code: def random_sized_crop_list(images, size, crop_area_fraction=0.08):
      """
      Perform random sized cropping on the given list of images. Random crop with
          size 8% - 100% image area and aspect ratio in [3/4, 4/3].
      Args:
          images (list): image to crop.
          size (int): size to crop.
          area_frac (float): area of fraction.
      Returns:
          (list): list of cropped image.
      """
      for _ in range(0, 10):
          height = images[0].shape[0]
          width = images[0].shape[1]
          area = height * width
          target_area = (
              np.random.uniform(crop_area_fraction, 1.0) * area
          )
          aspect_ratio = np.random.uniform(3.0 / 4.0, 4.0 / 3.0)
          w = int(round(math.sqrt(float(target_area) * aspect_ratio)))
          h = int(round(math.sqrt(float(target_area) / aspect_ratio)))
          if np.random.uniform() < 0.5:
              w, h = h, w
          if h <= height and w <= width:
              if height == h:
                  y_offset = 0
              else:
                  y_offset = np.random.randint(0, height - h)
              if width == w:
                  x_offset = 0
              else:
                  x_offset = np.random.randint(0, width - w)
              y_offset = int(y_offset)
              x_offset = int(x_offset)
  
              croppsed_images = []
              for image in images:
                  cropped = image[
                      y_offset : y_offset + h,
                      x_offset : x_offset + w,
                      :,
                  ]
                  assert (
                      cropped.shape[0] == h and cropped.shape[1] == w
                  ), "Wrong crop size"
                  cropped = cv2.resize(
                      cropped,
                      (size, size),
                      interpolation=cv2.INTER_LINEAR,
                  )
                  croppsed_images.append(cropped.astype(np.float32))
              return croppsed_images
  
      return [center_crop(size, scale(size, image)) for image in images]
  
imports: import math
  import numpy
  import cv2
label_desc: Use image node_id 22 for calling a global function with example usage: random_sized_crop_list(images, size, crop_area_fraction) and returns: unknown, croppsed_images