code: def detect_multilabel(labels: Union[List, np.ndarray]):
      if isinstance(labels, (np.ndarray, list, tuple)):
          labels = np.unique(labels)
      else:
          raise UserWarning(
              f"expect data type for label was list or np.ndarray but got {type(labels)}"
          )
  
      if len(labels) > 2:
          return True
      return False
  
file_path: chitra/chitra/visualization/metrics.py
imports: from itertools import product
  from typing import List, Union
  import matplotlib.pyplot
  import numpy
  from sklearn.metrics import confusion_matrix
  from chitra.logging import logger
label_desc: Use image node_id 1 for calling a global function with example usage: detect_multilabel(labels) and returns: False, True