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README
LGPL-3.0

1. 仓库说明

代码采用gateway管理用户当前批次的四张图,用于跑后续分支的代码

本仓库可以简单看成P2023CpfAnalysis、P2024EyeMachine的针对性重建仓库

在执行流程上优化如下:

  1. 同时使用相机增益,以及相机原图(共计四张)
  2. 相机原图会被用于常规的增强-分割,最终形成类airdoc的报告
  3. 相机增益图将直接用于算法分析,从而形成简单的筛查报告

在算法层面的优化如下:

  1. 分级上去掉cam系列代码,仅保留分类
  2. 增强不变,在分割上优化精度以及种类

在后台部署上优化如下:

  1. 使用16GB的jetson外置运算开发板,并固定ip
  2. 测试完成后,使用docker无间断运行

在客户端层面的优化如下:

客户端用于跑通流程,以及渲染数据的操作, 数据管理仍然交付远程gateway

  1. 提供py接口,控制台全流程的跑通
  2. 提供cpp接口,控制台全流程的跑通, 用于后续接入明星的拍摄程序,以及修正的Qt客户端
  3. 提供修正的web ui, 以支持流程的可视化跑通
  4. 提供修正的Qt客户端(由于无法和明星程序通信),所以仍然采取扫描的方式

2. 程序模块说明

2.1 Client

如果需要移植,通常拷贝HtmlTemplate, xxxModule到对应语言的工程中即可

  • Doc: 存放gateway接口的文档, 以及一些sample的运行数据
  • HtmlTemplate: 用于渲染的HTML模板
  • SampleData: 示例数据
  • PyModule: 全流程Py执行流程以及示例
  • JavaScriptModule: 全流程Js执行流程以及示例
  • CppModule: 全流程cpp执行流程以及示例

2.2 Service

Service的根目录是仓库目录,不是单纯的某个文件夹

  • Doc: DrEdge代码逻辑文档
  • Docker: DrEdge的Service相关模块的打包文件
  • ThirdPart: Service的依赖项
  • Service
    • DensGradeService: 分级结果计算的服务
    • StillGanEnhanceService: 图像增强的服务
    • UNetSegmentationService: 病灶分割以及量化统计的服务
    • TaskMain: Client的数据管理以及服务调用中间人

2.3 DrUI

  • PyQtDemo: Dr开发期功能验证客户端(win桌面)
    • 不可用于生产环境,仅用于功能快速开发体验
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简介

明星DR筛查边缘算法后台,可看作P2023CpfAnalysis的下游针对性重建仓库 展开 收起
Python 等 6 种语言
LGPL-3.0
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