Highlight chunk in red mask not dot

app.py

@@ -116,6 +116,15 @@ def build_masks(seg):
     movable_mask = water_mask | garbage_mask
     return water_mask, garbage_mask, movable_mask
 
+# Garbage mask can be highlighted in red
+def highlight_chunk_masks_on_frame(frame, labels, num_cc, color=(128, 0, 0)):
+    """Draw filled red areas over the garbage chunk regions"""
+    for lab in range(1, num_cc):
+        mask = (labels == lab).astype(np.uint8)
+        contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+        cv2.drawContours(frame, contours, -1, color, thickness=cv2.FILLED)
+    return frame
+
 # ── A* and KNN over binary water grid ─────────────────────────────────
 def astar(start, goal, occ):
     h   = lambda a,b: abs(a[0]-b[0])+abs(a[1]-b[1])
@@ -386,7 +395,7 @@ def _pipeline(uid,img_path):
     centres = []
     for x1, y1, x2, y2 in detections: # Define IoU heuristic
         '''
-        We conduct a 30% allowance whether the center 
+        We conduct a 20% allowance whether the center 
         of the detected garbage's bbox lies within the travelable zone
         which was segmented earlier to be the water and garbage zone
         '''
@@ -396,7 +405,7 @@ def _pipeline(uid,img_path):
         box_mask = movable_mask[y1:y2, x1:x2]              # ← use MOVABLE mask
         if box_mask.size == 0:
             continue
-        if np.count_nonzero(box_mask) / box_mask.size >= 0.3:
+        if np.count_nonzero(box_mask) / box_mask.size >= 0.2:
             centres.append([int((x1 + x2) / 2), int((y1 + y2) / 2)])
     # add chunk centres and deduplicate
     centres.extend(chunk_centres)
@@ -417,10 +426,13 @@ def _pipeline(uid,img_path):
     bg = bgr.copy()
     for _ in range(15000): # safety frames
         frame=bg.copy()
-        # draw garbage
+        # Draw garbage chunk masks in red
+        frame = highlight_chunk_masks_on_frame(frame, labels, num_cc, color=(0, 0, 255))
+        # Draw object detections as red (to green) dots
         for o in objs:
-            color=(0,0,255) if not o["col"] else (0,255,0)
-            x,y=o["pos"]; cv2.circle(frame,(x,y),6,color,-1)
+            color = (0, 0, 255) if not o["col"] else (0, 255, 0)
+            x, y = o["pos"]
+            cv2.circle(frame, (x, y), 6, color, -1)
         # robot
         robot.step(path)
         rx,ry=robot.pos; sp=robot.png