You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Hi, thanks for your great work. But I have a question here.
emm, when I have a multi classes semantic segmentation task, I can convert the label to one-hot format and do sigmoid to the output of the network then apply nn.BCELoss() to the label and outputs. (Certainly, one-hot + no sigmoid outputs + nn.BCEWithLogitsLoss is also ok), when i do the inference, i just do torch.sigmoid to the outputs of the network and set the thershold as 0.5, then i can get the correct results of semantic segmentation.So may I do the same thing to the lovasz_hinge()? one-hot + no sigmoid outputs + lovasz_hinge?Does that work? And the inference process is same as above?
The text was updated successfully, but these errors were encountered:
Hi, thanks for your great work. But I have a question here.
emm, when I have a multi classes semantic segmentation task, I can convert the label to one-hot format and do sigmoid to the output of the network then apply nn.BCELoss() to the label and outputs. (Certainly, one-hot + no sigmoid outputs + nn.BCEWithLogitsLoss is also ok), when i do the inference, i just do torch.sigmoid to the outputs of the network and set the thershold as 0.5, then i can get the correct results of semantic segmentation.So may I do the same thing to the lovasz_hinge()? one-hot + no sigmoid outputs + lovasz_hinge?Does that work? And the inference process is same as above?
The text was updated successfully, but these errors were encountered: