Fix nonlinear transformations

[sumanthratna]

• non_parametric: functional
• bspline: functional
• wendland: functional

Decreasing the learning rate solves the issue of the loss of microarchitectural details (airlab-unibas/airlab#26). Further experimentation with parameters may be necessary.

[jlevy44]

#6 I think this looks good enough to merge, just going to validate with a test.

[sumanthratna]

Nonparametric

python pathflow_mixmatch/cli.py register_images --im1 ./COAD_19_5pc.jpg --im2 ./COAD_19_5pc_S1.jpg --output_dir non_parametric/ --gpu_device 1 --transform_type non_parametric --no_segment_analysis True --verbose True --overwrite True --loss_fn ncc --lr 0.00001

B-spline

python pathflow_mixmatch/cli.py register_images --im1 ./COAD_19_5pc.jpg --im2 ./COAD_19_5pc_S1.jpg --output_dir bspline/ --gpu_device 1 --transform_type bspline --no_segment_analysis True --verbose True --overwrite True --loss_fn ncc --lr 0.00001

Wendland

python pathflow_mixmatch/cli.py register_images --im1 ./COAD_19_5pc.jpg --im2 ./COAD_19_5pc_S1.jpg --output_dir wendland/ --gpu_device 1 --transform_type wendland --no_segment_analysis True --verbose True --overwrite True --loss_fn ncc --lr 0.00001

[jlevy44]

Excellent, thanks!

[jlevy44]

Hey so I'm testing right now. Seems like nonlinear transforms run out of memory very quickly (32GB GPU). I'm running an affine transformation right now and all linear transforms seem to be okay

[jlevy44]

I think part of it is in the create_image_pyramids, airlab-unibas/airlab#29 which I have tried to remedy here: https://github.com/jlevy44/airlab . Still too much memory.

[jlevy44]

So still memory issues. I'm going to merge here and then open up a new PR. @sumanthratna I've added you as a collaborator so feel free to open additional branches in this repo.

[jlevy44]

In any case, it was functional and thus should have been merged anyways.