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Added kwargs so you can change most any options on transcribe from faster-whisper, stable-ts, or whisper

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This commit is contained in:
McCloudS
2024-08-03 07:02:32 -06:00
committed by GitHub
parent 13462b3eed
commit 43a33b1e89
1 changed files with 7 additions and 5 deletions
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12
subgen.py
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@@ -24,6 +24,7 @@ import av
import ffmpeg
import whisper
import re
import ast
from watchdog.observers.polling import PollingObserver as Observer
from watchdog.events import FileSystemEventHandler
import faster_whisper
@@ -102,6 +103,7 @@ def update_env_variables():
custom_regroup = os.getenv('CUSTOM_REGROUP', 'cm_sl=84_sl=42++++++1')
detect_language_length = os.getenv('DETECT_LANGUAGE_LENGTH', 30)
skipifexternalsub = convert_to_bool(os.getenv('SKIPIFEXTERNALSUB', False))
kwargs = ast.literal_eval(os.getenv('SUBGEN_KWARGS', ''))
set_env_variables('subgen.env')
@@ -444,9 +446,9 @@ async def asr(
if model_prompt:
custom_prompt = greetings_translations.get(language, '') or custom_model_prompt
if custom_regroup:
result = model.transcribe_stable(audio_data, task=task, input_sr=16000, language=language, progress_callback=progress, initial_prompt=custom_prompt, regroup=custom_regroup)
result = model.transcribe_stable(audio_data, task=task, input_sr=16000, language=language, progress_callback=progress, initial_prompt=custom_prompt, regroup=custom_regroup, **kwargs)
else:
result = model.transcribe_stable(audio_data, task=task, input_sr=16000, language=language, progress_callback=progress, initial_prompt=custom_prompt)
result = model.transcribe_stable(audio_data, task=task, input_sr=16000, language=language, progress_callback=progress, initial_prompt=custom_prompt, **kwargs)
appendLine(result)
elapsed_time = time.time() - start_time
minutes, seconds = divmod(int(elapsed_time), 60)
@@ -485,7 +487,7 @@ async def detect_language(
task_queue.put(task_id)
audio_data = np.frombuffer(audio_file.file.read(), np.int16).flatten().astype(np.float32) / 32768.0
detected_language = model.transcribe_stable(whisper.pad_or_trim(audio_data, int(detect_language_length) * 16000), input_sr=16000).language
detected_language = model.transcribe_stable(whisper.pad_or_trim(audio_data, int(detect_language_length) * 16000), input_sr=16000, **kwargs).language
# reverse lookup of language -> code, ex: "english" -> "en", "nynorsk" -> "nn", ...
language_code = get_key_by_value(whisper_languages, detected_language)
@@ -546,10 +548,10 @@ def gen_subtitles(file_path: str, transcription_type: str, force_language=None)
if custom_regroup:
result = model.transcribe_stable(file_path, language=force_language, task=transcription_type,
progress_callback=progress, initial_prompt=custom_model_prompt,
regroup=custom_regroup)
regroup=custom_regroup, **kwargs)
else:
result = model.transcribe_stable(file_path, language=force_language, task=transcription_type,
progress_callback=progress, initial_prompt=custom_model_prompt)
progress_callback=progress, initial_prompt=custom_model_prompt, **kwargs)
appendLine(result)
file_name, file_extension = os.path.splitext(file_path)