code: def test_brightness_rgb():
      value = np.concatenate(
          [
              np.ones((10, 10, 1)) * 1,
              np.ones((10, 10, 1)) * 2,
              np.ones((10, 10, 1)) * 3,
          ],
          axis=2,
      )
  
      batch = next(iter(numpy_shape_dataloader(value=value)))
  
      res = image_properties.brightness(batch)
  
      assert_that(res[0], close_to(1.86, 0.01))
  
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 3 for calling a global function with example usage: test_brightness_rgb() without return types