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It selects a label randomly within the voxel. Other ways to select label would be selecting argmax, or using the label distribution itself. However, currently these alternatives are not implemented yet.
I don't know if I put it clear. I want to build an FPN architecture, and I want to know the instance or semantic label for every output tower. Is there any fast implementation that I can refer to?
I see. It is a bit tricky to implement such models, but it is possible with get_kernel_map with kernel size 1 and sparse_quantize.
First, you use the sparse quantize with quantization 4*s to create labels and associate coordiates. At the last layer that you compute loss, you reorder the coordinates with get_kernel_map.
Thanks for sharing the code. I want to ask how to get the ground truth label if the output is 4s feature map, (ie. how to get the 4s ground truth)
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