debugging

SPIDER.py

@@ -76,13 +76,31 @@ def standardize_3D_image(
     if image.shape[0] < image.shape[2]:
         image = np.transpose(image, axes=[1, 2, 0])
     # Resize image
-    order = 0 if nearest_neighbor_interpolation else 1
-    image = skimage.transform.resize(image, resize_shape, order=order)
+    image = skimage.transform.resize(image, resize_shape)
     # Rescale to UInt8 type (required for PyArrow and PIL)
     image = skimage.img_as_ubyte(image)
     return image
 
-
+def standardize_3D_mask(
+    mask: np.ndarray,
+    resize_shape: Tuple[int, int, int],
+) -> np.ndarray:
+    """Aligns dimensions of image to be (height, width, channels); resizes
+    images to values specified in resize_shape using nearest neighbor interpolation; 
+    and rescales pixel values to Uint8."""
+    # Align height, width, channel dims
+    if mask.shape[0] < mask.shape[2]:
+        mask = np.transpose(mask, axes=[1, 2, 0])
+    # Resize mask
+    mask = skimage.transform.resize(
+        mask,
+        resize_shape,
+        order=0,
+        preserve_range=True,
+    )
+    # Rescale to UInt8 type (required for PyArrow and PIL)
+    mask = skimage.img_as_ubyte(mask)
+    return mask
 
 # Define constants
 MIN_IVD = 0
@@ -512,10 +530,9 @@ class SPIDER(datasets.GeneratorBasedBuilder):
             mask_array_standardized = np.array(mask_array_original, dtype='uint8')
 
             # Convert .mha mask to standardized numeric array
-            mask_array_standardized = standardize_3D_image(
+            mask_array_standardized = standardize_3D_mask(
                 mask_array_standardized,
                 resize_shape,
-                nearest_neighbor_interpolation=True,
             )
 
             # Extract overview data corresponding to image