import datetime from pathlib import Path import gradio as gr import random from style_bert_vits2.constants import ( DEFAULT_LENGTH, DEFAULT_LINE_SPLIT, DEFAULT_NOISE, DEFAULT_NOISEW, DEFAULT_SPLIT_INTERVAL, ) from style_bert_vits2.logging import logger from style_bert_vits2.models.infer import InvalidToneError from style_bert_vits2.nlp.japanese import pyopenjtalk_worker as pyopenjtalk from style_bert_vits2.tts_model import TTSModelHolder pyopenjtalk.initialize_worker() example_file = "chupa_examples.txt" initial_text = ( "ちゅぱ、ちゅるる、ぢゅ、んく、れーれゅれろれろれろ、じゅぽぽぽぽぽ……ちゅううう！" ) with open(example_file, "r", encoding="utf-8") as f: examples = f.read().splitlines() def get_random_text() -> str: return random.choice(examples) initial_md = """ # チュパ音合成デモ 2024-07-07: initial ver """ def make_interactive(): return gr.update(interactive=True, value="音声合成") def make_non_interactive(): return gr.update(interactive=False, value="音声合成（モデルをロードしてください）") def gr_util(item): if item == "プリセットから選ぶ": return (gr.update(visible=True), gr.Audio(visible=False, value=None)) else: return (gr.update(visible=False), gr.update(visible=True)) def create_inference_app(model_holder: TTSModelHolder) -> gr.Blocks: def tts_fn( model_name, model_path, text, language, sdp_ratio, noise_scale, noise_scale_w, length_scale, line_split, split_interval, speaker, ): model_holder.get_model(model_name, model_path) assert model_holder.current_model is not None speaker_id = model_holder.current_model.spk2id[speaker] start_time = datetime.datetime.now() try: sr, audio = model_holder.current_model.infer( text=text, language=language, sdp_ratio=sdp_ratio, noise=noise_scale, noise_w=noise_scale_w, length=length_scale, line_split=line_split, split_interval=split_interval, speaker_id=speaker_id, ) except InvalidToneError as e: logger.error(f"Tone error: {e}") return f"Error: アクセント指定が不正です:\n{e}", None except ValueError as e: logger.error(f"Value error: {e}") return f"Error: {e}", None end_time = datetime.datetime.now() duration = (end_time - start_time).total_seconds() message = f"Success, time: {duration} seconds." return message, (sr, audio) def get_model_files(model_name: str): return [str(f) for f in model_holder.model_files_dict[model_name]] model_names = model_holder.model_names if len(model_names) == 0: logger.error( f"モデルが見つかりませんでした。{model_holder.root_dir}にモデルを置いてください。" ) with gr.Blocks() as app: gr.Markdown( f"Error: モデルが見つかりませんでした。{model_holder.root_dir}にモデルを置いてください。" ) return app initial_pth_files = get_model_files(model_names[0]) model = model_holder.get_model(model_names[0], initial_pth_files[0]) speakers = list(model.spk2id.keys()) with gr.Blocks(theme="ParityError/Anime") as app: gr.Markdown(initial_md) with gr.Row(): with gr.Column(): with gr.Row(): with gr.Column(scale=3): model_name = gr.Dropdown( label="モデル一覧", choices=model_names, value=model_names[0], ) model_path = gr.Dropdown( label="モデルファイル", choices=initial_pth_files, value=initial_pth_files[0], ) refresh_button = gr.Button("更新", scale=1, visible=False) load_button = gr.Button("ロード", scale=1, variant="primary") with gr.Row(): text_input = gr.TextArea( label="テキスト", value=initial_text, scale=3 ) random_button = gr.Button("例から選ぶ 🎲", scale=1) random_button.click(get_random_text, outputs=[text_input]) with gr.Row(): length_scale = gr.Slider( minimum=0.1, maximum=2, value=DEFAULT_LENGTH, step=0.1, label="生成音声の長さ（Length）", ) sdp_ratio = gr.Slider( minimum=0, maximum=1, value=1, step=0.1, label="SDP Ratio", ) line_split = gr.Checkbox( label="改行で分けて生成（分けたほうが感情が乗ります）", value=DEFAULT_LINE_SPLIT, visible=False, ) split_interval = gr.Slider( minimum=0.0, maximum=2, value=DEFAULT_SPLIT_INTERVAL, step=0.1, label="改行ごとに挟む無音の長さ（秒）", ) line_split.change( lambda x: (gr.Slider(visible=x)), inputs=[line_split], outputs=[split_interval], ) language = gr.Dropdown( choices=["JP"], value="JP", label="Language", visible=False ) speaker = gr.Dropdown(label="話者", choices=speakers, value=speakers[0]) with gr.Accordion(label="詳細設定", open=True): noise_scale = gr.Slider( minimum=0.1, maximum=2, value=DEFAULT_NOISE, step=0.1, label="Noise", ) noise_scale_w = gr.Slider( minimum=0.1, maximum=2, value=DEFAULT_NOISEW, step=0.1, label="Noise_W", ) with gr.Column(): tts_button = gr.Button("音声合成", variant="primary") text_output = gr.Textbox(label="情報") audio_output = gr.Audio(label="結果") tts_button.click( tts_fn, inputs=[ model_name, model_path, text_input, language, sdp_ratio, noise_scale, noise_scale_w, length_scale, line_split, split_interval, speaker, ], outputs=[text_output, audio_output], ) model_name.change( model_holder.update_model_files_for_gradio, inputs=[model_name], outputs=[model_path], ) model_path.change(make_non_interactive, outputs=[tts_button]) refresh_button.click( model_holder.update_model_names_for_gradio, outputs=[model_name, model_path, tts_button], ) style = gr.Dropdown(label="スタイル", choices=[], visible=False) load_button.click( model_holder.get_model_for_gradio, inputs=[model_name, model_path], outputs=[style, tts_button, speaker], ) return app if __name__ == "__main__": import torch from style_bert_vits2.constants import Languages from style_bert_vits2.nlp import bert_models bert_models.load_model(Languages.JP) bert_models.load_tokenizer(Languages.JP) device = "cuda" if torch.cuda.is_available() else "cpu" model_holder = TTSModelHolder(Path("model_assets"), device) app = create_inference_app(model_holder) app.launch(inbrowser=True)