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我原来在Ubuntu虚拟机上做了一个opencv人脸检测的程序，用C++写的，其实很简单，就是每隔10ms通过摄像头抓取一帧图片，然后标记出人脸的位置
然后我在树莓派上安装了opencv库，但是编译运行这个程序的时候，本来每隔10ms一个循环的，但是实际上大概六七秒才完成一个循环，这个到底是哪里的问题，应该不是树莓派性能问题吧，我在网上看到国内外很多用树莓派做类似的人脸检测的，都很流畅，各位了解的帮我看一下吧
#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>
#ifdef _EiC
//#define WIN32
#endif
static CvMemStorage* storage = 0;
static CvHaarClassifierCascade* cascade = 0;
void detect_and_draw( IplImage* image );
const char* cascade_name =
"/Users/ang/Documents/workspace/eye/src/haarcascade_frontalface_alt.xml";
/* "haarcascade_profileface.xml";*/
int main( int argc, char** argv )
{
// cascade_name = "haarcascade_frontalface_alt2.xml";
cascade = (CvHaarClassifierCascade*)cvLoad( cascade_name, 0, 0, 0 );
if( !cascade )
{
fprintf( stderr, "ERROR: Could not load classifier cascade\n" );
return -1;
}
storage = cvCreateMemStorage(0);
cvNamedWindow( "result", 1 );
cvNamedWindow("source",1);
CvCapture *capture = cvCaptureFromCAM(0);
if(!capture)
printf("\n");
IplImage* image = NULL;
char key = cvWaitKey(10);
while( key != 'Q' && key != 'q' )
{
image = cvQueryFrame(capture);
if(!image)
{
printf("image NULL");
continue;
}
std::cout<<"width"<<image->width<<std::endl;
std::cout<<"height"<<image->height<<std::endl;
//cvShowImage("source",image);
detect_and_draw( image );
key = cvWaitKey(10);
//cvReleaseImage( &image );
}
cvReleaseImage( &image );
cvDestroyWindow("source");
cvDestroyWindow("result");
return 0;
}
void detect_and_draw(IplImage* img )
{
double scale=1.2;
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}}
};//Just some pretty colors to draw with
//Image Preparation
//
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);
cvCvtColor(img,gray, CV_BGR2GRAY);
cvResize(gray, small_img, CV_INTER_LINEAR);
cvEqualizeHist(small_img,small_img);
//Detect objects if any
//
cvClearMemStorage(storage);
double t = (double)cvGetTickCount();
CvSeq* objects = 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.) );
//Loop through found objects and draw boxes around them
for(int i=0;i<(objects? objects->total:0);++i)
{
CvRect* r=(CvRect*)cvGetSeqElem(objects,i);
cvRectangle(img, cvPoint(r->x*scale,r->y*scale), cvPoint((r->x+r->width)*scale,(r->y+r->height)*scale), colors[i%8]);
}
for( int i = 0; i < (objects? objects->total : 0); i++ )
{
CvRect* r = (CvRect*)cvGetSeqElem( objects, 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);
}
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