Update app.py

app.py

@@ -69,21 +69,6 @@ def predict_image(image):
                 transforms.ToTensor(), 
                 transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
                 ])
-<<<<<<< HEAD
-=======
-        classes = ('Speed limit (20km/h)',
-                'Speed limit (30km/h)', 
-                'Speed limit (50km/h)', 
-                'Speed limit (60km/h)', 
-                'Speed limit (70km/h)', 
-                'Speed limit (80km/h)', 
-                'Speed limit (100km/h)', 
-                'Speed limit (120km/h)')
-
-        device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-        model = torch.load('vgg11.pkl')
-        model.eval()
->>>>>>> 45956336369e64e58514a21a6f06f6e9c53a3d42
         image_tensor = test_transforms(image).float()
         image_tensor = image_tensor.unsqueeze_(0)
         with torch.no_grad():