@shivam2298 Thanks for replying.
What i basically follow.
For semantic segmentation, if you have only one label then you can just have a label map where at each pixel you have a 1 where the object of interest is and 0s everywhere else. If you have >1 label of interest, you should use one hot encoding to generate your label map.
(Please provide the important info that i am lacking)
So in this please explain what actually is happening in the last layer of the decoder as we r using cross entropy loss.
What i basically understand is if we have multiclass then each dimesion holds like… For the first layer of that dimension I would have ones for each pixel that belongs to class 1, for layer 2 I would have ones at all of the pixels that belong to class 2, etc. etc.