code: def test_brightness_grayscale():
      value = np.concatenate(
          [np.zeros((3, 10, 1)), np.ones((7, 10, 1))], axis=0
      )
      batch = next(iter(numpy_shape_dataloader(value=value)))
      res = image_properties.brightness(batch)
      assert_that(res, equal_to([0.7] * 4))
  
imports: from itertools import permutations
  from typing import Union
  import numpy
  import torch
  from hamcrest import assert_that, calling, close_to, equal_to, raises
  from torch.utils.data import DataLoader, Dataset
  from deepchecks.vision.datasets.detection import coco_torch
  from deepchecks.vision.utils import image_properties
  from deepchecks.vision.utils.detection_formatters import convert_batch_of_bboxes, convert_bbox, verify_bbox_format_notation
  from deepchecks.vision.vision_data import VisionData
label_desc: Use image node_id 2 for calling a global function with example usage: test_brightness_grayscale() without return types