class_docstr: Add bottom-right padding to a raw image or annotation image.
  
  Args:
      target_size (list|tuple): The target size after padding.
      im_padding_value (list, optional): The padding value of raw image.
          Default: [127.5, 127.5, 127.5].
      label_padding_value (int, optional): The padding value of annotation image. Default: 255.
  
  Raises:
      TypeError: When target_size is neither list nor tuple.
      ValueError: When the length of target_size is not 2.
class_docstr_tok: ["Add","bottom-right","padding","to","a","raw","image","or","annotation","image",".","Args",":","target_size","(","list|tuple",")",":","The","target","size","after","padding",".","im_padding_value","(","list",",","optional",")",":","The","padding","value","of","raw","image",".","Default",":","[","127.5",",","127.5",",","127.5","]",".","label_padding_value","(","int",",","optional",")",":","The","padding","value","of","annotation","image",".","Default",":","255",".","Raises",":","TypeError",":","When","target_size","is","neither","list","nor","tuple",".","ValueError",":","When","the","length","of","target_size","is","not","2","."]
code: def __init__(
      self, target_size, im_padding_value=(127.5, 127.5, 127.5)
  ):
      if isinstance(target_size, list) or isinstance(
          target_size, tuple
      ):
          if len(target_size) != 2:
              raise ValueError(
                  "`target_size` should include 2 elements, but it is {}".format(
                      target_size
                  )
              )
      else:
          raise TypeError(
              "Type of target_size is invalid. It should be list or tuple, now is {}".format(
                  type(target_size)
              )
          )
  
      self.target_size = target_size
      self.im_padding_value = im_padding_value
  
imports: import os
  import random
  import string
  import cv2
  import numpy
  from paddleseg.transforms import functional
  from paddleseg.cvlibs import manager
  from paddleseg.utils import seg_env
  from PIL import Image
label_desc: Use image node_id 1 to create a new Padding object  with example: obj = Padding(target_size, im_padding_value)