text: # -*- coding: utf-8 -*-
  import os
  from unittest import result
  import numpy as np
  import cv2
  import imgproc
  from tesserocr import PyTessBaseAPI
  
  # borrowed from https://github.com/lengstrom/fast-style-transfer/blob/master/src/utils.py
  def get_files(img_dir):
      imgs, masks, xmls = list_files(img_dir)
      return imgs, masks, xmls
  
  def list_files(in_path):
      img_files = []
      mask_files = []
      gt_files = []
      for (dirpath, dirnames, filenames) in os.walk(in_path):
          for file in filenames:
              filename, ext = os.path.splitext(file)
              ext = str.lower(ext)
              if ext == '.jpg' or ext == '.jpeg' or ext == '.gif' or ext == '.png' or ext == '.pgm':
                  img_files.append(os.path.join(dirpath, file))
              elif ext == '.bmp':
                  mask_files.append(os.path.join(dirpath, file))
              elif ext == '.xml' or ext == '.gt' or ext == '.txt':
                  gt_files.append(os.path.join(dirpath, file))
              elif ext == '.zip':
                  continue
      # img_files.sort()
      # mask_files.sort()
      # gt_files.sort()
      return img_files, mask_files, gt_files
  
  # crop and pass each bounding box through tesserocr - dylan-roussin
  # def read_image():
  #     print(boxes)
  
  
  
  
  # save result
  def saveResult(img_file, img, boxes, dirname='./result/', verticals=None, texts=None):
          """ save text detection result one by one
          Args:
              img_file (str): image file name
              img (array): raw image context
              boxes (array): array of result file
                  Shape: [num_detections, 4] for BB output / [num_detections, 4] for QUAD output
          Return:
              None
          """
          img = np.array(img)
  
          # make result file list
          filename, file_ext = os.path.splitext(os.path.basename(img_file))
  
          # result directory
          res_file = dirname + "res_" + filename + '.txt'
          res_img_file = dirname + "res_" + filename + '.jpg'
  
          if not os.path.isdir(dirname):
              os.mkdir(dirname)
  
          with open(res_file, 'w') as f:
              for i, box in enumerate(boxes):
                  poly = np.array(box).astype(np.int32).reshape((-1))
                  strResult = ','.join([str(p) for p in poly]) + '\r\n'
                  f.write(strResult)
  
                  poly = poly.reshape(-1, 2)
                  cv2.polylines(img, [poly.reshape((-1, 1, 2))], True, color=(0, 255, 0), thickness=2)
                  ptColor = (0, 255, 255)
                  if verticals is not None:
                      if verticals[i]:
                          ptColor = (255, 0, 0)
                  
                  if texts is not None:
                      font = cv2.FONT_HERSHEY_SIMPLEX
                      font_scale = 0.5
                      cv2.putText(img, "{}".format(texts[i]), (poly[0][0]+1, poly[0][1]+1), font, font_scale, (0, 0, 0), thickness=1)
                      cv2.putText(img, "{}".format(texts[i]), tuple(poly[0]), font, font_scale, (0, 255, 255), thickness=1)
  
          # Save result image
          cv2.imwrite(res_img_file, img)
  
  