public void ProcessImageTest2()
{
double[,] diag = Matrix.Magic(5);
Bitmap input;
new MatrixToImage().Convert(diag, out input);
// Create a new Kuwahara filter
Kuwahara filter = new Kuwahara();
// Apply the filter
Bitmap output = filter.Apply(input);
double[,] actual;
new ImageToMatrix().Convert(output, out actual);
string str = actual.ToString(CSharpMatrixFormatProvider.InvariantCulture);
double[,] expected =
{
{ 0.937254901960784, 0.909803921568627, 1, 0.972549019607843, 0.945098039215686 },
{ 0.913725490196078, 0.984313725490196, 0.976470588235294, 0.949019607843137, 0.941176470588235 },
{ 0.988235294117647, 0.980392156862745, 0.952941176470588, 0.925490196078431, 0.917647058823529 },
{ 0.964705882352941, 0.956862745098039, 0.929411764705882, 0.92156862745098, 0.992156862745098 },
{ 0.96078431372549, 0.933333333333333, 0.905882352941176, 0.996078431372549, 0.968627450980392 }
};
Assert.IsTrue(expected.IsEqual(actual, 1e-6));
}
public mEffectKuwahara(int kernalSize)
{
BitmapType = mFilter.BitmapTypes.GrayscaleBT709;
KernalSize = kernalSize;
Effect = new Kuwahara();
Effect.Size = KernalSize;
filter = Effect;
}
public void KuwaharaTest1()
{
Bitmap image = Accord.Imaging.Image.Clone(Resources.lena512);
Kuwahara kuwahara = new Kuwahara();
Bitmap result = kuwahara.Apply(image);
//ImageBox.Show(result);
Assert.IsNotNull(result);
}
public void KuwaharaTest1()
{
Bitmap image = Properties.Resources.lena512;
Kuwahara kuwahara = new Kuwahara();
Bitmap result = kuwahara.Apply(image);
//ImageBox.Show(result);
Assert.IsNotNull(result);
}
/// <summary>
/// Fast Implementation of Kuwahara filter. Work only with grayscale See https://en.wikipedia.org/wiki/Kuwahara_filter
/// </summary>
/// <param name="image"></param>
/// <param name="kernelSize">Kuwahara kernel size</param>
public static Bitmap GrayscaleKuwahara(this Bitmap image, int kernelSize)
{
if (image.PixelFormat != PixelFormat.Format8bppIndexed)
{
throw new NotSupportedException("Filter can be applied to binary 8bpp images only");
}
Kuwahara kuwahara = new Kuwahara {
Size = kernelSize
};
return(kuwahara.Apply(image));
}
/// <summary>
/// Kuwahara filter.
/// <para>Accord.NET internal call. See: <see cref="Accord.Imaging.Filters.Kuwahara"/> for details.</para>
/// </summary>
/// <param name="img">Image.</param>
/// <param name="size">the size of the kernel used in the Kuwahara filter. This should be odd and greater than or equal to five</param>
/// <param name="blockSize">the size of each of the four inner blocks used in the Kuwahara filter. This is always half the <paramref name="size"/> minus one.</param>
/// <param name="inPlace">Apply in place or not. If it is set to true return value can be omitted.</param>
/// <returns>Processed image.</returns>
public static Image <Gray, byte> Kuwahara(this Image <Gray, byte> img, int size = 5, int blockSize = 2, bool inPlace = false)
{
Kuwahara k = new Kuwahara();
return(img.ApplyFilter(k, inPlace));
}
/// <summary>
/// Kuwahara filter.
/// <para>Accord.NET internal call. See: <see cref="Accord.Imaging.Filters.Kuwahara"/> for details.</para>
/// </summary>
/// <param name="img">Image.</param>
/// <param name="size">the size of the kernel used in the Kuwahara filter. This should be odd and greater than or equal to five</param>
/// <param name="blockSize">the size of each of the four inner blocks used in the Kuwahara filter. This is always half the <paramref name="size"/> minus one.</param>
/// <param name="inPlace">Apply in place or not. If it is set to true return value can be omitted.</param>
/// <returns>Processed image.</returns>
public static Gray <byte>[,] Kuwahara(this Gray <byte>[,] img, int size = 5, int blockSize = 2, bool inPlace = false)
{
Kuwahara k = new Kuwahara();
return(img.ApplyFilter(k, inPlace));
}
private void kuwaharaToolStripMenuItem_Click(object sender, EventArgs e)
{
Kuwahara customMask = new Kuwahara(this);
customMask.Show();
}
/// <summary>
/// This is the method that actually does the work.
/// </summary>
/// <param name="DA">The DA object is used to retrieve from inputs and store in outputs.</param>
protected override void SolveInstance(IGH_DataAccess DA)
{
IGH_Goo goo = null;
Image image = new Image();
if (!DA.GetData(0, ref goo))
{
return;
}
if (!goo.TryGetImage(ref image))
{
return;
}
int mode = 0;
DA.GetData(1, ref mode);
double numValA = 0;
DA.GetData(2, ref numValA);
double numValB = 0;
DA.GetData(3, ref numValB);
Filter filter = new Filter();
switch ((FilterModes)mode)
{
case FilterModes.Additive:
SetParameter(2);
SetParameter(3);
filter = new Additive();
image.Filters.Add(new Additive());
break;
case FilterModes.Daube:
SetParameter(2, "S", "Size", "[0-1] Unitized adjustment value");
SetParameter(3);
filter = new Daube(numValA);
image.Filters.Add(new Daube(numValA));
break;
case FilterModes.SaltPepper:
SetParameter(2, "N", "Noise", "[0-1] Unitized adjustment value");
SetParameter(3);
filter = new SaltPepper(numValA);
image.Filters.Add(new SaltPepper(numValA));
break;
case FilterModes.Jitter:
SetParameter(2, "R", "Radius", "[0-1] Unitized adjustment value");
SetParameter(3);
filter = new Jitter(numValA);
image.Filters.Add(new Jitter(numValA));
break;
case FilterModes.Kuwahara:
SetParameter(2, "S", "Size", "[0-1] Unitized adjustment value");
SetParameter(3);
filter = new Kuwahara(numValA);
image.Filters.Add(new Kuwahara(numValA));
break;
case FilterModes.Posterize:
SetParameter(2, "I", "Interval", "[0-1] Unitized adjustment value");
SetParameter(3);
filter = new Posterize(numValA);
image.Filters.Add(new Posterize(numValA));
break;
case FilterModes.GaussianBlur:
SetParameter(2, "X", "Sigma", "[0-1] Unitized adjustment value");
SetParameter(3, "S", "Size", "[0-1] Unitized adjustment value");
filter = new GaussianBlur(numValA, numValB);
image.Filters.Add(new GaussianBlur(numValA, numValB));
break;
case FilterModes.Pixellate:
SetParameter(2, "W", "Width", "[0-1] Unitized adjustment value");
SetParameter(3, "H", "Height", "[0-1] Unitized adjustment value");
filter = new Pixellate(numValA, numValB);
image.Filters.Add(new Pixellate(numValA, numValB));
break;
case FilterModes.Blur:
SetParameter(2, "D", "Divisor", "[0-1] Unitized adjustment value");
SetParameter(3, "T", "Threshold", "[0-1] Unitized adjustment value");
filter = new Blur(numValA, numValB);
image.Filters.Add(new Blur(numValA, numValB));
break;
}
message = ((FilterModes)mode).ToString();
UpdateMessage();
DA.SetData(0, image);
DA.SetData(1, filter);
}
