From 457077448ff3ba0b6279c5c55356ba46b98a8bee Mon Sep 17 00:00:00 2001 From: MengzhangLI Date: Thu, 26 Aug 2021 18:35:35 +0800 Subject: [PATCH] [Fix] Fix some typos in README.md (#824) * fix README * Update README.md Co-authored-by: Junjun2016 * Update README_zh-CN.md Co-authored-by: Junjun2016 Co-authored-by: Junjun2016 --- README.md | 5 +++-- README_zh-CN.md | 5 +++-- 2 files changed, 6 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index 152955531..fb4e67e36 100644 --- a/README.md +++ b/README.md @@ -64,7 +64,7 @@ Supported backbones: - [x] [MobileNetV2 (CVPR'2018)](configs/mobilenet_v2) - [x] [MobileNetV3 (ICCV'2019)](configs/mobilenet_v3) - [x] [Vision Transformer (ICLR'2021)](configs/vit) -- [x] [Swin Transformer (arXiV'2021)](configs/swin) +- [x] [Swin Transformer (ArXiv'2021)](configs/swin) Supported methods: @@ -92,6 +92,7 @@ Supported methods: - [x] [PointRend (CVPR'2020)](configs/point_rend) - [x] [CGNet (TIP'2020)](configs/cgnet) - [x] [SETR (CVPR'2021)](configs/setr) +- [x] [SegFormer (ArXiv'2021)](configs/segformer) ## Installation @@ -101,7 +102,7 @@ Please refer to [get_started.md](docs/get_started.md#installation) for installat Please see [train.md](docs/train.md) and [inference.md](docs/inference.md) for the basic usage of MMSegmentation. There are also tutorials for [customizing dataset](docs/tutorials/customize_datasets.md), [designing data pipeline](docs/tutorials/data_pipeline.md), [customizing modules](docs/tutorials/customize_models.md), and [customizing runtime](docs/tutorials/customize_runtime.md). -We also provide many [training tricks](docs/tutorials/training_tricks.md). +We also provide many [training tricks](docs/tutorials/training_tricks.md) for better training and [usefule tools](docs/useful_tools.md) for deployment. 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/master/demo/MMSegmentation_Tutorial.ipynb) on Colab. diff --git a/README_zh-CN.md b/README_zh-CN.md index 01536b86f..9dc7ba539 100644 --- a/README_zh-CN.md +++ b/README_zh-CN.md @@ -63,7 +63,7 @@ MMSegmentation 是一个基于 PyTorch 的语义分割开源工具箱。它是 O - [x] [MobileNetV2 (CVPR'2018)](configs/mobilenet_v2) - [x] [MobileNetV3 (ICCV'2019)](configs/mobilenet_v3) - [x] [Vision Transformer (ICLR'2021)](configs/vit) -- [x] [Swin Transformer (arXiV'2021)](configs/swin) +- [x] [Swin Transformer (ArXiv'2021)](configs/swin) 已支持的算法： @@ -91,6 +91,7 @@ MMSegmentation 是一个基于 PyTorch 的语义分割开源工具箱。它是 O - [x] [PointRend (CVPR'2020)](configs/point_rend) - [x] [CGNet (TIP'2020)](configs/cgnet) - [x] [SETR (CVPR'2021)](configs/setr) +- [x] [SegFormer (ArXiv'2021)](configs/segformer) ## 安装 @@ -100,7 +101,7 @@ MMSegmentation 是一个基于 PyTorch 的语义分割开源工具箱。它是 O 请参考[训练教程](docs_zh-CN/train.md)和[测试教程](docs_zh-CN/inference.md)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[增加自定义数据集](docs_zh-CN/tutorials/customize_datasets.md)，[设计新的数据预处理流程](docs_zh-CN/tutorials/data_pipeline.md)，[增加自定义模型](docs_zh-CN/tutorials/customize_models.md)，[增加自定义的运行时配置](docs_zh-CN/tutorials/customize_runtime.md)。 -除此之外，我们也提供了很多实用的[训练技巧说明](docs_zh-CN/tutorials/training_tricks.md)。 +除此之外，我们也提供了很多实用的[训练技巧说明](docs_zh-CN/tutorials/training_tricks.md)和模型部署相关的[有用的工具](docs_zh-CN/useful_tools.md)。 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/master/demo/MMSegmentation_Tutorial.ipynb)。