import argparse from pathlib import Path import gradio as gr import torch import yaml from gradio_tabs.dataset import create_dataset_app from gradio_tabs.inference import create_inference_app from gradio_tabs.merge import create_merge_app from gradio_tabs.style_vectors import create_style_vectors_app from gradio_tabs.train import create_train_app from style_bert_vits2.constants import GRADIO_THEME, VERSION from style_bert_vits2.nlp.japanese import pyopenjtalk_worker from style_bert_vits2.nlp.japanese.user_dict import update_dict from style_bert_vits2.tts_model import TTSModelHolder # このプロセスからはワーカーを起動して辞書を使いたいので、ここで初期化 pyopenjtalk_worker.initialize_worker() # dict_data/ 以下の辞書データを pyopenjtalk に適用 update_dict() # Get path settings with Path("configs/paths.yml").open("r", encoding="utf-8") as f: path_config: dict[str, str] = yaml.safe_load(f.read()) # dataset_root = path_config["dataset_root"] assets_root = path_config["assets_root"] parser = argparse.ArgumentParser() parser.add_argument("--device", type=str, default="cuda") parser.add_argument("--host", type=str, default="127.0.0.1") parser.add_argument("--port", type=int, default=None) parser.add_argument("--no_autolaunch", action="store_true") parser.add_argument("--share", action="store_true") args = parser.parse_args() device = args.device if device == "cuda" and not torch.cuda.is_available(): device = "cpu" model_holder = TTSModelHolder(Path(assets_root), device) with gr.Blocks(theme=GRADIO_THEME) as app: gr.Markdown(f"# Style-Bert-VITS2 WebUI (version {VERSION})") with gr.Tabs(): with gr.Tab("音声合成"): create_inference_app(model_holder=model_holder) with gr.Tab("データセット作成"): create_dataset_app() with gr.Tab("学習"): create_train_app() with gr.Tab("スタイル作成"): create_style_vectors_app() with gr.Tab("マージ"): create_merge_app(model_holder=model_holder) app.launch( server_name=args.host, server_port=args.port, inbrowser=not args.no_autolaunch, share=args.share, )