cvcircle_cv::line_cv::mat(16)

return;

}

cout<<"ProcessingsamplesinClass"<<i<<endl;

vector<char*>file_vec=statdir.BeginBrowseFilenames("*.*");

for(j=0;j<file_vec.size();j++)

{

IplImage*cur_img=cvLoadImage(file_vec[j],CV_LOAD_IMAGE_GRAYSCALE);

cvResize(cur_img,standard,CV_INTER_AREA);

Matcur_mat=cvarrToMat(standard,true),des_mat;

cv::normalize(cur_mat,des_mat,0,255,NORM_MINMAX,CV_8UC1);

cvSaveImage(file_vec[j],cvCloneImage(&(IplImage)des_mat));

if(j!=file_vec.size())

{

images.push_back(des_mat);

labels.push_back(i);

}

else

{

testimages.push_back(des_mat);

testlabels.push_back(i);

}

}

cout<<file_vec.size()<<"images."<<endl;

}

}

并在main中调用：

intmain()

{

CvCapture*capture=0;

Matframe,frameCopy,image;

stringinputName;

intmode;

chardir[256]="D:\\Courses\\CV\\Face_recognition\\pic\\";

//preprocess_trainingdata(dir,K);//face_detectionandextracttofile

vector<Mat>images,testimages;

vector<int>labels,testlabels;

resizeandtogray(dir,K,images,labels,testimages,testlabels);//togray,normalizeandresize

system("pause");

return0;

}

2. 训练

有了vector<Mat> images,testimages;vector<int> labels,testlabels; 可以开始训练了，我们采用EigenFaceRecognizer建模。

在Prehelper.cpp中加入函数

Ptr<FaceRecognizer> Recognition(vector<Mat> images, vector<int> labels,vector<Mat> testimages, vector<int> testlabels)；

Ptr<FaceRecognizer>Recognition(vector<Mat>images,vector<int>labels,

vector<Mat>testimages,vector<int>testlabels)

{

Ptr<FaceRecognizer>model=createEigenFaceRecognizer(10);//10Principalcomponents

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