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@lzwme/captcha-cv-ocr

v1.2.1

Published

Verification code identification based on OCR (Tesseract) and CV (OpenCV)

Downloads

12

Readme

@lzwme/captcha-cv-ocr

本仓库 Fork 自 PillarsZhang/captcha-cv-ocr

simplest | grids_and_equations | dots_and_chars | slide_match | ... :-: | :-: | :-: | :-: | :-: | | | - | ... 2348 | 2x6=? | 7RVO | 滑块匹配 | ...

快速入门

安装

# use npm, yarn or pnpm
npm add @lzwme/captcha-cv-ocr

因为所需的 OpenCV 支持模块 @u4/opencv4nodejs 体积较大,编译过程复杂,请手动安装,或者参考官方的安装指南:

npm i @u4/opencv4nodejs

用法

API 调用示例

const path = require("path");
const { Cvocr, getCodesList } = require("captcha-cv-ocr");

// 获取支持的验证码识别类型列表
const codesList = getCodesList();
console.log('codes:', codesList);

(async () => {
    // mode 表示验证码的种类
    let mode = "simplest";
    const cvocr = new Cvocr(mode);
    // 其中的 num: 1 表示需要启动的 OCR Worker 数(多线程)
    await cvocr.init([{ num: 1 }]);
    // 支持文件地址、Base64、Buffer形式
    let ans = await cvocr.recognize("test/example/simplest.jpg"));
    console.log("ans:", ans)
    process.exit(0);
})()

基于 http server 的服务调用

通过启动本地 server 服务的方式,可以提供 http 接口调用能力。示例:

# 默认启动 3000 端口
node ./node_modules/@lzwme/captcha-cv-ocr/index.js

或通过调用 createServer 方法自行启动:

const { createServer } = require('@lzwme/captcha-cv-ocr');

createServer({ port: 3000 });

然后即可通过 post 请求的方式使用。示例(基于 fetch API,可在 Node.js 环境或 chrome 控制台直接调用):

async function httpOcrTest() {
    const body = {
        mode: 'simplest',
        // 验证码图片
        base64: 'data:image/jpg;base64,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',
        // slide_match 模式的底图
        originalBase64: '',
    };
    const result = await fetch('http://localhost:3000/ocr', {
        method: 'post',
        body: JSON.stringify(body),
        headers: { 'Content-Type': 'application/json' }
    }).then(d => d.json());
    console.log(result);
}

说明

第三种验证码(dots_and_chars)识别改为用 sharp 和纯 JavaScript 的 CV 算法来实现,方便在树莓派上运行,但效率相比前两者很低。

基于 docker 快速部署

docker pull lzwme/captcha-cv-ocr:latest
docker run -d -p 3600:3600 lzwme/captcha-cv-ocr

开发

git clone https://github.com/lzwme/captcha-cv-ocr
cd captcha-cv-ocr
npm install
# 约等于安装为全局模块
npm link

测试

npm test

已支持

simplest | grids_and_equations | dots_and_chars :-: | :-: | :-: | | 2348 | 2x6=? | 7RVO

新增支持

codes下的文件夹对应着不同种类的名字(自行命名),你可以参照已有的模板与API创建新的识别库,来适配其他各种验证码。

参考文档与额外说明

  • @u4/opencv4nodejs 依赖安装及编译
  • opencv4nodejs
    • Github | https://github.com/justadudewhohacks/opencv4nodejs
    • API | https://justadudewhohacks.github.io/opencv4nodejs/docs/Mat/
  • @u4/opencv4nodejs
    • https://github.com/UrielCh/opencv4nodejs
  • tesseract.js
    • 主页 | https://tesseract.projectnaptha.com/
    • Github | https://github.com/naptha/tesseract.js
    • API | https://github.com/naptha/tesseract.js#docs
    • 第三种验证码如果进行训练识别效果会更好
  • sharp
    • Github | https://github.com/lovell/sharp
    • API | https://sharp.pixelplumbing.com/api-constructor
    • 另外吐槽:只有编辑图像的基础功能,而且体验不是很理想需要绕过bug
  • ./lib/fakeOpenCV
    • 个人仿照 OpenCV 重写了一些图像算法

C++ / Python 的 OpenCV 海量资料也非常有帮助, 相应的函数基本都能在 opencv4nodejs 的 API 文档 里找到。