support windows system (#3635)

PaddleCV/image_classification/README.md

@@ -46,7 +46,8 @@ pip install numpy
 
 ### 数据准备
 
-下面给出了ImageNet分类任务的样例，首先，通过如下的方式进行数据的准备：
+下面给出了ImageNet分类任务的样例
+在Linux系统下通过如下的方式进行数据的准备：
 ```
 cd data/ILSVRC2012/
 sh download_imagenet2012.sh
@@ -69,6 +70,8 @@ val/ILSVRC2012_val_00000001.jpeg 65
 ```
 注意：可能需要根据本地环境调整reader.py中相关路径来正确读取数据。
 
+**Windows系统下请用户自行下载ImageNet数据。[label下载链接](http://paddle-imagenet-models.bj.bcebos.com/ImageNet_label.tgz)**
+
 ### 模型训练
 
 数据准备完毕后，可以通过如下的方式启动训练：

PaddleCV/image_classification/README_en.md

@@ -37,7 +37,8 @@ Running samples in this directory requires Python 2.7 and later, CUDA 8.0 and la
 
 ### Data preparation
 
-An example for ImageNet classification is as follows. First of all, preparation of imagenet data can be done as:
+An example for ImageNet classification is as follows.
+For Linux system, preparation of imagenet data can be done as:
 
 ```bash
 cd data/ILSVRC2012/
@@ -62,6 +63,7 @@ val/ILSVRC2012_val_00000001.jpeg 65
 ```
 
 Note: You may need to modify the data path in reader.py to load data correctly.
+**For windows system, Users should download ImageNet data by themselves. and the label list can be downloaded in [Here](http://paddle-imagenet-models.bj.bcebos.com/ImageNet_label.tgz)**
 
 ### Training