Implementing 2 stage training

src/gui/tabs/results_tab.py

@@ -117,8 +117,14 @@ class ResultsTab(QWidget):
         self.show_bboxes_checkbox = QCheckBox("Show Bounding Boxes")
         self.show_bboxes_checkbox.setChecked(True)
         self.show_bboxes_checkbox.stateChanged.connect(self._toggle_bboxes)
+        self.show_confidence_checkbox = QCheckBox("Show Confidence")
+        self.show_confidence_checkbox.setChecked(False)
+        self.show_confidence_checkbox.stateChanged.connect(
+            self._apply_detection_overlays
+        )
         toggles_layout.addWidget(self.show_masks_checkbox)
         toggles_layout.addWidget(self.show_bboxes_checkbox)
+        toggles_layout.addWidget(self.show_confidence_checkbox)
         toggles_layout.addStretch()
         preview_layout.addLayout(toggles_layout)
 
@@ -312,7 +318,12 @@ class ResultsTab(QWidget):
                 det.get("y_max"),
             ]
             if all(v is not None for v in bbox):
-                self.preview_canvas.draw_saved_bbox(bbox, color)
+                label = None
+                if self.show_confidence_checkbox.isChecked():
+                    confidence = det.get("confidence")
+                    if confidence is not None:
+                        label = f"{confidence:.2f}"
+                self.preview_canvas.draw_saved_bbox(bbox, color, label=label)
 
     def _convert_mask(self, mask_points: List[List[float]]) -> List[List[float]]:
         """Convert stored [x, y] masks to [y, x] format for the canvas."""