Update utils_mask.py

utils_mask.py

@@ -24,11 +24,11 @@ label_map = {
 }
 
 def extend_arm_mask(wrist, elbow, scale):
-    wrist = elbow + scale * (wrist - elbow)
-    return wrist
+  wrist = elbow + scale * (wrist - elbow)
+  return wrist
 
 def hole_fill(img):
-    img = np.pad(img[1:-1, 1:-1], pad_width=1, mode='constant', constant_values=0)
+    img = np.pad(img[1:-1, 1:-1], pad_width = 1, mode = 'constant', constant_values=0)
     img_copy = img.copy()
     mask = np.zeros((img.shape[0] + 2, img.shape[1] + 2), dtype=np.uint8)
 
@@ -51,7 +51,7 @@ def refine_mask(mask):
 
     return refine_mask
 
-def get_mask_location(model_type, category, model_parse: Image.Image, keypoint: dict, width=384, height=512):
+def get_mask_location(model_type, category, model_parse: Image.Image, keypoint: dict, width=384,height=512):
     im_parse = model_parse.resize((width, height), Image.NEAREST)
     parse_array = np.array(im_parse)
 
@@ -85,27 +85,21 @@ def get_mask_location(model_type, category, model_parse: Image.Image, keypoint:
 
         parser_mask_changeable += np.logical_and(parse_array, np.logical_not(parser_mask_fixed))
 
-    
-    elif category == 'lower_body' or category == 'full_body':
-        if category == 'lower_body':
-        # For lower body category, include only lower body parts of the garment
-            parse_mask = (parse_array == 5).astype(np.float32) + \
-                     (parse_array == 6).astype(np.float32)
-        else:
-        # For full body category, include all garment parts
-            parse_mask = (parse_array == 4).astype(np.float32) + \
-                     (parse_array == 5).astype(np.float32) + \
-                     (parse_array == 6).astype(np.float32)
-
-            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))
-
-        # Fill gaps in legs
-        leg_mask = cv2.dilate(parse_mask.astype(np.uint8), np.ones((5, 5), np.uint8), iterations=5)
-        parse_mask += leg_mask
-
+    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) + \
+                     (parse_array == 12).astype(np.float32) + \
+                     (parse_array == 13).astype(np.float32) + \
+                     (parse_array == 5).astype(np.float32)
+        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
 
@@ -170,4 +164,4 @@ def get_mask_location(model_type, category, model_parse: Image.Image, keypoint:
     mask = Image.fromarray(inpaint_mask.astype(np.uint8) * 255)
     mask_gray = Image.fromarray(inpaint_mask.astype(np.uint8) * 127)
 
-    return mask, mask_gray
+    return mask, mask_gray