code: def __init__(self):
      self.default_pretrained_model_path = os.path.join(
          self.directory, "humanseg_lite_inference", "model"
      )
      self._set_config()
  
imports: import argparse
  import ast
  import os
  import os.path
  import cv2
  import numpy
  import paddle.jit
  import paddle.static
  from paddle.inference import Config
  from paddle.inference import create_predictor
  from .data_feed import preprocess_v
  from .data_feed import reader
  from .optimal import postprocess_v
  from .optimal import threshold_mask
  from .processor import base64_to_cv2
  from .processor import check_dir
  from .processor import cv2_to_base64
  from .processor import postprocess
  from paddlehub.module.module import moduleinfo
  from paddlehub.module.module import runnable
  from paddlehub.module.module import serving
label_desc: Use image node_id 1 to create a new ShufflenetHumanSeg object  with example: obj = ShufflenetHumanSeg()