Weka_Segmentation (Fiji Javadocs 0-SNAPSHOT API)

java.lang.Object
- trainableSegmentation.Weka_Segmentation

All Implemented Interfaces:

ij.plugin.PlugIn
```
public class Weka_Segmentation
extends Object
implements ij.plugin.PlugIn
```
Segmentation plugin based on the machine learning library Weka

Field Summary

Fields
Modifier and Type	Field and Description
`static String`	`ADD_TRACE` name of the macro method to add the current trace to a class
`static String`	`APPLY_CLASSIFIER` name of the macro method to apply the current classifier to an image or stack
`static String`	`CHANGE_CLASS_NAME` name of the macro method to change a class name
`static String`	`CREATE_CLASS` name of the macro method to create a new class
`static String`	`DELETE_TRACE` name of the macro method to delete the current trace
`static String`	`GET_PROBABILITY` name of the macro method to get the probability maps
`static String`	`GET_RESULT` name of the macro method to get the binary result
`static String`	`LAUNCH_WEKA` name of the macro method to launch the Weka Chooser
`static String`	`LOAD_CLASSIFIER` name of the macro method to load a classifier from file
`static String`	`LOAD_DATA` name of the macro method to load data from an ARFF file
`static String`	`PLOT_RESULT` name of the macro method to plot the threshold curves
`static String`	`PLUGIN_NAME` plugin's name
`static String`	`PLUGIN_VERSION` plugin's current version
`static String`	`SAVE_CLASSIFIER` name of the macro method to save the current classifier into a file
`static String`	`SAVE_DATA` name of the macro method to save the current data into an ARFF file
`static String`	`SAVE_FEATURE_STACK` name of the macro method to save the feature stack into a file or files
`static String`	`SET_BALANCE` name of the macro method to enable/disable the class balance
`static String`	`SET_CLASSIFIER` name of the macro method to set a new classifier
`static String`	`SET_FEATURE` name of the macro method to enable/disable a feature
`static String`	`SET_HOMOGENIZATION` Deprecated. use SET_BALANCE instead
`static String`	`SET_MAXIMUM_SIGMA` name of the macro method to set the maximum kernel radius
`static String`	`SET_MEMBRANE_PATCH` name of the macro method to set the membrane patch size
`static String`	`SET_MEMBRANE_THICKNESS` name of the macro method to set the membrane thickness
`static String`	`SET_MINIMUM_SIGMA` name of the macro method to set the minimum kernel radius
`static String`	`SET_OPACITY` name of the macro method to set the overlay opacity
`static String`	`TOGGLE_OVERLAY` name of the macro method to toggle the overlay image
`static String`	`TRAIN_CLASSIFIER` name of the macro method to train the current classifier

Constructor Summary

Constructors
Constructor and Description

Weka_Segmentation()
Basic constructor for graphical user interface use

Constructors
Constructor and Description
`Weka_Segmentation()` Basic constructor for graphical user interface use

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`static void`	`addTrace(String classNum, String nSlice)` Add the current ROI to a specific class and slice.
`static void`	`applyClassifier(String dir, String fileName, String showResultsFlag, String storeResultsFlag, String probabilityMapsFlag, String storeDir)` Apply current classifier to specific image (2D or stack)
`void`	`applyClassifierToTestData()` Apply classifier to test data.
`static void`	`changeClassName(String classIndex, String className)` Change a class name
`static void`	`createNewClass(String inputName)` Create a new class
`static void`	`deleteTrace(String classNum, String nSlice, String index)` Delete a specific ROI from the list of a specific class and slice
`static void`	`disableMissingFeatures(GenericDialog gd)` Disables features which rely on missing third party libraries.
`static void`	`displayGraphs(Instances data, AbstractClassifier classifier)` Display the threshold curve window (for precision/recall, ROC, etc.).
`static ij.ImagePlus`	`getLabelImage()` Create label image out of the current user traces.
`static void`	`getProbability()` Display the current probability maps
`static void`	`getResult()` Get the current result (labeled image)
`static void`	`launchWeka()` Call the Weka chooser
`void`	`loadClassifier()` Load a Weka classifier from a file
`static void`	`loadClassifier(String newClassifierPathName)` Load a new classifier
`static void`	`loadData(String arffFilePathName)` Load training data from file
`void`	`loadTrainingData()` Load previously saved data
`static void`	`plotResultGraphs()` Plot the current result (threshold curves)
`static AbstractClassifier`	`readClassifier(String filename)` Load a Weka model (classifier) from a file
`static void`	`record(String command, String... args)` Macro-record a specific command.
`void`	`run(String arg)` Plugin run method
`void`	`saveClassifier()` Save current classifier into a file
`static boolean`	`saveClassifier(AbstractClassifier classifier, Instances trainHeader, String filename)` Write classifier into a file
`static void`	`saveClassifier(String classifierPathName)` Save current classifier into a file
`static void`	`saveData(String arffFilePathName)` Save training data into an ARFF file
`static void`	`saveFeatureStack(String dir, String fileWithExt)` Save current feature stack(s)
`void`	`saveTrainingData()` Save training model into a file
`static void`	`setClassBalance(String flagStr)` Set the class balance flag for training
`static void`	`setClassHomogenization(String flagStr)` Set the class homogenization flag for training
`static void`	`setClassifier(String classifierName, String options)` Set classifier for current segmentation
`static void`	`setFeature(String feature)` Enable/disable a single feature of the feature stack(s)
`static void`	`setMaximumSigma(String newMaxSigmaStr)` Set a new maximum radius for the feature filters
`static void`	`setMembranePatchSize(String newPatchSizeStr)` Set a new membrane patch size for current feature stack
`static void`	`setMembraneThickness(String newThicknessStr)` Set membrane thickness for current feature stack
`static void`	`setMinimumSigma(String newMinSigmaStr)` Set a new minimum radius for the feature filters
`static void`	`setOpacity(String newOpacity)` Set overlay opacity
`boolean`	`showSettingsDialog()` Show advanced settings dialog
`static void`	`toggleOverlay()` Toggle current result overlay image
`static void`	`trainClassifier()` Train the current classifier
`void`	`updateClassifiedImage(ij.ImagePlus classifiedImage)` Update the result image
`void`	`updateResultOverlay()` Update the result image overlay with the corresponding slice
`static boolean`	`writeClassifier(AbstractClassifier cls, String filename)` Write classifier into a file

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

- Field Detail
  - PLUGIN_NAME
```
public static final String PLUGIN_NAME
```
    plugin's name
    
    See Also:
    
    Constant Field Values
  - PLUGIN_VERSION
```
public static final String PLUGIN_VERSION
```
    plugin's current version
  - ADD_TRACE
```
public static final String ADD_TRACE
```
    name of the macro method to add the current trace to a class
    
    See Also:
    
    Constant Field Values
  - DELETE_TRACE
```
public static final String DELETE_TRACE
```
    name of the macro method to delete the current trace
    
    See Also:
    
    Constant Field Values
  - TRAIN_CLASSIFIER
```
public static final String TRAIN_CLASSIFIER
```
    name of the macro method to train the current classifier
    
    See Also:
    
    Constant Field Values
  - TOGGLE_OVERLAY
```
public static final String TOGGLE_OVERLAY
```
    name of the macro method to toggle the overlay image
    
    See Also:
    
    Constant Field Values
  - GET_RESULT
```
public static final String GET_RESULT
```
    name of the macro method to get the binary result
    
    See Also:
    
    Constant Field Values
  - GET_PROBABILITY
```
public static final String GET_PROBABILITY
```
    name of the macro method to get the probability maps
    
    See Also:
    
    Constant Field Values
  - PLOT_RESULT
```
public static final String PLOT_RESULT
```
    name of the macro method to plot the threshold curves
    
    See Also:
    
    Constant Field Values
  - APPLY_CLASSIFIER
```
public static final String APPLY_CLASSIFIER
```
    name of the macro method to apply the current classifier to an image or stack
    
    See Also:
    
    Constant Field Values
  - LOAD_CLASSIFIER
```
public static final String LOAD_CLASSIFIER
```
    name of the macro method to load a classifier from file
    
    See Also:
    
    Constant Field Values
  - SAVE_CLASSIFIER
```
public static final String SAVE_CLASSIFIER
```
    name of the macro method to save the current classifier into a file
    
    See Also:
    
    Constant Field Values
  - LOAD_DATA
```
public static final String LOAD_DATA
```
    name of the macro method to load data from an ARFF file
    
    See Also:
    
    Constant Field Values
  - SAVE_DATA
```
public static final String SAVE_DATA
```
    name of the macro method to save the current data into an ARFF file
    
    See Also:
    
    Constant Field Values
  - CREATE_CLASS
```
public static final String CREATE_CLASS
```
    name of the macro method to create a new class
    
    See Also:
    
    Constant Field Values
  - LAUNCH_WEKA
```
public static final String LAUNCH_WEKA
```
    name of the macro method to launch the Weka Chooser
    
    See Also:
    
    Constant Field Values
  - SET_FEATURE
```
public static final String SET_FEATURE
```
    name of the macro method to enable/disable a feature
    
    See Also:
    
    Constant Field Values
  - SET_MEMBRANE_THICKNESS
```
public static final String SET_MEMBRANE_THICKNESS
```
    name of the macro method to set the membrane thickness
    
    See Also:
    
    Constant Field Values
  - SET_MEMBRANE_PATCH
```
public static final String SET_MEMBRANE_PATCH
```
    name of the macro method to set the membrane patch size
    
    See Also:
    
    Constant Field Values
  - SET_MINIMUM_SIGMA
```
public static final String SET_MINIMUM_SIGMA
```
    name of the macro method to set the minimum kernel radius
    
    See Also:
    
    Constant Field Values
  - SET_MAXIMUM_SIGMA
```
public static final String SET_MAXIMUM_SIGMA
```
    name of the macro method to set the maximum kernel radius
    
    See Also:
    
    Constant Field Values
  - SET_HOMOGENIZATION
```
public static final String SET_HOMOGENIZATION
```
    Deprecated. use SET_BALANCE instead
    
    name of the macro method to enable/disable the class homogenization
    
    See Also:
    
    Constant Field Values
  - SET_BALANCE
```
public static final String SET_BALANCE
```
    name of the macro method to enable/disable the class balance
    
    See Also:
    
    Constant Field Values
  - SET_CLASSIFIER
```
public static final String SET_CLASSIFIER
```
    name of the macro method to set a new classifier
    
    See Also:
    
    Constant Field Values
  - SAVE_FEATURE_STACK
```
public static final String SAVE_FEATURE_STACK
```
    name of the macro method to save the feature stack into a file or files
    
    See Also:
    
    Constant Field Values
  - CHANGE_CLASS_NAME
```
public static final String CHANGE_CLASS_NAME
```
    name of the macro method to change a class name
    
    See Also:
    
    Constant Field Values
  - SET_OPACITY
```
public static final String SET_OPACITY
```
    name of the macro method to set the overlay opacity
    
    See Also:
    
    Constant Field Values
- Constructor Detail
  - Weka_Segmentation
```
public Weka_Segmentation()
```
    Basic constructor for graphical user interface use
- Method Detail
  - run
```
public void run(String arg)
```
    Plugin run method
    
    Specified by:
    
    run in interface ij.plugin.PlugIn
  - updateClassifiedImage
```
public void updateClassifiedImage(ij.ImagePlus classifiedImage)
```
    Update the result image
    
    Parameters:
    
    classifiedImage - new result image
  - updateResultOverlay
```
public void updateResultOverlay()
```
    Update the result image overlay with the corresponding slice
  - displayGraphs
```
public static void displayGraphs(Instances data,
                                 AbstractClassifier classifier)
```
    Display the threshold curve window (for precision/recall, ROC, etc.).
    
    Parameters:
    
    data - input instances
    
    classifier - classifier to evaluate
  - applyClassifierToTestData
```
public void applyClassifierToTestData()
```
    Apply classifier to test data. As it is implemented right now, it will use one thread per input image and slice.
  - loadClassifier
```
public void loadClassifier()
```
    Load a Weka classifier from a file
  - readClassifier
```
public static AbstractClassifier readClassifier(String filename)
```
    Load a Weka model (classifier) from a file
    
    Parameters:
    
    filename - complete path and file name
    
    Returns:
    
    classifier
  - saveClassifier
```
public void saveClassifier()
```
    Save current classifier into a file
  - saveClassifier
```
public static boolean saveClassifier(AbstractClassifier classifier,
                                     Instances trainHeader,
                                     String filename)
```
    Write classifier into a file
    
    Parameters:
    
    classifier - classifier
    
    trainHeader - train header containing attribute and class information
    
    filename - name (with complete path) of the destination file
    
    Returns:
    
    false if error
  - writeClassifier
```
public static boolean writeClassifier(AbstractClassifier cls,
                                      String filename)
```
    Write classifier into a file
    
    Parameters:
    
    cls - classifier
    
    filename - name (with complete path) of the destination file
    
    Returns:
    
    false if error
  - loadTrainingData
```
public void loadTrainingData()
```
    Load previously saved data
  - saveTrainingData
```
public void saveTrainingData()
```
    Save training model into a file
  - launchWeka
```
public static void launchWeka()
```
    Call the Weka chooser
  - showSettingsDialog
```
public boolean showSettingsDialog()
```
    Show advanced settings dialog
    
    Returns:
    
    false when canceled
  - record
```
public static void record(String command,
                          String... args)
```
    Macro-record a specific command. The command names match the static methods that reproduce that part of the code.
    
    Parameters:
    
    command - name of the command including package info
    
    args - set of arguments for the command
  - addTrace
```
public static void addTrace(String classNum,
                            String nSlice)
```
    Add the current ROI to a specific class and slice.
    
    Parameters:
    
    classNum - string representing the class index
    
    nSlice - string representing the slice number
  - deleteTrace
```
public static void deleteTrace(String classNum,
                               String nSlice,
                               String index)
```
    Delete a specific ROI from the list of a specific class and slice
    
    Parameters:
    
    classNum - string representing the class index
    
    nSlice - string representing the slice number
    
    index - string representing the index of the trace to remove
  - trainClassifier
```
public static void trainClassifier()
```
    Train the current classifier
  - getResult
```
public static void getResult()
```
    Get the current result (labeled image)
  - getProbability
```
public static void getProbability()
```
    Display the current probability maps
  - plotResultGraphs
```
public static void plotResultGraphs()
```
    Plot the current result (threshold curves)
  - applyClassifier
```
public static void applyClassifier(String dir,
                                   String fileName,
                                   String showResultsFlag,
                                   String storeResultsFlag,
                                   String probabilityMapsFlag,
                                   String storeDir)
```
    Apply current classifier to specific image (2D or stack)
    
    Parameters:
    
    dir - input image directory path
    
    fileName - input image name
    
    showResultsFlag - string containing the boolean flag to display results
    
    storeResultsFlag - string containing the boolean flag to store result in a directory
    
    probabilityMapsFlag - string containing the boolean flag to calculate probabilities instead of a binary result
    
    storeDir - directory to store the results
  - toggleOverlay
```
public static void toggleOverlay()
```
    Toggle current result overlay image
  - loadClassifier
```
public static void loadClassifier(String newClassifierPathName)
```
    Load a new classifier
    
    Parameters:
    
    newClassifierPathName - classifier file name with complete path
  - saveClassifier
```
public static void saveClassifier(String classifierPathName)
```
    Save current classifier into a file
    
    Parameters:
    
    classifierPathName - complete path name for the classifier file
  - loadData
```
public static void loadData(String arffFilePathName)
```
    Load training data from file
    
    Parameters:
    
    arffFilePathName - complete path name of the ARFF file
  - saveData
```
public static void saveData(String arffFilePathName)
```
    Save training data into an ARFF file
    
    Parameters:
    
    arffFilePathName - complete path name of the ARFF file
  - createNewClass
```
public static void createNewClass(String inputName)
```
    Create a new class
    
    Parameters:
    
    inputName - new class name
  - setMembraneThickness
```
public static void setMembraneThickness(String newThicknessStr)
```
    Set membrane thickness for current feature stack
    
    Parameters:
    
    newThicknessStr - new membrane thickness (in pixel units)
  - setMembranePatchSize
```
public static void setMembranePatchSize(String newPatchSizeStr)
```
    Set a new membrane patch size for current feature stack
    
    Parameters:
    
    newPatchSizeStr - new patch size (in pixel units)
  - setMinimumSigma
```
public static void setMinimumSigma(String newMinSigmaStr)
```
    Set a new minimum radius for the feature filters
    
    Parameters:
    
    newMinSigmaStr - new minimum radius (in float pixel units)
  - setMaximumSigma
```
public static void setMaximumSigma(String newMaxSigmaStr)
```
    Set a new maximum radius for the feature filters
    
    Parameters:
    
    newMaxSigmaStr - new maximum radius (in float pixel units)
  - setClassHomogenization
```
public static void setClassHomogenization(String flagStr)
```
    Set the class homogenization flag for training
    
    Parameters:
    
    flagStr - true/false if you want to balance the number of samples per class before training
  - setClassBalance
```
public static void setClassBalance(String flagStr)
```
    Set the class balance flag for training
    
    Parameters:
    
    flagStr - true/false if you want to balance the number of samples per class before training
  - setClassifier
```
public static void setClassifier(String classifierName,
                                 String options)
```
    Set classifier for current segmentation
    
    Parameters:
    
    classifierName - classifier name with complete package information
    
    options - classifier options
  - saveFeatureStack
```
public static void saveFeatureStack(String dir,
                                    String fileWithExt)
```
    Save current feature stack(s)
    
    Parameters:
    
    dir - directory to save the stack(s)
    
    fileWithExt - file name with extension for the file(s)
  - changeClassName
```
public static void changeClassName(String classIndex,
                                   String className)
```
    Change a class name
    
    Parameters:
    
    classIndex - index of the class to change
    
    className - new class name
  - setFeature
```
public static void setFeature(String feature)
```
    Enable/disable a single feature of the feature stack(s)
    
    Parameters:
    
    feature - name of the feature + "=" true/false to enable/disable
  - setOpacity
```
public static void setOpacity(String newOpacity)
```
    Set overlay opacity
    
    Parameters:
    
    newOpacity - string containing the new opacity value (integer 0-100)
  - disableMissingFeatures
```
public static void disableMissingFeatures(GenericDialog gd)
```
    Disables features which rely on missing third party libraries.
    
    Parameters:
    
    gd - settings dialog
  - getLabelImage
```
public static ij.ImagePlus getLabelImage()
```
    Create label image out of the current user traces. For convention, the label zero is used to define pixels with no class assigned. The rest of integer values correspond to the order of the classes (1 for the first class, 2 for the second class, etc.).
    
    Returns:
    
    label image containing user-defined traces (zero for undefined pixels)

Class Weka_Segmentation

Field Summary

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Field Detail

PLUGIN_NAME

PLUGIN_VERSION

ADD_TRACE

DELETE_TRACE

TRAIN_CLASSIFIER

TOGGLE_OVERLAY

GET_RESULT

GET_PROBABILITY

PLOT_RESULT

APPLY_CLASSIFIER

LOAD_CLASSIFIER

SAVE_CLASSIFIER

LOAD_DATA

SAVE_DATA

CREATE_CLASS

LAUNCH_WEKA

SET_FEATURE

SET_MEMBRANE_THICKNESS

SET_MEMBRANE_PATCH

SET_MINIMUM_SIGMA

SET_MAXIMUM_SIGMA

SET_HOMOGENIZATION

SET_BALANCE

SET_CLASSIFIER

SAVE_FEATURE_STACK

CHANGE_CLASS_NAME

SET_OPACITY

Constructor Detail

Weka_Segmentation

Method Detail

run

updateClassifiedImage

updateResultOverlay

displayGraphs

applyClassifierToTestData

loadClassifier

readClassifier

saveClassifier

saveClassifier

writeClassifier

loadTrainingData

saveTrainingData

launchWeka

showSettingsDialog

record

addTrace

deleteTrace

trainClassifier

getResult

getProbability

plotResultGraphs

applyClassifier

toggleOverlay

loadClassifier

saveClassifier

loadData

saveData

createNewClass

setMembraneThickness

setMembranePatchSize

setMinimumSigma

setMaximumSigma

setClassHomogenization

setClassBalance

setClassifier

saveFeatureStack

changeClassName

setFeature

setOpacity

disableMissingFeatures

getLabelImage