class_docstr: set config of preprocess, postprocess and visualize
  Args:
      model_dir (str): root path of model.yml
class_docstr_tok: ["set","config","of","preprocess",",","postprocess","and","visualize","Args",":","model_dir","(","str",")",":","root","path","of","model.yml"]
code: def print_config(self):
      print("-----------  Model Configuration -----------")
      print("%s: %s" % ("Model Arch", self.arch))
      print("%s: " % ("Transform Order"))
      for op_info in self.preprocess_infos:
          print("--%s: %s" % ("transform op", op_info["type"]))
      print("--------------------------------------------")
  
imports: import math
  import os
  import cv2
  import numpy
  import yaml
  from .infer import Detector
  from .keypoint_postprocess import HRNetPostProcess
  from .keypoint_preprocess import expand_crop
  from .visualize import visualize_pose
label_desc: Use image node_id 3 for calling the PredictConfig_KeyPoint obj's underlying member method code with example usage: obj.print_config() without return types