Just wondering if anyone has an example of Unet for binary segmentation using BCEWithLogitsLoss ?
I’m segmenting foreground vs background and there are many more 0s than 1s due to this. It looks like i should be using BCEWithLogitsLoss as my loss function, however using fastai this doesnt plug and play super well.
Do i need to define a new Unet to work with this loss function?
Also, this might be out of scope of this forum so i can ask on pytorch too, but it looks like this function takes as an argument the proportion of class imbalance - “pos_weight (Tensor, optional) – a weight of positive examples. Must be a vector with length equal to the number of classes.”
Does that mean i need to know across all my images how many pixels are 1 v 0