Upload app.py

app.py

@@ -80,13 +80,13 @@ def fn(glycan, model):
     pred = np.exp(pred)/sum(np.exp(pred)) # Softmax 
     pred = [float(x) for x in pred]
     pred = {class_list[i]:pred[i] for i in range(15)}
-    return pred, "graph.png"
+    return pred
 
 
 demo = gr.Interface(
     fn=fn,
     inputs=[gr.Textbox(label="Glycan sequence"), gr.Radio(label="Model",choices=["No data augmentation", "Random node deletion", "Ensemble"])],
-    outputs=[gr.Label(num_top_classes=15, label="Prediction"), gr.Image(label="Graph visualization")],
+    outputs=[gr.Label(num_top_classes=15, label="Prediction")],
     allow_flagging=False,
     title="SweetNet demo",
     examples=[["GlcOSN(a1-4)GlcA(b1-4)GlcOSN(a1-4)GlcAOS(b1-4)GlcOSN(a1-4)GlcOSN", "No data augmentation"],