KNN on water_mask

app.py

@@ -479,7 +479,7 @@ def _pipeline(uid,img_path):
         x1, y1, x2, y2 = map(int, [x1, y1, x2, y2])
         x1 = max(0, min(x1, 639)); y1 = max(0, min(y1, 639))
         x2 = max(0, min(x2, 639)); y2 = max(0, min(y2, 639))
-        box_mask = movable_mask[y1:y2, x1:x2]              # ← use MOVABLE mask
+        box_mask = movable_mask[y1:y2, x1:x2]              # ← switch to movable_mask
         if box_mask.size == 0:
             continue
         if np.count_nonzero(box_mask) / box_mask.size >= 0.2:
@@ -493,7 +493,7 @@ def _pipeline(uid,img_path):
         print(f"🧠 {len(centres)} garbage objects on water selected from {len(detections)} detections")
 
     # 3- Robot initialization, position and navigation
-    # find all (y,x) within movable_mask
+    # find all (y,x) within water-zone
     ys, xs = np.where(water_mask)
     if len(ys)==0:
         # no travelable zone → bail out
@@ -509,7 +509,7 @@ def _pipeline(uid,img_path):
     robot = Robot(SPRITE)
     # Robot will be spawn on the closest movable mask to top-left
     robot.pos = [spawn_x, spawn_y]
-    path  = knn_path(robot.pos, centres, movable_mask)
+    path  = knn_path(robot.pos, centres, water_mask)
 
     # 4- Video synthesis
     out_tmp=f"{OUTPUT_DIR}/{uid}_tmp.mp4"