code: def test_object_detection_metrics(self, metric):
      y_true = np.array([[[0, 0, 0, 0, 0], [0, 0, 0, 0, 0]]])
      y_pred = np.array([[[0, 0, 0, 0, 0], [0, 0, 0, 0, 0]]])
      if metric == Metrics.ERROR_RATE:
          diff = np.array(
              [
                  len(
                      ErrorLabeling(
                          ModelTask.OBJECT_DETECTION,
                          y_pred[image_idx],
                          y_true[image_idx],
                      ).compute_error_list()
                  )
                  > 0
                  for image_idx in range(len(y_true))
              ]
          )
          metric_value = metric_to_func[metric](y_true, y_pred, diff)
      else:
          metric_value = metric_to_func[metric](y_true, y_pred)
      assert isinstance(metric_value, float)
  
file_path: responsible-ai-toolbox/erroranalysis/tests/test_metrics.py
imports: import logging
  import numpy
  import pytest
  from erroranalysis._internal.constants import Metrics, ModelTask, binary_classification_metrics, multiclass_classification_metrics, object_detection_metrics, regression_metrics
  from erroranalysis._internal.metrics import metric_to_func
label_desc: Use image node_id 5 for calling the TestMetrics obj's underlying member method code with example usage: obj.test_object_detection_metrics(metric) without return types