diff --git a/mindarmour/natural_robustness/transform/image/blur.py b/mindarmour/natural_robustness/transform/image/blur.py
index e63b52f..f53a13f 100644
--- a/mindarmour/natural_robustness/transform/image/blur.py
+++ b/mindarmour/natural_robustness/transform/image/blur.py
@@ -34,7 +34,7 @@ class GaussianBlur(_NaturalPerturb):
         ksize (int): Size of gaussian kernel, this value must be non-negnative.
         auto_param (bool): Auto selected parameters. Selected parameters will preserve semantics of image.
 
-    Example:
+    Examples:
         >>> img = cv2.imread('1.png')
         >>> img = np.array(img)
         >>> ksize = 5
@@ -74,11 +74,11 @@ class MotionBlur(_NaturalPerturb):
 
     Args:
         degree (int): Degree of blur. This value must be positive. Suggested value range in [1, 15].
-        angle: (union[float, int]): Direction of motion blur. Angle=0 means up and down motion blur. Angle is
+        angle (union[float, int]): Direction of motion blur. Angle=0 means up and down motion blur. Angle is
             counterclockwise.
         auto_param (bool): Auto selected parameters. Selected parameters will preserve semantics of image.
 
-    Example:
+    Examples:
         >>> img = cv2.imread('1.png')
         >>> img = np.array(img)
         >>> angle = 0
@@ -132,7 +132,7 @@ class GradientBlur(_NaturalPerturb):
         center (bool): Blurred or clear at the center of a specified point.
         auto_param (bool): Auto selected parameters. Selected parameters will preserve semantics of image.
 
-    Example:
+    Examples:
         >>> img = cv2.imread('xx.png')
         >>> img = np.array(img)
         >>> number = 5
diff --git a/mindarmour/natural_robustness/transform/image/corruption.py b/mindarmour/natural_robustness/transform/image/corruption.py
index e80019b..0e66c19 100644
--- a/mindarmour/natural_robustness/transform/image/corruption.py
+++ b/mindarmour/natural_robustness/transform/image/corruption.py
@@ -35,7 +35,7 @@ class UniformNoise(_NaturalPerturb):
             [0.001, 0.15].
         auto_param (bool): Auto selected parameters. Selected parameters will preserve semantics of image.
 
-    Example:
+    Examples:
         >>> img = cv2.imread('1.png')
         >>> img = np.array(img)
         >>> factor = 0.1
@@ -80,7 +80,7 @@ class GaussianNoise(_NaturalPerturb):
             [0.001, 0.15].
         auto_param (bool): Auto selected parameters. Selected parameters will preserve semantics of image.
 
-    Example:
+    Examples:
         >>> img = cv2.imread('1.png')
         >>> img = np.array(img)
         >>> factor = 0.1
@@ -124,7 +124,7 @@ class SaltAndPepperNoise(_NaturalPerturb):
             [0.001, 0.15].
         auto_param (bool): Auto selected parameters. Selected parameters will preserve semantics of image.
 
-    Example:
+    Examples:
         >>> img = cv2.imread('1.png')
         >>> img = np.array(img)
         >>> factor = 0.1
diff --git a/mindarmour/natural_robustness/transform/image/luminance.py b/mindarmour/natural_robustness/transform/image/luminance.py
index da9063d..89e9827 100644
--- a/mindarmour/natural_robustness/transform/image/luminance.py
+++ b/mindarmour/natural_robustness/transform/image/luminance.py
@@ -28,16 +28,16 @@ TAG = 'Image Luminance'
 
 
 class Contrast(_NaturalPerturb):
-    """
+    r"""
     Contrast of an image.
 
     Args:
-        alpha (Union[float, int]): Control the contrast of an image. :math:`out_image = in_image*alpha+beta`.
+        alpha (Union[float, int]): Control the contrast of an image. :math:`out\_image = in\_image*alpha+beta`.
             Suggested value range in [0.2, 2].
         beta (Union[float, int]): Delta added to alpha. Default: 0.
         auto_param (bool): Auto selected parameters. Selected parameters will preserve semantics of image.
 
-    Example:
+    Examples:
         >>> img = cv2.imread('1.png')
         >>> img = np.array(img)
         >>> alpha = 0.1
diff --git a/mindarmour/natural_robustness/transform/image/transformation.py b/mindarmour/natural_robustness/transform/image/transformation.py
index 0a90fed..73e157c 100644
--- a/mindarmour/natural_robustness/transform/image/transformation.py
+++ b/mindarmour/natural_robustness/transform/image/transformation.py
@@ -37,7 +37,7 @@ class Translate(_NaturalPerturb):
             in [-0.1, 0.1].
         auto_param (bool): Auto selected parameters. Selected parameters will preserve semantics of image.
 
-    Example:
+    Examples:
         >>> img = cv2.imread('1.png')
         >>> img = np.array(img)
         >>> x_bias = 0.1
@@ -84,7 +84,7 @@ class Scale(_NaturalPerturb):
             abs(factor_y - factor_x) < 0.5.
         auto_param (bool): Auto selected parameters. Selected parameters will preserve semantics of image.
 
-    Example:
+    Examples:
         >>> img = cv2.imread('1.png')
         >>> img = np.array(img)
         >>> factor_x = 0.7
@@ -131,7 +131,7 @@ class Shear(_NaturalPerturb):
         direction (str): Direction of deformation. Optional value is 'vertical' or 'horizontal'.
         auto_param (bool): Auto selected parameters. Selected parameters will preserve semantics of image.
 
-    Example:
+    Examples:
         >>> img = cv2.imread('1.png')
         >>> img = np.array(img)
         >>> factor = 0.2
@@ -186,7 +186,7 @@ class Rotate(_NaturalPerturb):
         angle (Union[float, int]): Degrees of counter clockwise. Suggested value range in [-60, 60].
         auto_param (bool): Auto selected parameters. Selected parameters will preserve semantics of image.
 
-    Example:
+    Examples:
         >>> img = cv2.imread('1.png')
         >>> img = np.array(img)
         >>> angle = 20
@@ -240,7 +240,7 @@ class Perspective(_NaturalPerturb):
         dst_pos (list): The point coordinates of the 4 points in ori_pos after perspective transformation.
         auto_param (bool): Auto selected parameters. Selected parameters will preserve semantics of image.
 
-    Example:
+    Examples:
         >>> img = cv2.imread('1.png')
         >>> img = np.array(img)
         >>> ori_pos = [[0, 0], [0, 800], [800, 0], [800, 800]]