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My thinking with mentioning Rife in the name was in case in the future different kinds of alignment methods are added. For example it may make sense to add a traditional affine alignment method at some point, which would be better with images that are off by a lot, which could then be refined by this method. But maybe it makes more sense to think about that if it happens. What do you think?
It works pretty well; would there be interest in a PR that adds a chaiNNer node with that implementation (subject to whatever code quality cleanup is needed to meet chaiNNer standards)? As @pifroggi observed, it might complement the RIFE implementation.
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Yes, that would be nice if you wouldn't mind. I still would like it to not be a separate node but rather have a "rife" and a "homography" mode on the one node.
Yes, that would be nice if you wouldn't mind. I still would like it to not be a separate node but rather have a "rife" and a "homography" mode on the one node.
@joeyballentine I see why that's desirable in the general case, but isn't there some precedent in chaiNNer for using separate nodes for PyTorch-based stuff versus non-NN stuff (I guess so that dependency checking works properly)?
Continuing from @pifroggi's comment at #2714 (comment)
I have an implementation of OpenCV-based image alignment (based on a homography matrix) here: https://github.com/Splendide-Imaginarius/subimage-stitcher
It works pretty well; would there be interest in a PR that adds a chaiNNer node with that implementation (subject to whatever code quality cleanup is needed to meet chaiNNer standards)? As @pifroggi observed, it might complement the RIFE implementation.
The text was updated successfully, but these errors were encountered: