code: def from_folders(
      cls,
      predict_folder: Optional[str] = None,
      predict_transform: INPUT_TRANSFORM_TYPE = FaceDetectionInputTransform,
      input_cls: Type[Input] = ImageClassificationFolderInput,
      transform_kwargs: Optional[Dict] = None,
      **data_module_kwargs: Any,
  ) -> "FaceDetectionData":
      return cls(
          predict_input=input_cls(
              RunningStage.PREDICTING, predict_folder
          ),
          transform=predict_transform,
          transform_kwargs=transform_kwargs,
          **data_module_kwargs,
      )
  
file_path: lightning-flash/src/flash/image/face_detection/data.py
imports: from typing import Any, Dict, Optional, Sequence, Type
  from torch.utils.data import Dataset
  from flash.core.data.data_module import DataModule
  from flash.core.data.io.input import Input
  from flash.core.utilities.stability import beta
  from flash.core.utilities.stages import RunningStage
  from flash.core.utilities.types import INPUT_TRANSFORM_TYPE
  from flash.image.classification.data import ImageClassificationFilesInput, ImageClassificationFolderInput
  from flash.image.face_detection.input import FaceDetectionInput
  from flash.image.face_detection.input_transform import FaceDetectionInputTransform
label_desc: Use image node_id 3 for calling the FaceDetectionData obj's underlying member method code with example usage: obj.from_folders(cls, predict_folder, predict_transform, input_cls, transform_kwargs) and returns: cls