openCV库自带的行人检测demo求助【100分】

2012-03-15 04:21:31 2.1k 阅读 AI 写同款 · GEO 优化AI 选题数据监测一键分发 ›

opencv学习十六：圆检测圆检测原理圆周上任意三点所确定的圆，经Hough变换后在三维参数空间应对应一点。遍历圆周上所有点，任意三个点所确定的候选圆进行投票。遍历结束后，得票数最高点（理论上圆周上任意三点确定的圆在Hough变换后均对应三维参数空间中的同一点）所确定的圆即为该圆周上，绝大多数点所确定的圆（以下称为当选圆），即绝大多数点均在该当选圆的圆周上，以此确定该圆。圆形的表达式为(x−xcenter)2+(y−ycenter)2=r2(x−xcenter)2+(y−ycenter)2=r2，一个圆环的确定需要三个参数。阅读详情

如下是源代码

#include "opencv2/imgproc/imgproc.hpp"

#include "opencv2/objdetect/objdetect.hpp"

#include "opencv2/highgui/highgui.hpp"



#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());

    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;

}

弄了好久，代码编译正常，通过。运行时，提示0xc000000d，初始化失败。刚开始以为是HOGDescriptor初始化有问题，可自己重新初始化，依然报错0xc000000d。

也看过一个CSDN上的同样帖子，问题一样，他最后解决了，只是给了个确实是初始化对象失败的原因，但是没说具体修改方案，我也一直在弄了，还没解决掉，所以给个高分求助各位大侠

3Q

...全文

OpenCV+python：圆检测 1，圆检测基本原理对霍夫变换有了这样一种理解-----实际上就是坐标变换，是一种数学上的变换，然后再转换到参数坐标系进行讨论，最终确定待检测圆（或者其他形状）的数学方程。在极坐标系下，圆的数学表达式如下：类似于霍夫变换直线检测，这里我们也定义一个累加器，但是与直线检测不同的是，直线检测参数是二维的，而圆的参数是三维的。如果一个圆上的点，都沿着其梯度方向画线，那么所有线的角点就是圆心。OpenC... 阅读详情

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切换为时间正序

MarkovLGXu 2014-06-17

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我在多线程情况下遇到这个问题，已经解决，解决办法我写到了，看看能不能解决了 http://blog.csdn.net/eagleest/article/details/31741181

MarkovLGXu 2014-06-16

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问题是怎么解决的呢？在控制台下面没问题，在线程里面出错！

YUQING0314 2014-04-03

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引用 21 楼 haithink 的回复:

[quote=引用 19 楼 jzwsjcdown 的回复:] 楼主，可否可以说一下，怎么解决的啊？？小弟也遇到了这个问题。。。 InputArray _svmdetector=HOGDescriptor::getDefaultPeopleDetector(); 运行这个就报错。。。。

我也是这个问题，貌似控制台就没事，GUI程序就出错！！！！⊙﹏⊙b汗[/quote] 请问这个问题后来解决了吗？怎么解决的？我也卡在这句上了。。。

r101ab 2013-10-25

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求opencv的库，好人一生平安

pangdawa 2013-10-09

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引用 19 楼 jzwsjcdown 的回复:

楼主，可否可以说一下，怎么解决的啊？？小弟也遇到了这个问题。。。 InputArray _svmdetector=HOGDescriptor::getDefaultPeopleDetector(); 运行这个就报错。。。。

我也是这个问题，貌似控制台就没事，GUI程序就出错！！！！⊙﹏⊙b汗

luowanying 2013-09-05

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引用 15 楼 a06131021 的回复:

实验了可行

#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/objdetect/objdetect.hpp"
#include "opencv2/highgui/highgui.hpp"

#include<iostream>

#include <XnCppWrapper.h>

#include<cv.h>
#include<cxcore.h>
#include<highgui.h>

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

using namespace std ;

using namespace cv;

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");
}

void CheckOpenNIError( XnStatus result, string status )
{ 
	if( result != XN_STATUS_OK ) 
		cerr << status << " Error: " << xnGetStatusString( result ) << endl;
}

/*
int main(int argc, char** argv)
{
	XnStatus result = XN_STATUS_OK;  
//	xn::DepthMetaData depthMD;
	xn::ImageMetaData imageMD;

	//OpenCV
//	IplImage*  imgDepth16u=cvCreateImage(cvSize(640,480),IPL_DEPTH_16U,1);
	
//	IplImage*  depthShow=cvCreateImage(cvSize(640,480),IPL_DEPTH_8U,1);

	IplImage* imgRGB8u=cvCreateImage(cvSize(640,480),IPL_DEPTH_8U,3);
	IplImage* showImage=cvCreateImage(cvSize(640,480),IPL_DEPTH_8U,3);

	
//	cvNamedWindow("depth",1);
//	cvNamedWindow("image",1);
	char key=0;

	//【2】
	// context
	xn::Context context; 
	result = context.Init(); 
	CheckOpenNIError( result, "initialize context" );  

	// creategenerator  
//	xn::DepthGenerator depthGenerator;  
//	result = depthGenerator.Create( context ); 
//	CheckOpenNIError( result, "Create depth generator" );  

	xn::ImageGenerator imageGenerator;
	result = imageGenerator.Create( context ); 
	CheckOpenNIError( result, "Create image generator" );

	//【3】
	//map mode  
	XnMapOutputMode mapMode; 
	mapMode.nXRes = 640;  
	mapMode.nYRes = 480; 
	mapMode.nFPS = 30; 
//	result = depthGenerator.SetMapOutputMode( mapMode );  
	result = imageGenerator.SetMapOutputMode( mapMode );  

	//【4】
	// correct view port  
//	depthGenerator.GetAlternativeViewPointCap().SetViewPoint( imageGenerator ); 

	//【5】
	//read data
	result = context.StartGeneratingAll();  
	//【6】
	result = context.WaitNoneUpdateAll();  


    HOGDescriptor hog;
    hog.setSVMDetector(HOGDescriptor::getDefaultPeopleDetector());

	cvNamedWindow( "peopleDetect", 1 ) ;

	//减小检测图像的大小
	double scale = 0.5 ;
	IplImage* downScaleImage = cvCreateImage( cvSize(640*scale, 480*scale), IPL_DEPTH_8U,3 ) ;

	while( (key!=27) && !(result = context.WaitNoneUpdateAll( )) )
	{
		imageGenerator.GetMetaData(imageMD);
		memcpy(imgRGB8u->imageData,imageMD.Data(),640*480*3);

		cvCvtColor(imgRGB8u,showImage,CV_RGB2BGR);

		cvResize( showImage, downScaleImage ) ;
		

		//Hog处理人体检测
		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( downScaleImage, found, 0, Size(8,8), Size(32,32), 1.1, 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);

			cvRectangle(downScaleImage, r.tl(), r.br(), cv::Scalar(0,255,0), 3);
	    }

		cvResize( downScaleImage, showImage ) ;

		cvShowImage( "peopleDetect", showImage ) ;

		key = cvWaitKey(20) ;

	}
	

	cvDestroyWindow("peopleDetect") ;

	cvReleaseImage( &showImage ) ;
	cvReleaseImage( &imgRGB8u ) ;
	cvReleaseImage( &downScaleImage ) ;

	context.StopGeneratingAll();
	context.Shutdown();

	
	return 0 ;

}
*/

int main(int argc, char** argv)
{
	IplImage* person = cvLoadImage( "person.jpg", 1 ) ;

    HOGDescriptor hog;
    hog.setSVMDetector(HOGDescriptor::getDefaultPeopleDetector());

	cvNamedWindow( "peopleDetect", 1 ) ;

	
	//Hog处理人体检测
	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( person, 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);

		cvRectangle(person, r.tl(), r.br(), cv::Scalar(0,255,0), 3);
    }

	cvShowImage( "peopleDetect", person ) ;
	cvWaitKey() ;
	
	cvDestroyWindow("peopleDetect") ;
	cvReleaseImage( &person ) ;
	
	return 0 ;
}

为什么我运行出来却检测不到人体呢？试了很多图片都不行。。这个问题困扰我很久了，急求答案啊！

jzwsjcdown 2013-05-21

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楼主，可否可以说一下，怎么解决的啊？？小弟也遇到了这个问题。。。 InputArray _svmdetector=HOGDescriptor::getDefaultPeopleDetector(); 运行这个就报错。。。。

WTK-CV 2012-06-15

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看来大家对这个比较关注，不好意思最近比较忙

最近基于HOG+BOOST做了关于手势识别相关研究目前效果一般，等把效果等等做得稍微好点了发个总结目标训练检测的帖子到CSDN与大家一起学习。

xuhaohunter 2012-06-11

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这个解决了。但怎么根据OPenCV的CVSVM，CVBOOST，或者libSVM生成的模型，得到自己的HOG?

a06131021 2012-06-01

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请无视，楼上代码中注释部分，那个是我用OpenNI读取Kinect摄像头的代码，忘了删除了，
还有#include <XnCppWrapper.h>也忘记注释了

a06131021 2012-06-01

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实验了可行

#include "opencv2/imgproc/imgproc.hpp"

#include "opencv2/objdetect/objdetect.hpp"

#include "opencv2/highgui/highgui.hpp"



#include<iostream>



#include <XnCppWrapper.h>



#include<cv.h>

#include<cxcore.h>

#include<highgui.h>



#include <stdio.h>

#include <string.h>

#include <ctype.h>



using namespace std ;



using namespace cv;



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");

}



void CheckOpenNIError( XnStatus result, string status )

{ 

	if( result != XN_STATUS_OK ) 

		cerr << status << " Error: " << xnGetStatusString( result ) << endl;

}



/*

int main(int argc, char** argv)

{

	XnStatus result = XN_STATUS_OK;  

//	xn::DepthMetaData depthMD;

	xn::ImageMetaData imageMD;



	//OpenCV

//	IplImage*  imgDepth16u=cvCreateImage(cvSize(640,480),IPL_DEPTH_16U,1);

	

//	IplImage*  depthShow=cvCreateImage(cvSize(640,480),IPL_DEPTH_8U,1);



	IplImage* imgRGB8u=cvCreateImage(cvSize(640,480),IPL_DEPTH_8U,3);

	IplImage* showImage=cvCreateImage(cvSize(640,480),IPL_DEPTH_8U,3);



	

//	cvNamedWindow("depth",1);

//	cvNamedWindow("image",1);

	char key=0;



	//【2】

	// context

	xn::Context context; 

	result = context.Init(); 

	CheckOpenNIError( result, "initialize context" );  



	// creategenerator  

//	xn::DepthGenerator depthGenerator;  

//	result = depthGenerator.Create( context ); 

//	CheckOpenNIError( result, "Create depth generator" );  



	xn::ImageGenerator imageGenerator;

	result = imageGenerator.Create( context ); 

	CheckOpenNIError( result, "Create image generator" );



	//【3】

	//map mode  

	XnMapOutputMode mapMode; 

	mapMode.nXRes = 640;  

	mapMode.nYRes = 480; 

	mapMode.nFPS = 30; 

//	result = depthGenerator.SetMapOutputMode( mapMode );  

	result = imageGenerator.SetMapOutputMode( mapMode );  



	//【4】

	// correct view port  

//	depthGenerator.GetAlternativeViewPointCap().SetViewPoint( imageGenerator ); 



	//【5】

	//read data

	result = context.StartGeneratingAll();  

	//【6】

	result = context.WaitNoneUpdateAll();  





    HOGDescriptor hog;

    hog.setSVMDetector(HOGDescriptor::getDefaultPeopleDetector());



	cvNamedWindow( "peopleDetect", 1 ) ;



	//减小检测图像的大小

	double scale = 0.5 ;

	IplImage* downScaleImage = cvCreateImage( cvSize(640*scale, 480*scale), IPL_DEPTH_8U,3 ) ;



	while( (key!=27) && !(result = context.WaitNoneUpdateAll( )) )

	{

		imageGenerator.GetMetaData(imageMD);

		memcpy(imgRGB8u->imageData,imageMD.Data(),640*480*3);



		cvCvtColor(imgRGB8u,showImage,CV_RGB2BGR);



		cvResize( showImage, downScaleImage ) ;

		



		//Hog处理人体检测

		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( downScaleImage, found, 0, Size(8,8), Size(32,32), 1.1, 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);



			cvRectangle(downScaleImage, r.tl(), r.br(), cv::Scalar(0,255,0), 3);

	    }



		cvResize( downScaleImage, showImage ) ;



		cvShowImage( "peopleDetect", showImage ) ;



		key = cvWaitKey(20) ;



	}

	



	cvDestroyWindow("peopleDetect") ;



	cvReleaseImage( &showImage ) ;

	cvReleaseImage( &imgRGB8u ) ;

	cvReleaseImage( &downScaleImage ) ;



	context.StopGeneratingAll();

	context.Shutdown();



	

	return 0 ;



}

*/



int main(int argc, char** argv)

{

	IplImage* person = cvLoadImage( "person.jpg", 1 ) ;



    HOGDescriptor hog;

    hog.setSVMDetector(HOGDescriptor::getDefaultPeopleDetector());



	cvNamedWindow( "peopleDetect", 1 ) ;



	

	//Hog处理人体检测

	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( person, 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);



		cvRectangle(person, r.tl(), r.br(), cv::Scalar(0,255,0), 3);

    }



	cvShowImage( "peopleDetect", person ) ;

	cvWaitKey() ;

	

	cvDestroyWindow("peopleDetect") ;

	cvReleaseImage( &person ) ;

	

	return 0 ;

}

xuhaohunter 2012-04-28

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我也在调试OpenCV2.3.1自带的行人检测代码，遇到了一些问题。谁能发我一份调好的代码。434879601@qq.com

xuhaohunter 2012-04-28

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发我一份调好的代码。

xuhaohunter 2012-04-28

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我也在调试OPENCV2.3.1自带的行人检测程序，遇到了一些问题。有人能把调好的代码发我一份吗？谢谢了。434879601@qq.com

imlab 2012-03-23

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建议装OpenCV2.3的库试试，我用的就是2.3+VS2005.编译时需要CMake工具，网上自己找找。

libing64 2012-03-16

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img = imread(argv[1]);
argc 和argv 是在命令行下运行时会用到的参数，argc是可执行文件的名字，argv是要用到的参数
例如：在命令行下，（已经进入文件夹） detect.exe lean.jpg 回车就会将lean.jpg读入进行人脸检测~

楼主如果使用编译器的话，直接给filename赋值如E:\\imnage\\lean.jpg，将原来程序中的关于argv和argc的删掉就可以了~

向立天 2012-03-16

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[Quote=引用 7 楼 cimage 的回复:]

无法进入单步调试，不然就好解决了~F5 直接提示0xc000000d
[/Quote]
main函数都进不去？

WTK-CV 2012-03-16

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无法进入单步调试，不然就好解决了~F5 直接提示0xc000000d

向立天 2012-03-16

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调试看看呢

向立天 2012-03-16

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注释掉main函数内所有代码试试

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openCV库自带的行人检测demo求助【100分】

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