aopp

app.py

@@ -10,28 +10,26 @@ model_path = "origin-classifier-stage-2.pkl"
 dls_path = "dls_origin-classifier_v1.pkl"
 
 learner_inf = load_learner(model_path)
-
-
 dls = torch.load(dls_path)
 
-
 class_label_mapping = {label: idx for idx, label in enumerate(learner_inf.dls.vocab)}
 
-
 def predict_text(text):
     prediction = learner_inf.blurr_predict(text)[0]
     predicted_class_index = prediction['class_index']
     predicted_class_label = list(class_label_mapping.keys())[list(class_label_mapping.values()).index(predicted_class_index)]
     predicted_class_probability = prediction['probs'][predicted_class_index]
-    return f"Label: {predicted_class_label}, Probability: {predicted_class_probability * 100:.2f}%"
+    return {"Label": predicted_class_label, "Probability": predicted_class_probability}
 
 iface = gr.Interface(
     fn=predict_text,
     inputs="text",
-    outputs="text",
+    outputs=[
+        gr.outputs.Textbox(label="Label"),
+        gr.outputs.Label(num_top_classes=1, type="confidences", label="Probability")
+    ],
     title="Food Origin Classification App",
     description="Enter a Recipe, and it will predict the class label.",
 )
 
-
 iface.launch()