added changes to app to fix model loading errors

app.py

@@ -33,7 +33,22 @@ model.fc = nn.Linear(model.fc.in_features, 1000)
 model.load_state_dict(torch.load("model.pth", map_location=device))  # Load the trained weights (.pth)
 model.to(device)  # Move model to CPU (even if you have a GPU)
 
-model.eval()  # Set model to evaluation mode
+checkpoint = torch.load('model.pth', map_location='cpu')
+
+# Load the model weights
+model.load_state_dict(checkpoint['model_state_dict'])
+
+# If you need to resume training, load optimizer and scheduler states
+optimizer.load_state_dict(checkpoint['optimizer_state_dict'])
+scheduler.load_state_dict(checkpoint['scheduler_state_dict'])
+
+# If you want to resume from a specific epoch
+epoch = checkpoint['epoch']
+
+# Set the model to evaluation mode (for inference)
+model.eval()
+
+# model.eval()  # Set model to evaluation mode
 
 # Define the transformation required for the input image
 transform = transforms.Compose([