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diff --git a/README.md b/README.md
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-English | [简体中文](README_CN.md)
-
-# PaddleSeg
-
-[![Build Status](https://travis-ci.org/PaddlePaddle/PaddleSeg.svg?branch=master)](https://travis-ci.org/PaddlePaddle/PaddleSeg)
-[![License](https://img.shields.io/badge/license-Apache%202-blue.svg)](LICENSE)
-[![Version](https://img.shields.io/github/release/PaddlePaddle/PaddleSeg.svg)](https://github.com/PaddlePaddle/PaddleSeg/releases)
-![python version](https://img.shields.io/badge/python-3.6+-orange.svg)
-![support os](https://img.shields.io/badge/os-linux%2C%20win%2C%20mac-yellow.svg)
-
-<img src="./docs/images/seg_news_icon.png" width="50"/> *[2021-06-19] PaddleSeg Team won the AutoNUE 2021 Challenge: Semantic Segmentation Track in CVPR 2021! Technical Report can be found [here](https://bj.bcebos.com/paddleseg/docs/autonue21_presentation_PaddleSeg.pdf). Code will be coming soon.*
-
-![demo](./docs/images/cityscapes.gif)
-
-Welcome to PaddleSeg! PaddleSeg is an end-to-end image segmentation development kit developed based on [PaddlePaddle](https://www.paddlepaddle.org.cn), which covers a large number of high-quality segmentation models in different directions such as *high-performance* and *lightweight*. With the help of modular design, we provide two application methods: *Configuration Drive* and *API Calling*. So one can conveniently complete the entire image segmentation application from training to deployment through configuration calls or API calls.
-
-## Core Features
-
-* <img src="./docs/images/f1.png" width="20"/> **High Performance Model**: Based on the high-performance backbone trained by Baidu's self-developed [semi-supervised label knowledge distillation scheme (SSLD)](https://paddleclas.readthedocs.io/zh_CN/latest/advanced_tutorials/distillation/distillation.html#ssld), combined with the state of the art segmentation technology, we provides 50+ high-quality pre-training models, which are better than other open source implementations.
-
-* <img src="./docs/images/f2.png" width="20"/> **Modular Design**: PaddleSeg support 15+ mainstream *segmentation networks*, developers can start based on actual application scenarios and assemble diversified training configurations combined with modular design of *data enhancement strategies*, *backbone networks*, *loss functions* and other different components to meet different performance and accuracy requirements.
-
-* <img src="./docs/images/f3.png" width="20"/> **High Efficiency**: PaddleSeg provides multi-process asynchronous I/O, multi-card parallel training, evaluation and other acceleration strategies, combined with the memory optimization function of the PaddlePaddle, which can greatly reduce the training overhead of the segmentation model, all this allowing developers to lower cost and more efficiently train image segmentation model.
-
-* :heart:**You can go to  [Complete PaddleSeg Online Documentation Directory](https://paddleseg.readthedocs.io)  for more detailed documentation**:heart:
-
-## Technical Communication <img src="./docs/images/chat.png" width="30"/>
-
-* If you find any problems or have a suggestion with PaddleSeg, please send us issues through [GitHub Issues](https://github.com/PaddlePaddle/PaddleSeg/issues).
-* Welcome to Join PaddleSeg WeChat Group (left) and QQ Group (right)
-<div align="center">
-<img src="./docs/images/wechat_qq_623.png"  width = "500" />  
-</div>
-
-## Model Zoo
-
-|Model\Backbone|ResNet50|ResNet101|HRNetw18|HRNetw48|
-|-|-|-|-|-|
-|[ANN](./configs/ann)|✔|✔|||
-|[BiSeNetv2](./configs/bisenet)|-|-|-|-|
-|[DANet](./configs/danet)|✔|✔|||
-|[Deeplabv3](./configs/deeplabv3)|✔|✔|||
-|[Deeplabv3P](./configs/deeplabv3p)|✔|✔|||
-|[Fast-SCNN](./configs/fastscnn)|-|-|-|-|
-|[FCN](./configs/fcn)|||✔|✔|
-|[GCNet](./configs/gcnet)|✔|✔|||
-|[GSCNN](./configs/gscnn)|✔|✔|||
-|[HarDNet](./configs/hardnet)|-|-|-|-|
-|[OCRNet](./configs/ocrnet/)|||✔|✔|
-|[PSPNet](./configs/pspnet)|✔|✔|||
-|[U-Net](./configs/unet)|-|-|-|-|
-|[U<sup>2</sup>-Net](./configs/u2net)|-|-|-|-|
-|[Att U-Net](./configs/attention_unet)|-|-|-|-|
-|[U-Net++](./configs/unet_plusplus)|-|-|-|-|
-|[U-Net3+](./configs/unet_3plus)|-|-|-|-|
-|[DecoupledSegNet](./configs/decoupled_segnet)|✔|✔|||
-|[EMANet](./configs/emanet)|✔|✔|-|-|
-|[ISANet](./configs/isanet)|✔|✔|-|-|
-|[DNLNet](./configs/dnlnet)|✔|✔|-|-|
-|[SFNet](./configs/sfnet)|✔|-|-|-|
-|[PPSegLite](./configs/ppseg_lite)|-|-|-|-|
-
-## Dataset
-
-- [x] Cityscapes
-- [x] Pascal VOC
-- [x] ADE20K
-- [x] Pascal Context
-- [x] COCO stuff
-
-## Tutorials <img src="./docs/images/teach.png" width="30"/>
-
-* [Installation](./docs/install.md)
-* [Get Started](./docs/quick_start.md)
-*  Data Processing
-   * [Data Format Description](./docs/data/marker/marker_c.md)
-   * [Data Annotation and Transform](./docs/data/transform/transform_c.md)
-   * [Custom Dataset](./docs/data/custom/data_prepare.md)
-
-*  Design Idea of PaddleSeg
-    * [Detailed Configuration File](./docs/design/use/use.md)
-    * [Create Your Own Model](./docs/design/create/add_new_model.md)
-* [Model Training](/docs/train/train.md)
-* [Model Evaluation](./docs/evaluation/evaluate/evaluate.md)
-* [Model Export](./docs/export/export/model_export.md)
-
-*  Model Deploy
-    * [Inference](./docs/deployment/inference/inference.md)
-    * [Lite](./docs/deployment/lite/lite.md)
-    * [Serving](./docs/deployment/serving/serving.md)
-    * [Web](./docs/deployment/web/web.md)
-* [Model Compression](./docs/slim/slim/slim.md)
-*  API Tutorial
-    * [API Documention](./docs/apis)
-    * [API Application](./docs/api_example.md)
-*  Description of Important Modules
-    * [Data Augmentation](./docs/module/data/data.md)
-    * [Loss Description](./docs/module/loss/lovasz_loss.md)
-    * [Tricks](./docs/module/tricks/tricks.md)
-* Description of Classical Models
-    * [DeeplabV3](./docs/models/deeplabv3.md)
-    * [UNet](./docs/models/unet.md)
-    * [OCRNet](./docs/models/ocrnet.md)
-    * [Fast-SCNN](./docs/models/fascnn.md)
-* [PR Instruction](./docs/pr/pr/pr.md)
-* [FAQ](./docs/faq/faq/faq.md)
-
-## Installation
-
-#### step 1. Install PaddlePaddle
-
-System Requirements:
-* PaddlePaddle >= 2.0.0
-* Python >= 3.6+
-
-Highly recommend you install the GPU version of PaddlePaddle, due to large overhead of segmentation models, otherwise it could be out of memory while running the models. For more detailed installation tutorials, please refer to the official website of [PaddlePaddle](https://www.paddlepaddle.org.cn/install/quick?docurl=/documentation/docs/zh/2.0/install/)。
-
-
-#### step 2. Install PaddleSeg
-Support to construct a customized segmentation framework with *API Calling* method for flexible development.
-
-```shell
-pip install paddleseg
-```
-
-
-#### step 3. Download PaddleSeg Repo
-Support to complete the whole process segmentation application with *Configuration Drive* method, simple and fast.
-
-```shell
-git clone https://github.com/PaddlePaddle/PaddleSeg
-```
-
-#### step 4. Verify Installation
-Run the following command. If you can train normally, you have installed it successfully.
-
-```shell
-python train.py --config configs/quick_start/bisenet_optic_disc_512x512_1k.yml
-```
-
-
-## Practical Cases
-
-* [HumanSeg](./contrib/HumanSeg)
-* [Cityscapes SOTA](./contrib/CityscapesSOTA)
-* [PanopticSegmentation](./contrib/PanopticDeepLab)
-
-## Feedbacks and Contact
-* The dynamic version is still under development, if you find any issue or have an idea on new features, please don't hesitate to contact us via [GitHub Issues](https://github.com/PaddlePaddle/PaddleSeg/issues).
-* PaddleSeg User Group (QQ): 1004738029 or 850378321 or 793114768
-
-## Acknowledgement
-* Thanks [jm12138](https://github.com/jm12138) for contributing U<sup>2</sup>-Net.
-* Thanks [zjhellofss](https://github.com/zjhellofss) (Fu Shenshen) for contributing Attention U-Net, and Dice Loss.
-* Thanks [liuguoyu666](https://github.com/liguoyu666), [geoyee](https://github.com/geoyee) for contributing U-Net++ and U-Net3+.
-* Thanks [yazheng0307](https://github.com/yazheng0307) (LIU Zheng) for contributing quick-start document.
-
-## Citation
-If you find our project useful in your research, please consider citing:
-
-```latex
-@misc{liu2021paddleseg,
-      title={PaddleSeg: A High-Efficient Development Toolkit for Image Segmentation},
-      author={Yi Liu and Lutao Chu and Guowei Chen and Zewu Wu and Zeyu Chen and Baohua Lai and Yuying Hao},
-      year={2021},
-      eprint={2101.06175},
-      archivePrefix={arXiv},
-      primaryClass={cs.CV}
-}
-
-@misc{paddleseg2019,
-    title={PaddleSeg, End-to-end image segmentation kit based on PaddlePaddle},
-    author={PaddlePaddle Authors},
-    howpublished = {\url{https://github.com/PaddlePaddle/PaddleSeg}},
-    year={2019}
-}
-```
+README_CN.md
diff --git a/README_CN.md b/README_CN.md
@@ -1,4 +1,4 @@
-简体中文 | [English](README.md)
+简体中文 | [English](README_EN.md)
 
 # PaddleSeg
 

diff --git a/README_EN.md b/README_EN.md
@@ -0,0 +1,177 @@
+English | [简体中文](README_CN.md)
+
+# PaddleSeg
+
+[![Build Status](https://travis-ci.org/PaddlePaddle/PaddleSeg.svg?branch=master)](https://travis-ci.org/PaddlePaddle/PaddleSeg)
+[![License](https://img.shields.io/badge/license-Apache%202-blue.svg)](LICENSE)
+[![Version](https://img.shields.io/github/release/PaddlePaddle/PaddleSeg.svg)](https://github.com/PaddlePaddle/PaddleSeg/releases)
+![python version](https://img.shields.io/badge/python-3.6+-orange.svg)
+![support os](https://img.shields.io/badge/os-linux%2C%20win%2C%20mac-yellow.svg)
+
+<img src="./docs/images/seg_news_icon.png" width="50"/> *[2021-06-19] PaddleSeg Team won the AutoNUE 2021 Challenge: Semantic Segmentation Track in CVPR 2021! Technical Report can be found [here](https://bj.bcebos.com/paddleseg/docs/autonue21_presentation_PaddleSeg.pdf). Code will be coming soon.*
+
+![demo](./docs/images/cityscapes.gif)
+
+Welcome to PaddleSeg! PaddleSeg is an end-to-end image segmentation development kit developed based on [PaddlePaddle](https://www.paddlepaddle.org.cn), which covers a large number of high-quality segmentation models in different directions such as *high-performance* and *lightweight*. With the help of modular design, we provide two application methods: *Configuration Drive* and *API Calling*. So one can conveniently complete the entire image segmentation application from training to deployment through configuration calls or API calls.
+
+## Core Features
+
+* <img src="./docs/images/f1.png" width="20"/> **High Performance Model**: Based on the high-performance backbone trained by Baidu's self-developed [semi-supervised label knowledge distillation scheme (SSLD)](https://paddleclas.readthedocs.io/zh_CN/latest/advanced_tutorials/distillation/distillation.html#ssld), combined with the state of the art segmentation technology, we provides 50+ high-quality pre-training models, which are better than other open source implementations.
+
+* <img src="./docs/images/f2.png" width="20"/> **Modular Design**: PaddleSeg support 15+ mainstream *segmentation networks*, developers can start based on actual application scenarios and assemble diversified training configurations combined with modular design of *data enhancement strategies*, *backbone networks*, *loss functions* and other different components to meet different performance and accuracy requirements.
+
+* <img src="./docs/images/f3.png" width="20"/> **High Efficiency**: PaddleSeg provides multi-process asynchronous I/O, multi-card parallel training, evaluation and other acceleration strategies, combined with the memory optimization function of the PaddlePaddle, which can greatly reduce the training overhead of the segmentation model, all this allowing developers to lower cost and more efficiently train image segmentation model.
+
+* :heart:**You can go to  [Complete PaddleSeg Online Documentation Directory](https://paddleseg.readthedocs.io)  for more detailed documentation**:heart:
+
+## Technical Communication <img src="./docs/images/chat.png" width="30"/>
+
+* If you find any problems or have a suggestion with PaddleSeg, please send us issues through [GitHub Issues](https://github.com/PaddlePaddle/PaddleSeg/issues).
+* Welcome to Join PaddleSeg WeChat Group (left) and QQ Group (right)
+<div align="center">
+<img src="./docs/images/wechat_qq_623.png"  width = "500" />  
+</div>
+
+## Model Zoo
+
+|Model\Backbone|ResNet50|ResNet101|HRNetw18|HRNetw48|
+|-|-|-|-|-|
+|[ANN](./configs/ann)|✔|✔|||
+|[BiSeNetv2](./configs/bisenet)|-|-|-|-|
+|[DANet](./configs/danet)|✔|✔|||
+|[Deeplabv3](./configs/deeplabv3)|✔|✔|||
+|[Deeplabv3P](./configs/deeplabv3p)|✔|✔|||
+|[Fast-SCNN](./configs/fastscnn)|-|-|-|-|
+|[FCN](./configs/fcn)|||✔|✔|
+|[GCNet](./configs/gcnet)|✔|✔|||
+|[GSCNN](./configs/gscnn)|✔|✔|||
+|[HarDNet](./configs/hardnet)|-|-|-|-|
+|[OCRNet](./configs/ocrnet/)|||✔|✔|
+|[PSPNet](./configs/pspnet)|✔|✔|||
+|[U-Net](./configs/unet)|-|-|-|-|
+|[U<sup>2</sup>-Net](./configs/u2net)|-|-|-|-|
+|[Att U-Net](./configs/attention_unet)|-|-|-|-|
+|[U-Net++](./configs/unet_plusplus)|-|-|-|-|
+|[U-Net3+](./configs/unet_3plus)|-|-|-|-|
+|[DecoupledSegNet](./configs/decoupled_segnet)|✔|✔|||
+|[EMANet](./configs/emanet)|✔|✔|-|-|
+|[ISANet](./configs/isanet)|✔|✔|-|-|
+|[DNLNet](./configs/dnlnet)|✔|✔|-|-|
+|[SFNet](./configs/sfnet)|✔|-|-|-|
+|[PPSegLite](./configs/ppseg_lite)|-|-|-|-|
+
+## Dataset
+
+- [x] Cityscapes
+- [x] Pascal VOC
+- [x] ADE20K
+- [x] Pascal Context
+- [x] COCO stuff
+
+## Tutorials <img src="./docs/images/teach.png" width="30"/>
+
+* [Installation](./docs/install.md)
+* [Get Started](./docs/quick_start.md)
+*  Data Processing
+   * [Data Format Description](./docs/data/marker/marker_c.md)
+   * [Data Annotation and Transform](./docs/data/transform/transform_c.md)
+   * [Custom Dataset](./docs/data/custom/data_prepare.md)
+
+*  Design Idea of PaddleSeg
+    * [Detailed Configuration File](./docs/design/use/use.md)
+    * [Create Your Own Model](./docs/design/create/add_new_model.md)
+* [Model Training](/docs/train/train.md)
+* [Model Evaluation](./docs/evaluation/evaluate/evaluate.md)
+* [Model Export](./docs/export/export/model_export.md)
+
+*  Model Deploy
+    * [Inference](./docs/deployment/inference/inference.md)
+    * [Lite](./docs/deployment/lite/lite.md)
+    * [Serving](./docs/deployment/serving/serving.md)
+    * [Web](./docs/deployment/web/web.md)
+* [Model Compression](./docs/slim/slim/slim.md)
+*  API Tutorial
+    * [API Documention](./docs/apis)
+    * [API Application](./docs/api_example.md)
+*  Description of Important Modules
+    * [Data Augmentation](./docs/module/data/data.md)
+    * [Loss Description](./docs/module/loss/lovasz_loss.md)
+    * [Tricks](./docs/module/tricks/tricks.md)
+* Description of Classical Models
+    * [DeeplabV3](./docs/models/deeplabv3.md)
+    * [UNet](./docs/models/unet.md)
+    * [OCRNet](./docs/models/ocrnet.md)
+    * [Fast-SCNN](./docs/models/fascnn.md)
+* [PR Instruction](./docs/pr/pr/pr.md)
+* [FAQ](./docs/faq/faq/faq.md)
+
+## Installation
+
+#### step 1. Install PaddlePaddle
+
+System Requirements:
+* PaddlePaddle >= 2.0.0
+* Python >= 3.6+
+
+Highly recommend you install the GPU version of PaddlePaddle, due to large overhead of segmentation models, otherwise it could be out of memory while running the models. For more detailed installation tutorials, please refer to the official website of [PaddlePaddle](https://www.paddlepaddle.org.cn/install/quick?docurl=/documentation/docs/zh/2.0/install/)。
+
+
+#### step 2. Install PaddleSeg
+Support to construct a customized segmentation framework with *API Calling* method for flexible development.
+
+```shell
+pip install paddleseg
+```
+
+
+#### step 3. Download PaddleSeg Repo
+Support to complete the whole process segmentation application with *Configuration Drive* method, simple and fast.
+
+```shell
+git clone https://github.com/PaddlePaddle/PaddleSeg
+```
+
+#### step 4. Verify Installation
+Run the following command. If you can train normally, you have installed it successfully.
+
+```shell
+python train.py --config configs/quick_start/bisenet_optic_disc_512x512_1k.yml
+```
+
+
+## Practical Cases
+
+* [HumanSeg](./contrib/HumanSeg)
+* [Cityscapes SOTA](./contrib/CityscapesSOTA)
+* [PanopticSegmentation](./contrib/PanopticDeepLab)
+
+## Feedbacks and Contact
+* The dynamic version is still under development, if you find any issue or have an idea on new features, please don't hesitate to contact us via [GitHub Issues](https://github.com/PaddlePaddle/PaddleSeg/issues).
+* PaddleSeg User Group (QQ): 1004738029 or 850378321 or 793114768
+
+## Acknowledgement
+* Thanks [jm12138](https://github.com/jm12138) for contributing U<sup>2</sup>-Net.
+* Thanks [zjhellofss](https://github.com/zjhellofss) (Fu Shenshen) for contributing Attention U-Net, and Dice Loss.
+* Thanks [liuguoyu666](https://github.com/liguoyu666), [geoyee](https://github.com/geoyee) for contributing U-Net++ and U-Net3+.
+* Thanks [yazheng0307](https://github.com/yazheng0307) (LIU Zheng) for contributing quick-start document.
+
+## Citation
+If you find our project useful in your research, please consider citing:
+
+```latex
+@misc{liu2021paddleseg,
+      title={PaddleSeg: A High-Efficient Development Toolkit for Image Segmentation},
+      author={Yi Liu and Lutao Chu and Guowei Chen and Zewu Wu and Zeyu Chen and Baohua Lai and Yuying Hao},
+      year={2021},
+      eprint={2101.06175},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV}
+}
+
+@misc{paddleseg2019,
+    title={PaddleSeg, End-to-end image segmentation kit based on PaddlePaddle},
+    author={PaddlePaddle Authors},
+    howpublished = {\url{https://github.com/PaddlePaddle/PaddleSeg}},
+    year={2019}
+}
+```