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CvANN_MLP give for every sample the same result

asked 2013-10-04 11:44:27 -0500

sp_mic88 gravatar image

updated 2013-10-05 02:50:18 -0500

berak gravatar image

I have created a neural network with CvANN_MLP class, working with Opencv libraries in the 2.4.6 version. My Cv_ANN mlp network is:

 Mat trainingData(NUMERO_ESEMPI_TOTALE, 59, CV_32FC1);  
Mat trainingClasses(NUMERO_ESEMPI_TOTALE, 1, CV_32FC1);

for(int i=0;i<NUMERO_ESEMPI_TOTALE;i++){
    for(int j=0;j<59;j++){
        trainingData.at<float>(i,j) = featureVect[i][j];
    }
}

for(int i=0;i<NUMERO_ESEMPI_TOTALE;i++){
    trainingClasses.at<float>(i,0) = featureVect[i][59];
}

Mat testData (NUMERO_ESEMPI_TEST , 59, CV_32FC1);
Mat testClasses (NUMERO_ESEMPI_TEST , 1, CV_32FC1);
for(int i=0;i<NUMERO_ESEMPI_TEST;i++){
    for(int j=0;j<59;j++){
        testData.at<float>(i,j) = featureVectTest[i][j];
    }
}

//0 bocca, 1 non bocca.
testClasses.at<float>(0,0) = 1;
testClasses.at<float>(1,0) = 0;
testClasses.at<float>(2,0) = 1;
testClasses.at<float>(3,0) = 1;
testClasses.at<float>(4,0) = 0;
testClasses.at<float>(5,0) = 1;
testClasses.at<float>(6,0) = 0;
testClasses.at<float>(7,0) = 1;
testClasses.at<float>(8,0) = 1;
testClasses.at<float>(9,0) = 0;
testClasses.at<float>(10,0) = 0;
testClasses.at<float>(11,0) = 1;
testClasses.at<float>(12,0) = 0;
testClasses.at<float>(13,0) = 0;
testClasses.at<float>(14,0) = 0;
testClasses.at<float>(15,0) = 0;
testClasses.at<float>(16,0) = 0;
testClasses.at<float>(17,0) = 0;
testClasses.at<float>(18,0) = 0;
testClasses.at<float>(19,0) = 1;
testClasses.at<float>(20,0) = 1;
testClasses.at<float>(21,0) = 0;
testClasses.at<float>(22,0) = 1;
testClasses.at<float>(23,0) = 0;
testClasses.at<float>(24,0) = 1;
testClasses.at<float>(25,0) = 0;
testClasses.at<float>(26,0) = 0;
testClasses.at<float>(27,0) = 1;
testClasses.at<float>(28,0) = 1;
testClasses.at<float>(29,0) = 1;    

Mat layers = Mat(3, 1, CV_32SC1);
layers.row(0) = Scalar(59);
layers.row(1) = Scalar(3);
layers.row(2) = Scalar(1);

CvANN_MLP mlp;
CvANN_MLP_TrainParams params;
CvTermCriteria criteria;
criteria.max_iter = 100;
criteria.epsilon = 0.0000001;
criteria.type = CV_TERMCRIT_ITER | CV_TERMCRIT_EPS;
params.train_method = CvANN_MLP_TrainParams :: BACKPROP;
params.bp_dw_scale = 0.05 ;
params.bp_moment_scale = 0.05 ;
params.term_crit = criteria ;
mlp.create(layers);
// train
mlp.train(trainingData,trainingClasses,Mat(),Mat(),params);

Mat response(1, 1, CV_32FC1);
Mat predicted(testClasses.rows, 1, CV_32F);
Mat pred(NUMERO_ESEMPI_TEST, 1, CV_32FC1);
Mat pred1(NUMERO_ESEMPI_TEST, 1, CV_32FC1);
for(int i = 0; i < testData . rows ; i++){
    Mat response(1, 1, CV_32FC1);
    Mat sample = testData.row(i);
    mlp.predict(sample,response);
    predicted.at<float>(i ,0) = response.at <float>(0,0);
    pred.at<float>(i,0)=predicted.at<float>(i ,0);
    pred1.at<float>(i,0)=predicted.at<float>(i ,0);
    file<<"Value Image "<<i<<": "<<predicted.at<float>(i ,0)<<"\n";
    //cout<<"Value Image "<<i<<": "<<predicted.at<float>(i ,0)<<endl;
}

The problem is that this network return me for every test sample the same result. I don't know why. My network takes as input a set of feature vector with 59 input values and 1 output value. Could you help me?

Thanks in advance.

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answered 2013-12-04 07:13:32 -0500

Daf gravatar image

I think the output must be at least two classifications (outputs). But I share the problem of the prediction yielding the same answer.

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Comments

I have the same issue, I tried all the suggestions above but I still get the same value for all prediction -1.#QNAN00, could anyone please advise?

afahmy gravatar imageafahmy ( 2014-03-03 15:16:42 -0500 )edit

did you solve the problem? I face the same issue. All predicted values are the same though they are different samples.

cv_new gravatar imagecv_new ( 2015-06-19 02:21:01 -0500 )edit
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Asked: 2013-10-04 11:44:27 -0500

Seen: 1,025 times

Last updated: Dec 04 '13