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Orbit, a versatile image analysis software for biological image-based quantification
/*
* Orbit, a versatile image analysis software for biological image-based quantification.
* Copyright (C) 2009 - 2017 Actelion Pharmaceuticals Ltd., Gewerbestrasse 16, CH-4123 Allschwil, Switzerland.
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see classShapes = Collections.synchronizedList(new ArrayList());
protected final List classShapesToRestore = new ArrayList<>();
private FeatureDescription featureDescription = null;
private int boundaryClass = -1;
private int fixedCircularROI = 0;
private int fixedROIOffsetX = 0;
private int fixedROIOffsetY = 0;
private OrbitModel segmentationModel = null;
private OrbitModel secondarySegmentationModel = null;
private OrbitModel exclusionModel = null;
private boolean applyExclusionOnNegativeChannel = false;
private boolean performErodeDiliate = false; // only in exclusionMap implemented
private boolean useExclusionForSegmentation = false; // otherwise for classification
private boolean loadAnnotationsAsInversROI = false;
private int annotationGroup = 0; // <0 means ignore annotations, 0 means all annotations, >0 means specific annotation group
private int exclusionLevel = 1; // numMips-exlusionLevel
private boolean isCellClassification = false;
private int mipLayer = 0; // the images mipLayer used for training the model
/**
* constructs a model with default classShapes and defaultFeatureDescriptors, classifier and structure are set to null.
*/
public OrbitModel() {
// upd 28.06.2010: default class shapes and feature descriptors
classShapes = Collections.synchronizedList(new ArrayList(3));
classShapes.add(new ClassShape("Background", new Color(94, 6, 129), ClassShape.SHAPETYPE_POLYGONEXT));
classShapes.add(new ClassShape("Celltype 1", RecognitionFrame.getColorByNum(1), ClassShape.SHAPETYPE_POLYGONEXT));
classShapes.add(new ClassShape("Celltype 2", RecognitionFrame.getColorByNum(2), ClassShape.SHAPETYPE_POLYGONEXT));
featureDescription = new FeatureDescription();
orbitVersion = OrbitUtils.VERSION_STR;
}
/**
* constructs a model with a (already build) classifier.
*
* @param classifier
* @param structure
* @param classShapes
* @param featureDescription
*/
public OrbitModel(ClassifierWrapper classifier, Instances structure, List classShapes, FeatureDescription featureDescription) {
this.classShapes = Collections.synchronizedList(new ArrayList());
for (ClassShape cs : classShapes) {
if (cs.getColor().getRGB() == OrbitUtils.UNDEF_COLOR)
logger.warn("UNDEFINED Color (black) should not be used as class color!");
ClassShape newShape = cs.clone();
newShape.setShapeList(new ArrayList()); // store empty list to save memory
this.classShapes.add(newShape);
}
this.classifier = classifier;
this.structure = structure;
this.featureDescription = featureDescription;
orbitVersion = OrbitUtils.VERSION_STR;
}
/**
* Constructs a cloned model based on an old model.
* ClassShapesForReconstruction will be discarded!
*
* @param oldModel
*/
public OrbitModel(OrbitModel oldModel) {
if (oldModel.getClassShapes() != null)
this.classShapes = OrbitUtils.cloneClassShapes(oldModel.getClassShapes());
if (oldModel.getFeatureDescription() != null)
this.featureDescription = oldModel.getFeatureDescription().clone();
if (oldModel.getClassifier() != null) {
try {
this.classifier = ClassifierWrapper.makeCopy(oldModel.getClassifier());
} catch (Exception e) {
logger.error("cannot clone old classifier", e);
}
}
if (oldModel.getStructure() != null) {
this.structure = new Instances(oldModel.getStructure());
}
if (oldModel.getExclusionModel() != null)
this.setExclusionModel(new OrbitModel(oldModel.getExclusionModel()));
if (oldModel.getSegmentationModel() != null) {
this.setSegmentationModel(new OrbitModel(oldModel.getSegmentationModel()));
}
if (oldModel.getSecondarySegmentationModel() != null) {
this.setSecondarySegmentationModel(new OrbitModel(oldModel.getSecondarySegmentationModel()));
}
this.setMipLayer(oldModel.getMipLayer());
this.isCellClassification = oldModel.isCellClassification();
this.setBoundaryClass(oldModel.getBoundaryClass());
this.setFixedCircularROI(oldModel.getFixedCircularROI());
this.setFixedROIOffsetX(oldModel.getFixedROIOffsetX());
this.setFixedROIOffsetY(oldModel.getFixedROIOffsetY());
this.setLoadAnnotationsAsInversROI(oldModel.isLoadAnnotationsAsInversROI());
this.setOrbitVersion(oldModel.getOrbitVersion());
this.setVersion(oldModel.getVersion());
this.setAnnotationGroup(oldModel.getAnnotationGroup());
this.setApplyExclusionOnNegativeChannel(oldModel.applyExclusionOnNegativeChannel);
this.setPerformErodeDiliate(oldModel.isPerformErodeDiliate());
this.setExclusionLevel(oldModel.getExclusionLevel());
if (oldModel.getVersion() < 6 && oldModel.getExclusionLevel() == 0)
this.setExclusionLevel(1);
}
/**
* Constructs the model by loading the file
*
* @param filename
*/
public static OrbitModel LoadFromFile(String filename) {
File file = new File(filename);
if (file.isDirectory()) return null;
FileInputStream fis = null;
try {
fis = new FileInputStream(file);
return LoadFromInputStream(fis);
} catch (Exception ex) {
logger.error("cannot load model: {}", ex);
return null;
} finally {
try {
if (fis != null) fis.close();
} catch (IOException e1) {
e1.printStackTrace();
}
}
}
/**
* Constructs the model by loading the file via inputStream
*/
public static OrbitModel LoadFromInputStream(InputStream inStream) {
XStream xstream = new XStream();
OrbitModel model = null;
try {
byte[] bytes = toBytes(inStream);
GZIPInputStream zip = new GZIPInputStream(new ByteArrayInputStream(bytes));
//ObjectInputStream ois = new ObjectInputStream(zip);
ObjectInputStream ois = xstream.createObjectInputStream(zip);
try {
Object obj = ois.readObject();
model = (OrbitModel) obj;
// update sampleSize for old version models (in new versions it should be set)
if (model.getFeatureDescription() != null && model.getFeatureDescription().getSampleSize() == 0)
model.getFeatureDescription().setSampleSize(3);
// old annotation handling (without groups) -> use all annotations (annotation types have been converted already)
if (model.isLoadAnnotationsAsInversROI())
model.setAnnotationGroup(0);
if (model.getVersion() < 6 && model.getExclusionLevel() == 0) model.setExclusionLevel(1);
} catch (Exception ex) {
logger.error("cannot load model: {}", ex);
ex.printStackTrace();
} finally {
ois.close();
zip.close();
inStream.close();
}
} catch (Exception e) {
logger.error("Error: ", e);
e.printStackTrace();
}
// fixOldModelVersion(model);
return model;
}
private static byte[] toBytes(InputStream stream) throws IOException {
byte[] buffer = new byte[1024];
ByteArrayOutputStream os = new ByteArrayOutputStream();
int line = 0;
while ((line = stream.read(buffer)) != -1) {
os.write(buffer, 0, line);
}
stream.close();
os.flush();
os.close();
return os.toByteArray();
}
public static OrbitModel LoadFromOrbit(int modelId) throws Exception {
RawAnnotation anno = DALConfig.getImageProvider().LoadRawAnnotation(modelId);
if (anno.getRawAnnotationType() != RawAnnotation.ANNOTATION_TYPE_MODEL) {
throw new IllegalArgumentException("annotation " + modelId + " is not of type model annotation");
} else {
ModelAnnotation modelAnnotation = new ModelAnnotation(anno);
OrbitModel model = modelAnnotation.getModel();
// fixOldModelVersion(model);
return model;
}
}
public void saveModel(String filename) {
File file = new File(filename);
FileOutputStream fos = null;
try {
fos = new FileOutputStream(file);
fos.write(getAsByteArray());
fos.flush();
fos.close();
logger.info("model successfully saved to file " + filename);
} catch (Exception e) {
logger.error("Error", e);
e.printStackTrace();
} finally {
if (fos != null) try {
fos.close();
} catch (IOException e) {
}
}
}
/**
* Saves the model as a temp file (OrbitModel*.omo) and sets deleteOnExit.
*
* @param tempFolder
* @return
* @throws IOException
*/
public String saveModelAsTempFile(String tempFolder, boolean deleteOnExit) throws IOException {
File file = File.createTempFile("OrbitModel", OrbitUtils.MODEL_ENDING, new File(tempFolder));
if (deleteOnExit) file.deleteOnExit();
String filename = file.getAbsolutePath();
FileOutputStream fos = null;
try {
fos = new FileOutputStream(file);
fos.write(getAsByteArray());
fos.flush();
fos.close();
logger.info("model successfully saved to file " + filename);
} catch (Exception e) {
logger.error("Error", e);
e.printStackTrace();
} finally {
if (fos != null) try {
fos.close();
} catch (IOException e) {
}
}
return filename;
}
public int saveModelOrbit(String elb, String name, String userId) throws Exception {
ModelAnnotation modelAnnotation = new ModelAnnotation(this, elb, name, userId);
return DALConfig.getImageProvider().InsertRawAnnotation(modelAnnotation);
}
/**
* load all models from orbit, optional filter for a specific user (can be null)
*
* @param userId (user filter, can be null)
* @return
* @throws Exception
*/
public static List LoadFromOrbitUser(String userId) throws Exception {
List modelList = new ArrayList<>();
List annoList = DALConfig.getImageProvider().LoadRawAnnotationsByType(RawAnnotation.ANNOTATION_TYPE_MODEL);
for (RawAnnotation rawAnnotation : annoList) {
if (rawAnnotation.getRawAnnotationType() == RawAnnotation.ANNOTATION_TYPE_MODEL) {
if ((userId == null || userId.length() == 0) || userId.equals(rawAnnotation.getUserId())) {
ModelAnnotation modelAnnotation = new ModelAnnotation(rawAnnotation);
modelList.add(modelAnnotation);
}
}
}
return modelList;
}
public byte[] getAsByteArray() {
XStream xstream = new XStream();
byte[] res = null;
ByteArrayOutputStream outStream = null;
GZIPOutputStream zip = null;
ObjectOutputStream oos = null;
try {
outStream = new ByteArrayOutputStream();
zip = new GZIPOutputStream(outStream);
//oos = new ObjectOutputStream(zip);
oos = xstream.createObjectOutputStream(zip);
oos.writeObject(this);
oos.flush();
zip.flush();
oos.close(); // needed!!!
outStream.flush();
res = outStream.toByteArray();
} catch (Exception e) {
e.printStackTrace();
} finally {
if (outStream != null) try {
outStream.close();
} catch (IOException e) {
}
if (zip != null) try {
zip.close();
} catch (IOException e) {
}
if (oos != null) try {
oos.close();
} catch (IOException e) {
}
}
return res;
}
/**
* Removes nested segmentation and exclusion models from segmentation and exclusion model.
*/
public void cleanModel() {
if (segmentationModel != null) {
segmentationModel.setSegmentationModel(null);
segmentationModel.setExclusionModel(null);
}
if (exclusionModel != null) {
exclusionModel.setSegmentationModel(null);
exclusionModel.setExclusionModel(null);
}
}
/**
* Combines all classShapes of the iFrames, sets the orbit IDs and stores it in a separate list for later restoring.
*
* @param iFrames
*/
public void prepareModelforSaving(List iFrames) {
if (classShapesToRestore == null) return; // old deserialized model
// check for multiple-shape bug -> remove duplicate shapes
int cnt=0;
for (ClassShape cs: classShapesToRestore) {
cnt += cs.getShapeList().size();
}
if (cnt>10000) {
logger.info("more than 10000 class shapes - trying to remove duplicate shapes");
cleanUpShapesToRestore();
}
// collect open images
HashSet openRDFs = new HashSet<>();
if (iFrames != null) {
for (ImageFrame iFrame : iFrames) {
if (iFrame.getRdf()!=null) {
openRDFs.add(iFrame.getRdf().getRawDataFileId());
}
}
}
// save old class shapes from images which are not open
List classShapesToAdd = new ArrayList<>();
for (ClassShape cs: classShapesToRestore) {
ClassShape csNew = cs.clone();
csNew.getShapeList().clear();
for (Shape shape: cs.getShapeList()) {
if (shape instanceof IScaleableShape) {
IScaleableShape isc = (IScaleableShape) shape;
if (isc.getRdfId()>0) {
if (!openRDFs.contains(isc.getRdfId())) {
csNew.getShapeList().add(isc); // not open, so keep old one to add later
}
}
}
}
if (csNew.getShapeList().size()>0) {
classShapesToAdd.add(csNew);
}
}
// clear class shape list and initialize according to class shape drop-down box
classShapesToRestore.clear();
for (ClassShape cs : classShapes) {
ClassShape newShape = cs.clone();
newShape.setShapeList(Collections.synchronizedList(new ArrayList())); // store empty list
classShapesToRestore.add(newShape);
}
// add class shapes from open images
if (iFrames != null) {
for (ImageFrame iFrame : iFrames) {
if (iFrame.getRdf() != null) { // it's an Orbit image (not loaded from file)
if (iFrame.getRecognitionFrame().getClassShapes() != null) {
if (classShapes.size() == iFrame.getRecognitionFrame().getClassShapes().size()) { // check
for (int i = 0; i < classShapes.size(); i++) {
ClassShape cs = iFrame.getRecognitionFrame().getClassShapes().get(i);
for (Shape shape : cs.getShapeList()) {
if (shape instanceof IScaleableShape) {
((IScaleableShape) shape).setRdfId(iFrame.getRdf().getRawDataFileId());
classShapesToRestore.get(i).getShapeList().add(shape);
}
}
}
}
}
} else {
JOptionPane.showMessageDialog(null, "Training shapes from image " + iFrame.getTitle() + " cannot be saved because the image is not persistent in the Orbit database.\nThis is not a problem, but when loading the model you cannot reconstruct the training data.", "Cannot save training shapes", JOptionPane.WARNING_MESSAGE);
}
}
}
// add old (not open in images) class shapes
for (ClassShape csNew: classShapesToAdd) {
boolean found=false;
for (ClassShape cs: classShapesToRestore) {
if (cs.equalsSimple(csNew)) {
cs.getShapeList().addAll(csNew.getShapeList());
found = true;
break;
}
}
if (!found) classShapesToRestore.add(csNew);
}
}
public void cleanUpShapesToRestore() {
if (classShapesToRestore!=null) {
for (int csI=0; csI shapeList = new ArrayList<>();
for (Shape shape: cs.getShapeList()) {
boolean toAdd = true;
if (shape instanceof PolygonExt) {
PolygonExt pe = (PolygonExt) shape;
for (Shape shape2: shapeList) {
if (shape2 instanceof PolygonExt) {
PolygonExt pe2 = (PolygonExt) shape2;
if (pe2.equalsExact(pe)) {
toAdd = false;
break;
}
}
}
}
if (toAdd) {
shapeList.add(shape);
}
}
cs.setShapeList(shapeList);
logger.info("shapes to restore after ["+csI+"]: "+classShapesToRestore.get(csI).getShapeList().size());
}
}
}
/**
* convert models from old weka version
*
* @param model
*/
public static void fixOldModelVersion(final OrbitModel model) {
if (model == null) return; // nothing to fix
boolean oldWekaVersion = false;
try {
model.getStructure().classAttribute().numValues();
} catch (NullPointerException ne) {
oldWekaVersion = true;
}
// apply old model fix?
if (oldWekaVersion) {
logger.info("model from old weka version (< 3.7.11) detected, trying to apply fixes");
int numClasses = model.getClassShapes().size();
TissueFeatures tf = new TissueFeatures(model.getFeatureDescription(), null);
int numFeatures = tf.getFeaturesPerSample() * model.getFeatureDescription().getSampleSize() + 1;
ArrayList attrInfo = new ArrayList(numFeatures);
for (int a = 0; a < numFeatures - 1; a++) {
Attribute attr = new Attribute("a" + a);
attrInfo.add(attr);
}
List classValues = new ArrayList(numClasses);
for (int i = 0; i < numClasses; i++) {
classValues.add((i + 1) + ".0"); // "1.0", "2.0", ...
}
Attribute classAttr = new Attribute("class", classValues);
attrInfo.add(classAttr);
Instances structure = new Instances("trainSet pattern classes", attrInfo, 0);
structure.setClassIndex(numFeatures - 1);
model.setStructure(structure);
try {
if (model.getClassifier() != null && model.getClassifier().getClassifier() != null && model.getClassifier().getClassifier() instanceof SMO) {
SMO smo = ((SMO) model.getClassifier().getClassifier());
Field field = smo.getClass().getDeclaredField("m_classAttribute");
field.setAccessible(true);
field.set(smo, classAttr);
// missing values
ReplaceMissingValues rmv = new ReplaceMissingValues();
rmv.setInputFormat(structure);
Field missing = smo.getClass().getDeclaredField("m_Missing");
missing.setAccessible(true);
missing.set(smo, rmv);
// filter
Field filter = smo.getClass().getDeclaredField("m_Filter");
filter.setAccessible(true);
Filter normalize = (Filter) filter.get(smo);
RelationalLocator relLoc = new RelationalLocator(structure);
StringLocator strLoc = new StringLocator(structure);
Field outputRelAtts = normalize.getClass().getSuperclass().getSuperclass().getDeclaredField("m_OutputRelAtts");
outputRelAtts.setAccessible(true);
outputRelAtts.set(normalize, relLoc);
Field inputRelAtts = normalize.getClass().getSuperclass().getSuperclass().getDeclaredField("m_InputRelAtts");
inputRelAtts.setAccessible(true);
inputRelAtts.set(normalize, relLoc);
Field outputStrAtts = normalize.getClass().getSuperclass().getSuperclass().getDeclaredField("m_OutputStringAtts");
outputStrAtts.setAccessible(true);
outputStrAtts.set(normalize, strLoc);
Field inputStrAtts = normalize.getClass().getSuperclass().getSuperclass().getDeclaredField("m_InputStringAtts");
inputStrAtts.setAccessible(true);
inputStrAtts.set(normalize, strLoc);
Field outputFormat = normalize.getClass().getSuperclass().getSuperclass().getDeclaredField("m_OutputFormat");
outputFormat.setAccessible(true);
outputFormat.set(normalize, structure);
logger.info("fixes applied, the model should work with a weka version >= 3.7.11 now");
} // else: good luck...
} catch (Exception e) {
e.printStackTrace();
logger.error("new weka version fixes could not be applied: " + e.getMessage());
}
} // old weka version
fixOldModelVersion(model.getSegmentationModel()); // fixOldModelVersion can handle null
fixOldModelVersion(model.getSecondarySegmentationModel()); // fixOldModelVersion can handle null
fixOldModelVersion(model.getExclusionModel()); // fixOldModelVersion can handle null
}
public ClassifierWrapper getClassifier() {
return classifier;
}
public void setClassifier(ClassifierWrapper classifier) {
this.classifier = classifier;
}
public Instances getStructure() {
return structure;
}
public void setStructure(Instances structure) {
this.structure = structure;
}
public List getClassShapes() {
return classShapes;
}
public void setClassShapes(List classShapes) {
this.classShapes = classShapes;
}
public FeatureDescription getFeatureDescription() {
return featureDescription;
}
public void setFeatureDescription(FeatureDescription featureDescription) {
this.featureDescription = featureDescription;
}
public int getBoundaryClass() {
return boundaryClass;
}
public void setBoundaryClass(int boundaryClass) {
this.boundaryClass = boundaryClass;
}
public OrbitModel getSegmentationModel() {
return segmentationModel;
}
public void setSegmentationModel(OrbitModel segmentationModel) {
this.segmentationModel = segmentationModel;
}
public OrbitModel getSecondarySegmentationModel() {
return secondarySegmentationModel;
}
public void setSecondarySegmentationModel(OrbitModel secondarySegmentationModel) {
this.secondarySegmentationModel = secondarySegmentationModel;
}
public OrbitModel getExclusionModel() {
return exclusionModel;
}
public void setExclusionModel(OrbitModel exclusionModel) {
this.exclusionModel = exclusionModel;
}
public int getFixedCircularROI() {
return fixedCircularROI;
}
public void setFixedCircularROI(int fixedCircularROI) {
this.fixedCircularROI = fixedCircularROI;
}
public int getFixedROIOffsetX() {
return fixedROIOffsetX;
}
public int getFixedROIOffsetY() {
return fixedROIOffsetY;
}
public void setFixedROIOffsetX(int fixedROIOffsetX) {
this.fixedROIOffsetX = fixedROIOffsetX;
}
public void setFixedROIOffsetY(int fixedROIOffsetY) {
this.fixedROIOffsetY = fixedROIOffsetY;
}
public boolean isApplyExclusionOnNegativeChannel() {
return applyExclusionOnNegativeChannel;
}
public void setApplyExclusionOnNegativeChannel(boolean applyExclusionOnNegativeChannel) {
this.applyExclusionOnNegativeChannel = applyExclusionOnNegativeChannel;
}
public boolean isPerformErodeDiliate() {
return performErodeDiliate;
}
public void setPerformErodeDiliate(boolean performErodeDiliate) {
this.performErodeDiliate = performErodeDiliate;
}
public boolean isUseExclusionForSegmentation() {
return useExclusionForSegmentation;
}
public void setUseExclusionForSegmentation(boolean useExclusionForSegmentation) {
this.useExclusionForSegmentation = useExclusionForSegmentation;
}
public boolean isLoadAnnotationsAsInversROI() {
return loadAnnotationsAsInversROI;
}
public void setLoadAnnotationsAsInversROI(boolean loadAnnotationsAsInversROI) {
this.loadAnnotationsAsInversROI = loadAnnotationsAsInversROI;
}
public String getOrbitVersion() {
return orbitVersion;
}
public void setOrbitVersion(String orbitVersion) {
this.orbitVersion = orbitVersion;
}
public int getVersion() {
return version;
}
public void setVersion(int version) {
this.version = version;
}
public int getAnnotationGroup() {
return annotationGroup;
}
public void setAnnotationGroup(int annotationGroup) {
this.annotationGroup = annotationGroup;
}
public int getExclusionLevel() {
return exclusionLevel;
}
public void setExclusionLevel(int exclusionLevel) {
this.exclusionLevel = exclusionLevel;
}
public boolean isCellClassification() {
return isCellClassification;
}
public void setCellClassification(boolean isCellClassification) {
this.isCellClassification = isCellClassification;
}
public int getMipLayer() {
return mipLayer;
}
public void setMipLayer(int mipLayer) {
this.mipLayer = mipLayer;
}
public List getClassShapesToRestore() {
return classShapesToRestore;
}
@Override
public String toString() {
StringBuilder sb = new StringBuilder();
sb.append("Version=" + version + "\n");
sb.append("Built with OrbitImageAnalysis version: " + orbitVersion + "\n");
sb.append("ClassShapes:\n");
if (classShapes == null) sb.append("classShapes is null\n");
else {
for (ClassShape cs : classShapes) {
sb.append(" " + cs.toString() + "\n");
}
}
sb.append("mipLayer: " + mipLayer + "\n");
sb.append("isCellClassification: " + isCellClassification + "\n");
sb.append("boundaryClass: " + boundaryClass + "\n");
sb.append("fixedCircularROI: " + fixedCircularROI + "\n");
sb.append("fixedROIOffsetX: " + fixedROIOffsetX + "\n");
sb.append("fixedROIOffsetY: " + fixedROIOffsetY + "\n");
sb.append("AnnotationGroup: " + annotationGroup + "\n");
sb.append("ExclusionLevel: " + exclusionLevel+"\n");
sb.append("applyExclusionOnNegativeChannel: " + applyExclusionOnNegativeChannel + "\n");
sb.append("loadAnnotationsAsNegativeROI: " + loadAnnotationsAsInversROI + "\n");
sb.append("performErodeDiliate: " + performErodeDiliate + "\n");
sb.append("useExclusionForSegmentation: " + useExclusionForSegmentation + "\n");
sb.append("FeatureDescription:\n");
sb.append(featureDescription + "\n");
sb.append("Classifier: ");
sb.append(classifier == null ? "null" : ("set; isBuild:" + classifier.isBuild()) + "\n");
sb.append("Structure: ");
sb.append(structure == null ? "null" : ("numInstances:" + structure.size()) + "\n");
sb.append("SegmentationModel:\n" + segmentationModel + "\n***\n");
sb.append("SecondarySegmentationModel:\n" + secondarySegmentationModel + "\n***\n");
sb.append("ExclusionModel:\n" + exclusionModel + "\n***\n");
sb.append("------\n");
return sb.toString();
}
}