Update utils_mask.py

utils_mask.py

@@ -78,27 +78,31 @@ def get_mask_location(model_type, category, model_parse: Image.Image, keypoint:
     arms_right = (parse_array == label_map["right_arm"]).astype(np.float32)
 
     if category == 'dresses':
-        # Upper body mask
-        parse_mask_upper = (parse_array == 4).astype(np.float32) + (parse_array == 7).astype(np.float32)
-    
-        # Lower body masks
-        parse_mask_fixed_lower_cloth = (parse_array == label_map["skirt"]).astype(np.float32) + \
-                                       (parse_array == label_map["pants"]).astype(np.float32)
+        # Combine upper body category logic
+        parse_mask_upper = (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)) 
+        
+        # Combine lower body category logic
         parse_mask_legs = (parse_array == 6).astype(np.float32) + \
                           (parse_array == 12).astype(np.float32) + \
                           (parse_array == 13).astype(np.float32) + \
-                          (parse_array == 5).astype(np.float32)
-        parse_mask_legs_dilated = cv2.dilate(parse_mask_legs.astype(np.uint8), np.ones((6, 6), np.uint8), iterations=6) # Dilate legs
-    
-        # Fixed and changeable masks
-        parser_mask_fixed = (parse_array == label_map["upper_clothes"]).astype(np.float32) + \
-                            (parse_array == label_map["left_arm"]).astype(np.float32) + \
-                            (parse_array == label_map["right_arm"]).astype(np.float32) + \
-                            parse_mask_fixed_lower_cloth  # Add lower cloth to fixed mask
-        parser_mask_changeable = np.logical_and(parse_array, np.logical_not(parser_mask_fixed))
+                          (parse_array == 5).astype(np.float32) 
+        parser_mask_fixed += (parse_array == label_map["upper_clothes"]).astype(np.float32) + \
+                             (parse_array == label_map["left_arm"]).astype(np.float32) + \
+                             (parse_array == label_map["right_arm"]).astype(np.float32) 
+        
+        # Include parse_mask_legs in parser_mask_changeable
+        parser_mask_changeable = np.logical_or(parser_mask_changeable, parse_mask_legs)
+        
+        parse_mask_legs = cv2.dilate(parse_mask_legs.astype(np.uint8), np.ones((6, 6), np.uint8), iterations=6)
     
-        # Combine masks (upper body + dilated legs + changeable areas)
-        parse_mask = np.maximum.reduce([parse_mask_upper, parse_mask_legs_dilated, parser_mask_changeable.astype(np.float32)])  
+        # Combine the upper body mask with the leg mask
+        parse_mask = np.logical_and(parser_mask_changeable, np.logical_not(parse_mask))
+
+  
 
 
     elif category == 'upper_body':