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README
Apache-2.0

English | 简体中文

Introduction

MMFewShot 是一款基于 PyTorch 的少样本学习代码库,是 OpenMMLab 项目的成员之一。

主分支代码目前支持 PyTorch 1.5 以上的版本。

主要特性

  • 支持多种少样本任务

    MMFewShot 为少样本分类和检测任务提供了的统一实现和评估框架。

  • 模块化设计

    MMFewShot 将不同少样本任务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少样本算法模型。

  • 强大的基准模型与SOTA

    MMFewShot 提供了少样本分类和检测任务中最先进的算法和强大的基准模型.

更新

v0.1.0 版本已于 2021 年 11 月 24 日发布,可通过查阅更新日志了解更多细节以及发布历史。

安装与准备数据集

MMFewShot 依赖 PyTorchMMCV 。 请参考安装文档进行安装和参考数据准备准备数据集。

开始使用 MMFewShot

如果初次了解少样本学习,你可以从基础介绍开始了解少样本学习的基本概念和 MMFewShot 的框架。 如果对少样本学习很熟悉,请参考使用教程获取MMFewShot的基本用法。

MMFewShot 也提供了其他更详细的教程,包括:

基准测试和模型库

本工具箱支持的各个模型的结果和设置都可以在模型库页面中查看。

已支持的算法:

classification
Detection

参与贡献

我们感谢所有的贡献者为改进和提升 MMFewShot 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

MMFewShot 是一款由不同学校和公司共同贡献的开源项目。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。

我们希望该工具箱和基准测试可以为社区提供灵活的代码工具,供用户复现现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

如果您发现此项目对您的研究有用,请考虑引用:

@misc{mmfewshot2021,
    title={OpenMMLab Few Shot Learning Toolbox and Benchmark},
    author={mmfewshot Contributors},
    howpublished = {\url{https://github.com/open-mmlab/mmfewshot}},
    year={2021}
}

许可

该项目遵循Apache 2.0 license开源协议。

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
  • 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 团队的 官方交流 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

基于 MMClassification 和 MMDetetection 的开源少样本算法库,为少样本分类和检测算法提供了统一的框架和评估标准,是 OpenMMLab 项目的成员之一。 展开 收起
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