code: def get_char_dataset(
      config: dict,
  ) -> video_to_text.VideoToCharDataset:
      """
      Instantiates a Character Encoding based VideoToCharDataset.
  
      Args:
          config: Config of the VideoToCharDataset.
  
      Returns:
          An instance of VideoToCharDataset.
      """
      if "labels" not in config:
          logging.warning(
              f"dataset does not have explicitly defined labels"
          )
  
      dataset = video_to_text.VideoToCharDataset(
          manifest_filepath=config["manifest_filepath"],
          labels=config.get("labels", None),
          int_values=config.get("int_values", False),
          max_duration=config.get("max_duration", None),
          min_duration=config.get("min_duration", None),
          max_utts=config.get("max_utts", 0),
          blank_index=config.get("blank_index", -1),
          unk_index=config.get("unk_index", -1),
          normalize=config.get("normalize_transcripts", False),
          trim=config.get("trim_silence", False),
          parser=config.get("parser", "en"),
          return_sample_id=config.get("return_sample_id", False),
          channel_selector=config.get("channel_selector", None),
      )
      return dataset
  
file_path: NeMo/nemo/collections/multimodal/speech_cv/data/video_to_text_dataset.py
imports: from math import isclose
  from typing import Optional
  from omegaconf import DictConfig
  from nemo.collections.asr.data.audio_to_text_dataset import convert_to_config_list, get_chain_dataset
  from nemo.collections.multimodal.speech_cv.data import video_to_text
  from nemo.utils import logging
label_desc: Use image node_id 4 for calling a global function with example usage: get_char_dataset(config) and returns: dataset