code: def test_bbox_convertion_to_the_required_format():
      data = (
          (
              dict(
                  notation="xylxy", bbox=np.asarray([20, 15, 2, 41, 23])
              ),  # input
              np.asarray([2, 20, 15, 21, 8]),  # expected result
          ),
          (
              dict(
                  notation="cxcywhl",
                  bbox=np.asarray([50, 55, 100, 100, 0]),
              ),  # input
              np.asarray(
                  [0, (50 - 100 / 2), (55 - 100 / 2), 100, 100]
              ),  # expected result
          ),
          (
              dict(
                  notation="whxyl", bbox=np.asarray([35, 70, 10, 15, 1])
              ),  # input
              np.asarray(
                  [
                      1,
                      10,
                      15,
                      35,
                      70,
                  ]
              ),  # expected result
          ),
          (
              dict(  # input
                  notation="nxywhl",
                  bbox=np.asarray([0.20, 0.20, 20, 40, 1]),
                  image_width=100,
                  image_height=100,
              ),
              np.asarray(
                  [
                      1,
                      20,
                      20,
                      20,
                      40,
                  ]
              ),  # expected result
          ),
          (
              dict(  # input
                  notation="cxcylwhn",
                  bbox=np.asarray([0.12, 0.17, 0, 50, 100]),
                  image_width=600,
                  image_height=1200,
              ),
              np.asarray(
                  [
                      0,
                      47,
                      154.00000000000003,
                      50,
                      100,
                  ]
              ),  # expected result
          ),
      )
  
      for args, expected_result in data:
          result = convert_bbox(**args)
          assert_that(
              (result == expected_result).all(),
              f"Arguments: {args}, Result: {result}",
          )
  
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 17 for calling a global function with example usage: test_bbox_convertion_to_the_required_format() without return types