aopp

app.py

@@ -21,15 +21,16 @@ class_label_mapping = {label: idx for idx, label in enumerate(learner_inf.dls.vo
 # Define a function to make predictions
 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)]
-    return predicted_class_label
+    predicted_probs = prediction['scores']
+    predicted_labels = prediction['class_labels']
+    result = {label: f"{prob*100:.2f}%" for label, prob in zip(predicted_labels, predicted_probs)}
+    return result
 
 # Create a Gradio interface
 iface = gr.Interface(
     fn=predict_text,
     inputs="text",
-    outputs="text",
+    outputs="label",
     title="Food Origin Classification App",
     description="Enter a Recipe, and it will predict the class label.",
 )