Fix type - update any PIL.Image.Resampling (#20172)

src/transformers/image_transforms.py

@@ -232,7 +232,7 @@ def resize(
             The image to resize.
         size (`Tuple[int, int]`):
             The size to use for resizing the image.
-        resample (`int`, *optional*, defaults to `PIL.Image.Resampling.BILINEAR`):
+        resample (`int`, *optional*, defaults to `PILImageResampling.BILINEAR`):
             The filter to user for resampling.
         data_format (`ChannelDimension`, *optional*):
             The channel dimension format of the output image. If `None`, will use the inferred format from the input.

src/transformers/image_utils.py

@@ -372,7 +372,7 @@ class ImageFeatureExtractionMixin:
                 If `size` is an int and `default_to_square` is `True`, then image will be resized to (size, size). If
                 `size` is an int and `default_to_square` is `False`, then smaller edge of the image will be matched to
                 this number. i.e, if height > width, then image will be rescaled to (size * height / width, size).
-            resample (`int`, *optional*, defaults to `PIL.Image.Resampling.BILINEAR`):
+            resample (`int`, *optional*, defaults to `PILImageResampling.BILINEAR`):
                 The filter to user for resampling.
             default_to_square (`bool`, *optional*, defaults to `True`):
                 How to convert `size` when it is a single int. If set to `True`, the `size` will be converted to a

src/transformers/models/donut/feature_extraction_donut.py

@@ -48,11 +48,10 @@ class DonutFeatureExtractor(FeatureExtractionMixin, ImageFeatureExtractionMixin)
         size (`Tuple(int)`, *optional*, defaults to [1920, 2560]):
             Resize the shorter edge of the input to the minimum value of the given size. Should be a tuple of (width,
             height). Only has an effect if `do_resize` is set to `True`.
-        resample (`int`, *optional*, defaults to `PIL.Image.Resampling.BILINEAR`):
-            An optional resampling filter. This can be one of `PIL.Image.Resampling.NEAREST`,
-            `PIL.Image.Resampling.BOX`, `PIL.Image.Resampling.BILINEAR`, `PIL.Image.Resampling.HAMMING`,
-            `PIL.Image.Resampling.BICUBIC` or `PIL.Image.Resampling.LANCZOS`. Only has an effect if `do_resize` is set
-            to `True`.
+        resample (`int`, *optional*, defaults to `PILImageResampling.BILINEAR`):
+            An optional resampling filter. This can be one of `PILImageResampling.NEAREST`, `PILImageResampling.BOX`,
+            `PILImageResampling.BILINEAR`, `PILImageResampling.HAMMING`, `PILImageResampling.BICUBIC` or
+            `PILImageResampling.LANCZOS`. Only has an effect if `do_resize` is set to `True`.
         do_thumbnail (`bool`, *optional*, defaults to `True`):
             Whether to thumbnail the input to the given `size`.
         do_align_long_axis (`bool`, *optional*, defaults to `False`):

src/transformers/models/glpn/image_processing_glpn.py

@@ -42,7 +42,7 @@ class GLPNImageProcessor(BaseImageProcessor):
         size_divisor (`int`, *optional*, defaults to 32):
             When `do_resize` is `True`, images are resized so their height and width are rounded down to the closest
             multiple of `size_divisor`. Can be overridden by `size_divisor` in `preprocess`.
-        resample (`PIL.Image` resampling filter, *optional*, defaults to `PIL.Image.Resampling.BILINEAR`):
+        resample (`PIL.Image` resampling filter, *optional*, defaults to `PILImageResampling.BILINEAR`):
             Resampling filter to use if resizing the image. Can be overridden by `resample` in `preprocess`.
         do_rescale (`bool`, *optional*, defaults to `True`):
             Whether or not to apply the scaling factor (to make pixel values floats between 0. and 1.). Can be
@@ -80,7 +80,7 @@ class GLPNImageProcessor(BaseImageProcessor):
                 The image is resized so its height and width are rounded down to the closest multiple of
                 `size_divisor`.
             resample:
-                `PIL.Image` resampling filter to use when resizing the image e.g. `PIL.Image.Resampling.BILINEAR`.
+                `PIL.Image` resampling filter to use when resizing the image e.g. `PILImageResampling.BILINEAR`.
             data_format (`ChannelDimension` or `str`, *optional*):
                 The channel dimension format for the output image. If `None`, the channel dimension format of the input
                 image is used. Can be one of:
@@ -142,8 +142,8 @@ class GLPNImageProcessor(BaseImageProcessor):
                 When `do_resize` is `True`, images are resized so their height and width are rounded down to the
                 closest multiple of `size_divisor`.
             resample (`PIL.Image` resampling filter, *optional*, defaults to `self.resample`):
-                `PIL.Image` resampling filter to use if resizing the image e.g. `PIL.Image.Resampling.BILINEAR`. Only
-                has an effect if `do_resize` is set to `True`.
+                `PIL.Image` resampling filter to use if resizing the image e.g. `PILImageResampling.BILINEAR`. Only has
+                an effect if `do_resize` is set to `True`.
             do_rescale (`bool`, *optional*, defaults to `self.do_rescale`):
                 Whether or not to apply the scaling factor (to make pixel values floats between 0. and 1.).
             return_tensors (`str` or `TensorType`, *optional*):

src/transformers/models/maskformer/feature_extraction_maskformer.py

@@ -209,11 +209,10 @@ class MaskFormerFeatureExtractor(FeatureExtractionMixin, ImageFeatureExtractionM
         max_size (`int`, *optional*, defaults to 1333):
             The largest size an image dimension can have (otherwise it's capped). Only has an effect if `do_resize` is
             set to `True`.
-        resample (`int`, *optional*, defaults to `PIL.Image.Resampling.BILINEAR`):
-            An optional resampling filter. This can be one of `PIL.Image.Resampling.NEAREST`,
-            `PIL.Image.Resampling.BOX`, `PIL.Image.Resampling.BILINEAR`, `PIL.Image.Resampling.HAMMING`,
-            `PIL.Image.Resampling.BICUBIC` or `PIL.Image.Resampling.LANCZOS`. Only has an effect if `do_resize` is set
-            to `True`.
+        resample (`int`, *optional*, defaults to `PILImageResampling.BILINEAR`):
+            An optional resampling filter. This can be one of `PILImageResampling.NEAREST`, `PILImageResampling.BOX`,
+            `PILImageResampling.BILINEAR`, `PILImageResampling.HAMMING`, `PILImageResampling.BICUBIC` or
+            `PILImageResampling.LANCZOS`. Only has an effect if `do_resize` is set to `True`.
         size_divisibility (`int`, *optional*, defaults to 32):
             Some backbones need images divisible by a certain number. If not passed, it defaults to the value used in
             Swin Transformer.

src/transformers/models/owlvit/feature_extraction_owlvit.py

@@ -56,11 +56,10 @@ class OwlViTFeatureExtractor(FeatureExtractionMixin, ImageFeatureExtractionMixin
             The size to use for resizing the image. Only has an effect if `do_resize` is set to `True`. If `size` is a
             sequence like (h, w), output size will be matched to this. If `size` is an int, then image will be resized
             to (size, size).
-        resample (`int`, *optional*, defaults to `PIL.Image.Resampling.BICUBIC`):
-            An optional resampling filter. This can be one of `PIL.Image.Resampling.NEAREST`,
-            `PIL.Image.Resampling.BOX`, `PIL.Image.Resampling.BILINEAR`, `PIL.Image.Resampling.HAMMING`,
-            `PIL.Image.Resampling.BICUBIC` or `PIL.Image.Resampling.LANCZOS`. Only has an effect if `do_resize` is set
-            to `True`.
+        resample (`int`, *optional*, defaults to `PILImageResampling.BICUBIC`):
+            An optional resampling filter. This can be one of `PILImageResampling.NEAREST`, `PILImageResampling.BOX`,
+            `PILImageResampling.BILINEAR`, `PILImageResampling.HAMMING`, `PILImageResampling.BICUBIC` or
+            `PILImageResampling.LANCZOS`. Only has an effect if `do_resize` is set to `True`.
         do_center_crop (`bool`, *optional*, defaults to `False`):
             Whether to crop the input at the center. If the input size is smaller than `crop_size` along any edge, the
             image is padded with 0's and then center cropped.

src/transformers/models/segformer/image_processing_segformer.py

@@ -228,7 +228,7 @@ class SegformerImageProcessor(BaseImageProcessor):
         do_rescale: bool,
         do_normalize: bool,
         size: Optional[Dict[str, int]] = None,
-        resample: Optional[PILImageResampling] = None,
+        resample: PILImageResampling = None,
         rescale_factor: Optional[float] = None,
         image_mean: Optional[Union[float, List[float]]] = None,
         image_std: Optional[Union[float, List[float]]] = None,
@@ -325,7 +325,7 @@ class SegformerImageProcessor(BaseImageProcessor):
         segmentation_maps: Optional[ImageInput] = None,
         do_resize: Optional[bool] = None,
         size: Optional[Dict[str, int]] = None,
-        resample: Optional[PILImageResampling] = None,
+        resample: PILImageResampling = None,
         do_rescale: Optional[bool] = None,
         rescale_factor: Optional[float] = None,
         do_normalize: Optional[bool] = None,

tests/models/flava/test_feature_extraction_flava.py

@@ -31,6 +31,7 @@ if is_vision_available():
     import PIL
 
     from transformers import FlavaFeatureExtractor
+    from transformers.image_utils import PILImageResampling
     from transformers.models.flava.image_processing_flava import (
         FLAVA_CODEBOOK_MEAN,
         FLAVA_CODEBOOK_STD,
@@ -89,7 +90,7 @@ class FlavaFeatureExtractionTester(unittest.TestCase):
         self.min_resolution = min_resolution
         self.max_resolution = max_resolution
         self.size = size
-        self.resample = resample if resample is not None else PIL.Image.Resampling.BICUBIC
+        self.resample = resample if resample is not None else PILImageResampling.BICUBIC
         self.do_normalize = do_normalize
         self.image_mean = image_mean
         self.image_std = image_std
@@ -105,7 +106,7 @@ class FlavaFeatureExtractionTester(unittest.TestCase):
 
         self.codebook_do_resize = codebook_do_resize
         self.codebook_size = codebook_size
-        self.codebook_resample = codebook_resample if codebook_resample is not None else PIL.Image.Resampling.LANCZOS
+        self.codebook_resample = codebook_resample if codebook_resample is not None else PILImageResampling.LANCZOS
         self.codebook_do_center_crop = codebook_do_center_crop
         self.codebook_crop_size = codebook_crop_size
         self.codebook_do_map_pixels = codebook_do_map_pixels