Class AutoMaskingArgs
Class AutoMaskingArgs
Namn på plats: Aspose.Imaging.Masking.Options Församling: Aspose.Imaging.dll (25.4.0)
Representerar de argument som anges för automatiserade maskeringsmetoder
public class AutoMaskingArgs : IMaskingArgsInheritance
Implements
Arvsmedlemmar
object.GetType() , object.MemberwiseClone() , object.ToString() , object.Equals(object?) , object.Equals(object?, object?) , object.ReferenceEquals(object?, object?) , object.GetHashCode()
Examples
Detta exempel visar hur man bryter ned en rasterbild till flera bilder med hjälp av bildmasking och K-means segmentering algoritm. Bildmasking är en bildbehandlingsteknik som används för att dela bakgrunden från föregående bildobjekt.
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);
}
}
}
}Använd en segmentmask för att påskynda segmenteringsprocessen
// 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);
}
}
}
}Detta exempel visar hur man anger förslag för bildmasking algoritm för att förbättra precisionen av segmentering (klustering) metod. bildmasking är en bild bearbetning teknik som används för att dela bakgrunden från föregående bildobjekt.
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);
}
}
}
}Spara maskeringssessionen i en fil för långa sessioner, samt för möjligheten att återupptäcka sessionen i en annan miljö.
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 ange det maximala antalet iterationer.
public int MaxIterationNumber { get; set; }Fastighetsvärde
Examples
Detta exempel visar hur man bryter ned en rasterbild till flera bilder med hjälp av bildmasking och K-means segmentering algoritm. Bildmasking är en bildbehandlingsteknik som används för att dela bakgrunden från föregående bildobjekt.
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 ange antalet objektFör att separera den ursprungliga bilden till (alternativ), är standardvärdet 2 (objekt och bakgrund).
public int NumberOfObjects { get; set; }Fastighetsvärde
Examples
Detta exempel visar hur man bryter ned en rasterbild till flera bilder med hjälp av bildmasking och K-means segmentering algoritm. Bildmasking är en bildbehandlingsteknik som används för att dela bakgrunden från föregående bildobjekt.
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 sätta de punkter som tillhör separata objekt (alternativt)NumberOfObjects samordnar de objekt som tillhör NumberOfObjects ursprungliga bild.Denna parameter används för att öka segmenteringsmetodens precision.
public Point[][] ObjectsPoints { get; set; }Fastighetsvärde
Point [ [ ]
Examples
Detta exempel visar hur man anger förslag för bildmasking algoritm för att förbättra precisionen av segmentering (klustering) metod. bildmasking är en bild bearbetning teknik som används för att dela bakgrunden från föregående bildobjekt.
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
Få eller sätta objekt rektanglar som tillhör separata objekt (valfritt).Denna parameter används för att öka segmenteringsmetodens precision.
public Rectangle[] ObjectsRectangles { get; set; }Fastighetsvärde
Rectangle [ ]
Examples
Detta exempel visar hur man anger förslag för bildmasking algoritm för att förbättra precisionen av segmentering (klustering) metod. bildmasking är en bild bearbetning teknik som används för att dela bakgrunden från föregående bildobjekt.
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
Få eller ställa in punkterna som inte längre tillhör något objekt (alternativt).Denna parameter används endast vid omsegmentering.
public Point[] OrphanedPoints { get; set; }Fastighetsvärde
Point [ ]
Precision
Få eller ställa in precisionen av segmenteringsmetoden (alternativ).
public double Precision { get; set; }Fastighetsvärde
Examples
Detta exempel visar hur man bryter ned en rasterbild till flera bilder med hjälp av bildmasking och K-means segmentering algoritm. Bildmasking är en bildbehandlingsteknik som används för att dela bakgrunden från föregående bildobjekt.
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);
}
}
}
}