code: def predict_load_sample(
      self, sample: Dict[str, Any]
  ) -> Dict[str, Any]:
      if isinstance(sample[DataKeys.INPUT], BaseRecord):
          return self.load_sample(sample)
      filepath = sample[DataKeys.INPUT]
      image = np.array(load_image(filepath))
  
      record = BaseRecord([FilepathRecordComponent()])
      record.filepath = filepath
      record.set_img(image)
      record.add_component(
          ClassMapRecordComponent(task=tasks.detection)
      )
      return from_icevision_record(record)
  
file_path: lightning-flash/src/flash/core/integrations/icevision/data.py
imports: import inspect
  from typing import Any, Callable, Dict, List, Optional, Type, Union
  import numpy
  from flash.core.data.io.input import DataKeys, Input
  from flash.core.data.utilities.loading import IMG_EXTENSIONS, NP_EXTENSIONS, load_image
  from flash.core.data.utilities.paths import list_valid_files
  from flash.core.integrations.icevision.transforms import from_icevision_record
  from flash.core.utilities.imports import _ICEVISION_AVAILABLE, requires
label_desc: Use image node_id 4 for calling the IceVisionInput obj's underlying member method code with example usage: obj.predict_load_sample(sample) and returns: from_icevision_record, self