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超轻量级中文ocr,支持竖排文字识别, 支持ncnn、mnn、tnn推理 ( dbnet(1.8M) + crnn(2.5M) + anglenet(378KB)) 总模型仅4.7M

License: GNU General Public License v2.0

Python 2.37% Dockerfile 0.05% CMake 1.08% C++ 75.69% C 0.86% Kotlin 10.98% Batchfile 1.54% Shell 1.84% Java 0.60% C# 2.41% Visual Basic .NET 2.57%
ncnn ocr pytorch

chineseocr_lite's Introduction

chineseocr_lite 的 onnx 推理, 部署简单

原始项目分支(torch推理,ncnn推理等):master

环境

  • python3.6

  • linux/macos/windows

web服务启动

cd chineseocr_lite## 进入chineseocr目录
python backend/main.py 

识别结果展示

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参考

  1. TrWebOCR https://github.com/alisen39/TrWebOCR

QQ群

820075525

以下范例项目是参考Python代码翻译为各种语言的Demo,仅供参考

** 注意:以下各种demo均相互独立,只是同一个程序的不同版本 **

如果不想自己整合依赖库的话,以下demo的完整源码工程项目,请到Q群共享里自行下载

  • onnxruntime C++ demo,支持Windows、linux、macOS,目前仅支持cpu计算;
  • ncnn C++ demo,支持Windows、linux、macOS,分为cpu版与gpu版,gpu版使用ncnn+vulkan来支持gpu加速;
  • MNN C++ demo, 支持 windows、linux、macOs,目前仅支持cpu计算;
  • onnxruntime jvm demo: 以onnxruntime C++为基础,编译成jni供java或kotlin调用;
  • ncnn jvm demo: 以ncnn C++为基础,编译成jni供java或kotlin调用,同样分为cpu版与gpu版;
  • onnxruntime android demo: 以onnxruntime C++为基础,整合为一个独立的android模块供app调用;
  • ncnn jvm android demo: 以ncnn C++为基础,整合为一个独立的android模块供app调用,同样分为cpu版与gpu版;
  • MNN android demo: 以MNN C++为基础,整合为一个独立的android模块供app调用,支持cpu版本
  • onnxruntime c# demo: 完全以C#编写的onnxruntime demo;
  • onnxruntime vb.net demo: 完全以VB编写的onnxruntime demo;
  • 根据本项目和CRNN原理,推到出每个字符的位置demo,包括将字符组合成单词。

第三方Demo

  • TNN中文字符ocr: 根据本项目,基于TNN实现的轻量级中文字符ocr demo,支持iOS和Android系统,凭借TNN优化的CPU(ARMv7、ARMv8)和GPU(OpenCL、Metal)后端加速模型计算。

Android识别展示

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.NetDemo识别展示

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字符检测ocr Demo识别展示

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第三方 TNN Demo识别展示

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