!6855 [MS][LITE]Modified the download link

Merge pull request !6855 from gongdaguo/modify_download_link

model_zoo/official/lite/image_classification/README.en.md

@@ -78,7 +78,13 @@ app
 
 ### Configuring MindSpore Lite Dependencies
 
-When MindSpore C++ APIs are called at the Android JNI layer, related library files are required. You can use MindSpore Lite [source code compilation](https://www.mindspore.cn/tutorial/lite/en/master/use/build.html) to generate the MindSpore Lite version.　
+When MindSpore C++ APIs are called at the Android JNI layer, related library files are required. You can use MindSpore Lite [source code compilation](https://www.mindspore.cn/tutorial/lite/en/master/use/build.html) to generate the MindSpore Lite version. In this case, you need to use the compile command of generate with image preprocessing module.
+
+In this example, the build process automatically downloads the `mindspore-lite-1.0.0-minddata-arm64-cpu` by the `app/download.gradle` file and saves in the `app/src/main/cpp` directory.
+
+Note: if the automatic download fails, please manually download the relevant library files and put them in the corresponding location.
+
+mindspore-lite-1.0.0-minddata-arm64-cpu.tar.gz [Download link](https://ms-release.obs.cn-north-4.myhuaweicloud.com/1.0.0/lite/android_aarch64/mindspore-lite-1.0.0-minddata-arm64-cpu.tar.gz)
 
 ```
 android{
@@ -126,15 +132,9 @@ target_link_libraries(
 )
 ```
 
-* In this example, the  download.gradle File configuration auto download MindSpore Lite version,  placed in the 'app/src/main/cpp/' directory.
-
-  Note: if the automatic download fails, please manually download the relevant library files and put them in the corresponding location.
-
-  mindspore-lite-1.0.0-minddata-arm64-cpu.tar.gz [Download link](https://download.mindspore.cn/model_zoo/official/lite/lib/mindspore%20version%201.0/mindspore-lite-1.0.0-minddata-arm64-cpu.tar.gz)
-
 ### Downloading and Deploying a Model File
 
-In this example, the  download.gradle File configuration auto download `mobilenetv2.ms `and placed in the 'app / libs / arm64-v8a' directory.
+In this example, the  download.gradle File configuration auto download `mobilenetv2.ms `and placed in the 'app/libs/arm64-v8a' directory.
 
 Note: if the automatic download fails, please manually download the relevant library files and put them in the corresponding location.
 

model_zoo/official/lite/image_classification/README.md

@@ -86,14 +86,21 @@ app
 
 ### 配置MindSpore Lite依赖项
 
-Android JNI层调用MindSpore C++ API时，需要相关库文件支持。可通过MindSpore Lite[源码编译](https://www.mindspore.cn/tutorial/lite/zh-CN/master/use/build.html)生成"mindspore-lite-X.X.X-mindata-armXX-cpu"库文件包（包含`libmindspore-lite.so`库文件和相关头文件，可包含多个兼容架构）。
+Android JNI层调用MindSpore C++ API时，需要相关库文件支持。可通过MindSpore Lite[源码编译](https://www.mindspore.cn/tutorial/lite/zh-CN/master/use/build.html)生成`mindspore-lite-{version}-minddata-{os}-{device}.tar.gz`库文件包并解压缩（包含`libmindspore-lite.so`库文件和相关头文件），在本例中需使用生成带图像预处理模块的编译命令。
 
-本示例中，build过程由download.gradle文件自动从华为服务器下载MindSpore Lite 版本文件，并放置在`app / src / main/cpp/`目录下。
+> version：输出件版本号，与所编译的分支代码对应的版本一致。
+>
+> device：当前分为cpu（内置CPU算子）和gpu（内置CPU和GPU算子）。
+>
+> os：输出件应部署的操作系统。
 
-* 注：若自动下载失败，请手动下载相关库文件并将其放在对应位置：
+本示例中，build过程由download.gradle文件自动下载MindSpore Lite 版本文件，并放置在`app/src/main/cpp/`目录下。
 
-  mindspore-lite-1.0.0-minddata-arm64-cpu.tar.gz [下载链接](https://download.mindspore.cn/model_zoo/official/lite/lib/mindspore%20version%201.0/mindspore-lite-1.0.0-minddata-arm64-cpu.tar.gz)
+* 注：若自动下载失败，请手动下载相关库文件，解压并放在对应位置：
 
+  mindspore-lite-1.0.0-minddata-arm64-cpu.tar.gz [下载链接](https://ms-release.obs.cn-north-4.myhuaweicloud.com/1.0.0/lite/android_aarch64/mindspore-lite-1.0.0-minddata-arm64-cpu.tar.gz)
+
+在app的`build.gradle`文件中配置CMake编译支持，以及`arm64-v8a`的编译支持，如下所示：
 
 ```
 android{

model_zoo/official/lite/image_classification/app/download.gradle

@@ -10,7 +10,7 @@ def targetModelFile = "src/main/assets/model/mobilenetv2.ms"
 def mindSporeLibrary_arm64 = "src/main/cpp/${mindsporeLite_Version}.tar.gz"
 
 def modelDownloadUrl = "https://download.mindspore.cn/model_zoo/official/lite/mobilenetv2_openimage_lite/mobilenetv2.ms"
-def mindsporeLiteDownloadUrl = "https://download.mindspore.cn/model_zoo/official/lite/lib/mindspore%20version%201.0/${mindsporeLite_Version}.tar.gz"
+def mindsporeLiteDownloadUrl = "https://ms-release.obs.cn-north-4.myhuaweicloud.com/1.0.0/lite/android_aarch64/${mindsporeLite_Version}.tar.gz"
 
 def cleantargetMindSporeInclude = "src/main/cpp"
 

model_zoo/official/lite/object_detection/README.en.md

@@ -43,7 +43,14 @@ This object detection sample program on the Android device includes a Java layer
 
 ### Configuring MindSpore Lite Dependencies
 
-In Android studio, the compiled mindpool-lite-x.x.x-mindata-armxx-cpu package (including ` libmindspot- lite.so `The library file and related header files, which can contain multiple compatible architectures), are unzipped and placed in the 'app / SRC / main / CPP' directory of the app project, and the` build.gradle `Cmake and 'arm64-v8a' and 'armeabi-v7a' are configured in the file as follows It is shown as follows:
+When MindSpore C++ APIs are called at the Android JNI layer, related library files are required. You can use MindSpore Lite [source code compilation](https://www.mindspore.cn/tutorial/lite/en/master/use/build.html) to generate the MindSpore Lite version. In this case, you need to use the compile command of generate with image preprocessing module.
+
+In this example, the build process automatically downloads the `mindspore-lite-1.0.0-minddata-arm64-cpu` by the `app/download.gradle` file and saves in the `app/src/main/cpp` directory.
+
+Note: if the automatic download fails, please manually download the relevant library files and put them in the corresponding location.
+
+mindspore-lite-1.0.0-minddata-arm64-cpu.tar.gz [Download link](https://ms-release.obs.cn-north-4.myhuaweicloud.com/1.0.0/lite/android_aarch64/mindspore-lite-1.0.0-minddata-arm64-cpu.tar.gz)
+
 ```
 android{
     defaultConfig{
@@ -54,7 +61,7 @@ android{
         }
 
         ndk{ 
-            abiFilters'armeabi-v7a', 'arm64-v8a'  
+            abiFilters 'arm64-v8a'
         }
     }
 }
@@ -82,16 +89,6 @@ target_link_libraries(
 )
 ```
 
-
-
-In this example, the  download.gradle File configuration auto download library file,  placed in the 'app / libs / arm64-v8a' directory.
-
-Note: if the automatic download fails, please manually download the relevant library files and put them in the corresponding location.
-
-mindspore-lite-1.0.0-minddata-arm64-cpu.tar.gz [Download link](https://download.mindspore.cn/model_zoo/official/lite/lib/mindspore%20version%201.0/mindspore-lite-1.0.0-minddata-arm64-cpu.tar.gz)
-
-
-
 ### Downloading and Deploying a Model File
 
 In this example, the  download.gradle File configuration auto download `ssd.ms `and placed in the 'app / libs / arm64-v8a' directory.

model_zoo/official/lite/object_detection/README.md

@@ -85,9 +85,22 @@ app
 
 ### 配置MindSpore Lite依赖项
 
-Android JNI层调用MindSpore C++ API时，需要相关库文件支持。可通过MindSpore Lite[源码编译](https://www.mindspore.cn/tutorial/lite/zh-CN/master/use/build.html)生成"mindspore-lite-X.X.X-mindata-armXX-cpu"库文件包（包含`libmindspore-lite.so`库文件和相关头文件，可包含多个兼容架构）。
+Android JNI层调用MindSpore C++ API时，需要相关库文件支持。可通过MindSpore Lite[源码编译](https://www.mindspore.cn/tutorial/lite/zh-CN/master/use/build.html)生成`mindspore-lite-{version}-minddata-{os}-{device}.tar.gz`库文件包并解压缩（包含`libmindspore-lite.so`库文件和相关头文件），在本例中需使用生成带图像预处理模块的编译命令。
+
+> version：输出件版本号，与所编译的分支代码对应的版本一致。
+>
+> device：当前分为cpu（内置CPU算子）和gpu（内置CPU和GPU算子）。
+>
+> os：输出件应部署的操作系统。
+
+本示例中，build过程由download.gradle文件自动下载MindSpore Lite 版本文件，并放置在`app/src/main/cpp/`目录下。
+
+* 注：若自动下载失败，请手动下载相关库文件，解压并放在对应位置：
+
+  mindspore-lite-1.0.0-minddata-arm64-cpu.tar.gz [下载链接](https://ms-release.obs.cn-north-4.myhuaweicloud.com/1.0.0/lite/android_aarch64/mindspore-lite-1.0.0-minddata-arm64-cpu.tar.gz)
+
+在app的`build.gradle`文件中配置CMake编译支持，以及`arm64-v8a`的编译支持，如下所示：
 
-在Android Studio中将编译完成的mindspore-lite-X.X.X-mindata-armXX-cpu压缩包，解压之后放置在APP工程的`app/src/main/cpp`目录下，并在app的`build.gradle`文件中配置CMake编译支持，以及`arm64-v8a`和`armeabi-v7a`的编译支持，如下所示：
 ```
 android{
     defaultConfig{
@@ -126,16 +139,9 @@ target_link_libraries(
 )
 ```
 
-本示例中，app build过程由download.gradle文件自动从华为服务器下载mindspore所编译的库及相关头文件，并放置在`src/main/cpp`工程目录下。
-
-
-* 注：若自动下载失败，请手动下载相关库文件并将其放在对应位置：
-* mindspore-lite-1.0.0-minddata-arm64-cpu.tar.gz [下载链接](https://download.mindspore.cn/model_zoo/official/lite/lib/mindspore%20version%201.0/mindspore-lite-1.0.0-minddata-arm64-cpu.tar.gz)
-
-
 ### 下载及部署模型文件
 
-从MindSpore Model Hub中下载模型文件，本示例程序中使用的目标检测模型文件为`ssd.ms`，同样通过download.gradle脚本在APP构建时自动下载，并放置在`app/src/main/assets`工程目录下。
+从MindSpore Model Hub中下载模型文件，本示例程序中使用的目标检测模型文件为`ssd.ms`，同样通过`download.gradle`脚本在APP构建时自动下载，并放置在`app/src/main/assets`工程目录下。
 
 * 注：若下载失败请手动下载模型文件，ssd.ms [下载链接](https://download.mindspore.cn/model_zoo/official/lite/ssd_mobilenetv2_lite/ssd.ms)。
 

model_zoo/official/lite/object_detection/app/download.gradle

@@ -10,7 +10,7 @@ def targetModelFile = "src/main/assets/model/ssd.ms"
 def mindSporeLibrary_arm64 = "src/main/cpp/${mindsporeLite_Version}.tar.gz"
 
 def modelDownloadUrl = "https://download.mindspore.cn/model_zoo/official/lite/ssd_mobilenetv2_lite/ssd.ms"
-def mindsporeLiteDownloadUrl = "https://download.mindspore.cn/model_zoo/official/lite/lib/mindspore%20version%201.0/${mindsporeLite_Version}.tar.gz"
+def mindsporeLiteDownloadUrl = "https://ms-release.obs.cn-north-4.myhuaweicloud.com/1.0.0/lite/android_aarch64/${mindsporeLite_Version}.tar.gz"
 
 def cleantargetMindSporeInclude = "src/main/cpp"