bool EigenfaceRecognizer::train()
{
isTrained = false;
if(!loadTrainingImages())
return false;
//do principal component analysis
doPCA();
// project the training images onto the PCA subspace
projectedTrainImage = cvCreateMat( numTrainedImages, numEigenvalues, CV_32FC1 );
int offset = projectedTrainImage->step / sizeof(float);
for(int i = 0; i < numTrainedImages; i++)
{
//int offset = i * nEigens;
cvEigenDecomposite(
images[i],
numEigenvalues,
eigenVectors,
0, 0,
averageImage,
//projectedTrainFaceMat->data.fl + i*nEigens);
projectedTrainImage->data.fl + i*offset);
}
isTrained = true;
return isTrained;
}
void ofxFaceRecognizer::setup(int method_used, int _maxFaces, bool bAlreadySavedModel, string folderName) {
//eigen take much longer to load and longer to generate. also makes much larger yml file
string method_names[3] = {"eigen","fisher","lbph"};
// Create a FaceRecognizer and train it on the given images:
methodId = method_used;
methodName = method_names[method_used];
if(methodId == 0){
model = createEigenFaceRecognizer();
}
if(methodId == 1){
model = createFisherFaceRecognizer();
}
if(methodId == 2){
model = createLBPHFaceRecognizer();
}
//if(_maxFaces > 0){
maxFaces = _maxFaces;
//by default my training images should be 150x150 pixels
//will reset if you use loadTrainingImages()
image_width = 150;
image_height = 150;
//load in training images
loadTrainingImages(folderName,maxFaces);
string compiledDatabasePath = ofToDataPath("model_"+methodName+"_"+ofToString(maxFaces)+"_"+folderName+".yml");
if(bAlreadySavedModel){
cout<<"model .yml supposedly existing"<<endl;
model->load(compiledDatabasePath);
cout<<"loaded "<<maxFaces<<" faces with model "<<methodName<<endl;
}else{
cout<<"start training new model. this might take a very long time"<<endl;
cout<<"compiledDatabasePath "<<compiledDatabasePath<<endl;
cout<<"more so for fisher than eigen"<<endl;
model->train(allTrainingMats, allTrainingLabels);
model->save(ofToDataPath(compiledDatabasePath));
cout<<"trained and saved .yml with "<<maxFaces<<" faces with model "<<methodName<<endl;
}
// Quit if there are not enough images for this demo.
if(allTrainingMats.size() <= 1) {
string error_message = "This demo needs at least 2 images to work. Please add more images to your data set!";
CV_Error(CV_StsError, error_message);
}
}