Upload synthesizer_preprocess_audio.py with huggingface_hub

synthesizer_preprocess_audio.py

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+from synthesizer.preprocess import preprocess_dataset
+from synthesizer.hparams import hparams
+from utils.argutils import print_args
+from pathlib import Path
+import argparse
+
+
+if __name__ == "__main__":
+    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 <datasets_root>/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("--datasets_name", type=str, default="LibriSpeech", help=\
+        "Name of the dataset directory to process.")
+    parser.add_argument("--subfolders", type=str, default="train-clean-100, train-clean-360", help=\
+        "Comma-separated list of subfolders to process inside your dataset directory")
+    args = parser.parse_args()
+
+    # Process the arguments
+    if not hasattr(args, "out_dir"):
+        args.out_dir = args.datasets_root.joinpath("SV2TTS", "synthesizer")
+
+    # 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))