code: def __init__(self):
      self.default_pretrained_model_path = os.path.join(
          self.directory, "ace2p_human_parsing", "model"
      )
      # label list
      label_list_file = os.path.join(self.directory, "label_list.txt")
      with open(label_list_file, "r") as file:
          content = file.read()
      self.label_list = content.split("\n")
      # palette used in postprocess
      self.palette = get_palette(len(self.label_list))
      self._set_config()
  
imports: from __future__ import absolute_import
  from __future__ import division
  import ast
  import argparse
  import os
  import numpy
  import paddle
  import paddle.jit
  import paddle.static
  from paddle.inference import Config, create_predictor
  from paddlehub.module.module import moduleinfo, runnable, serving
  from .processor import get_palette, postprocess, base64_to_cv2, cv2_to_base64
  from .data_feed import reader
label_desc: Use image node_id 1 to create a new ACE2P object  with example: obj = ACE2P()