Hi!
An update regarding this matter, I tried a pure dlib example as shown below:
# C++ test Code
cxx"""
// The contents of this file are in the public domain. See LICENSE_FOR_EXAMPLE_PROGRAMS.txt
/*
This is an example illustrating the use of the matrix object
from the dlib C++ Library.
*/
#include <iostream>
#include <dlib/matrix.h>
using namespace dlib;
using namespace std;
// ----------------------------------------------------------------------------------------
int main()
{
// 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;
// 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;
// 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;
// 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;
// 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;
// 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;
// Note that you can always print a matrix to an output stream by saying:
cout << 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;
// 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);
}
// ----------------------------------------------------------------------------------------
"""
To add on to this, I defined my PKG_CONFIG_PATH as shown below:
ENV["PKG_CONFIG_PATH"]="/home/hp/OpenCV_installation/installation/OpenCV-3.4.1/lib/pkgconfig:/home/hp/cv2faces/cv4faces/dlib/build/dlib"
When I call my code as, @cxx main(), I get this:
0
x:
-0.211558
-13.9097
9.74368
M*x - y:
2.84217e-14
9.99201e-15
1.77636e-15
7.4
1.2
sum of all elements in M is 86.65
sum of all elements in M is 86.65
54.2 7.4 12.1
1 2 3
5.9 0.05 1
54.2, 7.4, 12.1
1, 2, 3
5.9, 0.05, 1
It’s weird that I am not getting any error this time.
I will appreciate any help regarding this.
Thanks
Vishwesh
