code: def test_drift_object_detection(
      coco_train_brightness_bias, coco_visiondata_test
  ):
      # Arrange
      check = PropertyLabelCorrelationChange(per_class=False)
  
      # Act
      result = check.run(
          coco_train_brightness_bias, coco_visiondata_test
      )
  
      # Assert
      assert_that(
          result.value,
          has_entries(
              {
                  "train": has_entries(
                      {"Brightness": close_to(0.087, 0.01)}
                  ),
                  "test": has_entries(
                      {"Brightness": close_to(0.016, 0.01)}
                  ),
                  "train-test difference": has_entries(
                      {"Brightness": close_to(0.071, 0.01)}
                  ),
              }
          ),
      )
      assert_that(result.display, has_length(greater_than(0)))
  
imports: import numpy
  import torch
  from hamcrest import assert_that, close_to, equal_to, greater_than, has_entries, has_length
  from deepchecks.vision.checks import PropertyLabelCorrelationChange
  from deepchecks.vision.utils.test_utils import replace_collate_fn_visiondata
  from tests.base.utils import equal_condition_result
label_desc: Use image node_id 5 for calling a global function with example usage: test_drift_object_detection(coco_train_brightness_bias, coco_visiondata_test) without return types