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📘使用文档 | 🛠️安装指南 | 👀模型库 | 🆕更新日志 | 🤔报告问题

English | 简体中文

简介

MMSegmentation 是一个基于 PyTorch 的语义分割开源工具箱。它是 OpenMMLab 项目的一部分。

主分支代码目前支持 PyTorch 1.5 以上的版本。

示例图片

Major features

主要特性

  • 统一的基准平台

    我们将各种各样的语义分割算法集成到了一个统一的工具箱,进行基准测试。

  • 模块化设计

    MMSegmentation 将分割框架解耦成不同的模块组件,通过组合不同的模块组件,用户可以便捷地构建自定义的分割模型。

  • 丰富的即插即用的算法和模型

    MMSegmentation 支持了众多主流的和最新的检测算法,例如 PSPNet,DeepLabV3,PSANet,DeepLabV3+ 等.

  • 速度快

    训练速度比其他语义分割代码库更快或者相当。

最新进展

💎 稳定版本

最新版本 v0.30.0 在 2023.01.11 发布:

  • 添加 projects 目录以及示例项目
  • 支持高质量合成人脸数据集

如果想了解更多版本更新细节和历史信息,请阅读更新日志

🌟 1.x 预览版本

全新的 MMSegmentation v1.0.0rc3 版本已经在 2022.12.31 发布:

  • 基于 MMEngine 统一了各组件接口。
  • 全面支持混合精度,训练测试速度更快。
  • 重构之后更加灵活的架构

欢迎在 1.x branch 发现更多的新特性。欢迎 issue 和 PR。

安装

请参考快速入门文档进行安装,参考数据集准备处理数据。

快速入门

请参考训练教程测试教程学习 MMSegmentation 的基本使用。 我们也提供了一些进阶教程,内容覆盖了:

同时,我们提供了 Colab 教程。你可以在这里浏览教程,或者直接在 Colab 上运行

基准测试和模型库

测试结果和模型可以在模型库中找到。

已支持的骨干网络:

已支持的算法:

已支持的数据集:

常见问题

如果遇到问题,请参考 常见问题解答

贡献指南

我们感谢所有的贡献者为改进和提升 MMSegmentation 所作出的努力。请参考贡献指南来了解参与项目贡献的相关指引。

致谢

MMSegmentation 是一个由来自不同高校和企业的研发人员共同参与贡献的开源项目。我们感谢所有为项目提供算法复现和新功能支持的贡献者,以及提供宝贵反馈的用户。 我们希望这个工具箱和基准测试可以为社区提供灵活的代码工具,供用户复现已有算法并开发自己的新模型,从而不断为开源社区提供贡献。

引用

如果你觉得本项目对你的研究工作有所帮助,请参考如下 bibtex 引用 MMSegmentation。

@misc{mmseg2020,
    title={{MMSegmentation}: OpenMMLab Semantic Segmentation Toolbox and Benchmark},
    author={MMSegmentation Contributors},
    howpublished = {\url{https://github.com/open-mmlab/mmsegmentation}},
    year={2020}
}

开源许可证

MMSegmentation 目前以 Apache 2.0 的许可证发布,但是其中有一部分功能并不是使用的 Apache2.0 许可证,我们在 许可证 中详细地列出了这些功能以及他们对应的许可证,如果您正在从事盈利性活动,请谨慎参考此文档。

OpenMMLab 的其他项目

  • MMCV: OpenMMLab 计算机视觉基础库
  • MIM: MIM 是 OpenMMlab 项目、算法、模型的统一入口
  • MMClassification: OpenMMLab 图像分类工具箱
  • MMDetection: OpenMMLab 目标检测工具箱
  • MMDetection3D: OpenMMLab 新一代通用 3D 目标检测平台
  • MMYOLO: OpenMMLab YOLO 系列工具箱和基准测试
  • MMRotate: OpenMMLab 旋转框检测工具箱与测试基准
  • MMSegmentation: OpenMMLab 语义分割工具箱
  • MMOCR: OpenMMLab 全流程文字检测识别理解工具包
  • MMPose: OpenMMLab 姿态估计工具箱
  • MMHuman3D: OpenMMLab 人体参数化模型工具箱与测试基准
  • MMSelfSup: OpenMMLab 自监督学习工具箱与测试基准
  • MMRazor: OpenMMLab 模型压缩工具箱与测试基准
  • MMFewShot: OpenMMLab 少样本学习工具箱与测试基准
  • MMAction2: OpenMMLab 新一代视频理解工具箱
  • MMTracking: OpenMMLab 一体化视频目标感知平台
  • MMFlow: OpenMMLab 光流估计工具箱与测试基准
  • MMEditing: OpenMMLab 图像视频编辑工具箱
  • MMGeneration: OpenMMLab 图片视频生成模型工具箱
  • MMDeploy: OpenMMLab 模型部署框架

欢迎加入 OpenMMLab 社区

扫描下方的二维码可关注 OpenMMLab 团队的 知乎官方账号,加入 OpenMMLab 团队 以及 MMSegmentation 的 QQ 群。

我们会在 OpenMMLab 社区为大家

  • 📢 分享 AI 框架的前沿核心技术
  • 💻 解读 PyTorch 常用模块源码
  • 📰 发布 OpenMMLab 的相关新闻
  • 🚀 介绍 OpenMMLab 开发的前沿算法
  • 🏃 获取更高效的问题答疑和意见反馈
  • 🔥 提供与各行各业开发者充分交流的平台

干货满满 📘,等你来撩 💗,OpenMMLab 社区期待您的加入 👬

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简介

MMSegmentation 是一个基于 PyTorch 的语义分割开源工具箱。它是 OpenMMLab 项目的一部分 展开 收起
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