mirror of
https://github.com/chidiwilliams/buzz.git
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Add Faster Whisper (#400)
This commit is contained in:
Chidi Williams
GitHub
parent
b8073027ce
commit
86626aa818
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@ -10,7 +10,7 @@ OpenAI's [Whisper](https://github.com/openai/whisper).
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[](https://GitHub.com/chidiwilliams/buzz/releases/)
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<blockquote>
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<p>Buzz is better on the App Store. Get a Mac-native version of Buzz with a cleaner look, audio playback, drag-and-drop import, transcript editing, search, and much more for $9.99.</p>
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<p>Buzz is better on the App Store. Get a Mac-native version of Buzz with a cleaner look, audio playback, drag-and-drop import, transcript editing, search, and much more.</p>
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<a href="https://apps.apple.com/us/app/buzz-captions/id6446018936?mt=12&itsct=apps_box_badge&itscg=30200"><img src="https://tools.applemediaservices.com/api/badges/download-on-the-mac-app-store/black/en-us?size=250x83&releaseDate=1679529600" alt="Download on the Mac App Store" /></a>
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</blockquote>
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@ -23,7 +23,7 @@ OpenAI's [Whisper](https://github.com/openai/whisper).
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- Import audio and video files and export transcripts to TXT, SRT, and
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VTT ([Demo](https://www.loom.com/share/cf263b099ac3481082bb56d19b7c87fe))
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- Supports [Whisper](https://github.com/openai/whisper#available-models-and-languages),
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[Whisper.cpp](https://github.com/ggerganov/whisper.cpp),
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[Whisper.cpp](https://github.com/ggerganov/whisper.cpp), [Faster Whisper](https://github.com/guillaumekln/faster-whisper),
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[Whisper-compatible Hugging Face models](https://huggingface.co/models?other=whisper), and
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the [OpenAI Whisper API](https://platform.openai.com/docs/api-reference/introduction)
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- Available on Mac, Windows, and Linux
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@ -188,6 +188,11 @@ class DownloadModelProgressDialog(QProgressDialog):
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def __init__(self, parent: Optional[QWidget], *args) -> None:
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super().__init__(_('Downloading model (0%, unknown time remaining)'),
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_('Cancel'), 0, 100, parent, *args)
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# Setting this to a high value to avoid showing the dialog for models that
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# are checked locally but set progress to 0 immediately, i.e. Hugging Face or Faster Whisper models
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self.setMinimumDuration(10_000)
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self.setWindowModality(Qt.WindowModality.ApplicationModal)
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self.start_time = datetime.now()
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self.setFixedSize(self.size())
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@ -1373,7 +1378,8 @@ class TranscriptionOptionsGroupBox(QGroupBox):
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model_type = self.transcription_options.model.model_type
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self.form_layout.setRowVisible(self.hugging_face_search_line_edit, model_type == ModelType.HUGGING_FACE)
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self.form_layout.setRowVisible(self.whisper_model_size_combo_box,
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(model_type == ModelType.WHISPER) or (model_type == ModelType.WHISPER_CPP))
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(model_type == ModelType.WHISPER) or (model_type == ModelType.WHISPER_CPP) or (
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model_type == ModelType.FASTER_WHISPER))
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self.form_layout.setRowVisible(self.openai_access_token_edit, model_type == ModelType.OPEN_AI_WHISPER_API)
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def on_model_type_changed(self, text: str):
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@ -6,6 +6,7 @@ import warnings
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from dataclasses import dataclass
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from typing import Optional
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import faster_whisper
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import requests
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import whisper
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from PyQt6.QtCore import QObject, pyqtSignal, pyqtSlot
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@ -26,6 +27,7 @@ class ModelType(enum.Enum):
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WHISPER = 'Whisper'
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WHISPER_CPP = 'Whisper.cpp'
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HUGGING_FACE = 'Hugging Face'
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FASTER_WHISPER = 'Faster Whisper'
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OPEN_AI_WHISPER_API = 'OpenAI Whisper API'
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@ -99,6 +101,11 @@ class ModelLoader(QObject):
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elif self.model_type == ModelType.OPEN_AI_WHISPER_API:
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file_path = ""
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elif self.model_type == ModelType.FASTER_WHISPER:
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self.progress.emit((0, 100))
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file_path = faster_whisper.download_model(size=self.whisper_model_size.value)
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self.progress.emit((100, 100))
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else:
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raise Exception("Invalid model type: " + self.model_type.value)
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@ -18,12 +18,15 @@ from multiprocessing.connection import Connection
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from random import randint
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from threading import Thread
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from typing import Any, List, Optional, Tuple, Union, Set
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import faster_whisper
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import openai
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import ffmpeg
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import numpy as np
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import sounddevice
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import stable_whisper
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import tqdm
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import whisper
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from PyQt6.QtCore import QObject, QProcess, pyqtSignal, pyqtSlot, QThread
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from sounddevice import PortAudioError
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@ -431,7 +434,7 @@ class WhisperFileTranscriber(FileTranscriber):
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recv_pipe, send_pipe = multiprocessing.Pipe(duplex=False)
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self.current_process = multiprocessing.Process(target=transcribe_whisper,
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self.current_process = multiprocessing.Process(target=self.transcribe_whisper,
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args=(send_pipe, self.transcription_task))
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if not self.stopped:
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self.current_process.start()
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@ -457,6 +460,97 @@ class WhisperFileTranscriber(FileTranscriber):
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return self.segments
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@classmethod
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def transcribe_whisper(cls, stderr_conn: Connection, task: FileTranscriptionTask) -> None:
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with pipe_stderr(stderr_conn):
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if task.transcription_options.model.model_type == ModelType.HUGGING_FACE:
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segments = cls.transcribe_hugging_face(task)
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elif task.transcription_options.model.model_type == ModelType.FASTER_WHISPER:
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segments = cls.transcribe_faster_whisper(task)
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elif task.transcription_options.model.model_type == ModelType.WHISPER:
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segments = cls.transcribe_openai_whisper(task)
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else:
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raise Exception(f"Invalid model type: {task.transcription_options.model.model_type}")
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segments_json = json.dumps(
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segments, ensure_ascii=True, default=vars)
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sys.stderr.write(f'segments = {segments_json}\n')
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sys.stderr.write(
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WhisperFileTranscriber.READ_LINE_THREAD_STOP_TOKEN + '\n')
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@classmethod
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def transcribe_hugging_face(cls, task: FileTranscriptionTask) -> List[Segment]:
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model = transformers_whisper.load_model(task.model_path)
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language = task.transcription_options.language if task.transcription_options.language is not None else 'en'
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result = model.transcribe(audio=task.file_path, language=language,
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task=task.transcription_options.task.value, verbose=False)
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return [
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Segment(
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start=int(segment.get('start') * 1000),
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end=int(segment.get('end') * 1000),
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text=segment.get('text'),
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) for segment in result.get('segments')]
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@classmethod
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def transcribe_faster_whisper(cls, task: FileTranscriptionTask) -> List[Segment]:
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model = faster_whisper.WhisperModel(
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model_size_or_path=task.transcription_options.model.whisper_model_size.value)
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whisper_segments, info = model.transcribe(audio=task.file_path,
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language=task.transcription_options.language,
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task=task.transcription_options.task.value,
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temperature=task.transcription_options.temperature,
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initial_prompt=task.transcription_options.initial_prompt,
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word_timestamps=task.transcription_options.word_level_timings)
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segments = []
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with tqdm.tqdm(total=round(info.duration, 2), unit=' seconds') as pbar:
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for segment in list(whisper_segments):
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# Segment will contain words if word-level timings is True
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if segment.words:
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for word in segment.words:
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segments.append(Segment(
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start=int(word.start * 1000),
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end=int(word.end * 1000),
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text=word.word
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))
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else:
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segments.append(Segment(
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start=int(segment.start * 1000),
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end=int(segment.end * 1000),
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text=segment.text
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))
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pbar.update(segment.end - segment.start)
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return segments
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@classmethod
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def transcribe_openai_whisper(cls, task: FileTranscriptionTask) -> List[Segment]:
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model = whisper.load_model(task.model_path)
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if task.transcription_options.word_level_timings:
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stable_whisper.modify_model(model)
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result = model.transcribe(
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audio=task.file_path, language=task.transcription_options.language,
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task=task.transcription_options.task.value, temperature=task.transcription_options.temperature,
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initial_prompt=task.transcription_options.initial_prompt, pbar=True)
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segments = stable_whisper.group_word_timestamps(result)
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return [Segment(
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start=int(segment.get('start') * 1000),
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end=int(segment.get('end') * 1000),
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text=segment.get('text'),
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) for segment in segments]
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result = model.transcribe(
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audio=task.file_path, language=task.transcription_options.language,
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task=task.transcription_options.task.value,
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temperature=task.transcription_options.temperature,
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initial_prompt=task.transcription_options.initial_prompt, verbose=False)
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segments = result.get('segments')
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return [Segment(
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start=int(segment.get('start') * 1000),
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end=int(segment.get('end') * 1000),
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text=segment.get('text'),
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) for segment in segments]
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def stop(self):
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self.stopped = True
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if self.started_process:
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@ -489,44 +583,6 @@ class WhisperFileTranscriber(FileTranscriber):
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continue
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def transcribe_whisper(stderr_conn: Connection, task: FileTranscriptionTask):
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with pipe_stderr(stderr_conn):
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if task.transcription_options.model.model_type == ModelType.HUGGING_FACE:
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model = transformers_whisper.load_model(task.model_path)
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language = task.transcription_options.language if task.transcription_options.language is not None else 'en'
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result = model.transcribe(audio=task.file_path, language=language,
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task=task.transcription_options.task.value, verbose=False)
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whisper_segments = result.get('segments')
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else:
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model = whisper.load_model(task.model_path)
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if task.transcription_options.word_level_timings:
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stable_whisper.modify_model(model)
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result = model.transcribe(
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audio=task.file_path, language=task.transcription_options.language,
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task=task.transcription_options.task.value, temperature=task.transcription_options.temperature,
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initial_prompt=task.transcription_options.initial_prompt, pbar=True)
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whisper_segments = stable_whisper.group_word_timestamps(result)
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else:
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result = model.transcribe(
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audio=task.file_path, language=task.transcription_options.language,
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task=task.transcription_options.task.value,
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temperature=task.transcription_options.temperature,
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initial_prompt=task.transcription_options.initial_prompt, verbose=False)
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whisper_segments = result.get('segments')
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segments = [
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Segment(
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start=int(segment.get('start') * 1000),
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end=int(segment.get('end') * 1000),
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text=segment.get('text'),
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) for segment in whisper_segments]
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segments_json = json.dumps(
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segments, ensure_ascii=True, default=vars)
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sys.stderr.write(f'segments = {segments_json}\n')
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sys.stderr.write(
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WhisperFileTranscriber.READ_LINE_THREAD_STOP_TOKEN + '\n')
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def write_output(path: str, segments: List[Segment], output_format: OutputFormat):
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logging.debug(
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'Writing transcription output, path = %s, output format = %s, number of segments = %s', path, output_format,
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@ -681,9 +737,12 @@ class FileTranscriberQueueWorker(QObject):
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task=self.current_task)
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elif model_type == ModelType.OPEN_AI_WHISPER_API:
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self.current_transcriber = OpenAIWhisperAPIFileTranscriber(task=self.current_task)
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elif model_type == ModelType.HUGGING_FACE or \
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model_type == ModelType.WHISPER or \
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model_type == ModelType.FASTER_WHISPER:
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self.current_transcriber = WhisperFileTranscriber(task=self.current_task)
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else:
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self.current_transcriber = WhisperFileTranscriber(
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task=self.current_task)
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raise Exception(f'Unknown model type: {model_type}')
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self.current_transcriber_thread = QThread(self)
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301
poetry.lock
generated
301
poetry.lock
generated
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@ -1,4 +1,4 @@
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# This file is automatically @generated by Poetry and should not be changed by hand.
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# This file is automatically @generated by Poetry 1.4.2 and should not be changed by hand.
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[[package]]
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name = "aiohttp"
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@ -211,6 +211,60 @@ files = [
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pycodestyle = ">=2.9.1"
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toml = "*"
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[[package]]
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name = "av"
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version = "10.0.0"
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description = "Pythonic bindings for FFmpeg's libraries."
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category = "main"
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optional = false
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python-versions = "*"
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||||
{file = "av-10.0.0-pp37-pypy37_pp73-win_amd64.whl", hash = "sha256:86bb3f6e8cce62ad18cd34eb2eadd091d99f51b40be81c929b53fbd8fecf6d90"},
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||||
{file = "av-10.0.0-pp38-pypy38_pp73-macosx_10_9_x86_64.whl", hash = "sha256:f7b508813abbc100162d305a1ac9b2dd16e5128d56f2ac69639fc6a4b5aca69e"},
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||||
{file = "av-10.0.0-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:98cc376199c0aa6e9365d03e0f4e67cfb209e40fe9c0cf566372f9daf2a0c779"},
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||||
{file = "av-10.0.0-pp38-pypy38_pp73-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:1b459ca0ef25c1a0e370112556bdc5b7752f76dc9bd497acaf3e653171e4b946"},
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{file = "av-10.0.0-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ab930735112c1f788cc4d47c42c59ba0dd214d815aa906e1addf39af91d15194"},
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{file = "av-10.0.0-pp39-pypy39_pp73-macosx_10_9_x86_64.whl", hash = "sha256:13fe0b48b9211539323ecebbf84154c86c72d16723c6d0af76e29ae5c3a614b2"},
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{file = "av-10.0.0-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c2eeec7beaebfe9e2213b3c94b482381187d0afdcb632f93239b44dc668b97df"},
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{file = "av-10.0.0-pp39-pypy39_pp73-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:3dac2a8b0791c3373270e32f6cd27e6b60628565a188e40a5d9660d3aab05e33"},
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||||
{file = "av-10.0.0-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1cdede2325cb750b5bf79238bbf06f9c2a70b757b12726003769a43493b7233a"},
|
||||
{file = "av-10.0.0-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:9788e6e15db0910fb8e1548ba7540799d07066177710590a5794a524c4910e05"},
|
||||
{file = "av-10.0.0.tar.gz", hash = "sha256:8afd3d5610e1086f3b2d8389d66672ea78624516912c93612de64dcaa4c67e05"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "certifi"
|
||||
version = "2022.12.7"
|
||||
|
|
@ -339,6 +393,24 @@ files = [
|
|||
{file = "colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "coloredlogs"
|
||||
version = "15.0.1"
|
||||
description = "Colored terminal output for Python's logging module"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
|
||||
files = [
|
||||
{file = "coloredlogs-15.0.1-py2.py3-none-any.whl", hash = "sha256:612ee75c546f53e92e70049c9dbfcc18c935a2b9a53b66085ce9ef6a6e5c0934"},
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||||
{file = "coloredlogs-15.0.1.tar.gz", hash = "sha256:7c991aa71a4577af2f82600d8f8f3a89f936baeaf9b50a9c197da014e5bf16b0"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
humanfriendly = ">=9.1"
|
||||
|
||||
[package.extras]
|
||||
cron = ["capturer (>=2.4)"]
|
||||
|
||||
[[package]]
|
||||
name = "coverage"
|
||||
version = "6.5.0"
|
||||
|
|
@ -405,6 +477,44 @@ tomli = {version = "*", optional = true, markers = "python_full_version <= \"3.1
|
|||
[package.extras]
|
||||
toml = ["tomli"]
|
||||
|
||||
[[package]]
|
||||
name = "ctranslate2"
|
||||
version = "3.11.0"
|
||||
description = "Fast inference engine for Transformer models"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
files = [
|
||||
{file = "ctranslate2-3.11.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:ada5dc2965fd4eca8ce48df1dad7cf01f6706eb021532b2463413dc72b659adb"},
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{file = "ctranslate2-3.11.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:a9aeb5b4573196536a81d07099ab41a48e65fb1a461e81973da29e5a8d1a99b1"},
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{file = "ctranslate2-3.11.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9ce94d67ee09161fd751df4fa54c51086926cf54a9c3f62755974a124ab11a76"},
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{file = "ctranslate2-3.11.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9eee0eb7fabe665c88387e11c0d4bb9ee09cbb47bdfe6a4daba172c83a426fcb"},
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{file = "ctranslate2-3.11.0-cp310-cp310-win_amd64.whl", hash = "sha256:72d3d7549bd0ac06e2249449fba3129589c700362daec1594dd28fa95c3527af"},
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{file = "ctranslate2-3.11.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:ac843eefc575bf03164edb7c3cc0f529b9b612cb1b605cf818bfa05477381f8e"},
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||||
{file = "ctranslate2-3.11.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:1591231065eb2d17ff40787dac974538fb7be4853e35a90d4fc6d5d323617991"},
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||||
{file = "ctranslate2-3.11.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1da13aab5038b877a5de93620a014d191c86b976083060a650727199297c74f3"},
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||||
{file = "ctranslate2-3.11.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:605e469729797177cc548f064c208369dea3852153ba813ee56ec344cada2dcf"},
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||||
{file = "ctranslate2-3.11.0-cp311-cp311-win_amd64.whl", hash = "sha256:a2cb3c274c87801d1a3f61c0885230188802689364b0b1e338f868476e09d860"},
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{file = "ctranslate2-3.11.0-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:232baeee6acf9be4e6c283f627d6ad6c388bb147f90cc25d55d2970654a88d8f"},
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{file = "ctranslate2-3.11.0-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:672665d4c5c58cd37be80496849cad5efb66127b5c94710147483f050cafb555"},
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{file = "ctranslate2-3.11.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0d5c6a033d9e190fa217efbf191b1cb6d7140f361981c797910e1235a6d27318"},
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{file = "ctranslate2-3.11.0-cp37-cp37m-win_amd64.whl", hash = "sha256:faa64d7749827830e681d182d38f4a8ae5abbf446e28920c26246d1a3c303cdb"},
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||||
{file = "ctranslate2-3.11.0-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:ce7fb95a2397ba29559335b7f4e29746e35e141bf2afcb2355b26b2ca2a6e98b"},
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||||
{file = "ctranslate2-3.11.0-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:86e3236bb16be0f3161eb56a78f462cb2ab3d5f4d79d10ae63a5af0d13c0d7f2"},
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{file = "ctranslate2-3.11.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f670029212d53761992febace83f006163aa16c7a4fbd70c8d2aebd875da4c6f"},
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{file = "ctranslate2-3.11.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6dfe6a7854e5f51bc6705ddb5a1148fb76d760900d6b081271fc6744ba458a5f"},
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{file = "ctranslate2-3.11.0-cp38-cp38-win_amd64.whl", hash = "sha256:604e827d7d8c5e50295063b0566636fa9034c2a0e7a4ce62d1bc8eb9cebb1eb7"},
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{file = "ctranslate2-3.11.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:8cc83d458d1fae7207d25dd699806afd597f09d93a245fed45736a17e78cacec"},
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{file = "ctranslate2-3.11.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:01473b8bdb112e05107184087896e8523fb92d690d4d0e5624e4b3b5bd8abd5f"},
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||||
{file = "ctranslate2-3.11.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0ebbebf99e0bf236cdc07c35db20decfdee691f66fd6ffe16f4d63f24a56b7e3"},
|
||||
{file = "ctranslate2-3.11.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f8ce3995eeda90bd8f4acab093e899f6f00a6b44d3c52aea25f7b9a1ef747441"},
|
||||
{file = "ctranslate2-3.11.0-cp39-cp39-win_amd64.whl", hash = "sha256:2cbb1292faac837b4cf4c8054558b791ce47392e34e7e2a35f2357d62d034895"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
numpy = "*"
|
||||
pyyaml = ">=5.3,<7"
|
||||
|
||||
[[package]]
|
||||
name = "ctypesgen"
|
||||
version = "1.1.1"
|
||||
|
|
@ -459,6 +569,29 @@ files = [
|
|||
[package.extras]
|
||||
test = ["pytest (>=6)"]
|
||||
|
||||
[[package]]
|
||||
name = "faster-whisper"
|
||||
version = "0.4.1"
|
||||
description = "Faster Whisper transcription with CTranslate2"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "faster-whisper-0.4.1.tar.gz", hash = "sha256:f528f58c1bdc6ac505fae6abfaddb80e6b23df018ebc16a5e0ee5ebaeb9ab3bc"},
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{file = "faster_whisper-0.4.1-py3-none-any.whl", hash = "sha256:7fec7bb7b9071d484a3a7612fc5fd12cc56ffe2948d54320ca3abe16d9939384"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
av = ">=10.0.0,<11.0.0"
|
||||
ctranslate2 = ">=3.10,<4"
|
||||
huggingface-hub = ">=0.13"
|
||||
onnxruntime = {version = ">=1.14.0,<1.15.0", markers = "python_version < \"3.11\""}
|
||||
tokenizers = ">=0.13.0,<0.14.0"
|
||||
|
||||
[package.extras]
|
||||
conversion = ["transformers[torch] (>=4.23)"]
|
||||
dev = ["black (>=23.0.0,<24.0.0)", "flake8 (>=6.0.0,<7.0.0)", "isort (>=5.0.0,<6.0.0)", "pytest (>=7.0.0,<8.0.0)"]
|
||||
|
||||
[[package]]
|
||||
name = "ffmpeg-python"
|
||||
version = "0.2.0"
|
||||
|
|
@ -493,6 +626,18 @@ files = [
|
|||
docs = ["furo (>=2022.9.29)", "sphinx (>=5.3)", "sphinx-autodoc-typehints (>=1.19.5)"]
|
||||
testing = ["covdefaults (>=2.2.2)", "coverage (>=6.5)", "pytest (>=7.2)", "pytest-cov (>=4)", "pytest-timeout (>=2.1)"]
|
||||
|
||||
[[package]]
|
||||
name = "flatbuffers"
|
||||
version = "23.3.3"
|
||||
description = "The FlatBuffers serialization format for Python"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = "*"
|
||||
files = [
|
||||
{file = "flatbuffers-23.3.3-py2.py3-none-any.whl", hash = "sha256:5ad36d376240090757e8f0a2cfaf6abcc81c6536c0dc988060375fd0899121f8"},
|
||||
{file = "flatbuffers-23.3.3.tar.gz", hash = "sha256:cabd87c4882f37840f6081f094b2c5bc28cefc2a6357732746936d055ab45c3d"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "frozenlist"
|
||||
version = "1.3.3"
|
||||
|
|
@ -590,14 +735,14 @@ files = [
|
|||
|
||||
[[package]]
|
||||
name = "huggingface-hub"
|
||||
version = "0.11.1"
|
||||
version = "0.13.4"
|
||||
description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.7.0"
|
||||
files = [
|
||||
{file = "huggingface_hub-0.11.1-py3-none-any.whl", hash = "sha256:11eed7aab4fa4d1fb532f2aea3379ef4998d9f6bc24a330834dfedd3dac7f441"},
|
||||
{file = "huggingface_hub-0.11.1.tar.gz", hash = "sha256:8b9ebf9bbb1782f6f0419ec490973a6487c6c4ed84293a8a325d34c4f898f53f"},
|
||||
{file = "huggingface_hub-0.13.4-py3-none-any.whl", hash = "sha256:4d3d40593de6673d624a4baaaf249b9bf5165bfcafd1ad58de361931f0b4fda5"},
|
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{file = "huggingface_hub-0.13.4.tar.gz", hash = "sha256:db83d9c2f76aed8cf49893ffadd6be24e82074da2f64b1d36b8ba40eb255e115"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -605,20 +750,35 @@ filelock = "*"
|
|||
packaging = ">=20.9"
|
||||
pyyaml = ">=5.1"
|
||||
requests = "*"
|
||||
tqdm = "*"
|
||||
tqdm = ">=4.42.1"
|
||||
typing-extensions = ">=3.7.4.3"
|
||||
|
||||
[package.extras]
|
||||
all = ["InquirerPy (==0.3.4)", "Jinja2", "black (==22.3)", "flake8 (>=3.8.3)", "flake8-bugbear", "isort (>=5.5.4)", "jedi", "mypy (==0.982)", "pytest", "pytest-cov", "pytest-env", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3"]
|
||||
all = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "black (>=23.1,<24.0)", "jedi", "mypy (==0.982)", "pytest", "pytest-cov", "pytest-env", "pytest-xdist", "ruff (>=0.0.241)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3"]
|
||||
cli = ["InquirerPy (==0.3.4)"]
|
||||
dev = ["InquirerPy (==0.3.4)", "Jinja2", "black (==22.3)", "flake8 (>=3.8.3)", "flake8-bugbear", "isort (>=5.5.4)", "jedi", "mypy (==0.982)", "pytest", "pytest-cov", "pytest-env", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3"]
|
||||
dev = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "black (>=23.1,<24.0)", "jedi", "mypy (==0.982)", "pytest", "pytest-cov", "pytest-env", "pytest-xdist", "ruff (>=0.0.241)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3"]
|
||||
fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
|
||||
quality = ["black (==22.3)", "flake8 (>=3.8.3)", "flake8-bugbear", "isort (>=5.5.4)", "mypy (==0.982)"]
|
||||
quality = ["black (>=23.1,<24.0)", "mypy (==0.982)", "ruff (>=0.0.241)"]
|
||||
tensorflow = ["graphviz", "pydot", "tensorflow"]
|
||||
testing = ["InquirerPy (==0.3.4)", "Jinja2", "isort (>=5.5.4)", "jedi", "pytest", "pytest-cov", "pytest-env", "soundfile"]
|
||||
testing = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "jedi", "pytest", "pytest-cov", "pytest-env", "pytest-xdist", "soundfile"]
|
||||
torch = ["torch"]
|
||||
typing = ["types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3"]
|
||||
|
||||
[[package]]
|
||||
name = "humanfriendly"
|
||||
version = "10.0"
|
||||
description = "Human friendly output for text interfaces using Python"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
|
||||
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|
||||
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||||
|
||||
[[package]]
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||||
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||||
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||||
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|
||||
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||||
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|
@ -996,6 +1223,29 @@ pyyaml = ">=5.1"
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[[package]]
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name = "pycodestyle"
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||||
version = "2.10.0"
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|
|
@ -1151,6 +1401,18 @@ files = [
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||||
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[[package]]
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||||
name = "pytest"
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version = "7.2.0"
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|
|
@ -1487,6 +1749,21 @@ files = [
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whisper = "*"
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||||
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[[package]]
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description = "Computer algebra system (CAS) in Python"
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[[package]]
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@ -1503,11 +1780,14 @@ files = [
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@ -1516,6 +1796,7 @@ files = [
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|
|
@ -1935,4 +2216,4 @@ multidict = ">=4.0"
|
|||
[metadata]
|
||||
lock-version = "2.0"
|
||||
python-versions = ">=3.9.13,<3.11"
|
||||
content-hash = "a33abc3b1f27979981b5fcfa544253a966c4be74aaef036615af5cbbe5abfe0c"
|
||||
content-hash = "1221c97d2440f0de33521f1c1f97f89d52d43ec18984629f591421c11012ebfc"
|
||||
|
|
|
|||
|
|
@ -18,6 +18,7 @@ humanize = "^4.4.0"
|
|||
PyQt6 = "^6.4.0"
|
||||
stable-ts = "^1.0.1"
|
||||
openai = "^0.27.1"
|
||||
faster-whisper = "^0.4.1"
|
||||
|
||||
[tool.poetry.group.dev.dependencies]
|
||||
autopep8 = "^1.7.0"
|
||||
|
|
|
|||
|
|
@ -117,7 +117,14 @@ class TestWhisperFileTranscriber:
|
|||
' Bienvenue dans Passe-Relle. Un podcast pensé pour évêyer la curiosité des apprenances '
|
||||
'et des apprenances de français.')],
|
||||
TranscriptionModel(model_type=ModelType.HUGGING_FACE,
|
||||
hugging_face_model_id='openai/whisper-tiny'), False)
|
||||
hugging_face_model_id='openai/whisper-tiny'), False),
|
||||
pytest.param(
|
||||
False, [Segment(start=0, end=8400,
|
||||
text=' Bienvenue dans Passrel, un podcast pensé pour éveiller la curiosité des apprenances et des apprenances de français.')],
|
||||
TranscriptionModel(model_type=ModelType.FASTER_WHISPER, whisper_model_size=WhisperModelSize.TINY), True,
|
||||
marks=pytest.mark.skipif(platform.system() == 'Darwin',
|
||||
reason='Error with libiomp5 already initialized on GH action runner: https://github.com/chidiwilliams/buzz/actions/runs/4657331262/jobs/8241832087')
|
||||
)
|
||||
])
|
||||
def test_transcribe(self, qtbot: QtBot, word_level_timings: bool, expected_segments: List[Segment],
|
||||
model: TranscriptionModel, check_progress):
|
||||
|
|
@ -127,13 +134,14 @@ class TestWhisperFileTranscriber:
|
|||
word_level_timings=word_level_timings,
|
||||
model=model)
|
||||
model_path = get_model_path(transcription_options.model)
|
||||
file_path = os.path.abspath(os.path.join(os.path.dirname(__file__), '..', 'testdata/whisper-french.mp3'))
|
||||
file_transcription_options = FileTranscriptionOptions(
|
||||
file_paths=['testdata/whisper-french.mp3'])
|
||||
file_paths=[file_path])
|
||||
|
||||
transcriber = WhisperFileTranscriber(
|
||||
task=FileTranscriptionTask(transcription_options=transcription_options,
|
||||
file_transcription_options=file_transcription_options,
|
||||
file_path='testdata/whisper-french.mp3', model_path=model_path))
|
||||
file_path=file_path, model_path=model_path))
|
||||
transcriber.progress.connect(mock_progress)
|
||||
transcriber.completed.connect(mock_completed)
|
||||
with qtbot.wait_signal(transcriber.progress, timeout=10 * 6000), qtbot.wait_signal(transcriber.completed,
|
||||
|
|
|
|||
Loading…
Reference in a new issue