Hi, I'd like to use ImageAugmentationLayer in my binary image segmentation neural network. However, it seems like I can't get the ImageSegmentationLayer to do exactly the same transform on my input image as on my target mask. Is there a hidden way to do this that's not mentioned in the docs? It seems like every invocation of the layer will use a new random crop, but I need to do the exact same random crop on pairs of images. Cheers!
@Matteo - was this limitation overcome in the latest versions? I can't find a way to lock the random cropping so that I can augment input and output images of the same random crop. Neither outside training as a pre-processing step. BlockRandom does not seem to lock the random crop parameters. Thanks
In the meantime I'm using this function to do it.
randomCrop[is_, sz_] := Module[{x = RandomReal[{-1, 1}], y = RandomReal[{-1, 1}]}, ImageCrop[#, sz, {x, y}] & /@ is ]
