* 验证码地址:https://007.qq.com/online.html
* 使用OpenCv模板匹配
* 成功率90%左右
* Java + Selenium + OpenCV
产品样例
来吧!展示!
注意!!!
· 在模拟滑动时不能按照相同速度或者过快的速度滑动,需要向人滑动时一样先快后慢,这样才不容易被识别。
模拟滑动代码↓↓↓
/** * 模拟人工移动 * @param driver * @param element页面滑块 * @param distance需要移动距离 */ public static void move(WebDriver driver, WebElement element, int distance) throws InterruptedException { int randomTime = 0; if (distance > 90) { randomTime = 250; } else if (distance > 80 && distance <= 90) { randomTime = 150; } List<Integer> track = getMoveTrack(distance - 2); int moveY = 1; try { Actions actions = new Actions(driver); actions.clickAndHold(element).perform(); Thread.sleep(200); for (int i = 0; i < track.size(); i++) { actions.moveByOffset(track.get(i), moveY).perform(); Thread.sleep(new Random().nextInt(300) + randomTime); } Thread.sleep(200); actions.release(element).perform(); } catch (Exception e) { e.printStackTrace(); } } /** * 根据距离获取滑动轨迹 * @param distance需要移动的距离 * @return */ public static List<Integer> getMoveTrack(int distance) { List<Integer> track = new ArrayList<>();// 移动轨迹 Random random = new Random(); int current = 0;// 已经移动的距离 int mid = (int) distance * 4 / 5;// 减速阈值 int a = 0; int move = 0;// 每次循环移动的距离 while (true) { a = random.nextInt(10); if (current <= mid) { move += a;// 不断加速 } else { move -= a; } if ((current + move) < distance) { track.add(move); } else { track.add(distance - current); break; } current += move; } return track; }
看操作,no bb,直接上代码
private final String INDEX_URL = "https://007.qq.com/online.html?ADTAG=index.head"; private void seleniumTest() { ChromeDriverManager manager = ChromeDriverManager.getInstance(); int status = -1; try { WebDriver driver = manager.getDriver(); driver.get(INDEX_URL); driver.manage().window().maximize(); // 设置浏览器窗口最大化 Thread.sleep(10000); driver.findElement(By.className("wp-onb-tit")).findElements(By.tagName("a")).get(1).click(); Thread.sleep(500); // 点击出现滑动图 waitWebElement(driver, By.id("code"), 500).click(); Thread.sleep(100); // 获取到验证区域 driver.switchTo().frame(waitWebElement(driver, By.id("tcaptcha_iframe"), 500)); Thread.sleep(100); // 获取滑动按钮 WebElement moveElemet = waitWebElement(driver, By.id("tcaptcha_drag_button"), 500); Thread.sleep(100); // 获取带阴影的背景图 String bgUrl = waitWebElement(driver, By.id("slideBg"), 500).getAttribute("src"); Thread.sleep(100); // 获取带阴影的小图 String sUrl = waitWebElement(driver, By.id("slideBlock"), 500).getAttribute("src"); Thread.sleep(100); // 获取高度 String topStr = waitWebElement(driver, By.id("slideBlock"), 500).getAttribute("style").substring(32, 36); int top = Integer.parseInt(topStr.substring(0, topStr.indexOf("p"))) * 2; Thread.sleep(100); // 计算移动距离 int distance = (int) Double.parseDouble(getTencentDistance(bgUrl, sUrl, top)); // 滑动 move(driver, moveElemet, distance); Thread.sleep(5000); } catch (Exception e) { e.printStackTrace(); } finally { manager.closeDriver(status); } } /** * 获取腾讯验证滑动距离 * * @return */ public static String dllPath = "C://chrome//opencv_java440.dll"; public String getTencentDistance(String bUrl, String sUrl, int top) { System.load(dllPath); File bFile = new File("C:/qq_b.jpg"); File sFile = new File("C:/qq_s.jpg"); try { FileUtils.copyURLToFile(new URL(bUrl), bFile); FileUtils.copyURLToFile(new URL(sUrl), sFile); BufferedImage bgBI = ImageIO.read(bFile); BufferedImage sBI = ImageIO.read(sFile); // 裁剪 bgBI = bgBI.getSubimage(360, top, bgBI.getWidth() - 370, sBI.getHeight()); ImageIO.write(bgBI, "png", bFile); Mat s_mat = Imgcodecs.imread(sFile.getPath()); Mat b_mat = Imgcodecs.imread(bFile.getPath()); // 转灰度图像 Mat s_newMat = new Mat(); Imgproc.cvtColor(s_mat, s_newMat, Imgproc.COLOR_BGR2GRAY); // 二值化图像 binaryzation(s_newMat); Imgcodecs.imwrite(sFile.getPath(), s_newMat); int result_rows = b_mat.rows() - s_mat.rows() + 1; int result_cols = b_mat.cols() - s_mat.cols() + 1; Mat g_result = new Mat(result_rows, result_cols, CvType.CV_32FC1); Imgproc.matchTemplate(b_mat, s_mat, g_result, Imgproc.TM_SQDIFF); // 归一化平方差匹配法 // 归一化相关匹配法 Core.normalize(g_result, g_result, 0, 1, Core.NORM_MINMAX, -1, new Mat()); Point matchLocation = new Point(); MinMaxLocResult mmlr = Core.minMaxLoc(g_result); matchLocation = mmlr.maxLoc; // 此处使用maxLoc还是minLoc取决于使用的匹配算法 Imgproc.rectangle(b_mat, matchLocation, new Point(matchLocation.x + s_mat.cols(), matchLocation.y + s_mat.rows()), new Scalar(0, 0, 0, 0)); return "" + ((matchLocation.x + s_mat.cols() + 360 - sBI.getWidth() - 46) / 2); } catch (Throwable e) { e.printStackTrace(); return null; } finally { bFile.delete(); sFile.delete(); } } /** * * @param mat * 二值化图像 */ public static void binaryzation(Mat mat) { int BLACK = 0; int WHITE = 255; int ucThre = 0, ucThre_new = 127; int nBack_count, nData_count; int nBack_sum, nData_sum; int nValue; int i, j; int width = mat.width(), height = mat.height(); // 寻找最佳的阙值 while (ucThre != ucThre_new) { nBack_sum = nData_sum = 0; nBack_count = nData_count = 0; for (j = 0; j < height; ++j) { for (i = 0; i < width; i++) { nValue = (int) mat.get(j, i)[0]; if (nValue > ucThre_new) { nBack_sum += nValue; nBack_count++; } else { nData_sum += nValue; nData_count++; } } } nBack_sum = nBack_sum / nBack_count; nData_sum = nData_sum / nData_count; ucThre = ucThre_new; ucThre_new = (nBack_sum + nData_sum) / 2; } // 二值化处理 int nBlack = 0; int nWhite = 0; for (j = 0; j < height; ++j) { for (i = 0; i < width; ++i) { nValue = (int) mat.get(j, i)[0]; if (nValue > ucThre_new) { mat.put(j, i, WHITE); nWhite++; } else { mat.put(j, i, BLACK); nBlack++; } } } // 确保白底黑字 if (nBlack > nWhite) { for (j = 0; j < height; ++j) { for (i = 0; i < width; ++i) { nValue = (int) (mat.get(j, i)[0]); if (nValue == 0) { mat.put(j, i, WHITE); } else { mat.put(j, i, BLACK); } } } } } // 延时加载 private static WebElement waitWebElement(WebDriver driver, By by, int count) throws Exception { WebElement webElement = null; boolean isWait = false; for (int k = 0; k < count; k++) { try { webElement = driver.findElement(by); if (isWait) System.out.println(" ok!"); return webElement; } catch (org.openqa.selenium.NoSuchElementException ex) { isWait = true; if (k == 0) System.out.print("waitWebElement(" + by.toString() + ")"); else System.out.print("."); Thread.sleep(50); } } if (isWait) System.out.println(" outTime!"); return null; }
到此这篇关于使用java + selenium + OpenCV破解腾讯防水墙滑动验证码的文章就介绍到这了,更多相关java selenium 滑动验证码内容请搜索自学编程网以前的文章或继续浏览下面的相关文章希望大家以后多多支持自学编程网!
- 本文固定链接: https://zxbcw.cn/post/200927/
- 转载请注明:必须在正文中标注并保留原文链接
- QQ群: PHP高手阵营官方总群(344148542)
- QQ群: Yii2.0开发(304864863)