code: def image_batch(channels_first):
      """
      Image fixtures of shape NHWC and NCHW and a sample object detection label.
      """
      channels = 3
      height = 20
      width = 16
  
      if channels_first:
          data_shape = (2, channels, height, width)
      else:
          data_shape = (2, height, width, channels)
      x = (0.5 * np.ones((data_shape))).astype(ART_NUMPY_DTYPE)
  
      y = []
      for _ in range(len(x)):
          y_1, x_1 = np.random.uniform(0, (height / 2, width / 2))
          y_2, x_2 = np.random.uniform(
              (y_1 + 3, x_1 + 3), (height, width)
          )
          target_dict = {
              "boxes": np.array([[x_1, y_1, x_2, y_2]]),
              "labels": np.array([0]),
          }
          y.append(target_dict)
  
      return x, y
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  import numpy
  import pytest
  from art.config import ART_NUMPY_DTYPE
label_desc: Use image node_id 1 for calling a global function with example usage: image_batch(channels_first) and returns: x,  y