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超轻量级中文ocr,支持竖排文字识别, 支持ncnn推理 , psenet(8.5M) + crnn(6.3M) + anglenet(1.5M) 总模型仅17M

Python 10.37% Makefile 1.15% C++ 75.15% Objective-C 0.01% CMake 2.84% CSS 1.01% JavaScript 4.92% HTML 0.48% C 4.05%

chineseocr_lite's Introduction

本项目基于chineseocrpsenet 实现中文自然场景文字检测及识别

环境

pytorch 1.2.0

实现功能

  • 提供轻量的backone检测模型psenet(8.5M),crnn_lstm_lite(9.5M) 和行文本方向分类网络(1.5M)
  • 任意方向文字检测,识别时判断行文本方向
  • crnn\crnn_lite lstm\dense识别(ocr-dense和ocr-lstm是搬运chineseocr的)
  • 支持竖直文本识别
  • ncnn 实现 psenet (未实现核扩展)
  • ncnn 实现 crnn_dense (改变了全连接为conv1x1)
  • ncnn 实现 shuuflenev2 角度分类网络

web服务启动

cd chineseocr_lite## 进入chineseocr目录
python app.py 8080 ##8080端口号,可以设置任意端口

访问服务

http://127.0.0.1:8080/ocr

识别结果展示

ncnn检测结果展示

参考

  1. crnn https://github.com/meijieru/crnn.pytorch.git
  2. chineseocr https://github.com/chineseocr/chineseocr
  3. Psenet https://github.com/WenmuZhou/PSENet.pytorch
  4. 语言模型实现 https://github.com/lukhy/masr

chineseocr_lite's People

Contributors

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Watchers

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