Class AutoMaskingArgs
Class AutoMaskingArgs
Navne til: Aspose.Imaging.Masking.Options Sammensætning: Aspose.Imaging.dll (25.4.0)
Representerer de argumenter, der er angivet for automatiserede maskeringsmetoder
public class AutoMaskingArgs : IMaskingArgsInheritance
Implements
De arvede medlemmer
object.GetType() , object.MemberwiseClone() , object.ToString() , object.Equals(object?) , object.Equals(object?, object?) , object.ReferenceEquals(object?, object?) , object.GetHashCode()
Examples
Dette eksempel viser, hvordan man nedbryder et rasterbillede i flere billeder ved hjælp af billedmasking og K-means segmentation algoritme.
string dir = "c:\\temp\\";
using (Aspose.Imaging.RasterImage image = (Aspose.Imaging.RasterImage)Aspose.Imaging.Image.Load(dir + "Blue hills.png"))
{
Aspose.Imaging.Masking.Options.AutoMaskingArgs args = new Aspose.Imaging.Masking.Options.AutoMaskingArgs();
// Set the number of clusters (separated objects). The default value is 2, the foreground object and the background.
args.NumberOfObjects = 3;
// Set the maximum number of iterations.
args.MaxIterationNumber = 50;
// Set the precision of segmentation method (optional)
args.Precision = 1;
// Each cluster (segment) will be stored to a separate PNG file.
Aspose.Imaging.ImageOptions.PngOptions exportOptions = new Aspose.Imaging.ImageOptions.PngOptions();
exportOptions.ColorType = Aspose.Imaging.FileFormats.Png.PngColorType.TruecolorWithAlpha;
exportOptions.Source = new Aspose.Imaging.Sources.StreamSource(new System.IO.MemoryStream());
Aspose.Imaging.Masking.Options.MaskingOptions maskingOptions = new Aspose.Imaging.Masking.Options.MaskingOptions();
// Use K-means clustering.
// K-means clustering allows to split image into several independent clusters (segments).
maskingOptions.Method = Masking.Options.SegmentationMethod.KMeans;
maskingOptions.Decompose = true;
maskingOptions.Args = args;
// The backgroung color will be orange.
maskingOptions.BackgroundReplacementColor = Aspose.Imaging.Color.Orange;
maskingOptions.ExportOptions = exportOptions;
// Create an instance of the ImageMasking class.
Aspose.Imaging.Masking.ImageMasking masking = new Aspose.Imaging.Masking.ImageMasking(image);
// Divide the source image into several clusters (segments).
using (Aspose.Imaging.Masking.Result.MaskingResult maskingResult = masking.Decompose(maskingOptions))
{
// Obtain images from masking result and save them to PNG.
for (int i = 0; i < maskingResult.Length; i++)
{
string outputFileName = string.Format("Blue hills.Segment{0}.png", maskingResult[i].ObjectNumber);
using (Aspose.Imaging.Image resultImage = maskingResult[i].GetImage())
{
resultImage.Save(dir + outputFileName);
}
}
}
}Brug af en segmentmaske til at fremskynde segmentationsprocessen
// Masking export options
Aspose.Imaging.ImageOptions.PngOptions exportOptions = new Aspose.Imaging.ImageOptions.PngOptions();
exportOptions.ColorType = Aspose.Imaging.FileFormats.Png.PngColorType.TruecolorWithAlpha;
exportOptions.Source = new Aspose.Imaging.Sources.StreamSource(new System.IO.MemoryStream());
Aspose.Imaging.Masking.Options.MaskingOptions maskingOptions = new Aspose.Imaging.Masking.Options.MaskingOptions();
// Use GraphCut clustering.
maskingOptions.Method = Masking.Options.SegmentationMethod.GraphCut;
maskingOptions.Decompose = false;
maskingOptions.Args = new Aspose.Imaging.Masking.Options.AutoMaskingArgs();
// The backgroung color will be transparent.
maskingOptions.BackgroundReplacementColor = Aspose.Imaging.Color.Transparent;
maskingOptions.ExportOptions = exportOptions;
string dir = "c:\\temp\\";
using (Aspose.Imaging.RasterImage image = (Aspose.Imaging.RasterImage)Aspose.Imaging.Image.Load(dir + "BigImage.jpg"))
{
Aspose.Imaging.Size imageSize = image.Size;
// Reducing image size to speed up the segmentation process
image.ResizeHeightProportionally(600, Aspose.Imaging.ResizeType.HighQualityResample);
// Create an instance of the ImageMasking class.
Aspose.Imaging.Masking.ImageMasking masking = new Aspose.Imaging.Masking.ImageMasking(image);
// Divide the source image into several clusters (segments).
using (Aspose.Imaging.Masking.Result.MaskingResult maskingResult = masking.Decompose(maskingOptions))
{
// Getting the foreground mask
using (Aspose.Imaging.RasterImage foregroundMask = maskingResult[1].GetMask())
{
// Increase the size of the mask to the size of the original image
foregroundMask.Resize(imageSize.Width, imageSize.Height, Aspose.Imaging.ResizeType.NearestNeighbourResample);
// Applying the mask to the original image to obtain a foreground segment
using (Aspose.Imaging.RasterImage originImage = (Aspose.Imaging.RasterImage)Aspose.Imaging.Image.Load(dir + "BigImage.jpg"))
{
Aspose.Imaging.Masking.ImageMasking.ApplyMask(originImage, foregroundMask, maskingOptions);
originImage.Save(dir + "BigImage_foreground.png", exportOptions);
}
}
}
}Dette eksempel viser, hvordan man angiver forslag til billedmasking algoritme for at forbedre nøjagtigheden af segmentation (klustering) metode. billedet masking er en billedsbehandlingsteknik, der bruges til at splitte baggrunden fra de foregroundbilledobjekter.
string dir = "c:\\temp\\";
using (Aspose.Imaging.RasterImage image = (Aspose.Imaging.RasterImage)Aspose.Imaging.Image.Load(dir + "Gorilla.bmp"))
{
Aspose.Imaging.Masking.Options.AutoMaskingArgs args = new Aspose.Imaging.Masking.Options.AutoMaskingArgs();
// Suggestion #1.
// Analyze the image visually and set the area of interest. The result of segmentation will include only objects that will be completely located within this area.
args.ObjectsRectangles = new Rectangle[]
{
new Rectangle(86, 6, 270, 364),
};
// Suggestion #2.
// Analyze the image visually and set the points that belong to separated objects.
args.ObjectsPoints = new Point[][]
{
new Point[] { new Point(103, 326) },
new Point[] { new Point(280, 43) },
new Point[] { new Point(319, 86) },
};
// Each cluster (segment) will be stored to a separate PNG file.
Aspose.Imaging.ImageOptions.PngOptions exportOptions = new Aspose.Imaging.ImageOptions.PngOptions();
exportOptions.ColorType = Aspose.Imaging.FileFormats.Png.PngColorType.TruecolorWithAlpha;
exportOptions.Source = new Aspose.Imaging.Sources.StreamSource(new System.IO.MemoryStream());
Aspose.Imaging.Masking.Options.MaskingOptions maskingOptions = new Aspose.Imaging.Masking.Options.MaskingOptions();
// Use GraphCut clustering.
maskingOptions.Method = Masking.Options.SegmentationMethod.GraphCut;
maskingOptions.Decompose = false;
maskingOptions.Args = args;
// The backgroung color will be orange.
maskingOptions.BackgroundReplacementColor = Aspose.Imaging.Color.Orange;
maskingOptions.ExportOptions = exportOptions;
// Create an instance of the ImageMasking class.
Aspose.Imaging.Masking.ImageMasking masking = new Aspose.Imaging.Masking.ImageMasking(image);
// Divide the source image into several clusters (segments).
using (Aspose.Imaging.Masking.Result.MaskingResult maskingResult = masking.Decompose(maskingOptions))
{
// Obtain images from masking result and save them to PNG.
for (int i = 0; i < maskingResult.Length; i++)
{
string outputFileName = string.Format("Gorilla.Segment{0}.png", maskingResult[i].ObjectNumber);
using (Aspose.Imaging.Image resultImage = maskingResult[i].GetImage())
{
resultImage.Save(dir + outputFileName);
}
}
}
}Spare maskersessionen til en fil for lange sessioner, såvel som muligheden for at genoptage sessionen i et andet miljø.
string dir = "c:\\temp\\";
string sessionBackupFile = dir + "session.bak";
// Masking export options
Aspose.Imaging.ImageOptions.PngOptions exportOptions = new Aspose.Imaging.ImageOptions.PngOptions();
exportOptions.ColorType = Aspose.Imaging.FileFormats.Png.PngColorType.TruecolorWithAlpha;
exportOptions.Source = new Aspose.Imaging.Sources.StreamSource(new System.IO.MemoryStream());
Aspose.Imaging.Masking.Options.MaskingOptions maskingOptions = new Aspose.Imaging.Masking.Options.MaskingOptions();
// Use GraphCut clustering.
maskingOptions.Method = Masking.Options.SegmentationMethod.GraphCut;
maskingOptions.Decompose = false;
maskingOptions.Args = new Aspose.Imaging.Masking.Options.AutoMaskingArgs();
// The backgroung color will be orange.
maskingOptions.BackgroundReplacementColor = Aspose.Imaging.Color.Orange;
maskingOptions.ExportOptions = exportOptions;
// Starting a session for the first time and saving to a file
using (Aspose.Imaging.RasterImage image = (Aspose.Imaging.RasterImage)Aspose.Imaging.Image.Load(dir + "Gorilla.bmp"))
{
// Create an instance of the ImageMasking class.
Aspose.Imaging.Masking.ImageMasking masking = new Aspose.Imaging.Masking.ImageMasking(image);
using (Aspose.Imaging.Masking.IMaskingSession session = masking.CreateSession(maskingOptions))
{
using (Aspose.Imaging.Masking.Result.MaskingResult maskingResult = session.Decompose())
{
using (Aspose.Imaging.RasterImage segmentImage = maskingResult[1].GetImage())
{
segmentImage.Save(dir + "step1.png");
}
}
session.Save(sessionBackupFile);
}
}
// Resuming a masking session from a file
using (Aspose.Imaging.RasterImage image = (Aspose.Imaging.RasterImage)Aspose.Imaging.Image.Load(dir + "Gorilla.bmp"))
{
// Create an instance of the ImageMasking class.
Aspose.Imaging.Masking.ImageMasking masking = new Aspose.Imaging.Masking.ImageMasking(image);
using (Aspose.Imaging.Masking.IMaskingSession session = masking.LoadSession(sessionBackupFile))
{
Aspose.Imaging.Masking.Options.AutoMaskingArgs args = new Aspose.Imaging.Masking.Options.AutoMaskingArgs();
// Analyze the image visually and set the points that belong to separated objects.
args.ObjectsPoints = new Point[][]
{
new Point[]
{
new Point(0, 0), new Point(0, 1), new Point(1, 0),
new Point(1, 1), new Point(2, 0), new Point(2, 1),
new Point(3, 0), new Point(3, 1)
},
};
using (Aspose.Imaging.Masking.Result.MaskingResult maskingResult = session.ImproveDecomposition(args))
{
// Explicit transfer of export options, since it is not serializable
maskingResult.MaskingOptions.ExportOptions = exportOptions;
using (Aspose.Imaging.RasterImage segmentImage = maskingResult[1].GetImage())
{
segmentImage.Save(dir + "step2.png");
}
}
}
}Constructors
AutoMaskingArgs()
public AutoMaskingArgs()Properties
MaxIterationNumber
Få eller indstille det maksimale antal iterationer.
public int MaxIterationNumber { get; set; }Ejendomsværdi
Examples
Dette eksempel viser, hvordan man nedbryder et rasterbillede i flere billeder ved hjælp af billedmasking og K-means segmentation algoritme.
string dir = "c:\\temp\\";
using (Aspose.Imaging.RasterImage image = (Aspose.Imaging.RasterImage)Aspose.Imaging.Image.Load(dir + "Blue hills.png"))
{
Aspose.Imaging.Masking.Options.AutoMaskingArgs args = new Aspose.Imaging.Masking.Options.AutoMaskingArgs();
// Set the number of clusters (separated objects). The default value is 2, the foreground object and the background.
args.NumberOfObjects = 3;
// Set the maximum number of iterations.
args.MaxIterationNumber = 50;
// Set the precision of segmentation method (optional)
args.Precision = 1;
// Each cluster (segment) will be stored to a separate PNG file.
Aspose.Imaging.ImageOptions.PngOptions exportOptions = new Aspose.Imaging.ImageOptions.PngOptions();
exportOptions.ColorType = Aspose.Imaging.FileFormats.Png.PngColorType.TruecolorWithAlpha;
exportOptions.Source = new Aspose.Imaging.Sources.StreamSource(new System.IO.MemoryStream());
Aspose.Imaging.Masking.Options.MaskingOptions maskingOptions = new Aspose.Imaging.Masking.Options.MaskingOptions();
// Use K-means clustering.
// K-means clustering allows to split image into several independent clusters (segments).
maskingOptions.Method = Masking.Options.SegmentationMethod.KMeans;
maskingOptions.Decompose = true;
maskingOptions.Args = args;
// The backgroung color will be orange.
maskingOptions.BackgroundReplacementColor = Aspose.Imaging.Color.Orange;
maskingOptions.ExportOptions = exportOptions;
// Create an instance of the ImageMasking class.
Aspose.Imaging.Masking.ImageMasking masking = new Aspose.Imaging.Masking.ImageMasking(image);
// Divide the source image into several clusters (segments).
using (Aspose.Imaging.Masking.Result.MaskingResult maskingResult = masking.Decompose(maskingOptions))
{
// Obtain images from masking result and save them to PNG.
for (int i = 0; i < maskingResult.Length; i++)
{
string outputFileName = string.Format("Blue hills.Segment{0}.png", maskingResult[i].ObjectNumber);
using (Aspose.Imaging.Image resultImage = maskingResult[i].GetImage())
{
resultImage.Save(dir + outputFileName);
}
}
}
}NumberOfObjects
Få eller indsætte antallet af objekterfor at adskille det oprindelige billede til (optional), er standardværdien 2 (objekt og baggrund).
public int NumberOfObjects { get; set; }Ejendomsværdi
Examples
Dette eksempel viser, hvordan man nedbryder et rasterbillede i flere billeder ved hjælp af billedmasking og K-means segmentation algoritme.
string dir = "c:\\temp\\";
using (Aspose.Imaging.RasterImage image = (Aspose.Imaging.RasterImage)Aspose.Imaging.Image.Load(dir + "Blue hills.png"))
{
Aspose.Imaging.Masking.Options.AutoMaskingArgs args = new Aspose.Imaging.Masking.Options.AutoMaskingArgs();
// Set the number of clusters (separated objects). The default value is 2, the foreground object and the background.
args.NumberOfObjects = 3;
// Set the maximum number of iterations.
args.MaxIterationNumber = 50;
// Set the precision of segmentation method (optional)
args.Precision = 1;
// Each cluster (segment) will be stored to a separate PNG file.
Aspose.Imaging.ImageOptions.PngOptions exportOptions = new Aspose.Imaging.ImageOptions.PngOptions();
exportOptions.ColorType = Aspose.Imaging.FileFormats.Png.PngColorType.TruecolorWithAlpha;
exportOptions.Source = new Aspose.Imaging.Sources.StreamSource(new System.IO.MemoryStream());
Aspose.Imaging.Masking.Options.MaskingOptions maskingOptions = new Aspose.Imaging.Masking.Options.MaskingOptions();
// Use K-means clustering.
// K-means clustering allows to split image into several independent clusters (segments).
maskingOptions.Method = Masking.Options.SegmentationMethod.KMeans;
maskingOptions.Decompose = true;
maskingOptions.Args = args;
// The backgroung color will be orange.
maskingOptions.BackgroundReplacementColor = Aspose.Imaging.Color.Orange;
maskingOptions.ExportOptions = exportOptions;
// Create an instance of the ImageMasking class.
Aspose.Imaging.Masking.ImageMasking masking = new Aspose.Imaging.Masking.ImageMasking(image);
// Divide the source image into several clusters (segments).
using (Aspose.Imaging.Masking.Result.MaskingResult maskingResult = masking.Decompose(maskingOptions))
{
// Obtain images from masking result and save them to PNG.
for (int i = 0; i < maskingResult.Length; i++)
{
string outputFileName = string.Format("Blue hills.Segment{0}.png", maskingResult[i].ObjectNumber);
using (Aspose.Imaging.Image resultImage = maskingResult[i].GetImage())
{
resultImage.Save(dir + outputFileName);
}
}
}
}ObjectsPoints
Få eller indsætte de punkter, der tilhører separate objekter (valgligt)NumberOfObjects koordinerer de objekter, der tilhører NumberOnobjetts elementer i det oprindelige billede.Denne parameter bruges til at øge segmentationsmetodens præcision.
public Point[][] ObjectsPoints { get; set; }Ejendomsværdi
Point [][]
Examples
Dette eksempel viser, hvordan man angiver forslag til billedmasking algoritme for at forbedre nøjagtigheden af segmentation (klustering) metode. billedet masking er en billedsbehandlingsteknik, der bruges til at splitte baggrunden fra de foregroundbilledobjekter.
string dir = "c:\\temp\\";
using (Aspose.Imaging.RasterImage image = (Aspose.Imaging.RasterImage)Aspose.Imaging.Image.Load(dir + "Gorilla.bmp"))
{
Aspose.Imaging.Masking.Options.AutoMaskingArgs args = new Aspose.Imaging.Masking.Options.AutoMaskingArgs();
// Suggestion #1.
// Analyze the image visually and set the area of interest. The result of segmentation will include only objects that will be completely located within this area.
args.ObjectsRectangles = new Rectangle[]
{
new Rectangle(86, 6, 270, 364),
};
// Suggestion #2.
// Analyze the image visually and set the points that belong to separated objects.
args.ObjectsPoints = new Point[][]
{
new Point[] { new Point(103, 326) },
new Point[] { new Point(280, 43) },
new Point[] { new Point(319, 86) },
};
// Each cluster (segment) will be stored to a separate PNG file.
Aspose.Imaging.ImageOptions.PngOptions exportOptions = new Aspose.Imaging.ImageOptions.PngOptions();
exportOptions.ColorType = Aspose.Imaging.FileFormats.Png.PngColorType.TruecolorWithAlpha;
exportOptions.Source = new Aspose.Imaging.Sources.StreamSource(new System.IO.MemoryStream());
Aspose.Imaging.Masking.Options.MaskingOptions maskingOptions = new Aspose.Imaging.Masking.Options.MaskingOptions();
// Use GraphCut clustering.
maskingOptions.Method = Masking.Options.SegmentationMethod.GraphCut;
maskingOptions.Decompose = false;
maskingOptions.Args = args;
// The backgroung color will be orange.
maskingOptions.BackgroundReplacementColor = Aspose.Imaging.Color.Orange;
maskingOptions.ExportOptions = exportOptions;
// Create an instance of the ImageMasking class.
Aspose.Imaging.Masking.ImageMasking masking = new Aspose.Imaging.Masking.ImageMasking(image);
// Divide the source image into several clusters (segments).
using (Aspose.Imaging.Masking.Result.MaskingResult maskingResult = masking.Decompose(maskingOptions))
{
// Obtain images from masking result and save them to PNG.
for (int i = 0; i < maskingResult.Length; i++)
{
string outputFileName = string.Format("Gorilla.Segment{0}.png", maskingResult[i].ObjectNumber);
using (Aspose.Imaging.Image resultImage = maskingResult[i].GetImage())
{
resultImage.Save(dir + outputFileName);
}
}
}
}ObjectsRectangles
Giver eller sætter objekterne rektangler, der tilhører separate objekter (optional).Denne parameter bruges til at øge segmentationsmetodens præcision.
public Rectangle[] ObjectsRectangles { get; set; }Ejendomsværdi
Rectangle []
Examples
Dette eksempel viser, hvordan man angiver forslag til billedmasking algoritme for at forbedre nøjagtigheden af segmentation (klustering) metode. billedet masking er en billedsbehandlingsteknik, der bruges til at splitte baggrunden fra de foregroundbilledobjekter.
string dir = "c:\\temp\\";
using (Aspose.Imaging.RasterImage image = (Aspose.Imaging.RasterImage)Aspose.Imaging.Image.Load(dir + "Gorilla.bmp"))
{
Aspose.Imaging.Masking.Options.AutoMaskingArgs args = new Aspose.Imaging.Masking.Options.AutoMaskingArgs();
// Suggestion #1.
// Analyze the image visually and set the area of interest. The result of segmentation will include only objects that will be completely located within this area.
args.ObjectsRectangles = new Rectangle[]
{
new Rectangle(86, 6, 270, 364),
};
// Suggestion #2.
// Analyze the image visually and set the points that belong to separated objects.
args.ObjectsPoints = new Point[][]
{
new Point[] { new Point(103, 326) },
new Point[] { new Point(280, 43) },
new Point[] { new Point(319, 86) },
};
// Each cluster (segment) will be stored to a separate PNG file.
Aspose.Imaging.ImageOptions.PngOptions exportOptions = new Aspose.Imaging.ImageOptions.PngOptions();
exportOptions.ColorType = Aspose.Imaging.FileFormats.Png.PngColorType.TruecolorWithAlpha;
exportOptions.Source = new Aspose.Imaging.Sources.StreamSource(new System.IO.MemoryStream());
Aspose.Imaging.Masking.Options.MaskingOptions maskingOptions = new Aspose.Imaging.Masking.Options.MaskingOptions();
// Use GraphCut clustering.
maskingOptions.Method = Masking.Options.SegmentationMethod.GraphCut;
maskingOptions.Decompose = false;
maskingOptions.Args = args;
// The backgroung color will be orange.
maskingOptions.BackgroundReplacementColor = Aspose.Imaging.Color.Orange;
maskingOptions.ExportOptions = exportOptions;
// Create an instance of the ImageMasking class.
Aspose.Imaging.Masking.ImageMasking masking = new Aspose.Imaging.Masking.ImageMasking(image);
// Divide the source image into several clusters (segments).
using (Aspose.Imaging.Masking.Result.MaskingResult maskingResult = masking.Decompose(maskingOptions))
{
// Obtain images from masking result and save them to PNG.
for (int i = 0; i < maskingResult.Length; i++)
{
string outputFileName = string.Format("Gorilla.Segment{0}.png", maskingResult[i].ObjectNumber);
using (Aspose.Imaging.Image resultImage = maskingResult[i].GetImage())
{
resultImage.Save(dir + outputFileName);
}
}
}
}OrphanedPoints
Giver eller sætter de punkter, der ikke længere tilhører et objekt (optional).Denne parameter anvendes kun i tilfælde af gensegmentering.
public Point[] OrphanedPoints { get; set; }Ejendomsværdi
Point []
Precision
Få eller indstille præcision af segmentation metode (valglig).
public double Precision { get; set; }Ejendomsværdi
Examples
Dette eksempel viser, hvordan man nedbryder et rasterbillede i flere billeder ved hjælp af billedmasking og K-means segmentation algoritme.
string dir = "c:\\temp\\";
using (Aspose.Imaging.RasterImage image = (Aspose.Imaging.RasterImage)Aspose.Imaging.Image.Load(dir + "Blue hills.png"))
{
Aspose.Imaging.Masking.Options.AutoMaskingArgs args = new Aspose.Imaging.Masking.Options.AutoMaskingArgs();
// Set the number of clusters (separated objects). The default value is 2, the foreground object and the background.
args.NumberOfObjects = 3;
// Set the maximum number of iterations.
args.MaxIterationNumber = 50;
// Set the precision of segmentation method (optional)
args.Precision = 1;
// Each cluster (segment) will be stored to a separate PNG file.
Aspose.Imaging.ImageOptions.PngOptions exportOptions = new Aspose.Imaging.ImageOptions.PngOptions();
exportOptions.ColorType = Aspose.Imaging.FileFormats.Png.PngColorType.TruecolorWithAlpha;
exportOptions.Source = new Aspose.Imaging.Sources.StreamSource(new System.IO.MemoryStream());
Aspose.Imaging.Masking.Options.MaskingOptions maskingOptions = new Aspose.Imaging.Masking.Options.MaskingOptions();
// Use K-means clustering.
// K-means clustering allows to split image into several independent clusters (segments).
maskingOptions.Method = Masking.Options.SegmentationMethod.KMeans;
maskingOptions.Decompose = true;
maskingOptions.Args = args;
// The backgroung color will be orange.
maskingOptions.BackgroundReplacementColor = Aspose.Imaging.Color.Orange;
maskingOptions.ExportOptions = exportOptions;
// Create an instance of the ImageMasking class.
Aspose.Imaging.Masking.ImageMasking masking = new Aspose.Imaging.Masking.ImageMasking(image);
// Divide the source image into several clusters (segments).
using (Aspose.Imaging.Masking.Result.MaskingResult maskingResult = masking.Decompose(maskingOptions))
{
// Obtain images from masking result and save them to PNG.
for (int i = 0; i < maskingResult.Length; i++)
{
string outputFileName = string.Format("Blue hills.Segment{0}.png", maskingResult[i].ObjectNumber);
using (Aspose.Imaging.Image resultImage = maskingResult[i].GetImage())
{
resultImage.Save(dir + outputFileName);
}
}
}
}