Update app.py

app.py

@@ -1,22 +1,12 @@
+
 import gradio as gr
 from transformers import pipeline
 
 
-
 def classify_sentiment(audio, model):
   pipe = pipeline("audio-classification", model=model)
-  sentiment_classifier = pipe(audio)
-  return sentiment_classifier
-
-#def classify_sentiment(audio, model):
-  #pipe = pipeline("audio-classification", model=model)
-  #sentiment_classifier = pipe(audio)
-  
-  #preds_dict={}
-  #for sentiment_classifier in preds[0]:
-      #preds_dict[pred['label']] = pred['score']
-
-  return preds_dict
+  pred = pipe(audio)
+  return {dic["label"]: dic["score"] for dic in pred}
 
 input_audio = [gr.inputs.Audio(source="microphone", type="filepath", label="Record/ Drop audio"), gr.inputs.Dropdown(["DrishtiSharma/wav2vec2-base-finetuned-sentiment-mesd-v11", "hackathon-pln-es/wav2vec2-base-finetuned-sentiment-mesd"], label="Model Name")]
 label = gr.outputs.Label(num_top_classes=5)
@@ -27,3 +17,4 @@ gr.Interface(
     outputs = label,
     #examples=[["test1.wav", "DrishtiSharma/wav2vec2-base-finetuned-sentiment-mesd-v11"], ["test2.wav", "hackathon-pln-es/wav2vec2-base-finetuned-sentiment-mesd"]],
     theme="grass").launch()
+