# 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
from gradio_client import utils as client_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 client_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 = ["Honkai: Star Rail", "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 = ["Honkai: Star Rail", "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\n"
"[](https://colab.research.google.com/drive/10QOk9NPgoKZUXkIhhuVaZ7SYra1MPMKH?usp=share_link)\n\n"
"[](https://huggingface.co/spaces/sayashi/vits-models?duplicate=true)\n\n"
"[](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)