changed to a single function

app.py

@@ -6,7 +6,7 @@ import os
 
 #%%
 whisper = pipeline(model='jlvdoorn/whisper-large-v2-atco2-asr-atcosim', use_auth_token=os.environ['HUGGINGFACE_TOKEN'])
-bert_atco_ner = pipeline(model='Jzuluaga/bert-base-ner-atc-en-atco2-1h')
+# bert_atco_ner = pipeline(model='Jzuluaga/bert-base-ner-atc-en-atco2-1h')
 
 #%%
 def transcribe(audio_mic, audio_file):
@@ -18,38 +18,38 @@ def transcribe(audio_mic, audio_file):
         return 'There was no audio to transcribe...'
 
 #%%
-def extractCallSignCommand(transcription):
-    if type(transcription) is str:
-        result = bert_atco_ner(transcription)
-        callsigns = []
-        commands = []
-        values = []
-        for item in result:
-            if 'callsign' in item['entity']:
-                callsigns.append(item['word'])
-            if 'command' in item['entity']:
-                commands.append(item['word'])
-            if 'value' in item['entity']:
-                values.append(item['word'])
+# def extractCallSignCommand(transcription):
+#     if type(transcription) is str:
+#         result = bert_atco_ner(transcription)
+#         callsigns = []
+#         commands = []
+#         values = []
+#         for item in result:
+#             if 'callsign' in item['entity']:
+#                 callsigns.append(item['word'])
+#             if 'command' in item['entity']:
+#                 commands.append(item['word'])
+#             if 'value' in item['entity']:
+#                 values.append(item['word'])
                 
-        return 'Callsigns: ' + ', '.join(callsigns) + '\nCommands: ' + ', '.join(commands) + '\nValues: ' + ', '.join(values)
-    else:
-        return 'There was no transcription to extract a callsign or command from...'
+#         return 'Callsigns: ' + ', '.join(callsigns) + '\nCommands: ' + ', '.join(commands) + '\nValues: ' + ', '.join(values)
+#     else:
+#         return 'There was no transcription to extract a callsign or command from...'
 
 #%%
-def transcribeAndExtract(audio_mic, audio_file, transcribe_only):
-    transcription = transcribe(audio_mic, audio_file)
-    if not transcribe_only:
-        callSignCommandValues = extractCallSignCommand(transcription)
-    else:
-        callSignCommandValues = ''
-    return transcription, callSignCommandValues
+# def transcribeAndExtract(audio_mic, audio_file, transcribe_only):
+#     transcription = transcribe(audio_mic, audio_file)
+#     if not transcribe_only:
+#         callSignCommandValues = extractCallSignCommand(transcription)
+#     else:
+#         callSignCommandValues = ''
+#     return transcription, callSignCommandValues
 
 #%%
 iface = gr.Interface(
-        fn=transcribeAndExtract,
-        inputs=[gr.Audio(source='microphone', type='filepath'), gr.Audio(source='upload', type='filepath'), gr.Checkbox(label='Transcribe only', default=False)],
-        outputs=[gr.Text(label='Transcription'), gr.Text(label='Callsigns, commands and values')],
+        fn=transcribe,
+        inputs=[gr.Audio(source='microphone', type='filepath'), gr.Audio(source='upload', type='filepath')],
+        outputs=gr.Text(label='Transcription'),
         title='Whisper Large v2 - ATCO2-ASR-ATCOSIM',
         description='This demo will transcribe ATC audio files by using the Whisper Large v2 model fine-tuned on the ATCO2 and ATCOSIM datasets. Further it uses a Named Entity Recognition model to extract callsigns, commands and values from the transcription. This model is based on Google\'s BERT model and fine-tuned on the ATCO2 dataset.',
 )