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Correct me if I get it wrong. Accoring to c8e496f, now the array is in shape of [n_samples, n_features], just like scikit-learn or other python packages. So,
One column per data vector (e.g. a SIFT descriptor)
I think you mean
One row per data vector (e.g. a SIFT descriptor)
And there are some inconsistent usage, say vlad, when I update the commits from it use different array ordering. Now we have two different array ordering, which will make users confused. We need to make it consistent.
The text was updated successfully, but these errors were encountered:
As you can see from #20 there was a lot of discussion about which ordering was the "right" ordering. And for the fisher module it was agreed in that PR that the [n_samples, n_features] was appropriate for the underlying call to vlfeat.
Obviously it would be best to standardize this and test that the underlying modules actually act correctly - but this is beyond my personal scope as I don't use any of the modules recently contributed. Again - happy to try and generally review and cut releases but don't have the scope to actually make this wrapper feature complete.
Correct me if I get it wrong. Accoring to c8e496f, now the array is in shape of
[n_samples, n_features]
, just like scikit-learn or other python packages. So,cyvlfeat/cyvlfeat/fisher/fisher.py
Lines 16 to 17 in 102ba95
I think you mean
And there are some inconsistent usage, say
vlad
, when I update the commits from it use different array ordering. Now we have two different array ordering, which will make users confused. We need to make it consistent.The text was updated successfully, but these errors were encountered: