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@ -20,14 +20,14 @@
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/mmsegmentation)](https://pypi.org/project/mmsegmentation/)
[![PyPI](https://img.shields.io/pypi/v/mmsegmentation)](https://pypi.org/project/mmsegmentation)
[![docs](https://img.shields.io/badge/docs-latest-blue)](https://mmsegmentation.readthedocs.io/en/1.x/)
[![docs](https://img.shields.io/badge/docs-latest-blue)](https://mmsegmentation.readthedocs.io/en/main/)
[![badge](https://github.com/open-mmlab/mmsegmentation/workflows/build/badge.svg)](https://github.com/open-mmlab/mmsegmentation/actions)
[![codecov](https://codecov.io/gh/open-mmlab/mmsegmentation/branch/master/graph/badge.svg)](https://codecov.io/gh/open-mmlab/mmsegmentation)
[![license](https://img.shields.io/github/license/open-mmlab/mmsegmentation.svg)](https://github.com/open-mmlab/mmsegmentation/blob/1.x/LICENSE)
[![license](https://img.shields.io/github/license/open-mmlab/mmsegmentation.svg)](https://github.com/open-mmlab/mmsegmentation/blob/main/LICENSE)
[![issue resolution](https://isitmaintained.com/badge/resolution/open-mmlab/mmsegmentation.svg)](https://github.com/open-mmlab/mmsegmentation/issues)
[![open issues](https://isitmaintained.com/badge/open/open-mmlab/mmsegmentation.svg)](https://github.com/open-mmlab/mmsegmentation/issues)
Documentation: <https://mmsegmentation.readthedocs.io/en/1.x/>
Documentation: <https://mmsegmentation.readthedocs.io/en/main/>
English | [简体中文](README_zh-CN.md)
@ -58,7 +58,7 @@ English | [简体中文](README_zh-CN.md)
MMSegmentation is an open source semantic segmentation toolbox based on PyTorch.
It is a part of the OpenMMLab project.
The 1.x branch works with **PyTorch 1.6+**.
The main branch works with **PyTorch 1.6+**.
![demo image](resources/seg_demo.gif)
@ -96,12 +96,12 @@ Please refer to [get_started.md](docs/en/get_started.md#installation) for instal
Please see [Overview](docs/en/overview.md) for the general introduction of MMSegmentation.
Please see [user guides](https://mmsegmentation.readthedocs.io/en/1.x/user_guides/index.html#) for the basic usage of MMSegmentation.
Please see [user guides](https://mmsegmentation.readthedocs.io/en/main/user_guides/index.html#) for the basic usage of MMSegmentation.
There are also [advanced tutorials](https://mmsegmentation.readthedocs.io/en/main/advanced_guides/index.html) for in-depth understanding of mmseg design and implementation .
A Colab tutorial is also provided. You may preview the notebook [here](demo/MMSegmentation_Tutorial.ipynb) or directly [run](https://colab.research.google.com/github/open-mmlab/mmsegmentation/blob/1.x/demo/MMSegmentation_Tutorial.ipynb) on Colab.
A Colab tutorial is also provided. You may preview the notebook [here](demo/MMSegmentation_Tutorial.ipynb) or directly [run](https://colab.research.google.com/github/open-mmlab/mmsegmentation/blob/main/demo/MMSegmentation_Tutorial.ipynb) on Colab.
To migrate from MMSegmentation 1.x, please refer to [migration](docs/en/migration).
To migrate from MMSegmentation 0.x, please refer to [migration](docs/en/migration).
## Benchmark and model zoo
@ -173,23 +173,23 @@ Results and models are available in the [model zoo](docs/en/model_zoo.md).
<details open>
<summary>Supported datasets:</summary>
- [x] [Cityscapes](https://github.com/open-mmlab/mmsegmentation/blob/1.x/docs/en/user_guides/2_dataset_prepare.md#cityscapes)
- [x] [PASCAL VOC](https://github.com/open-mmlab/mmsegmentation/blob/1.x/docs/en/user_guides/2_dataset_prepare.md#pascal-voc)
- [x] [ADE20K](https://github.com/open-mmlab/mmsegmentation/blob/1.x/docs/en/user_guides/2_dataset_prepare.md#ade20k)
- [x] [Pascal Context](https://github.com/open-mmlab/mmsegmentation/blob/1.x/docs/en/user_guides/2_dataset_prepare.md#pascal-context)
- [x] [COCO-Stuff 10k](https://github.com/open-mmlab/mmsegmentation/blob/1.x/docs/en/user_guides/2_dataset_prepare.md#coco-stuff-10k)
- [x] [COCO-Stuff 164k](https://github.com/open-mmlab/mmsegmentation/blob/1.x/docs/en/user_guides/2_dataset_prepare.md#coco-stuff-164k)
- [x] [CHASE_DB1](https://github.com/open-mmlab/mmsegmentation/blob/1.x/docs/en/user_guides/2_dataset_prepare.md#chase-db1)
- [x] [DRIVE](https://github.com/open-mmlab/mmsegmentation/blob/1.x/docs/en/user_guides/2_dataset_prepare.md#drive)
- [x] [HRF](https://github.com/open-mmlab/mmsegmentation/blob/1.x/docs/en/user_guides/2_dataset_prepare.md#hrf)
- [x] [STARE](https://github.com/open-mmlab/mmsegmentation/blob/1.x/docs/en/user_guides/2_dataset_prepare.md#stare)
- [x] [Dark Zurich](https://github.com/open-mmlab/mmsegmentation/blob/1.x/docs/en/user_guides/2_dataset_prepare.md#dark-zurich)
- [x] [Nighttime Driving](https://github.com/open-mmlab/mmsegmentation/blob/1.x/docs/en/user_guides/2_dataset_prepare.md#nighttime-driving)
- [x] [LoveDA](https://github.com/open-mmlab/mmsegmentation/blob/1.x/docs/en/user_guides/2_dataset_prepare.md#loveda)
- [x] [Potsdam](https://github.com/open-mmlab/mmsegmentation/blob/1.x/docs/en/user_guides/2_dataset_prepare.md#isprs-potsdam)
- [x] [Vaihingen](https://github.com/open-mmlab/mmsegmentation/blob/1.x/docs/en/user_guides/2_dataset_prepare.md#isprs-vaihingen)
- [x] [iSAID](https://github.com/open-mmlab/mmsegmentation/blob/1.x/docs/en/user_guides/2_dataset_prepare.md#isaid)
- [x] [Mapillary Vistas](https://github.com/open-mmlab/mmsegmentation/blob/1.x/docs/en/user_guides/2_dataset_prepare.md#mapillary-vistas-datasets)
- [x] [Cityscapes](https://github.com/open-mmlab/mmsegmentation/blob/main/docs/en/user_guides/2_dataset_prepare.md#cityscapes)
- [x] [PASCAL VOC](https://github.com/open-mmlab/mmsegmentation/blob/main/docs/en/user_guides/2_dataset_prepare.md#pascal-voc)
- [x] [ADE20K](https://github.com/open-mmlab/mmsegmentation/blob/main/docs/en/user_guides/2_dataset_prepare.md#ade20k)
- [x] [Pascal Context](https://github.com/open-mmlab/mmsegmentation/blob/main/docs/en/user_guides/2_dataset_prepare.md#pascal-context)
- [x] [COCO-Stuff 10k](https://github.com/open-mmlab/mmsegmentation/blob/main/docs/en/user_guides/2_dataset_prepare.md#coco-stuff-10k)
- [x] [COCO-Stuff 164k](https://github.com/open-mmlab/mmsegmentation/blob/main/docs/en/user_guides/2_dataset_prepare.md#coco-stuff-164k)
- [x] [CHASE_DB1](https://github.com/open-mmlab/mmsegmentation/blob/main/docs/en/user_guides/2_dataset_prepare.md#chase-db1)
- [x] [DRIVE](https://github.com/open-mmlab/mmsegmentation/blob/main/docs/en/user_guides/2_dataset_prepare.md#drive)
- [x] [HRF](https://github.com/open-mmlab/mmsegmentation/blob/main/docs/en/user_guides/2_dataset_prepare.md#hrf)
- [x] [STARE](https://github.com/open-mmlab/mmsegmentation/blob/main/docs/en/user_guides/2_dataset_prepare.md#stare)
- [x] [Dark Zurich](https://github.com/open-mmlab/mmsegmentation/blob/main/docs/en/user_guides/2_dataset_prepare.md#dark-zurich)
- [x] [Nighttime Driving](https://github.com/open-mmlab/mmsegmentation/blob/main/docs/en/user_guides/2_dataset_prepare.md#nighttime-driving)
- [x] [LoveDA](https://github.com/open-mmlab/mmsegmentation/blob/main/docs/en/user_guides/2_dataset_prepare.md#loveda)
- [x] [Potsdam](https://github.com/open-mmlab/mmsegmentation/blob/main/docs/en/user_guides/2_dataset_prepare.md#isprs-potsdam)
- [x] [Vaihingen](https://github.com/open-mmlab/mmsegmentation/blob/main/docs/en/user_guides/2_dataset_prepare.md#isprs-vaihingen)
- [x] [iSAID](https://github.com/open-mmlab/mmsegmentation/blob/main/docs/en/user_guides/2_dataset_prepare.md#isaid)
- [x] [Mapillary Vistas](https://github.com/open-mmlab/mmsegmentation/blob/main/docs/en/user_guides/2_dataset_prepare.md#mapillary-vistas-datasets)
</details>

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README_zh-CN.md
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@ -20,14 +20,14 @@
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/mmsegmentation)](https://pypi.org/project/mmsegmentation/)
[![PyPI](https://img.shields.io/pypi/v/mmsegmentation)](https://pypi.org/project/mmsegmentation)
[![docs](https://img.shields.io/badge/docs-latest-blue)](https://mmsegmentation.readthedocs.io/zh_CN/1.x/)
[![docs](https://img.shields.io/badge/docs-latest-blue)](https://mmsegmentation.readthedocs.io/zh_CN/main/)
[![badge](https://github.com/open-mmlab/mmsegmentation/workflows/build/badge.svg)](https://github.com/open-mmlab/mmsegmentation/actions)
[![codecov](https://codecov.io/gh/open-mmlab/mmsegmentation/branch/master/graph/badge.svg)](https://codecov.io/gh/open-mmlab/mmsegmentation)
[![license](https://img.shields.io/github/license/open-mmlab/mmsegmentation.svg)](https://github.com/open-mmlab/mmsegmentation/blob/1.x/LICENSE)
[![license](https://img.shields.io/github/license/open-mmlab/mmsegmentation.svg)](https://github.com/open-mmlab/mmsegmentation/blob/main/LICENSE)
[![issue resolution](https://isitmaintained.com/badge/resolution/open-mmlab/mmsegmentation.svg)](https://github.com/open-mmlab/mmsegmentation/issues)
[![open issues](https://isitmaintained.com/badge/open/open-mmlab/mmsegmentation.svg)](https://github.com/open-mmlab/mmsegmentation/issues)
文档: <https://mmsegmentation.readthedocs.io/zh_CN/latest>
文档: <https://mmsegmentation.readthedocs.io/zh_CN/main>
[English](README.md) | 简体中文
@ -57,7 +57,7 @@
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。
1.x 分支代码目前支持 PyTorch 1.6 以上的版本。
main 分支代码目前支持 PyTorch 1.6 以上的版本。
![示例图片](resources/seg_demo.gif)
@ -92,11 +92,11 @@ MMSegmentation 是一个基于 PyTorch 的语义分割开源工具箱。它是 O
请参考[概述](docs/zh_cn/overview.md)对 MMSegmetation 进行初步了解
请参考[用户指南](https://mmsegmentation.readthedocs.io/zh_CN/1.x/user_guides/index.html)了解 mmseg 的基本使用，以及[进阶指南](https://mmsegmentation.readthedocs.io/zh_CN/1.x/advanced_guides/index.html)深入了解 mmseg 设计和代码实现。
请参考[用户指南](https://mmsegmentation.readthedocs.io/zh_CN/main/user_guides/index.html)了解 mmseg 的基本使用，以及[进阶指南](https://mmsegmentation.readthedocs.io/zh_CN/main/advanced_guides/index.html)深入了解 mmseg 设计和代码实现。
同时，我们提供了 Colab 教程。你可以在[这里](demo/MMSegmentation_Tutorial.ipynb)浏览教程，或者直接在 Colab 上[运行](https://colab.research.google.com/github/open-mmlab/mmsegmentation/blob/1.x/demo/MMSegmentation_Tutorial.ipynb)。
同时，我们提供了 Colab 教程。你可以在[这里](demo/MMSegmentation_Tutorial.ipynb)浏览教程，或者直接在 Colab 上[运行](https://colab.research.google.com/github/open-mmlab/mmsegmentation/blob/main/demo/MMSegmentation_Tutorial.ipynb)。
若需要将0.x版本的代码迁移至新版，请参考[迁移文档](docs/zh_cn/migration)。
若需要将 0.x 版本的代码迁移至新版，请参考[迁移文档](docs/zh_cn/migration)。
## 基准测试和模型库
@ -168,23 +168,23 @@ MMSegmentation 是一个基于 PyTorch 的语义分割开源工具箱。它是 O
<details open>
<summary>已支持的数据集：</summary>
- [x] [Cityscapes](https://github.com/open-mmlab/mmsegmentation/blob/1.x/docs/zh_cn/dataset_prepare.md#cityscapes)
- [x] [PASCAL VOC](https://github.com/open-mmlab/mmsegmentation/blob/1.x/docs/zh_cn/dataset_prepare.md#pascal-voc)
- [x] [ADE20K](https://github.com/open-mmlab/mmsegmentation/blob/1.x/docs/zh_cn/dataset_prepare.md#ade20k)
- [x] [Pascal Context](https://github.com/open-mmlab/mmsegmentation/blob/1.x/docs/zh_cn/dataset_prepare.md#pascal-context)
- [x] [COCO-Stuff 10k](https://github.com/open-mmlab/mmsegmentation/blob/1.x/docs/zh_cn/dataset_prepare.md#coco-stuff-10k)
- [x] [COCO-Stuff 164k](https://github.com/open-mmlab/mmsegmentation/blob/1.x/docs/zh_cn/dataset_prepare.md#coco-stuff-164k)
- [x] [CHASE_DB1](https://github.com/open-mmlab/mmsegmentation/blob/1.x/docs/zh_cn/dataset_prepare.md#chase-db1)
- [x] [DRIVE](https://github.com/open-mmlab/mmsegmentation/blob/1.x/docs/zh_cn/dataset_prepare.md#drive)
- [x] [HRF](https://github.com/open-mmlab/mmsegmentation/blob/1.x/docs/zh_cn/dataset_prepare.md#hrf)
- [x] [STARE](https://github.com/open-mmlab/mmsegmentation/blob/1.x/docs/zh_cn/dataset_prepare.md#stare)
- [x] [Dark Zurich](https://github.com/open-mmlab/mmsegmentation/blob/1.x/docs/zh_cn/dataset_prepare.md#dark-zurich)
- [x] [Nighttime Driving](https://github.com/open-mmlab/mmsegmentation/blob/1.x/docs/zh_cn/dataset_prepare.md#nighttime-driving)
- [x] [LoveDA](https://github.com/open-mmlab/mmsegmentation/blob/1.x/docs/zh_cn/dataset_prepare.md#loveda)
- [x] [Potsdam](https://github.com/open-mmlab/mmsegmentation/blob/1.x/docs/zh_cn/dataset_prepare.md#isprs-potsdam)
- [x] [Vaihingen](https://github.com/open-mmlab/mmsegmentation/blob/1.x/docs/zh_cn/dataset_prepare.md#isprs-vaihingen)
- [x] [iSAID](https://github.com/open-mmlab/mmsegmentation/blob/1.x/docs/zh_cn/dataset_prepare.md#isaid)
- [x] [Mapillary Vistas](https://github.com/open-mmlab/mmsegmentation/blob/1.x/docs/en/user_guides/2_dataset_prepare.md#mapillary-vistas-datasets)
- [x] [Cityscapes](https://github.com/open-mmlab/mmsegmentation/blob/main/docs/zh_cn/dataset_prepare.md#cityscapes)
- [x] [PASCAL VOC](https://github.com/open-mmlab/mmsegmentation/blob/main/docs/zh_cn/dataset_prepare.md#pascal-voc)
- [x] [ADE20K](https://github.com/open-mmlab/mmsegmentation/blob/main/docs/zh_cn/dataset_prepare.md#ade20k)
- [x] [Pascal Context](https://github.com/open-mmlab/mmsegmentation/blob/main/docs/zh_cn/dataset_prepare.md#pascal-context)
- [x] [COCO-Stuff 10k](https://github.com/open-mmlab/mmsegmentation/blob/main/docs/zh_cn/dataset_prepare.md#coco-stuff-10k)
- [x] [COCO-Stuff 164k](https://github.com/open-mmlab/mmsegmentation/blob/main/docs/zh_cn/dataset_prepare.md#coco-stuff-164k)
- [x] [CHASE_DB1](https://github.com/open-mmlab/mmsegmentation/blob/main/docs/zh_cn/dataset_prepare.md#chase-db1)
- [x] [DRIVE](https://github.com/open-mmlab/mmsegmentation/blob/main/docs/zh_cn/dataset_prepare.md#drive)
- [x] [HRF](https://github.com/open-mmlab/mmsegmentation/blob/main/docs/zh_cn/dataset_prepare.md#hrf)
- [x] [STARE](https://github.com/open-mmlab/mmsegmentation/blob/main/docs/zh_cn/dataset_prepare.md#stare)
- [x] [Dark Zurich](https://github.com/open-mmlab/mmsegmentation/blob/main/docs/zh_cn/dataset_prepare.md#dark-zurich)
- [x] [Nighttime Driving](https://github.com/open-mmlab/mmsegmentation/blob/main/docs/zh_cn/dataset_prepare.md#nighttime-driving)
- [x] [LoveDA](https://github.com/open-mmlab/mmsegmentation/blob/main/docs/zh_cn/dataset_prepare.md#loveda)
- [x] [Potsdam](https://github.com/open-mmlab/mmsegmentation/blob/main/docs/zh_cn/dataset_prepare.md#isprs-potsdam)
- [x] [Vaihingen](https://github.com/open-mmlab/mmsegmentation/blob/main/docs/zh_cn/dataset_prepare.md#isprs-vaihingen)
- [x] [iSAID](https://github.com/open-mmlab/mmsegmentation/blob/main/docs/zh_cn/dataset_prepare.md#isaid)
- [x] [Mapillary Vistas](https://github.com/open-mmlab/mmsegmentation/blob/main/docs/en/user_guides/2_dataset_prepare.md#mapillary-vistas-datasets)
</details>