code: def __init__(
      self,
      fill_value=0,
      fg_limit=(0.7, 0.9),
      always_apply=False,
      p=1.0,
  ):
      super(RectangleBorderAugmentation, self).__init__(always_apply, p)
      # assert limit>0.0 and limit<1.0
      assert isinstance(fg_limit, tuple)
      assert fg_limit[1] > fg_limit[0]
      self.fill_value = 0
      self.fg_limit = fg_limit
  
imports: import numpy
  import cv2
  import os
  import os.path
  import albumentations
  from albumentations.core.transforms_interface import ImageOnlyTransform
  from albumentations.pytorch import ToTensorV2
label_desc: Use image node_id 1 to create a new RectangleBorderAugmentation object from inherited base classes: ImageOnlyTransform with example: obj = RectangleBorderAugmentation(fill_value, fg_limit, always_apply, p)