ImgMain.py

# -*- coding: utf-8 -*-


import cv2
from Convert import Convert
from CharMap import charMap
import numpy as np



def cutting_img(im,im_position,xoffset = 1,yoffset = 1):
    # 识别出的字符个数
    im_number = len(im_position[1])
    if(im_number>=4): im_number = 4;

    imgArr = []
    # 切割字符
    for i in range(im_number):
        im_start_X = im_position[1][i][0] - xoffset
        im_end_X = im_position[1][i][1] + xoffset
        im_start_Y = im_position[2][i][0] - yoffset
        im_end_Y = im_position[2][i][1] + yoffset
        cropped = im[im_start_Y:im_end_Y, im_start_X:im_end_X]
        imgArr.append(cropped)
        # cv2.imwrite(str(i)+"v.jpg",cropped) # 查看切割效果
    return im_number,imgArr



def get_code(code_request):
    cvt = Convert()
    req = code_request
    # 注意有些教务加装了所谓云防护，没有请求头会拦截，导致获取不了验证码图片，报错可以打印req.content看看
    img = cvt.run(req.content)
    # cv2.imwrite("v.jpg",img)  # 查看验证码

    # 切割的位置
    im_position = ([7, 7, 7, 7], [[5, 12], [15, 22], [25, 32], [34, 41]], [[4, 15], [4, 15], [4, 15], [4, 15]])

    cutting_img_num,imgArr = cutting_img(img,im_position,1,1)

    # 识别验证码
    result=""
    for i in range(cutting_img_num):
        try:
          template = imgArr[i]
          tempResult=""
          matchingDegree=0.0
          for char in charMap:
            img = np.asarray(charMap[char],dtype = np.uint8)
            res = cv2.matchTemplate(img,template,3) #img原图 template模板   用模板匹配原图
            min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res)
            if(max_val>matchingDegree):
              tempResult=char
              matchingDegree=max_val
          result += tempResult
          matchingDegree=0.0
        except Exception as err:
          raise Exception
          # print("ERROR "+ str(err))
          pass

    return result