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I can run the estimate_plausible_tags function just fine- the model seems to be working, but calling extract_feature or extract_binary_feature returns KeyError: 'encode1'
looking in to it a little, it seems the error was generated as the output of : feature = self._extract(imgs, layername='encode1')
and in the illust2vec model, the layers are only iterations of convX_Y, reluX_Y, and poolX.
Passing actual layer names doesn't seem to get rid of the error or produce any results so I'm lost with this...
On windows, chainer is v5.2
The text was updated successfully, but these errors were encountered:
Had the same issue, using illust2vec_ver200.caffemodel instead of illust2vec_tag_ver200.caffemodel when creating illust2vec solved the problem.
This is also demonstrated in how to use, yet it is easy to unsee.
I can run the estimate_plausible_tags function just fine- the model seems to be working, but calling extract_feature or extract_binary_feature returns
KeyError: 'encode1'
looking in to it a little, it seems the error was generated as the output of :
feature = self._extract(imgs, layername='encode1')
and in the illust2vec model, the layers are only iterations of convX_Y, reluX_Y, and poolX.
Passing actual layer names doesn't seem to get rid of the error or produce any results so I'm lost with this...
On windows, chainer is v5.2
The text was updated successfully, but these errors were encountered: