code: def find_noun_phrases(caption: str) -> list:
      """Find noun phrases in a caption using nltk.
      Args:
          caption (str): The caption to analyze.
  
      Returns:
          list: List of noun phrases found in the caption.
  
      Examples:
          >>> caption = 'There is two cat and a remote in the picture'
          >>> find_noun_phrases(caption) # ['cat', 'a remote', 'the picture']
      """
      try:
          import nltk
  
          nltk.download("punkt", download_dir="~/nltk_data")
          nltk.download(
              "averaged_perceptron_tagger", download_dir="~/nltk_data"
          )
      except ImportError:
          raise RuntimeError(
              "nltk is not installed, please install it by: "
              "pip install nltk."
          )
  
      caption = caption.lower()
      tokens = nltk.word_tokenize(caption)
      pos_tags = nltk.pos_tag(tokens)
  
      grammar = "NP: {<DT>?<JJ.*>*<NN.*>+}"
      cp = nltk.RegexpParser(grammar)
      result = cp.parse(pos_tags)
  
      noun_phrases = []
      for subtree in result.subtrees():
          if subtree.label() == "NP":
              noun_phrases.append(
                  " ".join(t[0] for t in subtree.leaves())
              )
  
      return noun_phrases
  
imports: import copy
  import re
  import warnings
  from typing import Optional, Tuple, Union
  import torch
  from torch import Tensor
  from mmdet.registry import MODELS
  from mmdet.structures import SampleList
  from mmdet.utils import ConfigType, OptConfigType, OptMultiConfig
  from .single_stage import SingleStageDetector
label_desc: Use image node_id 1 for calling a global function with example usage: find_noun_phrases(caption) and returns: noun_phrases