print("! CAUTION ! Slicing audio with whisperx is terrible. Please consider using a different whisper backend if you want to slice audio.")
os.makedirs(f'{outdir}/audio/',exist_ok=True)
os.makedirs(f'{outdir}/audio/',exist_ok=True)
results={}
results={}
@ -1708,7 +1688,7 @@ def setup_args():
parser.add_argument("--output-volume",type=float,default=default_arguments['output-volume'],help="Adjusts volume of output")
parser.add_argument("--output-volume",type=float,default=default_arguments['output-volume'],help="Adjusts volume of output")
parser.add_argument("--autoregressive-model",default=default_arguments['autoregressive-model'],help="Specifies which autoregressive model to use for sampling.")
parser.add_argument("--autoregressive-model",default=default_arguments['autoregressive-model'],help="Specifies which autoregressive model to use for sampling.")
parser.add_argument("--whisper-backend",default=default_arguments['whisper-backend'],action='store_true',help="Picks which whisper backend to use (openai/whisper, lightmare/whispercpp, m-bain/whisperx)")
parser.add_argument("--whisper-backend",default=default_arguments['whisper-backend'],action='store_true',help="Picks which whisper backend to use (openai/whisper, lightmare/whispercpp)")
parser.add_argument("--whisper-model",default=default_arguments['whisper-model'],help="Specifies which whisper model to use for transcription.")
parser.add_argument("--whisper-model",default=default_arguments['whisper-model'],help="Specifies which whisper model to use for transcription.")