Simplifying

- avoid using classmethod if the class argument is not used, use staticmethod instead
- avoid testing for is_mask three times if one is enough

Former-commit-id: 1116e3096cd5210a0596d1f3938989016e0f3b6c

utils/data_loading.py

@@ -25,26 +25,26 @@ class BasicDataset(Dataset):
     def __len__(self):
         return len(self.ids)
 
-    @classmethod
-    def preprocess(cls, pil_img, scale, is_mask):
+    @staticmethod
+    def preprocess(pil_img, scale, is_mask):
         w, h = pil_img.size
         newW, newH = int(scale * w), int(scale * h)
         assert newW > 0 and newH > 0, 'Scale is too small, resized images would have no pixel'
         pil_img = pil_img.resize((newW, newH), resample=Image.NEAREST if is_mask else Image.BICUBIC)
         img_ndarray = np.asarray(pil_img)
 
-        if img_ndarray.ndim == 2 and not is_mask:
-            img_ndarray = img_ndarray[np.newaxis, ...]
-        elif not is_mask:
-            img_ndarray = img_ndarray.transpose((2, 0, 1))
-
         if not is_mask:
+            if img_ndarray.ndim == 2:
+                img_ndarray = img_ndarray[np.newaxis, ...]
+            else:
+                img_ndarray = img_ndarray.transpose((2, 0, 1))
+
             img_ndarray = img_ndarray / 255
 
         return img_ndarray
 
-    @classmethod
-    def load(cls, filename):
+    @staticmethod
+    def load(filename):
         ext = splitext(filename)[1]
         if ext in ['.npz', '.npy']:
             return Image.fromarray(np.load(filename))