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				https://github.com/karl0ss/bazarr-ai-sub-generator.git
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	more cleanup
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										5
									
								
								.vscode/launch.json
									
									
									
									
										vendored
									
									
								
							
							
						
						
									
										5
									
								
								.vscode/launch.json
									
									
									
									
										vendored
									
									
								
							@ -11,12 +11,15 @@
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            "program": "${file}",
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            "console": "integratedTerminal",
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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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                "--model",
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                "base",
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                "--show",
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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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@ -77,7 +77,6 @@ def main():
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        "--show",
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        type=str,
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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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                              or X->English translation ('translate')",
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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.sonarr import update_show_in_sonarr
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from utils.whisper import WhisperAI
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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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from utils.decorator import measure_time
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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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    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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        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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    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(show)
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    print(
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										13
									
								
								bazarr-ai-sub-generator/utils/decorator.py
									
									
									
									
									
										Normal file
									
								
							
							
						
						
									
										13
									
								
								bazarr-ai-sub-generator/utils/decorator.py
									
									
									
									
									
										Normal file
									
								
							@ -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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ffmpeg-python==0.2.0
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git+https://github.com/openai/whisper.git
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