code: def load_sample(self, sample: Dict[str, Any]) -> Dict[str, Any]:
      filepath = sample[DataKeys.INPUT]
      sample = super().load_sample(sample)
      if not self.predicting:
          fo_dataset = fo.load_dataset(self._fo_dataset_name)
          fo_sample = fo_dataset[filepath]
          sample[DataKeys.TARGET] = fo_sample[self.label_field].mask
      return sample
  
imports: import os
  from typing import Any, Dict, List, Optional, Tuple, 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 PATH_TYPE, filter_valid_files
  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
  from flash.image.data import ImageFilesInput, ImageNumpyInput, ImageTensorInput
  from flash.image.segmentation.output import SegmentationLabelsOutput
label_desc: Use image node_id 3 for calling the SemanticSegmentationFiftyOneInput obj's underlying member method code with example usage: obj.load_sample(sample) and returns: sample