code: def test_image_property_outliers_check_mnist(mnist_visiondata_train):
      # Act
      result = ImagePropertyOutliers().run(mnist_visiondata_train)
  
      # Assert
      assert_that(result, is_correct_image_property_outliers_result())
      assert_that(
          result.value,
          has_entries(
              {
                  "Brightness": has_entries(
                      {
                          "outliers_identifiers": has_length(5),
                          "lower_limit": close_to(11.871, 0.01),
                          "upper_limit": close_to(57.15, 0.01),
                      }
                  ),
                  "Mean Red Relative Intensity": instance_of(str),
                  "Mean Green Relative Intensity": instance_of(str),
                  "Mean Blue Relative Intensity": instance_of(str),
              }
          ),
      )
  
file_path: deepchecks/tests/vision/checks/data_integrity/image_property_outliers_test.py
imports: import numpy
  from hamcrest import all_of, any_of, assert_that, calling, close_to, has_entries, has_key, has_length, has_properties, instance_of, is_, raises
  from hamcrest.core.matcher import Matcher
  from deepchecks.core import CheckResult
  from deepchecks.core.errors import DeepchecksProcessError, NotEnoughSamplesError
  from deepchecks.vision.checks import ImagePropertyOutliers
  from deepchecks.vision.utils.image_properties import default_image_properties
label_desc: Use image node_id 4 for calling a global function with example usage: test_image_property_outliers_check_mnist(mnist_visiondata_train) without return types