improve readme

docs/zh_CN/fastdeploy/amlogic/a311d/cpp/README.md

@@ -16,8 +16,16 @@
 
 2. 将编译后的库拷贝到当前目录，可使用如下命令：
 ```bash
+# 下载部署示例代码
+git clone https://github.com/PaddlePaddle/FastDeploy.git
+cd  FastDeploy/examples/vision/classification/paddleclas/amlogic/a311d/cpp/
+
+# 如果您希望从PaddleClas下载示例代码，请运行
 git clone https://github.com/PaddlePaddle/PaddleClas.git
+# 注意：如果当前分支找不到下面的fastdeploy测试代码，请切换到develop分支
+git checkout develop
 cd PaddleClas/deploy/fastdeploy/amlogic/a311d/cpp/
+
 cp -r FastDeploy/build/fastdeploy-timvx/ ./
 ```
 

docs/zh_CN/fastdeploy/ascend/cpp/README.md

@@ -15,7 +15,13 @@
 
 ```bash
 # 下载部署示例代码
+git clone https://github.com/PaddlePaddle/FastDeploy.git
+cd  FastDeploy/examples/vision/classification/paddleclas/ascend/cpp
+
+# 如果您希望从PaddleClas下载示例代码，请运行
 git clone https://github.com/PaddlePaddle/PaddleClas.git
+# 注意：如果当前分支找不到下面的fastdeploy测试代码，请切换到develop分支
+git checkout develop
 cd PaddleClas/deploy/fastdeploy/ascend/cpp
 
 mkdir build

docs/zh_CN/fastdeploy/ascend/python/README.md

@@ -12,7 +12,13 @@
 # 安装FastDpeloy 昇腾预测库 python包（详细文档请参考`部署环境准备`）
 
 # 下载部署示例代码
+git clone https://github.com/PaddlePaddle/FastDeploy.git
+cd  FastDeploy/examples/vision/classification/paddleclas/ascend/python
+
+# 如果您希望从PaddleClas下载示例代码，请运行
 git clone https://github.com/PaddlePaddle/PaddleClas.git
+# 注意：如果当前分支找不到下面的fastdeploy测试代码，请切换到develop分支
+git checkout develop
 cd PaddleClas/deploy/fastdeploy/ascend/python
 
 # 下载ResNet50_vd模型文件和测试图片

docs/zh_CN/fastdeploy/cpu-gpu/c/README.md

@@ -16,7 +16,13 @@ PaddleClas支持利用FastDeploy在NVIDIA GPU、X86 CPU、飞腾CPU、ARM CPU、
 ## 4.运行部署示例
 ```bash
 # 下载部署示例代码
+git clone https://github.com/PaddlePaddle/FastDeploy.git
+cd  FastDeploy/examples/vision/classification/paddleclas/cpu-gpu/c
+
+# 如果您希望从PaddleClas下载示例代码，请运行
 git clone https://github.com/PaddlePaddle/PaddleClas.git
+# 注意：如果当前分支找不到下面的fastdeploy测试代码，请切换到develop分支
+git checkout develop
 cd PaddleClas/deploy/fastdeploy/cpu-gpu/c
 
 mkdir build

docs/zh_CN/fastdeploy/cpu-gpu/cpp/README.md

@@ -16,7 +16,13 @@ PaddleClas支持利用FastDeploy在NVIDIA GPU、X86 CPU、飞腾CPU、ARM CPU、
 
 ```bash
 # 下载部署示例代码
+git clone https://github.com/PaddlePaddle/FastDeploy.git
+cd  FastDeploy/examples/vision/classification/paddleclas/cpu-gpu/cpp
+
+# 如果您希望从PaddleClas下载示例代码，请运行
 git clone https://github.com/PaddlePaddle/PaddleClas.git
+# 注意：如果当前分支找不到下面的fastdeploy测试代码，请切换到develop分支
+git checkout develop
 cd PaddleClas/deploy/fastdeploy/cpu-gpu/cpp
 
 mkdir build

docs/zh_CN/fastdeploy/cpu-gpu/csharp/README.md

@@ -31,7 +31,13 @@ PaddleClas支持利用FastDeploy在NVIDIA GPU、X86 CPU、飞腾CPU、ARM CPU、
 https://bj.bcebos.com/fastdeploy/release/cpp/fastdeploy-linux-x64-x.x.x.tgz
 
 # 下载部署示例代码
+git clone https://github.com/PaddlePaddle/FastDeploy.git
+cd  FastDeploy\examples\vision\classification\paddleclas\cpu-gpu\csharp
+
+# 如果您希望从PaddleClas下载示例代码，请运行
 git clone https://github.com/PaddlePaddle/PaddleClas.git
+# 注意：如果当前分支找不到下面的fastdeploy测试代码，请切换到develop分支
+git checkout develop
 cd D:\PaddleClas\deploy\fastdeploy\cpu-gpu\csharp
 
 mkdir build && cd build

docs/zh_CN/fastdeploy/cpu-gpu/python/README.md

@@ -17,7 +17,14 @@ pip install fastdeploy-gpu-python -f https://www.paddlepaddle.org.cn/whl/fastdep
 conda config --add channels conda-forge && conda install cudatoolkit=11.2 cudnn=8.2
 
 # 下载部署示例代码
+# 下载部署示例代码
+git clone https://github.com/PaddlePaddle/FastDeploy.git
+cd  FastDeploy/examples/vision/classification/paddleclas/cpu-gpu/python
+
+# 如果您希望从PaddleClas下载示例代码，请运行
 git clone https://github.com/PaddlePaddle/PaddleClas.git
+# 注意：如果当前分支找不到下面的fastdeploy测试代码，请切换到develop分支
+git checkout develop
 cd PaddleClas/deploy/fastdeploy/cpu-gpu/python
 
 # 下载ResNet50_vd模型文件和测试图片

docs/zh_CN/fastdeploy/graphcore/cpp/README.md

@@ -13,7 +13,13 @@
 
 ```bash
 # 下载部署示例代码
+git clone https://github.com/PaddlePaddle/FastDeploy.git
+cd  FastDeploy/examples/vision/classification/paddleclas/graphcore/cpp
+
+# 如果您希望从PaddleClas下载示例代码，请运行
 git clone https://github.com/PaddlePaddle/PaddleClas.git
+# 注意：如果当前分支找不到下面的fastdeploy测试代码，请切换到develop分支
+git checkout develop
 cd PaddleClas/deploy/fastdeploy/graphcore/cpp
 
 mkdir build

docs/zh_CN/fastdeploy/graphcore/python/README.md

@@ -12,7 +12,13 @@
 # 安装FastDpeloy Graphcore IPU预测库 python包（详细文档请参考`部署环境准备`）
 
 # 下载部署示例代码
+git clone https://github.com/PaddlePaddle/FastDeploy.git
+cd  FastDeploy/examples/vision/classification/paddleclas/graphcore/python
+
+# 如果您希望从PaddleClas下载示例代码，请运行
 git clone https://github.com/PaddlePaddle/PaddleClas.git
+# 注意：如果当前分支找不到下面的fastdeploy测试代码，请切换到develop分支
+git checkout develop
 cd PaddleClas/deploy/fastdeploy/graphcore/python
 
 # 下载ResNet50_vd模型文件和测试图片

docs/zh_CN/fastdeploy/kunlun/cpp/README.md → docs/zh_CN/fastdeploy/kunlunxin/cpp/README.md

@@ -13,13 +13,19 @@
 
 ```bash
 # 下载部署示例代码
+git clone https://github.com/PaddlePaddle/FastDeploy.git
+cd  FastDeploy/examples/vision/classification/paddleclas/kunlunxin/cpp
+
+# 如果您希望从PaddleClas下载示例代码，请运行
 git clone https://github.com/PaddlePaddle/PaddleClas.git
-cd PaddleClas/deploy/fastdeploy/kunlun/cpp
+# 注意：如果当前分支找不到下面的fastdeploy测试代码，请切换到develop分支
+git checkout develop
+cd PaddleClas/deploy/fastdeploy/kunlunxin/cpp
 
 mkdir build
 cd build
 # 使用编译完成的FastDeploy库编译infer_demo
-cmake .. -DFASTDEPLOY_INSTALL_DIR=${PWD}/fastdeploy-kunlun
+cmake .. -DFASTDEPLOY_INSTALL_DIR=${PWD}/fastdeploy-kunlunxin
 make -j
 
 # 下载ResNet50_vd模型文件和测试图片

docs/zh_CN/fastdeploy/kunlun/python/README.md → docs/zh_CN/fastdeploy/kunlunxin/python/README.md

@@ -12,8 +12,14 @@
 # 安装FastDpeloy 预测库 python包（详细文档请参考`部署环境准备`）
 
 # 下载部署示例代码
+git clone https://github.com/PaddlePaddle/FastDeploy.git
+cd  FastDeploy/examples/vision/classification/paddleclas/kunlunxin/python
+
+# 如果您希望从PaddleClas下载示例代码，请运行
 git clone https://github.com/PaddlePaddle/PaddleClas.git
-cd PaddleClas/deploy/fastdeploy/kunlun/python
+# 注意：如果当前分支找不到下面的fastdeploy测试代码，请切换到develop分支
+git checkout develop
+cd PaddleClas/deploy/fastdeploy/kunlunxin/python
 
 # 下载ResNet50_vd模型文件和测试图片
 wget https://bj.bcebos.com/paddlehub/fastdeploy/ResNet50_vd_infer.tgz

docs/zh_CN/fastdeploy/rockchip/rknpu2/cpp/README.md

@@ -51,6 +51,17 @@ wget https://gitee.com/paddlepaddle/PaddleClas/raw/release/2.4/deploy/images/Ima
 #### 3.2.4 编译example
 
 ```bash
+# 下载部署示例代码
+git clone https://github.com/PaddlePaddle/FastDeploy.git
+cd  FastDeploy/examples/vision/classification/paddleclas/rockchip/rknpu2/cpp
+
+# 如果您希望从PaddleClas下载示例代码，请运行
+git clone https://github.com/PaddlePaddle/PaddleClas.git
+# 注意：如果当前分支找不到下面的fastdeploy测试代码，请切换到develop分支
+git checkout develop
+cd PaddleClas/deploy/fastdeploy/rockchip/rknpu2/cpp
+
+
 cd build
 cmake ..
 make -j8

docs/zh_CN/fastdeploy/rockchip/rknpu2/python/README.md

@@ -16,7 +16,13 @@
 # 安装FastDpeloy RKNPU2 python包（详细文档请参考`部署环境准备`）
 
 # 下载部署示例代码
+git clone https://github.com/PaddlePaddle/FastDeploy.git
+cd  FastDeploy/examples/vision/classification/paddleclas/rockchip/rknpu2/python
+
+# 如果您希望从PaddleClas下载示例代码，请运行
 git clone https://github.com/PaddlePaddle/PaddleClas.git
+# 注意：如果当前分支找不到下面的fastdeploy测试代码，请切换到develop分支
+git checkout develop
 cd PaddleClas/deploy/fastdeploy/rockchip/rknpu2/python
 
 # 下载图片

docs/zh_CN/fastdeploy/rockchip/rv1126/cpp/README.md

@@ -20,7 +20,16 @@ cp -r FastDeploy/build/fastdeploy-timvx/ PaddleClas/deploy/fastdeploy/rockchip/r
 
 3. 在当前路径下载部署所需的模型和示例图片：
 ```bash
+# 下载部署示例代码
+git clone https://github.com/PaddlePaddle/FastDeploy.git
+cd  FastDeploy/examples/vision/classification/paddleclas/rockchip/rv1126/cpp/
+
+# 如果您希望从PaddleClas下载示例代码，请运行
+git clone https://github.com/PaddlePaddle/PaddleClas.git
+# 注意：如果当前分支找不到下面的fastdeploy测试代码，请切换到develop分支
+git checkout develop
 cd PaddleClas/deploy/fastdeploy/rockchip/rv1126/cpp/
+
 mkdir models && mkdir images
 wget https://bj.bcebos.com/paddlehub/fastdeploy/resnet50_vd_ptq.tar
 tar -xvf resnet50_vd_ptq.tar

docs/zh_CN/fastdeploy/serving/README.md

@@ -9,7 +9,13 @@ PaddleClas 服务化部署示例是利用FastDeploy Serving搭建的服务化部
 
 ```bash
 # 下载部署示例代码
+git clone https://github.com/PaddlePaddle/FastDeploy.git
+cd  FastDeploy/examples/vision/classification/paddleclas/serving
+
+# 如果您希望从PaddleClas下载示例代码，请运行
 git clone https://github.com/PaddlePaddle/PaddleClas.git
+# 注意：如果当前分支找不到下面的fastdeploy测试代码，请切换到develop分支
+git checkout develop
 cd PaddleClas/deploy/fastdeploy/serving
 
 # 下载ResNet50_vd模型文件和测试图片

docs/zh_CN/fastdeploy/sophgo/cpp/README.md

@@ -41,6 +41,16 @@ cp ILSVRC2012_val_00000010.jpeg ./images
 ### 3.4 编译example
 
 ```bash
+# 下载部署示例代码
+git clone https://github.com/PaddlePaddle/FastDeploy.git
+cd  FastDeploy/examples/vision/classification/paddleclas/sophgo/cpp
+
+# 如果您希望从PaddleClas下载示例代码，请运行
+git clone https://github.com/PaddlePaddle/PaddleClas.git
+# 注意：如果当前分支找不到下面的fastdeploy测试代码，请切换到develop分支
+git checkout develop
+cd PaddleClas/deploy/fastdeploy/sophgo/cpp
+
 cd build
 cmake .. -DFASTDEPLOY_INSTALL_DIR=${PWD}/fastdeploy-x.x.x
 make

docs/zh_CN/fastdeploy/sophgo/python/README.md

@@ -9,7 +9,14 @@
 ## 2.运行部署示例
 ```bash
 # 下载部署示例代码
+# 下载部署示例代码
+git clone https://github.com/PaddlePaddle/FastDeploy.git
+cd  FastDeploy/examples/vision/classification/paddleclas/sophgo/python
+
+# 如果您希望从PaddleClas下载示例代码，请运行
 git clone https://github.com/PaddlePaddle/PaddleClas.git
+# 注意：如果当前分支找不到下面的fastdeploy测试代码，请切换到develop分支
+git checkout develop
 cd PaddleClas/deploy/fastdeploy/sophgo/python
 
 # 下载图片