android demo build docs and script

docs/getting_started/models/demo_app_models.yaml

 # The name of library
-library_name: library_name
-target_abis: [armeabi-v7a, arm64-v8a]
-# The soc serialno of specific device.
-# Get by command `adb shell getprop | grep ro.board.platform | cut -d [ -f3 | cut -d ] -f1`.
-target_socs: [msm8998]
+library_name: mobilenet
+target_abis: [arm64-v8a]
 embed_model_data: 1
 # The build mode for model(s).
 # 'code' stand for transfer model(s) into cpp code, 'proto' for model(s) in protobuf file(s).
 build_type: code
-linkshared: 1
+linkshared: 0
 # One yaml config file can contain multi models' config message.
 models:
-  model_name: # model tag, which will be used in model loading and must be specific.
+  mobilenet_v1: # model tag, which will be used in model loading and must be specific.
     platform: tensorflow
-    model_file_path: path/to/model64.pb # also support http:// and https://
-    model_sha256_checksum: 7f7462333406e7dea87222737590ebb7d94490194d2f21a7d72bafa87e64e9f9
+    # support local path, http:// and https://
+    model_file_path: https://cnbj1.fds.api.xiaomi.com/mace/miai-models/mobilenet-v1/mobilenet-v1-1.0.pb
+    model_sha256_checksum: 71b10f540ece33c49a7b51f5d4095fc9bd78ce46ebf0300487b2ee23d71294e6
     subgraphs:
-      - input_tensors: input_node
-        input_shapes: 1,64,64,3
-        output_tensors: output_node
-        output_shapes: 1,64,64,2
-    runtime: gpu
-    data_type: fp16_fp32
+      - input_tensors: input
+        input_shapes: 1,224,224,3
+        output_tensors: MobilenetV1/Predictions/Reshape_1
+        output_shapes: 1,1001
+    runtime: cpu+gpu
     limit_opencl_kernel_time: 0
     nnlib_graph_mode: 0
-    obfuscate: 1
+    obfuscate: 0
     winograd: 0
-    input_files:
-      - path/to/input_files # support http://
-  second_net:
-    platform: caffe
-    model_file_path: path/to/model.prototxt
-    weight_file_path: path/to/weight.caffemodel
-    model_sha256_checksum: 05d92625809dc9edd6484882335c48c043397aed450a168d75eb8b538e86881a
-    weight_sha256_checksum: 05d92625809dc9edd6484882335c48c043397aed450a168d75eb8b538e86881a
+  mobilenet_v2:
+    platform: tensorflow
+    model_file_path: https://cnbj1.fds.api.xiaomi.com/mace/miai-models/mobilenet-v2/mobilenet-v2-1.0.pb
+    model_sha256_checksum: 369f9a5f38f3c15b4311c1c84c032ce868da9f371b5f78c13d3ea3c537389bb4
     subgraphs:
-      - input_tensors:
-          - input_node0
-          - input_node1
-        input_shapes:
-          - 1,256,256,3
-          - 1,128,128,3
-        output_tensors:
-          - output_node0
-          - output_node1
-        output_shapes:
-          - 1,256,256,2
-          - 1,1,1,2
-        validation_inputs_data:
-          - path/to/input_files # support http://
-    runtime: cpu
-    limit_opencl_kernel_time: 1
+      - input_tensors: input
+        input_shapes: 1,224,224,3
+        output_tensors: MobilenetV2/Predictions/Reshape_1
+        output_shapes: 1,1001
+    runtime: cpu+gpu
+    limit_opencl_kernel_time: 0
     nnlib_graph_mode: 0
-    obfuscate: 1
+    obfuscate: 0
     winograd: 0

mace/examples/android/README.md

+Android Demo
+------------
+------------
+
+Try it by downloading the [APK](https://cnbj1.fds.api.xiaomi.com/mace/demo/mace_android_demo.apk).
+
+How to build
+---------------
+* Build native library, please refer to [docs](docs) for more information.
+    ```
+    # Execute following commands from the project's root directory
+    python tools/converter.py build --config=docs/getting_started/models/demo_app_models.yaml
+    cp -r build/mobilenet/include/ mace/examples/android/macelibrary/src/main/cpp/
+    cp -r build/mobilenet/lib/ mace/examples/android/macelibrary/src/main/cpp/
+    ```
+* Build APK
+  * Import the `mace/examples/android` directory as a new Android Studio project and select `install run`
+  * Or build it with gradle:
+    ```
+    cd mace/exampls/android
+    ./gradlew installAppRelease
+    ```
+* You can also build native library and APK with `mace/examples/android/build.sh`
+    ```
+    cd mace/exampls/android
+    ./build.sh
+    ```

mace/examples/android/README_zh.md

-# mace demo使用方法
-
-* 使用前需要生成静态库和头文件,具体参考[文档](docs)
-    * 把mace/public目录下的mace.h和mace_runtime.h拷贝到macelibrary/src/main/cpp/include下面
-    * 把生成的mace/codegen/engine/mace_engine_factory.h拷贝到macelibrary/src/main/cpp/include下面
-    * 静态库的路径是在mace/build/demo_app_models/lib/下
-* 使用android studio 导入项目,然后运行install run
-* 还可以使用gradle命令(需要安装gradle)生成apk 具体命令例如:./gradlew assemble(或者Release|Debug)
-
-## 交流与反馈
-* 欢迎通过Github Issues提交问题报告与建议
-* QQ群: 756046893
-
-## License
-[Apache License 2.0](LICENSE).

mace/examples/android/app/src/main/assets/BUILD

-package(default_visibility = ["//visibility:public"])
-
-licenses(["notice"])  # Apache 2.0
-
-# It is necessary to use this filegroup rather than globbing the files in this
-# folder directly the examples/android:tensorflow_demo target due to the fact
-# that assets_dir is necessarily set to "" there (to allow using other
-# arbitrary targets as assets).
-filegroup(
-    name = "asset_files",
-    srcs = glob(
-        ["**/*"],
-        exclude = ["BUILD"],
-    ),
-)

mace/examples/android/app/src/main/java/com/xiaomi/mace/demo/result/ResultData.java

@@ -17,7 +17,7 @@ package com.xiaomi.mace.demo.result;
 public class ResultData {
     public String name;
     public float probability;
-    public long costTime;  //毫秒
+    public long costTime;  // ms
 
     public ResultData(String name, float probability) {
         this.name = name;

mace/examples/android/build.sh

+#!/usr/bin/env bash
+
+set -e -u -o pipefail
+
+pushd ../../../
+python tools/converter.py build --config=docs/getting_started/models/demo_app_models.yaml
+
+cp -r build/mobilenet/include/ mace/examples/android/macelibrary/src/main/cpp/
+cp -r build/mobilenet/lib/ mace/examples/android/macelibrary/src/main/cpp/
+
+popd
+
+./gradlew installAppRelease

mace/examples/android/macelibrary/CMakeLists.txt

@@ -13,7 +13,8 @@ cmake_minimum_required(VERSION 3.4.1)
 #set(CMAKE_LIBRARY_OUTPUT_DIRECTORY ${PROJECT_SOURCE_DIR}/../app/libs/${ANDROID_ABI})
 
 include_directories(${CMAKE_SOURCE_DIR}/)
-file(GLOB static_file ${CMAKE_SOURCE_DIR}/../../../build/demo_app_models/lib/arm64-v8a/*.a)
+include_directories(${CMAKE_SOURCE_DIR}/src/main/cpp/include)
+file(GLOB static_file ${CMAKE_SOURCE_DIR}/src/main/cpp/lib/arm64-v8a/*.a)
 
 MESSAGE(STATUS "FILE URL = ${CMAKE_SOURCE_DIR}")
 MESSAGE(STATUS "FILE URL = ${static_file}")

mace/examples/android/macelibrary/src/main/cpp/image_classify.cc

@@ -25,9 +25,9 @@
 #include <vector>
 #include <numeric>
 
-#include "src/main/cpp/include/mace.h"
-#include "src/main/cpp/include/mace_runtime.h"
-#include "src/main/cpp/include/mace_engine_factory.h"
+#include "src/main/cpp/include/mace/public/mace.h"
+#include "src/main/cpp/include/mace/public/mace_runtime.h"
+#include "src/main/cpp/include/mace/public/mace_engine_factory.h"
 
 namespace {
 
@@ -45,9 +45,9 @@ struct MaceContext {
   mace::DeviceType device_type = mace::DeviceType::CPU;
   std::map<std::string, ModelInfo> model_infos = {
       {"mobilenet_v1", {"input", "MobilenetV1/Predictions/Reshape_1",
-                            {1, 224, 224, 3}, {1, 1, 1, 1001}}},
+                            {1, 224, 224, 3}, {1, 1001}}},
       {"mobilenet_v2", {"input", "MobilenetV2/Predictions/Reshape_1",
-                            {1, 224, 224, 3}, {1, 1, 1, 1001}}}
+                            {1, 224, 224, 3}, {1, 1001}}}
   };
 };
 
@@ -146,11 +146,11 @@ Java_com_xiaomi_mace_JniMaceUtils_maceMobilenetCreateEngine(
 
   mace::MaceStatus create_engine_status =
       CreateMaceEngineFromCode(mace_context.model_name,
-                       std::string(),
-                       input_names,
-                       output_names,
-                       mace_context.device_type,
-                       &mace_context.engine);
+                               std::string(),
+                               input_names,
+                               output_names,
+                               mace_context.device_type,
+                               &mace_context.engine);
 
   __android_log_print(ANDROID_LOG_ERROR,
                       "image_classify attrs",