class_docstr: Get hint and mask images for colorization.
  
  This method is prepared for user guided colorization tasks. Take the original RGB images as imput,
  we will obtain the local hints and correspoding mask to guid colorization process.
  
  Args:
     percent(float): Probability for ignoring hint in an iteration.
     num_points(int): Number of selected hints in an iteration.
     samp(str): Sample method, default is normal.
     use_avg(bool): Whether to use mean in selected hint area.
  
  Return:
      hint(np.ndarray): hint images
      mask(np.ndarray): mask images
code: def __init__(
      self,
      percent: float,
      num_points: int = None,
      samp: str = "normal",
      use_avg: bool = True,
  ):
      self.percent = percent
      self.num_points = num_points
      self.samp = samp
      self.use_avg = use_avg
  
imports: import paddle
  import numpy
label_desc: Use image node_id 1 to create a new ColorizeHint object  with example: obj = ColorizeHint(percent, num_points, samp, use_avg)