class_docstr: An image resizing pre-processor.
  
  :param observation_space: The observation space to pre-process.
  :param target_size: Target size of resized image.
  :param transpose: Transpose rgb channel is required (should be last dimension such as [96, 96, 3]).
class_docstr_tok: ["An","image","resizing","pre-processor",".",":","param","observation_space",":","The","observation","space","to","pre-process",".",":","param","target_size",":","Target","size","of","resized","image",".",":","param","transpose",":","Transpose","rgb","channel","is","required","(","should","be","last","dimension","such","as","[","96",",","96",",","3","]",")","."]
code: def __init__(
      self,
      observation_space: spaces.Box,
      target_size: Sequence[int],
      transpose: bool,
  ):
      super().__init__(observation_space)
      self.target_size = list(target_size)
      self.transpose = transpose
  
file_path: maze/maze/core/wrappers/observation_preprocessing/preprocessors/resize_img.py
imports: from typing import Tuple, Sequence
  import numpy
  from gym import spaces
  from PIL import Image
  from maze.core.wrappers.observation_preprocessing.preprocessors.base import PreProcessor
  from maze.core.annotations import override
label_desc: Use image node_id 1 to create a new ResizeImgPreProcessor object from inherited base classes: PreProcessor with example: obj = ResizeImgPreProcessor(observation_space, target_size, transpose)