add easy split for label and probability

app.py

@@ -35,6 +35,6 @@ def predict(image):
         top_prob, top_idx = probs.topk(1, dim=1)
         idx_to_class = {v:k for k,v in classes.items()}
         label = idx_to_class[top_idx[0][0].item()]
-        return f"{label} ({top_prob[0][0].item()})"
+        return f"{label}|({top_prob[0][0].item()})"
 
 gr.Interface(fn=predict, inputs=gr.Image(type="pil"), outputs="text").launch()