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chinese-ocr's Introduction

本文基于tensorflow、keras/pytorch实现对自然场景的文字检测及端到端的OCR中文文字识别

实现功能

  • 文字方向检测 0、90、180、270度检测 (运用vgg16分类模型实现,正在整理中)
  • 文字检测
  • 不定长OCR识别

环境部署

sh setup.sh

模型训练

训练keras版本的crnn

cd train & sh train-keras.sh   

训练pytorch版本的crnn

cd train & sh train-pytorch.sh   

文字检测

文本检测参考(https://github.com/eragonruan/text-detection-ctpn)

在原作者的代码基础上修改编译代码,新增支持CPU模式下的文字检测,详见:https://github.com/chineseocr/new-text-detection-ctpn.git

OCR 端到端识别:GRU+CTC

ocr识别采用GRU+CTC端到到识别技术,实现不分隔识别不定长文字

提供keras 与pytorch版本的训练代码,在理解keras的基础上,可以切换到pytorch版本,此版本更稳定

识别结果展示

文字检测及OCR识别结果

倾斜文字

参考

1.crnn https://github.com/meijieru/crnn.pytorch.git

2.keras-crnn 版本实现参考 https://www.zhihu.com/question/59645822

3.ctpn https://github.com/eragonruan/text-detection-ctpn , https://github.com/tianzhi0549/CTPN

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