nice work！
I obtained good results using a private dataset for a four-class classification [0,100,200,255]. However, I encountered a puzzling issue. When I used the command "pymic_nll test config/unet_trinet.cfg" to run the test set, the generated pred_mask values are not only [0,100,200,255], but essentially include all values from 0 to 255.
I am certain that I used four-class classification during my training and I can see the Dice coefficient for each class.
nice work！
I obtained good results using a private dataset for a four-class classification [0,100,200,255]. However, I encountered a puzzling issue. When I used the command "pymic_nll test config/unet_trinet.cfg" to run the test set, the generated pred_mask values are not only [0,100,200,255], but essentially include all values from 0 to 255.
I am certain that I used four-class classification during my training and I can see the Dice coefficient for each class.