class_docstr: Dataset for colorization. It contains 1193 and 400 pictures for Monet and Vango paintings style, respectively.
  We collected data from https://people.eecs.berkeley.edu/~taesung_park/CycleGAN/datasets/.
  
  Args:
     transform(callmethod) : The method of preprocess images.
     mode(str): The mode for preparing dataset.
  
  Returns:
      DataSet: An iterable object for data iterating
code: def __init__(self, transform: Callable, mode: str = "train"):
      self.mode = mode
      self.transform = transform
  
      if self.mode == "train":
          self.file = "train"
      elif self.mode == "test":
          self.file = "test"
  
      self.file = os.path.join(hubenv.DATA_HOME, "canvas", self.file)
      self.data = get_img_file(self.file)
  
file_path: PaddleHub/paddlehub/datasets/canvas.py
imports: import os
  from typing import Callable
  import paddle
  import numpy
  import paddlehub.env
  from paddlehub.vision.utils import get_img_file
  from paddlehub.utils.download import download_data
label_desc: Use image node_id 1 to create a new Canvas object from inherited base classes: paddle.io with example: obj = Canvas(transform, mode)