diff --git a/research/cv/DnCNN/infer/data/preprocess/export_bin_file.py b/research/cv/DnCNN/infer/data/preprocess/export_bin_file.py
index b4b5462ec9637e9fcf5840cd4d4aa78597df2f3e..14c0cb59612d02afe5b1a5a1f55aa8dfa82cd8e3 100644
--- a/research/cv/DnCNN/infer/data/preprocess/export_bin_file.py
+++ b/research/cv/DnCNN/infer/data/preprocess/export_bin_file.py
@@ -23,7 +23,7 @@ import numpy as np
 import cv2
 import mindspore
 import mindspore.dataset as ds
-import mindspore.dataset.transforms.c_transforms as C
+import mindspore.dataset.transforms as C
 
 
 def ResziePadding(img, fixed_side=256):
diff --git a/research/cv/FaceDetection/src/data_preprocess.py b/research/cv/FaceDetection/src/data_preprocess.py
index 8c1e7ebaae726b0fce08dfebe12add3fd95420a2..40081559b9bf3d760af2d6da2547708b62f405a5 100644
--- a/research/cv/FaceDetection/src/data_preprocess.py
+++ b/research/cv/FaceDetection/src/data_preprocess.py
@@ -31,7 +31,7 @@ class SingleScaleTrans:
     def __call__(self, imgs, ann, image_names, image_size, batch_info):
 
         size = self.resize
-        decode = P.Decode(True)
+        decode = V.Decode(True)
         resize_letter_box_op = ResizeLetterbox(input_dim=size)
 
         to_tensor = V.ToTensor()
@@ -204,11 +204,11 @@ def preprocess_fn(image, annotation):
     anchors = config.anchors
     anchors_mask = config.anchors_mask
 
-    decode = P.Decode(True)
+    decode = V.Decode(True)
     random_crop_letter_box_op = RandomCropLetterbox(jitter=jitter, input_dim=size)
     random_flip_op = RandomFlip(flip)
     hsv_shift_op = HSVShift(hue, sat, val)
-    to_tensor = P.ToTensor()
+    to_tensor = V.ToTensor()
 
     img_pil = decode(image)
     input_data = img_pil, annotation