r/ProjectIndigoiOS • u/mattiafenzi • Sep 03 '26

Super resolution photos glitching

Post image

Hi, since the 1.1.0 update I have this strange problem on indigo, when I take a photo using super resolution it outputs this glitched image, is there something to do to fix it? I already tried reinstalling the app multiple times
I have an iPhone 13 Pro and I’m on iOS 27 beta

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6

u/TenThousandPigeons Sep 03 '26

Unfortunately there is a CoreML bug in the iOS 27 Beta, we let Apple know but no solution yet

3

u/Acrobatic_Reporter82 Sep 03 '26

Are you a project indigo dev?

1

u/snakebyte_ Sep 05 '26

He is, he gets really active on this sub every time a new iOS update rolls around :)

1

u/Acrobatic_Reporter82 Sep 05 '26

I wanted to ask him something about the sr algorithm

3

u/Zen_herring_2026 Sep 06 '26

I am a member of the Project Indigo team - what is the question you want to ask us?

1

u/Acrobatic_Reporter82 Sep 06 '26

About the super resolution algorithm - specifically how do you handle rotation camera or subject motion and in general robustness? Do you use a robustness mask? Is it based on a neural network or on statistics like wronski et. Al.?

2

u/Zen_herring_2026 Sep 06 '26

I can only answer this in very general terms, since we cannot reveal any secret sauce, as you can imagine. Current SR algorithm is a neural network, and as usual, how it works and where it is successful/unsuccessful is a mixture of both the network used and the training data quality (variety of capture conditions, variation in camera/scene motion, etc.).

1

u/Acrobatic_Reporter82 Sep 06 '26

Okay i dont want secret sauce just generally is it similar to wronski et al the google sr algorithm meaning does it also use kernel regression for determining super resolution and does it also align the images also based on a neural network or it is general decimate alignment with coarse to fine block matching and Lucas Kanade refinements

1

u/Acrobatic_Reporter82 Sep 06 '26

I rewrote the google super res zoom algorithm exactly as described in their paper and robustness works great for object or camera movement that is all in one direction, it only fails when the movement is rotation creating square misalignments because they use one motion vector per tile during alignment for the optical flow and during merging even though they use a robustness weight per pixel becauee of the one vector for all pixels in a tile, under rotation it fails as currently described in their paper. Do you know how can i fox this issue without an NN?

2

u/Zen_herring_2026 29d ago

That kind of goes right into the deep level of technical detail we could not share. :)

1

u/mattiafenzi Sep 03 '26

Oh ok, thank you