Hello. I  am rather new to Pytorch (used to work mostly with keras in previous jobs) and I am in need of some help.  I am facing some  issues when I implemented a segmentation model using the u-net from segmentation models
import segmentation_models_pytorch as smp
model_old = smp.Unet(
encoder_name=“resnet34”,
encoder_weights=None,
in_channels=3,
classes=8,
).to(device)
I train the model and it get quite ok results quite fast, but each pixel has always 0 or 1 at the final result. There is no degree of belief/pertinence  of the pixel/area to the class. I really need the degree so I can apply some thresholds.
Is that  expected from an U-NET, is is characteristic from this implementation or should I be doing something different to achieve that? Could any kind soul give me some pointers?