Ubuntu下搭建Android PCL、OPENCV开发环境
搭建步骤
- PCL
-
- 下载 PCL for android
- Android studio中配置
- java 、 c++ 混合开发opencv
-
- C++部分
-
- 1、首先下载 opencv-android-sdk
- 2、解压
- 3、修改 CMakeLists.txt 链接 libopencv_java4.so
- 4、在C++代码中使用opencv
- JAVA部分
- Android studio 中配置
-
- 1、导入OpenCV module：
- 2、配置opencv410 的build.gradle
- 3、将opencv添加为app的 module dependences
PCL
PCL（Point Cloud Library）是在吸收了前人点云相关研究基础上建立起来的大型跨平台开源C++编程库，它实现了大量点云相关的通用算法和高效数据结构，涉及到点云获取、滤波、分割、配准、检索、特征提取、识别、追踪、曲面重建、可视化等。支持多种操作系统平台，可在Windows、Linux、Android、Mac OS X、部分嵌入式实时系统上运行。如果说OpenCV是2D信息获取与处理的结晶，那么PCL就在3D信息获取与处理上具有同等地位，PCL是BSD授权方式，可以免费进行商业和学术应用。
下载 PCL for android
PCL一般需要我们自己编译，过程相当麻烦，这里提供已经编译好的
链接:pcl download
Android studio中配置
将下载好的压缩包解压，里面包含了lib和include头文件。打开android studio，打开CmakeLists，按如下进行配置：
cmake_minimum_required(VERSION 3.4.1)
set(PCL_BUILD "/home/xxx/PCL_android/build")
set(PCL_INCLUDE "${PCL_BUILD}/pcl-android")
set(BOOST_INCLUDE "${PCL_BUILD}/boost-android")
set(FLANN_INCLUDE "${PCL_BUILD}/flann-android")
set(EIGEN_INCLUDE "${PCL_BUILD}/eigen")
set(QHULL_INCLUDE "${PCL_BUILD}/qhull-android")
set(PCL_STATIC_LIB_DIR "${PCL_INCLUDE}/lib")
set(BOOST_STATIC_LIB_DIR "${BOOST_INCLUDE}/lib")
set(FLANN_STATIC_LIB_DIR "${FLANN_INCLUDE}/lib")
set(QHULL_STATIC_LIB_DIR "${QHULL_INCLUDE}/lib")
include_directories(${PCL_INCLUDE}/include)
include_directories(${BOOST_INCLUDE}/include)
include_directories(${FLANN_INCLUDE}/include)
include_directories(${QHULL_INCLUDE}/include)
include_directories(${EIGEN_INCLUDE})
function(importLib dirName libName)
add_library(${libName} SHARED IMPORTED)
set_target_properties(${libName}
PROPERTIES
IMPORTED_LOCATION
"${dirName}/${libName}.a")
endfunction(importLib)
set(libFlannNames
libflann_cpp_s
libflann_s
)
set(libBoostNames
libboost_thread
libboost_signals
libboost_program_options
libboost_filesystem
libboost_system
libboost_regex
libboost_iostreams
libboost_date_time
)
set(libQhullNames
libqhullstatic
)
set(libPclNames
libpcl_stereo
libpcl_2d
libpcl_segmentation
libpcl_recognition
libpcl_ml
libpcl_io
libpcl_io_ply
libpcl_filters
libpcl_tracking
libpcl_search
libpcl_registration
libpcl_keypoints
libpcl_features
libpcl_surface
libpcl_sample_consensus
libpcl_octree
libpcl_kdtree
libpcl_common
)
foreach(lib ${libPclNames})
importLib(${PCL_STATIC_LIB_DIR} ${lib})
endforeach(lib)
foreach(lib ${libFlannNames})
importLib(${FLANN_STATIC_LIB_DIR} ${lib})
endforeach(lib)
foreach(lib ${libBoostNames})
importLib(${BOOST_STATIC_LIB_DIR} ${lib})
endforeach(lib)
foreach(lib ${libQhullNames})
importLib(${QHULL_STATIC_LIB_DIR} ${lib})
endforeach(lib)
add_library(native-jni SHARED
native-jni.cpp
)
target_link_libraries(
native-jni
${libPclNames}
${libFlannNames}
${libBoostNames}
${libQhullNames}
android
log)
build.gradle中添加编译设置
app--> build.gradle:
android {
..../
externalNativeBuild {
cmake {
cppFlags "-DBOOST_SYSTEM_NO_DEPRECATED"
//arguments '-DANDROID_TOOLCHAIN=clang', '-DANDROID_STL=c++_static', '-DCMAKE_BUILD_TYPE=Release'
abiFilters 'armeabi-v7a','x86', 'arm64-v8a', 'x86_64'
}
}
}
OK， 就是这么简单的配置，难点主要是自己编译android版的pcl sdk。有兴趣的朋友可以自己尝试用ndk去编译自己想要的pcl这里不详说了。
java 、 c++ 混合开发opencv
Opencv做图像处理的都不陌生吧，OpenCV是一个基于BSD许可（开源）发行的跨平台计算机视觉库，可以运行在Linux、Windows、Android和Mac OS操作系统上。它轻量级而且高效——由一系列 C 函数和少量 C++ 类构成，同时提供了Python、Ruby、MATLAB等语言的接口，实现了图像处理和计算机视觉方面的很多通用算法。接下来介绍如何在Android上搭建Opencv Java && c++混合开发环境。
C++部分
1、首先下载 opencv-android-sdk
直接去官网下就OK。
链接:opencv download
选择自己想要的版本下载。
2、解压
将下载的压缩包解压，把 Opencv/OpenCV-android-sdk/sdk/native/libs 下的so库文件到项目的Libs下面（没有Libs就自己新建一个，跟src同级目录），
build.gradle中加一段：
sourceSets{
main{
jniLibs.srcDirs = ['libs']
}
}
3、修改 CMakeLists.txt 链接 libopencv_java4.so
NDK开发基本使用CmakeLists来构建项目，因此这里只说明CmakeLists的配置，我的配置如下:
# opencv 公共路径
set(pathToOpenCv /home/xxx/Opencv/OpenCV-android-sdk)
# 配置native依赖,引入 opencv 头文件
include_directories(${pathToOpenCv}/sdk/native/jni/include)
add_library(
opencv_java4
SHARED
IMPORTED)
set_target_properties(
opencv_java4
PROPERTIES
IMPORTED_LOCATION
../../../../libs/${ANDROID_ABI}/libopencv_java4.so
)
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).
#native-lib.cpp
fusionmeasure.cpp
)
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.
native-lib
opencv_java4
# Links the target library to the log library
# included in the NDK.
android
GLESv3
${log-lib})
4、在C++代码中使用opencv
#include 上面的配置顺利的话。纯C++开发已经足够，但是opencv还提供了java api，所以接下来再介绍java开发opencv如何配置。
JAVA部分
opencv也提供了java层的api，打开我们解压好的文件夹，会看到有 java 文件夹（OpenCV-android-sdk/sdk/java）。接下来进行配置。
Android studio 中配置
1、导入OpenCV module：
–> 菜单栏选择File
–> new
–> imported module
–> 选择Opencv/OpenCV-android-sdk/sdk/java
–> module名字随便取，这里假定为：opencv410
2、配置opencv410 的build.gradle
直接复制一份项目的 build.gradle(app)，去掉ndk编译的配置，这里举例我的配置，注意里面有两个地方要做修改，一个是第一行的 “apply plugin: ‘com.android.application’” 变为 **apply plugin: ‘com.android.library’ **， 还有就是删除 applicationId
// 这里要修改为 com.android.library
apply plugin: 'com.android.library'
android {
compileSdkVersion 28
buildToolsVersion "29.0.2"
defaultConfig {
//applicationId "com.example.myopencvprj" 删除
minSdkVersion 19
targetSdkVersion 28
versionCode 1
versionName "1.0"
testInstrumentationRunner "androidx.test.runner.AndroidJUnitRunner"
externalNativeBuild {
cmake {
//cppFlags ""
//abiFilters 'armeabi-v7a', 'arm64-v8a'
}
}
}
buildTypes {
release {
minifyEnabled false
proguardFiles getDefaultProguardFile('proguard-android-optimize.txt'), 'proguard-rules.pro'
}
}
sourceSets{
main{
jniLibs.srcDirs = ['libs']
}
}
}
dependencies {
implementation fileTree(dir: 'libs', include: ['*.jar'])
implementation 'androidx.constraintlayout:constraintlayout:1.1.3'
implementation 'com.android.support:design:28.1.1'
implementation 'com.github.chrisbanes.photoview:library:1.2.4'
implementation 'com.afollestad.material-dialogs:core:0.9.1.0'
implementation 'com.afollestad.material-dialogs:commons:0.9.1.0'
testImplementation 'junit:junit:4.12'
}
3、将opencv添加为app的 module dependences
build.gradle中添加如下：
implementation project(path: ‘:openCV410’).
OK 大功告成。