mirror of
https://github.com/storytold/storyteller-ml.git
synced 2026-10-21 08:06:47 +00:00
49 lines
2.3 KiB
Python
49 lines
2.3 KiB
Python
# FakeYou StyleTTS 2 Inference
|
|
|
|
import os
|
|
import torch
|
|
import argparse
|
|
import numpy as np
|
|
import soundfile as sf
|
|
from styletts2importable import compute_style, inference
|
|
from tortoise.utils.text import split_and_recombine_text
|
|
|
|
def clsynthesize(text_file_path, voice_path, vcsteps, style_npz_path=None, npz_output_path=None):
|
|
# Load the text from the file
|
|
with open(text_file_path, 'r', encoding="utf-8") as file:
|
|
text = file.read()
|
|
|
|
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
|
|
|
|
if style_npz_path and os.path.exists(style_npz_path):
|
|
# Load style vector from NPZ file
|
|
style_vector_np = np.load(style_npz_path)['style_vector']
|
|
custom_voice = torch.from_numpy(style_vector_np).float().to(device)
|
|
elif voice_path:
|
|
# Compute and save style vector
|
|
custom_voice = compute_style(voice_path, save_npz=True, npz_path=npz_output_path or "default_output_path.npz").to(device)
|
|
else:
|
|
raise ValueError("Either a voice path or an input style NPZ file must be provided")
|
|
|
|
texts = split_and_recombine_text(text)
|
|
audios = [inference(t, custom_voice, alpha=0.3, beta=0.7, diffusion_steps=vcsteps, embedding_scale=1) for t in texts]
|
|
|
|
return 24000, np.concatenate(audios)
|
|
|
|
def main():
|
|
parser = argparse.ArgumentParser(description='CLI for StyleTTS Voice Synthesis')
|
|
parser.add_argument('--input', type=str, required=True, help='Path to the text file')
|
|
parser.add_argument('--voice', type=str, help='Path to the custom voice audio file (optional if using --input-style-npz)')
|
|
parser.add_argument('--vcsteps', type=int, required=True, help='Number of diffusion steps')
|
|
parser.add_argument('--output', type=str, help='Output path for the synthesized audio file (optional)')
|
|
parser.add_argument('--input-style-npz', type=str, help='Path to the input style vector NPZ file')
|
|
parser.add_argument('--output-style-npz', type=str, help='Output path for the style vector NPZ file')
|
|
args = parser.parse_args()
|
|
|
|
if args.output:
|
|
sample_rate, audio = clsynthesize(args.input, args.voice, args.vcsteps, args.input_style_npz, args.output_style_npz)
|
|
sf.write(args.output, audio, sample_rate)
|
|
|
|
if __name__ == "__main__":
|
|
main()
|