Updating deep learning module to support delphinID models

.classpath

@@ -6,7 +6,7 @@
 			<attribute name="maven.pomderived" value="true"/>
 		</attributes>
 	</classpathentry>
-	<classpathentry kind="con" path="org.eclipse.jdt.launching.JRE_CONTAINER/org.eclipse.jdt.internal.debug.ui.launcher.StandardVMType/Amazon Coretto 21">
+	<classpathentry kind="con" path="org.eclipse.jdt.launching.JRE_CONTAINER/org.eclipse.jdt.internal.debug.ui.launcher.StandardVMType/jdk-21.0.2.13-hotspot">
 		<attributes>
 			<attribute name="module" value="true"/>
 			<attribute name="maven.pomderived" value="true"/>

src/pamViewFX/fxNodes/connectionPane/ConnectionPane.java

@@ -411,26 +411,29 @@ public class ConnectionPane extends Pane {
 		if (includeBranch) {
 			StandardConnectionSocket socket;
 			for (int i = 0; i < parentNode.getConnectionPlugs().size(); i++) {
-				socket = (StandardConnectionSocket) parentNode.getConnectionPlugs().get(i).getConnectedShape();
-				if (socket == null || !socket.isBranch())
-					continue;
-				// is this socket connected to child node?
-				if (socket.getParentConnectionPlug().getConnectedShape() != null) {
+				if (parentNode.getConnectionPlugs().get(i).getConnectedShape() instanceof StandardConnectionSocket) {
+					socket = (StandardConnectionSocket) parentNode.getConnectionPlugs().get(i).getConnectedShape();
+					if (socket == null || !socket.isBranch())
+						continue;
+					// is this socket connected to child node?
+					if (socket.getParentConnectionPlug().getConnectedShape() != null) {
 
-					if (socket.getParentConnectionPlug().getConnectedShape().getConnectionNode() == childNode) {
-						// return socket.getParentConnectionPlug();
-						node = socket.getConnectedShape();
-					} 
-					else if (bypassStructure && socket.getParentConnectionPlug().getConnectedShape()
-							.getConnectionNode() instanceof ConnectionStructure) {
-						// go down another level
-						node = getConnectionPlug(parentNode,
-								socket.getParentConnectionPlug().getConnectedShape().getConnectionNode(), includeBranch,
-								bypassStructure);
+						if (socket.getParentConnectionPlug().getConnectedShape().getConnectionNode() == childNode) {
+							// return socket.getParentConnectionPlug();
+							node = socket.getConnectedShape();
+						} 
+						else if (bypassStructure && socket.getParentConnectionPlug().getConnectedShape()
+								.getConnectionNode() instanceof ConnectionStructure) {
+							// go down another level
+							node = getConnectionPlug(parentNode,
+									socket.getParentConnectionPlug().getConnectedShape().getConnectionNode(), includeBranch,
+									bypassStructure);
+						}
 					}
+
+					if (node != null)
+						return node;
 				}
-				if (node != null)
-					return node;
 
 			}
 		}

src/rawDeepLearningClassifier/DLStatus.java

@@ -12,7 +12,7 @@ public enum DLStatus {
 			" The model failed to load - this could be because it is incompatible with PAMGuard or an uknown file format.",
 			ErrorLevel.ERROR),
 
-	MODEL_LOAD_SUCCESS("The model loaded", " The model successfully load", ErrorLevel.NO_ERROR),
+	MODEL_LOAD_SUCCESS("The model loaded", " The model successfully loaded", ErrorLevel.NO_ERROR),
 
 	DOWNLOAD_STARTING("Download starting", "The model is downloading", ErrorLevel.NO_ERROR),
 

src/rawDeepLearningClassifier/DLZipUtils.java

@@ -0,0 +1,106 @@
+package rawDeepLearningClassifier;
+
+import java.io.BufferedInputStream;
+import java.io.File;
+import java.io.FileInputStream;
+import java.io.FileOutputStream;
+import java.io.IOException;
+import java.io.OutputStream;
+import java.net.URI;
+import java.net.URISyntaxException;
+import java.util.Enumeration;
+import java.util.zip.ZipEntry;
+import java.util.zip.ZipException;
+import java.util.zip.ZipFile;
+import java.util.zip.ZipInputStream;
+
+
+public class DLZipUtils {
+	
+	/**
+	 * Find the first file within a zip folder that matches a pattern. This peaks into the zip file instead of decompressing it. 
+	 * @param zipUri - uri to the zip file
+	 * @param filePattern - the file pattern to match - the file must contain this string. 
+	 * @return null if no file found and the file pqth if the file is founf
+	 * @throws ZipException
+	 * @throws IOException
+	 */
+	public  static String getZipFilePath(URI zipUri, String filePattern) throws ZipException, IOException {
+		return getZipFilePath(new File(zipUri),  filePattern);
+	}
+	
+	
+	/**
+	 * Extract a single file from a zip folder.
+	 * @param zipPackage - URI to the the zip file
+	 * @param fileToBeExtracted - the name of the file to be extracted 
+	 * @param - the folder path  to extract the file to.
+	 * @return - return the File that  has been extracted.  
+	 * @throws IOException
+	 * @throws URISyntaxException 
+	 */
+	public static File extractFile(String zipPackage, String fileToBeExtracted, String outFolder) throws IOException, URISyntaxException {
+		 return extractFile( new URI(zipPackage),  fileToBeExtracted,  outFolder) ;
+	}
+
+	
+	/**
+	 * Extract a single file from a zip folder.
+	 * @param zipPackage - path the the zip file
+	 * @param fileToBeExtracted - the name of the file to be extracted 
+	 * @param - the folder path  to extract the file to.
+	 * @return - return the File that  has been extracted.  
+	 * @throws IOException
+	 */
+	public static File extractFile(URI zipPackage, String fileToBeExtracted, String outFolder) throws IOException {
+		File fileOut = new File(outFolder, fileToBeExtracted); 
+        OutputStream out = new FileOutputStream(fileOut);
+        FileInputStream fileInputStream = new FileInputStream(new File(zipPackage));
+        BufferedInputStream bufferedInputStream = new BufferedInputStream(fileInputStream );
+        ZipInputStream zin = new ZipInputStream(bufferedInputStream);
+        ZipEntry ze = null;
+        while ((ze = zin.getNextEntry()) != null) {
+            if (ze.getName().equals(fileToBeExtracted)) {
+                byte[] buffer = new byte[9000];
+                int len;
+                while ((len = zin.read(buffer)) != -1) {
+                    out.write(buffer, 0, len);
+                }
+                out.close();
+                break;
+            }
+        }
+        zin.close();
+        
+        return fileOut;
+	}
+	
+	
+	/**
+	 * Find the first file within a zip folder that matches a pattern. 
+	 * @param zipFile - uri to the zip file
+	 * @param filePattern - the file pattern to match - the file must contain this string. 
+	 * @return null if no file found and the file pqth if the file is founf
+	 * @throws ZipException
+	 * @throws IOException
+	 */
+	public static String getZipFilePath(File zipFileIn, String filePattern) throws ZipException, IOException {
+			
+		try (ZipFile zipFile = new ZipFile(zipFileIn)) {
+		    Enumeration<? extends ZipEntry> entries = zipFile.entries();
+		    //this iterates through all files, including in sub folders. 
+		    while (entries.hasMoreElements()) {
+		        ZipEntry entry = entries.nextElement();
+		        // Check if entry is a directory
+		        if (!entry.isDirectory()) {
+		           //System.out.println(entry); 
+		           if (entry.getName().contains(filePattern)) {
+		        	   return entry.getName();
+		           }
+		        }
+		    }
+		}
+		return null;
+	}
+
+}

src/rawDeepLearningClassifier/dlClassification/DLClassifierChooser.java

@@ -1,14 +1,21 @@
 package rawDeepLearningClassifier.dlClassification;
 
+import java.io.File;
+import java.io.IOException;
 import java.net.URI;
 
+import org.codehaus.plexus.util.FileUtils;
+import org.jamdev.jdl4pam.transforms.jsonfile.DLTransformsParser;
+import org.json.JSONObject;
+
+import ai.djl.repository.FilenameUtils;
 import rawDeepLearningClassifier.DLControl;
+import rawDeepLearningClassifier.DLZipUtils;
 
 /**
- * Selects which type of DL classiifer to use. 
+ * Selects which type of DL classifier to use. 
+ * 
  * @author Jamie Macaulay
- * 
- *
  */
 public class DLClassifierChooser {
 
@@ -19,10 +26,62 @@ public class DLClassifierChooser {
 		this.dlControl = dlControl; 
 	}
 
-	
+	/**
+	 * Select the correct classifier model to use from a URI. 
+	 * @param modelURI - the URI
+	 * @return the classifier model that runs the file. 
+	 */
 	public DLClassiferModel selectClassiferModel(URI modelURI) {
 
-		//check for model compatibility. 
+		String extension = FileUtils.getExtension(modelURI.getPath());
+
+
+		if (extension.equals("zip")) {
+			//If the model is a zip file it may contain a model and a metadata file. Want to check 
+			//this metadata file in case it points to a particular framework.
+			try {
+				String settingsFile = DLZipUtils.getZipFilePath(modelURI, ".pdtf");
+				System.out.println("Settings file: " +settingsFile);
+				if (settingsFile!=null) {
+					//there's a settings file - does it contain a metadata field describing which
+					//type of classifier it belongs to. 
+					String outFolder = System.getProperty("user.home") +  File.separator + "PAMGuard_temp";
+					new File(outFolder).mkdir();
+
+					File file = DLZipUtils.extractFile(modelURI, settingsFile, outFolder);
+					if (file!=null) {
+						//now we need to open the file and get a specific JSON field which describes the model. 
+						//read the JSON string from the the file. 
+						String jsonString  = DLTransformsParser.readJSONString(file);
+						JSONObject object = new JSONObject(jsonString); 
+
+						JSONObject frameworkObject = object.getJSONObject("framework_info");
+						String frameworkString = frameworkObject.getString("framework");
+
+						for (DLClassiferModel model: dlControl.getDLModels()) {
+							//System.out.println("frameworkString: " + frameworkString + "  " + model.getName());
+							if (model.getName().toLowerCase().equals(frameworkString.trim().toLowerCase())) return model;
+						}
+
+					} 
+					else {
+						System.err.println("DLClassifierChooser: Unable to extract the metadata file even though it exists in the zip archive:??"); 
+					}
+				}
+				else {
+					System.err.println("DLClassifierChooser: The zip file does not contain a metadata  file for the deep learning model"); 
+				}
+			} catch (IOException e) {
+				// TODO Auto-generated catch block
+				e.printStackTrace();
+			}
+		}
+
+		// Check for model compatibility. This usually means checking for a file
+		// extension. Note that a koogu .kgu model. for example can cxontain a metadata
+		// file without the correct @koogu@ field. In this instance the model is loaded
+		// properly because of the file extension but would not have been loaded by
+		// checking the metadata as above
 		for (DLClassiferModel model: dlControl.getDLModels()) {
 			if (model.isModelType(modelURI)) return model; 
 		}

src/rawDeepLearningClassifier/dlClassification/StandardClassifierModel.java

@@ -87,6 +87,7 @@ public abstract class StandardClassifierModel implements DLClassiferModel, PamSe
 			return modelResult; //returns to the classifier. 
 		}
 		else {
+			//REAL TIME
 			//add to a buffer if in real time. 
 			if (workerThread.getQueue().size()>DLModelWorker.MAX_QUEUE_SIZE) {
 				//we are not doing well - clear the buffer

src/rawDeepLearningClassifier/dlClassification/animalSpot/SoundSpotClassifier.java

@@ -62,9 +62,7 @@ public class SoundSpotClassifier extends StandardClassifierModel {
 		this.soundSpotUI= new SoundSpotUI(this); 
 		//load the previous settings
 		PamSettingManager.getInstance().registerSettings(this);
-
 //		System.out.println("LOADED CLASS NAMES: currParams.classNames: " + soundSpotParmas.classNames); 
-
 	}
 
 

src/rawDeepLearningClassifier/dlClassification/animalSpot/StandardModelPane.java

@@ -201,6 +201,7 @@ public abstract class StandardModelPane extends SettingsPane<StandardModelParams
 		//speciesIDBox.setMaxWidth(100);
 //		speciesIDBox.setPrefWidth(100);
 		speciesIDBox.prefHeightProperty().bind(detectionSpinner.heightProperty());
+		speciesIDBox.setMaxWidth(200); //otherwise expands too much if multiple classes selected
 		
 		validator = new PamValidator();
 		

src/rawDeepLearningClassifier/dlClassification/archiveModel/ArchiveModelClassifier.java

@@ -177,7 +177,6 @@ public abstract class ArchiveModelClassifier extends StandardClassifierModel {
 
 	@Override
 	public boolean isModelType(URI uri) {
-		//Ketos is easy because there are not many files with a .ktpb extension. 
 		return super.isModelExtensions(uri);
 	}
 

src/rawDeepLearningClassifier/dlClassification/archiveModel/ArchiveModelWorker.java

@@ -257,32 +257,5 @@ public class ArchiveModelWorker extends GenericModelWorker {
 		return dlModel==null;
 	}
 
-	/**
-	 * Find the first file within a zip folder that matches a pattern. 
-	 * @param zipFile - uri to the zip file
-	 * @param filePattern - the file pattern to match - the file must contain this string. 
-	 * @return null if no file found and the file pqth if the file is founf
-	 * @throws ZipException
-	 * @throws IOException
-	 */
-	static String getZipFilePath(File zipFileIn, String filePattern) throws ZipException, IOException {
-			
-		try (ZipFile zipFile = new ZipFile(zipFileIn)) {
-		    Enumeration<? extends ZipEntry> entries = zipFile.entries();
-		    //this iterates through all files, including in sub folders. 
-		    while (entries.hasMoreElements()) {
-		        ZipEntry entry = entries.nextElement();
-		        // Check if entry is a directory
-		        if (!entry.isDirectory()) {
-		           //System.out.println(entry); 
-		           if (entry.getName().contains(filePattern)) {
-		        	   return entry.getName();
-		           }
-		        }
-		    }
-		}
-		return null;
-	}
-
 
 }

src/rawDeepLearningClassifier/dlClassification/archiveModel/PamZipModelClassifier.java

@@ -6,6 +6,7 @@ import java.net.URI;
 import java.util.zip.ZipException;
 import rawDeepLearningClassifier.DLControl;
 import rawDeepLearningClassifier.DLStatus;
+import rawDeepLearningClassifier.DLZipUtils;
 
 /**
  * Loads a zip file and checks for a saved model alongside a pamguard settings file
@@ -72,8 +73,8 @@ public class PamZipModelClassifier extends ArchiveModelClassifier {
 	 * @throws ZipException
 	 * @throws IOException
 	 */
-	private static String getZipFilePath(URI zipUri, String filePattern) throws ZipException, IOException {
-		return ArchiveModelWorker.getZipFilePath(new File(zipUri),  filePattern);
+	public  static String getZipFilePath(URI zipUri, String filePattern) throws ZipException, IOException {
+		return DLZipUtils.getZipFilePath(new File(zipUri),  filePattern);
 	}
 	
 	/**

src/rawDeepLearningClassifier/dlClassification/archiveModel/SimpleArchiveModel.java

@@ -58,9 +58,14 @@ public class SimpleArchiveModel extends ArchiveModel {
 		return "zip_model";
 	}
 
-	
+	/**
+	 * Gte the relative path of file within a zip folder. 
+	 * @param zipFolder
+	 * @param fileEnd
+	 * @return
+	 * @throws IOException
+	 */
 	private static String getRelFilePath(String zipFolder, String fileEnd) throws IOException {
-		  // find files matched `png` file extension from folder C:\\test
 		  try (Stream<Path> walk = Files.walk(Paths.get(zipFolder))) {
 		      List<String> result = walk
 		              .filter(p -> !Files.isDirectory(p))   // not a directory

src/rawDeepLearningClassifier/dlClassification/delphinID/DelphinIDClassifier.java

@@ -0,0 +1,41 @@
+package rawDeepLearningClassifier.dlClassification.delphinID;
+
+import rawDeepLearningClassifier.DLControl;
+import rawDeepLearningClassifier.dlClassification.archiveModel.ArchiveModelClassifier;
+import rawDeepLearningClassifier.dlClassification.archiveModel.ArchiveModelWorker;
+
+/**
+ * A classifier based on the delphinID method which uses whistle contours to predict
+ * dolphin species. 
+ * 
+ * @author Jamie Macaulay
+ *
+ */
+public class DelphinIDClassifier extends ArchiveModelClassifier{
+
+	private static final String MODEL_NAME = "delphinID";
+	
+	/**
+	 * Reference to the worker
+	 */
+	private DelphinIDWorker delphinIDWorker;
+
+	public DelphinIDClassifier(DLControl dlControl) {
+		super(dlControl);
+	}
+	
+	@Override
+	public String getName() {
+		return MODEL_NAME;
+	}
+	
+	@Override
+	public ArchiveModelWorker getModelWorker() {
+		if (delphinIDWorker==null) {
+			delphinIDWorker= new DelphinIDWorker(); 
+		}
+		return delphinIDWorker;
+	}
+
+	
+}

src/rawDeepLearningClassifier/dlClassification/delphinID/DelphinIDParams.java

@@ -0,0 +1,12 @@
+package rawDeepLearningClassifier.dlClassification.delphinID;
+
+import rawDeepLearningClassifier.dlClassification.animalSpot.StandardModelParams;
+
+public class DelphinIDParams extends StandardModelParams {
+
+	/**
+	 * 
+	 */
+	private static final long serialVersionUID = 1L;
+
+}

src/rawDeepLearningClassifier/dlClassification/delphinID/DelphinIDWorker.java

@@ -0,0 +1,10 @@
+package rawDeepLearningClassifier.dlClassification.delphinID;
+
+import rawDeepLearningClassifier.dlClassification.archiveModel.ArchiveModelWorker;
+
+public class DelphinIDWorker extends ArchiveModelWorker{
+
+	
+
+	
+}

src/rawDeepLearningClassifier/layoutFX/DLSettingsPane.java

@@ -39,6 +39,7 @@ import rawDeepLearningClassifier.DLControl;
 import rawDeepLearningClassifier.DLStatus;
 import rawDeepLearningClassifier.RawDLParams;
 import warnings.PamWarning;
+import whistlesAndMoans.ConnectedRegionDataUnit;
 
 /**
  * The settings pane. 
@@ -159,6 +160,7 @@ public class DLSettingsPane  extends SettingsPane<RawDLParams>{
 		sourcePane = new GroupedSourcePaneFX("Raw Sound Data", RawDataUnit.class, true, false, true);
 		sourcePane.addSourceType(ClickDetection.class, false);
 		sourcePane.addSourceType(ClipDataUnit.class, false);
+		sourcePane.addSourceType(ConnectedRegionDataUnit.class, false);
 
 
 		vBox.getChildren().add(sourcePane);

src/rawDeepLearningClassifier/segmenter/SegmenterDetectionGroup.java

@@ -0,0 +1,20 @@
+package rawDeepLearningClassifier.segmenter;
+
+import Localiser.detectionGroupLocaliser.GroupDetection;
+import PamguardMVC.PamDataUnit;
+
+/**
+ * A group of detection which are within a particular segment. This is used to pass detection groups straight to
+ * 
+ *  
+ *  * @author Jamie Macaulay
+ *
+ */
+public class SegmenterDetectionGroup extends GroupDetection<PamDataUnit> {
+
+	public SegmenterDetectionGroup(long timeMilliseconds, int channelBitmap, long startSample, long duration) {
+		super(timeMilliseconds, channelBitmap, startSample, duration);
+		// TODO Auto-generated constructor stub
+	}
+
+}

src/rawDeepLearningClassifier/segmenter/SegmenterGroupDataBlock.java

@@ -0,0 +1,18 @@
+package rawDeepLearningClassifier.segmenter;
+
+import PamguardMVC.PamDataBlock;
+import PamguardMVC.PamProcess;
+
+/**
+ * 
+ * @author Jamie Macaulay
+ *
+ */
+public class SegmenterGroupDataBlock extends PamDataBlock<SegmenterDetectionGroup> {
+
+	public SegmenterGroupDataBlock(String dataName, PamProcess parentProcess, int channelMap) {
+		super(SegmenterDetectionGroup.class, dataName, parentProcess, channelMap);
+		// TODO Auto-generated constructor stub
+	}
+
+}

src/rawDeepLearningClassifier/segmenter/SegmenterProcess.java

@@ -21,6 +21,7 @@ import PamguardMVC.debug.Debug;
 import clickDetector.ClickDetection;
 import clipgenerator.ClipDataUnit;
 import rawDeepLearningClassifier.DLControl;
+import whistlesAndMoans.ConnectedRegionDataUnit;
 import PamUtils.PamCalendar;
 
 
@@ -60,6 +61,11 @@ public class SegmenterProcess extends PamProcess {
 	PamSymbol defaultSymbol = new PamSymbol(PamSymbolType.SYMBOL_DIAMOND, 10, 12, false,
 			Color.CYAN, Color.CYAN);
 
+	/**
+	 * Holds groups of data units which are within a defined segment. 
+	 */
+	private SegmenterGroupDataBlock segmenterGroupDataBlock; 
+
 
 	public SegmenterProcess(DLControl pamControlledUnit, PamDataBlock parentDataBlock) {
 		super(pamControlledUnit, parentDataBlock);
@@ -76,7 +82,12 @@ public class SegmenterProcess extends PamProcess {
 
 		segmenterDataBlock = new SegmenterDataBlock("Segmented Raw Data", this,
 				dlControl.getDLParams().groupedSourceParams.getChanOrSeqBitmap());
+		
+		segmenterGroupDataBlock = new SegmenterGroupDataBlock("Segmented Raw Data", this,
+				dlControl.getDLParams().groupedSourceParams.getChanOrSeqBitmap());
+		
 		addOutputDataBlock(segmenterDataBlock);
+		addOutputDataBlock(segmenterGroupDataBlock);
 
 		setProcessName("Segmenter");  
 
@@ -208,11 +219,25 @@ public class SegmenterProcess extends PamProcess {
 			else if (pamRawData instanceof ClipDataUnit)  {
 				newClipData(pamRawData);
 			}
+			else if (pamRawData instanceof ConnectedRegionDataUnit)  {
+				newWhistleData(pamRawData);
+			}
 		}
 
 	}
 
 
+	/**
+	 * A new whistle data unit. 
+	 * @param dataUnit - the whistle data unit. 
+	 */
+	private void newWhistleData(PamDataUnit dataUnit) {
+		ConnectedRegionDataUnit rawDataUnit = (ConnectedRegionDataUnit) dataUnit;
+
+		
+	}
+
+
 	/**
 	 * A new raw data unit. 
 	 * @param obs - the PAM observable 
@@ -344,7 +369,7 @@ public class SegmenterProcess extends PamProcess {
 	 * 
 	 * @param unit         - the data unit which contains relevant metadata on time
 	 *                     etc.
-	 * @param rawDataChunk - the sound chunk to segment extracted form the data
+	 * @param rawDataChunk - the sound chunk to segment extracted from the data
 	 *                     unit.
 	 * @param iChan        - the channel that is being segmented
 	 * @param forceSave    - make sure that all data is passed into the buffers and