from PIL import Image,ImageGrab
from selenium import webdriver
from selenium.webdriver import ActionChains
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from collections import Counter
import time
二值化
def sharp(image):
w, h = image.size
tem = 0
for i in range(w):
for j in range(h):
tem += image.getpixel((i, j))
pixel_ave = tem / w / h
for i in range(w):
for j in range(h):
p = image.getpixel((i, j))
if p > pixel_ave:
image.putpixel((i, j), 255)
else:
image.putpixel((i, j), 0)
return image
#获得图片的像素点集
def getPointList(i, j, Range):
for x in range(i - Range, i + Range + 1):
for y in range(j - Range, j + Range + 1):
if x == i and y == j: continue
yield (x, y)

本文介绍了一种使用Python和Selenium自动识别并破解京东网站滑块验证码的方法,通过图像处理和机器学习技术,实现了对验证码图片的二值化、降噪处理及滑块位置的精确计算。
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