本文共 5981 字，大约阅读时间需要 19 分钟。

环境安装

效果展示

源码

import os
import cv2
import time
import random
import requests
import numpy as np
from PIL import Image
from io import BytesIO
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver import ActionChains
from selenium.webdriver.support.wait import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
class CrackSlider():
    def __init__(self):
        self.browser = webdriver.Chrome()
        self.s2 = r'//*[@id="captcha_div"]/div/div[1]/div/div[1]/img[1]'
        self.s3 = r'//*[@id="captcha_div"]/div/div[1]/div/div[1]/img[2]'
        self.url = 'http://app.miit-eidc.org.cn/miitxxgk/gonggao/xxgk/queryCpParamPage?dataTag=Z&gid=U3119671&pc=303'
        self.wait = WebDriverWait(self.browser, 20)
        self.browser.get(self.url)
    def get_img(self, target, template, xp):
        time.sleep(3)
        target_link = self.browser.find_element_by_xpath(self.s2).get_attribute("src")
        template_link = self.browser.find_element_by_xpath(self.s3).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)
        template_img.save(template)
        size_loc = target_img.size
        print('size_loc[0]-----\n')
        print(size_loc[0])
        zoom = xp / int(size_loc[0])
        print('zoom-----\n')
        print(zoom)
        return zoom
    def change_size(self, file):
        image = cv2.imread(file, 1)
        img = cv2.medianBlur(image, 5)
        b = cv2.threshold(img, 15, 255, cv2.THRESH_BINARY)
        binary_image = b[1]
        binary_image = cv2.cvtColor(binary_image, cv2.COLOR_BGR2GRAY)
        x, y = binary_image.shape
        edges_x = []
        edges_y = []
        for i in range(x):
            for j in range(y):
                if binary_image[i][j] == 255:
                    edges_x.append(i)
                    edges_y.append(j)
        left = min(edges_x)
        right = max(edges_x)
        width = right - left
        bottom = min(edges_y)
        top = max(edges_y)
        height = top - bottom
        pre1_picture = image[left:left + width, bottom:bottom + height]
        return pre1_picture
    def match(self, target, template):
        img_gray = cv2.imread(target, 0)
        img_rgb = self.change_size(template)
        template = cv2.cvtColor(img_rgb, cv2.COLOR_BGR2GRAY)
        res = cv2.matchTemplate(img_gray, template, cv2.TM_CCOEFF_NORMED)
        run = 1
        L = 0
        R = 1
        while run < 20:
            run += 1
            threshold = (R + L) / 2
            if threshold < 0:
                print('Error')
                return None
            loc = np.where(res >= threshold)
            if len(loc[1]) > 1:
                L += (R - L) / 2
            elif len(loc[1]) == 1:
                break
            elif len(loc[1]) < 1:
                R -= (R - L) / 2
        res = loc[1][0]
        print('match distance-----\n')
        print(res)
        return res
    def move_to_gap(self, tracks):
        slider = self.wait.until(EC.element_to_be_clickable((By.CLASS_NAME, 'yidun_slider')))
        ActionChains(self.browser).click_and_hold(slider).perform()
        while tracks:
            x = tracks.pop(0)
            ActionChains(self.browser).move_by_offset(xoffset=x, yoffset=0).perform()
        time.sleep(0.05)
        ActionChains(self.browser).release().perform()
    def move_to_gap1(self, distance):
        distance += 46
        time.sleep(1)
        element = self.browser.find_element_by_xpath(self.s3)
        ActionChains(self.browser).click_and_hold(on_element=element).perform()
        ActionChains(self.browser).move_to_element_with_offset(to_element=element, xoffset=distance, yoffset=0).perform()
        time.sleep(1.38)
        ActionChains(self.browser).release(on_element=element).perform()
    def move_to_gap2(self, distance):
        element = self.browser.find_elements_by_class_name("yidun_slider")[0]
        action = ActionChains(self.browser)
        mouse_action = action.click_and_hold(on_element=element)
        distance += 11
        distance = int(distance * 32/33)
        move_steps = int(distance/4)
        for i in range(0,move_steps):
            mouse_action.move_by_offset(4,random.randint(-5,5)).perform()
        time.sleep(0.1)
        mouse_action.release().perform()
    def get_tracks(self, distance, seconds, ease_func):
        distance += 20
        tracks = [0]
        offsets = [0]
        for t in np.arange(0.0, seconds, 0.1):
            ease = ease_func
            offset = round(ease(t / seconds) * distance)
            tracks.append(offset - offsets[-1])
            offsets.append(offset)
        tracks.extend([-3, -2, -3, -2, -2, -2, -2, -1, -0, -1, -1, -1])
        return tracks
    def get_tracks1(self, distance):
        """根据偏移量获取移动轨迹
        :param distance: 偏移量
        :return: 移动轨迹
        """
        track = []
        current = 0
        mid = distance * 4 / 5
        t = 0.2
        v = 0
        while current < distance:
            if current < mid:
                a = 4
            else:
                a = -3
            v0 = v
            v = v0 + a * t
            move = v0 * t + 1 / 2 * a * t * t
            current += move
            track.append(round(move))
        return track
    def ease_out_quart(self, x):
        res = 1 - pow(1 - x, 4)
        return res
if __name__ == '__main__':
    xp = 320
    target = 'target.jpg'
    template = 'template.png'
    cs = CrackSlider()
    zoom = cs.get_img(target, template, xp)
    distance = cs.match(target, template)
    track = cs.get_tracks((distance + 7) * zoom, random.randint(2, 4), cs.ease_out_quart)
    cs.move_to_gap(track)

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