Sometimes when training a segmentation-model, the given masks/labels overlap. For example, a single point might belong to two classes at the same time.
There are UNet implementations which accept multiple classes as labels, by taking a target with multiple channels (one for each type of mask) per image.
What would be the best way to do this with the fastai library. Is this even possible?