class_docstr: A dataset from images from a single scene.
class_docstr_tok: ["A","dataset","from","images","from","a","single","scene","."]
code: def __getitem__(self, index) -> FrameData:
      if index >= len(self):
          raise IndexError(f"index {index} out of range {len(self)}")
      image = self.images[index]
      pose = self.poses[index]
      frame_type = self.frame_types[index]
      fg_probability = (
          None
          if self.fg_probabilities is None
          else self.fg_probabilities[index]
      )
  
      frame_data = FrameData(
          frame_number=index,
          sequence_name=_SINGLE_SEQUENCE_NAME,
          sequence_category=self.object_name,
          camera=pose,
          # pyre-ignore
          image_size_hw=torch.tensor(image.shape[1:], dtype=torch.long),
          image_rgb=image,
          fg_probability=fg_probability,
          frame_type=frame_type,
      )
      return frame_data
  
imports: from dataclasses import field
  from typing import Iterable, Iterator, List, Optional, Sequence, Tuple
  import numpy
  import torch
  from pytorch3d.implicitron.tools.config import Configurable, expand_args_fields, run_auto_creation
  from pytorch3d.renderer import CamerasBase, join_cameras_as_batch, PerspectiveCameras
  from .dataset_base import DatasetBase
  from .dataset_map_provider import DatasetMap, DatasetMapProviderBase, PathManagerFactory
  from .frame_data import FrameData
  from .utils import DATASET_TYPE_KNOWN, DATASET_TYPE_UNKNOWN
label_desc: Use image node_id 4 for calling the SingleSceneDataset obj's underlying member method code with example usage: obj.__getitem__(index) and returns: frame_data