deleted the comments

main.py

@@ -141,25 +141,21 @@ async def stop_detection():
 @app.post("/upload_audio/")
 async def upload_audio(file: UploadFile = File(...)):
     try:
-        # Read the uploaded file
+
         audio_data = await file.read()
 
-        # Convert the audio file to the appropriate format for processing
         audio_segment = AudioSegment.from_file(io.BytesIO(audio_data), format=file.filename.split('.')[-1])
         wav_io = io.BytesIO()
         audio_segment.export(wav_io, format="wav")
         wav_io.seek(0)
         audio, sr = sf.read(wav_io, dtype='float32')
 
-        # If audio has more than one channel, average them
         if audio.ndim > 1:
             audio = np.mean(audio, axis=1)
 
-        # Extract features
         features = extract_features(audio)
         features = scaler.transform(features.reshape(1, -1))
         
-        # Predict using the loaded model
         prediction = model.predict(features)
         is_fake = prediction[0]
         result = 'fake' if is_fake else 'real'