Delete model.py

model.py

@@ -1,25 +0,0 @@
-import torch
-import torch.nn as nn
-
-class UNet(nn.Module):
-    def __init__(self, in_channels=3, out_channels=1):
-        super(UNet, self).__init__()
-        # Definição simplificada da UNet
-        self.enc1 = nn.Sequential(
-            nn.Conv2d(in_channels, 64, kernel_size=3, padding=1),
-            nn.ReLU(),
-            nn.Conv2d(64, 64, kernel_size=3, padding=1),
-            nn.ReLU()
-        )
-        self.pool = nn.MaxPool2d(2)
-        self.dec1 = nn.Sequential(
-            nn.ConvTranspose2d(64, 64, kernel_size=2, stride=2),
-            nn.ReLU(),
-            nn.Conv2d(64, out_channels, kernel_size=1)
-        )
-
-    def forward(self, x):
-        x1 = self.enc1(x)
-        x2 = self.pool(x1)
-        x3 = self.dec1(x2)
-        return x3