code: def adjust_contrast_grey(img, target=0.4):
      contrast, high, low = contrast_grey(img)
      if contrast < target:
          img = img.astype(int)
          ratio = 200.0 / np.maximum(10, high - low)
          img = (img - low + 25) * ratio
          img = np.maximum(
              np.full(img.shape, 0),
              np.minimum(np.full(img.shape, 255), img),
          ).astype(np.uint8)
      return img
  
imports: from PIL import Image
  import torch
  import torch.backends.cudnn
  import torch.utils.data
  import torch.nn.functional
  import torchvision.transforms
  import numpy
  from collections import OrderedDict
  import importlib
  from .utils import CTCLabelConverter
  import math
label_desc: Use image node_id 3 for calling a global function with example usage: adjust_contrast_grey(img, target) and returns: img