You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
There are several instances in the test suite which create keras_preprocessing.image.ImageDataGenerator instances where both zca_whitening and featurewise_std_normalization are set to True, for example:
However, when zca_whitening is set, featurewise_std_normalization is ignored.
Is there a preference for one config over the other? For example, if zca_whitening is preferred, we could simply set featurewise_std_normalization to False or vice-versa. Alternatively if both states are important, we could parametrize on these configs.
The text was updated successfully, but these errors were encountered:
There are several instances in the test suite which create
keras_preprocessing.image.ImageDataGenerator
instances where bothzca_whitening
andfeaturewise_std_normalization
are set toTrue
, for example:deepcell-tf/deepcell/image_generators/image_generators_test.py
Lines 484 to 490 in 17b54eb
However, when
zca_whitening
is set,featurewise_std_normalization
is ignored.Is there a preference for one config over the other? For example, if
zca_whitening
is preferred, we could simply setfeaturewise_std_normalization
to False or vice-versa. Alternatively if both states are important, we could parametrize on these configs.The text was updated successfully, but these errors were encountered: