Refactor 092024 (#52)

* fixes confusion between per tile and global preprocessing methods

* fixes formatting

* fixes rounding of downsampling

fixes typos, formatting and comment contents

* updates logic of handling tiles

* updates demo scripts

* fixes IntelliJ warnings

* bumps version number

build.gradle

@@ -25,7 +25,7 @@ ext.qupathVersion = gradle.ext.qupathVersion
 
 description = 'QuPath extension to use Cellpose'
 
-version = "0.9.6-SNAPSHOT"
+version = "0.9.6"
 
 dependencies {
     implementation "io.github.qupath:qupath-gui-fx:${qupathVersion}"

src/main/java/qupath/ext/biop/cellpose/CellposeBuilder.java

@@ -226,7 +226,7 @@ public CellposeBuilder preprocess(ImageOp... ops) {
      * @param global preprocessing operation
      * @return this builder
      */
-    public CellposeBuilder preprocess(TileOpCreator global) {
+    public CellposeBuilder preprocessGlobal(TileOpCreator global) {
         this.globalPreprocessing = global;
         return this;
     }
@@ -761,7 +761,7 @@ public CellposeBuilder normalizePercentilesGlobal(double percentileMin, double p
         this.noCellposeNormalization();
 
         // Add this operation to the preprocessing
-        return this.preprocess(normOp);
+        return this.preprocessGlobal(normOp);
     }
 
     /**
@@ -834,7 +834,7 @@ public Cellpose2D build() {
 
         cellpose.extendChannelOp = extendChannelOp;
 
-
+        // TODO make compatible with --all_channels
         if (this.channels.length > 2) {
             logger.warn("You supplied {} channels, but Cellpose needs two channels at most. Keeping the first two", channels.length);
             this.channels = Arrays.copyOf(this.channels, 2);

src/main/java/qupath/ext/biop/cellpose/CellposeExtension.java

@@ -69,7 +69,6 @@ public void installExtension(QuPathGUI qupath) {
         StringProperty omniposePath = PathPrefs.createPersistentPreference("omniposePythonPath", "");
         StringProperty condaPath = PathPrefs.createPersistentPreference("condaPath", "");
 
-
         //Set options to current values
         options.setCellposePythonPath(cellposePath.get());
         options.setOmniposePythonPath(omniposePath.get());

src/main/java/qupath/ext/biop/cellpose/CellposeSetup.java

@@ -8,7 +8,6 @@ public class CellposeSetup {
     private static final CellposeSetup instance = new CellposeSetup();
     private String cellposePythonPath = null;
     private String omniposePythonPath = null;
-
     private String condaPath = null;
 
     public static CellposeSetup getInstance() {
@@ -41,7 +40,7 @@ public void setCondaPath(String condaPath) {
 
     private void checkPath(String path) {
         // It should be a file and it should exist
-        if( !path.equals("")) {
+        if(!path.trim().isEmpty()) {
             File toCheck = new File(path);
             if (!toCheck.exists())
                 Dialogs.showWarningNotification("Cellpose/Omnipose extension: Path not found", "The path to \"" + path + "\" does not exist or does not point to a valid file.");

src/main/resources/scripts/Cellpose_detection_template.groovy

@@ -20,41 +20,41 @@
 // Specify the model name (cyto, nuclei, cyto2, ... or a path to your custom model as a string)
 // Other models for Cellpose https://cellpose.readthedocs.io/en/latest/models.html
 // And for Omnipose: https://omnipose.readthedocs.io/models.html
-def pathModel = 'cyto2'
+def pathModel = 'cyto3'
 def cellpose = Cellpose2D.builder( pathModel )
         .pixelSize( 0.5 )                  // Resolution for detection in um
         .channels( 'DAPI' )	               // Select detection channel(s)
 //        .tempDirectory( new File( '/tmp' ) ) // Temporary directory to export images to. defaults to 'cellpose-temp' inside the QuPath Project
-//        .preprocess( ImageOps.Filters.median(1) )                // List of preprocessing ImageOps to run on the images before exporting them
-//        .normalizePercentilesGlobal(0.1, 99.8, 10) // Convenience global percentile normalization. arguments are percentileMin, percentileMax, dowsample.
-//        .tileSize(1024)                  // If your GPU can take it, make larger tiles to process fewer of them. Useful for Omnipose
-//        .cellposeChannels(1,2)           // Overwrites the logic of this plugin with these two values. These will be sent directly to --chan and --chan2
-//        .cellprobThreshold(0.0)          // Threshold for the mask detection, defaults to 0.0
-//        .flowThreshold(0.4)              // Threshold for the flows, defaults to 0.4
-//        .diameter(15)                    // Median object diameter. Set to 0.0 for the `bact_omni` model or for automatic computation
+//        .preprocess( ImageOps.Filters.median( 1 ) )                // List of preprocessing ImageOps to run on the images before exporting them
+//        .normalizePercentilesGlobal( 0.1, 99.8, 10 ) // Convenience global percentile normalization. arguments are percentileMin, percentileMax, dowsample.
+//        .tileSize( 1024 )                  // If your GPU can take it, make larger tiles to process fewer of them. Useful for Omnipose
+//        .cellposeChannels( 1,2 )           // Overwrites the logic of this plugin with these two values. These will be sent directly to --chan and --chan2
+//        .cellprobThreshold( 0.0 )          // Threshold for the mask detection, defaults to 0.0
+//        .flowThreshold( 0.4 )              // Threshold for the flows, defaults to 0.4
+//        .diameter( 15 )                    // Median object diameter. Set to 0.0 for the `bact_omni` model or for automatic computation
 //        .useOmnipose()                   // Use omnipose instead
-//        .addParameter("cluster")         // Any parameter from cellpose or omnipose not available in the builder.
-//        .addParameter("save_flows")      // Any parameter from cellpose or omnipose not available in the builder.
-//        .addParameter("anisotropy", "3") // Any parameter from cellpose or omnipose not available in the builder.
-//        .cellExpansion(5.0)              // Approximate cells based upon nucleus expansion
-//        .cellConstrainScale(1.5)         // Constrain cell expansion using nucleus size
-//        .classify("My Detections")       // PathClass to give newly created objects
+//        .addParameter( "cluster" )         // Any parameter from cellpose or omnipose not available in the builder.
+//        .addParameter( "save_flows" )      // Any parameter from cellpose or omnipose not available in the builder.
+//        .addParameter( "anisotropy", "3" ) // Any parameter from cellpose or omnipose not available in the builder.
+//        .cellExpansion( 5.0 )              // Approximate cells based upon nucleus expansion
+//        .cellConstrainScale( 1.5 )         // Constrain cell expansion using nucleus size
+//        .classify( "My Detections" )       // PathClass to give newly created objects
 //        .measureShape()                  // Add shape measurements
 //        .measureIntensity()              // Add cell measurements (in all compartments)
 //        .createAnnotations()             // Make annotations instead of detections. This ignores cellExpansion
-//        .simplify(0)                     // Simplification 1.6 by default, set to 0 to get the cellpose masks as precisely as possible
+//        .simplify( 0 )                     // Simplification 1.6 by default, set to 0 to get the cellpose masks as precisely as possible
         .build()
 
 // Run detection for the selected objects
 def imageData = getCurrentImageData()
 def pathObjects = getSelectedObjects() // To process only selected annotations, useful while testing
 // def pathObjects = getAnnotationObjects() // To process all annotations. For working in batch mode
 if (pathObjects.isEmpty()) {
-    Dialogs.showErrorMessage("Cellpose", "Please select a parent object!")
+    Dialogs.showErrorMessage( "Cellpose", "Please select a parent object!" )
     return
 }
 
-cellpose.detectObjects(imageData, pathObjects)
+cellpose.detectObjects( imageData, pathObjects )
 
 // You could do some post-processing here, e.g. to remove objects that are too small, but it is usually better to
 // do this in a separate script so you can see the results before deleting anything.

src/main/resources/scripts/Cellpose_training_template.groovy

@@ -17,18 +17,18 @@
  */
 
 // First we need to create a Cellpose2D builder and add all parameters that we want to use for training
-def cellpose = Cellpose2D.builder("cyto") // Can choose "None" if you want to train from scratch
-        .channels("DAPI", "CY3")  // or work with .cellposeChannels( channel1, channel2 ) and follow the cellpose way
-//                .preprocess(ImageOps.Filters.gaussianBlur(1)) // Optional preprocessing QuPath Ops
-//                .epochs(500)             // Optional: will default to 500
-//                .groundTruthDirectory( new File("/my/ground/truth/folder")) // Optional: If you wish to save your GT elsewhere than the QuPath Project
-//                .learningRate(0.2)       // Optional: Will default to 0.2
-//                .batchSize(8)            // Optional: Will default to 8
-//                .minTrainMasks(5)        // Optional: Will default to 5
-//                .addParameter("save_flows")      // Any parameter from cellpose not available in the builder. See https://cellpose.readthedocs.io/en/latest/command.html
-//                .addParameter("anisotropy", "3") // Any parameter from cellpose not available in the builder. See https://cellpose.readthedocs.io/en/latest/command.html
-//                .modelDirectory( new File("My/folder/for/models")) // Optional place to store resulting model. Will default to QuPath project root, and make a 'models' folder
-//                .saveBuilder("My Builder") // Optional: Will save a builder json file that can be reloaded with Cellpose2D.builder(File builderFile)
+def cellpose = Cellpose2D.builder( "cyto3" )    // Can choose "None" if you want to train from scratch
+        .channels( "DAPI", "CY3" )                         // or work with .cellposeChannels( channel1, channel2 ) and follow the cellpose way
+//                .preprocess( ImageOps.Filters.gaussianBlur( 1 ) ) // Optional preprocessing QuPath Ops
+//                .epochs(500)                                      // Optional: will default to 500
+//                .groundTruthDirectory( new File( "/my/ground/truth/folder" ) ) // Optional: If you wish to save your GT elsewhere than the QuPath Project
+//                .learningRate(0.2)                                // Optional: Will default to 0.2
+//                .batchSize(8)                                     // Optional: Will default to 8
+//                .minTrainMasks(5)                                 // Optional: Will default to 5
+//                .addParameter("save_flows")                       // Any parameter from cellpose not available in the builder. See https://cellpose.readthedocs.io/en/latest/command.html
+//                .addParameter("anisotropy", "3")                  // Any parameter from cellpose not available in the builder. See https://cellpose.readthedocs.io/en/latest/command.html
+//                .modelDirectory( new File("D:/models/" ) )        // Optional place to store resulting model. Will default to QuPath project root, and make a 'models' folder
+//                .saveBuilder("My Builder")                        // Optional: Will save a builder json file that can be reloaded with Cellpose2D.builder(File builderFile)
         .build()
 
 // Now we can train a new model

src/main/resources/scripts/Create_Cellpose_training_and_validation_images.groovy

@@ -21,7 +21,7 @@ import qupath.ext.biop.cellpose.Cellpose2D
 
 // Build a Cellpose instance for saving the image pairs
 def cellpose = Cellpose2D.builder( "None" )     // No effect, as this script only exports the images
-//                .channels( "DAPI", "CY3" )    // Optional: Image channels to export
+//                .channels( "DAPI", "CY3" )                        // Optional: Image channels to export
 //                .preprocess( ImageOps.Filters.gaussianBlur( 1 ) ) // Optional: preprocessing QuPath Ops 
                 .build()
 

src/main/resources/scripts/Detect_nuclei_and_cells_using_Cellpose.groovy

@@ -19,18 +19,18 @@ if (pathObjects.isEmpty()) {
 clearDetections()
 
 // Create a Cellpose detectors for cyto and nuclei
-def pathModel_cyto = 'cyto2'
+def pathModel_cyto = 'cyto3'
 def cellpose_cyto = Cellpose2D.builder( pathModel_cyto )
-        .channels("HCS","DAPI")
+        .channels( "HCS","DAPI" )
         .pixelSize( 0.3 )              // Resolution for detection
-        .diameter(30)                  // Median object diameter. Set to 0.0 for the `bact_omni` model or for automatic computation
+        .diameter(30 )                  // Median object diameter. Set to 0.0 for the `bact_omni` model or for automatic computation
         .measureShape()                // Add shape measurements
         .measureIntensity()            // Add cell measurements (in all compartments) 
         .build()
 
-def pathModel_nuc = 'cyto2'
+def pathModel_nuc = 'cyto3'
 def cellpose_nuc = Cellpose2D.builder( pathModel_nuc )
-        .channels("DAPI")
+        .channels("DAPI" )
         .pixelSize( 0.3 )              // Resolution for detection
         .diameter(10)                  // Median object diameter. Set to 0.0 for the `bact_omni` model or for automatic computation
         .build()