diff --git a/control/cli/synthesizer_preprocess_audio.py b/control/cli/synthesizer_preprocess_audio.py deleted file mode 100644 index 12270fe..0000000 --- a/control/cli/synthesizer_preprocess_audio.py +++ /dev/null @@ -1,65 +0,0 @@ -from models.synthesizer.preprocess import preprocess_dataset -from models.synthesizer.hparams import hparams -from utils.argutils import print_args -from pathlib import Path -import argparse - - -recognized_datasets = [ - "aidatatang_200zh", - "magicdata", - "aishell3" -] - -if __name__ == "__main__": - print("This method is deprecaded and will not be longer supported, please use 'pre.py'") - parser = argparse.ArgumentParser( - description="Preprocesses audio files from datasets, encodes them as mel spectrograms " - "and writes them to the disk. Audio files are also saved, to be used by the " - "vocoder for training.", - formatter_class=argparse.ArgumentDefaultsHelpFormatter - ) - parser.add_argument("datasets_root", type=Path, help=\ - "Path to the directory containing your LibriSpeech/TTS datasets.") - parser.add_argument("-o", "--out_dir", type=Path, default=argparse.SUPPRESS, help=\ - "Path to the output directory that will contain the mel spectrograms, the audios and the " - "embeds. Defaults to /SV2TTS/synthesizer/") - parser.add_argument("-n", "--n_processes", type=int, default=None, help=\ - "Number of processes in parallel.") - parser.add_argument("-s", "--skip_existing", action="store_true", help=\ - "Whether to overwrite existing files with the same name. Useful if the preprocessing was " - "interrupted.") - parser.add_argument("--hparams", type=str, default="", help=\ - "Hyperparameter overrides as a comma-separated list of name-value pairs") - parser.add_argument("--no_trim", action="store_true", help=\ - "Preprocess audio without trimming silences (not recommended).") - parser.add_argument("--no_alignments", action="store_true", help=\ - "Use this option when dataset does not include alignments\ - (these are used to split long audio files into sub-utterances.)") - parser.add_argument("--dataset", type=str, default="aidatatang_200zh", help=\ - "Name of the dataset to process, allowing values: magicdata, aidatatang_200zh.") - args = parser.parse_args() - - # Process the arguments - if not hasattr(args, "out_dir"): - args.out_dir = args.datasets_root.joinpath("SV2TTS", "synthesizer") - assert args.dataset in recognized_datasets, 'is not supported, please vote for it in https://github.com/babysor/MockingBird/issues/10' - # Create directories - assert args.datasets_root.exists() - args.out_dir.mkdir(exist_ok=True, parents=True) - - # Verify webrtcvad is available - if not args.no_trim: - try: - import webrtcvad - except: - raise ModuleNotFoundError("Package 'webrtcvad' not found. This package enables " - "noise removal and is recommended. Please install and try again. If installation fails, " - "use --no_trim to disable this error message.") - del args.no_trim - - # Preprocess the dataset - print_args(args, parser) - args.hparams = hparams.parse(args.hparams) - - preprocess_dataset(**vars(args)) \ No newline at end of file diff --git a/control/cli/synthesizer_preprocess_embeds.py b/control/cli/synthesizer_preprocess_embeds.py deleted file mode 100644 index 38c9e2f..0000000 --- a/control/cli/synthesizer_preprocess_embeds.py +++ /dev/null @@ -1,26 +0,0 @@ -from models.synthesizer.preprocess import create_embeddings -from utils.argutils import print_args -from pathlib import Path -import argparse - - -if __name__ == "__main__": - print("This method is deprecaded and will not be longer supported, please use 'pre.py'") - parser = argparse.ArgumentParser( - description="Creates embeddings for the synthesizer from the LibriSpeech utterances.", - formatter_class=argparse.ArgumentDefaultsHelpFormatter - ) - parser.add_argument("synthesizer_root", type=Path, help=\ - "Path to the synthesizer training data that contains the audios and the train.txt file. " - "If you let everything as default, it should be /SV2TTS/synthesizer/.") - parser.add_argument("-e", "--encoder_model_fpath", type=Path, - default="data/ckpt/encoder/pretrained.pt", help=\ - "Path your trained encoder model.") - parser.add_argument("-n", "--n_processes", type=int, default=4, help= \ - "Number of parallel processes. An encoder is created for each, so you may need to lower " - "this value on GPUs with low memory. Set it to 1 if CUDA is unhappy.") - args = parser.parse_args() - - # Preprocess the dataset - print_args(args, parser) - create_embeddings(**vars(args))