Update app.py

app.py

@@ -25,13 +25,17 @@ def predict(img):
     confidences: python dictionary containing confidences
     '''
     # Transform image to pytorch tensor of shape [1, 3, 224, 224]
+    print(type(img))
     img = T.PILToTensor()(img).unsqueeze(0)
+    print(type(img))
     img = T.Resize(size=(224, 224))(img)
+    print(type(img))
     
     # Use model without gradients to reduce computation
     with torch.no_grad():
         # Get the tensor that contains the predictions
-        prediction = F.softmax(model(img)[0], dim=0)
+        out = model(img)
+        prediction = F.softmax(out[0], dim=0)
         # Turn the above tensor into a dictionary with the humand-readable label and probability.
         confidences = {labels[i]: float(prediction[i]) for i in range(1000)}
 
@@ -41,4 +45,4 @@ gr.Interface(fn=predict,
              inputs=gr.Image(type="pil"),
              outputs=gr.Label(num_top_classes=10),
              theme="default",
-            ).launch()
+            ).launch(share=True)