/// <summary>
/// Calculates LBP from 2D array
/// Enter array, radius and neighbours.
/// </summary>
public static void PipelineLBP(double[,] image, Parameters param,
out double[,] result, out int[] histogram)
{
// Create instance of LBPApplication and set input variables
LBPApplication LBPapp = new LBPApplication
{
Image = image,
Param = param,
MRE = false // Don't use MRELBP methods
};
// Result image size
LBPapp.d = LBPapp.Param.Radius;
LBPapp.xSize = image.GetLength(0) - 2 * LBPapp.d;
LBPapp.ySize = image.GetLength(1) - 2 * LBPapp.d;
// Calculate mapping and LBP image
LBPapp.GetMapping();
LBPapp.CalculateImage();
// Calculate histogram
LBPapp.GetHistogram();
// output variables
result = LBPapp.LBPISMapped; // Mapping
histogram = LBPapp.histS;
}
/// <summary>
/// Calculates MRELBP from 2D array
/// Enter array and parameters class including small and large radius, neighbours and kernel weights.
/// Weights are for center pixels (w_c), small (w_r[0]) and large (w_r[1]) radius.
/// </summary>
public static void PipelineMRELBP(double[,] image, Parameters param,
out double[,] LBPIL, out double[,] LBPIS, out double[,] LBPIR, out int[] histL, out int[] histS, out int[] histR, out int[] histCenter)
{
// Create instance of LBPApplication and set input variables
LBPApplication MRELBPapp = new LBPApplication
{
Image = image,
Param = param,
d = param.LargeRadius + (param.W_r[0] - 1) / 2,
MRE = true // Median robust extended LBP
};
// Calculate mapping
MRELBPapp.GetMapping();
// Result image size
MRELBPapp.xSize = image.GetLength(0) - 2 * MRELBPapp.d;
MRELBPapp.ySize = image.GetLength(1) - 2 * MRELBPapp.d;
// Scale image
MRELBPapp.Scaling();
// Median filtering using given weights
MRELBPapp.FilterImage();
// Calculate LBP image
MRELBPapp.CalculateImage();
// Calculate histogram
MRELBPapp.GetHistogram();
// output variables
//LBPIL = MRELBPapp.LBPILMapped; // Mapping
//LBPIS = MRELBPapp.LBPISMapped;
//LBPIR = MRELBPapp.LBPIRMapped;
LBPIL = MRELBPapp.LBPIL; // No mapping
LBPIS = MRELBPapp.LBPIS;
LBPIR = MRELBPapp.LBPIR;
histL = MRELBPapp.histL;
histS = MRELBPapp.histS;
histR = MRELBPapp.histR;
histCenter = MRELBPapp.histCenter;
}
/// <summary>
/// Calculate single LBP image. For LBP image, path and savepath should be defined first.
/// For MRELBP image meanpath, stdpath and savepath should be defined first.
/// </summary>
public void CalculateSingle()
{
// Timer
var time = Stopwatch.StartNew();
// Load image
double[,] image, imagemean, imagestd;
if (param.Meanstd)
{
if (param.ImageType == ".dat" && meanpath.EndsWith(".dat") && stdpath.EndsWith(".dat"))
{
lbpreader.ReadLBPFeatures(param.Precision, meanpath); // Read binary image
imagemean = lbpreader.image_double;
lbpreader.ReadLBPFeatures(param.Precision, stdpath); // Read binary image
imagestd = lbpreader.image_double;
image = imagemean.Add(imagestd); // Combine mean and std images
}
else if ((meanpath.EndsWith(".png") && stdpath.EndsWith(".png")) || (meanpath.EndsWith(".bmp") && stdpath.EndsWith(".png")))
{
imagemean = Functions.Load(meanpath).ToDouble();
imagestd = Functions.Load(stdpath).ToDouble();
image = imagemean.Add(imagestd); // Combine mean and std images
}
else
{
Console.WriteLine("One of image types not compatible.\n");
return;
}
}
else
{
if (param.ImageType == ".dat" && path.EndsWith(".dat"))
{
lbpreader.ReadLBPFeatures(param.Precision, path); // Read binary image
image = lbpreader.image_double;
}
else if (path.EndsWith(".png") || path.EndsWith(".bmp"))
{
image = Functions.Load(path).ToDouble();
}
else
{
Console.WriteLine("Image type not compatible.\n");
return;
}
}
// LBP
if (param.Mre)
{
if (param.Stand)
{
// Grayscale normalization (weights and sigmas from parameters class)
var standrd = new LocalStandardization(param.W_stand[0], param.W_stand[1], param.W_stand[2], param.W_stand[3]);
standrd.Standardize(ref image, "Reflect"); // standardize given image
}
// Run MRELBP
Console.WriteLine("\nRunning MRELBP:\n");
LBPApplication.PipelineMRELBP(image, param,
out double[,] LBPIL, out double[,] LBPIS, out double[,] LBPIR, out int[] histL, out int[] histS, out int[] histR, out int[] histCenter);
if (param.Meanstd) // update save path for mean and std images
{
path = meanpath;
}
if (param.Save && savepath != null) // Save images
{
Functions.Save(savepath + "\\" + Path.GetFileName(path).Replace(Path.GetExtension(path), "") + "_LBPIL.png", LBPIL, param.Scale);
Functions.Save(savepath + "\\" + Path.GetFileName(path).Replace(Path.GetExtension(path), "") + "_LBPIS.png", LBPIS, param.Scale);
Functions.Save(savepath + "\\" + Path.GetFileName(path).Replace(Path.GetExtension(path), "") + "_LBPIR.png", LBPIR, param.Scale);
}
// Concatenate histograms
f = Matrix.Concatenate(histCenter, Matrix.Concatenate(histL, Matrix.Concatenate(histS, histR)));
}
else
{
// Run LBP
Console.WriteLine("\nRunning LBP:\n");
LBPApplication.PipelineLBP(image, param,
out double[,] LBPresult, out int[] LBPhistogram); // Get LBP for test image;
if (param.Save) // Save images
{
Functions.Save(savepath + "\\" + Path.GetFileName(path).Replace(Path.GetExtension(path), "") + "_LBP.png", LBPresult, param.Scale);
}
f = LBPhistogram;
}
// Results
features = Matrix.Concatenate(features, f);
if (savepath != null)
{
// Write features to csv
Functions.WriteCSV(features.ToSingle(), savepath + "\\features.csv");
// Write features to binary file
var binwriter = new BinaryWriterApp()
{
filename = savepath + "\\features.dat"
};
binwriter.SaveBinary(features);
}
Console.WriteLine("LBP images calculated and results saved.\nElapsed time: {0}min {1}sec", time.Elapsed.Minutes, time.Elapsed.Seconds);
time.Stop();
}
/// <summary>
/// Calculate all images from given path directory with selected extension.
/// Savepath sould also be defined.
/// </summary>
public void CalculateBatch()
{
// Timer
var time = Stopwatch.StartNew();
var timeFull = Stopwatch.StartNew();
// Get files from sample directory
string[] dir;
if (param.ImageType == ".dat")
{
dir = Directory.GetFiles(path, "*.dat");
}
else
{
dir = Directory.GetFiles(path, "*.png");
}
Array.Sort(dir);
if (param.Mre)
{
// Loop for calculating MRELBP for whole dataset
for (int k = 0; k < dir.Length; k++)
{
// Load images
double[,] imagemean, imagestd, image = null;
if (param.ImageType == ".dat" && param.Meanstd)
{
lbpreader.ReadLBPFeatures(param.Precision, dir[k]); // Read binary mean image
imagemean = lbpreader.image_double;
k++;
lbpreader.ReadLBPFeatures(param.Precision, dir[k]); // Read binary std image
imagestd = lbpreader.image_double;
image = imagemean.Add(imagestd); // Combine mean and std images
}
else if (param.Meanstd) // Check whether to sum two adjacent images
{
imagemean = Functions.Load(dir[k]).ToDouble();
k++;
imagestd = Functions.Load(dir[k]).ToDouble();
image = imagemean.Add(imagestd); // Combine mean and std images
}
else if (param.ImageType == ".dat" && !param.Meanstd) // Don't combine images
{
lbpreader.ReadLBPFeatures(param.Precision, dir[k]); // Read binary mean image
image = lbpreader.image_double;
}
else if (!param.Meanstd)
{
image = Functions.Load(dir[k]).ToDouble();
}
if (param.Stand)
{
// Grayscale normalization (weights and sigmas from parameters class)
var standrd = new LocalStandardization(param.W_stand[0], param.W_stand[1], param.W_stand[2], param.W_stand[3]);
standrd.Standardize(ref image, "Reflect"); // standardize given image
}
// Calculate MRELBP
LBPApplication.PipelineMRELBP(image, param,
out double[,] LBPIL, out double[,] LBPIS, out double[,] LBPIR, out int[] histL, out int[] histS, out int[] histR, out int[] histCenter);
// Concatenate histograms
f = Matrix.Concatenate(histCenter, Matrix.Concatenate(histL, Matrix.Concatenate(histS, histR)));
features = Matrix.Concatenate(features, f);
if (param.Save && savepath != null) // Save LBP image
{
Functions.Save(savepath + "\\" + Path.GetFileName(dir[k]).Replace(Path.GetExtension(dir[k]), "") + "_small.png", LBPIS, param.Scale);
Functions.Save(savepath + "\\" + Path.GetFileName(dir[k]).Replace(Path.GetExtension(dir[k]), "") + "_large.png", LBPIL, param.Scale);
Functions.Save(savepath + "\\" + Path.GetFileName(dir[k]).Replace(Path.GetExtension(dir[k]), "") + "_radial.png", LBPIR, param.Scale);
}
Console.WriteLine("Image: {0}, elapsed time: {1}ms", dir[k], time.ElapsedMilliseconds);
time.Restart();
}
}
else
{
// Loop for calculating LBP for whole dataset
for (int k = 0; k < dir.Length; k++)
{
// Load images
double[,] image;
if (param.ImageType == ".dat")
{
lbpreader.ReadLBPFeatures(param.Precision, dir[k]); // Read binary image
image = lbpreader.image_double;
}
else
{
image = Functions.Load(dir[k]).ToDouble(); // Read png or bmp image
}
LBPApplication.PipelineLBP(image, param,
out double[,] LBPresult, out int[] LBPhistogram); // Get LBP for test image;
// Concatenate histograms
features = Matrix.Concatenate(features, LBPhistogram);
if (param.Save && savepath != null) // Save images
{
Functions.Save(savepath + "\\" + Path.GetFileName(dir[k]).Replace(Path.GetExtension(dir[k]), "") + "_LBP.png", LBPresult, param.Scale);
}
Console.WriteLine("Image: {0}, elapsed time: {1}ms", dir[k], time.ElapsedMilliseconds);
time.Restart();
}
}
if (savepath != null)
{
// Write features to csv
Functions.WriteCSV(features.ToSingle(), savepath + "\\features.csv");
// Write features to binary file
var binwriter = new BinaryWriterApp()
{
filename = savepath + "\\features.dat"
};
binwriter.SaveBinary(features);
}
Console.WriteLine("All LBP images calculated and results saved.\nElapsed time: {0}min {1}sec", timeFull.Elapsed.Minutes, timeFull.Elapsed.Seconds);
time.Stop(); timeFull.Stop();
}
