code: def __call__(self, *imgs):
      ret = self.get_params(
          self.degrees,
          self.translate,
          self.scale,
          self.shear,
          imgs[0].size,
      )
      w, h = imgs[0].size
      imgs = map(lambda x: F.pad(x, w // 2, 0, self.resample), imgs)
      imgs = map(lambda x: F.affine(x, *ret, resample=0), imgs)
      imgs = map(lambda x: F.center_crop(x, (w, h)), imgs)
      return imgs
  
imports: import os
  import cv2
  import numpy
  import random
  import torchvision.transforms.functional
  from torchvision.transforms import RandomResizedCrop, ColorJitter, RandomAffine
  import PIL
  from PIL import Image
  import collections
  import settings
label_desc: Use image node_id 2 for calling the RandomAffineWithMask obj's underlying member method code with example usage: obj.__call__() and returns: imgs