code: def test_extract_features_fridge_metadata(self):
      data = load_fridge_dataset()
      extracted_features, feature_names = extract_dataset_features(data)
      expected_feature_names = [
          MEAN_PIXEL_VALUE
      ] + FRIDGE_METADATA_FEATURES
      validate_extracted_features(
          extracted_features,
          feature_names,
          expected_feature_names,
          data,
      )
  
file_path: responsible-ai-toolbox/responsibleai_vision/tests/test_feature_extractors.py
imports: from common_vision_utils import load_flowers_dataset, load_fridge_dataset, load_fridge_object_detection_dataset, load_imagenet_dataset
  from responsibleai.feature_metadata import FeatureMetadata
  from responsibleai_vision.common.constants import ExtractedFeatures, ImageColumns, ImageModes
  from responsibleai_vision.utils.feature_extractors import extract_features
label_desc: Use image node_id 2 for calling the TestFeatureExtractors obj's underlying member method code with example usage: obj.test_extract_features_fridge_metadata() without return types