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i want train neural network to classify two type of images but when train network this error occurred :

OpenCV Error: Bad argument (output training data should be a floating-point matrix with the number of rows equal to the number of training samples and the number of columns equal to the size of last (output) layer) in cv::ml::ANN_MLPImpl::prepare_to_train, file C:\buildslave64\win64_amdocl\master_PackSlave-win64-vc14-shared\opencv\modules\ml\src\ann_mlp.cpp, line 675

my code :

#include "opencv2\core.hpp"#include "opencv2\imgproc.hpp"#include "opencv2\imgcodecs.hpp"#include "opencv2\highgui.hpp"#include "opencv2\ml.hpp"#include <string>#include "lbp.h"
using namespace cv;
using namespace cv::ml;
void LoadTrainingData();
 
Mat Data;
Mat Lables;
//const int numberOfClass1 = 2384;
//const int numberOfClass2 = 2462;
const int numberOfClass1 = 23;
const int numberOfClass2 = 24;
int Class1 = 1;
int Class2 = -1;
const int imageDimention = 22;
 
std::string NumberToString(size_t Number)
{
    std::stringstream ss;
    ss << Number;
    return ss.str();
}
 
void main() {
    LoadTrainingData();
    Ptr<ann_mlp> annClassifier;
    annClassifier = ANN_MLP::create();
    annClassifier->setActivationFunction(ANN_MLP::ActivationFunctions::SIGMOID_SYM);
    Mat layers(1, 3, CV_32F);
    layers.at<float>(0) = Data.cols;
    layers.at<float>(1) = 100;
    layers.at<float>(2) = 2;
    annClassifier->setLayerSizes(layers);
    annClassifier->setTermCriteria(TermCriteria(TermCriteria::MAX_ITER, 100, 1e-6));
    annClassifier->setTrainMethod(ANN_MLP::TrainingMethods::BACKPROP);
    bool trained = annClassifier->train(Data,ROW_SAMPLE,Lables);
    if (trained)
        annClassifier->save("Ann_sigmoid_eye");
}
 
void LoadTrainingData() {
    Data = Mat(numberOfClass1 + numberOfClass2, imageDimention*imageDimention, CV_32FC1);
    Lables = Mat(numberOfClass1 + numberOfClass2,1 , CV_32SC1);
    // load openEye 
    Mat img;
    Mat lbpImg;
    Mat row;
    std::string path;
    for (size_t i = 1; i <= numberOfClass2; i++)
    {
        path = "class1 (" + NumberToString(i) + ").jpg";
        img = imread(path);
        if (img.channels() > 1)
            cvtColor(img, img, CV_BGR2GRAY);
        lbp::ELBP(img,lbpImg, 1, 16); 

        row = lbpImg.reshape(0, 1);
        row.convertTo(row, CV_32FC1);
        Data.push_back(row);
        Lables.push_back(Class1);
    }
    for (size_t i = 1; i <= numberOfClass1; i++)
    {
        path ="class2 (" + NumberToString(i) + ").jpg";
        img = imread(path);
        if (img.channels() > 1)
            cvtColor(img, img, CV_BGR2GRAY);
        lbp::ELBP(img,lbpImg, 1, 16);
        row = lbpImg.reshape(0, 1);
        row.convertTo(row, CV_32FC1);
        Data.push_back(row);
        Lables.push_back(Class2);
    }
}

i don't why this happen ! please help me,thanks.