public void LearningBasedWBExtractSimpleFeatures()
{
using (var wb = LearningBasedWB.Create(null))
using (var src = Image("lenna.png"))
using (var dst = new Mat())
{
wb.ExtractSimpleFeatures(src, dst);
unsafe
{
// 1. Chromaticity of an average (R,G,B) tuple
// 2. Chromaticity of the brightest (R,G,B) tuple (while ignoring saturated pixels)
// 3. Chromaticity of the dominant (R,G,B) tuple (the one that has the highest value
// in the RGB histogram)
// 4. Mode of the chromaticity palette, that is constructed by taking 300 most common
// colors according to the RGB histogram and projecting them on the chromaticity plane.
// Mode is the most high-density point of the palette, which is computed by a straightforward
// fixed-bandwidth kernel density estimator with a Epanechnikov kernel function.
Console.WriteLine(dst.DataPointer[0]);
Console.WriteLine(dst.DataPointer[1]);
Console.WriteLine(dst.DataPointer[2]);
Console.WriteLine(dst.DataPointer[3]);
}
}
}
public void Sample()
{
if (!Debugger.IsAttached)
{
return;
}
string[] files;
using (var dialog = new System.Windows.Forms.OpenFileDialog
{
RestoreDirectory = true,
Multiselect = true,
Filter = "Image Files(*.png;*.jpg;*.jpeg;*.bmp)|*.png;*.jpg;*.jpeg;*.bmp"
})
{
if (dialog.ShowDialog() != System.Windows.Forms.DialogResult.OK)
{
return;
}
files = dialog.FileNames;
}
var desktop = Environment.GetFolderPath(Environment.SpecialFolder.Desktop);
var dstDir = System.IO.Path.Combine(desktop, "WB");
System.IO.Directory.CreateDirectory(dstDir);
using var simpleWB = SimpleWB.Create();
using var learningWB = LearningBasedWB.Create("");
using var grayworldWB = GrayworldWB.Create();
foreach (var file in files)
{
testOutputHelper.WriteLine(System.IO.Path.GetFileNameWithoutExtension(file));
using var src = new Mat(file);
using var dstSimple = new Mat();
using var dstLearning = new Mat();
using var dstGrayworld = new Mat();
simpleWB.BalanceWhite(src, dstSimple);
learningWB.BalanceWhite(src, dstLearning);
grayworldWB.BalanceWhite(src, dstGrayworld);
using var temp1 = new Mat();
using var temp2 = new Mat();
using var dst = new Mat();
Cv2.HConcat(src, dstSimple, temp1);
Cv2.HConcat(dstLearning, dstGrayworld, temp2);
Cv2.VConcat(temp1, temp2, dst);
/*
* using (new Window("src", src))
* using (new Window("dst", dst))
* {
* Cv2.WaitKey();
* }*/
dst.SaveImage(System.IO.Path.Combine(dstDir, $"{System.IO.Path.GetFileNameWithoutExtension(file)}.png"));
}
}
public void LearningBasedWBProperties()
{
using var wb = LearningBasedWB.Create(null);
var histBinNum = wb.HistBinNum;
var rangeMaxVal = wb.RangeMaxVal;
var saturationThreshold = wb.SaturationThreshold;
const int ival = 100;
const float fval = 100f;
wb.HistBinNum = ival;
wb.RangeMaxVal = ival;
wb.SaturationThreshold = fval;
Assert.Equal(ival, wb.HistBinNum);
Assert.Equal(ival, wb.RangeMaxVal);
Assert.Equal(fval, wb.SaturationThreshold);
Assert.NotEqual(histBinNum, wb.HistBinNum);
Assert.NotEqual(rangeMaxVal, wb.RangeMaxVal);
Assert.NotEqual(saturationThreshold, wb.SaturationThreshold);
}