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 void AddImage(string filename, string category)
{
string uniqueID = Guid.NewGuid().ToString();
// Try to read as a bitmap. The caller should have a catch block that will handle non images (better to do this now than bomb later)
BitmapSource bitmap = new BitmapImage(new Uri(filename));
// Build entry
FeatureRecognizer_Image entry = new FeatureRecognizer_Image()
{
Category = category,
UniqueID = uniqueID,
Filename = filename,
//ImageControl = FeatureRecognizer.GetTreeviewImageCtrl(new BitmapImage(new Uri(filename))),
//Bitmap = bitmap,
};
// Store it
//FeatureRecognizer.AddImage(entry, _images, treeImages, cboImageLabel);
_images.Add(entry);
}
