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
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