Scaling factor cancels out for depth values

[jocodeone]

I just found your code as I was searching for NYU Depth Data loaders. First of all, thanks a lot for making this public.

I think your scaling is not applied correctly.
As you divide by s, you reverse this by applying the transformation for the image and the depth values. Therefore you have the same depth values, but a scaled image. To correct this, you have to divide the depth values by the squared scaling when you still apply the same transformation.

Not sure whether this has an impact at all, but the camera world geometry is not correct as a result and maybe that has also an impact on the training itself.

sparse-to-dense.pytorch/dataloaders/nyu_dataloader.py

Line 14 in 10efc6d

depth_np = depth / s