private static double[] GetTrainingImage(FeatureRecognizer_Image image, ConvolutionBase2D kernel)
{
// Enlarge the initial image by the kernel's reduction so that after convolution, it is the desired size
VectorInt reduction = kernel.GetReduction();
if (reduction.X != reduction.Y)
{
throw new ApplicationException(string.Format("Kernel should be square: {0}x{1}", reduction.X, reduction.Y));
}
BitmapSource bitmap = new BitmapImage(new Uri(image.Filename));
bitmap = UtilityWPF.ResizeImage(bitmap, IMAGESIZE + reduction.X, true);
Convolution2D retVal = UtilityWPF.ConvertToConvolution(bitmap, 1d);
if (retVal.Width != retVal.Height)
{
retVal = Convolutions.ExtendBorders(retVal, IMAGESIZE + reduction.X, IMAGESIZE + reduction.X); //NOTE: width or height is already the desired size, this will just enlarge the other to make it square
}
retVal = Convolutions.Convolute(retVal, kernel);
retVal = Convolutions.Abs(retVal);
// It looks better when it's black on white
double[] inverted = retVal.Values.
Select(o => 1d - o).
ToArray();
return(inverted);
}
private static Convolution2D Convolute(Convolution2D conv, ToVectorInstructions instr)
{
Convolution2D retVal = conv;
if (retVal.Width != retVal.Height)
{
int max = Math.Max(retVal.Width, retVal.Height);
retVal = Convolutions.ExtendBorders(retVal, max, max); // make it square
}
if (instr.ShouldNormalize)
{
retVal = Convolutions.Normalize(retVal);
}
if (instr.Convolution != null)
{
retVal = Convolutions.Convolute(retVal, instr.Convolution);
}
retVal = Convolutions.MaxPool(retVal, instr.ToSize, instr.ToSize);
retVal = Convolutions.Abs(retVal);
return(retVal);
}
private void ApplyFilter(ConvolutionBase2D kernel)
{
// Convert the original image to grayscale
Convolution2D image = GetOriginalImageGrays();
if (image == null)
{
// The original image is empty
return;
}
Convolution2D filtered = null;
if (kernel is Convolution2D)
{
#region Single
Convolution2D kernelSingle = (Convolution2D)kernel;
// This window builds kernels without gain or iterations, so make a clone with those tacked on
Convolution2D kernelFinal = new Convolution2D(
kernelSingle.Values,
kernelSingle.Width,
kernelSingle.Height,
kernelSingle.IsNegPos,
trkGain.Value,
Convert.ToInt32(trkIterations.Value),
chkExpandBorder.IsChecked.Value);
filtered = Convolutions.Convolute(image, kernelFinal);
if (chkSubtract.IsChecked.Value)
{
filtered = Convolutions.Subtract(image, filtered);
}
#endregion
}
else if (kernel is ConvolutionSet2D)
{
#region Set
ConvolutionSet2D kernelSet = (ConvolutionSet2D)kernel;
filtered = Convolutions.Convolute(image, kernelSet);
#endregion
}
else
{
throw new ArgumentException("Unknown type of kernel: " + kernel.GetType().ToString());
}
// Show Filtered
modifiedImage.Source = Convolutions.GetBitmap(filtered, (ConvolutionResultNegPosColoring)cboEdgeColors.SelectedValue);
}
