CODEWITHSUNDEEP
c++opencvsvm
Vino
Vino

Reputation: 177

OpenCV : Training SVM Error - Assertion failed

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 :)

Upvotes: 0

Views: 3002

Answers (1)

Berriel
Berriel

Reputation: 13601

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:

Upvotes: 1

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