dlib 18 android编译dlib库，运行matrix_ex demo

01 android studio 创建支持c++项目

打开android studio后，构建一个支持c++的项目，具体步骤如下：

01.01 Start a new Android Studio project

01.02 Configure your new project

Application name:dlib-android-buildCompany domain:soft.example.com勾选 Include C++ supportProject location:D:\git\dlib\build\dlib-android-build

01.03 Target Android Devices选择默认项

01.04 Add an Activity to Mobile 选择Basic Activity

01.05 Customize the Activity选择默认值

01.06 Customize C++ Support

C++ Standard 选择C++11勾选 Exceptions Support(-fexceptions)勾选 Runtime Type Information Support (-frtti)

02 导入dlib库，配置android属性

02.01 导入dlib库源码

把下载好的dlib目录中的dlib子目录，拷贝到D:\git\dlib\build\dlib-android-build\app\src\main\cpp中。

02.02 修改CMakeLists.txt配置项

修改D:\git\dlib\build\dlib-android-build\app\CMakeLists.txt配置项。
在add_library和find_library之间加入一句include(src/main/cpp/dlib/cmake)
在target_link_libraries中添加dlib

02.03 配置build.gradle

配置D:\git\dlib\build\dlib-android-build\app\build.gradle
在build.gradle的externalNativeBuild的cmake中添加arguments "-DANDROID_STL=c++_shared"

03 导入C++demo中的 matrix_ex

创建这个android项目，默认已经有native-lib.cpp文件，内容如下：

#include <jni.h>#include <string>extern "C"JNIEXPORT jstring JNICALLJava_com_example_soft_dlib_1android_1build_MainActivity_stringFromJNI(        JNIEnv *env,        jobject /* this */) {    std::string hello = "Hello from C++";    return env->NewStringUTF(hello.c_str());}

dlib的github下载的源代码中，有dlib\examples\matrix_ex.cpp。因为stringFromJNI返回值是string类型，把matrix_ex 内容稍作修改，把默认输出改为字符串。拷贝到native-lib.cpp，最后native-lib.cpp的内容如下：

#include <jni.h>#include <string>#include <iostream>#include <dlib/matrix.h>#include <sstream>using namespace dlib;using namespace std;// ----------------------------------------------------------------------------------------string matrix_ex(){    stringstream ssout;    // Let's begin this example by using the library to solve a simple    // linear system.    //    // We will find the value of x such that y = M*x where    //    //      3.5    // y =  1.2    //      7.8    //    // and M is    //    //      54.2   7.4   12.1    // M =  1      2     3    //      5.9    0.05  1    // First let's declare these 3 matrices.    // This declares a matrix that contains doubles and has 3 rows and 1 column.    // Moreover, it's size is a compile time constant since we put it inside the <>.    matrix<double,3,1> y;    // Make a 3 by 3 matrix of doubles for the M matrix.  In this case, M is    // sized at runtime and can therefore be resized later by calling M.set_size().    matrix<double> M(3,3);    // You may be wondering why someone would want to specify the size of a    // matrix at compile time when you don't have to.  The reason is two fold.    // First, there is often a substantial performance improvement, especially    // for small matrices, because it enables a number of optimizations that    // otherwise would be impossible.  Second, the dlib::matrix object checks    // these compile time sizes to ensure that the matrices are being used    // correctly.  For example, if you attempt to compile the expression y*y you    // will get a compiler error since that is not a legal matrix operation (the    // matrix dimensions don't make sense as a matrix multiplication).  So if    // you know the size of a matrix at compile time then it is always a good    // idea to let the compiler know about it.    // Now we need to initialize the y and M matrices and we can do so like this:    M = 54.2,  7.4,  12.1,            1,     2,    3,            5.9,   0.05, 1;    y = 3.5,            1.2,            7.8;    // The solution to y = M*x can be obtained by multiplying the inverse of M    // with y.  As an aside, you should *NEVER* use the auto keyword to capture    // the output from a matrix expression.  So don't do this: auto x = inv(M)*y;    // To understand why, read the matrix_expressions_ex.cpp example program.    matrix<double> x = inv(M)*y;    cout << "x: \n" << x << endl;    ssout << "x: \n" << x << endl;    // We can check that it really worked by plugging x back into the original equation    // and subtracting y to see if we get a column vector with values all very close    // to zero (Which is what happens.  Also, the values may not be exactly zero because    // there may be some numerical error and round off).    cout << "M*x - y: \n" << M*x - y << endl;    ssout << "M*x - y: \n" << M*x - y << endl;    // Also note that we can create run-time sized column or row vectors like so    matrix<double,0,1> runtime_sized_column_vector;    matrix<double,1,0> runtime_sized_row_vector;    // and then they are sized by saying    runtime_sized_column_vector.set_size(3);    // Similarly, the x matrix can be resized by calling set_size(num rows, num columns).  For example    x.set_size(3,4);  // x now has 3 rows and 4 columns.    // The elements of a matrix are accessed using the () operator like so:    cout << M(0,1) << endl;    ssout << M(0,1) << endl;    // The above expression prints out the value 7.4.  That is, the value of    // the element at row 0 and column 1.    // If we have a matrix that is a row or column vector.  That is, it contains either    // a single row or a single column then we know that any access is always either    // to row 0 or column 0 so we can omit that 0 and use the following syntax.    cout << y(1) << endl;    ssout << y(1) << endl;    // The above expression prints out the value 1.2    // Let's compute the sum of elements in the M matrix.    double M_sum = 0;    // loop over all the rows    for (long r = 0; r < M.nr(); ++r)    {        // loop over all the columns        for (long c = 0; c < M.nc(); ++c)        {            M_sum += M(r,c);        }    }    cout << "sum of all elements in M is " << M_sum << endl;    ssout << "sum of all elements in M is " << M_sum << endl;    // The above code is just to show you how to loop over the elements of a matrix.  An    // easier way to find this sum is to do the following:    cout << "sum of all elements in M is " << sum(M) << endl;    ssout << "sum of all elements in M is " << sum(M) << endl;    // Note that you can always print a matrix to an output stream by saying:    cout << M << endl;    ssout << M << endl;    // which will print:    //   54.2  7.4 12.1    //      1    2    3    //    5.9 0.05    1    // However, if you want to print using comma separators instead of spaces you can say:    cout << csv << M << endl;    ssout << csv << M << endl;    // and you will instead get this as output:    //   54.2, 7.4, 12.1    //   1, 2, 3    //   5.9, 0.05, 1    // Conversely, you can also read in a matrix that uses either space, tab, or comma    // separated values by uncommenting the following:    // cin >> M;    // -----------------------------  Comparison with MATLAB ------------------------------    // Here I list a set of Matlab commands and their equivalent expressions using the dlib    // matrix.  Note that there are a lot more functions defined for the dlib::matrix.  See    // the HTML documentation for a full listing.    matrix<double> A, B, C, D, E;    matrix<int> Aint;    matrix<long> Blong;    // MATLAB: A = eye(3)    A = identity_matrix<double>(3);    // MATLAB: B = ones(3,4)    B = ones_matrix<double>(3,4);    // MATLAB: B = rand(3,4)    B = randm(3,4);    // MATLAB: C = 1.4*A    C = 1.4*A;    // MATLAB: D = A.*C    D = pointwise_multiply(A,C);    // MATLAB: E = A * B    E = A*B;    // MATLAB: E = A + B    E = A + C;    // MATLAB: E = A + 5    E = A + 5;    // MATLAB: E = E'    E = trans(E);  // Note that if you want a conjugate transpose then you need to say conj(trans(E))    // MATLAB: E = B' * B    E = trans(B)*B;    double var;    // MATLAB: var = A(1,2)    var = A(0,1); // dlib::matrix is 0 indexed rather than starting at 1 like Matlab.    // MATLAB: C = round(C)    C = round(C);    // MATLAB: C = floor(C)    C = floor(C);    // MATLAB: C = ceil(C)    C = ceil(C);    // MATLAB: C = diag(B)    C = diag(B);    // MATLAB: B = cast(A, "int32")    Aint = matrix_cast<int>(A);    // MATLAB: A = B(1,:)    A = rowm(B,0);    // MATLAB: A = B([1:2],:)    A = rowm(B,range(0,1));    // MATLAB: A = B(:,1)    A = colm(B,0);    // MATLAB: A = [1:5]    Blong = range(1,5);    // MATLAB: A = [1:2:5]    Blong = range(1,2,5);    // MATLAB: A = B([1:3], [1:2])    A = subm(B, range(0,2), range(0,1));    // or equivalently    A = subm(B, rectangle(0,0,1,2));    // MATLAB: A = B([1:3], [1:2:4])    A = subm(B, range(0,2), range(0,2,3));    // MATLAB: B(:,:) = 5    B = 5;    // or equivalently    set_all_elements(B,5);    // MATLAB: B([1:2],[1,2]) = 7    set_subm(B,range(0,1), range(0,1)) = 7;    // MATLAB: B([1:3],[2:3]) = A    set_subm(B,range(0,2), range(1,2)) = A;    // MATLAB: B(:,1) = 4    set_colm(B,0) = 4;    // MATLAB: B(:,[1:2]) = 4    set_colm(B,range(0,1)) = 4;    // MATLAB: B(:,1) = B(:,2)    set_colm(B,0) = colm(B,1);    // MATLAB: B(1,:) = 4    set_rowm(B,0) = 4;    // MATLAB: B(1,:) = B(2,:)    set_rowm(B,0) = rowm(B,1);    // MATLAB: var = det(E' * E)    var = det(trans(E)*E);    // MATLAB: C = pinv(E)    C = pinv(E);    // MATLAB: C = inv(E)    C = inv(E);    // MATLAB: [A,B,C] = svd(E)    svd(E,A,B,C);    // MATLAB: A = chol(E,'lower')    A = chol(E);    // MATLAB: var = min(min(A))    var = min(A);    return ssout.str();}extern "C"JNIEXPORT jstring JNICALLJava_com_example_soft_dlib_1android_1build_MainActivity_stringFromJNI(        JNIEnv *env,        jobject /* this */) {    //std::string hello = "Hello from C++";    std::string hello = matrix_ex();    return env->NewStringUTF(hello.c_str());}

04 编译，调试

04.01 编译

选择Build==>Make Project菜单，或者Ctrl+F9键编译。

04.02 调试

选择Run==>Debug ‘app’菜单，或者Shift+F9键调试。

04.03 运行结果