在上一篇文章《我的第一个caffe C 程序》中，说明了如何编写一个最简单的caffe C 程序，但我的最终目的是希望在Android app中使用caffe框架。所以接下来我就将模型测试程序testXOR移植到Android中，让Android app也能使用caffe深度学习框架。
caffe框架采用C 语言编写，具有良好的可移植性，不过官方代码并没有Android平台的移植。好在民间大神也很多，网上搜索了一把，发现已经有人做了caffe的Android平台移植，项目地址为：https://github.com/sh1r0/caffe-android-lib。
编译caffe-android-lib
caffe-android-lib的编译，建议还是采取docker的方式进行构建。我尝试过使用本地的android NDK进行编译，发现NDK版本不同，编译存在一定的问题。caffe-android-lib项目主页上有docker构建方法：
代码语言：javascript复制git clone --recursive https://github.com/sh1r0/caffe-android-lib.git
cd caffe-android-lib
# build image
docker build -t caffe-android-lib .
# run a container for building your own caffe-android-lib, e.g.,
docker run --rm --name caffe-android-builder
-e ANDROID_ABI=x86_64
-e N_JOBS=2
-v $(pwd)/android_lib/x86_64:/caffe-android-lib/android_lib
caffe-android-lib ./build.sh注意：指导上指定的ANDROID_ABI为x86_64，对于大多数手机而言，请修改为armeabi-v7a
编译好之后，caffe及关联库的头文件和库文件都位于android_lib目录下。在后面的步骤中，需要将这些头文件复制到示例工程下。
Android项目
在Android Studio中新建一个Android项目，跟着向导一步步来即可。然后将上一步骤的android_lib目录下的头文件和库文件复制过来，我把它们放在了cpp/third_party目录下了。caffe库是build为一个so，所以我将它放在了jniLibs目录下。
完整的项目源码可参考：https://gitee.com/mogoweb/dpexamples.git
在XORusingCAFFE-android目录下即为android版本的caffe示例程序。C 端的代码如下：
代码语言：javascript复制extern "C" JNIEXPORT jstringJNICALL
Java_com_mogoweb_caffe_xorusingcaffe_MainActivity_startXORTest(
JNIEnv *env,
jobject /* this */,
jstring modelProto,
jstring caffeModel) {
// caffe is using google logging (aka 'glog') as its logging module, and hence this module must be initialized once when running caffe.
// Therefore the following line
::google::InitGoogleLogging(""); // load the trained weights cached inside XOR_iter_5000000.caffemodel
shared_ptr<Net<float> > testnet; std::string modelproto = jstring2string(env, modelProto);
std::string caffemodel = jstring2string(env, caffeModel);
__android_log_print(ANDROID_LOG_INFO, "XOR", "modelproto:%s, caffemodel:%s", modelproto.c_str(), caffemodel.c_str());
testnet.reset(new Net<float>(modelproto, TEST));
testnet->CopyTrainedLayersFrom(caffemodel); // obtain the input MemoryData layer and pass the input to it for testing
float testab[] = {0, 0, 0, 1, 1, 0, 1, 1};
float testc[] = {0, 1, 1, 0}; MemoryDataLayer<float> *dataLayer_testnet = (MemoryDataLayer<float> *)(testnet->layer_by_name("test_inputdata").get()); dataLayer_testnet->Reset(testab, testc, 4); // calculate the neural network output
testnet->Forward(); // access blobs to display results
boost::shared_ptr<Blob<float> > output_layer = testnet->blob_by_name("output"); const float* begin = output_layer->cpu_data();
const float* end = begin 4; // We know the output size is 4, and we save the outputs into the result vector
vector<float> result(begin, end); // display the result
char buf[512] = {0};
string s;
for (int i = 0; i < result.size(); i ) {
sprintf(buf, "input: %d xor %d, truth: %d, result by NN: %fn",
(int)testab[i * 2 0], (int)testab[i * 2 1], (int)testc[i],result[i]);
s = buf;
} __android_log_print(ANDROID_LOG_INFO, "XOR", "test result:%s", s.c_str());
return string2jstring(env, s);
}相比linux版本的代码，有几处修改：
- 模型文件路径从Java层传递过来，也就是model.prototxt和XOR_iter_5000000.caffemodel文件的完整路径
- 输出结果通过JNI返回到Java层。
Java端的代码如下：
代码语言：javascript复制public class MainActivity extends AppCompatActivity {
File sdcard = Environment.getExternalStorageDirectory();
String modelDir = sdcard.getAbsolutePath();
String modelProto = modelDir "/model.prototxt";
String modelBinary = modelDir "/XOR_iter_5000000.caffemodel"; // Used to load the 'native-lib' library on application startup.
static {
System.loadLibrary("native-lib");
System.loadLibrary("caffe");
} @Override
protected void onCreate(Bundle savedInstanceState) {
super.onCreate(savedInstanceState);
setContentView(R.layout.activity_main); final TextView tv = findViewById(R.id.result);
Button btn = findViewById(R.id.start_test);
btn.setOnClickListener(new View.OnClickListener() {
@Override
public void onClick(View view) {
tv.setText(MainActivity.this.startXORTest(modelProto, modelBinary));
}
});
} /**
* A native method that is implemented by the 'native-lib' native library,
* which is packaged with this application.
*/
public native String startXORTest(String modelProto, String caffeModel);
}代码中假设模型文件位于sdcard中，所以在运行代码之前，需要将model.prototxt和XOR_iter_5000000.caffemodel文件push到/sdcard/中。
代码语言：javascript复制adb push app/src/main/model/model.prototxt /sdcard/
adb push app/src/main/model/XOR_iter_5000000.caffemodel /sdcard/代码编译与运行
使用android studio进行build，关键在于CMakeLists.txt的编写：
代码语言：javascript复制# For more information about using CMake with Android Studio, read the
# documentation: https://d.android.com/studio/projects/add-native-code.html# Sets the minimum version of CMake required to build the native library.cmake_minimum_required(VERSION 3.4.1)# Creates and names a library, sets it as either STATIC
# or SHARED, and provides the relative paths to its source code.
# You can define multiple libraries, and CMake builds them for you.
# Gradle automatically packages shared libraries with your APK.add_library( # Sets the name of the library.
native-lib # Sets the library as a shared library.
SHARED # Provides a relative path to your source file(s).
src/main/cpp/native-lib.cpp )add_definitions(-DCPU_ONLY)add_compile_options(-std=c 11)include_directories(${CMAKE_SOURCE_DIR}/src/main/cpp/third_party/caffe/include
${CMAKE_SOURCE_DIR}/src/main/cpp/third_party/boost/include
${CMAKE_SOURCE_DIR}/src/main/cpp/third_party/gflags/include
${CMAKE_SOURCE_DIR}/src/main/cpp/third_party/glog/include
${CMAKE_SOURCE_DIR}/src/main/cpp/third_party/protobuf/include
${CMAKE_SOURCE_DIR}/src/main/cpp/third_party/openblas/include)add_library(boost_system STATIC IMPORTED)
set_target_properties(boost_system
PROPERTIES
IMPORTED_LOCATION
${CMAKE_SOURCE_DIR}/src/main/cpp/third_party/boost/lib/libboost_system.a )add_library(caffe SHARED IMPORTED)
set_target_properties(caffe PROPERTIES IMPORTED_LOCATION
${CMAKE_SOURCE_DIR}/src/main/jniLibs/armeabi-v7a/libcaffe.so)# Searches for a specified prebuilt library and stores the path as a
# variable. Because CMake includes system libraries in the search path by
# default, you only need to specify the name of the public NDK library
# you want to add. CMake verifies that the library exists before
# completing its build.find_library( # Sets the name of the path variable.
log-lib # Specifies the name of the NDK library that
# you want CMake to locate.
log )# Specifies libraries CMake should link to your target library. You
# can link multiple libraries, such as libraries you define in this
# build script, prebuilt third-party libraries, or system libraries.target_link_libraries( # Specifies the target library.
native-lib # Links the target library to the log library
# included in the NDK.
${log-lib}
caffe
boost_system)需要注意的是：
- 需要添加-DCPU_ONLY的定义，因为在Android app中，暂时还无法使用GPU
- 需要加上caffe及相关库的头文件路径
- 需要链接caffe及相关库
最后运行的结果和linux PC环境下的一致：
参考
- 我的第一个caffe C 程序
- caffe-android-lib)
