dd

app.py

@@ -16,7 +16,7 @@ def predict(inp):
   img = transforms.ToTensor()(inp)
   img = torchvision.transforms.Resize((800, 800))(img)
   img = torchvision.transforms.CenterCrop(CROP)(img)
-  img = img..unsqueeze(0)
+  img = img.unsqueeze(0)
   with torch.no_grad():
     prediction = torch.nn.functional.softmax(model(img)[0], dim=0)
     confidences = {labels[i]: float(prediction[i]) for i in range(2)}