code: def test_outliers_check_coco_without_display(coco_visiondata_train):
      # Act
      result = LabelPropertyOutliers().run(
          coco_visiondata_train, with_display=False
      )
  
      # Assert
      assert_that(
          result,
          is_correct_label_property_outliers_result(
              DEFAULT_OBJECT_DETECTION_LABEL_PROPERTIES,
              with_display=False,
          ),
      )
      assert_that(
          result.value,
          has_entries(
              {
                  "Number of Bounding Boxes Per Image": has_entries(
                      {
                          "outliers_identifiers": contains_exactly(
                              "21", "30", "1", "5", "11", "20"
                          ),
                          "lower_limit": is_(0),
                          "upper_limit": is_(20.125),
                      }
                  ),
                  "Bounding Box Area (in pixels)": instance_of(dict),
              }
          ),
      )
  
file_path: deepchecks/tests/vision/checks/data_integrity/label_property_outliers_test.py
imports: from hamcrest import all_of, any_of, assert_that, calling, close_to, contains_exactly, equal_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
  from deepchecks.vision.checks import LabelPropertyOutliers
  from deepchecks.vision.utils.label_prediction_properties import DEFAULT_OBJECT_DETECTION_LABEL_PROPERTIES
label_desc: Use image node_id 5 for calling a global function with example usage: test_outliers_check_coco_without_display(coco_visiondata_train) without return types