python批量识别图片指定区域文字内容

pip install aircv

pip install Pillow

sudo apt-get install libpng12-dev 
sudo apt-get install libjpeg62-dev 
sudo apt-get install libtiff4-dev 
sudo apt-get install gcc 
sudo apt-get install g++ 
sudo apt-get install automake

sudo apt-get install tesseract-ocr

pip install pytesseract

#!/usr/bin/python2.7 
# -*- coding: utf-8 -*- 
import aircv


def matchImg(imgsrc, imgobj, confidence=0.2):
 """
  图片对比识别imgobj在imgsrc上的相对位置（批量识别统一图片中需要的部分）
 :param imgsrc: 原始图片路径(str)
 :param imgobj: 待查找图片路径（模板）(str)
 :param confidence: 识别度（0<confidence<1.0）
 :return: None or dict({'confidence': 相似度(float), 'rectangle': 原始图片上的矩形坐标(tuple), 'result': 中心坐标(tuple)})
 """
 imsrc = aircv.imread(imgsrc)
 imobj = aircv.imread(imgobj)

 match_result = aircv.find_template(imsrc, imobj,
         confidence) # {'confidence': 0.5435812473297119, 'rectangle': ((394, 384), (394, 416), (450, 384), (450, 416)), 'result': (422.0, 400.0)}
 if match_result is not None:
  match_result['shape'] = (imsrc.shape[1], imsrc.shape[0]) # 0为高，1为宽

 return match_result

#!/usr/bin/python2.7 
# -*- coding: utf-8 -*- 
from PIL import Image, ImageEnhance

def cutImg(imgsrc, out_img_name, coordinate):
 """
  根据坐标位置剪切图片
 :param imgsrc: 原始图片路径(str)
 :param out_img_name: 剪切输出图片路径(str)
 :param coordinate: 原始图片上的坐标(tuple) egg:(x, y, w, h) ---> x,y为矩形左上角坐标, w,h为右下角坐标
 :return:
 """
 image = Image.open(imgsrc)
 region = image.crop(coordinate)
 region = ImageEnhance.Contrast(region).enhance(1.5)
 region.save(out_img_name)

#!/usr/bin/python2.7 
# -*- coding: utf-8 -*- 
import pytesseract
from PIL import Image

image = Image.open('bb.png')
code = pytesseract.image_to_string(image)
print（code）