code: def load_labels_map(
      self,
      num_classes: Optional[int] = None,
      labels_map: Optional[Dict[int, Tuple[int, int, int]]] = None,
  ) -> None:
      if num_classes is not None:
          self.num_classes = num_classes
          labels_map = (
              labels_map
              or SegmentationLabelsOutput.create_random_labels_map(
                  num_classes
              )
          )
  
      if labels_map is not None:
          self.labels_map = labels_map
  
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 1 for calling the SemanticSegmentationInput obj's underlying member method code with example usage: obj.load_labels_map(num_classes, labels_map) without return types