code: def __init__(self, args):
      self.args = args
      self.cfg = DeployConfig(args.config, args.vertical_screen)
      self.compose = T.Compose(self.cfg.transforms)
  
      pred_cfg = PredictConfig(self.cfg.model, self.cfg.params)
      pred_cfg.disable_glog_info()
      if self.args.use_gpu:
          pred_cfg.enable_use_gpu(100, 0)
  
      self.predictor = create_predictor(pred_cfg)
      if self.args.test_speed:
          self.cost_averager = TimeAverager()
  
      if args.use_optic_flow:
          self.disflow = cv2.DISOpticalFlow_create(
              cv2.DISOPTICAL_FLOW_PRESET_ULTRAFAST
          )
          width, height = self.cfg.target_size()
          self.prev_gray = np.zeros((height, width), np.uint8)
          self.prev_cfd = np.zeros((height, width), np.float32)
          self.is_first_frame = True
  
imports: import codecs
  import os
  import sys
  import time
  import yaml
  import numpy
  import cv2
  import paddle
  from paddle.inference import create_predictor, PrecisionType
  from paddle.inference import Config
  import paddleseg.transforms
  from paddleseg.core.infer import reverse_transform
  from paddleseg.cvlibs import manager
  from paddleseg.utils import TimeAverager
  from optic_flow_process import optic_flow_process
label_desc: Use image node_id 1 to create a new Predictor object  with example: obj = Predictor(args)