mirror of
https://github.com/karl0ss/bazarr-ai-sub-generator.git
synced 2025-04-26 14:59:21 +01:00
more cleanup
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parent
7e83e4ef1e
commit
281b3cabc1
5
.vscode/launch.json
vendored
5
.vscode/launch.json
vendored
@ -11,12 +11,15 @@
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"program": "${file}",
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"program": "${file}",
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"console": "integratedTerminal",
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"console": "integratedTerminal",
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"justMyCode": false,
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"justMyCode": false,
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"env": {
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"CUDA_VISIBLE_DEVICES": "1"
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},
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"args": [
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"args": [
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"--model",
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"--model",
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"base",
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"base",
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"--show",
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"--show",
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"Gary Neville's Soccerbox"
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"Gary Neville's Soccerbox"
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],
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]
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}
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}
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]
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]
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}
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}
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@ -77,7 +77,6 @@ def main():
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"--show",
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"--show",
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type=str,
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type=str,
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default=None,
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default=None,
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#choices=["transcribe", "translate"],
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help="whether to perform X->X speech recognition ('transcribe') \
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help="whether to perform X->X speech recognition ('transcribe') \
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or X->English translation ('translate')",
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or X->English translation ('translate')",
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)
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)
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@ -7,26 +7,13 @@ from utils.ffmpeg import get_audio, add_subtitles_to_mp4
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from utils.bazarr import get_wanted_episodes, get_episode_details, sync_series
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from utils.bazarr import get_wanted_episodes, get_episode_details, sync_series
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from utils.sonarr import update_show_in_sonarr
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from utils.sonarr import update_show_in_sonarr
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from utils.whisper import WhisperAI
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from utils.whisper import WhisperAI
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from utils.decorator import measure_time
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def measure_time(func):
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def wrapper(*args, **kwargs):
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start_time = time.time()
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result = func(*args, **kwargs)
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end_time = time.time()
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duration = end_time - start_time
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print(f"Function '{func.__name__}' executed in: {duration:.6f} seconds")
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return result
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return wrapper
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def process(args: dict):
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def process(args: dict):
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model_name: str = args.pop("model")
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model_name: str = args.pop("model")
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language: str = args.pop("language")
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language: str = args.pop("language")
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show: str = args.pop("show")
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show: str = args.pop("show")
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# sample_interval: str = args.pop("sample_interval")
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# audio_channel: str = args.pop("audio_channel")
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if model_name.endswith(".en"):
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if model_name.endswith(".en"):
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warnings.warn(
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warnings.warn(
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@ -38,9 +25,7 @@ def process(args: dict):
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args["language"] = language
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args["language"] = language
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model_args = {}
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model_args = {}
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# model_args["model_size_or_path"] = model_name
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model_args["device"] = args.pop("device")
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model_args["device"] = args.pop("device")
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# model_args["compute_type"] = args.pop("compute_type")
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list_of_episodes_needing_subtitles = get_wanted_episodes(show)
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list_of_episodes_needing_subtitles = get_wanted_episodes(show)
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print(
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print(
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13
bazarr-ai-sub-generator/utils/decorator.py
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13
bazarr-ai-sub-generator/utils/decorator.py
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@ -0,0 +1,13 @@
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import time
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from datetime import timedelta
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def measure_time(func):
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def wrapper(*args, **kwargs):
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start_time = time.time()
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result = func(*args, **kwargs)
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end_time = time.time()
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duration = end_time - start_time
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human_readable_duration = str(timedelta(seconds=duration))
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print(f"Function '{func.__name__}' executed in: {human_readable_duration}")
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return result
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return wrapper
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@ -1,4 +1,3 @@
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faster-whisper==0.10.0
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tqdm==4.56.0
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tqdm==4.56.0
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ffmpeg-python==0.2.0
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ffmpeg-python==0.2.0
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git+https://github.com/openai/whisper.git
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git+https://github.com/openai/whisper.git
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