Bdtjtk

I got an exception in this function - I am trying to read mnist dataset from this function but I got an exception. I think the dataset file is not reading - During debug the values of reading is blank so its very clear it not reading, how to cope with this situation.

 int main(int argc, char** argv)

    {

        cout<<"Start of the main function";





        long start, end;

        start = clock();



        vector<Mat> trainX;

        vector<Mat> testX;

        Mat trainY, testY;



        readData(trainX, trainY, "C:\UserssadiqDocumentsVisual Studio 2010ProjectscnnmyNewOpenCVmyNewOpenCVmnisttrain-images-idx3-ubyte", "C:\UserssadiqDocumentsVisual Studio 2010ProjectscnnmyNewOpenCVmyNewOpenCVmnisttrain-labels-idx1-ubyte", 60000);

        readData(testX, testY, "C:\UserssadiqDocumentsVisual Studio 2010ProjectscnnmyNewOpenCVmyNewOpenCVmnistt10k-images-idx3-ubyte", "C:\UserssadiqDocumentsVisual Studio 2010ProjectscnnmyNewOpenCVmyNewOpenCVmnistt10k-labels-idx1-ubyte", 10000);



        cout<<"Read trainX successfully, including "<<trainX[0].cols * trainX[0].rows<<" features and "<<trainX.size()<<" samples."<<endl;

        cout<<"Read trainY successfully, including "<<trainY.cols<<" samples"<<endl;

        cout<<"Read testX successfully, including "<<testX[0].cols * testX[0].rows<<" features and "<<testX.size()<<" samples."<<endl;

        cout<<"Read testY successfully, including "<<testY.cols<<" samples"<<endl;



        int nfeatures = trainX[0].rows * trainX[0].cols;

        int imgDim = trainX[0].rows;

        int nsamples = trainX.size();

        Cvl cvl;

        vector<Ntw> HiddenLayers;

        SMR smr;



        ConvNetInitPrarms(cvl, HiddenLayers, smr, imgDim, nsamples);

        // Train network using Back Propogation

        batch = nsamples / 100;

        Mat tpX = concatenateMat(trainX);

        double lrate = getLearningRate(tpX);

        cout<<"lrate = "<<lrate<<endl;

        trainNetwork(trainX, trainY, cvl, HiddenLayers, smr, 3e-3, 200000, lrate);



        if(! G_CHECKING){

            // Save the trained kernels, you can load them into Matlab/GNU Octave to see what are they look like.

            saveWeight(cvl.layer[0].W, "w0");

            saveWeight(cvl.layer[1].W, "w1");

            saveWeight(cvl.layer[2].W, "w2");

            saveWeight(cvl.layer[3].W, "w3");

            saveWeight(cvl.layer[4].W, "w4");

            saveWeight(cvl.layer[5].W, "w5");

            saveWeight(cvl.layer[6].W, "w6");

            saveWeight(cvl.layer[7].W, "w7");



            // Test use test set

            Mat result = resultProdict(testX, cvl, HiddenLayers, smr, 3e-3);

            Mat err(testY);

            err -= result;

            int correct = err.cols;

            for(int i=0; i<err.cols; i++){

                if(err.ATD(0, i) != 0) --correct;

            }

            cout<<"correct: "<<correct<<", total: "<<err.cols<<", accuracy: "<<double(correct) / (double)(err.cols)<<endl;

        }    

        end = clock();

        cout<<"Totally used time: "<<((double)(end - start)) / CLOCKS_PER_SEC<<" second"<<endl;

        return 0;

    }