Search

Hi,

Someone can point me to a D implementation of the classical OpenCV find homography matrix?

Thank you,
Paolo

On Sunday, 21 April 2024 at 14:57:33 UTC, Paolo Invernizzi wrote:

>

Hi,

Someone can point me to a D implementation of the classical OpenCV find homography matrix?

Thank you,
Paolo

Kinda some work but it should be doable using DCV and mir.lubeck in theory

DCV can compute, not sift or surf b, but similar features https://github.com/libmir/dcv/blob/master/examples/features/source/app.d

Lubeck computes singular value decomposition
https://github.com/kaleidicassociates/lubeck

And this method but with mir ndslices

On Sunday, 21 April 2024 at 14:57:33 UTC, Paolo Invernizzi wrote:

>

Hi,

Someone can point me to a D implementation of the classical OpenCV find homography matrix?

Thank you,
Paolo

Just for future records in the forum.

/+dub.sdl:
dependency "lubeck" version="~>1.5.4"
+/
import std;
import mir.ndslice;
import kaleidic.lubeck;

``````void main()
{
double[2] x_1 = [93,-7];
double[2] y_1 = [63,0];
double[2] x_2 = [293,3];
double[2] y_2 = [868,-6];
double[2] x_3 = [1207,7];
double[2] y_3 = [998,-4];
double[2] x_4 = [1218,3];
double[2] y_4 = [309,2];

auto A = [
-x_1[0], -y_1[0], -1, 0, 0, 0, x_1[0]*x_1[1], y_1[0]*x_1[1], x_1[1],
0, 0, 0, -x_1[0], -y_1[0], -1, x_1[0]*y_1[1], y_1[0]*y_1[1], y_1[1],
-x_2[0], -y_2[0], -1, 0, 0, 0, x_2[0]*x_2[1], y_2[0]*x_2[1], x_2[1],
0, 0, 0, -x_2[0], -y_2[0], -1, x_2[0]*y_2[1], y_2[0]*y_2[1], y_2[1],
-x_3[0], -y_3[0], -1, 0, 0, 0, x_3[0]*x_3[1], y_3[0]*x_3[1], x_3[1],
0, 0, 0, -x_3[0], -y_3[0], -1, x_3[0]*y_3[1], y_3[0]*y_3[1], y_3[1],
-x_4[0], -y_4[0], -1, 0, 0, 0, x_4[0]*x_4[1], y_4[0]*x_4[1], x_4[1],
0, 0, 0, -x_4[0], -y_4[0], -1, x_4[0]*y_4[1], y_4[0]*y_4[1], y_4[1]
].sliced(8, 9);

auto svdResult = svd(A);

auto homography = svdResult.vt[\$-1].sliced(3, 3);
auto transformedPoint = homography.mtimes([1679,  128, 1].sliced.as!double.slice);
transformedPoint[] /= transformedPoint[2];

writeln(transformedPoint); //[4, 7, 1]
}
``````

On Sunday, 21 April 2024 at 14:57:33 UTC, Paolo Invernizzi wrote:

>

Hi,

Someone can point me to a D implementation of the classical OpenCV find homography matrix?

Thank you,
Paolo

Something I wrote awhile ago...

``````import kaleidic.lubeck : svd;
import gfm.math;
import mir.ndslice : sliced;

auto generateTransformationArray(int[] p) {
return generateTransformationArray(p[0],p[1],p[2],p[3]);
}

auto generateTransformationArray(int x, int y, int x_, int y_) {
return [-x, -y, -1, 0, 0, 0, x*x_, y*x_, x_,
0, 0, 0, -x, -y, -1, x*y_, y*y_, y_];
}

auto transformCoor (mat3d mat, vec3d vec) {
auto res = mat * vec;
return res / res[2];
}

auto findHomography (int[][] correspondances) {
auto a = correspondances
.map!(a => a.generateTransformationArray)
.joiner
.array
.sliced(8,9);

auto r = a.svd;
auto homog = r.vt.back;
return mat3d(homog.map!(a => a/homog.back).array);
}
``````

On Sunday, 21 April 2024 at 14:57:33 UTC, Paolo Invernizzi wrote:

>

Hi,

Someone can point me to a D implementation of the classical OpenCV find homography matrix?

Thank you,
Paolo

Now, we can do image stitching using DCV. It needs improvements though.

https://github.com/libmir/dcv/tree/master/examples/imagestitchinghomography