這個是在數字影象處理課程裡面的乙個小實踐內容。參考網上已有**重新配置編譯，效果不錯。
人臉識別的庫使用的是haarcascade_frontalface檔案，包含在opencv當中的。
關鍵部分**如下：
//本原始碼只為學習交流之用
//typersever from gzhu
static cvmemstorage* storage = 0;
static cvhaarclassifiercascade* cascade = 0;
void detect_and_draw( iplimage* image );
const char* cascade_name =
"haarcascade_frontalface_alt.xml";
/* "haarcascade_profileface.xml";*/
int main( int argc, char** argv )
cvnamedwindow( "result", 1 );
//const char* filename = "d:/程式/opencv/mytest/mytestfacedetection/lena.jpg";
//iplimage* image = cvloadimage( filename, 1 );
//cvshowimage( "first", image );
storage = cvcreatememstorage(0);
while(1)
cvreleaseimage( &pframe );
cvdestroywindow("result");
return 0;
}void detect_and_draw(iplimage* img )
},},},},
},},},}
};//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); //直方圖均衡
//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)
for( int i = 0; i < (objects? objects->total : 0); i++ )
cvshowimage( "result", img );
cvreleaseimage(&gray);
cvreleaseimage(&small_img);
}
工程檔案見本人資源。歡迎學習交流。
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