Add log and status widgets

These are useful to give the user feedback as to the processing.  The
'segment everything' process has multiple steps

1.  Generate prompts
2.  Encode prompts and image then decode to get labels.
3.  Add extra properties (like solidity, circularity, hue etc.) to
    labels and generate 3D stacked labels.

We can use the log and status bar to give feedback for each step.

src/napari_segment_everything/segment_everything.py

@@ -33,6 +33,8 @@
     QGroupBox,
     QSizePolicy,
     QMessageBox,
+    QTextBrowser,
+    QProgressBar,
 )
 
 
@@ -310,6 +312,14 @@ def initUI(self):
         self.save_project_button.clicked.connect(self.save_project)
         layout.addWidget(self.save_project_button)
 
+        # add status log and progress
+        self.textBrowser_log = QTextBrowser()
+        self.progressBar = QProgressBar()
+
+        layout.addWidget(self.textBrowser_log)
+        layout.addWidget(self.progressBar)
+
+
         self.setLayout(layout)
 
     def change_slider(self, index):
@@ -367,6 +377,9 @@ def process(self):
         box_nms_thresh = self.box_nms_thresh_spinner.spinner.value()
         crop_n_layers = self.crop_n_layers_spinner.spinner.value()
 
+        # add delimiter to log (TODO consider using ***** for delimiter)
+        self.textBrowser_log.append("")
+
         if model_selection == "vit_b":
             self._predictor = get_sam_automatic_mask_generator(
                 model_selection,
@@ -376,32 +389,42 @@ def process(self):
                 box_nms_thresh=box_nms_thresh,
                 crop_n_layers=crop_n_layers,
             )
+
+            self.textBrowser_log.append("Running SAM automatic mask generator recipe")
+            self.textBrowser_log.append(f"SAM prompt is grid of {points_per_side} by {points_per_side} points")
+            self.progressBar.setValue(30)
 
+            self.textBrowser_log.append("Generating 3D labels with vitb model")
             self.results = self._predictor.generate(self.image)
 
         if model_selection == "mobileSAMv2":
+            self.textBrowser_log.append("Running mobileSAMv2 recipe")
+            self.progressBar.setValue(20)
+            self.textBrowser_log.append("Detecting bounding boxes with YOLO Object Aware Model")
             bounding_boxes = get_bounding_boxes(self.image, imgsz=1024, device='cuda')
+            self.textBrowser_log.append(f"SAM prompt is {len(bounding_boxes)} bounding boxes")
+            self.progressBar.setValue(40)
+            self.textBrowser_log.append("Generating 3D labels with efficientvit_l2 model")
             self.results = get_mobileSAMv2(self.image, bounding_boxes)
             for result, bbox in zip(self.results, bounding_boxes):
                 result["prompt_bbox"] = bbox
         self.results = sorted(
             self.results, key=lambda x: x["area"], reverse=False
         )
 
-        print(len(self.results), "objects found")
+        self.textBrowser_log.append(str(len(self.results))+" objects found")
+        self.progressBar.setValue(60)
 
         label_num = 1
         for result in self.results:
             result["keep"] = True
             result["label_num"] = label_num
             label_num += 1
-
-        add_properties_to_label_image(self.image, self.results)
-
+        
+        self.textBrowser_log.append("Adding properties to label image")
+        add_properties_to_label_image(self.image, self.results)        
         label_image = make_label_image_3d(self.results)
 
-        print(label_image.shape)
-
         self.add_points()
         self.add_boxes()
 
@@ -410,6 +433,9 @@ def process(self):
         self.viewer.dims.ndisplay = 3
         self._3D_labels_layer.translate = (-len(self.results), 0, 0)
 
+        self.textBrowser_log.append("Finished generating 3D labels")
+        self.progressBar.setValue(100)
+
     def update_slider_min_max(self):
 
         stats = [