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asked 2016-05-13 03:17:15 -0600

RubixCube gravatar image

Neural Network in OpenCV 3.1.0

Hello everyone!

I am currently trying to get OpenCV's neural network module running, unluckily so far with less success. Initialization and training works fine (at least as far as I can verify it) but as soon as I try to do a prediction, I'm receiving segmentation fault errors... I tried training / predicting on both Windows 8 as well as Ubuntu 16.04 on a custom Linux build as well as on a third-party Windows build respectively, as soon as I try a prediction, the same error occurs.

I also prepared some usable example code. Of course I know that training on randomly generated data makes not too much sense in practice, I only wanted to keep things simple for a minimum running example:

#include <opencv2/ml/ml.hpp>

using namespace cv;
using namespace cv::ml;

int main(int argc, char *argv[])
{
    //create random training data
    Mat_<float> data(100, 100);
    randn(data, Mat::zeros(1, 1, data.type()), Mat::ones(1, 1, data.type()));

    //half of the samples for each class
    Mat_<float> responses(data.rows, 1);
    for (int i=0; i<responses.rows; ++i)
        responses(i, 0) = i < responses.rows / 2 ? 0 : 1;

    //create the neural network
    Mat_<int> layerSizes(1, 3);
    layerSizes(0, 0) = data.cols;
    layerSizes(0, 1) = 20;
    layerSizes(0, 2) = 1;

    Ptr<ANN_MLP> networkPtr = ANN_MLP::create();
    ANN_MLP* network = networkPtr.get();
    network->setLayerSizes(layerSizes);
    network->setActivationFunction(0, 0.1, 0.1);
    network->setTrainMethod(0, 0.1, 0.1);

    /*
    //test to change variable type flags -> problem stays the same
    Mat_<int> varType = Mat(1, data.cols+1, CV_8U);
    for (int i = 0; i<data.cols; ++i)
        varType(0, i) = VAR_ORDERED;
    varType(0, varType.cols-1) = VAR_CATEGORICAL;
    //varType(0, varType.cols-1) = VAR_ORDERED;
    Ptr<TrainData> trainData = TrainData::create(data, ROW_SAMPLE, responses, noArray(), noArray(), noArray(), varType);
    */

    Ptr<TrainData> trainData = TrainData::create(data, ROW_SAMPLE, responses);
    network->train(trainData);

    if (network->isTrained())
    {
        printf("Predict:\n");
        network->predict(Mat::ones(1, data.cols, data.type())); //SEGMENTATION FAULT
        printf("Prediction done!\n");
    }

    return 0;
}

Does anyone got the Neural Network running in OpenCV 3.1.0? For me either I'm doing something wrong (in case, please let me know) or this is a bug in OpenCV... I would appreciate any comments :-)

Neural Network in OpenCV 3.1.0

Hello everyone!

I am currently trying to get OpenCV's neural network module running, unluckily so far with less success. Initialization and training works fine (at least as far as I can verify it) but as soon as I try to do a prediction, I'm receiving segmentation fault errors... I tried training / predicting on both Windows 8 as well as Ubuntu 16.04 on a custom Linux build as well as on a third-party Windows build respectively, as soon as I try a prediction, the same error occurs.

I also prepared some usable example code. Of course I know that training on randomly generated data makes not too much sense in practice, I only wanted to keep things simple for a minimum running example:

#include <opencv2/ml/ml.hpp>

using namespace cv;
using namespace cv::ml;

int main(int argc, char *argv[])
{
    //create random training data
    Mat_<float> data(100, 100);
    randn(data, Mat::zeros(1, 1, data.type()), Mat::ones(1, 1, data.type()));

    //half of the samples for each class
    Mat_<float> responses(data.rows, 1);
    for (int i=0; i<responses.rows; ++i)
        responses(i, 0) = i < responses.rows / 2 ? 0 : 1;

    //create the neural network
    Mat_<int> layerSizes(1, 3);
    layerSizes(0, 0) = data.cols;
    layerSizes(0, 1) = 20;
    layerSizes(0, 2) = 1;

    Ptr<ANN_MLP> networkPtr = ANN_MLP::create();
    ANN_MLP* network = networkPtr.get();
    network->setLayerSizes(layerSizes);
    network->setActivationFunction(0, 0.1, 0.1);
    network->setTrainMethod(0, 0.1, 0.1);

    /*
    //test to change variable type flags -> problem stays the same
    Mat_<int> varType = Mat(1, data.cols+1, CV_8U);
    for (int i = 0; i<data.cols; ++i)
        varType(0, i) = VAR_ORDERED;
    varType(0, varType.cols-1) = VAR_CATEGORICAL;
    //varType(0, varType.cols-1) = VAR_ORDERED;
    Ptr<TrainData> trainData = TrainData::create(data, ROW_SAMPLE, responses, noArray(), noArray(), noArray(), varType);
    */

    Ptr<TrainData> trainData = TrainData::create(data, ROW_SAMPLE, responses);
    network->train(trainData);

    if (network->isTrained())
    {
        printf("Predict:\n");
        network->predict(Mat::ones(1, data.cols, data.type())); //SEGMENTATION FAULT
        printf("Prediction done!\n");
    }

    return 0;
}

Does anyone got the Neural Network running in OpenCV 3.1.0? For me either I'm doing something wrong (in case, please let me know) or this is a bug in OpenCV... I would appreciate any comments :-)

edit - updated source code:

#include <opencv2/ml/ml.hpp>

using namespace cv;
using namespace cv::ml;

int main(int argc, char *argv[])
{
    //create random training data
    Mat_<float> data(100, 100);
    randn(data, Mat::zeros(1, 1, data.type()), Mat::ones(1, 1, data.type()));

    //half of the samples for each class
    Mat_<float> responses(data.rows, 2);
    for (int i = 0; i<data.rows; ++i)
    {
        if (i < data.rows/2)
        {
            data(i, 0) = 1;
            data(i, 1) = 0;
        }
        else
        {
            data(i, 0) = 0;
            data(i, 1) = 1;
        }
    }

    //Mat_<float> responses(data.rows, 1);
    //for (int i=0; i<responses.rows; ++i)
    //    responses(i, 0) = i < responses.rows / 2 ? 0 : 1;

    //create the neural network
    Mat_<int> layerSizes(1, 3);
    layerSizes(0, 0) = data.cols;
    layerSizes(0, 1) = 20;
    layerSizes(0, 2) = 2;

    Ptr<ANN_MLP> network = ANN_MLP::create();
    network->setLayerSizes(layerSizes);
    network->setActivationFunction(0, 0.1, 0.1);
    network->setTrainMethod(0, 0.1, 0.1);

    Mat_<int> varType = Mat(1, data.cols+2, CV_8U);
    for (int i = 0; i<data.cols; ++i)
        varType(0, i) = VAR_ORDERED;
    //varType(0, varType.cols-2) = varType(0, varType.cols-1) = VAR_CATEGORICAL;
    varType(0, varType.cols-1) = varType(0, varType.cols-1) = VAR_ORDERED;
    Ptr<TrainData> trainData = TrainData::create(data, ROW_SAMPLE, responses, noArray(), noArray(), noArray(), varType);

    network->train(trainData);
    if (network->isTrained())
    {
        printf("Predict:\n");
        network->predict(Mat::ones(1, data.cols, data.type()));
        printf("Prediction done!\n");

        for (int i=0; i<data.rows; ++i)
            network->predict(data.row(i));
    }

    return 0;
}

Neural Network in OpenCV 3.1.0

Hello everyone!

I am currently trying to get OpenCV's neural network module running, unluckily so far with less success. Initialization and training works fine (at least as far as I can verify it) but as soon as I try to do a prediction, I'm receiving segmentation fault errors... I tried training / predicting on both Windows 8 as well as Ubuntu 16.04 on a custom Linux build as well as on a third-party Windows build respectively, as soon as I try a prediction, the same error occurs.

I also prepared some usable example code. Of course I know that training on randomly generated data makes not too much sense in practice, I only wanted to keep things simple for a minimum running example:

#include <opencv2/ml/ml.hpp>

using namespace cv;
using namespace cv::ml;

int main(int argc, char *argv[])
{
    //create random training data
    Mat_<float> data(100, 100);
    randn(data, Mat::zeros(1, 1, data.type()), Mat::ones(1, 1, data.type()));

    //half of the samples for each class
    Mat_<float> responses(data.rows, 1);
    for (int i=0; i<responses.rows; ++i)
        responses(i, 0) = i < responses.rows / 2 ? 0 : 1;

    //create the neural network
    Mat_<int> layerSizes(1, 3);
    layerSizes(0, 0) = data.cols;
    layerSizes(0, 1) = 20;
    layerSizes(0, 2) = 1;

    Ptr<ANN_MLP> networkPtr = ANN_MLP::create();
    ANN_MLP* network = networkPtr.get();
    network->setLayerSizes(layerSizes);
    network->setActivationFunction(0, 0.1, 0.1);
    network->setTrainMethod(0, 0.1, 0.1);

    /*
    //test to change variable type flags -> problem stays the same
    Mat_<int> varType = Mat(1, data.cols+1, CV_8U);
    for (int i = 0; i<data.cols; ++i)
        varType(0, i) = VAR_ORDERED;
    varType(0, varType.cols-1) = VAR_CATEGORICAL;
    //varType(0, varType.cols-1) = VAR_ORDERED;
    Ptr<TrainData> trainData = TrainData::create(data, ROW_SAMPLE, responses, noArray(), noArray(), noArray(), varType);
    */

    Ptr<TrainData> trainData = TrainData::create(data, ROW_SAMPLE, responses);
    network->train(trainData);

    if (network->isTrained())
    {
        printf("Predict:\n");
        network->predict(Mat::ones(1, data.cols, data.type())); //SEGMENTATION FAULT
        printf("Prediction done!\n");
    }

    return 0;
}

Does anyone got the Neural Network running in OpenCV 3.1.0? For me either I'm doing something wrong (in case, please let me know) or this is a bug in OpenCV... I would appreciate any comments :-)

edit - updated source code:

#include <opencv2/ml/ml.hpp>

using namespace cv;
using namespace cv::ml;

int main(int argc, char *argv[])
{
    //create random training data
    Mat_<float> data(100, 100);
    randn(data, Mat::zeros(1, 1, data.type()), Mat::ones(1, 1, data.type()));

    //half of the samples for each class
    Mat_<float> responses(data.rows, 2);
    for (int i = 0; i<data.rows; ++i)
    {
        if (i < data.rows/2)
        {
            data(i, 0) = 1;
            data(i, 1) = 0;
        }
        else
        {
            data(i, 0) = 0;
            data(i, 1) = 1;
        }
    }

    //Mat_<float> responses(data.rows, 1);
    //for (int i=0; i<responses.rows; ++i)
    //    responses(i, 0) = i < responses.rows / 2 ? 0 : 1;

    //create the neural network
    Mat_<int> layerSizes(1, 3);
    layerSizes(0, 0) = data.cols;
    layerSizes(0, 1) = 20;
    layerSizes(0, 2) = 2;

    Ptr<ANN_MLP> network = ANN_MLP::create();
    network->setLayerSizes(layerSizes);
    network->setActivationFunction(0, 0.1, 0.1);
    network->setTrainMethod(0, 0.1, 0.1);

    Mat_<int> varType = Mat(1, data.cols+2, CV_8U);
    for (int i = 0; i<data.cols; ++i)
        varType(0, i) = VAR_ORDERED;
    //varType(0, varType.cols-2) = varType(0, varType.cols-1) = VAR_CATEGORICAL;
    varType(0, varType.cols-1) varType.cols-2) = varType(0, varType.cols-1) = VAR_ORDERED;
    Ptr<TrainData> trainData = TrainData::create(data, ROW_SAMPLE, responses, noArray(), noArray(), noArray(), varType);

    network->train(trainData);
    if (network->isTrained())
    {
        printf("Predict:\n");
        network->predict(Mat::ones(1, data.cols, data.type()));
        printf("Prediction done!\n");

        for (int i=0; i<data.rows; ++i)
            network->predict(data.row(i));
    }

    return 0;
}
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