generalized Dice loss for segmentation for Caffe

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I am struggling to implement the generalized Dice loss for Caffe as Python Layer, which calculates loss for sub-volumes. I am hoping to get some help here. Or at least, if there is any code, please share the link.

I have 5 labels (0: background and labels1:4 for objects). Since I am getting a patch from 3D data, some of the subvolumes only contain the background. How the dice loss should be calculated for this sub-volumes?

Why in this line of code for creating One-hot label, the author has separated the background voxels counting?

Do we calculate the volume overlap for the background voxels too?

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