Dev

coralnet_toolbox/Annotations/QtAnnotation.py

@@ -118,12 +118,30 @@ def update_user_confidence(self, new_label: 'Label'):
         self.show_message = False
 
     def update_label(self, new_label: 'Label'):
+        # Initializing
         if self.label is None:
             self.label = new_label
-            self.update_graphics_item()
-        if self.label.id != new_label.id:
+        # Updating
+        elif self.label.id != new_label.id or self.label.color != new_label.color:
+            # Update the label in user_confidence if it exists
+            if self.user_confidence:
+                old_confidence = next(iter(self.user_confidence.values()))
+                self.user_confidence = {new_label: old_confidence}
+
+            # Update the label in machine_confidence if it exists
+            if self.machine_confidence:
+                new_machine_confidence = {}
+                for label, confidence in self.machine_confidence.items():
+                    if label.id == self.label.id:
+                        new_machine_confidence[new_label] = confidence
+                    else:
+                        new_machine_confidence[label] = confidence
+                self.machine_confidence = new_machine_confidence
+            # Update the label
             self.label = new_label
-            self.update_graphics_item()
+
+        # Always update the graphics item
+        self.update_graphics_item()
 
     def _prepare_data_for_qimage(self, data):
         if data.shape[0] == 3:  # RGB image

coralnet_toolbox/MachineLearning/ExportDataset/QtBase.py

@@ -85,8 +85,7 @@ def setup_info_layout(self):
         layout = QVBoxLayout()
 
         # Create a QLabel with explanatory text and hyperlink
-        info_label = QLabel("Export Patches, Rectangles, and Polygons to create a YOLO-formatted \
-                             Classification, Detection or Segmentation dataset.")
+        info_label = QLabel("Export Patches, Rectangles, and Polygons to create a YOLO-formatted Classification, Detection or Segmentation dataset.")
 
         info_label.setOpenExternalLinks(True)
         info_label.setWordWrap(True)

coralnet_toolbox/QtLabelWindow.py

@@ -405,7 +405,10 @@ def edit_labels(self, old_label, new_label, delete_old=False):
 
         self.update_labels_per_row()
         self.reorganize_labels()
-
+
+        # Refresh the scene with the new label
+        self.annotation_window.set_image(self.annotation_window.current_image_path)
+
     def delete_label(self, label):
         if (label.short_label_code == "Review" and
                 label.long_label_code == "Review" and

coralnet_toolbox/__init__.py

@@ -2,7 +2,7 @@
 
 from coralnet_toolbox.main import run
 
-__version__ = "0.0.13"
+__version__ = "0.0.14"
 __author__ = "Jordan Pierce"
 __email__ = "[email protected]"
 __credits__ = "National Center for Coastal and Ocean Sciences (NCCOS)"

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "coralnet-toolbox"
-version = "0.0.13"
+version = "0.0.14"
 dynamic = [
     "dependencies",
 ]
@@ -48,7 +48,7 @@ universal = true
 
 
 [tool.bumpversion]
-current_version = "0.0.13"
+current_version = "0.0.14"
 commit = true
 tag = true