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Update subgen.py

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This commit is contained in:
McCloudS
2024-02-10 14:35:43 -07:00
committed by GitHub
parent 05894c31f4
commit e4c02c5c6f
1 changed files with 15 additions and 13 deletions
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subgen/subgen.py
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@@ -49,7 +49,7 @@ path_mapping_to = os.getenv('PATH_MAPPING_TO', '/Volumes/TV')
model_location = os.getenv('MODEL_PATH', '.')
transcribe_folders = os.getenv('TRANSCRIBE_FOLDERS', '')
transcribe_or_translate = os.getenv('TRANSCRIBE_OR_TRANSLATE', 'translate')
force_detected_language_to = os.getenv('FORCE_DETECTED_LANGUAGE_TO', None)
force_detected_language_to = os.getenv('FORCE_DETECTED_LANGUAGE_TO', '')
hf_transformers = os.getenv('HF_TRANSFORMERS', False)
hf_batch_size = os.getenv('HF_BATCH_SIZE', 24)
clear_vram_on_complete = os.getenv('CLEAR_VRAM_ON_COMPLETE', True)
@@ -259,7 +259,7 @@ def start_model():
if model is None:
logging.debug("Model was purged, need to re-create")
if(hf_transformers):
logging.debug("Use Hugging Face Transformers, whisper_threads, concurrent_transcriptions, and model_location variables are ignored!")
logging.debug("Using Hugging Face Transformers, whisper_threads, concurrent_transcriptions, and model_location variables are ignored!")
model = stable_whisper.load_hf_whisper(whisper_model, device=transcribe_device)
else:
model = stable_whisper.load_faster_whisper(whisper_model, download_root=model_location, device=transcribe_device, cpu_threads=whisper_threads, num_workers=concurrent_transcriptions, compute_type=compute_type)
@@ -290,7 +290,7 @@ def get_lang_pair(whisper_languages, key):
else:
return whisper_languages[other_side]
def gen_subtitles(file_path: str, transcribe_or_translate_str: str, front=True, forceLanguage=force_detected_language_to) -> None:
def gen_subtitles(file_path: str, transcribe_or_translate: str, front=True, forceLanguage=None) -> None:
"""Generates subtitles for a video file.
Args:
@@ -300,8 +300,8 @@ def gen_subtitles(file_path: str, transcribe_or_translate_str: str, front=True,
"""
try:
if not is_video_file(file_path):
logging.debug(f"{file_path} isn't a video file!")
if not has_audio(file_path):
logging.debug(f"{file_path} doesn't have any audio to transcribe!")
return None
if file_path not in files_to_transcribe:
@@ -327,11 +327,14 @@ def gen_subtitles(file_path: str, transcribe_or_translate_str: str, front=True,
print(f"Transcribing file: {os.path.basename(file_path)}")
start_time = time.time()
start_model()
global force_detected_language_to
if force_detected_language_to:
forceLanguage = force_detected_language_to
print(f"Forcing language to {forceLanguage}")
if(hf_transformers):
result = model.transcribe(file_path, language=forceLanguage, batch_size=hf_batch_size, task=transcribe_or_translate_str)
result = model.transcribe(file_path, language=forceLanguage, batch_size=hf_batch_size, task=transcribe_or_translate)
else:
result = model.transcribe_stable(file_path, language=forceLanguage, task=transcribe_or_translate_str)
result = model.transcribe_stable(file_path, language=forceLanguage, task=transcribe_or_translate)
result.to_srt_vtt(get_file_name_without_extension(file_path) + subextension, word_level=word_level_highlight)
elapsed_time = time.time() - start_time
minutes, seconds = divmod(int(elapsed_time), 60)
@@ -503,15 +506,14 @@ def get_jellyfin_admin(users):
raise Exception("Unable to find administrator user in Jellyfin")
def is_video_file(file_path):
av.logging.set_level(av.logging.PANIC)
def has_audio(file_path):
try:
container = av.open(file_path)
for stream in container.streams:
if stream.type == 'video':
if stream.type == 'audio':
return True
return False
except av.AVError:
except (av.AVError, UnicodeDecodeError):
return False
def path_mapping(fullpath):
@@ -532,7 +534,7 @@ def transcribe_existing(transcribe_folders, forceLanguage=None):
gen_subtitles(path_mapping(file_path), transcribe_or_translate, False, forceLanguage)
# if the path specified was actually a single file and not a folder, process it
if os.path.isfile(path):
if is_video_file(path):
if has_audio(path):
gen_subtitles(path_mapping(path), transcribe_or_translate, False, forceLanguage)
print("Finished searching and queueing files for transcription")