MNISTPatchReconstructionApplication.hpp

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#ifndef MNISTPATCHRECONSTRUCTIONAPPLICATION_H_
#define MNISTPATCHRECONSTRUCTIONAPPLICATION_H_


#include <opengl/application/OpenGLContinuousLearningApplication.hpp>

#include <opengl/visualization/WindowMatrix2D.hpp>
#include <opengl/visualization/WindowCollectorChart.hpp>
using namespace mic::opengl::visualization;

#include <importers/MNISTPatchImporter.hpp>

#include <mlnn/BackpropagationNeuralNetwork.hpp>
using namespace mic::mlnn;

namespace mic {
namespace applications {

class MNISTPatchReconstructionApplication: public mic::opengl::application::OpenGLContinuousLearningApplication {
public:
    MNISTPatchReconstructionApplication(std::string node_name_ = "mnist_patch_autoencoder_reconstruction");

    virtual ~MNISTPatchReconstructionApplication();

protected:
    virtual void initializePropertyDependentVariables();

    virtual void initialize(int argc, char* argv[]);

    virtual bool performLearningStep();

    virtual void collectTestStatistics();

    virtual void populateTestStatistics();


private:
    mic::types::MatrixXfPtr input_image;

    mic::types::MatrixXfPtr reconstructed_image;

    mic::importers::MNISTPatchImporter* training_dataset_importer;

    mic::importers::MNISTPatchImporter* test_dataset_importer;

    WindowMatrix2D* w2d_input;

    WindowMatrix2D* w2d_reconstruction;

    WindowCollectorChart<float>* w_chart;

    size_t patch_size;

    mic::utils::DataCollectorPtr<std::string, float> collector_ptr;

    mic::configuration::Property<std::string> mlnn_filename;

    mic::configuration::Property<bool> mlnn_save;

    mic::configuration::Property<bool> mlnn_load;

    BackpropagationNeuralNetwork<float> neural_net;

};

} /* namespace applications */
} /* namespace mic */

#endif /* MNISTPATCHRECONSTRUCTIONAPPLICATION_H_ */