class_docstr: Apply a bitmap-style transformation to an image.
  
  This transformation replaces all pixel values below a certain threshold with a specified value.
  
  Args:
      value (int, optional): The value to replace pixels below the threshold with. Default is 0.
      lower (int, optional): The threshold value below which pixels will be replaced. Default is 200.
      always_apply (bool, optional): Whether to always apply this transformation. Default is False.
      p (float, optional): The probability of applying this transformation. Default is 0.5.
  
  Returns:
      numpy.ndarray: The transformed image.
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code: def apply(self, img, **params):
      img = img.copy()
      img[img < self.lower] = self.value
      return img
  
file_path: nougat/nougat/transforms.py
imports: import albumentations
  from albumentations.pytorch import ToTensorV2
  import cv2
  import numpy
  from timm.data.constants import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
label_desc: Use image node_id 2 for calling the Bitmap obj's underlying member method code with example usage: obj.apply(img) and returns: img