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python入门教程 - 滑块实战[附源码]

发布2022-03-26浏览624次

详情内容

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Python基础教程|xin3721自学网ul li id=itemtitlePython3 从入门到精通视频教程/li /ul ul li class=description Python是一种跨平台的计算机程序设计语言。是一种面向对象的动态类型语言，最初被设计用于编写自动化脚本(shell)，icon-default.png?t=M276https://www.xin3721.com/eschool/pythonxin3721/

环境安装

安装python需要的依赖包

cv2 安装可以参考这里：python 安装 cv2 - 已解决_JavaPub-rodert的博客-CSDN博客

安装webdriver -> chrome

下载对应版本，放在本地 D:\anaconda3\Scripts 目录下

CNPM Binaries Mirror

效果展示

GIF效果：https://tva2.sinaimg.cn/large/007F3CC8ly1h0ku3yh9g5g31ex0pfwus.gif

cv2使用参考：CV2模块使用（详细教程）_王张飞的博客-CSDN博客_cv2

注意：测试时慢点刷，容易封IP。

源码

有问题可以留言探讨，公众号：JavaPub

对源码加了大量注释

测试网站：访问行为验证

  1. import os
  2. import cv2
  3. import time
  4. import random
  5. import requests
  6. import numpy as np
  7. from PIL import Image
  8. from io import BytesIO
  9. from selenium import webdriver
  10. from selenium.webdriver.common.by import By
  11. from selenium.webdriver import ActionChains
  12. from selenium.webdriver.support.wait import WebDriverWait
  13. from selenium.webdriver.support import expected_conditions as EC
  14.  
  15. class CrackSlider():
  16.     def __init__(self):
  17.         # self.browser = webdriver.Edge()
  18.         self.browser = webdriver.Chrome()
  19.         self.s2 = r'//*[@id="captcha_div"]/div/div[1]/div/div[1]/img[1]'
  20.         self.s3 = r'//*[@id="captcha_div"]/div/div[1]/div/div[1]/img[2]'
  21.         self.url = 'http://app.miit-eidc.org.cn/miitxxgk/gonggao/xxgk/queryCpParamPage?dataTag=Z&gid=U3119671&pc=303'  # 测试网站
  22.         self.wait = WebDriverWait(self.browser, 20)
  23.         self.browser.get(self.url)
  24.  
  25.     # 保存俩张图片
  26.     def get_img(self, target, template, xp):
  27.         time.sleep(3)
  28.         target_link = self.browser.find_element_by_xpath(self.s2).get_attribute("src")
  29.         template_link = self.browser.find_element_by_xpath(self.s3).get_attribute("src")
  30.         target_img = Image.open(BytesIO(requests.get(target_link).content))
  31.         template_img = Image.open(BytesIO(requests.get(template_link).content))
  32.         target_img.save(target)
  33.         template_img.save(template)
  34.         size_loc = target_img.size
  35.         print('size_loc[0]-----\n')
  36.         print(size_loc[0])
  37.         zoom = xp / int(size_loc[0])  # 耦合像素
  38.         print('zoom-----\n')
  39.         print(zoom)
  40.         return zoom
  41.  
  42.     def change_size(self, file):
  43.         image = cv2.imread(file, 1)  # 读取图片 image_name应该是变量
  44.         img = cv2.medianBlur(image, 5)  # 中值滤波，去除黑色边际中可能含有的噪声干扰。去噪。
  45.         b = cv2.threshold(img, 15, 255, cv2.THRESH_BINARY)  # 调整裁剪效果，二值化处理。
  46.         binary_image = b[1]  # 二值图--具有三通道
  47.         binary_image = cv2.cvtColor(binary_image, cv2.COLOR_BGR2GRAY)
  48.         x, y = binary_image.shape
  49.         edges_x = []
  50.         edges_y = []
  51.         for i in range(x):
  52.             for j in range(y):
  53.                 if binary_image[i][j] == 255:
  54.                     edges_x.append(i)
  55.                     edges_y.append(j)
  56.  
  57.         left = min(edges_x)  # 左边界
  58.         right = max(edges_x)  # 右边界
  59.         width = right - left  # 宽度
  60.         bottom = min(edges_y)  # 底部
  61.         top = max(edges_y)  # 顶部
  62.         height = top - bottom  # 高度
  63.         pre1_picture = image[left:left + width, bottom:bottom + height]  # 图片截取
  64.         return pre1_picture  # 返回图片数据
  65.  
  66.     # 匹配比对俩图距离
  67.     def match(self, target, template):
  68.         img_gray = cv2.imread(target, 0)
  69.         img_rgb = self.change_size(template)
  70.         template = cv2.cvtColor(img_rgb, cv2.COLOR_BGR2GRAY) # 图片格式转换为灰度图片 
  71.         # cv2.imshow('template', template)
  72.         # cv2.waitKey(0)
  73.         res = cv2.matchTemplate(img_gray, template, cv2.TM_CCOEFF_NORMED) # 匹配模式，匹配图片
  74.         run = 1
  75.  
  76.         # 使用二分法查找阈值的精确值
  77.         L = 0
  78.         R = 1
  79.         while run < 20:
  80.             run += 1
  81.             threshold = (R + L) / 2
  82.             if threshold < 0:
  83.                 print('Error')
  84.                 return None
  85.             loc = np.where(res >= threshold)
  86.             if len(loc[1]) > 1:
  87.                 L += (R - L) / 2
  88.             elif len(loc[1]) == 1:
  89.                 break
  90.             elif len(loc[1]) < 1:
  91.                 R -= (R - L) / 2
  92.         res = loc[1][0]
  93.         print('match distance-----\n')
  94.         print(res)
  95.         return res
  96.  
  97.     def move_to_gap(self, tracks):
  98.         slider = self.wait.until(EC.element_to_be_clickable((By.CLASS_NAME, 'yidun_slider')))
  99.         ActionChains(self.browser).click_and_hold(slider).perform()
  100.         #element = self.browser.find_element_by_xpath(self.s3)
  101.         #ActionChains(self.browser).click_and_hold(on_element=element).perform()
  102.         while tracks:
  103.             x = tracks.pop(0)
  104.             print('tracks.pop(0)-----\n')
  105.             print(x)
  106.             ActionChains(self.browser).move_by_offset(xoffset=x, yoffset=0).perform()
  107.             #ActionChains(self.browser).move_to_element_with_offset(to_element=element, xoffset=x, yoffset=0).perform()
  108.             #time.sleep(0.01)
  109.         time.sleep(0.05)
  110.         ActionChains(self.browser).release().perform()
  111.  
  112.     def move_to_gap1(self, distance):
  113.         distance += 46
  114.         time.sleep(1)
  115.         element = self.browser.find_element_by_xpath(self.s3)
  116.         ActionChains(self.browser).click_and_hold(on_element=element).perform()
  117.         ActionChains(self.browser).move_to_element_with_offset(to_element=element, xoffset=distance, yoffset=0).perform()
  118.         #ActionChains(self.browser).release().perform()
  119.         time.sleep(1.38)
  120.         ActionChains(self.browser).release(on_element=element).perform()
  121.  
  122.     def move_to_gap2(self, distance):
  123.         element = self.browser.find_elements_by_class_name("yidun_slider")[0]
  124.         action = ActionChains(self.browser)
  125.         mouse_action = action.click_and_hold(on_element=element)
  126.         distance += 11
  127.         distance = int(distance * 32/33)
  128.         move_steps = int(distance/4)
  129.         for i in range(0,move_steps):
  130.             mouse_action.move_by_offset(4,random.randint(-5,5)).perform()
  131.         time.sleep(0.1)
  132.         mouse_action.release().perform()    
  133.  
  134.     # 计算出先加速、后加速的数组
  135.     def get_tracks(self, distance, seconds, ease_func):
  136.         distance += 20
  137.         tracks = [0]
  138.         offsets = [0]
  139.         for t in np.arange(0.0, seconds, 0.1):
  140.             ease = ease_func
  141.             print('ease-----\n')
  142.             print(ease)
  143.             offset = round(ease(t / seconds) * distance)
  144.             print('offset-----\n')
  145.             print(offset)
  146.             tracks.append(offset - offsets[-1])
  147.             print('offset - offsets[-1]-----\n')
  148.             print(offset - offsets[-1])
  149.             offsets.append(offset)
  150.             print('offsets-----\n')
  151.             print(offsets)
  152.         tracks.extend([-3, -2, -3, -2, -2, -2, -2, -1, -0, -1, -1, -1])
  153.         return tracks
  154.     def get_tracks1(self,distance):
  155.         """
  156.         根据偏移量获取移动轨迹
  157.         :param distance: 偏移量
  158.         :return: 移动轨迹
  159.         """
  160.         # 移动轨迹
  161.         track = []
  162.         # 当前位移
  163.         current = 0
  164.         # 减速阈值
  165.         mid = distance * 4 / 5
  166.         # 计算间隔
  167.         t = 0.2
  168.         # 初速度
  169.         v = 0
  170.  
  171.         while current < distance:
  172.             if current < mid:
  173.                 # 加速度为正 2
  174.                 a = 4
  175.             else:
  176.                 # 加速度为负 3
  177.                 a = -3
  178.             # 初速度 v0
  179.             v0 = v
  180.             # 当前速度 v = v0 + at
  181.             v = v0 + a * t
  182.             # 移动距离 x = v0t + 1/2 * a * t^2
  183.             move = v0 * t + 1 / 2 * a * t * t
  184.             # 当前位移
  185.             current += move
  186.             # 加入轨迹
  187.             track.append(round(move))
  188.         return track
  189.  
  190.     def ease_out_quart(self, x):
  191.         res = 1 - pow(1 - x, 4)
  192.         print('ease_out_quart-----\n')
  193.         print(res)
  194.         return res
  195.  
  196. # 发生意外，请留言。https://javapub.blog.csdn.net/article/details/123730597
  197. if __name__ == '__main__':
  198.     xp = 320  # 验证码的像素-长
  199.     target = 'target.jpg'  # 临时保存的图片名
  200.     template = 'template.png'  # 临时保存的图片名
  201.  
  202.     cs = CrackSlider()
  203.     zoom = cs.get_img(target, template, xp)
  204.     distance = cs.match(target, template)
  205.     track = cs.get_tracks((distance + 7) * zoom, random.randint(2, 4), cs.ease_out_quart)
  206.     #track = cs.get_tracks1(distance)
  207.     #track = cs.get_tracks((distance + 7) * zoom, random.randint(1, 2), cs.ease_out_quart)
  208.     cs.move_to_gap(track)
  209.     #cs.move_to_gap1(distance)
  210.     #cs.move_to_gap2(distance)
  211.     time.sleep(2)
  212.     #cs.browser.close()

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