code: def load_data(
      self,
      folder: PATH_TYPE,
      target_formatter: Optional[TargetFormatter] = None,
  ) -> List[Dict[str, Any]]:
      files, targets = make_dataset(
          folder, extensions=IMG_EXTENSIONS + NP_EXTENSIONS
      )
      return super().load_data(
          files, targets, target_formatter=target_formatter
      )
  
imports: import os
  from typing import Any, Callable, Dict, List, Optional, Union
  import pandas
  from flash.core.data.io.classification_input import ClassificationInputMixin
  from flash.core.data.io.input import DataKeys
  from flash.core.data.utilities.classification import MultiBinaryTargetFormatter, TargetFormatter
  from flash.core.data.utilities.data_frame import resolve_files, resolve_targets
  from flash.core.data.utilities.loading import load_data_frame
  from flash.core.data.utilities.paths import PATH_TYPE, filter_valid_files, make_dataset
  from flash.core.data.utilities.samples import to_samples
  from flash.core.integrations.fiftyone.utils import FiftyOneLabelUtilities
  from flash.core.utilities.imports import _FIFTYONE_AVAILABLE, lazy_import, requires
  from flash.image.data import IMG_EXTENSIONS, NP_EXTENSIONS, ImageFilesInput, ImageInput, ImageNumpyInput, ImageTensorInput
label_desc: Use image node_id 1 for calling the ImageClassificationFolderInput obj's underlying member method code with example usage: obj.load_data(folder, target_formatter) and returns: super