Train SVM and save it with OpenCV 3.0 - c++

Question

I am using Visual Studio 2010, with OpenCV 3.0. I'm trying to train a SVM and to save it into a file, but I am having problems.
My purpose is to extract the HOG features of some images and train a SVM with them. All seems to be right, but when I try to save the model in a xml file I obtain the following error:
Unhandled exception in 0x000007fefd9bb16d (KernelBase.dll) in TrainSVM.exe: Exception de MICROSOFT C++: cv::Exception at memory location 0x0026e1b0.
And then this is showed in console:
OpenCV Error: Parsing error (SVM model data is invalid, check sv_count, var_* an
d class_count tags) in cv::ml::SVMImpl::write, file C:\builds\master_PackSlave-w
in64-vc12-shared\opencv\modules\ml\src\svm.cpp, line 2027
The error seems to appear when the SVM has not been trained properly, but I don't understand where I have failed, because the line
svm->train(auxResult)
has "true" as result.
I have checked the images and they are loaded properly, anybody could help me?
Thanks in advance.
Here is the code:
String imagesPathPos = "Positivas/*.jpg"; // it has filters, too !
vector<String> fp;
glob(imagesPathPos, fp);
int tamaño = fp.size();
std::vector<cv::Point> positions;
positions.push_back(cv::Point(0,0));
std::vector<float> descriptor;
Ptr<TrainData> auxResult;
for (size_t i=0; i<fp.size(); ++i)
{
string nameFile = fp[i];
Mat img = imread(fp[i]);
cv::Mat grayImg;
cvtColor( img, grayImg, COLOR_BGR2GRAY );
hog.compute(grayImg,descriptor,winStride,trainingPadding,positions);
Mat auxDescriptor = cv::Mat(descriptor);
Mat descriptorMat(1,auxDescriptor.rows,CV_32FC1);
transpose(auxDescriptor, descriptorMat);
trainingData.push_back(descriptorMat);
trainingLabels.push_back(labelPositive);
}
String imagesPathNeg = "Negativas/*.jpg";
vector<String> fn;
glob(imagesPathNeg, fn, true);
for (size_t i=0; i<fn.size(); i++)
{
Mat img = imread(fn[i]);
cv::Mat grayImg;
cvtColor( img, grayImg, COLOR_BGR2GRAY );
hog.compute(grayImg,descriptor,Size(),Size(),positions);
Mat auxDescriptor = cv::Mat(descriptor);
Mat descriptorMat(1,auxDescriptor.rows,CV_32FC1);
transpose(auxDescriptor, descriptorMat);
trainingData.push_back(descriptorMat);
trainingLabels.push_back(labelPositive);
}
auxResult = TrainData::create(trainingData, type, trainingLabels);
svm->train(auxResult);
svm->save("output.xml");

Answer 1

You are defining "labelPositive" even when the images are negative. Possibly the error is there, within the loop through the vector fn:
trainingLabels.push_back(labelPositive);
You should use a parameter named "labelNegative" defined as -1.