code: def random_scale(images, word_level_char_bbox, scale_range):
      scale = random.sample(scale_range, 1)[0]
  
      for i in range(len(images)):
          images[i] = cv2.resize(
              images[i], dsize=None, fx=scale, fy=scale
          )
  
      for i in range(len(word_level_char_bbox)):
          word_level_char_bbox[i] *= scale
  
      return images
  
file_path: EasyOCR/trainer/craft/data/imgaug.py
imports: import random
  import cv2
  import numpy
  from PIL import Image
  from torchvision.transforms.functional import resized_crop, crop
  from torchvision.transforms import RandomResizedCrop, RandomCrop
  from torchvision.transforms import InterpolationMode
label_desc: Use image node_id 6 for calling a global function with example usage: random_scale(images, word_level_char_bbox, scale_range) and returns: images