UPDATE

sorghum_pipeline/features/morphology.py

@@ -79,8 +79,8 @@ class MorphologyExtractor:
             else:
                 features['traits']['plant_height_cm'] = 0.0
 
-            # YOLO tips overlay (optional)
-            yolo_img, tips = self._detect_yolo_tips(rgb, clean_mask)
+            # YOLO tips overlay (optional) — use the original mask (same as frontend)
+            yolo_img, tips = self._detect_yolo_tips(rgb, mask)
             if yolo_img is not None:
                 features['images']['yolo_tips'] = yolo_img
             features['traits']['num_yolo_tips'] = int(len(tips) if tips is not None else 0)
@@ -170,11 +170,24 @@ class MorphologyExtractor:
         return vis
     
     def _create_white_background_overlay(self, rgb: np.ndarray, mask: np.ndarray) -> np.ndarray:
-        """Return white background with plant pixels in original colors."""
+        """Return white background with plant pixels in original colors.
+        The mask here is normalized to a single-channel binary mask so it matches the frontend mask behavior.
+        """
         img_no_bg = rgb.copy()
-        img_no_bg[mask == 0] = 0
+        # Normalize mask to single-channel binary
+        if mask is None:
+            bin_mask = None
+        else:
+            m = mask
+            if m.ndim == 3:
+                m = cv2.cvtColor(m, cv2.COLOR_BGR2GRAY)
+            m = m.astype(np.uint8)
+            _, bin_mask = cv2.threshold(m, 0, 255, cv2.THRESH_BINARY)
+        if bin_mask is None:
+            return np.full_like(rgb, 255, dtype=np.uint8)
+        img_no_bg[bin_mask == 0] = 0
         overlay = np.full_like(rgb, 255, dtype=np.uint8)
-        overlay[mask > 0] = img_no_bg[mask > 0]
+        overlay[bin_mask > 0] = img_no_bg[bin_mask > 0]
         return overlay
     
     def _detect_yolo_tips(self, rgb: np.ndarray, mask: np.ndarray):