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Hi, I managed to train and test the Bayesian SegNet model with the default number of classes on the CamVid dataset (11). Now I'd like to train that on only 2 classes (path/background + ignore) which I managed to get working with standard SegNet by simply changing the output size.
Now when I perform training on Bayesian SegNet using CamVid, I get a solid score for each class plus low values of the loss function, so the network seems to train as it should. Now when I run the script test_bayesian_segnet.py, the entire output is saturated to class 1.0 but works fine for the original number of classes (11).
Any help is appreciated!
Regards, Filip
The text was updated successfully, but these errors were encountered:
Hi, I managed to train and test the Bayesian SegNet model with the default number of classes on the CamVid dataset (11). Now I'd like to train that on only 2 classes (path/background + ignore) which I managed to get working with standard SegNet by simply changing the output size.
Now when I perform training on Bayesian SegNet using CamVid, I get a solid score for each class plus low values of the loss function, so the network seems to train as it should. Now when I run the script test_bayesian_segnet.py, the entire output is saturated to class 1.0 but works fine for the original number of classes (11).
Any help is appreciated!
Regards, Filip
The text was updated successfully, but these errors were encountered: