How to implement weighted Cross Entropy Loss for lane marking segmentation

[KFrank]

Hi Fikrat!

@Fikrat

Therefore, my target is to implement Weighted Cross Entropy Loss, aiming at providing more weights to colourful pixels, rather than black pixels.

If your problem is one a binary segmentation, presumably
black = background, color = foreground, then you should use
BCEWithLogitsLoss and the pos_weight argument that you
pass to its constructor.

If it’s multi-class segmentation, e.g., black = background, some
colors or patterns = lane 1, some other colors or patterns = lane 2,
etc., then you should use CrossEntropyLoss and the weight
argument passed to its constructor.

Best.

K. Frank