Refer to Resampling enum

docs/handbook/concepts.rst

@@ -148,44 +148,44 @@ pixel, the Python Imaging Library provides different resampling *filters*.
 
 .. py:currentmodule:: PIL.Image
 
-.. data:: NEAREST
+.. data:: Resampling.NEAREST
 
     Pick one nearest pixel from the input image. Ignore all other input pixels.
 
-.. data:: BOX
+.. data:: Resampling.BOX
 
     Each pixel of source image contributes to one pixel of the
     destination image with identical weights.
-    For upscaling is equivalent of :data:`NEAREST`.
+    For upscaling is equivalent of :data:`Resampling.NEAREST`.
     This filter can only be used with the :py:meth:`~PIL.Image.Image.resize`
     and :py:meth:`~PIL.Image.Image.thumbnail` methods.
 
     .. versionadded:: 3.4.0
 
-.. data:: BILINEAR
+.. data:: Resampling.BILINEAR
 
     For resize calculate the output pixel value using linear interpolation
     on all pixels that may contribute to the output value.
     For other transformations linear interpolation over a 2x2 environment
     in the input image is used.
 
-.. data:: HAMMING
+.. data:: Resampling.HAMMING
 
-    Produces a sharper image than :data:`BILINEAR`, doesn't have dislocations
-    on local level like with :data:`BOX`.
+    Produces a sharper image than :data:`Resampling.BILINEAR`, doesn't have
+    dislocations on local level like with :data:`Resampling.BOX`.
     This filter can only be used with the :py:meth:`~PIL.Image.Image.resize`
     and :py:meth:`~PIL.Image.Image.thumbnail` methods.
 
     .. versionadded:: 3.4.0
 
-.. data:: BICUBIC
+.. data:: Resampling.BICUBIC
 
     For resize calculate the output pixel value using cubic interpolation
     on all pixels that may contribute to the output value.
     For other transformations cubic interpolation over a 4x4 environment
     in the input image is used.
 
-.. data:: LANCZOS
+.. data:: Resampling.LANCZOS
 
     Calculate the output pixel value using a high-quality Lanczos filter (a
     truncated sinc) on all pixels that may contribute to the output value.