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| # coding=utf-8 | |
| import os | |
| import re | |
| import argparse | |
| import utils | |
| import commons | |
| import json | |
| import torch | |
| import gradio as gr | |
| from models import SynthesizerTrn | |
| from text import text_to_sequence | |
| from torch import no_grad, LongTensor | |
| import gradio.processing_utils as gr_processing_utils | |
| import logging | |
| logging.getLogger('numba').setLevel(logging.WARNING) | |
| limitation = os.getenv("SYSTEM") == "spaces" # limit text and audio length in huggingface spaces | |
| hps_ms = utils.get_hparams_from_file(r'config/config.json') | |
| audio_postprocess_ori = gr.Audio.postprocess | |
| def audio_postprocess(self, y): | |
| data = audio_postprocess_ori(self, y) | |
| if data is None: | |
| return None | |
| return gr_processing_utils.encode_url_or_file_to_base64(data["name"]) | |
| gr.Audio.postprocess = audio_postprocess | |
| def get_text(text, hps): | |
| text_norm, clean_text = text_to_sequence(text, hps.symbols, hps.data.text_cleaners) | |
| if hps.data.add_blank: | |
| text_norm = commons.intersperse(text_norm, 0) | |
| text_norm = LongTensor(text_norm) | |
| return text_norm, clean_text | |
| def create_tts_fn(net_g_ms, speaker_id): | |
| def tts_fn(text, language, noise_scale, noise_scale_w, length_scale): | |
| text = text.replace('\n', ' ').replace('\r', '').replace(" ", "") | |
| if limitation: | |
| text_len = len(re.sub("\[([A-Z]{2})\]", "", text)) | |
| max_len = 100 | |
| if text_len > max_len: | |
| return "Error: Text is too long", None | |
| if language == 0: | |
| text = f"[ZH]{text}[ZH]" | |
| elif language == 1: | |
| text = f"[JA]{text}[JA]" | |
| else: | |
| text = f"{text}" | |
| stn_tst, clean_text = get_text(text, hps_ms) | |
| with no_grad(): | |
| x_tst = stn_tst.unsqueeze(0).to(device) | |
| x_tst_lengths = LongTensor([stn_tst.size(0)]).to(device) | |
| sid = LongTensor([speaker_id]).to(device) | |
| audio = net_g_ms.infer(x_tst, x_tst_lengths, sid=sid, noise_scale=noise_scale, noise_scale_w=noise_scale_w, | |
| length_scale=length_scale)[0][0, 0].data.cpu().float().numpy() | |
| return "Success", (22050, audio) | |
| return tts_fn | |
| def change_lang(language): | |
| if language == 0: | |
| return 0.6, 0.668, 1.2 | |
| else: | |
| return 0.6, 0.668, 1 | |
| download_audio_js = """ | |
| () =>{{ | |
| let root = document.querySelector("body > gradio-app"); | |
| if (root.shadowRoot != null) | |
| root = root.shadowRoot; | |
| let audio = root.querySelector("#tts-audio-{audio_id}").querySelector("audio"); | |
| let text = root.querySelector("#input-text-{audio_id}").querySelector("textarea"); | |
| if (audio == undefined) | |
| return; | |
| text = text.value; | |
| if (text == undefined) | |
| text = Math.floor(Math.random()*100000000); | |
| audio = audio.src; | |
| let oA = document.createElement("a"); | |
| oA.download = text.substr(0, 20)+'.wav'; | |
| oA.href = audio; | |
| document.body.appendChild(oA); | |
| oA.click(); | |
| oA.remove(); | |
| }} | |
| """ | |
| if __name__ == '__main__': | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument('--device', type=str, default='cpu') | |
| parser.add_argument("--share", action="store_true", default=False, help="share gradio app") | |
| args = parser.parse_args() | |
| device = torch.device(args.device) | |
| models = [] | |
| with open("pretrained_models/info.json", "r", encoding="utf-8") as f: | |
| models_info = json.load(f) | |
| for i, info in models_info.items(): | |
| sid = info['sid'] | |
| name_en = info['name_en'] | |
| name_zh = info['name_zh'] | |
| title = info['title'] | |
| cover = f"pretrained_models/{i}/{info['cover']}" | |
| example = info['example'] | |
| language = info['language'] | |
| net_g_ms = SynthesizerTrn( | |
| len(hps_ms.symbols), | |
| hps_ms.data.filter_length // 2 + 1, | |
| hps_ms.train.segment_size // hps_ms.data.hop_length, | |
| n_speakers=hps_ms.data.n_speakers, | |
| **hps_ms.model) | |
| utils.load_checkpoint(f'pretrained_models/{i}/{i}.pth', net_g_ms, None) | |
| _ = net_g_ms.eval().to(device) | |
| models.append((sid, name_en, name_zh, title, cover, example, language, net_g_ms, create_tts_fn(net_g_ms, sid))) | |
| with gr.Blocks() as app: | |
| gr.Markdown( | |
| "# <center> vits-models\n" | |
| "\n\n" | |
| "[Open In Colab]" | |
| "(https://colab.research.google.com/drive/10QOk9NPgoKZUXkIhhuVaZ7SYra1MPMKH?usp=share_link)" | |
| " without queue and length limitation.(无需等待队列，并且没有长度限制)\n\n" | |
| ) | |
| with gr.Tabs(): | |
| with gr.TabItem("EN"): | |
| for (sid, name_en, name_zh, title, cover, example, language, net_g_ms, tts_fn) in models: | |
| with gr.TabItem(name_en): | |
| with gr.Row(): | |
| gr.Markdown( | |
| '<div align="center">' | |
| f'<a><strong>{title}</strong></a>' | |
| f'<img style="width:auto;height:300px;" src="file/{cover}">' if cover else "" | |
| '</div>' | |
| ) | |
| with gr.Row(): | |
| with gr.Column(): | |
| input_text = gr.Textbox(label="Text (100 words limitation)", lines=5, value=example, elem_id=f"input-text-en-{name_en.replace(' ','')}") | |
| lang = gr.Dropdown(label="Language", choices=["Chinese", "Japanese", "Mix（wrap the Chinese text with [ZH][ZH], wrap the Japanese text with [JA][JA]）"], | |
| type="index", value=language) | |
| btn = gr.Button(value="Generate") | |
| with gr.Row(): | |
| ns = gr.Slider(label="noise_scale", minimum=0.1, maximum=1.0, step=0.1, value=0.6, interactive=True) | |
| nsw = gr.Slider(label="noise_scale_w", minimum=0.1, maximum=1.0, step=0.1, value=0.668, interactive=True) | |
| ls = gr.Slider(label="length_scale", minimum=0.1, maximum=2.0, step=0.1, value=1.2 if language=="Chinese" else 1, interactive=True) | |
| with gr.Column(): | |
| o1 = gr.Textbox(label="Output Message") | |
| o2 = gr.Audio(label="Output Audio", elem_id=f"tts-audio-en-{name_en.replace(' ','')}") | |
| download = gr.Button("Download Audio") | |
| btn.click(tts_fn, inputs=[input_text, lang, ns, nsw, ls], outputs=[o1, o2]) | |
| download.click(None, [], [], _js=download_audio_js.format(audio_id=f"en-{name_en.replace(' ','')}")) | |
| lang.change(change_lang, inputs=[lang], outputs=[ns, nsw, ls]) | |
| with gr.TabItem("中文"): | |
| for (sid, name_en, name_zh, title, cover, example, language, net_g_ms, tts_fn) in models: | |
| with gr.TabItem(name_zh): | |
| with gr.Row(): | |
| gr.Markdown( | |
| '<div align="center">' | |
| f'<a><strong>{title}</strong></a>' | |
| f'<img style="width:auto;height:300px;" src="file/{cover}">' if cover else "" | |
| '</div>' | |
| ) | |
| with gr.Row(): | |
| with gr.Column(): | |
| input_text = gr.Textbox(label="文本 (100字上限)", lines=5, value=example, elem_id=f"input-text-zh-{name_zh}") | |
| lang = gr.Dropdown(label="语言", choices=["中文", "日语", "中日混合（中文用[ZH][ZH]包裹起来，日文用[JA][JA]包裹起来）"], | |
| type="index", value="中文"if language == "Chinese" else "日语") | |
| btn = gr.Button(value="生成") | |
| with gr.Row(): | |
| ns = gr.Slider(label="控制感情变化程度", minimum=0.1, maximum=1.0, step=0.1, value=0.6, interactive=True) | |
| nsw = gr.Slider(label="控制音素发音长度", minimum=0.1, maximum=1.0, step=0.1, value=0.668, interactive=True) | |
| ls = gr.Slider(label="控制整体语速", minimum=0.1, maximum=2.0, step=0.1, value=1.2 if language=="Chinese" else 1, interactive=True) | |
| with gr.Column(): | |
| o1 = gr.Textbox(label="输出信息") | |
| o2 = gr.Audio(label="输出音频", elem_id=f"tts-audio-zh-{name_zh}") | |
| download = gr.Button("下载音频") | |
| btn.click(tts_fn, inputs=[input_text, lang, ns, nsw, ls], outputs=[o1, o2]) | |
| download.click(None, [], [], _js=download_audio_js.format(audio_id=f"zh-{name_zh}")) | |
| lang.change(change_lang, inputs=[lang], outputs=[ns, nsw, ls]) | |
| app.queue(concurrency_count=1).launch(show_api=False, share=args.share) | |