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README.md

@@ -10,8 +10,8 @@ library_name: pytorch
 
 ## Model Description
 Custom UNet model for Pix2Pix image translation.
-- **Image Size:** 256
-- **Model Type:** Small (256)
+- **Image Size:** 1024
+- **Model Type:** Big (1024)
 
 ## Usage
 
@@ -36,13 +36,21 @@ UNet(
     (3): ReLU(inplace=True)
     (4): Conv2d(128, 256, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1))
     (5): ReLU(inplace=True)
+    (6): Conv2d(256, 512, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1))
+    (7): ReLU(inplace=True)
+    (8): Conv2d(512, 1024, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1))
+    (9): ReLU(inplace=True)
   )
   (decoder): Sequential(
-    (0): ConvTranspose2d(256, 128, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1))
+    (0): ConvTranspose2d(1024, 512, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1))
     (1): ReLU(inplace=True)
-    (2): ConvTranspose2d(128, 64, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1))
+    (2): ConvTranspose2d(512, 256, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1))
     (3): ReLU(inplace=True)
-    (4): ConvTranspose2d(64, 3, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1))
-    (5): Tanh()
+    (4): ConvTranspose2d(256, 128, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1))
+    (5): ReLU(inplace=True)
+    (6): ConvTranspose2d(128, 64, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1))
+    (7): ReLU(inplace=True)
+    (8): ConvTranspose2d(64, 3, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1))
+    (9): Tanh()
   )
 )