class_docstr: Simple container holding classification labels of a particular tensor.
  
  Example usage:
    # The first added label list can be used as category names as needed.
    labels = Labels()
      .add(['/m/011l78', '/m/031d23'])
      .add(['cat', 'dog], 'en')
      .add(['chat', 'chien], 'fr')
class_docstr_tok: ["Simple","container","holding","classification","labels","of","a","particular","tensor",".","Example","usage",":","#","The","first","added","label","list","can","be","used","as","category","names","as","needed",".","labels","=","Labels","(",")",".add","(","[","'\/m\/011l78","'",",","'\/m\/031d23","'","]",")",".add","(","[","'cat","'",",","'dog","]",",","'en","'",")",".add","(","[","'chat","'",",","'chien","]",",","'fr","'",")"]
code: def __init__(self) -> None:
      self._labels = []
  
imports: import collections
  import csv
  import dataclasses
  import os
  import tempfile
  from typing import List, Optional, Tuple, Union
  import flatbuffers
  from mediapipe.tasks.metadata import metadata_schema_py_generated
  from mediapipe.tasks.python.metadata import metadata
  from mediapipe.tasks.python.metadata.metadata_writers import metadata_info
  from mediapipe.tasks.python.metadata.metadata_writers import writer_utils
label_desc: Use image node_id 1 to create a new Labels object from inherited base classes: object with example: obj = Labels()