code: def is_rois_input(sample):
      """
      check if a sample is rois for object detection
  
      Parameters
      ----------
      sample
          The sampled data.
  
      Returns
      -------
      bool, whether a sample is rois for object detection
      """
      return (
          isinstance(sample, list)
          and len(sample)
          and isinstance(sample[0], list)
          and len(sample[0]) == 5
      )
  
imports: import ast
  import codecs
  import copy
  import re
  import warnings
  from io import BytesIO
  from typing import Callable, Dict, Iterable, List, Optional, Tuple, Union
  import numpy
  import pandas
  import PIL
  from omegaconf import ListConfig
  from text_unidecode import unidecode
  from timm.data.constants import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD, IMAGENET_INCEPTION_MEAN, IMAGENET_INCEPTION_STD
  from tokenizers import pre_tokenizers
  from torchvision import transforms
  from ..constants import CLIP_IMAGE_MEAN, CLIP_IMAGE_STD, IDENTIFIER, IMAGE, IMAGE_BYTEARRAY, IMAGE_PATH, MMDET_IMAGE, MMLAB_MODELS
  from .collator import DictCollator
  from .preprocess_dataframe import MultiModalFeaturePreprocessor
  from .randaug import RandAugment
  from .trivial_augmenter import TrivialAugment
label_desc: Use image node_id 11 for calling a global function with example usage: is_rois_input(sample) and returns: unknown