code: def test_match_bboxes_hungarian(
      gt_bboxes,
      pred_bboxes,
      num_classes,
      true_positives,
      false_positives,
      false_negatives,
      confusion_matrix,
  ):
      gt_bboxes, gt_labels = gt_bboxes
      pred_bboxes, pred_labels = pred_bboxes
  
      gt_bboxes = np.asarray(gt_bboxes)
      gt_labels = np.asarray(gt_labels)
  
      pred_bboxes = np.asarray(pred_bboxes)
      pred_labels = np.asarray(pred_labels)
  
      result = match_bboxes_hungarian(
          pred_bboxes,
          pred_labels,
          gt_bboxes,
          gt_labels,
          num_classes=num_classes,
          iou_threshold=0.5,
      )
  
      np.testing.assert_equal(result.true_positives, true_positives)
      np.testing.assert_equal(result.false_positives, false_positives)
      np.testing.assert_equal(result.false_negatives, false_negatives)
      np.testing.assert_equal(result.confusion_matrix, confusion_matrix)
  
imports: import numpy
  import pytest
  import torch
  from pytorch_toolbelt.inference.functional import unpad_xyxy_bboxes, pad_image_tensor, unpad_image_tensor, pad_tensor_to_size
  from pytorch_toolbelt.modules.encoders import make_n_channel_input
  from pytorch_toolbelt.utils import match_bboxes, match_bboxes_hungarian, get_collate_for_dataset
  from torch import nn
  from torch.utils.data import ConcatDataset
  from functools import partial
label_desc: Use image node_id 9 for calling a global function with example usage: test_match_bboxes_hungarian(gt_bboxes, pred_bboxes, num_classes, true_positives, false_positives, false_negatives, confusion_matrix) without return types