deep learning – Sugarcube

ImaproFX – JavaFX Image Processing Framework

Grasping the essence of image processing and analysis algorithms may prove to be quite difficult. To simplify the comprehension of such algorithms, sugarcubeIT proposes ImaproFX, a Java FX user interface providing live visual feedback thanks to interactive controllers.

The real power of ImaproFX comes from it’s Java coding framework… Coders can create their own image analysis ribbons simply by extending and implementing an abstract “ImaproFilterFx” class :

public class ContrastFilterFx extends ImaproFilterFx
{

    public @FXML Slider contrastSlider, luminositySlider;
    public @FXML CheckBox invertCheckbox;

    public ContrastFilterFx(FxEnvironment env)
    {
        super(env, "Contrast & Luminosity");
    }

    @Override
    public void reset()
    {
        contrastSlider.setValue(0);
        luminositySlider.setValue(0);
        invertCheckbox.setSelected(false);
    }

    @Override
    public void process(FilterImage image)
    {
        double contrast = Math.tan((0.5 + contrastSlider.getValue() / 200) * Math.PI / 2.0);
        double luminosity = luminositySlider.getValue() / 100;

        if (invertCheckbox.isSelected())
            contrast = -contrast;

        for (int y = 0; y < image.getHeight(); y++)
            for (int x = 0; x < image.getWidth(); x++)
            {
                float value = (float) ((image.getValue(x, y) - 0.5f) * contrast + 0.5f);

                if (value > 1)
                    value = 1;
                else if (value < 0)
                    value = 0;

                image.setValue(x, y, value + luminosity);
            }
    }
}

public class ContrastFilterFx extends ImaproFilterFx

{

public @FXML Slider contrastSlider, luminositySlider;

public @FXML CheckBox invertCheckbox;

public ContrastFilterFx(FxEnvironment env)

{

super(env, "Contrast & Luminosity");

}

@Override

public void reset()

{

contrastSlider.setValue(0);

luminositySlider.setValue(0);

invertCheckbox.setSelected(false);

}

@Override

public void process(FilterImage image)

{

double contrast = Math.tan((0.5 + contrastSlider.getValue() / 200) * Math.PI / 2.0);

double luminosity = luminositySlider.getValue() / 100;

if (invertCheckbox.isSelected())

contrast = -contrast;

for (int y = 0; y < image.getHeight(); y++)

for (int x = 0; x < image.getWidth(); x++)

{

float value = (float) ((image.getValue(x, y) - 0.5f) * contrast + 0.5f);

if (value > 1)

value = 1;

else if (value < 0)

value = 0;

image.setValue(x, y, value + luminosity);

}

Post written by Jean-Luc Bloechle

An interesting feature of Deep Neural Networks is their ability to tend to a simplified image using few neurons and many layers… Watch this CNN training evolution giving birth to AI artistic painting !

Using sugarcube’s Deep Learning API :

CNN cnn = new CNN(1, 1, xy.length);
for (int i = 0; i< 11; i++)
  cnn.addFull(16, CNN.RELU);
cnn.addRegression(3);

CNNTrainer trainer = cnn.trainer();
trainer.method = CNNTrainer.SGD;
trainer.learningRate = 0.01;
trainer.momentum = 0.3;
trainer.batchSize = 1;
trainer.l2Decay = 0;
trainer.reset();

CNN cnn = new CNN(1, 1, xy.length);

for (int i = 0; i< 11; i++)

cnn.addFull(16, CNN.RELU);

cnn.addRegression(3);

CNNTrainer trainer = cnn.trainer();

trainer.method = CNNTrainer.SGD;

trainer.learningRate = 0.01;

trainer.momentum = 0.3;

trainer.batchSize = 1;

trainer.l2Decay = 0;

trainer.reset();

Post written by Jean-Luc Bloechle

Tag: deep learning

ImaproFX – Image Processing Framework

Deep Neural Network – Learning to draw