Spaces:
Running
Running
# 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, _clean_text | |
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, is_symbol): | |
text_norm, clean_text = text_to_sequence(text, hps.symbols, [] if is_symbol else 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, is_symbol): | |
text = text.replace('\n', ' ').replace('\r', '').replace(" ", "") | |
if limitation: | |
text_len = len(re.sub("\[([A-Z]{2})\]", "", text)) | |
max_len = 100 | |
if is_symbol: | |
max_len *= 3 | |
if text_len > max_len: | |
return "Error: Text is too long", None | |
if not is_symbol: | |
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, is_symbol) | |
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 create_to_symbol_fn(hps): | |
def to_symbol_fn(is_symbol_input, input_text, temp_lang): | |
if temp_lang == 0: | |
clean_text = f'[ZH]{input_text}[ZH]' | |
elif temp_lang == 1: | |
clean_text = f'[JA]{input_text}[JA]' | |
else: | |
clean_text = input_text | |
return _clean_text(clean_text, hps.data.text_cleaners) if is_symbol_input else '' | |
return to_symbol_fn | |
def change_lang(language): | |
if language == 0: | |
return 0.6, 0.668, 1.2 | |
elif language == 1: | |
return 0.6, 0.668, 1 | |
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('--api', action="store_true", default=False) | |
parser.add_argument("--share", action="store_true", default=False, help="share gradio app") | |
parser.add_argument("--all", action="store_true", default=False, help="enable all models") | |
args = parser.parse_args() | |
device = torch.device(args.device) | |
categories = ["Blue Archive", "Lycoris Recoil"] | |
others = { | |
"Princess Connect! Re:Dive": "https://huggingface.co/spaces/sayashi/vits-models-pcr", | |
"Genshin Impact": "https://huggingface.co/spaces/sayashi/vits-models-genshin-bh3", | |
"Honkai Impact 3rd": "https://huggingface.co/spaces/sayashi/vits-models-genshin-bh3", | |
"Overwatch 2": "https://huggingface.co/spaces/sayashi/vits-models-ow2", | |
} | |
if args.all: | |
categories = ["Blue Archive", "Lycoris Recoil", "Princess Connect! Re:Dive", "Genshin Impact", "Honkai Impact 3rd", "Overwatch 2"] | |
others = {} | |
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(): | |
if info['title'].split("-")[0] not in categories or not info['enable']: | |
continue | |
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 if info['type'] == "multi" else 0, | |
**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), create_to_symbol_fn(hps_ms))) | |
with gr.Blocks() as app: | |
gr.Markdown( | |
"# <center> vits-models\n" | |
"## <center> Please do not generate content that could infringe upon the rights or cause harm to individuals or organizations.\n" | |
"## <center> 请不要生成会对个人以及组织造成侵害的内容\n" | |
"![visitor badge](https://visitor-badge.glitch.me/badge?page_id=sayashi.vits-models)\n\n" | |
"[![image](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/10QOk9NPgoKZUXkIhhuVaZ7SYra1MPMKH?usp=share_link)\n\n" | |
"[![Duplicate this Space](https://huggingface.co/datasets/huggingface/badges/raw/main/duplicate-this-space-sm-dark.svg)](https://huggingface.co/spaces/sayashi/vits-models?duplicate=true)\n\n" | |
"[![Finetune your own model](https://badgen.net/badge/icon/github?icon=github&label=Finetune%20your%20own%20model)](https://github.com/SayaSS/vits-finetuning)" | |
) | |
with gr.Tabs(): | |
for category in categories: | |
with gr.TabItem(category): | |
with gr.TabItem("EN"): | |
for (sid, name_en, name_zh, title, cover, example, language, net_g_ms, tts_fn, to_symbol_fn) in models: | |
if title.split("-")[0] != category: | |
continue | |
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)" if limitation else "Text", 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) | |
with gr.Accordion(label="Advanced Options", open=False): | |
symbol_input = gr.Checkbox(value=False, label="Symbol input") | |
symbol_list = gr.Dataset(label="Symbol list", components=[input_text], | |
samples=[[x] for x in hps_ms.symbols]) | |
symbol_list_json = gr.Json(value=hps_ms.symbols, visible=False) | |
btn = gr.Button(value="Generate", variant="primary") | |
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, symbol_input], outputs=[o1, o2], api_name=f"tts-{name_en}") | |
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]) | |
symbol_input.change( | |
to_symbol_fn, | |
[symbol_input, input_text, lang], | |
[input_text] | |
) | |
symbol_list.click(None, [symbol_list, symbol_list_json], [input_text], | |
_js=f""" | |
(i,symbols) => {{ | |
let root = document.querySelector("body > gradio-app"); | |
if (root.shadowRoot != null) | |
root = root.shadowRoot; | |
let text_input = root.querySelector("#input-text-en-{name_en.replace(' ', '')}").querySelector("textarea"); | |
let startPos = text_input.selectionStart; | |
let endPos = text_input.selectionEnd; | |
let oldTxt = text_input.value; | |
let result = oldTxt.substring(0, startPos) + symbols[i] + oldTxt.substring(endPos); | |
text_input.value = result; | |
let x = window.scrollX, y = window.scrollY; | |
text_input.focus(); | |
text_input.selectionStart = startPos + symbols[i].length; | |
text_input.selectionEnd = startPos + symbols[i].length; | |
text_input.blur(); | |
window.scrollTo(x, y); | |
return text_input.value; | |
}}""") | |
with gr.TabItem("中文"): | |
for (sid, name_en, name_zh, title, cover, example, language, net_g_ms, tts_fn, to_symbol_fn) in models: | |
if title.split("-")[0] != category: | |
continue | |
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)" if limitation else "文本", 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") | |
with gr.Accordion(label="高级选项", open=False): | |
symbol_input = gr.Checkbox(value=False, label="符号输入") | |
symbol_list = gr.Dataset(label="符号列表", components=[input_text], | |
samples=[[x] for x in hps_ms.symbols]) | |
symbol_list_json = gr.Json(value=hps_ms.symbols, visible=False) | |
btn = gr.Button(value="生成", variant="primary") | |
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, symbol_input], 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]) | |
symbol_input.change( | |
to_symbol_fn, | |
[symbol_input, input_text, lang], | |
[input_text] | |
) | |
symbol_list.click(None, [symbol_list, symbol_list_json], [input_text], | |
_js=f""" | |
(i,symbols) => {{ | |
let root = document.querySelector("body > gradio-app"); | |
if (root.shadowRoot != null) | |
root = root.shadowRoot; | |
let text_input = root.querySelector("#input-text-zh-{name_zh}").querySelector("textarea"); | |
let startPos = text_input.selectionStart; | |
let endPos = text_input.selectionEnd; | |
let oldTxt = text_input.value; | |
let result = oldTxt.substring(0, startPos) + symbols[i] + oldTxt.substring(endPos); | |
text_input.value = result; | |
let x = window.scrollX, y = window.scrollY; | |
text_input.focus(); | |
text_input.selectionStart = startPos + symbols[i].length; | |
text_input.selectionEnd = startPos + symbols[i].length; | |
text_input.blur(); | |
window.scrollTo(x, y); | |
return text_input.value; | |
}}""") | |
for category, link in others.items(): | |
with gr.TabItem(category): | |
gr.Markdown( | |
f''' | |
<center> | |
<h2>Click to Go</h2> | |
<a href="{link}"> | |
<img src="https://huggingface.co/datasets/huggingface/badges/raw/main/open-in-hf-spaces-xl-dark.svg" | |
</a> | |
</center> | |
''' | |
) | |
app.queue(concurrency_count=1, api_open=args.api).launch(share=args.share) | |