Files
2023-05-22 23:09:00 -03:00

70 lines
1.3 KiB
Python

import os
import json
import argparse
import torch
import numpy as np
import soundfile as sf
from tsvitsfe import TSVITSFE
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument(
"--text",
type=str,
default=None,
help="raw text to synthesize, for single-sentence mode only",
)
parser.add_argument(
"--config",
type=str,
required=True,
help="Path to config",
)
parser.add_argument(
"--checkpoint",
type=str,
required=True,
help="Path to TorchScript-exported model file.",
)
parser.add_argument(
"--out-path",
type=str,
required=True,
help="Path to store files",
)
parser.add_argument(
"--device",
type=str,
required=True,
help="device. cuda or cpu",
)
args = parser.parse_args()
os.makedirs(
args.out_path, exist_ok=True)
vits_fe = TSVITSFE()
print("Loading model...")
vits_fe.load(args.checkpoint,args.config,args.device)
print("Doing inference...")
out_aud = vits_fe.infer(args.text)
out_fn = os.path.join(args.out_path,"audio1.wav")
sf.write(out_fn, out_aud, vits_fe.hps.data.sampling_rate)
print(f"Wrote audio file {out_fn}")