darknet使用ncnn并移植到android _Android

【darknet使用ncnn并移植到android】逆水行舟用力撑，一篙松劲退千寻。这篇文章主要讲述darknet使用ncnn并移植到android相关的知识，希望能为你提供帮助。
项目使用的版本是老版darknet2ncnn，之后作者适配到了ncnn最新版。
编译安卓版ncnn
在linux下编译，查看官方教程即可。注意使用与android studio相同版本的ndk。设置android studio ndk：修改local.properties，ndk.dir=D:softbackAndroidandroid-ndk-r15c
添加相关源文件
将darknet、ncnn、darknet2ncnn相关源文件和头文件按目录添加到cpp目录下，目录结构如下：

├─darknet │├─include │└─src ├─darknet2ncnn │├─include │└─src └─ncnn ├─include └─src

darknet源码报错：

compare.c:17:13 error: initializing ‘network‘ (aka ‘struct network‘) with an expression of incompatible type ‘network *‘ (aka ‘struct network *‘);
 dereference with *.

修改compare.c，多处对应的指针类型和引用改一下就OK。
在darknet和darknet2ncnn package下new package，添加相关源码，但编译后android studio中该源码目录会显示在cpp目录下，不清楚啥原因，不过不影响编译。
编写Cmakelists.txt
这个是重点，很多问题就是没有写好Cmakelists.txt引起的。

cmake_minimum_required(VERSION 2.8.10)set(CMAKE_BUILD_TYPE RELEASE)set(libs " ${CMAKE_SOURCE_DIR}/src/main/jniLibs" ) include_directories(${CMAKE_SOURCE_DIR}/src/main/cpp/darknet2ncnn/include ${CMAKE_SOURCE_DIR}/src/main/cpp/ncnn/include ${CMAKE_SOURCE_DIR}/src/main/cpp/darknet/include ${CMAKE_SOURCE_DIR}/src/main/cpp/darknet2ncnn/src ${CMAKE_SOURCE_DIR}/src/main/cpp/ncnn/src)set(CMAKE_STATIC_LINKER_FLAGS " -lm-pthread -fopenmp -lstdc++" ) set(CMAKE_C_FLAGS" ${CMAKE_C_FLAGS} -Ofast -Wno-unused-result-Wfatal-errors -fPIC -fno-rtti -fno-exceptions" ) set(CMAKE_CXX_FLAGS" ${CMAKE_CXX_FLAGS} -std=c++11 -Ofast -Wno-unused-result-Wfatal-errors -fPIC -fno-rtti -fno-exceptions" )add_library (libncnn STATIC IMPORTED) set_target_properties(libncnn PROPERTIES IMPORTED_LOCATION ${CMAKE_SOURCE_DIR}/src/main/jniLibs/armeabi-v7a/libncnn.a)file(GLOB_RECURSE darknet_src ${CMAKE_SOURCE_DIR}/src/main/cpp/darknet/src/*.c)set(darknet2ncnn_dir ${CMAKE_SOURCE_DIR}/src/main/cpp/darknet2ncnn/src) set(darknet2ncnn_src ${darknet2ncnn_dir}/layer/darknet_activation.cpp ${darknet2ncnn_dir}/layer/darknet_shortcut.cpp ${darknet2ncnn_dir}/layer/yolov1_detection.cpp ${darknet2ncnn_dir}/layer/yolov3_detection.cpp ${darknet2ncnn_dir}/object_detection.cpp ${darknet2ncnn_dir}/register_darknet.cpp ${darknet2ncnn_dir}/darknet2ncnn.cpp)set(ncnn_src ${CMAKE_SOURCE_DIR}/src/main/cpp/ncnn/src)set(lib_src ${darknet_src} ${darknet2ncnn_src} ${CMAKE_SOURCE_DIR}/src/main/cpp/yolov3-tiny-jni.cpp)add_library( # Sets the name of the library. yolov3_tiny_jni# Sets the library as a shared library. SHARED# Provides a relative path to your source file(s). ${lib_src})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)target_link_libraries( # Specifies the target library. yolov3_tiny_jni libncnn jnigraphics# Links the target library to the log library # included in the NDK. ${log-lib})

错误解决
报错：undefined reference to ‘typeinfo for ncnn::Layer‘，这个在arm-linux交叉编译时遇到过，添加-fno-rtti编译选项即可。
报错：fatal error: use of undeclared identifier ‘nullptr‘，添加-std=c++11编译选项即可。
make project编译成功，so生成位置：appuildintermediatescmakedebugobjarmeabi-v7a
build apk报错：Cause: org.jetbrains.plugins.gradle.tooling.util.ModuleComponentIdentifierImpl.getModuleIdentifier()Lorg/gradle/api/artifacts/ModuleIdentifier; 更新android studio即可.
ex.extract返回-100，一般是没找到目标，这里有两种可能，一种是模型正确检测正确，测试图片本来就没目标，另一种情况就是模型有问题，不能正常检测到我们的目标。我反复检查了测试图片和模型都没问题，最后发现还是加载模型错误：

private String getPathFromAssets(String assetsFileName){ File f = new File(getCacheDir()+" /" +assetsFileName); if (!f.exists()) try { InputStream is = getAssets().open(assetsFileName); int size = is.available(); byte[] buffer = new byte[size]; is.read(buffer); is.close(); FileOutputStream fos = new FileOutputStream(f); fos.write(buffer); fos.close(); } catch (Exception e) { throw new RuntimeException(e); } return f.getPath(); }

之前的模型已经加载到缓存中了，后来我更换过一次模型，但是缓存没删除，还是之前的模型，所以一直检测不到目标，将if (!f.exists())注释掉，每次初始化都重新写入缓存，最后成功检测到目标。
总结
其实也比较简单，主要就写了个Cmakelists.txt。参考以下两项目，感谢作者大佬。
参考
安卓应用层
darknet2ncnn