Hi,
I have a UNet that does binary semantic segmentation and I wanted to extend it to detect multiple classes. The first idea that I got was to train a model for each class and then when I would do the prediction, I would use a combined model between all pretrained models. Any idea on how to approach this?
Also, if this is not a good idea and if you have a better approach please let me know