Re^3: Abstract image registration or feature detection

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Re^4: Abstract image registration or feature detection by pryrt (Abbot) on Jul 04, 2022 at 20:54 UTC
Okay, 5.30.2 & PDL 2.021 and 5.32.1 & PDL 2.025 (the last pre-bundled Perl+PDL from Strawberry) both worked like my 5.30.0 & PDL 2.019. But I was able to install PDL 5.080 with Perl 5.32.1, to get slightly newer PDL but slightly older Perl than you. But it showed the same dimensional difference. So I did some debug to make it work without PDL::Matrix #!perl -l use 5.012; # //, strict, say use warnings; use PDL 2.057; #use PDL::Matrix; print "perl version $]"; print "PDL version $PDL::VERSION"; print my $red_in = (pdl [ # reference [419 , 17 ], # p01 [772 , 13 ], # p02 [348 , 102], # p03 [720 , 95 ], # p04 [58 , 238], # p05 [218 , 236], # p06 [55 , 333], # p07 [58 , 391], # p08 [60 , 498], # p09 [58 , 554], # p10 [1061, 553], # p11 [60 , 892], # p12 ])->append(ones(1))->transpose; print my $red_out = (pdl [ # target_41 [487, 466], # p01 [531, 630], # p02 [439, 447], # p03 [486, 618], # p04 [340, 328], # p05 [358, 401], # p06 [297, 343], # p07 [274, 349], # p08 [227, 366], # p09 [205, 374], # p10 [313, 809], # p11 [77 , 420], # p12 ])->append(ones(1))->transpose; print my $blue_in = (pdl [ # reference [438,331], # q01 [432,392], # q02 [436,493], # q03 [436,552], # q04 [439,602], # q05 ])->append(ones(1))->transpose; print my $blue_out_for_checking = (pdl [ # target_41 [339,508], # q01 [314,518], # q02 [265,533], # q03 [245,537], # q04 [228,544], # q05 ])->append(ones(1))->transpose; $\ = ''; print for "sx = ", my $sx = sum( $red_in->transpose->slice(0) ), + "\n", "sy = ", my $sy = sum( $red_in->transpose->slice(1) ), + "\n", "s1 = ", my $s1 = sum( $red_in->transpose->slice(2) ), + "\n", "sxx = ", my $sxx = sum( $red_in->transpose->slice(0)2 ), + "\n", "syy = ", my $syy = sum( $red_in->transpose->slice(1)2 ), + "\n", "sxy = ", my $sxy = sum( $red_in->transpose->slice(0)$red_in->tra +nspose->slice(1) ), "\n", "sv = ", my $sv = sum( $red_out->transpose->slice(0) ), + "\n", "sw = ", my $sw = sum( $red_out->transpose->slice(1) ), + "\n", "sxv = ", my $sxv = sum( $red_in->transpose->slice(0)$red_out->tr +anspose->slice(0) ), "\n", "sxw = ", my $sxw = sum( $red_in->transpose->slice(0)$red_out->tr +anspose->slice(1) ), "\n", "syv = ", my $syv = sum( $red_in->transpose->slice(1)$red_out->tr +anspose->slice(0) ), "\n", "syw = ", my $syw = sum( $red_in->transpose->slice(1)*$red_out->tr +anspose->slice(1) ), "\n", ; $\ = "\n"; print "G => ", my $G = pdl [ [ $sxx, $sxy, $sx ], [ $sxy, $syy, $sy ], [ $sx, $sy, $s1 ], ]; print "Q => ", my $Q = pdl [ [ $sxv, $sxw ], [ $syv, $syw ], [ $sv, $sw ], ]; print "P => ", my $P = inv($G) x $Q; # print "P->transpose", $P->transpose; # print "P->append->transpose", $P->append(zeros(1))->transpose; print "abcdef001 => ", my $abcdef001 = $P->append(zeros(1))->transpose +->set(2,2,1); print "blue out calc => ", my $blue_out_calc = $abcdef001 x $blue_in; print "error => ", $blue_out_calc - $blue_out_for_checking; # no more +than one pixel off __END__ perl version 5.032001 PDL version 2.080 [ [ 419 772 348 720 58 218 55 58 60 58 1061 60] [ 17 13 102 95 238 236 333 391 498 554 553 892] [ 1 1 1 1 1 1 1 1 1 1 1 1] ] [ [487 531 439 486 340 358 297 274 227 205 313 77] [466 630 447 618 328 401 343 349 366 374 809 420] [ 1 1 1 1 1 1 1 1 1 1 1 1] ] [ [438 432 436 436 439] [331 392 493 552 602] [ 1 1 1 1 1] ] [ [339 314 265 245 228] [508 518 533 537 544] [ 1 1 1 1 1] ] sx = 3887 sy = 3922 s1 = 12 sxx = 2604611 syy = 2052390 sxy = 929565 sv = 4034 sw = 5551 sxv = 1608891 sxw = 2354880 syv = 945962 syw = 1755275 G => [ [2604611 929565 3887] [ 929565 2052390 3922] [ 3887 3922 12] ] Q => [ [1608891 2354880] [ 945962 1755275] [ 4034 5551] ] P => [ [0.11504241 0.44420653] [-0.4325134 0.11994661] [ 440.26231 279.49489] ] abcdef001 => [ [0.11504241 -0.4325134 440.26231] [0.44420653 0.11994661 279.49489] [ 0 0 1] ] blue out calc => [ [ 347.48895 320.41538 277.19169 251.6734 230.39286] [ 513.75967 518.41118 532.30261 539.37946 546.70941] [ 1 1 1 1 1] ] error => [ [ 8.488949 6.4153774 12.191694 6.6734037 2.3928612] [ 5.7596723 0.41117608 -0.69739064 2.3794591 2.709409] [ 0 0 0 0 0] ] [download] This shows the 12-ish pixel error, but will hopefully work with your 2.057 (and definitely worked with my 2.080).	[reply] [d/l]
Re^4: Abstract image registration or feature detection by kikuchiyo (Hermit) on Jul 04, 2022 at 21:01 UTC
Minimal pair: `perl -MPDL -MPDL::Matrix -e '$m = mpdl [[2,0],[0,2]]; $v = vpdl [1,2]; + print $m x $v' [ [2] [4] ]` [download] vs. `perl -MPDL -MPDL::Matrix -e '$m = mpdl [[2,0],[0,2]]; $v = vpdl [1,2]; + print inv($m) x $v' Dim mismatch in matmult of [2x2] x [2x1]: 2 != 1 at /usr/lib64/perl5/v +endor_perl/PDL/Primitive.pm line 274. PDL::matmult(PDL=SCALAR(0x5600a82130e0), PDL::Matrix=SCALAR(0x5600 +a8202ba0), PDL=SCALAR(0x5600a8d718c8)) called at /usr/lib64/perl5/ven +dor_perl/PDL/Primitive.pm line 31 PDL::__ANON__(PDL=SCALAR(0x5600a82130e0), PDL::Matrix=SCALAR(0x560 +0a8202ba0), "") called at -e line 1` [download] This looks like a bug in PDL::Matrix, specifically with inv.	[reply] [d/l] [select]
Re^5: Abstract image registration or feature detection by etj (Priest) on Jul 05, 2022 at 20:51 UTC
As now noted on pryrt's excellent bug report (thank you), this will still work as expected if you switch your `inv($m)` to `$m->inv`. This will then engage PDL::Matrix's overload of `x`, which is what you need here. I would strongly encourage you not to use PDL::Matrix, because somewhat similar to PDL::Complex, it is full of gotchas. Even though after some head-scratching it became clear what exactly was happening here, it's not particularly clear how to fix it - a keyhole change to the Perl function PDL::MatrixOps::inv to make it ensure the output was the right class would resolve this exact issue. But since that uses lu_backsub for its work, and that is an eye-wateringly complicated Perl function as well, it will not be easy. That function's output variable comes from some PDL::Slices operations. If someone were minded to at least use `git bisect` to identify the commit that broke it, that would be very helpful. Even better would be a pull-request that fixes this (obviously with a test, in `t/matrix.t`), that will use our amazing CI to check it doesn't break anything else in main PDL or known downstreams. A top tip would be that `make coretest` runs `t/matrix.t`, with a very minimal build otherwise that allows a very quick dev cycle. As a hopefully practical (as well as better-performance, because it uses LAPACK) alternative, have you taken a look at PDL::LinearAlgebra?	[reply] [d/l] [select]
Re^5: Abstract image registration or feature detection by pryrt (Abbot) on Jul 05, 2022 at 19:28 UTC
kikichiyo, Thanks for that SSCCE. I included it in a bug report	[reply]
Re^4: Abstract image registration or feature detection by etj (Priest) on Jul 05, 2022 at 21:26 UTC
The way to avoid needing `mpdl` is to transpose your data, and use `pdl`, and I would recommend doing so. But as observed elsewhere, there are almost certainly out-of-the-box solutions to this particular problem.	[reply] [d/l] [select]