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50 lines
2.4 KiB
Python
50 lines
2.4 KiB
Python
from pathlib import Path
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import argparse
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from models.ppg2mel.preprocess import preprocess_dataset
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from pathlib import Path
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import argparse
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recognized_datasets = [
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"aidatatang_200zh",
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"aidatatang_200zh_s", # sample
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]
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(
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description="Preprocesses audio files from datasets, to be used by the "
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"ppg2mel model for training.",
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formatter_class=argparse.ArgumentDefaultsHelpFormatter
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)
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parser.add_argument("datasets_root", type=Path, help=\
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"Path to the directory containing your datasets.")
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parser.add_argument("-d", "--dataset", type=str, default="aidatatang_200zh", help=\
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"Name of the dataset to process, allowing values: aidatatang_200zh.")
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parser.add_argument("-o", "--out_dir", type=Path, default=argparse.SUPPRESS, help=\
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"Path to the output directory that will contain the mel spectrograms, the audios and the "
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"embeds. Defaults to <datasets_root>/PPGVC/ppg2mel/")
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parser.add_argument("-n", "--n_processes", type=int, default=8, help=\
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"Number of processes in parallel.")
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# parser.add_argument("-s", "--skip_existing", action="store_true", help=\
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# "Whether to overwrite existing files with the same name. Useful if the preprocessing was "
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# "interrupted. ")
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# parser.add_argument("--hparams", type=str, default="", help=\
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# "Hyperparameter overrides as a comma-separated list of name-value pairs")
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# parser.add_argument("--no_trim", action="store_true", help=\
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# "Preprocess audio without trimming silences (not recommended).")
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parser.add_argument("-pf", "--ppg_encoder_model_fpath", type=Path, default="ppg_extractor/saved_models/24epoch.pt", help=\
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"Path your trained ppg encoder model.")
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parser.add_argument("-sf", "--speaker_encoder_model", type=Path, default="encoder/saved_models/pretrained_bak_5805000.pt", help=\
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"Path your trained speaker encoder model.")
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args = parser.parse_args()
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assert args.dataset in recognized_datasets, 'is not supported, file a issue to propose a new one'
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# Create directories
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assert args.datasets_root.exists()
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if not hasattr(args, "out_dir"):
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args.out_dir = args.datasets_root.joinpath("PPGVC", "ppg2mel")
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args.out_dir.mkdir(exist_ok=True, parents=True)
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preprocess_dataset(**vars(args))
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