diff --git a/paddlenlp/transformers/clip/feature_extraction.py b/paddlenlp/transformers/clip/feature_extraction.py
index d1c9e68646ea..27544cc8e13c 100644
--- a/paddlenlp/transformers/clip/feature_extraction.py
+++ b/paddlenlp/transformers/clip/feature_extraction.py
@@ -19,7 +19,7 @@
 import paddle
 import numpy as np
 from PIL import Image
-
+from PIL.Image import Resampling
 from ..feature_extraction_utils import BatchFeature
 from ..tokenizer_utils_base import TensorType
 from ..image_utils import ImageFeatureExtractionMixin
@@ -37,10 +37,10 @@ class CLIPFeatureExtractor(ImageFeatureExtractionMixin):
             Whether to resize the input to a certain `size`.
         size (`int`, *optional*, defaults to 224):
             Resize the input to the given size. Only has an effect if `do_resize` is set to `True`.
-        resample (`int`, *optional*, defaults to `PIL.Image.BICUBIC`):
-            An optional resampling filter. This can be one of `PIL.Image.NEAREST`, `PIL.Image.BOX`,
-            `PIL.Image.BILINEAR`, `PIL.Image.HAMMING`, `PIL.Image.BICUBIC` or `PIL.Image.LANCZOS`. Only has an effect
-            if `do_resize` is set to `True`.
+        resample (`int`, *optional*, defaults to `PIL.Image.Resampling.BICUBIC`):
+            An optional resampling filter. This can be one of `PIL.Image.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`.
         do_center_crop (`bool`, *optional*, defaults to `True`):
             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.
@@ -61,7 +61,7 @@ class CLIPFeatureExtractor(ImageFeatureExtractionMixin):
     def __init__(self,
                  do_resize=True,
                  size=224,
-                 resample=Image.BICUBIC,
+                 resample=Resampling.BICUBIC,
                  do_center_crop=True,
                  crop_size=224,
                  do_normalize=True,
diff --git a/paddlenlp/transformers/ernie_vil/feature_extraction.py b/paddlenlp/transformers/ernie_vil/feature_extraction.py
index 4becffeaffa5..f937beb44049 100644
--- a/paddlenlp/transformers/ernie_vil/feature_extraction.py
+++ b/paddlenlp/transformers/ernie_vil/feature_extraction.py
@@ -20,6 +20,7 @@
 import paddle
 import numpy as np
 from PIL import Image
+from PIL.Image import Resampling
 
 from ..feature_extraction_utils import BatchFeature
 from ..tokenizer_utils_base import TensorType
@@ -38,10 +39,10 @@ class ErnieViLFeatureExtractor(ImageFeatureExtractionMixin):
             Whether to resize the input to a certain `size`.
         size (`int`, *optional*, defaults to 224):
             Resize the input to the given size. Only has an effect if `do_resize` is set to `True`.
-        resample (`int`, *optional*, defaults to `PIL.Image.BICUBIC`):
-            An optional resampling filter. This can be one of `PIL.Image.NEAREST`, `PIL.Image.BOX`,
-            `PIL.Image.BILINEAR`, `PIL.Image.HAMMING`, `PIL.Image.BICUBIC` or `PIL.Image.LANCZOS`. Only has an effect
-            if `do_resize` is set to `True`.
+        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`.
         do_center_crop (`bool`, *optional*, defaults to `True`):
             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.
@@ -62,7 +63,7 @@ class ErnieViLFeatureExtractor(ImageFeatureExtractionMixin):
     def __init__(self,
                  do_resize=True,
                  size=224,
-                 resample=Image.BICUBIC,
+                 resample=Resampling.BICUBIC,
                  do_center_crop=True,
                  crop_size=224,
                  do_normalize=True,
diff --git a/paddlenlp/transformers/image_utils.py b/paddlenlp/transformers/image_utils.py
index 4eb66338ef51..4945471d5020 100644
--- a/paddlenlp/transformers/image_utils.py
+++ b/paddlenlp/transformers/image_utils.py
@@ -1,6 +1,6 @@
 # coding=utf-8
-# Copyright 2021 The HuggingFace Inc. team.
 # Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+# Copyright 2021 The HuggingFace Inc. team.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -18,9 +18,9 @@
 from typing import List, Union
 import paddle
 import numpy as np
-from PIL import Image
 import PIL.Image
 import PIL.ImageOps
+from PIL.Image import Resampling
 
 import requests
 
@@ -210,7 +210,7 @@ def normalize(self, image, mean, std):
     def resize(self,
                image,
                size,
-               resample=Image.BILINEAR,
+               resample=Resampling.BILINEAR,
                default_to_square=True,
                max_size=None):
         """
@@ -224,7 +224,7 @@ def resize(self,
                 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.BILINEAR`):
+            resample (`int`, *optional*, defaults to `PIL.Image.Resampling.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
@@ -376,7 +376,7 @@ def flip_channel_order(self, image):
     def rotate(self,
                image,
                angle,
-               resample=Image.NEAREST,
+               resample=Resampling.NEAREST,
                expand=0,
                center=None,
                translate=None,