Open LLLLLLoki opened 4 years ago
def forward(self,input, target): ''' input: [N, C] target: [N, ] ''' prob = torch.softmax(input, dim=1) prob = torch.gather(prob, dim=1, index=target.unsqueeze(1)) dsc_i = 1 - ((1 - prob) * prob) / ((1 - prob) * prob + 1) dice_loss = dsc_i.mean() return dice_loss
论文中是 DSC(Xi)= (2(1-p)p*y + r)/((1-p)p + y +r)
代码中没看到用diceloss呀,只有focalloss 和label smoothing.
论文中是 DSC(Xi)= (2(1-p)p*y + r)/((1-p)p + y +r)