code: def test_cohort_filter_object_detection(self):
      model_task = ModelTask.OBJECT_DETECTION
      model = get_object_detection_fridge_model()
  
      dataset = load_fridge_object_detection_dataset()
      X_test = dataset[[ImageColumns.IMAGE]]
      y_test = dataset[[ImageColumns.LABEL]]
      validation_data = create_validation_data(X_test, y_test)
  
      feature_names = [ImageColumns.IMAGE]
  
      run_error_analyzer(
          validation_data,
          model,
          X_test,
          y_test,
          feature_names,
          categorical_features=[],
          model_task=model_task,
      )
  
imports: import numpy
  import pandas
  import pytest
  from erroranalysis._internal.cohort_filter import filter_from_cohort
  from erroranalysis._internal.constants import ARG, COLUMN, METHOD, PRED_Y, ROW_INDEX, TRUE_Y, ImageColumns, ModelTask
  from erroranalysis._internal.error_analyzer import ModelAnalyzer
  from rai_test_utils.datasets.tabular import create_diabetes_data, create_iris_data, create_simple_titanic_data
  from rai_test_utils.datasets.vision import load_fridge_object_detection_dataset
  from rai_test_utils.models.sklearn import create_sklearn_random_forest_regressor, create_sklearn_svm_classifier, create_titanic_pipeline
  from rai_test_utils.models.torch import get_object_detection_fridge_model
  from raiutils.cohort import CohortFilterMethods
label_desc: Use image node_id 14 for calling the TestCohortFilter obj's underlying member method code with example usage: obj.test_cohort_filter_object_detection() without return types