about the index of positive

[FL77N]

Hi! Thanks for your great works! I have a question about the index of positive, which I find in your onenet paper pseudocode as following:

# index of positive sample: N _, src_ind = torch.min(cost_mat, dim=0)
 # index of ground-truth: N tgt_ind = torch.arange(N)

but in the code as following using Hungarian Algorithm:

#  _, src_ind = torch.min(C, dim=0)
#  tgt_ind = torch.arange(len(tgt_ids)).to(src_ind)
src_ind, tgt_ind = linear_sum_assignment(C.cpu())
indices.append((src_ind, tgt_ind))

is the performance of Hungarian Algorithm better than that?