Update utils_mask.py

utils_mask.py

@@ -83,30 +83,20 @@ def get_mask_location(model_type, category, model_parse: Image.Image, keypoint:
                            (parse_array == 12).astype(np.float32) + \
                            (parse_array == 13).astype(np.float32) + \
                            (parse_array == 5).astype(np.float32)
-        parser_mask_fixed_lower_cloth = (parse_array == label_map["skirt"]).astype(np.float32) + \
-                                        (parse_array == label_map["pants"]).astype(np.float32)
-        parser_mask_fixed += parser_mask_fixed_lower_cloth
 
-        parse_mask = np.logical_or(parse_mask_upper, parse_mask_lower)
-
-        # Dilate the leg mask to ensure coverage and fill gaps
-        parse_mask_legs = np.logical_or.reduce((parse_array == label_map["left_leg"],
-                                                parse_array == label_map["right_leg"],
-                                                parse_array == label_map["skirt"],
-                                                parse_array == label_map["pants"])).astype(np.float32)
+        # Fill only the gaps between the legs
+        parse_mask_legs = (parse_array == label_map["left_leg"]).astype(np.float32) + \
+                          (parse_array == label_map["right_leg"]).astype(np.float32)
         parse_mask_legs_dilated = cv2.dilate(parse_mask_legs.astype(np.uint8), np.ones((5, 5), np.uint8), iterations=6)
         parse_mask_lower = np.maximum(parse_mask_lower, parse_mask_legs_dilated)
 
-        # Only fill the gaps between the legs
+        # Close the gap between the legs
         fill_gap_between_legs = cv2.morphologyEx(parse_mask_lower.astype(np.uint8), cv2.MORPH_CLOSE, np.ones((15, 15), np.uint8))
 
         parse_mask = np.logical_or(parse_mask_upper, fill_gap_between_legs)
 
     elif category == 'upper_body':
         parse_mask = (parse_array == 4).astype(np.float32) + (parse_array == 7).astype(np.float32)
-        parser_mask_fixed_lower_cloth = (parse_array == label_map["skirt"]).astype(np.float32) + \
-                                        (parse_array == label_map["pants"]).astype(np.float32)
-        parser_mask_fixed += parser_mask_fixed_lower_cloth
         parser_mask_changeable += np.logical_and(parse_array, np.logical_not(parser_mask_fixed))
     elif category == 'lower_body':
         parse_mask = (parse_array == 6).astype(np.float32) + \