from PIL import Image
from pytesseract import *
from fnmatch import fnmatch
from queue import Queue
import matplotlib.pyplot as plt
import cv2
import time
import osdef clear_border(img,img_name):'''去除边框'''h, w = img.shape[:2]for y in range(0, w):for x in range(0, h):# if y ==0 or y == w -1 or y == w - 2:if y < 4 or y > w -4:img[x, y] = 255# if x == 0 or x == h - 1 or x == h - 2:if x < 4 or x > h - 4:img[x, y] = 255return imgdef interference_line(img, img_name):'''干扰线降噪'''h, w = img.shape[:2]# ！！！opencv矩阵点是反的# img[1,2] 1:图片的高度，2：图片的宽度for r in range(0,2):for y in range(1, w - 1):for x in range(1, h - 1):count = 0if img[x, y - 1] > 245:count = count + 1if img[x, y + 1] > 245:count = count + 1if img[x - 1, y] > 245:count = count + 1if img[x + 1, y] > 245:count = count + 1if count > 2:img[x, y] = 255return imgdef interference_point(img,img_name, x = 0, y = 0):"""点降噪9邻域框,以当前点为中心的田字框,黑点个数:param x::param y::return:"""# todo 判断图片的长宽度下限cur_pixel = img[x,y]# 当前像素点的值height,width = img.shape[:2]for y in range(0, width - 1):for x in range(0, height - 1):if y == 0:  # 第一行if x == 0:  # 左上顶点,4邻域# 中心点旁边3个点sum = int(cur_pixel) \+ int(img[x, y + 1]) \+ int(img[x + 1, y]) \+ int(img[x + 1, y + 1])if sum <= 2 * 245:img[x, y] = 0elif x == height - 1:  # 右上顶点sum = int(cur_pixel) \+ int(img[x, y + 1]) \+ int(img[x - 1, y]) \+ int(img[x - 1, y + 1])if sum <= 2 * 245:img[x, y] = 0else:  # 最上非顶点,6邻域sum = int(img[x - 1, y]) \+ int(img[x - 1, y + 1]) \+ int(cur_pixel) \+ int(img[x, y + 1]) \+ int(img[x + 1, y]) \+ int(img[x + 1, y + 1])if sum <= 3 * 245:img[x, y] = 0elif y == width - 1:  # 最下面一行if x == 0:  # 左下顶点# 中心点旁边3个点sum = int(cur_pixel) \+ int(img[x + 1, y]) \+ int(img[x + 1, y - 1]) \+ int(img[x, y - 1])if sum <= 2 * 245:img[x, y] = 0elif x == height - 1:  # 右下顶点sum = int(cur_pixel) \+ int(img[x, y - 1]) \+ int(img[x - 1, y]) \+ int(img[x - 1, y - 1])if sum <= 2 * 245:img[x, y] = 0else:  # 最下非顶点,6邻域sum = int(cur_pixel) \+ int(img[x - 1, y]) \+ int(img[x + 1, y]) \+ int(img[x, y - 1]) \+ int(img[x - 1, y - 1]) \+ int(img[x + 1, y - 1])if sum <= 3 * 245:img[x, y] = 0else:  # y不在边界if x == 0:  # 左边非顶点sum = int(img[x, y - 1]) \+ int(cur_pixel) \+ int(img[x, y + 1]) \+ int(img[x + 1, y - 1]) \+ int(img[x + 1, y]) \+ int(img[x + 1, y + 1])if sum <= 3 * 245:img[x, y] = 0elif x == height - 1:  # 右边非顶点sum = int(img[x, y - 1]) \+ int(cur_pixel) \+ int(img[x, y + 1]) \+ int(img[x - 1, y - 1]) \+ int(img[x - 1, y]) \+ int(img[x - 1, y + 1])if sum <= 3 * 245:img[x, y] = 0else:  # 具备9领域条件的sum = int(img[x - 1, y - 1]) \+ int(img[x - 1, y]) \+ int(img[x - 1, y + 1]) \+ int(img[x, y - 1]) \+ int(cur_pixel) \+ int(img[x, y + 1]) \+ int(img[x + 1, y - 1]) \+ int(img[x + 1, y]) \+ int(img[x + 1, y + 1])if sum <= 4 * 245:img[x, y] = 0return imgdef _get_dynamic_binary_image(filedir,img_name):'''自适应阀值二值化'''filename =   './easy_code/' + img_name.split('.')[0] + '-binary.jpg'img_name = filedir + '/' + img_nameim = cv2.imread(img_name)im = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)th1 = cv2.adaptiveThreshold(im, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 21, 1)return th1def recognize():　　filedir = './images'　　#验证码路径for file in os.listdir(filedir):if fnmatch(file, '*.jpg'):img_name = file# 自适应阈值二值化im = _get_dynamic_binary_image(filedir,img_name)# 去除边框im = clear_border(im,img_name)# 对图片进行干扰线降噪im = interference_line(im,img_name)# 对图片进行点降噪im = interference_point(im,img_name)filename =  './easy_code/' + img_name.split('.')[0] + '-interferencePoint.jpg'　　#easy_code为保存路径cv2.imwrite(filename,im)　　#保存图片

recognize()