docstr: initialize with the necessary elements
  Args:
      lang(str): the selection of languages
      det(bool): Whether to use text detector.
      rec(bool): Whether to use text recognizer.
      use_angle_cls(bool): Whether to use text orientation classifier.
      enable_mkldnn(bool): Whether to enable mkldnn.
      use_gpu (bool): Whether to use gpu.
      box_thresh(float): the threshold of the detected text box's confidence
      angle_classification_thresh(float): the threshold of the angle classification confidence
docstr_tok: ["initialize","with","the","necessary","elements","Args",":","lang","(","str",")",":","the","selection","of","languages","det","(","bool",")",":","Whether","to","use","text","detector",".","rec","(","bool",")",":","Whether","to","use","text","recognizer",".","use_angle_cls","(","bool",")",":","Whether","to","use","text","orientation","classifier",".","enable_mkldnn","(","bool",")",":","Whether","to","enable","mkldnn",".","use_gpu","(","bool",")",":","Whether","to","use","gpu",".","box_thresh","(","float",")",":","the","threshold","of","the","detected","text","box","'s","confidence","angle_classification_thresh","(","float",")",":","the","threshold","of","the","angle","classification","confidence"]
code: def __init__(
      self,
      lang="ch",
      det=True,
      rec=True,
      use_angle_cls=False,
      enable_mkldnn=False,
      use_gpu=False,
      box_thresh=0.6,
      angle_classification_thresh=0.9,
  ):
      """
      initialize with the necessary elements
      Args:
          lang(str): the selection of languages
          det(bool): Whether to use text detector.
          rec(bool): Whether to use text recognizer.
          use_angle_cls(bool): Whether to use text orientation classifier.
          enable_mkldnn(bool): Whether to enable mkldnn.
          use_gpu (bool): Whether to use gpu.
          box_thresh(float): the threshold of the detected text box's confidence
          angle_classification_thresh(float): the threshold of the angle classification confidence
      """
      self.lang = lang
      self.logger = get_logger()
      self.det = det
      self.rec = rec
      self.use_angle_cls = use_angle_cls
      self.engine = PaddleOCR(
          lang=lang,
          det=det,
          rec=rec,
          use_angle_cls=use_angle_cls,
          enable_mkldnn=enable_mkldnn,
          use_gpu=use_gpu,
          det_db_box_thresh=box_thresh,
          cls_thresh=angle_classification_thresh,
      )
      self.det_model_dir = self.engine.text_detector.args.det_model_dir
      self.rec_model_dir = self.engine.text_detector.args.rec_model_dir
      self.cls_model_dir = self.engine.text_detector.args.cls_model_dir
  
file_path: PaddleHub/modules/image/text_recognition/multi_languages_ocr_db_crnn/module.py
imports: import argparse
  import os
  import ast
  import paddle
  import paddle.static
  import paddle2onnx
  import paddle2onnx
  from paddleocr import PaddleOCR
  from paddleocr.ppocr.utils.logging import get_logger
  from paddleocr.tools.infer.utility import base64_to_cv2
  from paddlehub.module.module import moduleinfo, runnable, serving
  from .utils import read_images, save_result_image, mkdir
label_desc: Use image node_id 1 to create a new MultiLangOCR object  with example: obj = MultiLangOCR(lang, det, rec, use_angle_cls, enable_mkldnn, use_gpu, box_thresh, angle_classification_thresh)