[Enhancement] refine the install doc (PaddlePaddle#2073)

Author: juncaipeng

benchmark/README.md

@@ -2,6 +2,8 @@ English | [简体中文](README_CN.md)
 
 # Benchmark Introduction
 
+`PaddleSeg/benchmark` is used for monitoring the speed of model training.
+
 The content is as follow:
 
 ```

benchmark/README_CN.md

@@ -2,6 +2,9 @@
 
 # Benchmark说明
 
+`PaddleSeg/benchmark`用于监控模型训练的速度。
+
+
 目录结构如下：
 ```
 ├── README.md  

configs/README.md

@@ -1,4 +1,7 @@
 English | [简体中文](README_cn.md)
+
+The config files of different models are saved in `PaddleSeg/configs`.
+PaddleSeg use the config files to train, validate and export models.
 # Configuration items
 
 ----

configs/README_cn.md

@@ -1,3 +1,4 @@
+大量模型的配置文件保存在`PaddleSeg/configs`目录下。 PaddleSeg使用这些配置文件进行模型训练、测试和导出。
 
 # 配置项
 

docs/install.md

@@ -13,62 +13,68 @@ English | [简体中文](install_cn.md)
 
 ### 1. Install PaddlePaddle
 
+Please refer to the [installation doc](https://www.paddlepaddle.org.cn/documentation/docs/en/install/index_en.html) to install PaddlePaddle (the version >= 2.2).
+
 Highly recommend you install the GPU version of PaddlePaddle, due to the large overhead of segmentation models, otherwise, it could be out of memory while running the models.
 
-```
-# CUDA10.1
-python -m pip install paddlepaddle-gpu==2.2.1.post101 -f https://www.paddlepaddle.org.cn/whl/linux/mkl/avx/stable.html
+For example, run the following command to install Paddle with pip for Linux, CUDA 10.1.
 
-# CPU
-python -m pip install paddlepaddle==2.2.1 -i https://mirror.baidu.com/pypi/simple
 ```
-- For quick installation of more CUDA versions or environments, please refer to [PaddlePaddle Quick Installation Document](https://www.paddlepaddle.org.cn/install/quick)
-- For more installation methods such as conda or source code compilation and installation methods, please refer to [PaddlePaddle Installation Document](https://www.paddlepaddle.org.cn/documentation/docs/zh/install/index_en.html)
+python -m pip install paddlepaddle-gpu==2.2.2.post101 -f https://www.paddlepaddle.org.cn/whl/linux/mkl/avx/stable.html
+```
+
 
-Please make sure that your PaddlePaddle is installed successfully and the version is not lower than the required version. Use the following command to verify.
+In Python interpreter, run the following command to confirm whether PaddlePaddle is installed successfully
 
 ```
-# Confirm that PaddlePaddle is installed successfully in your Python interpreter
 >>> import paddle
 >>> paddle.utils.run_check()
 
-# Confirm PaddlePaddle version
-python -c "import paddle; print(paddle.__version__)"
-
 # If the following prompt appears on the command line, the PaddlePaddle installation is successful.
 # PaddlePaddle is installed successfully! Let's start deep learning with PaddlePaddle now.
-```
-
 
+# Confirm PaddlePaddle version
+>>> print(paddle.__version__)
 
-## 2. Install PaddleSeg
-Support API method for flexible development.
-```
-pip install paddleseg
 ```
 
-## 3. Download Repo
-Support Configuration Drive for simple and fast development.
+## 2. Download Repo
+
+Clone the PaddleSeg repo from Github.
 
 ```
 git clone https://github.com/PaddlePaddle/PaddleSeg
 ```
 
 ## 4. Install Dependencies
+
 ```
 cd PaddleSeg
 pip install -r requirements.txt
-
-#If a version error occurs during installation, you can try to delete the old version and re-run the script.
 ```
+
+If a version error occurs during installation, you can try to delete the old version and re-run the script.
 ## 5. Verify Installation
 
-Run the following command to verify PaddleSeg installation. The predicted results will be in output/result if successful.
+In the root of PaddleSeg, run the following command. If there are no error in terminal log, you can use PaddleSeg to train, validate, test and export models with config method.
+
+```
+cd PaddleSeg
+sh tests/run_check_install.sh
+```
+
+## 3. Install PaddleSeg (Optional)
+
+Besides, PaddleSeg also supports api method for flexible development, which requires the PaddleSeg is installed in python libs.
 
-```python
-python predict.py \
-       --config configs/quick_start/pp_liteseg_optic_disc_512x512_1k.yml \
-       --model_path https://paddleseg.bj.bcebos.com/dygraph/optic_disc/pp_liteseg_optic_disc_512x512_1k/model.pdparams\
-       --image_path docs/images/optic_test_image.jpg \
-       --save_dir output/result
+Run the following command to compile and install PaddleSeg from source code.
+
+```
+cd PaddleSeg
+python setup.py install
+```
+
+Or, you can install the release PaddleSeg.
+```
+pip install paddleseg
 ```

docs/install_cn.md

@@ -14,55 +14,77 @@
 ## 安装说明
 
 ### 1. 安装PaddlePaddle
-```
-# CUDA10.1
-python -m pip install paddlepaddle-gpu==2.2.1.post101 -f https://www.paddlepaddle.org.cn/whl/linux/mkl/avx/stable.html
 
-# CPU
-python -m pip install paddlepaddle==2.2.1 -i https://mirror.baidu.com/pypi/simple
+请参考[快速安装文档](https://www.paddlepaddle.org.cn/install/quick)或者[详细安装文档](https://www.paddlepaddle.org.cn/documentation/docs/zh/install/index_cn.html)，安装PaddlePaddle （要求不低于2.2版本）。
+
+比如Linux、CUDA 10.1，使用pip安装GPU版本，执行如下命令。
+
+```
+python -m pip install paddlepaddle-gpu==2.2.2.post101 -f https://www.paddlepaddle.org.cn/whl/linux/mkl/avx/stable.html
 ```
-- 更多CUDA版本或环境快速安装，请参考[PaddlePaddle快速安装文档](https://www.paddlepaddle.org.cn/install/quick)
-- 更多安装方式例如conda或源码编译安装方法，请参考[PaddlePaddle安装文档](https://www.paddlepaddle.org.cn/documentation/docs/zh/install/index_cn.html)
 
-请确保您的PaddlePaddle安装成功并且版本不低于需求版本。使用以下命令进行验证。
+使用如下命令验证PaddlePaddle是否安装成功，并且查看版本。
 
 ```
-# 在您的Python解释器中确认PaddlePaddle安装成功
+# 在Python解释器中顺利执行如下命令
 >>> import paddle
 >>> paddle.utils.run_check()
 
-# 确认PaddlePaddle版本
-python -c "import paddle; print(paddle.__version__)"
-
 # 如果命令行出现以下提示，说明PaddlePaddle安装成功
 # PaddlePaddle is installed successfully! Let's start deep learning with PaddlePaddle now.
+
+# 查看PaddlePaddle版本
+>>> print(paddle.__version__)
+
 ```
 
-## 2. 安装PaddleSeg
-支持API方式灵活开发。
+## 2. 下载PaddleSeg代码
+
+从Github下载PaddleSeg代码。
+
 ```
-pip install paddleseg
+git clone https://github.com/PaddlePaddle/PaddleSeg
 ```
 
-## 3. 下载PaddleSeg代码
+如果连不上Github，可以从Gitee下载PaddleSeg代码，但是Gitee上代码可能不是最新。
+
 ```
-git clone https://github.com/PaddlePaddle/PaddleSeg
+git clone https://gitee.com/paddlepaddle/PaddleSeg.git
 ```
-## 4. 安装PaddleSeg依赖
+
+## 3. 安装PaddleSeg依赖
+
 ```
 cd PaddleSeg
 pip install -r requirements.txt
+```
+
+如果安装时出现版本错误，可以尝试删除旧版本，重新运行该脚本。
+
+## 4.确认环境安装成功
+
+在PaddleSeg目录下执行如下命令，会进行简单的单卡训练和单卡预测。
+
+查看执行输出的log，没有报错，则验证安装成功。
+
+然后，基于PaddleSeg，你可以使用配置文件的方式来训练、验证、测试和导出模型。
 
-#如果安装时出现版本错误，可以尝试删除旧版本，重新运行该脚本。
 ```
-## 5.确认环境安装成功
+sh tests/run_check_install.sh
+```
+
+## 5. 安装PaddleSeg包（可选）
 
-在PaddleSeg目录下，执行下面命令，如果PaddleSeg/output文件夹中出现预测结果，则证明安装成功。
+PaddleSeg也支持API方式灵活开发。 API开发方式要求大家将PaddleSeg安装到Python库中。
 
-```python
-python predict.py \
-       --config configs/quick_start/pp_liteseg_optic_disc_512x512_1k.yml \
-       --model_path https://paddleseg.bj.bcebos.com/dygraph/optic_disc/pp_liteseg_optic_disc_512x512_1k/model.pdparams\
-       --image_path docs/images/optic_test_image.jpg \
-       --save_dir output/result
+
+执行如下命令，从源码编译安装PaddleSeg包。
+```
+cd PaddleSeg
+python setup.py install
+```
+
+或者直接安装发布的PaddleSeg包。
+```
+pip install paddleseg
 ```

tests/run_check_install.sh

@@ -0,0 +1,23 @@
+# download data
+mkdir data
+cd data
+wget https://paddleseg.bj.bcebos.com/dataset/optic_disc_seg.zip
+unzip optic_disc_seg.zip > /dev/null
+cd ..
+
+# check traing
+python train.py \
+    --config configs/quick_start/pp_liteseg_optic_disc_512x512_1k.yml \
+    --iters 20 \
+    --do_eval \
+    --save_interval 20 \
+    --save_dir output/pp_liteseg_optic_disc
+
+echo -e "\n\n"
+
+# check predicting
+python predict.py \
+    --config configs/quick_start/pp_liteseg_optic_disc_512x512_1k.yml \
+    --model_path https://paddleseg.bj.bcebos.com/dygraph/optic_disc/pp_liteseg_optic_disc_512x512_1k/model.pdparams\
+    --image_path docs/images/optic_test_image.jpg \
+    --save_dir output/result