[Doc] add vision processor python api doc (#1655)

* add vision processor python api doc

* fix reviewed problem

* fix reviewed problem

python/fastdeploy/vision/common/processors.py

@@ -9,7 +9,7 @@ class Processor():
     def __call__(self, mat):
         """call for processing input.
 
-        :param mat: the input data FDMat or FDMatBatch.
+        :param mat: The input data FDMat or FDMatBatch.
         """
         self.processor(mat)
 
@@ -18,10 +18,10 @@ class ResizeByShort(Processor):
     def __init__(self, target_size: int, interp=1, use_scale=True, max_hw=[]):
         """Create a ResizeByShort operation with the given parameters.
 
-        :param target_size: the target short size to resize the image
-        :param interp: optionally, the interpolation mode for resizing image
-        :param use_scale: optionally, whether to scale image
-        :param max_hw: max spatial size which is used by ResizeByShort
+        :param target_size: The target short size to resize the image
+        :param interp: Optionally, the interpolation mode for resizing image
+        :param use_scale: Optionally, whether to scale image
+        :param max_hw: Max spatial size which is used by ResizeByShort
         """
         self.processor = C.vision.processors.ResizeByShort(target_size, interp,
                                                            use_scale, max_hw)
@@ -31,8 +31,8 @@ class CenterCrop(Processor):
     def __init__(self, width, height):
         """Create a CenterCrop operation with the given parameters.
 
-        :param width: desired width of the cropped image
-        :param height: desired height of the cropped image
+        :param width: Desired width of the cropped image
+        :param height: Desired height of the cropped image
         """
         self.processor = C.vision.processors.CenterCrop(width, height)
 
@@ -41,10 +41,10 @@ class Pad(Processor):
     def __init__(self, top: int, bottom: int, left: int, right: int, value=[]):
         """Create a Pad operation with the given parameters.
 
-        :param top: the top padding
-        :param bottom: the bottom padding
-        :param left: the left padding
-        :param right: the right padding
+        :param top: The top padding
+        :param bottom: The bottom padding
+        :param left: The left padding
+        :param right: The right padding
         :param value: the value that is used to pad on the input image
         """
         self.processor = C.vision.processors.Pad(top, bottom, left, right,
@@ -61,11 +61,11 @@ class NormalizeAndPermute(Processor):
                  swap_rb=False):
         """Creae a Normalize and a Permute operation with the given parameters.
 
-        :param mean     A list containing the mean of each channel
-        :param std      A list containing the standard deviation of each channel
-        :param is_scale Specifies if the image are being scaled or not
-        :param min      A list containing the minimum value of each channel
-        :param max      A list containing the maximum value of each channel
+        :param mean: A list containing the mean of each channel
+        :param std: A list containing the standard deviation of each channel
+        :param is_scale: Specifies if the image are being scaled or not
+        :param min: A list containing the minimum value of each channel
+        :param max: A list containing the maximum value of each channel
         """
         self.processor = C.vision.processors.NormalizeAndPermute(
             mean, std, is_scale, min, max, swap_rb)
@@ -75,7 +75,7 @@ class Cast(Processor):
     def __init__(self, dtype="float"):
         """Creat a new cast opereaton with given dtype
 
-        :param dtype dtype of the output
+        :param dtype: Target dtype of the output
         """
         self.processor = C.vision.processors.Cast(dtype)
 
@@ -90,20 +90,15 @@ class HWC2CHW(Processor):
 
 
 class Normalize(Processor):
-    def __init__(self,
-                 mean=[],
-                 std=[],
-                 is_scale=True,
-                 min=[],
-                 max=[],
+    def __init__(self, mean, std, is_scale=True, min=[], max=[],
                  swap_rb=False):
         """Creat a new normalize opereator with given paremeters.
 
-        :param mean     A list containing the mean of each channel
-        :param std      A list containing the standard deviation of each channel
-        :param is_scale Specifies if the image are being scaled or not
-        :param min      A list containing the minimum value of each channel
-        :param max      A list containing the maximum value of each channel
+        :param mean: A list containing the mean of each channel
+        :param std: A list containing the standard deviation of each channel
+        :param is_scale: Specifies if the image are being scaled or not
+        :param min: A list containing the minimum value of each channel
+        :param max: A list containing the maximum value of each channel
         """
         self.processor = C.vision.processors.Normalize(mean, std, is_scale,
                                                        min, max, swap_rb)
@@ -113,9 +108,9 @@ class PadToSize(Processor):
     def __init__(self, width, height, value=[]):
         """Create a new PadToSize opereator with given parameters.
 
-        :param width     Desired width of the output image
-        :param height    Desired height of the output image
-        :param value     values to pad with
+        :param width: Desired width of the output image
+        :param height: Desired height of the output image
+        :param value: Values to pad with
         """
         self.processor = C.vision.processors.PadToSize(width, height, value)
 
@@ -130,12 +125,12 @@ class Resize(Processor):
                  use_scale=False):
         """Create a Resize operation with the given parameters.
 
-        :param width   Desired width of the output image
-        :param height  Desired height of the output image
-        :param scale_w Scales the width in x-direction
-        :param scale_h Scales the height in y-direction
-        :param interp: optionally, the interpolation mode for resizing image
-        :param use_scale: optionally, whether to scale image
+        :param width: Desired width of the output image
+        :param height: Desired height of the output image
+        :param scale_w: Scales the width in x-direction
+        :param scale_h: Scales the height in y-direction
+        :param interp: Optionally, the interpolation mode for resizing image
+        :param use_scale: Optionally, whether to scale image
         """
         self.processor = C.vision.processors.Resize(width, height, scale_w,
                                                     scale_h, interp, use_scale)
@@ -145,7 +140,7 @@ class StridePad(Processor):
     def __init__(self, stride, value=[]):
         """Create a StridePad processor with given parameters.
 
-        :param stride Stride of the processor
-        :param value  values to pad with
+        :param stride: Stride of the processor
+        :param value: Values to pad with
         """
         self.processor = C.vision.processors.StridePad(stride, value)