KMeansCommand Constructor(int,KMeansCommandFlags,RasterColor[])

Summary

Initializes a new KMeansCommand class object with explicit parameters.

Syntax

Objective-C

C++/CLI

Java

Python

public KMeansCommand( 
   int Clusters, 
   KMeansCommandFlags Type, 
   RasterColor[] InCenters 
)

- (instancetype)initWithClusters:(NSInteger)clusters type:(LTKMeansCommandFlags)type inCenters:(nullable NSArray<LTRasterColor *> *)inCenters NS_DESIGNATED_INITIALIZER;

public KMeansCommand( 
   int Clusters,  
   KMeansCommandFlags Type,  
   ArrayList<RasterColor> InCenters 
)

public: 
KMeansCommand(  
   int Clusters, 
   KMeansCommandFlags Type, 
   array<RasterColor>^ InCenters 
)

__init__(self,Clusters,Type,InCenters) # Overloaded constructor

Parameters

Clusters
Number of output clusters or colors in the output image.

Type
Flag that determines which initializing algorithm to use when choosing the initial centers for the clusters.

InCenters
If the Type is KMeans_UserDefined, InCenters should be a reference to an array of RasterColor values that represents the initial centers.

Remarks

RasterColor[] InCenters should be null if Type is KMeans_Random or KMeans_Uniform. If Type is KMeans_UserDefined, RasterColor[] InCenters should be filled with the initial centers for the clusters.

Example

Java

using Leadtools; 
using Leadtools.Codecs; 
using Leadtools.ImageProcessing.Core; 
 
public void KMeansConstructorExample() 
{ 
   RasterCodecs codecs = new RasterCodecs(); 
   codecs.ThrowExceptionsOnInvalidImages = true; 
 
   //Load an image 
   RasterImage image = codecs.Load(Path.Combine(LEAD_VARS.ImagesDir, "cannon.jpg")); 
 
   //Prepare the command 
   KMeansCommand command = new KMeansCommand(7, KMeansCommandFlags.KMeans_Random, null); 
 
   command.Run(image); 
} 
 
static class LEAD_VARS 
{ 
   public const string ImagesDir = @"C:\LEADTOOLS23\Resources\Images"; 
}

 
import java.io.File; 
import java.io.IOException; 
 
import org.junit.*; 
import org.junit.Test; 
import org.junit.runner.JUnitCore; 
import org.junit.runner.Result; 
import org.junit.runner.notification.Failure; 
import static org.junit.Assert.*; 
 
import leadtools.*; 
import leadtools.codecs.*; 
import leadtools.imageprocessing.core.*; 
 
 
public void kMeansConstructorExample() { 
    RasterCodecs codecs = new RasterCodecs(); 
    codecs.setThrowExceptionsOnInvalidImages(true); 
 
    // Load an image 
    String LEAD_VARS_IMAGES_DIR = "C:\\LEADTOOLS23\\Resources\\Images"; 
    RasterImage image = codecs.load(combine(LEAD_VARS_IMAGES_DIR, "cannon.jpg")); 
 
    // Prepare the command 
    KMeansCommand command = new KMeansCommand(7, KMeansCommandFlags.KMEANS_RANDOM, null); 
    assertTrue(command.getClusters() == 7 && command.getType() == KMeansCommandFlags.KMEANS_RANDOM); 
 
    command.run(image); 
    codecs.save(image, combine(LEAD_VARS_IMAGES_DIR, "cannonConstructResult.jpg"), RasterImageFormat.JPEG, 24); 
 
    assertTrue(new File(combine(LEAD_VARS_IMAGES_DIR, "cannonConstructResult.jpg")).exists()); 
    System.out.println( 
            "Command run and image exported to: " + combine(LEAD_VARS_IMAGES_DIR, "cannonConstructResult.jpg")); 
}

Requirements

Target Platforms

Reference

KMeansCommand Class

KMeansCommand Members

Overload List

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Help Version 23.0.2024.3.3

Leadtools.ImageProcessing.Core Assembly

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