Update app.py

app.py

@@ -96,8 +96,14 @@ from torchvision import transforms
 
 model = load_model()
 
+augs = transforms.Compose([
+    transforms.Resize((224, 224)),
+    transforms.ToTensor()
+])
+
 def predict(inp):
-  inp = transforms.Resize((224, 224))(inp).transforms.ToTensor()(inp).unsqueeze(0)
+  # inp = transforms.Resize((224, 224))(inp).transforms.ToTensor()(inp).unsqueeze(0)
+  inp = augs(inp).unsqueeze(0)
   with torch.no_grad():
     prediction = torch.nn.functional.softmax(model(inp)[0], dim=0)
     confidences = {labels[i]: float(prediction[i]) for i in range(3)}