OpenCV : Training SVM Error - Assertion failed - c++

Question

Im writing program to classify objects using SVM and BoW. I am getting the following error when I try use the TrainData::create() member function to create the data necessary to train SVM classifier.
OpenCV Error: Assertion failed (responses.type() == CV_32F || responses.type() == CV_32S) in setData
This is my function to read the train data from a director, compute BoW histogram for each train image, create a matrix of all descriptors of all train images in a matrix and the create the train data, labels and then train the SVM
void trainClassifier(string dictionaryPath, string trainDataPath, string saveClassifierPath, int samples){
//Write file
FileStorage readFile(dictionaryPath, FileStorage::READ);
//Load into Dictionary matrix
readFile["Data"] >> dictionary;
if(dictionary.empty() == false)
{
cout << "Error loading visual vocalbulary" << endl;
}
//Set the Bow descripter with the dictionary
testBOW.setVocabulary(dictionary);
//Inititate variables
vector<KeyPoint> keypointTrain;
vector<DMatch> matchTrain;
Mat descriptorTrain;
//inputTrain -> input images, inputFeatures -> BoW descriptor output
Mat inputTrain;
Mat inputFeatures;
//Label array
vector<string> label;
//Create a string to read files from directory
string updatedDataPath;
for(int i = 1; i <= samples; i++)
{
//Update the string updateDataPath to correspond the image FILENAME with each iteration
updatedDataPath.append(trainDataPath);
updatedDataPath += to_string(i);
updatedDataPath.append(".JPEG");
//Read FILE from the updated datapath
inputTrain = imread(updatedDataPath);
//Convert to single channel, since classifier takes only single channel data
cvtColor(inputTrain, inputTrain, CV_BGR2GRAY);
//Generate BoW features/histogram for the train image
testBOW.compute(inputTrain, keypointTrain, inputFeatures);
//Load the data in the descriptor Matrix
descriptorTrain.push_back(inputFeatures);
//Generate label according to the sample
if(samples > 1 && samples <= 10)
{
label.push_back("OBJ1 POSSITIVE");
}
else if (samples > 11 && samples <= 20)
{
label.push_back("OBJ1 NEGATIVE");
}
//Reset data path
updatedDataPath.clear();
}
//Convert the descriptor matrix into 32-pt float to make it compatible with classifier
if(descriptorTrain.type() != CV_32F)
{
descriptorTrain.convertTo(descriptorTrain, CV_32F);
}
//Create train data using TrainData::create()
Ptr<TrainData> trainData = TrainData::create(descriptorTrain, ROW_SAMPLE, label);
//Iniitialize Support vector based classifier (SVM) to classify and detect object
Ptr<SVM>SVM = SVM::create();
SVM->setType(SVM::C_SVC);
SVM->setKernel(SVM::LINEAR);
SVM->setTermCriteria(TermCriteria(TermCriteria::MAX_ITER, 100, 1e-6));
//Now train the SVM
SVM->trainAuto(trainData);
SVM->save(saveClassifierPath);
cout << "Classifier training status: SUCCESSFUL" << endl;}
Any help is appreciated. Thanks and cheers :)

Answer 1

You are using a vector<string> as the TrainData responses.
//Label array
vector<string> label;
// [long code]
//Create train data using TrainData::create()
Ptr<TrainData> trainData = TrainData::create(descriptorTrain, ROW_SAMPLE, label);
And it shoud be a Mat CV_32F or CV_32S, as the error says.
You can confirm that at:
documentation: TrainData::create(...)
source-code: TrainData::create(...) that calls setData(...)