ColorClustering (Fiji Javadocs 0-SNAPSHOT API)

java.lang.Object
- trainableSegmentation.unsupervised.ColorClustering

```
public class ColorClustering
extends Object
```
This class contains all the library methods to perform color clustering based on a few color space transformations and the Weka clusterers.

Author:

Josu Salinas and Ignacio Arganda-Carreras

Nested Class Summary

Nested Classes
Modifier and Type Class and Description

static class ColorClustering.Channel
Names of all channels (features) that can be used.

Nested Classes
Modifier and Type	Class and Description
`static class`	`ColorClustering.Channel` Names of all channels (features) that can be used.

Constructor Summary

Constructors
Constructor and Description
`ColorClustering(ij.ImagePlus image)` Constructor using only image, features and clusterer will be set as null
`ColorClustering(ij.ImagePlus image, int numSamples, ArrayList<ColorClustering.Channel> selectedChannels)` Creates color clustering object based on image, number of samples and selected channels.

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`ij.ImagePlus`	`createClusteredImage(FeatureStackArray featureStackArray)` Creates clustered image based on provided FeatureStackArray and using private clusterer, returns as ImagePlus
`AbstractClusterer`	`createClusterer(AbstractClusterer selectedClusterer)` Build clusterer using the current features and the provided number of clusters.
`void`	`createFeatures()` Generate the features based on the selected color space channels.
`boolean`	`createFile(String path, Instances theInstances)` Create ARFF file of features with provided name.
`FeatureStackArray`	`createFSArray(ij.ImagePlus image)` Create FeatureStackArray based on provided image and selected channels (private variable)
`ij.ImagePlus`	`createProbabilityMaps(FeatureStackArray featureStackArray)` Create probability map based on provided features and current cluster.
`Instances`	`getFeaturesInstances()` Get features instances that are being used
`FeatureStackArray`	`getFeatureStackArray()` Get FeatureStackArray that is being used
`ij.ImagePlus`	`getImage()` Get image that is being used
`int`	`getNumSamples()` Get number of samples that is being used
`AbstractClusterer`	`getTheClusterer()` Get abstract clusterer that has been created
`boolean`	`loadClusterer(String path)` Load clusterer from path
`boolean`	`saveClusterer(String filename)` Save clusterer to a file
`void`	`setChannels(ArrayList<ColorClustering.Channel> selectedChannels)` Set channels to use
`void`	`setFeaturesInstances(Instances featuresInstances)` Set features instances that are to be used
`void`	`setFeatureStackArray(FeatureStackArray featureStackArray)` Set FeatureStackArray that is to be used
`void`	`setImage(ij.ImagePlus image)` Set image that is to be used
`void`	`setNumSamples(int numSamples)` Set number of samples that is to be used
`void`	`setTheClusterer(AbstractClusterer theClusterer)` Set abstract clusterer to be used

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Constructor Detail
  - ColorClustering
```
public ColorClustering(ij.ImagePlus image)
```
    Constructor using only image, features and clusterer will be set as null
    
    Parameters:
    
    image - input color image to clusterize
  - ColorClustering
```
public ColorClustering(ij.ImagePlus image,
                       int numSamples,
                       ArrayList<ColorClustering.Channel> selectedChannels)
```
    Creates color clustering object based on image, number of samples and selected channels. Creates the features.
    
    Parameters:
    
    image - input color image
    
    numSamples - number of samples to use
    
    selectedChannels - list of color space channels (features) to use
- Method Detail
  - createClusterer
```
public AbstractClusterer createClusterer(AbstractClusterer selectedClusterer)
```
    Build clusterer using the current features and the provided number of clusters.
    
    Parameters:
    
    selectedClusterer - clustering Weka model to build
    
    Returns:
    
    built clustering Weka model
  - createFeatures
```
public void createFeatures()
```
    Generate the features based on the selected color space channels.
  - createFSArray
```
public FeatureStackArray createFSArray(ij.ImagePlus image)
```
    Create FeatureStackArray based on provided image and selected channels (private variable)
    
    Parameters:
    
    image - input color image
    
    Returns:
    
    feature stack array
  - createProbabilityMaps
```
public ij.ImagePlus createProbabilityMaps(FeatureStackArray featureStackArray)
```
    Create probability map based on provided features and current cluster.
    
    Parameters:
    
    featureStackArray - input array of feature stacks
    
    Returns:
    
    image containing the probability maps of each cluster
  - createClusteredImage
```
public ij.ImagePlus createClusteredImage(FeatureStackArray featureStackArray)
```
    Creates clustered image based on provided FeatureStackArray and using private clusterer, returns as ImagePlus
    
    Parameters:
    
    featureStackArray - input array of feature stacks
    
    Returns:
    
    clusterized image (one label per cluster)
  - createFile
```
public boolean createFile(String path,
                          Instances theInstances)
```
    Create ARFF file of features with provided name.
    
    Parameters:
    
    path - complete path to output ARFF file
    
    theInstances - dataset of instances to saved to file
    
    Returns:
    
    true if the file was correctly saved, false otherwise
  - saveClusterer
```
public boolean saveClusterer(String filename)
```
    Save clusterer to a file
    
    Parameters:
    
    filename - path to file to be saved
    
    Returns:
    
    boolean value showing success/failure
  - loadClusterer
```
public boolean loadClusterer(String path)
```
    Load clusterer from path
    
    Parameters:
    
    path - Path of file to be loaded
    
    Returns:
    
    boolean value showing success/failure
  - getNumSamples
```
public int getNumSamples()
```
    Get number of samples that is being used
    
    Returns:
    
    number of samples that is being used
  - setNumSamples
```
public void setNumSamples(int numSamples)
```
    Set number of samples that is to be used
    
    Parameters:
    
    numSamples - number of samples that is to be used
  - getImage
```
public ij.ImagePlus getImage()
```
    Get image that is being used
    
    Returns:
    
    color image being used
  - setImage
```
public void setImage(ij.ImagePlus image)
```
    Set image that is to be used
    
    Parameters:
    
    image - color image to be clusterized
  - getFeatureStackArray
```
public FeatureStackArray getFeatureStackArray()
```
    Get FeatureStackArray that is being used
    
    Returns:
    
    array of feature stacks used for clustering
  - setFeatureStackArray
```
public void setFeatureStackArray(FeatureStackArray featureStackArray)
```
    Set FeatureStackArray that is to be used
    
    Parameters:
    
    featureStackArray - array of feature stacks to use in clustering
  - getFeaturesInstances
```
public Instances getFeaturesInstances()
```
    Get features instances that are being used
    
    Returns:
    
    set of instances used for building the clusterer
  - setFeaturesInstances
```
public void setFeaturesInstances(Instances featuresInstances)
```
    Set features instances that are to be used
    
    Parameters:
    
    featuresInstances - set of instances to be used to build the clusterer
  - getTheClusterer
```
public AbstractClusterer getTheClusterer()
```
    Get abstract clusterer that has been created
    
    Returns:
    
    current clusterer
  - setTheClusterer
```
public void setTheClusterer(AbstractClusterer theClusterer)
```
    Set abstract clusterer to be used
    
    Parameters:
    
    theClusterer - clustering Weka model to use
  - setChannels
```
public void setChannels(ArrayList<ColorClustering.Channel> selectedChannels)
```
    Set channels to use
    
    Parameters:
    
    selectedChannels - list of selected channels

Class ColorClustering

Nested Class Summary

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Constructor Detail

ColorClustering

ColorClustering

Method Detail

createClusterer

createFeatures

createFSArray

createProbabilityMaps

createClusteredImage

createFile

saveClusterer

loadClusterer

getNumSamples

setNumSamples

getImage

setImage

getFeatureStackArray

setFeatureStackArray

getFeaturesInstances

setFeaturesInstances

getTheClusterer

setTheClusterer

setChannels