79.         double t = (double)getTickCount();  
80.         // run the detector with default parameters. to get a higher hit-rate   
81.         // (and more false alarms, respectively), decrease the hitThreshold and   
82.         // groupThreshold (set groupThreshold to 0 to turn off the grouping completely).   
83.         hog.detectMultiScale(img, found, 0, Size(8,8), Size(32,32), 1.05, 2);  
84.         t = (double)getTickCount() - t;  
85.         printf("tdetection time = %gms\n", t*1000./cv::getTickFrequency());  
86.         size_t i, j;  
87.         for( i = 0; i < found.size(); i++ )  
88.         {  
89.             Rect r = found[i];  
90.             for( j = 0; j < found.size(); j++ )  
91.                 if( j != i && (r & found[j]) == r)  
92.                     break;  
93.             if( j == found.size() )  
94.                 found_filtered.push_back(r);  
95.         }  
96.         for( i = 0; i < found_filtered.size(); i++ )  
97.         {  
98.             Rect r = found_filtered[i];  
99.             // the HOG detector returns slightly larger rectangles than the real objects.   
100.             // so we slightly shrink the rectangles to get a nicer output.   
101.             r.x += cvRound(r.width*0.1);  
102.             r.width = cvRound(r.width*0.8);  
103.             r.y += cvRound(r.height*0.07);  
104.             r.height = cvRound(r.height*0.8);  
105.             rectangle(img, r.tl(), r.br(), cv::Scalar(0,255,0), 3);  
106.         }  
107.         imshow("people detector", img);  
108.         int c = waitKey(0) & 255;  
109.         if( c == 'q' || c == 'Q' || !f)  
110.             break;  
111.     }  
112.     if(f)  
113.         fclose(f);  
114.     return 0;  
115. }  

#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.youkuaiyun.com/scut1135/article/details/7329398