vinhloiit / signet-pytorch Goto Github PK
View Code? Open in Web Editor NEWSigNet implementation in Pytorch
License: MIT License
SigNet implementation in Pytorch
License: MIT License
Please leave the trained model for me, thanks a lot!
我看原论文中模型里所有的最大池化层大小都是33,在这个实现里都是22的,请问有没有试验过两种哪个性能好呢?
The last layer is 256, but the SigNet paper specifies 128.
(Note: the network trains much more quickly with 128.)
You implement loss = self.alpha * (1-y) * distance**2 + \ self.beta * y * (torch.max(torch.zeros_like(distance), self.margin - distance)**2)
as your contrastive loss, however, in your dataset split and preprocessing script, you label (genuine, genuine) as 1 and (genuine,forged) as 0, which means when y=0, your loss = alpha * distance between pairs and it will be minimized, but hopefully they should be as far as possible.
loss = self.alpha * y * distance**2 + \ self.beta * (1-y) * (torch.max(torch.zeros_like(distance), self.margin - distance)**2)
would be a correct implementation.
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