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loicland avatar loicland commented on June 8, 2024

This is because 0 is used as the nolabel class during training (stairs are not evaluated). Since the nolabel class is never predicted, we shift the labels by one when evaluating.

To see this, remember that the columns of target for a superpoint are as follows, (see here):

  • col0: label mode, ie the most common label the superpoint
  • col1: number of unannotated points
  • col2+: number of point of each label

When training, we use the cross entropy with the label mode (target[0]), see here. When evaluating, we compute the precision of the point-level predictions (target[2:]), see here.

from superpoint_graph.

fclairec avatar fclairec commented on June 8, 2024

Thanks @loicland for the explanation. I found my thinking mistake..

from superpoint_graph.

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