digitalmars.D.learn - Find homography in D?
- Paolo Invernizzi (5/5) Apr 21 Hi,
- Ferhat =?UTF-8?B?S3VydHVsbXXFnw==?= (9/14) Apr 21 Kinda some work but it should be doable using DCV and mir.lubeck
- Ferhat =?UTF-8?B?S3VydHVsbXXFnw==?= (45/50) Apr 30 Just for future records in the forum.
- Jordan Wilson (28/33) Apr 30 Something I wrote awhile ago...
- Ferhat =?UTF-8?B?S3VydHVsbXXFnw==?= (4/9) May 13 Now, we can do image stitching using DCV. It needs improvements
Hi, Someone can point me to a D implementation of the classical OpenCV find homography matrix? Thank you, Paolo
Apr 21
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, PaoloKinda 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 https://medium.com/all-things-about-robotics-and-computer-vision/homography-and-how-to-calculate-it-8abf3a13ddc5
Apr 21
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, PaoloJust for future records in the forum. // https://math.stackexchange.com/questions/3509039/calculate-homography-with-and-without-svd /+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] }
Apr 30
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, PaoloSomething 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); } ```
Apr 30
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, PaoloNow, we can do image stitching using DCV. It needs improvements though. https://github.com/libmir/dcv/tree/master/examples/imagestitchinghomography
May 13