Add progress bar

app.py

@@ -14,7 +14,7 @@ model_id = "facebook/mms-1b-all"
 processor = AutoProcessor.from_pretrained(model_id)
 model = Wav2Vec2ForCTC.from_pretrained(model_id)
 
-def transcribe(audio_file_mic=None, audio_file_upload=None, language="English (eng)"):
+def transcribe(audio_file_mic=None, audio_file_upload=None, language="English (eng)", progress=gr.Progress()):
     if audio_file_mic:
         audio_file = audio_file_mic
     elif audio_file_upload:
@@ -22,10 +22,12 @@ def transcribe(audio_file_mic=None, audio_file_upload=None, language="English (e
     else:
         return "Please upload an audio file or record one"
 
+    progress(0, desc="Starting")
+
     # Make sure audio is 16kHz
     speech, sample_rate = librosa.load(audio_file)
     if sample_rate != 16000:
-        print('resampling')
+        progress(1, desc="Resampling")
         speech = librosa.resample(speech, orig_sr=sample_rate, target_sr=16000)
 
     # Cut speech into chunks
@@ -38,7 +40,8 @@ def transcribe(audio_file_mic=None, audio_file_upload=None, language="English (e
     model.load_adapter(language_code)
 
     transcriptions = []
-    for chunk in chunks:
+    progress(2, desc="Transcribing")
+    for chunk in progress.tqdm(chunks, desc="Transcribing"):
         inputs = processor(chunk, sampling_rate=16_000, return_tensors="pt")
 
         with torch.no_grad():