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fix tfile naming

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Max Bain
2023-03-30 19:24:42 +01:00
parent ae4a9de307
commit d0fa028045
1 changed files with 9 additions and 10 deletions
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19
whisperx/transcribe.py
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@ -45,8 +45,8 @@ def cli():
# vad params
parser.add_argument("--vad_filter", action="store_true", help="Whether to pre-segment audio with VAD, highly recommended! Produces more accurate alignment + timestamp see WhisperX paper https://arxiv.org/abs/2303.00747")
parser.add_argument("--vad_onset", type=float, default=0.767, help="Onset threshold for VAD (see pyannote.audio)")
parser.add_argument("--vad_offset", type=float, default=0.363, help="Offset threshold for VAD (see pyannote.audio).")
parser.add_argument("--vad_onset", type=float, default=0.500, help="Onset threshold for VAD (see pyannote.audio), reduce this if speech is not being detected")
parser.add_argument("--vad_offset", type=float, default=0.363, help="Offset threshold for VAD (see pyannote.audio), reduce this if speech is not being detected.")
# diarization params
parser.add_argument("--diarize", action="store_true", help="Apply diarization to assign speaker labels to each segment/word")
@ -75,6 +75,7 @@ def cli():
parser.add_argument("--hf_token", type=str, default=None, help="Hugging Face Access Token to access PyAnnote gated models")
parser.add_argument("--model_flush", action="store_true", help="Flush memory from each model after use, reduces GPU requirement but slower processing >1 audio file.")
parser.add_argument("--tmp_dir", default=None, help="Temporary directory to write audio file if input if not .wav format (only for VAD).")
# fmt: on
args = parser.parse_args().__dict__
@ -146,23 +147,21 @@ def cli():
writer = get_writer(output_format, output_dir)
for audio_path in args.pop("audio"):
input_audio_path = audio_path
if vad_model is not None:
if not audio_path.endswith(".wav"):
print("VAD requires .wav format, converting to wav as a tempfile...")
tfile = tempfile.NamedTemporaryFile(delete=True, suffix=".wav")
ffmpeg.input(audio_path, threads=0).output(tfile.name, ac=1, ar=SAMPLE_RATE).run(cmd=["ffmpeg"])
vad_audio_path = tfile.name
else:
vad_audio_path = audio_path
input_audio_path = tfile.name
print("Performing VAD...")
result = transcribe_with_vad(model, vad_audio_path, vad_model, temperature=temperature, **args)
result = transcribe_with_vad(model, input_audio_path, vad_model, temperature=temperature, **args)
if tfile is not None:
tfile.close()
else:
print("Performing transcription...")
result = transcribe(model, audio_path, temperature=temperature, **args)
result = transcribe(model, input_audio_path, temperature=temperature, **args)
if align_model is not None:
if result["language"] != align_metadata["language"]:
@ -170,11 +169,11 @@ def cli():
print(f"New language found ({result['language']})! Previous was ({align_metadata['language']}), loading new alignment model for new language...")
align_model, align_metadata = load_align_model(result["language"], device)
result = align(result["segments"], align_model, align_metadata, audio_path, device,
result = align(result["segments"], align_model, align_metadata, input_audio_path, device,
extend_duration=align_extend, start_from_previous=align_from_prev, interpolate_method=interpolate_method)
# if diarize_model is not None:
# diarize_segments = diarize_model(audio_path, min_speakers=min_speakers, max_speakers=max_speakers)
# diarize_segments = diarize_model(input_audio_path, min_speakers=min_speakers, max_speakers=max_speakers)
# results_segments, word_segments = assign_word_speakers(diarize_segments, )
writer(result, audio_path)