Hi Oleg,
I have a case where I'm trying to generate dense GCPs between a raw image and a reference ortho image. Because they look a little different, ipfind/ipmatch struggle... so I have to collect a few matches manually. I then want to run parallel_stereo to generate dense matches. (I don't use correlator-mode, because the images are not aligned, so I need the affine-epipolar mode... also, I know the two images do actually correlate well enough, as I tested this elsewhere).
The problem is that stereo_pprc failes because it tries to use RANSAC on the matches I give it (I only have 8)... also, if fails when I use the auto match point generation in stereo_pprc, and despite experimenting with the parameters, I couldn't get it to continue. However, I know the ones I collected are good enough to go directly to the affine epipolar reprojection step. But I don't seem to be able to force stereo_pprc to skip the RANSAC step and simply use the matches I give it? Maybe I'm missing something?!
I tried using all these options (in various combinations):
--skip-rough-homography
--min-num-ip 5
--ip-num-ransac-iterations 0
--alignment-num-ransac-iterations 0
... but every time the RANSAC outlier removal is invoked in stereo_pprc, and the process fails.
As an alternative, I also collected some gcps to generate a basic camera for the raw image, which I then mapprojected and then successully correlated with the reference ortho using parallel_stereo correlator-mode to get dense matches. This works well!... but I end up with matches between the mapprojected raw image and the reference ortho... and I want them for the raw image.
Is there a way to project mapprojected image coordinates backt to the raw geometry? Bundle adjust and stereo_tri has this logic under the hood somewhere... it would be super handy to be able to access it for his purpose. It would be GCP collection from refrence imagery much more viable.
Cheers,
J