Update

Signed-off-by: shiyu22 <shiyu.chen@zilliz.com>

README.md

@@ -21,14 +21,14 @@ __init__(self, size: int)
   - supported types: `int`
 
 ```python
-__call__(self, img: Union[np.ndarray, Image.Image, torch.Tensor, str])
+__call__(self, img: Union[Image.Image, torch.Tensor, str])
 ```
 
 **Args:**
 
 - img:
   - the input image to be processed
-  - supported type: `np.ndarry` or ` PIL.image` or `str` (path of the image)
+  - supported type: ` PIL.image` or `str` (path of the image)
 
 **Returns:**
 
@@ -51,4 +51,3 @@ The `towhee/transform-image` Operator is used for image transformation and is an
 ## Reference
 
 - https://pytorch.org/vision/stable/transforms.html
-

transform_image.py

@@ -15,7 +15,6 @@
 from typing import NamedTuple, Union
 
 import torch
-import numpy as np
 from PIL import Image
 from torchvision import transforms
 
@@ -43,14 +42,14 @@ class TransformImage(Operator):
             ]
         )
 
-    def __call__(self, img: Union[np.ndarray, Image.Image, torch.Tensor, str]) -> NamedTuple('Outputs', [('img_transformed', torch.Tensor)]):
+    def __call__(self, img: Union[Image.Image, torch.Tensor, str]) -> NamedTuple('Outputs', [('img_transformed', torch.Tensor)]):
         """
         Call it when use this class.
         
         Args:
-            img(`Union[np.ndarray, Image.Image, torch.Tensor, str]`):
+            img(`Union[mage.Image, torch.Tensor, str]`):
                 The image data to be normalized, you can try one of the 
-                four formats: np.ndarray, Image.Image, torch.Tensor and str.
+                four formats: Image.Image, torch.Tensor and str.
         Returns:
             (`torch.Tensor`)
                 The normalized image tensor.

transform_image.yaml

@@ -8,6 +8,6 @@ init:
   size: int
 call:
   input:
-    img: Union[np.ndarray, Image.Image, torch.Tensor, str]
+    img: Union[Image.Image, torch.Tensor, str]
   output:
     img_transformed: torch.Tensor