I have several different raster layers; each layer is derived from the same scene and each represent a different Vegetation Index layer (where each pixel represents a unique vegetation index value). I wish to use each imagery layer to create Deep Learning samples using the 'Label Objects for Deep Learning' tool. Critically, I wish to re-use the polygon shapes created for one raster layer for each of the raster layers. In other words, I need to create a set of Deep Learning samples using one raster layer, and then simply take the same polygon shapes for those training samples and overlay them onto the other raster layers to create a new set of training samples for those layers. I have experimented with the tools and have not found a way to do this. Can anyone recommend a workflow or suggest a workaround?