python 利用百度API识别图片文字（多线程版）

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
\"\"\"
Created on Tue Jun 12 09:37:38 2018
利用百度api实现图片文本识别
@author: XnCSD
\"\"\"

import glob
from os import path
import os
from aip import AipOcr
from PIL import Image
from queue import Queue
import threading
import datetime

def convertimg(picfile, outdir):
  \'\'\'调整图片大小，对于过大的图片进行压缩
  picfile:  图片路径
  outdir：  图片输出路径
  \'\'\'
  img = Image.open(picfile)
  width, height = img.size
  while (width * height > 4000000): # 该数值压缩后的图片大约 两百多k
    width = width // 2
    height = height // 2
  new_img = img.resize((width, height), Image.BILINEAR)
  new_img.save(path.join(outdir, os.path.basename(picfile)))


def baiduOCR(ts_queue):
  \"\"\"利用百度api识别文本，并保存提取的文字
  picfile:  图片文件名
  outfile:  输出文件
  \"\"\"
  while not ts_queue.empty():
    picfile = ts_queue.get()
    filename = path.basename(picfile)
    outfile = \'D:\\Study\\pythonProject\\scrapy\\IpProxy\\port_zidian.txt\'
    APP_ID = \'\' # 刚才获取的 ID，下同
    API_KEY = \'\'
    SECRECT_KEY = \'\'
    client = AipOcr(APP_ID, API_KEY, SECRECT_KEY)

    i = open(picfile, \'rb\')
    img = i.read()
    print(\"正在识别图片：\\t\" + filename)
    message = client.basicGeneral(img) # 通用文字识别，每天 50 000 次免费
    # message = client.basicAccurate(img)  # 通用文字高精度识别，每天 800 次免费
    #print(\"识别成功！\")
    i.close()
    try:
      filename1 = filename.split(\'.\')[0]
      filename1 = \'\'.join(filename1)
      with open(outfile, \'a+\') as fo:
        for text in message.get(\'words_result\'):
          fo.writelines(\'\\\'\' + filename1 + \'\\\'\' + \':\' + text.get(\'words\') + \',\')
          fo.writelines(\'\\n\')
        # fo.writelines(\"+\" * 60 + \'\\n\')
        # fo.writelines(\"识别图片：\\t\" + filename + \"\\n\" * 2)
        # fo.writelines(\"文本内容：\\n\")
        # # 输出文本内容
        # for text in message.get(\'words_result\'):
        #   fo.writelines(text.get(\'words\') + \'\\n\')
        # fo.writelines(\'\\n\' * 2)
      os.remove(filename)
      print(\"识别成功！\")
    except:
      print(\'识别失败\')



    print(\"文本导出成功！\")
    print()
def duqu_tupian(dir):
  ts_queue = Queue(10000)

  outdir = dir
  # if path.exists(outfile):
  #   os.remove(outfile)
  if not path.exists(outdir):
    os.mkdir(outdir)
  print(\"压缩过大的图片...\")
  # 首先对过大的图片进行压缩，以提高识别速度，将压缩的图片保存与临时文件夹中
  try:
    for picfile in glob.glob(r\"D:\\Study\\pythonProject\\scrapy\\IpProxy\\端口\\*\"):
      convertimg(picfile, outdir)
    print(\"图片识别...\")
    for picfile in glob.glob(\"tmp/*\"):
      ts_queue.put(picfile)
      #baiduOCR(picfile, outfile)
      #os.remove(picfile)
    print(\'图片文本提取结束！文本输出结果位于文件中。\' )
    #os.removedirs(outdir)
    return ts_queue
  except:
    print(\'失败\')

if __name__ == \"__main__\":

  start = datetime.datetime.now().replace(microsecond=0)
  t = \'tmp\'
  s = duqu_tupian(t)
  threads = []
  for i in range(100):
    t = threading.Thread(target=baiduOCR, name=\'th-\' + str(i), kwargs={\'ts_queue\': s})
    threads.append(t)
  for t in threads:
    t.start()
  for t in threads:
    t.join()
  end = datetime.datetime.now().replace(microsecond=0)
  print(\'删除耗时：\' + str(end - start))