code: def get_salt_existence():
      train_mask = pd.read_csv(settings.LABEL_FILE)
      salt_exists_dict = {}
      for row in train_mask.values:
          salt_exists_dict[row[0]] = (
              0 if (row[1] is np.nan or len(row[1]) < 1) else 1
          )
      return salt_exists_dict
  
imports: import os
  import json
  import sys
  import time
  import numpy
  import pandas
  from PIL import Image
  from tqdm import tqdm
  from pycocotools import mask
  from sklearn.model_selection import KFold
  import settings
label_desc: Use image node_id 6 for calling a global function with example usage: get_salt_existence() and returns: salt_exists_dict