esword618/rotatecode

基于d4nst/RotNet的使用，实现模拟完成旋转拖动验证码

感谢

首先先感谢这位老哥的无私分享，老哥牛！我直接使用了人家的模型，正确率超高！！！

奉上大哥的github：觉得有用的同学可以支持一下 https://github.com/d4nst/RotNet/

RotNet

This repository contains the code necessary to train and test convolutional neural networks (CNNs) for predicting the rotation angle of an image to correct its orientation. There are scripts to train two models, one on MNIST and another one on the Google Street View dataset. Since the data for this application is generated on-the-fly, you can also train using your own images in a similar way. A detailed explanation of the code and motivation for this project can be found in my blog.

使用

模型三百多兆，放在百度云上了，需要解压放在根目录

链接：https://pan.baidu.com/s/1bmI55uEKNn_qfXZw6uUVpg 提取码：zjvh

baidu_pyppeteer.py 是模拟登录百度指数

correct_rotation.py 用来预测角度并纠正

correct_rotation_for_angle.py 只返回预测的角度

#最后 共同学习，如果你有更好的方式，可以分享出来，一起进步