import random

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
import time
import cv2
import pytesseract
import requests
import os
import numpy as np
from io import BytesIO
from PIL import Image
from selenium.webdriver import ChromeOptions
driver = webdriver.Chrome()

# 打开登录页面
driver.get('https://www.tadu.com/v3/loginpage?logintype=taduphone')
# 等待账号输入框可见

# 去除浏览器识别
option = ChromeOptions()
#隐藏浏览器
option.add_argument('--headlless')
option.add_argument('--disable-gpu')


def get_tracks(distance):
    distance += 20
    v = 0
    t = 0.2
    forward_tracks = []
    current = 0
    mid = distance * 3 / 5
    while current < distance:
        if current < mid:
            a = 2
        else:
            a = -3
        s = v * t + 0.5 * a * (t ** 2)
        v = v + a * t
        current += s
        forward_tracks.append(round(s))

    back_tracks = [-3, -3, -2, -2, -2, -2, -2, -1, -1, -1]
    return {'forward_tracks': forward_tracks, 'back_tracks': back_tracks}


def crack_slider(tracks):
    wait = WebDriverWait(driver, 5)

    slider = wait.until(EC.element_to_be_clickable((By.CLASS_NAME, 'tc-drag-thumb')))
    ActionChains(driver).click_and_hold(slider).perform()  # 模拟按住鼠标左键

    for track in tracks['forward_tracks']:
        ActionChains(driver).move_by_offset(xoffset=track, yoffset=0).perform()

    time.sleep(0.5)
    for back_tracks in tracks['back_tracks']:
        ActionChains(driver).move_by_offset(xoffset=back_tracks, yoffset=0).perform()
    print("1212313")
    ActionChains(driver).move_by_offset(xoffset=-4, yoffset=0).perform()
    ActionChains(driver).move_by_offset(xoffset=4, yoffset=0).perform()
    time.sleep(0.5)

    ActionChains(driver).release().perform()  # 释放左键
    return 0


# 下载图片到本地
def get_image(img_url,imgname):
    # 以流的形式下载文件
    image=requests.get(img_url,stream=True)
    imgName = ''.join(["./", imgname])
    with open(imgName, 'wb') as f:
        for chunk in image.iter_content(chunk_size=1024): # 循环写入  chunk_size：每次下载的数据大小
            if chunk:
                f.write(chunk)
                f.flush()
        f.close()

def get_image_offset(background_image_url, slider_image_url):
    back_image = 'back_image.png'  # 背景图像命名

    slider_image = 'slider_image.png'  # 滑块图像命名

    get_image(background_image_url, back_image)

    get_image(slider_image_url, slider_image)

    # 获取图片并灰度化
    block = cv2.imread(slider_image, 0)

    template = cv2.imread(back_image, 0)

    w, h = block.shape[::-1]
    # print(w, h)
    # 二值化后图片名称
    block_name = 'block.jpg'
    template_name = 'template.jpg'
    # 保存二值化后的图片
    cv2.imwrite(block_name, block)

    cv2.imwrite(template_name, template)

    block = cv2.imread(block_name)

    block = cv2.cvtColor(block, cv2.COLOR_RGB2GRAY)

    block = abs(255 - block)

    cv2.imwrite(block_name, block)

    block = cv2.imread(block_name)

    template = cv2.imread(template_name)

    # 获取偏移量
    # 模板匹配，查找block在template中的位置，返回result是一个矩阵，是每个点的匹配结果
    result = cv2.matchTemplate(block, template, cv2.TM_CCOEFF_NORMED)

    x, y = np.unravel_index(result.argmax(), result.shape)

    print(x, y)
    # 由于获取到的验证码图片像素与实际的像素有差(实际：280*158 原图：680*390)，故对获取到的坐标进行处理
    offset = y * (295 / 680)

    # 画矩形圈出匹配的区域
    # 参数解释：1.原图 2.矩阵的左上点坐标 3.矩阵的右下点坐标 4.画线对应的rgb颜色 5.线的宽度
    cv2.rectangle(template, (y, x), (y + w, x + h), (7, 249, 151), 2)

    show(template)

    return offset
# 显示图片
def show(name):

	cv2.imshow('Show', name)

	cv2.waitKey(0)

	cv2.destroyAllWindows()

# 实现规避检测
option.add_experimental_option('excludeSwitches', ['enable-automation'])
option.add_experimental_option("detach", True)
# 采取去除特征识别，即以下两行代码。
script = 'Object.defineProperty(navigator, "webdriver", {get: () => false,});'
driver.execute_script(script)

js = 'return window.navigator.webdriver'
print(driver.execute_script(js))  # 可以直接在终端输出webdriver检测结果


option.add_experimental_option('excludeSwitches', ['enable-automation'])
option.add_experimental_option("detach", True)

account_switch=WebDriverWait(driver, 10).until(EC.presence_of_element_located((By.ID, 'phoneAccountSwitch')))
account_switch.click()

username_input = WebDriverWait(driver, 10).until(EC.presence_of_element_located((By.CLASS_NAME, 'accountInput')))
password_input = WebDriverWait(driver, 10).until(EC.presence_of_element_located((By.CLASS_NAME, 'accountPass')))

username_input.send_keys('td188310339')  # 用户名
password_input.send_keys('Aa123456')  # 密码

submit = WebDriverWait(driver, 10).until(EC.presence_of_element_located((By.CLASS_NAME, 'accountLogin_bt')))
submit.click()

frame=WebDriverWait(driver, 10).until(EC.presence_of_element_located((By.ID, 'tcaptcha_iframe')))
driver.switch_to.frame(frame)
time.sleep(10)

img=WebDriverWait(driver, 10).until(EC.presence_of_element_located((By.ID, 'slideBg')))
image_url = img.get_attribute('src')  # 图片的URL

img2=WebDriverWait(driver, 10).until(EC.presence_of_element_located((By.ID, 'slideBlock')))
image2_url = img2.get_attribute('src')  # 图片的URL

x=get_image_offset(image_url,image2_url)
print(x)

drag_button =WebDriverWait(driver, 10).until(EC.presence_of_element_located((By.ID, 'tcaptcha_drag_thumb')))

ActionChains(driver).click_and_hold(drag_button).perform()
time.sleep(0.5)
# 遍历轨迹进行滑动
time.sleep(0.01)
crack_slider(get_tracks(x))

time.sleep(2)
cookies = driver.get_cookies()
cookies=''.join([f'{cookie["name"]}={cookie["value"]};' for cookie in cookies])
print(cookies)