code: def get_df_unique_classes(data: pd.DataFrame):
      """
      Get the unique classes in the dataframe for object detection
      Parameters
      ----------
      data
          pd.DataFrame holding the data for object detection
      Returns
      -------
          list of unique classes
      """
      unique_classes = {}
      for idx in range(data.shape[0]):
          row = data.iloc[idx]
          rois = row["rois"]
          for roi in rois:
              _, _, _, _, class_label = roi
              if class_label not in unique_classes:
                  unique_classes[class_label] = len(unique_classes)
      return list(unique_classes.keys())
  
imports: import json
  import logging
  import os
  import warnings
  from pathlib import Path
  from typing import Dict, Iterable, List, Optional, Union
  import defusedxml.ElementTree
  import numpy
  import pandas
  import PIL
  from torchmetrics.detection.mean_ap import MeanAveragePrecision
  from ..constants import BBOX, LABEL, MAP, MAP_50, MAP_75, MAP_LARGE, MAP_MEDIUM, MAP_SMALL, MAR_1, MAR_10, MAR_100, MAR_LARGE, MAR_MEDIUM, MAR_SMALL, MEAN_AVERAGE_PRECISION
  from .download import download, is_url
label_desc: Use image node_id 2 for calling a global function with example usage: get_df_unique_classes(data) and returns: list