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app.py

@@ -16,7 +16,7 @@ class_names = ['CRVO',
   'Macular Hole',
   'Myelinated Nerve Fiber',
   'Normal',
-  'Pathological Mypoia',
+  'Pathological Myopia',
   'Retinitis Pigmentosa']
 
 ### 2. Model and transforms preparation ###
@@ -25,7 +25,6 @@ class_names = ['CRVO',
 resnet50, resnet50_transforms = create_resnet50_model(
     num_classes=len(class_names), # actual value would also work
 )
-resnet50.fc = nn.Linear(2048, 10)
 
 # Load saved weights
 resnet50.load_state_dict(

model.py

@@ -20,7 +20,6 @@ def create_resnet50_model(num_classes:int=10, # 4
     weights = torchvision.models.ResNet50_Weights.DEFAULT
     transforms = weights.transforms()
     model = torchvision.models.resnet50(weights=weights)
-    model.fc = nn.Linear(2048, 10)
 
     # 4. Freeze all layers in base model
     for param in model.parameters():