- 环境准备
首先,确保你已安装 Haxe。可以通过以下命令安装:
bash
haxelib setup
创建一个新的 Haxe 项目:
bash
mkdir captcha_recognizer
cd captcha_recognizer
haxelib create
2. 下载验证码图片
使用 haxe.Http 下载验证码图片并保存到本地:
haxe
class Main {
static function main() {
downloadCaptcha("https://captcha7.scrape.center/captcha.png", "captcha.png");
}
static function downloadCaptcha(url:String, savePath:String) {
var http = new haxe.Http(url);
http.onData = function(data:String) {
haxe.Resource.save(savePath, data);
trace("验证码图片已保存为 " + savePath);
};
http.request(false);
}
}
3. 图像处理与 OCR 识别
使用 tesseract 进行图像处理和 OCR 识别。你需要确保已安装 Tesseract,并在 Haxe 中进行绑定:
haxe
import sys.io.File;
class Main {
static function recognizeCaptcha(imagePath:String):String {
// 假设你已经实现了调用 Tesseract 的逻辑
var text = Tesseract.recognize(imagePath);
trace("识别结果: " + text);
return text;
}
}
4. 自动化登录
使用 haxe.Http 发送 POST 请求,模拟登录操作:
haxe
class Main {
static function login(username:String, password:String, captcha:String) {
var url = "https://captcha7.scrape.center/login";
var http = new haxe.Http(url);
http.postData = "username=" + username + "&password=" + password + "&captcha=" + captcha;
http.onData = function(response:String) {
trace("登录成功: " + response);
};
http.request(false);
}
}
5. 主程序
整合上述代码,创建主程序:
haxe
class Main {
static function main() {
var captchaUrl = "https://captcha7.scrape.center/captcha.png";
var captchaPath = "captcha.png";
// 下载验证码图片
downloadCaptcha(captchaUrl, captchaPath);
// 识别验证码
var captchaText = recognizeCaptcha(captchaPath);
// 模拟登录
login("admin", "admin", captchaText);
}
// 包含之前的下载、识别和登录方法
}
标签:function,http,String,captcha,验证码,var,haxe,Haxe,识别 From: https://www.cnblogs.com/ocr1/p/18495927