From b75a2e1f2f5e95a104df29162102d10643e93684 Mon Sep 17 00:00:00 2001
From: "s.islam" <s.islam@fz-juelich.de>
Date: Thu, 5 May 2022 14:48:54 +0200
Subject: [PATCH] REPORT-7: Ch:1, resnet152, L1
---
code/model_Unet.py | 4 ++--
1 file changed, 2 insertions(+), 2 deletions(-)
diff --git a/code/model_Unet.py b/code/model_Unet.py
index 8f0bdfb..e25c863 100644
--- a/code/model_Unet.py
+++ b/code/model_Unet.py
@@ -31,13 +31,13 @@ class TestModule(pl.LightningModule):
# Define the model
self.model = smp.Unet(
- encoder_name="resnet34", # Also consider using smaller or larger encoders
+ encoder_name="resnet152", # Also consider using smaller or larger encoders
encoder_weights= "imagenet", # Do the pretrained weights help? Try with or without
in_channels=1, # We use 1 chanel transmittance as input
classes=1, # classes == output channels. We use one output channel for cyto data
activation="sigmoid"
)
- self.loss_f = RMILoss(with_logits=True) #torch.nn.L1Loss() #RMILoss(with_logits=True) #torch.nn.MSELoss()
+ self.loss_f = torch.nn.L1Loss() #torch.nn.L1Loss() #RMILoss(with_logits=True) #torch.nn.MSELoss()
def forward(self, x):
x = self.model(x)
--
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