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"]
docstr: Raises:
      ValueError: loaded model not in supported model type
code: def check_model(self, yml_conf):
      """
      Raises:
          ValueError: loaded model not in supported model type
      """
      for support_model in SUPPORT_MODELS:
          if support_model in yml_conf["arch"]:
              return True
      raise ValueError(
          "Unsupported arch: {}, expect {}".format(
              yml_conf["arch"], SUPPORT_MODELS
          )
      )
  
imports: import glob
  import json
  import math
  import os
  from pathlib import Path
  import cv2
  import numpy
  import yaml
  from paddle.inference import Config
  from paddle.inference import create_predictor
  from .keypoint_preprocess import EvalAffine
  from .keypoint_preprocess import expand_crop
  from .keypoint_preprocess import TopDownEvalAffine
  from .preprocess import decode_image
  from .preprocess import LetterBoxResize
  from .preprocess import NormalizeImage
  from .preprocess import Pad
  from .preprocess import PadStride
  from .preprocess import Permute
  from .preprocess import preprocess
  from .preprocess import Resize
  from .preprocess import WarpAffine
  from .visualize import visualize_box
label_desc: Use image node_id 2 for calling the PredictConfig obj's underlying member method code with example usage: obj.check_model(yml_conf) and returns: True