Real-Time-Voice-Cloning / demo_toolbox.py
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from pathlib import Path
from toolbox import Toolbox
from utils.argutils import print_args
from utils.modelutils import check_model_paths
import argparse
import os
if __name__ == '__main__':
parser = argparse.ArgumentParser(
description="Runs the toolbox",
formatter_class=argparse.ArgumentDefaultsHelpFormatter
)
parser.add_argument("-d", "--datasets_root", type=Path, help= \
"Path to the directory containing your datasets. See toolbox/__init__.py for a list of "
"supported datasets.", default=None)
parser.add_argument("-e", "--enc_models_dir", type=Path, default="encoder/saved_models",
help="Directory containing saved encoder models")
parser.add_argument("-s", "--syn_models_dir", type=Path, default="synthesizer/saved_models",
help="Directory containing saved synthesizer models")
parser.add_argument("-v", "--voc_models_dir", type=Path, default="vocoder/saved_models",
help="Directory containing saved vocoder models")
parser.add_argument("--cpu", action="store_true", help=\
"If True, processing is done on CPU, even when a GPU is available.")
parser.add_argument("--seed", type=int, default=None, help=\
"Optional random number seed value to make toolbox deterministic.")
parser.add_argument("--no_mp3_support", action="store_true", help=\
"If True, no mp3 files are allowed.")
args = parser.parse_args()
print_args(args, parser)
if args.cpu:
# Hide GPUs from Pytorch to force CPU processing
os.environ["CUDA_VISIBLE_DEVICES"] = "-1"
del args.cpu
## Remind the user to download pretrained models if needed
check_model_paths(encoder_path=args.enc_models_dir, synthesizer_path=args.syn_models_dir,
vocoder_path=args.voc_models_dir)
# Launch the toolbox
Toolbox(**vars(args))