fix resnet mismatch

app.py

@@ -11,8 +11,8 @@ class MyCarClassifier(torch.nn.Module):
     def __init__(self, num_classes=196):  # Stanford Cars has 196 classes
         super(MyCarClassifier, self).__init__()
         # Example: replace with your actual model architecture
-        from torchvision.models import resnet18
-        self.model = resnet18(pretrained=False)
+        from torchvision.models import resnet50
+        self.model = resnet50(pretrained=False)
         self.model.fc = torch.nn.Linear(self.model.fc.in_features, num_classes)
     
     def forward(self, x):
@@ -22,7 +22,7 @@ class MyCarClassifier(torch.nn.Module):
 # 2. Load model weights
 # --------------------------
 model = MyCarClassifier()
-model.load_state_dict(torch.load("best_stanford_cars_transfer_model.pth", map_location="cpu"), strict=False)
+model.load_state_dict(torch.load("best_stanford_cars_transfer_model.pth", map_location="cpu"), strict=True)
 model.eval()  # important for inference
 
 # --------------------------