Class AutoMaskingArgs
Class AutoMaskingArgs
名称: Aspose.Imaging.Masking.Options 收藏: Aspose.Imaging.dll (25.4.0)
代表对自动化面具方法所规定的论点
public class AutoMaskingArgs : IMaskingArgsInheritance
Implements
继承人
object.GetType() , object.MemberwiseClone() , object.ToString() , object.Equals(object?) , object.Equals(object?, object?) , object.ReferenceEquals(object?, object?) , object.GetHashCode()
Examples
这个例子表明如何将拉斯特图像分成多个图像,使用图像面具和K的分区算法,图像面具是一种图像处理技术,用于将背景与前方图像对象分开。
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);
}
}
}
}使用分区面具加速分区过程
// 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);
}
}
}
}这个例子表明如何指定图像面具算法的建议,以提高分区(分区)方法的准确性。
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);
}
}
}
}将隐藏会话存储在一个文件中长时间的会话,以及在另一个环境中重复会话的可能性。
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
接收或设置最大数的 iterations。
public int MaxIterationNumber { get; set; }财产价值
Examples
这个例子表明如何将拉斯特图像分成多个图像,使用图像面具和K的分区算法,图像面具是一种图像处理技术,用于将背景与前方图像对象分开。
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
接收或设置对象的数量要将初始图像分为(可选),默认值为2(对象和背景)。
public int NumberOfObjects { get; set; }财产价值
Examples
这个例子表明如何将拉斯特图像分成多个图像,使用图像面具和K的分区算法,图像面具是一种图像处理技术,用于将背景与前方图像对象分开。
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
接收或设置属于分离物体的点(可选)NumberOfObjects 协调属于 NumberOfObjects 最初图像的对象。这个参数用于提高分区方法的准确性。
public Point[][] ObjectsPoints { get; set; }财产价值
Point [ ]
Examples
这个例子表明如何指定图像面具算法的建议,以提高分区(分区)方法的准确性。
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
接收或设置属于分离物体的对象直角(可选)。这个参数用于提高分区方法的准确性。
public Rectangle[] ObjectsRectangles { get; set; }财产价值
Rectangle ( )
Examples
这个例子表明如何指定图像面具算法的建议,以提高分区(分区)方法的准确性。
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
接收或设置不再属于任何对象的点(可选)。该参数仅在重组情况下使用。
public Point[] OrphanedPoints { get; set; }财产价值
Point ( )
Precision
接收或设置分区方法的准确性(可选)。
public double Precision { get; set; }财产价值
Examples
这个例子表明如何将拉斯特图像分成多个图像,使用图像面具和K的分区算法,图像面具是一种图像处理技术,用于将背景与前方图像对象分开。
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);
}
}
}
}