jhj0517 commited on
Commit
f51bcba
·
1 Parent(s): 08d7176

disable redundant torchvision warning message

Browse files
modules/diarize/diarize_pipeline.py CHANGED
@@ -1,10 +1,14 @@
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  import numpy as np
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  import pandas as pd
 
 
 
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  from pyannote.audio import Pipeline
 
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  from typing import Optional, Union
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  import torch
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- import whisperx
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- import os
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  class DiarizationPipeline:
@@ -25,10 +29,10 @@ class DiarizationPipeline:
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  def __call__(self, audio: Union[str, np.ndarray], min_speakers=None, max_speakers=None):
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  if isinstance(audio, str):
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- audio = whisperx.load_audio(audio)
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  audio_data = {
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  'waveform': torch.from_numpy(audio[None, :]),
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- 'sample_rate': whisperx.audio.SAMPLE_RATE
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  }
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  segments = self.model(audio_data, min_speakers=min_speakers, max_speakers=max_speakers)
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  diarize_df = pd.DataFrame(segments.itertracks(yield_label=True), columns=['segment', 'label', 'speaker'])
 
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  import numpy as np
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  import pandas as pd
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+ import sys
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+ import os
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+ sys.stderr = open(os.devnull, 'w')
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  from pyannote.audio import Pipeline
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+ sys.stderr.close()
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  from typing import Optional, Union
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  import torch
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+
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+ from modules.diarize.audio_loader import load_audio, SAMPLE_RATE
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  class DiarizationPipeline:
 
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  def __call__(self, audio: Union[str, np.ndarray], min_speakers=None, max_speakers=None):
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  if isinstance(audio, str):
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+ audio = load_audio(audio)
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  audio_data = {
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  'waveform': torch.from_numpy(audio[None, :]),
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+ 'sample_rate': SAMPLE_RATE
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  }
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  segments = self.model(audio_data, min_speakers=min_speakers, max_speakers=max_speakers)
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  diarize_df = pd.DataFrame(segments.itertracks(yield_label=True), columns=['segment', 'label', 'speaker'])