获取验证码图片

识别缺口位置

生成滑块拖动路径

模拟实现滑块拼合

 

1 import time  2 from io import BytesIO  3 from PIL import Image  4 from selenium import webdriver  5 from selenium.webdriver import ActionChains  6 from selenium.webdriver.common.by import By  7 from selenium.webdriver.support.ui import WebDriverWait  8 from selenium.webdriver.support import expected_conditions as EC  9  10 EMAIL = '1764662628@qq.com' 11 PASSWORD = '***' 12 BORDER = 6 13 INIT_LEFT = 60 14  15  16 class CrackGeetest(): 17     def __init__(self): 18         self.url = 'https://account.geetest.com/login' 19         self.browser = webdriver.Chrome() 20         self.wait = WebDriverWait(self.browser, 20) 21         self.email = EMAIL 22         self.password = PASSWORD 23      24     def __del__(self): 25         self.browser.close() 26      27     def get_geetest_button(self): 28         """ 29         获取初始验证按钮 30         :return: 31         """ 32         button = self.wait.until(EC.element_to_be_clickable((By.CLASS_NAME, 'geetest_radar_tip'))) 33         return button 34      35     def get_position(self): 36         """ 37         获取验证码位置 38         :return: 验证码位置元组 39         """ 40         img = self.wait.until(EC.presence_of_element_located((By.CLASS_NAME, 'geetest_canvas_img'))) 41         time.sleep(2) 42         location = img.location 43         size = img.size 44         top, bottom, left, right = location['y'], location['y'] + size['height'], location['x'], location['x'] + size[ 45             'width'] 46         return (top, bottom, left, right) 47      48     def get_screenshot(self): 49         """ 50         获取网页截图 51         :return: 截图对象 52         """ 53         screenshot = self.browser.get_screenshot_as_png() 54         screenshot = Image.open(BytesIO(screenshot)) 55         return screenshot 56      57     def get_slider(self): 58         """ 59         获取滑块 60         :return: 滑块对象 61         """ 62         slider = self.wait.until(EC.element_to_be_clickable((By.CLASS_NAME, 'geetest_slider_button'))) 63         return slider 64      65     def get_geetest_image(self, name='captcha.png'): 66         """ 67         获取验证码图片 68         :return: 图片对象 69         """ 70         top, bottom, left, right = self.get_position() 71         print('验证码位置', top, bottom, left, right) 72         screenshot = self.get_screenshot() 73         captcha = screenshot.crop((left, top, right, bottom)) 74         captcha.save(name) 75         return captcha 76      77     def open(self): 78         """ 79         打开网页输入用户名密码 80         :return: None 81         """ 82         self.browser.get(self.url) 83         email = self.wait.until(EC.presence_of_element_located((By.ID, 'email'))) 84         password = self.wait.until(EC.presence_of_element_located((By.ID, 'password'))) 85         email.send_keys(self.email) 86         password.send_keys(self.password) 87      88     def get_gap(self, image1, image2): 89         """ 90         获取缺口偏移量 91         :param image1: 不带缺口图片 92         :param image2: 带缺口图片 93         :return: 94         """ 95         left = 60 96         for i in range(left, image1.size[0]): 97             for j in range(image1.size[1]): 98                 if not self.is_pixel_equal(image1, image2, i, j): 99                     left = i100                     return left101         return left102     103     def is_pixel_equal(self, image1, image2, x, y):104         """105         判断两个像素是否相同106         :param image1: 图片1107         :param image2: 图片2108         :param x: 位置x109         :param y: 位置y110         :return: 像素是否相同111         """112         # 取两个图片的像素点113         pixel1 = image1.load()[x, y]114         pixel2 = image2.load()[x, y]115         threshold = 60116         if abs(pixel1[0] - pixel2[0]) < threshold and abs(pixel1[1] - pixel2[1]) < threshold and abs(117                 pixel1[2] - pixel2[2]) < threshold:118             return True119         else:120             return False121     122     def get_track(self, distance):123         """124         根据偏移量获取移动轨迹125         :param distance: 偏移量126         :return: 移动轨迹127         """128         # 移动轨迹129         track = []130         # 当前位移131         current = 0132         # 减速阈值133         mid = distance * 4 / 5134         # 计算间隔135         t = 0.2136         # 初速度137         v = 0138         139         while current < distance:140             if current < mid:141                 # 加速度为正2142                 a = 2143             else:144                 # 加速度为负3145                 a = -3146             # 初速度v0147             v0 = v148             # 当前速度v = v0 + at149             v = v0 + a * t150             # 移动距离x = v0t + 1/2 * a * t^2151             move = v0 * t + 1 / 2 * a * t * t152             # 当前位移153             current += move154             # 加入轨迹155             track.append(round(move))156         return track157     158     def move_to_gap(self, slider, track):159         """160         拖动滑块到缺口处161         :param slider: 滑块162         :param track: 轨迹163         :return:164         """165         ActionChains(self.browser).click_and_hold(slider).perform()166         for x in track:167             ActionChains(self.browser).move_by_offset(xoffset=x, yoffset=0).perform()168         time.sleep(0.5)169         ActionChains(self.browser).release().perform()170     171     def login(self):172         """173         登录174         :return: None175         """176         submit = self.wait.until(EC.element_to_be_clickable((By.CLASS_NAME, 'login-btn')))177         submit.click()178         time.sleep(10)179         print('登录成功')180     181     def crack(self):182         # 输入用户名密码183         self.open()184         # 点击验证按钮185         button = self.get_geetest_button()186         button.click()187         # 获取验证码图片188         image1 = self.get_geetest_image('captcha1.png')189         # 点按呼出缺口190         slider = self.get_slider()191         slider.click()192         # 获取带缺口的验证码图片193         image2 = self.get_geetest_image('captcha2.png')194         # 获取缺口位置195         gap = self.get_gap(image1, image2)196         print('缺口位置', gap)197         # 减去缺口位移198         gap -= BORDER199         # 获取移动轨迹200         track = self.get_track(gap)201         print('滑动轨迹', track)202         # 拖动滑块203         self.move_to_gap(slider, track)204         205         success = self.wait.until(206             EC.text_to_be_present_in_element((By.CLASS_NAME, 'geetest_success_radar_tip_content'), '验证成功'))207         print(success)208         209         # 失败后重试210         if not success:211             self.crack()212         else:213             self.login()214 215 216 if __name__ == '__main__':217     crack = CrackGeetest()218     crack.crack()

 

估计是高分屏的原因，截全图下来的时候我用画图软件看了图形验证码的像素位置，刚好是给的位置参数乘以2，所以保存下来的2张验证码的图还要压缩一下分辨率，加入下面语句就可以做对比匹配了。

1 captcha = screenshot.crop((2*left, 2*top, 2*right, 2*bottom))2 size = 258,1593 captcha.thumbnail(size)

 

修改参数

1 import time  2 from io import BytesIO  3 from PIL import Image  4 from selenium import webdriver  5 from selenium.webdriver import ActionChains  6 from selenium.webdriver.common.by import By  7 from selenium.webdriver.support.ui import WebDriverWait  8 from selenium.webdriver.support import expected_conditions as EC  9  10 EMAIL = '1764662628@qq.com' 11 PASSWORD = '***' 12 BORDER = 6 13 INIT_LEFT = 60 14  15  16 class CrackGeetest(): 17     def __init__(self): 18         self.url = 'https://account.geetest.com/login' 19         self.browser = webdriver.Chrome() 20         self.wait = WebDriverWait(self.browser, 20) 21         self.email = EMAIL 22         self.password = PASSWORD 23      24     def __del__(self): 25         self.browser.close() 26      27     def get_geetest_button(self): 28         """ 29         获取初始验证按钮 30         :return: 31         """ 32         button = self.wait.until(EC.element_to_be_clickable((By.CLASS_NAME, 'geetest_radar_tip'))) 33         return button 34      35     def get_position(self): 36         """ 37         获取验证码位置 38         :return: 验证码位置元组 39         """ 40         img = self.wait.until(EC.presence_of_element_located((By.CLASS_NAME, 'geetest_canvas_img'))) 41         time.sleep(2) 42         location = img.location 43         size = img.size 44         top, bottom, left, right = location['y'], location['y'] + size['height'], location['x'], location['x'] + size[ 45             'width'] 46         return (top, bottom, left, right) 47      48     def get_screenshot(self): 49         """ 50         获取网页截图 51         :return: 截图对象 52         """ 53         screenshot = self.browser.get_screenshot_as_png() 54         screenshot = Image.open(BytesIO(screenshot)) 55         return screenshot 56      57     def get_slider(self): 58         """ 59         获取滑块 60         :return: 滑块对象 61         """ 62         slider = self.wait.until(EC.element_to_be_clickable((By.CLASS_NAME, 'geetest_slider_button'))) 63         return slider 64      65     def get_geetest_image(self, name='captcha.png'): 66         """ 67         获取验证码图片 68         :return: 图片对象 69         """ 70         top, bottom, left, right = self.get_position() 71         print('验证码位置', top, bottom, left, right) 72         screenshot = self.get_screenshot() 73         #captcha = screenshot.crop((left, top, right, bottom)) 74         captcha = screenshot.crop((2*left, 2*top, 2*right, 2*bottom)) 75         size = 258,159 76         captcha.thumbnail(size) 77         captcha.save(name) 78         return captcha 79      80     def open(self): 81         """ 82         打开网页输入用户名密码 83         :return: None 84         """ 85         self.browser.get(self.url) 86         email = self.wait.until(EC.presence_of_element_located((By.ID, 'email'))) 87         password = self.wait.until(EC.presence_of_element_located((By.ID, 'password'))) 88         email.send_keys(self.email) 89         password.send_keys(self.password) 90      91     def get_gap(self, image1, image2): 92         """ 93         获取缺口偏移量 94         :param image1: 不带缺口图片 95         :param image2: 带缺口图片 96         :return: 97         """ 98         left = 60 99         for i in range(left, image1.size[0]):100             for j in range(image1.size[1]):101                 if not self.is_pixel_equal(image1, image2, i, j):102                     left = i103                     return left104         return left105     106     def is_pixel_equal(self, image1, image2, x, y):107         """108         判断两个像素是否相同109         :param image1: 图片1110         :param image2: 图片2111         :param x: 位置x112         :param y: 位置y113         :return: 像素是否相同114         """115         # 取两个图片的像素点116         pixel1 = image1.load()[x, y]117         pixel2 = image2.load()[x, y]118         threshold = 60119         if abs(pixel1[0] - pixel2[0]) < threshold and abs(pixel1[1] - pixel2[1]) < threshold and abs(120                 pixel1[2] - pixel2[2]) < threshold:121             return True122         else:123             return False124     125     def get_track(self, distance):126         """127         根据偏移量获取移动轨迹128         :param distance: 偏移量129         :return: 移动轨迹130         """131         # 移动轨迹132         track = []133         # 当前位移134         current = 0135         # 减速阈值136         mid = distance * 4 / 5137         print("距离")138         print(distance)139         print(mid)140         # 计算间隔141         t = 0.1142         # 初速度143         v = 0144         145         while current < distance:146             if current < mid:147                 # 加速度为正2148                 a = 2149             else:150                 # 加速度为负3151                 a = -3152             # 初速度v0153             v0 = v154             print("速度")155             print(v)156             # 当前速度v = v0 + at157             v = v0 + a * t158             # 移动距离x = v0t + 1/2 * a * t^2159             move = v0 * t + 1 / 2 * a * t * t160             print("移动距离")161             print(move)162             # 当前位移163             current += move164             print("当前位移")165             print(current)166             # 加入轨迹167             track.append(round(move))168         return track169     170     def move_to_gap(self, slider, track):171         """172         拖动滑块到缺口处173         :param slider: 滑块174         :param track: 轨迹175         :return:176         """177         ActionChains(self.browser).click_and_hold(slider).perform()178         for x in track:179             ActionChains(self.browser).move_by_offset(xoffset=x, yoffset=0).perform()180         time.sleep(0.5)181         ActionChains(self.browser).release().perform()182     183     def login(self):184         """185         登录186         :return: None187         """188         submit = self.wait.until(EC.element_to_be_clickable((By.CLASS_NAME, 'login-btn')))189         submit.click()190         time.sleep(10)191         print('登录成功')192     193     def crack(self):194         # 输入用户名密码195         self.open()196         # 点击验证按钮197         button = self.get_geetest_button()198         button.click()199         # 获取验证码图片200         image1 = self.get_geetest_image('captcha1.png')201         # 点按呼出缺口202         slider = self.get_slider()203         slider.click()204         # 获取带缺口的验证码图片205         image2 = self.get_geetest_image('captcha2.png')206         # 获取缺口位置207         gap = self.get_gap(image1, image2)208         print('缺口位置', gap)209         # 减去缺口位移210         gap -= BORDER211         # 获取移动轨迹212         track = self.get_track(gap)213         print('滑动轨迹', track)214         # 拖动滑块215         self.move_to_gap(slider, track)216         217         success = self.wait.until(218             EC.text_to_be_present_in_element((By.CLASS_NAME, 'geetest_success_radar_tip_content'), '验证成功'))219         print(success)220         221         # 失败后重试222         if not success:223             self.crack()224         else:225             self.login()226 227 228 if __name__ == '__main__':229     crack = CrackGeetest()230     crack.crack()

结果输出：

1 wljdeMacBook-Pro:Desktop wlj$ python3 CrackGeetest.py  2 验证码位置 172 331 528 786  3 验证码位置 172 331 528 786  4 缺口位置 94  5 距离  6 88  7 70.4  8 速度  9 0 10 移动距离 11 0.010000000000000002 12 当前位移 13 0.010000000000000002 14 速度 15 0.2 16 移动距离 17 0.030000000000000006 18 当前位移 19 0.04000000000000001 20 速度 21 0.4 22 移动距离 23 0.05000000000000001 24 当前位移 25 0.09000000000000002 26 速度 27 0.6000000000000001 28 移动距离 29 0.07 30 当前位移 31 0.16000000000000003 32 速度 33 0.8 34 移动距离 35 0.09000000000000002 36 当前位移 37 0.25000000000000006 38 速度 39 1.0 40 移动距离 41 0.11000000000000001 42 当前位移 43 0.3600000000000001 44 速度 45 1.2 46 移动距离 47 0.13 48 当前位移 49 0.4900000000000001 50 速度 51 1.4 52 移动距离 53 0.15 54 当前位移 55 0.6400000000000001 56 速度 57 1.5999999999999999 58 移动距离 59 0.17 60 当前位移 61 0.8100000000000002 62 速度 63 1.7999999999999998 64 移动距离 65 0.19 66 当前位移 67 1.0000000000000002 68 速度 69 1.9999999999999998 70 移动距离 71 0.21 72 当前位移 73 1.2100000000000002 74 速度 75 2.1999999999999997 76 移动距离 77 0.22999999999999998 78 当前位移 79 1.4400000000000002 80 速度 81 2.4 82 移动距离 83 0.25 84 当前位移 85 1.6900000000000002 86 速度 87 2.6 88 移动距离 89 0.27 90 当前位移 91 1.9600000000000002 92 速度 93 2.8000000000000003 94 移动距离 95 0.29000000000000004 96 当前位移 97 2.25 98 速度 99 3.0000000000000004100 移动距离101 0.31000000000000005102 当前位移103 2.56104 速度105 3.2000000000000006106 移动距离107 0.33000000000000007108 当前位移109 2.89110 速度111 3.400000000000001112 移动距离113 0.3500000000000001114 当前位移115 3.24116 速度117 3.600000000000001118 移动距离119 0.3700000000000001120 当前位移121 3.6100000000000003122 速度123 3.800000000000001124 移动距离125 0.3900000000000001126 当前位移127 4.0128 速度129 4.000000000000001130 移动距离131 0.41000000000000014132 当前位移133 4.41134 速度135 4.200000000000001136 移动距离137 0.43000000000000016138 当前位移139 4.84140 速度141 4.400000000000001142 移动距离143 0.4500000000000002144 当前位移145 5.29146 速度147 4.600000000000001148 移动距离149 0.4700000000000002150 当前位移151 5.76152 速度153 4.800000000000002154 移动距离155 0.4900000000000002156 当前位移157 6.25158 速度159 5.000000000000002160 移动距离161 0.5100000000000002162 当前位移163 6.76164 速度165 5.200000000000002166 移动距离167 0.5300000000000002168 当前位移169 7.29170 速度171 5.400000000000002172 移动距离173 0.5500000000000003174 当前位移175 7.84176 速度177 5.600000000000002178 移动距离179 0.5700000000000003180 当前位移181 8.41182 速度183 5.8000000000000025184 移动距离185 0.5900000000000003186 当前位移187 9.0188 速度189 6.000000000000003190 移动距离191 0.6100000000000003192 当前位移193 9.61194 速度195 6.200000000000003196 移动距离197 0.6300000000000003198 当前位移199 10.24200 速度201 6.400000000000003202 移动距离203 0.6500000000000004204 当前位移205 10.89206 速度207 6.600000000000003208 移动距离209 0.6700000000000004210 当前位移211 11.56212 速度213 6.800000000000003214 移动距离215 0.6900000000000004216 当前位移217 12.25218 速度219 7.0000000000000036220 移动距离221 0.7100000000000004222 当前位移223 12.96224 速度225 7.200000000000004226 移动距离227 0.7300000000000004228 当前位移229 13.690000000000001230 速度231 7.400000000000004232 移动距离233 0.7500000000000004234 当前位移235 14.440000000000001236 速度237 7.600000000000004238 移动距离239 0.7700000000000005240 当前位移241 15.21242 速度243 7.800000000000004244 移动距离245 0.7900000000000005246 当前位移247 16.0248 速度249 8.000000000000004250 移动距离251 0.8100000000000004252 当前位移253 16.81254 速度255 8.200000000000003256 移动距离257 0.8300000000000003258 当前位移259 17.64260 速度261 8.400000000000002262 移动距离263 0.8500000000000003264 当前位移265 18.490000000000002266 速度267 8.600000000000001268 移动距离269 0.8700000000000002270 当前位移271 19.360000000000003272 速度273 8.8274 移动距离275 0.8900000000000001276 当前位移277 20.250000000000004278 速度279 9.0280 移动距离281 0.91282 当前位移283 21.160000000000004284 速度285 9.2286 移动距离287 0.9299999999999999288 当前位移289 22.090000000000003290 速度291 9.399999999999999292 移动距离293 0.95294 当前位移295 23.040000000000003296 速度297 9.599999999999998298 移动距离299 0.9699999999999999300 当前位移301 24.01302 速度303 9.799999999999997304 移动距离305 0.9899999999999998306 当前位移307 25.0308 速度309 9.999999999999996310 移动距离311 1.0099999999999996312 当前位移313 26.009999999999998314 速度315 10.199999999999996316 移动距离317 1.0299999999999996318 当前位移319 27.04320 速度321 10.399999999999995322 移动距离323 1.0499999999999996324 当前位移325 28.09326 速度327 10.599999999999994328 移动距离329 1.0699999999999994330 当前位移331 29.16332 速度333 10.799999999999994334 移动距离335 1.0899999999999994336 当前位移337 30.25338 速度339 10.999999999999993340 移动距离341 1.1099999999999994342 当前位移343 31.36344 速度345 11.199999999999992346 移动距离347 1.1299999999999992348 当前位移349 32.49350 速度351 11.399999999999991352 移动距离353 1.1499999999999992354 当前位移355 33.64356 速度357 11.59999999999999358 移动距离359 1.169999999999999360 当前位移361 34.81362 速度363 11.79999999999999364 移动距离365 1.189999999999999366 当前位移367 36.0368 速度369 11.99999999999999370 移动距离371 1.209999999999999372 当前位移373 37.21374 速度375 12.199999999999989376 移动距离377 1.2299999999999989378 当前位移379 38.44380 速度381 12.399999999999988382 移动距离383 1.249999999999999384 当前位移385 39.69386 速度387 12.599999999999987388 移动距离389 1.269999999999999390 当前位移391 40.959999999999994392 速度393 12.799999999999986394 移动距离395 1.2899999999999987396 当前位移397 42.24999999999999398 速度399 12.999999999999986400 移动距离401 1.3099999999999987402 当前位移403 43.55999999999999404 速度405 13.199999999999985406 移动距离407 1.3299999999999985408 当前位移409 44.889999999999986410 速度411 13.399999999999984412 移动距离413 1.3499999999999985414 当前位移415 46.23999999999999416 速度417 13.599999999999984418 移动距离419 1.3699999999999986420 当前位移421 47.609999999999985422 速度423 13.799999999999983424 移动距离425 1.3899999999999983426 当前位移427 48.999999999999986428 速度429 13.999999999999982430 移动距离431 1.4099999999999984432 当前位移433 50.40999999999998434 速度435 14.199999999999982436 移动距离437 1.4299999999999982438 当前位移439 51.83999999999998440 速度441 14.39999999999998442 移动距离443 1.4499999999999982444 当前位移445 53.28999999999998446 速度447 14.59999999999998448 移动距离449 1.4699999999999982450 当前位移451 54.75999999999998452 速度453 14.79999999999998454 移动距离455 1.489999999999998456 当前位移457 56.24999999999997458 速度459 14.999999999999979460 移动距离461 1.509999999999998462 当前位移463 57.75999999999997464 速度465 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