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Update asr.py
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@ -247,7 +247,7 @@ class FasterWhisperPipeline(Pipeline):
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return final_iterator
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def transcribe(
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self, audio: Union[str, np.ndarray], batch_size=None, num_workers=0, language=None, task=None
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self, audio: Union[str, np.ndarray], batch_size=None, num_workers=0, language=None, task=None, print_progress = False
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) -> TranscriptionResult:
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if isinstance(audio, str):
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audio = load_audio(audio)
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@ -287,8 +287,9 @@ class FasterWhisperPipeline(Pipeline):
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batch_size = batch_size or self._batch_size
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total_segments = len(vad_segments)
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for idx, out in enumerate(self.__call__(data(audio, vad_segments), batch_size=batch_size, num_workers=num_workers)):
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percent_complete = ((idx + 1) / total_segments) * 100
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print(f"Progress: {percent_complete:.2f}%...")
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if print_progress:
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percent_complete = ((idx + 1) / total_segments) * 100
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print(f"Progress: {percent_complete:.2f}%...")
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text = out['text']
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if batch_size in [0, 1, None]:
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text = text[0]
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