selenium+opencv实现滑块验证码的登陆

options = WEBdriver.FirefoxOptions()
driver = webdriver.Firefox(options=options)
driver.get('网址')
driver.find_element("link text", "登录").click()
name = driver.find_element("id", "name-input")
name.send_keys("账号######") # 输入账号
pw = driver.find_element("id", "passWord-input")
pw.send_keys("密码#########") # 输入密码
driver.find_element("id", "submit").click() # 提交

driver.switch_to.frame('tcaptcha_iframe')
 # 切换iframe
img = driver.find_element("id", "slideBg").get_attribute('src')
headers = {
    'Accept': "application/JSON, text/plain, **",
        'User-Agent': "Mozilla/5.0 (windows NT 10.0; WOW64) AppleWebKit/537.36 (Khtml, like Gecko) Chrome/65.0.3325.181 Safari/537.36"
    }
    driver.get('网址')
    driver.find_element("link text", "登录").click()
    name = driver.find_element("id", "name-input")
    name.send_keys(username)
    pw = driver.find_element("id", "password-input")
    pw.send_keys(password)
    driver.find_element("id", "submit").click()
    time.sleep(2)
    driver.switch_to.frame('tcaptcha_iframe')
    img = driver.find_element("id", "slideBg").get_attribute('src')
    r = requests.get(img, headers=headers)
    with open('img.png', 'wb') as f:
        f.write(r.content)
    block = driver.find_element("id", "slideBlock").get_attribute('src')
    r = requests.get(block, headers=headers)
    with open('block.png', 'wb') as f:
        f.write(r.content)
 
 
if __name__ == '__main__':
    options = webdriver.FirefoxOptions()
    driver = webdriver.Firefox(options=options)
    user = "##########"
    pw = "############"
    login_in(user, pw)
    image = "img.png"
    tpl = "block.png"
    length = block_loc.match(image, tpl)
    print(length)
    drag_block(length)

import cv2
import numpy as np
 
 
def avg_mean(img):
    mean_val, _, _, _ = cv2.mean(img)
    print("平均灰度：", mean_val)
    return mean_val
 
 
def match(image, temp):
    img = cv2.imread(image)
    tpl = cv2.imread(temp)
    tpl_gray = cv2.cvtColor(tpl, cv2.COLOR_BGR2GRAY)
    # cv2.imshow("111", tpl_gray)
    width, height = tpl_gray.shape
    for h in range(height):
        for w in range(width):
            if tpl_gray[w, h] == 0:
                tpl_gray[w, h] = 96
    binary = cv2.inRange(tpl_gray, 96, 96)
    kernel = np.ones((8, 8), np.uint8)
    template = cv2.morphologyEx(binary, cv2.MORPH_OPEN, kernel)
    # cv2.imshow('tpl', template)
    print(img.shape)
    gauss = cv2.GaussianBlur(img, [5, 5], 0)
    img_gray = cv2.cvtColor(gauss, cv2.COLOR_BGR2GRAY)
    # cv2.imshow("111", img_gray)
    if avg_mean(img) > 140:
        ret, target = cv2.threshold(img_gray, 105, 255, cv2.THRESH_BINARY) # 二值化
    elif avg_mean(img) > 102:
        ret, target = cv2.threshold(img_gray, 95, 255, cv2.THRESH_BINARY)  # 二值化
    else:
        ret, target = cv2.threshold(img_gray, 80, 255, cv2.THRESH_BINARY)
    # cv2.imshow('target', target)
    result = cv2.matchTemplate(target, template, cv2.TM_CCOEFF_NORMED)
    min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(result)
    left_up = max_loc
    print(left_up)
    right_down = (left_up[0] + height, left_up[1] + width)
    cv2.rectangle(img, left_up, right_down, (0, 0, 255), 2)
    # cv2.imshow('res', img)
    length = (left_up[0] - 26*2)/2
    return length