Dev

README.md

@@ -66,6 +66,63 @@ The `toolbox` also uses the following to create rectangle and polygon annotation
 
 ## Tools
 
+<div align="center">
+  <table>
+    <tr>
+      <td align="center">
+        <img src="https://raw.githubusercontent.com/Jordan-Pierce/CoralNet-Toolbox/refs/heads/main/figures/tools/Patches.gif" height="200"/>
+        <br>
+        <em>Patch Annotation Tool</em>
+      </td>
+      <td align="center">
+        <img src="https://raw.githubusercontent.com/Jordan-Pierce/CoralNet-Toolbox/refs/heads/main/figures/tools/Rectangles.gif" height="200"/>
+        <br>
+        <em>Rectangle Annotation Tool</em>
+      </td>
+      <td align="center">
+        <img src="https://raw.githubusercontent.com/Jordan-Pierce/CoralNet-Toolbox/refs/heads/main/figures/tools/Polygons.gif" height="200"/>
+        <br>
+        <em>Polygon Annotation Tool</em>
+      </td>
+    </tr>
+    <tr>
+      <td align="center">
+        <img src="https://raw.githubusercontent.com/Jordan-Pierce/CoralNet-Toolbox/refs/heads/main/figures/tools/Classification.gif" height="200"/>
+        <br>
+        <em>Patch-based Image Classification</em>
+      </td>
+      <td align="center">
+        <img src="https://raw.githubusercontent.com/Jordan-Pierce/CoralNet-Toolbox/refs/heads/main/figures/tools/Object_Detection.gif" height="200"/>
+        <br>
+        <em>Object Detection</em>
+      </td>
+      <td align="center">
+        <img src="https://raw.githubusercontent.com/Jordan-Pierce/CoralNet-Toolbox/refs/heads/main/figures/tools/Instance_Segmentation.gif" height="200"/>
+        <br>
+        <em>Instance Segmentation</em>
+      </td>
+    </tr>
+    <tr>
+      <td align="center">
+        <img src="https://raw.githubusercontent.com/Jordan-Pierce/CoralNet-Toolbox/refs/heads/main/figures/tools/Segment_Anything.gif" height="200"/>
+        <br>
+        <em>Segment Anything Model (SAM)</em>
+      </td>
+      <td align="center">
+        <img src="https://raw.githubusercontent.com/Jordan-Pierce/CoralNet-Toolbox/refs/heads/main/figures/tools/Classifying_Polygons.gif" height="200"/>
+        <br>
+        <em>Polygon Classification</em>
+      </td>
+      <td align="center">
+        <img src="https://raw.githubusercontent.com/Jordan-Pierce/CoralNet-Toolbox/refs/heads/main/figures/tools/Classifying_Orthomosaics.gif" height="200"/>
+        <br>
+        <em>Orthomosaic Patch-based Image Classification</em>
+      </td>
+    </tr>
+  </table>
+</div>
+
+
 Enhance your CoralNet experience with these tools:
 - ✏️ Annotate: Create annotations freely
 - 👁️ Visualize: See CoralNet and CPCe annotations superimposed on images

coralnet_toolbox/Annotations/QtPolygonAnnotation.py

@@ -1,5 +1,6 @@
 import warnings
 
+import cv2
 import math
 import numpy as np
 
@@ -202,6 +203,15 @@ def create_cropped_image(self, rasterio_src):
 
         # Read the data from rasterio
         data = rasterio_src.read(window=window)
+
+        # Create mask from polygon
+        polygon_points = np.array([(p.x() - min_x, p.y() - min_y) for p in self.points])
+        mask = np.zeros((window.height, window.width), dtype=np.uint8)
+        cv2.fillPoly(mask, [polygon_points.astype(np.int32)], 1)
+
+        # Apply mask to each channel
+        for i in range(data.shape[0]):
+            data[i] = data[i] * mask
 
         # Ensure the data is in the correct format for QImage
         data = self._prepare_data_for_qimage(data)

coralnet_toolbox/IO/QtExportTagLabAnnotations.py

@@ -69,9 +69,8 @@ def export_annotations(self):
                 taglab_data = {
                     "filename": file_path,
                     "working_area": None,
-                    "dictionary_name": "scripps",
-                    "dictionary_description": "These color codes are the ones typically used by the "
-                                              "Scripps Institution of Oceanography (UCSD)",
+                    "dictionary_name": "custom_dictionary",
+                    "dictionary_description": "These annotations were exported from CoralNet-Toolbox.",
                     "labels": {},
                     "images": []
                 }
@@ -127,18 +126,20 @@ def export_annotations(self):
                     if isinstance(annotation, PolygonAnnotation):
                         # Calculate bounding box, centroid, area, perimeter, and contour
                         points = annotation.points
-                        min_x = min(point.x() for point in points)
-                        min_y = min(point.y() for point in points)
-                        max_x = max(point.x() for point in points)
-                        max_y = max(point.y() for point in points)
-                        centroid_x = sum(point.x() for point in points) / len(points)
-                        centroid_y = sum(point.y() for point in points) / len(points)
-                        area = annotation.calculate_area()
-                        perimeter = annotation.calculate_perimeter()
+                        min_x = int(min(point.x() for point in points))
+                        min_y = int(min(point.y() for point in points))
+                        max_x = int(max(point.x() for point in points))
+                        max_y = int(max(point.y() for point in points))
+                        width = max_x - min_x
+                        height = max_y - min_y
+                        centroid_x = float(f"{sum(point.x() for point in points) / len(points):.1f}")
+                        centroid_y = float(f"{sum(point.y() for point in points) / len(points):.1f}")
+                        area = float(f"{annotation.calculate_area():.1f}")
+                        perimeter = float(f"{annotation.calculate_perimeter():.1f}")
                         contour = self.taglabToPoints(np.array([[point.x(), point.y()] for point in points]))
 
                         annotation_dict = {
-                            "bbox": [min_x, min_y, max_x, max_y],
+                            "bbox": [min_y, min_x, width, height],
                             "centroid": [centroid_x, centroid_y],
                             "area": area,
                             "perimeter": perimeter,

coralnet_toolbox/IO/QtExportTagLabLabels.py

@@ -0,0 +1,75 @@
+import warnings
+warnings.filterwarnings("ignore", category=DeprecationWarning)
+
+import json
+
+from PyQt5.QtCore import Qt
+from PyQt5.QtWidgets import QFileDialog, QMessageBox, QApplication
+
+from coralnet_toolbox.QtProgressBar import ProgressBar
+
+
+# ----------------------------------------------------------------------------------------------------------------------
+# Classes
+# ----------------------------------------------------------------------------------------------------------------------
+
+
+class ExportTagLabLabels:
+    def __init__(self, main_window):
+        self.main_window = main_window
+        self.label_window = main_window.label_window
+
+    def export_taglab_labels(self):
+        self.main_window.untoggle_all_tools()
+
+        options = QFileDialog.Options() 
+        file_path, _ = QFileDialog.getSaveFileName(self.label_window,
+                                                   "Export TagLab Labels",
+                                                   "",
+                                                   "JSON Files (*.json);;All Files (*)",
+                                                   options=options)
+        if file_path:
+            # Make cursor busy
+            QApplication.setOverrideCursor(Qt.WaitCursor)
+            total_labels = len(self.label_window.labels)
+            progress_bar = ProgressBar(self.label_window, "Exporting TagLab Labels")
+            progress_bar.show()
+            progress_bar.start_progress(total_labels)
+
+            try:
+                # Convert labels to list format
+                labels_list = []
+                for label in self.label_window.labels:
+                    label_entry = {
+                        'id': f"{label.short_label_code}",
+                        'name': f"{label.short_label_code}",
+                        'description': None,
+                        'fill': label.color.getRgb()[:3],
+                        'border': [200, 200, 200],
+                        'visible': True
+                    }
+                    labels_list.append(label_entry)
+                    progress_bar.update_progress()
+
+                taglab_data = {
+                    'Name': 'custom_dictionary',
+                    'Description': 'This label dictionary was exported from CoralNet-Toolbox.',
+                    'Labels': labels_list
+                }
+
+                with open(file_path, 'w') as file:
+                    json.dump(taglab_data, file, indent=4)
+
+                QMessageBox.information(self.label_window,
+                                        "Labels Exported", 
+                                        "TagLab labels have been successfully exported.")
+
+            except Exception as e:
+                QMessageBox.warning(self.label_window,
+                                    "Error Exporting Labels",
+                                    f"An error occurred while exporting TagLab labels: {str(e)}")
+
+            finally:
+                QApplication.restoreOverrideCursor()
+                progress_bar.stop_progress()
+                progress_bar.close()

coralnet_toolbox/IO/__init__.py

@@ -6,6 +6,7 @@
 from .QtImportViscoreAnnotations import ImportViscoreAnnotations
 from .QtImportTagLabAnnotations import ImportTagLabAnnotations
 from .QtExportLabels import ExportLabels
+from .QtExportTagLabLabels import ExportTagLabLabels
 from .QtExportAnnotations import ExportAnnotations
 from .QtExportCoralNetAnnotations import ExportCoralNetAnnotations
 from .QtExportViscoreAnnotations import ExportViscoreAnnotations
@@ -20,6 +21,7 @@
     'ImportViscoreAnnotations',
     'ImportTagLabAnnotations',
     'ExportLabels',
+    'ExportTagLabLabels',
     'ExportAnnotations',
     'ExportCoralNetAnnotations', 
     'ExportViscoreAnnotations',

coralnet_toolbox/QtAnnotationWindow.py

@@ -634,20 +634,36 @@ def delete_label_annotations(self, label):
                 del self.annotations_dict[annotation.id]
 
     def delete_image_annotations(self, image_path):
-        annotations = self.get_image_annotations(image_path)
-        self.delete_annotations(annotations)
+        """Efficiently delete all annotations for a given image path"""
+        # Get IDs of annotations to delete
+        annotation_ids = [
+            annotation_id for annotation_id, annotation in self.annotations_dict.items()
+            if annotation.image_path == image_path
+        ]
+
+        # Delete graphics items and annotations in batch
+        for annotation_id in annotation_ids:
+            annotation = self.annotations_dict[annotation_id]
+            annotation.delete()  # Remove graphics item
+            del self.annotations_dict[annotation_id]  # Remove from dictionary
+            self.annotationDeleted.emit(annotation_id)  # Emit signal
+
+        # Clear confidence window if needed
+        if self.current_image_path == image_path:
+            self.main_window.confidence_window.clear_display()
 
     def delete_image(self, image_path):
         # Delete all annotations associated with image path
         self.delete_annotations(self.get_image_annotations(image_path))
         # Delete the image
         if self.current_image_path == image_path:
             self.scene.clear()
+            self.main_window.confidence_window.clear_display()
             self.current_image_path = None
             self.image_pixmap = None
             self.rasterio_image = None
-            self.active_image = False  # Reset image_set flag
-
+            self.active_image = False 
+            
     def clear_scene(self):
         # Clean up
         self.unselect_annotations()

coralnet_toolbox/QtEventFilter.py

@@ -24,6 +24,8 @@ def __init__(self, main_window):
         self.segment_deploy_model_dialog = main_window.segment_deploy_model_dialog
         self.sam_deploy_generator_dialog = main_window.sam_deploy_generator_dialog
         self.auto_distill_deploy_model_dialog = main_window.auto_distill_deploy_model_dialog
+
+        self.tile_inference_dialog = main_window.tile_inference_dialog
 
     def eventFilter(self, obj, event):
         if event.type() == QEvent.KeyPress:
@@ -33,7 +35,13 @@ def eventFilter(self, obj, event):
                 if event.key() in [Qt.Key_W, Qt.Key_A, Qt.Key_S, Qt.Key_D]:
                     self.label_window.handle_wasd_key(event.key())
                     return True
-
+
+                # Handle G key for displaying existing tile inference parameters
+                if event.key() == Qt.Key_G:
+                    if self.main_window.tile_inference_tool_action.isChecked():
+                        self.tile_inference_dialog.update_tile_graphics()
+                    return True
+
                 # Handle hotkey for image classification prediction
                 if event.key() == Qt.Key_1:
                     self.classify_deploy_model_dialog.predict()
@@ -89,6 +97,14 @@ def eventFilter(self, obj, event):
             if event.key() == Qt.Key_Escape:
                 self.show_exit_confirmation_dialog()
                 return True
+
+        # Handle key release events 
+        elif event.type() == QEvent.KeyRelease:
+
+            # Handle G key for removing existing tile inference parameter
+            if event.key() == Qt.Key_G:
+                self.tile_inference_dialog.clear_tile_graphics()
+                return True
 
         # Return False for other events to allow them to be processed by the target object
         return False