Chose best ultralytics#19 version

models/common.py

@@ -850,20 +850,24 @@ def forward(self, x):
 class Seg(nn.Module):
 
     def __init__(self, in_channels):
+
         super().__init__()
-        self.cv1 = Conv(in_channels, 96, k=3)
+        self.cv1 = Conv(in_channels, 32, k=3)
+        self.cv11 = Conv(96, 32, k=3)
+
         self.upsample = nn.Upsample(scale_factor=2, mode='nearest')
-        self.cv2 = Conv(192, 48, k=3)
-        self.cv3 = Conv(48, 16, k=3)
+        self.cv2 = Conv(64, 32, k=3)
+        self.cv3 = Conv(32, 16, k=3)
         self.cv4 = Conv(16, 1, act=False)
         self.relu = nn.ReLU()
-
         self.dropout_normal = nn.Dropout(0.5)
 
     def forward(self, x, skipped_input):
+
         x = self.cv1(x)
         x = self.upsample(x)
-        x = torch.cat((x, skipped_input[0]), 1)  # Skip connection
+        x2 = self.cv11(skipped_input[0])
+        x = torch.cat((x, x2), 1)  # Skip connection
 
         x = self.cv2(x)
         x = self.upsample(x)