Comments (2)
davidsandberg
commented on May 1, 2024
There is a first version of something similar on a separate branch called "classifier_pretrain". The goal with this branch was to bootstrap training by first training the network as a classifier and after convergence swapping the last fully connected layer with one that maps the output from the network to an embedding, trained using triplet loss. But this code is quite untested yet, but it would be nice to merge the two ways of training into one if it doesn't mess up the code too much.
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rasmushaglund
commented on May 1, 2024
Ok cool, I'll check that out and see if I could make something out of it. I guess it could be a good example to include in facenet.
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