spegling av
https://github.com/karl0ss/bazarr-ai-sub-generator.git
synced 2025-07-03 05:09:09 +01:00
67 rader
2.3 KiB
Python
67 rader
2.3 KiB
Python
import os
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import warnings
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import tempfile
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import time
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from utils.files import filename, write_srt
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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.sonarr import update_show_in_sonarr
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from utils.whisper import WhisperAI
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def process(args: dict):
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model_name: str = args.pop("model")
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language: str = args.pop("language")
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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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warnings.warn(
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f"{model_name} is an English-only model, forcing English detection."
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)
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args["language"] = "en"
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# if translate task used and language argument is set, then use it
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elif language != "auto":
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args["language"] = language
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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["compute_type"] = args.pop("compute_type")
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list_of_episodes_needing_subtitles = get_wanted_episodes()
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print(
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f"Found {list_of_episodes_needing_subtitles['total']} episodes needing subtitles."
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)
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for episode in list_of_episodes_needing_subtitles["data"]:
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print(f"Processing {episode['seriesTitle']} - {episode['episode_number']}")
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episode_data = get_episode_details(episode["sonarrEpisodeId"])
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audios = get_audio([episode_data["path"]], audio_channel, sample_interval)
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subtitles = get_subtitles(audios, tempfile.gettempdir(), model_args, args)
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add_subtitles_to_mp4(subtitles)
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update_show_in_sonarr(episode["sonarrSeriesId"])
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time.sleep(5)
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sync_series()
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def get_subtitles(
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audio_paths: list, output_dir: str, model_args: dict, transcribe_args: dict
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):
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model = WhisperAI(model_args, transcribe_args)
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subtitles_path = {}
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for path, audio_path in audio_paths.items():
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print(f"Generating subtitles for {filename(path)}... This might take a while.")
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srt_path = os.path.join(output_dir, f"{filename(path)}.srt")
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segments = model.transcribe(audio_path)
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with open(srt_path, "w", encoding="utf-8") as srt:
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write_srt(segments, file=srt)
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subtitles_path[path] = srt_path
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return subtitles_path
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