Update utils_mask.py

utils_mask.py

@@ -85,10 +85,10 @@ def get_mask_location(model_type, category, model_parse: Image.Image, keypoint:
         parser_mask_fixed += parser_mask_fixed_lower_cloth
 
         # Create a mask for the legs (including skirts and pants)
-        parse_mask_legs = (parse_array == label_map["skirt"]).astype(np.float32) + \
-                          (parse_array == label_map["pants"]).astype(np.float32) + \
-                          (parse_array == label_map["left_leg"]).astype(np.float32) + \
-                          (parse_array == label_map["right_leg"]).astype(np.float32)
+        parse_mask_legs = np.logical_or.reduce((parse_array == label_map["skirt"],
+                                                parse_array == label_map["pants"],
+                                                parse_array == label_map["left_leg"],
+                                                parse_array == label_map["right_leg"])).astype(np.float32)
 
         # Dilate the leg mask to ensure coverage and fill gaps
         parse_mask_legs = cv2.dilate(parse_mask_legs.astype(np.uint8), np.ones((6, 6), np.uint8), iterations=6)
@@ -101,7 +101,6 @@ def get_mask_location(model_type, category, model_parse: Image.Image, keypoint:
         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) + \
                      (parse_array == 12).astype(np.float32) + \
@@ -110,7 +109,6 @@ def get_mask_location(model_type, category, model_parse: Image.Image, keypoint:
         parser_mask_fixed += (parse_array == label_map["upper_clothes"]).astype(np.float32) + \
                              (parse_array == 14).astype(np.float32) + \
                              (parse_array == 15).astype(np.float32)
-        parser_mask_changeable += np.logical_and(parse_array, np.logical_not(parser_mask_fixed))
     else:
         raise NotImplementedError
 
@@ -154,13 +152,13 @@ def get_mask_location(model_type, category, model_parse: Image.Image, keypoint:
         parser_mask_fixed += hands_left + hands_right
 
     parser_mask_fixed = np.logical_or(parser_mask_fixed, parse_head)
-    parse_mask = cv2.dilate(parse_mask, np.ones((5, 5), np.uint16), iterations=5)
+    parse_mask = cv2.dilate(parse_mask.astype(np.uint8), np.ones((5, 5), np.uint8), iterations=5)
     if category == 'dresses' or category == 'upper_body':
         neck_mask = (parse_array == 18).astype(np.float32)
-        neck_mask = cv2.dilate(neck_mask, np.ones((5, 5), np.uint16), iterations=1)
+        neck_mask = cv2.dilate(neck_mask.astype(np.uint8), np.ones((5, 5), np.uint8), iterations=1)
         neck_mask = np.logical_and(neck_mask, np.logical_not(parse_head))
         parse_mask = np.logical_or(parse_mask, neck_mask)
-        arm_mask = cv2.dilate(np.logical_or(im_arms_left, im_arms_right).astype('float32'), np.ones((5, 5), np.uint16), iterations=4)
+        arm_mask = cv2.dilate(np.logical_or(im_arms_left, im_arms_right).astype('float32'), np.ones((5, 5), np.uint8), iterations=4)
         parse_mask += np.logical_or(parse_mask, arm_mask)
 
     parse_mask = np.logical_and(parser_mask_changeable, np.logical_not(parse_mask))