2017-11-30 05:45:19 +00:00
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# full assembly of the sub-parts to form the complete net
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2018-11-10 22:42:16 +00:00
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import torch.nn.functional as F
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2017-11-30 05:45:19 +00:00
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from .unet_parts import *
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2017-08-16 12:24:29 +00:00
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class UNet(nn.Module):
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def __init__(self, n_channels, n_classes):
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super(UNet, self).__init__()
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self.inc = inconv(n_channels, 64)
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self.down1 = down(64, 128)
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self.down2 = down(128, 256)
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self.down3 = down(256, 512)
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2017-08-17 13:33:47 +00:00
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self.down4 = down(512, 512)
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self.up1 = up(1024, 256)
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self.up2 = up(512, 128)
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self.up3 = up(256, 64)
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2017-08-16 12:24:29 +00:00
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self.up4 = up(128, 64)
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self.outc = outconv(64, n_classes)
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def forward(self, x):
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x1 = self.inc(x)
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x2 = self.down1(x1)
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x3 = self.down2(x2)
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x4 = self.down3(x3)
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x5 = self.down4(x4)
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x = self.up1(x5, x4)
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x = self.up2(x, x3)
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x = self.up3(x, x2)
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x = self.up4(x, x1)
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x = self.outc(x)
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2018-11-10 22:42:16 +00:00
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return F.sigmoid(x)
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