code: def test_object_detection_coco_with_condition(
      coco_visiondata_train, coco_visiondata_test
  ):
      # Act
      check = NewLabels().add_condition_new_label_ratio_less_or_equal(
          0.1
      )
      result = check.conditions_decision(
          check.run(coco_visiondata_train, coco_visiondata_test)
      )
      # Assert
      assert_that(
          result,
          has_items(
              equal_condition_result(
                  is_pass=False,
                  name="Percentage of new labels in the test set is less or equal to 10%",
                  details=(
                      "10.08% of labels found in test set were not in train set. "
                      "New labels most common in test set: ['donut', 'tennis racket', 'boat']"
                  ),
              )
          ),
      )
  
file_path: deepchecks/tests/vision/checks/train_test_validation/new_labels_test.py
imports: from hamcrest import assert_that, equal_to, greater_than, has_entries, has_items, has_length
  from deepchecks.vision.checks import NewLabels
  from deepchecks.vision.datasets.classification.mnist_torch import collate_without_model
  from deepchecks.vision.datasets.detection.coco_torch import collate_without_model
  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 3 for calling a global function with example usage: test_object_detection_coco_with_condition(coco_visiondata_train, coco_visiondata_test) without return types