from selenium import webdriver
# chrome_path要改成你自己的路徑
chrome_path = r"C:\Users\11248\AppData\Local\Google\Chrome\Application\chromedriver.exe"
url = 'https://icas.jnu.edu.cn/cas/login'
driver = webdriver.Chrome(chrome_path)
driver.get(url)

import time
import requests
from PIL import Image
from selenium.webdriver.common.by import By
from io import BytesIO

time.sleep(5)	# 進(jìn)入頁(yè)面要停留幾秒鐘，等頁(yè)面加載完
target_link = driver.find_element(By.CLASS_NAME, "yidun_bg-img").get_attribute('src')
template_link = driver.find_element(By.CLASS_NAME, "yidun_jigsaw").get_attribute('src')

target_img = Image.open(BytesIO(requests.get(target_link).content))
template_img = Image.open(BytesIO(requests.get(template_link).content))
target_img.save('target.jpg')
template_img.save('template.png')

def handel_img(img):
    imgGray = cv2.cvtColor(img, cv2.COLOR_RGBA2GRAY)  # 轉(zhuǎn)灰度圖
    imgBlur = cv2.GaussianBlur(imgGray, (5, 5), 1)  # 高斯模糊
    imgCanny = cv2.Canny(imgBlur, 60, 60)  # Canny算子邊緣檢測(cè)
    return imgCanny

def add_alpha_channel(img):
    """ 為jpg圖像添加alpha通道 """
    r_channel, g_channel, b_channel = cv2.split(img)  # 剝離jpg圖像通道
    alpha_channel = np.ones(b_channel.shape, dtype=b_channel.dtype) * 255  # 創(chuàng)建Alpha通道
    img_new = cv2.merge((r_channel, g_channel, b_channel, alpha_channel))  # 融合通道
    return img_new

import cv2
# 讀取圖像
def match(img_jpg_path, img_png_path):
    # 讀取圖像
    img_jpg = cv2.imread(img_jpg_path, cv2.IMREAD_UNCHANGED)
    img_png = cv2.imread(img_png_path, cv2.IMREAD_UNCHANGED)
    # 判斷jpg圖像是否已經(jīng)為4通道
    if img_jpg.shape[2] == 3:
        img_jpg = add_alpha_channel(img_jpg)
    img = handel_img(img_jpg)
    small_img = handel_img(img_png)
    res_TM_CCOEFF_NORMED = cv2.matchTemplate(img, small_img, 3)
    value = cv2.minMaxLoc(res_TM_CCOEFF_NORMED)
    value = value[3][0]  # 獲取到移動(dòng)距離
    return value

def merge_img(jpg_img, png_img, y1, y2, x1, x2):
    """ 將png透明圖像與jpg圖像疊加
        y1,y2,x1,x2為疊加位置坐標(biāo)值
    """
    # 判斷jpg圖像是否已經(jīng)為4通道
    if jpg_img.shape[2] == 3:
        jpg_img = add_alpha_channel(jpg_img)
    # 獲取要覆蓋圖像的alpha值，將像素值除以255，使值保持在0-1之間
    alpha_png = png_img[yy1:yy2, xx1:xx2, 3] / 255.0
    alpha_jpg = 1 - alpha_png

    # 開(kāi)始疊加
    for c in range(0, 3):
        jpg_img[y1:y2, x1:x2, c] = ((alpha_jpg * jpg_img[y1:y2, x1:x2, c]) + (alpha_png * png_img[yy1:yy2, xx1:xx2, c]))

    return jpg_img
    
img_jpg_path = 'target.jpg'  # 讀者可自行修改文件路徑
img_png_path = 'template.png'  # 讀者可自行修改文件路徑
x1 = match(img_jpg_path, img_png_path)
y1 = 0
x2 = x1 + img_png.shape[1]
y2 = y1 + img_png.shape[0]
# 開(kāi)始疊加
res_img = merge_img(img_jpg, img_png, y1, y2, x1, x2)
cv2.imshow("res_img ", res_img)
cv2.waitKey(0)

from selenium.webdriver.support import expected_conditions as EC
from selenium.webdriver.support.wait import WebDriverWait
from selenium.webdriver import ActionChains

def crack_slider(distance):
	wait = WebDriverWait(driver, 20)
    slider = wait.until(EC.element_to_be_clickable((By.CLASS_NAME, 'yidun_slider')))
    ActionChains(self.driver).click_and_hold(slider).perform()
    ActionChains(self.driver).move_by_offset(xoffset=distance, yoffset=0).perform()
    time.sleep(2)
    ActionChains(self.driver).release().perform()
    return 0

	distance = distance / 480 * 345

distance = distance /480 * 345 + 12

 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, 20)
      slider = wait.until(EC.element_to_be_clickable((By.CLASS_NAME, 'yidun_slider')))
      ActionChains(driver).click_and_hold(slider).perform() # 模擬按住鼠標(biāo)左鍵

      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()

      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()	# 釋放左鍵
      return 0

# coding=utf-8
import re
import requests
import time
from io import BytesIO

import cv2
import numpy as np
from PIL import Image
from selenium import webdriver
from selenium.webdriver import ActionChains
from selenium.webdriver.common.by import By
from selenium.webdriver.support import expected_conditions as EC
from selenium.webdriver.support.wait import WebDriverWait

class CrackSlider():
    # 通過(guò)瀏覽器截圖，識(shí)別驗(yàn)證碼中缺口位置，獲取需要滑動(dòng)距離，并破解滑動(dòng)驗(yàn)證碼

    def __init__(self):
        super(CrackSlider, self).__init__()
        self.opts = webdriver.ChromeOptions()
        self.opts.add_experimental_option('excludeSwitches', ['enable-logging'])
        # self.driver = webdriver.Chrome(ChromeDriverManager().install(), options=self.opts)
        chrome_path = r"C:\Users\11248\AppData\Local\Google\Chrome\Application\chromedriver.exe"
        self.driver = webdriver.Chrome(chrome_path, options=self.opts)

        self.url = 'https://icas.jnu.edu.cn/cas/login'
        self.wait = WebDriverWait(self.driver, 10)

    def get_pic(self):
        self.driver.get(self.url)
        time.sleep(5)
        target_link = self.driver.find_element(By.CLASS_NAME, "yidun_bg-img").get_attribute('src')
        template_link = self.driver.find_element(By.CLASS_NAME, "yidun_jigsaw").get_attribute('src')

        target_img = Image.open(BytesIO(requests.get(target_link).content))
        template_img = Image.open(BytesIO(requests.get(template_link).content))
        target_img.save('target.jpg')
        template_img.save('template.png')

    def crack_slider(self, distance):
        slider = self.wait.until(EC.element_to_be_clickable((By.CLASS_NAME, 'yidun_slider')))
        ActionChains(self.driver).click_and_hold(slider).perform()
        ActionChains(self.driver).move_by_offset(xoffset=distance, yoffset=0).perform()
        time.sleep(2)
        ActionChains(self.driver).release().perform()
        return 0

def add_alpha_channel(img):
    """ 為jpg圖像添加alpha通道 """

    r_channel, g_channel, b_channel = cv2.split(img)  # 剝離jpg圖像通道
    alpha_channel = np.ones(b_channel.shape, dtype=b_channel.dtype) * 255  # 創(chuàng)建Alpha通道

    img_new = cv2.merge((r_channel, g_channel, b_channel, alpha_channel))  # 融合通道
    return img_new

def handel_img(img):
    imgGray = cv2.cvtColor(img, cv2.COLOR_RGBA2GRAY)  # 轉(zhuǎn)灰度圖
    imgBlur = cv2.GaussianBlur(imgGray, (5, 5), 1)  # 高斯模糊
    imgCanny = cv2.Canny(imgBlur, 60, 60)  # Canny算子邊緣檢測(cè)
    return imgCanny

def match(img_jpg_path, img_png_path):
    # 讀取圖像
    img_jpg = cv2.imread(img_jpg_path, cv2.IMREAD_UNCHANGED)
    img_png = cv2.imread(img_png_path, cv2.IMREAD_UNCHANGED)
    # 判斷jpg圖像是否已經(jīng)為4通道
    if img_jpg.shape[2] == 3:
        img_jpg = add_alpha_channel(img_jpg)
    img = handel_img(img_jpg)
    small_img = handel_img(img_png)
    res_TM_CCOEFF_NORMED = cv2.matchTemplate(img, small_img, 3)
    value = cv2.minMaxLoc(res_TM_CCOEFF_NORMED)
    value = value[3][0]  # 獲取到移動(dòng)距離
    return value

# 1. 打開(kāi)chromedriver，試試下載圖片
cs = CrackSlider()
cs.get_pic()
# 2. 對(duì)比圖片，計(jì)算距離
img_jpg_path = 'target.jpg'  # 讀者可自行修改文件路徑
img_png_path = 'template.png'  # 讀者可自行修改文件路徑
distance = match(img_jpg_path, img_png_path)
distance = distance /480 * 345 + 12
# 3. 移動(dòng)
cs.crack_slider(distance)