import torch import torch.nn as nn import torch.nn.functional as F from unet_parts import * class UNet(nn.Module): def __init__(self, n_channels, n_classes): super(UNet, self).__init__() self.inc = inconv(n_channels, 64) self.down1 = down(64, 128) self.down2 = down(128, 256) self.down3 = down(256, 512) self.down4 = down(512, 512) self.up1 = up(1024, 256) self.up2 = up(512, 128) self.up3 = up(256, 64) self.up4 = up(128, 64) self.outc = outconv(64, n_classes) def forward(self, x): x1 = self.inc(x) x2 = self.down1(x1) x3 = self.down2(x2) x4 = self.down3(x3) x5 = self.down4(x4) x = self.up1(x5, x4) x = self.up2(x, x3) x = self.up3(x, x2) x = self.up4(x, x1) x = self.outc(x) return x