gr.Checkbox(label="Include Bounding Boxes", value=True)],

app.py

@@ -55,13 +55,9 @@ def annotate(image: Union[Image.Image, np.ndarray], detection_results: List[Dete
         score = detection.score
         box = detection.box
         mask = detection.mask
-        color = (255, 255, 255)  # White color for bounding boxes and text
-
-        # Draw the filled rectangle (white filling)
-        cv2.rectangle(image_cv2, (box.xmin, box.ymin), (box.xmax, box.ymax), color, -1)  # Filled white rectangle
-        # Draw the border
-        cv2.rectangle(image_cv2, (box.xmin, box.ymin), (box.xmax, box.ymax), color, 2)  # Border
+        color = np.random.randint(0, 256, size=3).tolist()
 
+        cv2.rectangle(image_cv2, (box.xmin, box.ymin), (box.xmax, box.ymax), color, 2)
         cv2.putText(image_cv2, f'{label}: {score:.2f}', (box.xmin, box.ymin - 10),
                     cv2.FONT_HERSHEY_SIMPLEX, 0.5, color, 2)
 
@@ -197,9 +193,12 @@ def detections_to_json(detections):
         detections_list.append(detection_dict)
     return detections_list
 
-def process_image(image, include_json):
+def process_image(image, include_json, include_bboxes):
     labels = ["insect"]
     original_image, detections = grounded_segmentation(image, labels, threshold=0.3, polygon_refinement=True)
+    if not include_bboxes:
+        for detection in detections:
+            detection.box = None
     yellow_background_with_insects = create_yellow_background_with_insects(np.array(original_image), detections)
     if include_json:
         detections_json = detections_to_json(detections)
@@ -216,7 +215,7 @@ examples = [
 
 gr.Interface(
     fn=process_image,
-    inputs=[gr.Image(type="pil"), gr.Checkbox(label="Include JSON", value=False)],
+    inputs=[gr.Image(type="pil"), gr.Checkbox(label="Include JSON", value=False), gr.Checkbox(label="Include Bounding Boxes", value=True)],
     outputs=[gr.Image(type="numpy"), gr.Textbox()],
     title="InsectSAM 🐞",
     examples=examples