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卷积神经网络实现的验证码识别

Home Page: http://captcha.chxj.name/

Python 45.05% Shell 0.51% HTML 28.27% PHP 26.18%
neural-network cnn-keras tensorflow

captcha_cracker's Introduction

captcha_cracker

在线Demo

简介

这是一个基于 Keras 编写的卷积神经网络模型,简单实现的验证码识别功能。

Captcha 是一款 Laravel 社区中流行的验证码生成库, 项目模型的训练集以及在线测试所用到的验证码均采用该库生成。

运行环境 Ubuntu16.04 python3.5.2 virtualenv Tensorflow Backend

实现原理

  • Captcha 生成2组每组2000个4位验证码图片(图片尺寸:36×120),并等分成4份(单张图片尺寸:36×30),将单个字符的图片分类保存在 images 目录中作为训练集(每组8000张图片)。
  • 生成2组每组500个4位验证码图片(图片尺寸:36×120),并等分成4份(单张图片尺寸:36×30),将单个字符的图片分类保存在 images 目录中作为测试集(每组2000张图片)。
  • 运行 pack_data.py 将图片转为 RGB 矩阵并用cPickle打包为单个文件
  • 运行 train.py 分别使用两组训练、测试数据对模型进行各100轮的训练,模型权重保存在 weights.hdf5 文件中

生成验证码代码样例可参考 CaptchaGenerator.php

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