opencv - Assertion Failed (Layer_sizes!=0) CvANN_MLP::predict -

i trying classify input image classify function .xml file have made. training artificial neural network(ann) don't know wrong trying code book"practical projects opencv" full code of book available in github: https://github.com/masteringopencv/code/tree/master/chapter5_numberplaterecognition

technically used own way extract number segments full picture , created ocr.xlm file.

i have no idea why when try classify input segmented image(mat input array) see error : assertion failed (layer_sizes!=0) cvann_mlp::predict

here code

char const strcharacters[] = { '1', '2', '3', '4', '5', '6', '7', '8', '9' }; int const numcharacters = 9; cvann_mlp ann;   void train(mat traindata, mat classes, int nlayers){      filestorage fs;     fs.open("ocr.xml", filestorage::read);     mat traindata;     fs["trainingdata"] >> traindata;     fs["classes"] >> classes;       mat layers(1, 3, cv_32sc1);      layers.at<int>(0,0) = traindata.cols;//input layer     layers.at<int>(1,0) = nlayers;//hidden layer     layers.at<int>(2,0) = numcharacters;//output layer     int buffer[] = { traindata.cols, 16, numcharacters };     ann.create(layers, cvann_mlp::sigmoid_sym, 1, 1);     //prepare trainclases     //create mat n trained data m classes     mat trainclasses;     trainclasses.create(traindata.rows, numcharacters, cv_32f);     (int = 0; < trainclasses.rows; i++)     {         (int k = 0; k < trainclasses.cols; k++)         {             //if class of data same k class             if (k == classes.at<int>(i))                 trainclasses.at<float>(i, k) = 1;             else                 trainclasses.at<float>(i, k) = 0;         }     }      mat weights(1, traindata.rows, cv_32fc1, scalar::all(1));      //learn classifier     ann.train(traindata, trainclasses, weights); }   int classify(mat f){      float result = -1;     mat output(1, numcharacters, cv_32fc1);     ann.predict(f, output);     point maxloc;     double maxval;     minmaxloc(output, 0, &maxval, 0, &maxloc);     //we need know in output max val, x (cols) class.     //  result = output.at < float >(0, 0);      return maxloc.x; } 

i call calssify in main code:

int character = classify(roiresized); 

i appreciate help. suggestion?

i know post old, answer can useful other one. must add layers in neuronal network before using prediction.

e.g :

// define parameters neural network (mlp)  // set network 3 layer 256->10->10 // - 1 input node per attribute in sample // - 10 hidden nodes // - 1 output node per class  int layers_d[] = { attributes_per_sample, 10,  number_of_classes}; cvmat* layers = cvcreatematheader(1,3,cv_32sc1); cvinitmatheader(layers, 1,3,cv_32sc1, layers_d);  // create network using sigmoid function alpha , beta // parameters 0.6 , 1 specified respectively (refer manual)  cvann_mlp* nnetwork = new cvann_mlp; nnetwork->create(layers, cvann_mlp::sigmoid_sym, 0.6, 1); 

source : https://github.com/arnaudgelas/opencvexamples/blob/master/neuralnetwork/neuralnetwork.cpp