text: import glob
  import os
  import shutil
  import sys
  import time
  import cv2
  import numpy as np
  import tensorflow as tf
  from lib.detect.text_2_line_detector import *
  from lib.detect.plateDetector import *
  from lib.lprNet.run_lprnet import *
  
  sys.path.append('.')
  
  def get_low_box(coods):
      temp = []
      for i in range(0, len(coods)):
          box = coods[i]
          y_max = max(int(box[1]), int(box[3]))
          temp.append(y_max)
      if temp:
          return temp.index(max(temp))
      return temp
  
  
  def getPlate_OCR(img):
      
      detect_output_full = get_license_plate_full(img, detection_graph_full)
      for coordinate_full, label in detect_output_full.items():
          license_plate_image_full = img[int(coordinate_full[1]):int(coordinate_full[3]), int(coordinate_full[0]):int(coordinate_full[2])]
  
      detect_output_low = get_license_plate_low(img, detection_graph_low)
  
      if len(detect_output_low.values()) == 2:
          multi_box = []
  
          for coordinate_low, label in detect_output_low.items():
              start = time.time()
              multi_box.append(coordinate_low)
          low_box = get_low_box(multi_box)
          box_new = multi_box[low_box]
          license_plate_image_low = img[int(box_new[1]):int(box_new[3]), int(box_new[0]):int(box_new[2])]
          detected_list = extract_license_number(license_plate_image_low)
  
      return detected_list, full_license_plate_image, license_plate_image_low
  
  
  