REVA-QCAV/unet/unet_model.py
milesial 7ea54febec Added CLI for predict, cleaned up code, updated README
Former-commit-id: 77555ccc0925a8fba796ce7e42843d95b6e9dce0
2017-11-30 06:45:19 +01:00

38 lines
986 B
Python

#!/usr/bin/python
# full assembly of the sub-parts to form the complete net
import torch
import torch.nn as nn
import torch.nn.functional as F
# python 3 confusing imports :(
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