新版無完整背景圖片滑塊驗證碼

步驟：

1、將圖片灰度，兩張都要灰度

2、將圖片銳化，兩張都要銳化

3、計算2d卷積核，兩張都要計算

4、卷積結果最大的點所在區域即為與卷積核（小滑塊）邊緣重合度最高的區域。

那麼在背景圖中，與小滑塊重合度最高的區域應該為缺口區域。因此我們找到的卷積結果最大的點就是背景圖缺口的中心點。

import requests
import cv2
import time
import os
from scipy import signal
from selenium import webdriver	#用來驅動瀏覽器的
from selenium.webdriver import ActionChains	#破解滑動驗證碼的時候用，可拖動圖片
from selenium.webdriver.common.keys import Keys

# 通過新版無原圖滑塊驗證碼
class Pass_slide:

    def __init__(self):
        self.driver = webdriver.Chrome()


    def input_user_pwd(self):
        self.driver.get('https://star.toutiao.com/')
        # 數字賬號密碼登入
        self.driver.find_element_by_xpath('//*[@id="app"]/div/div[1]/div[2]/div[2]/div[1]').click()
        time.sleep(1)
        self.driver.find_element_by_xpath('/html/body/div/div/div[2]/div[2]/div/div/div[2]/div[2]/div[1]/div/div[1]').click()
        time.sleep(1)
        # 輸入賬號
        self.driver.find_element_by_xpath('//*[@id="account-sdk"]/section/div[3]/div[1]/div[2]/div/input').send_keys(
            'username'
        )
        # 輸入密碼
        self.driver.find_element_by_xpath('//*[@id="account-sdk"]/section/div[3]/div[2]/div/div/input').send_keys(
            'password'
        )
        time.sleep(1)
        # 點選登入
        self.driver.find_element_by_xpath('//*[@id="account-sdk"]/section/div[6]/button').click()
        time.sleep(1)

    def slide_button(self):
        # 定位滑塊位置
        # 方式一：通過圖片定位位置
        # button = self.driver.find_element_by_xpath('//*[@id="account-sdk-slide-container"]/div/div[2]/img[2]')
        # 方式二： 用 Xpath 定位位置
        # button = self.driver.find_element_by_xpath(
        #     '//*[@id="account-sdk-slide-container"]/div/div[3]/div[2]/div[2]/div'
        # )
        # 方式三：通過 class 來定位
        button = self.driver.find_element_by_class_name('sc-jKJlTe')
        time.sleep(1)
        return button

    def move_to_slide(self,distance):
        # tracks是要傳入的移動軌跡
        ActionChains(self.driver).click_and_hold(self.slide_button()).perform()  # 移動
        for x in self.track(distance):
            ActionChains(self.driver).move_by_offset(xoffset=x, yoffset=0).perform()
        time.sleep(0.3)
        ActionChains(self.driver).release().perform()

    def track(self, distance):  # distance為傳入的總距離
        # 移動軌跡
        track = []
        current = 0  # 當前位移
        mid = distance * 4 / 5  # 減速閾值
        t = 0.2  # 計算間隔
        v = 1  # 初速度
        while current < distance:
            if current < mid:
                a = 4  # 加速度為2
            else:
                a = -3  # 加速度為-2
            v0 = v
            v = v0 + a * t  # 當前速度
            move = v0 * t + 1 / 2 * a * t * t  # 移動距離
            current += move  # 當前位移
            track.append(round(move))  # 加入軌跡
        return track

    def download_slide_auth_code_img(self):
        # 下載滑塊，和背景缺口圖片
        if not os.path.exists('./Auth_Slide_Img'):
            os.mkdir('./Auth_Slide_Img')
        big_img_url = self.driver.find_element_by_xpath(
            '//*[@id="account-sdk-slide-container"]/div/div[2]/img[1]').get_attribute('src')  # 缺口背景圖片 地址
        small_img_url = self.driver.find_element_by_xpath(
            '//*[@id="account-sdk-slide-container"]/div/div[2]/img[2]').get_attribute('src')  # 滑塊的圖片 地址

        with open('Auth_Slide_Img/big_slide_img.jpg', 'wb') as f:
            f.write(requests.get(big_img_url).content)
        with open('Auth_Slide_Img/small_slide_img.jpg', 'wb') as f:
            f.write(requests.get(small_img_url).content)


    # 圖片轉為 灰度圖片
    def img2gray(self, image):
        self.download_slide_auth_code_img()
        img_rgb = cv2.imread(image)  # 讀入圖片
        img_gray = cv2.cvtColor(img_rgb, cv2.COLOR_BGR2GRAY)  # 轉灰度圖片
        # cv2.imwrite(image, img_gray)  # 儲存圖片，第一個引數：path, 第二個引數：儲存的圖片
        return img_gray

    # 銳化邊緣
    def canny_edge(self, image):
        self.img2gray(image)
        img = cv2.imread(image, 0)
        blur = cv2.GaussianBlur(img, (3, 3), 0)  # 用高斯濾波處理原影象降噪
        canny = cv2.Canny(blur, threshold1=200, threshold2=300)  # 銳化圖片
        # cv2.imwrite(image, canny)  # 儲存圖片
        # cv2.imshow('candy', can)  # 彈出圖片
        cv2.waitKey()
        cv2.destroyAllWindows()  # 關閉視窗
        return canny

    # 計算 2d 卷積
    def convole2d(self, bg_array, fillter):
        bg_h, bg_w = bg_array.shape[:2]
        fillter_h, fillter_w = fillter.shape[:2]
        c_full = signal.convolve(bg_array, fillter, mode='full')
        kr, kc = fillter_h // 2, fillter_w // 2
        c_same = c_full[
                 fillter_h - kr - 1: bg_h + fillter_h - kr - 1,
                 fillter_w - kc - 1: bg_w + fillter_w - kr - 1,
                 ]
        return c_same

    # 最終位置
    def find_max_point(self, arrays, search_on_horizontal_center=False):
        max_point = 0
        max_point_pos = None

        array_rows, arrays_cols = arrays.shape
        if search_on_horizontal_center:
            for col in range(arrays_cols):
                if arrays[array_rows // 2, col] > max_point:
                    max_point = arrays[array_rows // 2, col]
                    max_point_pos = col, array_rows // 2
        else:
            for row in range(array_rows):
                for col in range(arrays_cols):
                    if arrays[row, col] > max_point:
                        max_point = arrays[row, col]
                        max_point_pos = col, row

        return max_point_pos

    def main(self):
        self.input_user_pwd()
        canny1 = self.canny_edge('Auth_Slide_Img/big_slide_img.jpg')
        canny2 = self.canny_edge('Auth_Slide_Img/small_slide_img.jpg')
        convoled_after = self.convole2d(canny1, canny2)
        distance = self.find_max_point(convoled_after)
        print(distance)
        self.move_to_slide(distance[0])
        return distance[0]

    def is_login(self):

        try:
            time.sleep(3)
            html = self.driver.find_element_by_xpath('/html/body/div[1]/div[2]/div/div[1]/button/i').click()
            print('login success!')
            self.driver.find_element_by_xpath(
                '/html/body/div[1]/div[1]/div[2]/div[1]/div[1]/div/div[2]/div[2]/div[1]/div[2]/div[1]/span').click()
            time.sleep(1)
            self.driver.find_element_by_xpath(
                '/html/body/div[1]/div[1]/div[2]/div[1]/div[1]/div/div[3]/div/div[1]/button/i').click()
            return True
        except:
            self.driver.close()
            print('login failed trying...')
            # self.is_login()
            return False

    def movement_search(self):
        self.driver.find_element_by_xpath('/html/body/div[1]/div[1]/div[2]/div[1]/div[1]/div/div[1]/div[1]/div/div[2]/div[3]/div/div[1]/input').send_keys('口紅')
        time.sleep(10)
        self.driver.find_element_by_xpath('/html/body/div[1]/div[1]/div[2]/div[1]/div[1]/div/div[1]/div[1]/div/div[2]/div[3]/i').send_keys(Keys.ENTER)
        time.sleep(6)
        self.driver.find_element_by_xpath('/html/body/div[1]/div[1]/div[2]/div[1]/div[1]/div/div[2]/div[1]/div/div[2]/div/div/div[1]/div[1]/div[1]/div[1]/div[2]/div[1]/div[1]').click()
        price1 = self.driver.find_element_by_xpath('/html/body/div[1]/div[1]/div[2]/div[1]/div[1]/div/div[1]/div/div[2]/div[2]/div[1]/div[1]/div[1]/div[1]/div/div[1]/div[1]/div/text()').extract()
        price2 = self.driver.find_element_by_xpath('/html/body/div[1]/div[1]/div[2]/div[1]/div[1]/div/div[1]/div/div[2]/div[2]/div[1]/div[2]/div[1]/div[1]/div/div[1]/div[1]/div/text()').extract()
        print(price1, price2)



run = Pass_slide()
run.main()
login_result = run.is_login()
print(login_result)

run.movement_search()