code: def test_pgd(get_pytorch_detr):
      object_detector, x_test, y_test = get_pytorch_detr
  
      from art.attacks.evasion import ProjectedGradientDescent
      from PIL import Image
  
      imgs = []
      for i in x_test:
          img = Image.fromarray(
              (i * 255).astype(np.uint8).transpose(1, 2, 0)
          )
          img = img.resize(size=(800, 800))
          imgs.append(np.array(img))
      x_test = np.array(imgs).transpose(0, 3, 1, 2)
  
      attack = ProjectedGradientDescent(
          estimator=object_detector, max_iter=2
      )
      x_test_adv = attack.generate(x=x_test, y=y_test)
      np.testing.assert_raises(
          AssertionError,
          np.testing.assert_array_equal,
          x_test_adv,
          x_test,
      )
  
file_path: adversarial-robustness-toolbox/tests/estimators/object_detection/test_pytorch_detection_transformer.py
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  import numpy
  import pytest
label_desc: Use image node_id 8 for calling a global function with example usage: test_pgd(get_pytorch_detr) without return types