reverting to prior to add version choice

app.py

@@ -11,25 +11,14 @@ def get_x(df):
 def get_y(df):
     return df.pattern
    
-learn_removeSilence = load_learner('xresnet50_pitch3_removeSilence.pkl')
+learn = load_learner('xresnet50_pitch3_removeSilence.pkl')
 
-learn_plain = load_learner('xresnet50_pitch3.pkl')
+labels = learn.dls.vocab
 
-labels = learn_removeSilence.dls.vocab
-
-#def process(Record, Upload, version):
- #   if version == 'remove silence':
-  #      return predict(Record, Upload, learn_removeSilence)
-   # elif version == 'plain':
-    #    return predict(Record, Upload, learn_plain)
-
-def predict(Record, Upload, version):
+def predict(Record, Upload):
     if Upload: path = Upload
     else: path = Record
-    if version == 'remove silence':
-        spec,pred,pred_idx,probs = learn_removeSilence.predict(str(path), with_input=True)
-    elif version == 'plain':
-        spec,pred,pred_idx,probs = learn_plain.predict(str(path), with_input=True)
+    spec,pred,pred_idx,probs = learn.predict(str(path), with_input=True)
     fig,ax = plt.subplots(figsize=(16,10))
     show_image(spec, ax=ax)
     ax.invert_yaxis()
@@ -42,16 +31,9 @@ description = "This model will predict the pitch accent pattern of a word based
 
 article="<p style='text-align: center'><a href='https://mizoru.github.io/blog/2021/12/25/Japanese-pitch.html' target='_blank'>How did I make this and what is it for?</a></p>"
 
-ex_paths = ['代わる.mp3'],['大丈夫な.mp3'],['熱くない.mp3'], ['あめー雨.mp3'], ['あめー飴.mp3']
-
-examples = [[path, '', 'remove silence'] for path in ex_paths]
+examples = [['代わる.mp3'],['大丈夫な.mp3'],['熱くない.mp3'], ['あめー雨.mp3'], ['あめー飴.mp3']]
 
 enable_queue=True
 
-gr.Interface(fn=predict,
-inputs=[gr.inputs.Audio(source='microphone', type='filepath', optional=True),
-gr.inputs.Audio(source='upload', type='filepath', optional=True),
-gr.inputs.Radio(choices=['plain','remove silence'], type="value", default='remove silence', label='version')
-],
-outputs=  [gr.outputs.Label(num_top_classes=3), gr.outputs.Image(type="plot", label='Spectrogram')], title=title,description=description,article=article,examples=examples).launch(debug=True, enable_queue=enable_queue)
+gr.Interface(fn=predict,inputs=[gr.inputs.Audio(source='microphone', type='filepath', optional=True), gr.inputs.Audio(source='upload', type='filepath', optional=True)], outputs=  [gr.outputs.Label(num_top_classes=3), gr.outputs.Image(type="plot", label='Spectrogram')], title=title,description=description,article=article,examples=examples).launch(debug=True, enable_queue=enable_queue)