| from models.networks.modules import * | |
| class BaseNet(nn.Module): | |
| def __init__(self, in_channels=1, out_channels=1, norm=True): | |
| super(BaseNet, self).__init__() | |
| self.n_channels = in_channels | |
| self.n_classes = out_channels | |
| self.inc = DoubleConv(in_channels, 32, norm=norm) | |
| self.down1 = Down(32, 64, norm=norm) | |
| self.down2 = Down(64, 128, norm=norm) | |
| self.down3 = Down(128, 128, norm=norm) | |
| self.up1 = Up(256, 64, bilinear=True, norm=norm) | |
| self.up2 = Up(128, 32, bilinear=True, norm=norm) | |
| self.up3 = Up(64, 32, bilinear=True, norm=norm) | |
| self.outc = OutConv(32, out_channels) | |
| def forward(self, x): | |
| x1 = self.inc(x) | |
| x2 = self.down1(x1) | |
| x3 = self.down2(x2) | |
| x4 = self.down3(x3) | |
| x = self.up1(x4, x3) | |
| x = self.up2(x, x2) | |
| x = self.up3(x, x1) | |
| logits = self.outc(x) | |
| return logits | |
| class IAN(BaseNet): | |
| def __init__(self, in_channels=1, out_channels=1, norm=True): | |
| super(IAN, self).__init__(in_channels, out_channels, norm) | |
| class ANSN(BaseNet): | |
| def __init__(self, in_channels=1, out_channels=1, norm=True): | |
| super(ANSN, self).__init__(in_channels, out_channels, norm) | |
| self.outc = OutConv(32, out_channels, act=False) | |
| class FuseNet(nn.Module): | |
| def __init__(self, in_channels=1, out_channels=1, norm=False): | |
| super(FuseNet, self).__init__() | |
| self.inc = AttentiveDoubleConv(in_channels, 32, norm=norm, leaky=False) | |
| self.down1 = AttentiveDown(32, 64, norm=norm, leaky=False) | |
| self.down2 = AttentiveDown(64, 64, norm=norm, leaky=False) | |
| self.up1 = AttentiveUp(128, 32, bilinear=True, norm=norm, leaky=False) | |
| self.up2 = AttentiveUp(64, 32, bilinear=True, norm=norm, leaky=False) | |
| self.outc = OutConv(32, out_channels) | |
| def forward(self, x): | |
| x1 = self.inc(x) | |
| x2 = self.down1(x1) | |
| x3 = self.down2(x2) | |
| x = self.up1(x3, x2) | |
| x = self.up2(x, x1) | |
| logits = self.outc(x) | |
| return logits | |
| if __name__ == '__main__': | |
| for key in FuseNet(4, 2).state_dict().keys(): | |
| print(key) | |