code: def create_submission(meta, predictions):
      output = []
      for image_id, mask in zip(meta["id"].values, predictions):
          rle_encoded = " ".join(
              str(rle) for rle in run_length_encoding(mask)
          )
          output.append([image_id, rle_encoded])
  
      submission = pd.DataFrame(
          output, columns=["id", "rle_mask"]
      ).astype(str)
      return submission
  
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 1 for calling a global function with example usage: create_submission(meta, predictions) and returns: submission