code: def draw(self, words: List[Word]):
      font_variants = random.choice(self.fonts)
      canvas = np.zeros((0, 0), dtype=np.uint8)
      offset = int(
          font_variants.default_font.char_height // 2
          + max(
              abs(self.params.min_script_offset),
              abs(self.params.max_script_offset),
          )
          * font_variants.default_font.char_height
      )
      x = 0
      for word in words:
          font = font_variants.variants[word.variant]
          scale = [1, 0.5, 0.5][word.script]
          if (
              self.params.min_script_offset
              == self.params.max_script_offset
          ):
              script_offset = 0
          else:
              script_offset = int(
                  np.random.uniform(
                      self.params.min_script_offset,
                      self.params.max_script_offset,
                  )
                  * font.char_height
                  * scale
              )
          o = [
              0,
              font.topline - font.char_height - script_offset,
              font.baseline - font.char_height - script_offset,
          ][word.script]
          img = font.draw(word.text, scale, word.spacing)
          canvas = _extendToCanvas(canvas, img, (x, offset + o))
          x += img.shape[1]
  
      sums = np.mean(canvas, axis=1)
      cut_top = 0
      while cut_top < len(sums) - 1 and sums[cut_top + 1] == 255:
          cut_top += 1
  
      canvas = canvas[cut_top:, :]
      return np.pad(
          canvas, ((3, 3), (3, 3)), "constant", constant_values=255
      )
  
imports: from PIL import ImageFont, ImageDraw, Image
  import numpy
  import random
  from skimage.transform import rescale
  from enum import IntEnum
  from collections import namedtuple
  from typing import List
  import logging
  from calamari_ocr.ocr.dataset.datareader.generated_line_dataset import LineGeneratorParams
label_desc: Use image node_id 2 for calling the LineGenerator obj's underlying member method code with example usage: obj.draw(words) and returns: np