code: def test_get_segment_pred_area():
      t1 = torch.Tensor(
          [[[0.3, 0.6, 0.1], [0.3, 0.6, 0.1], [0.3, 0.6, 0.1]]] * 3
      )
      t2 = torch.Tensor(
          [[[0.3, 0.3, 0.4], [0.3, 0.6, 0.1], [0.3, 0.6, 0.1]]] * 3
      )
  
      t1 = torch.transpose(t1, 0, 2)
      t2 = torch.transpose(t2, 0, 2)
  
      batch = [t1, t2]
      res = _get_segment_pred_area(batch)
      expected_result = [[9], [6, 3]]
      assert_that(res, contains_exactly(*expected_result))
  
file_path: deepchecks/tests/vision/utils_tests/label_prediction_properties_test.py
imports: import torch
  from hamcrest import assert_that, contains_exactly
  from deepchecks.vision.utils.label_prediction_properties import _count_classes_by_segment_in_image, _count_pred_classes_by_segment_in_image, _get_predicted_classes_per_image_semantic_segmentation, _get_samples_per_class_semantic_segmentation, _get_segment_area, _get_segment_pred_area
label_desc: Use image node_id 4 for calling a global function with example usage: test_get_segment_pred_area() without return types