code: def __init__(self):
      self.default_pretrained_model_path = os.path.join(
          self.directory, "pose-resnet50-mpii-384x384", "model"
      )
      self._set_config()
  
imports: from __future__ import absolute_import
  from __future__ import division
  import ast
  import os
  import argparse
  import paddle
  import paddle.jit
  import paddle.static
  import numpy
  from paddle.inference import Config, create_predictor
  from paddlehub.module.module import moduleinfo, runnable, serving
  from .processor import base64_to_cv2, postprocess
  from .data_feed import reader
label_desc: Use image node_id 1 to create a new HumanPoseEstimation object  with example: obj = HumanPoseEstimation()