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# coding=utf-8
import os
import re
import utils
import commons
import json
import gradio as gr
from models import SynthesizerTrn
from text import text_to_sequence
from torch import no_grad, LongTensor
import logging
logging.getLogger('numba').setLevel(logging.WARNING)
hps_ms = utils.get_hparams_from_file(r'config/config.json')
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(" ", "")
text_len = len(re.sub("\[([A-Z]{2})\]", "", text))
max_len = 150
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)
x_tst_lengths = LongTensor([stn_tst.size(0)])
sid = LongTensor([speaker_id])
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.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").querySelector("audio");
let text = root.querySelector("#input-text").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__':
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():
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)
_ = net_g_ms.eval()
sid = info['sid']
name_en = info['name_en']
name_zh = info['name_zh']
title = info['title']
cover = f"pretrained_models/{i}/{info['cover']}"
utils.load_checkpoint(f'pretrained_models/{i}/{i}.pth', net_g_ms, None)
models.append((sid, name_en, name_zh, title, cover, net_g_ms, create_tts_fn(net_g_ms, sid)))
with gr.Blocks() as app:
gr.Markdown(
"# <center> vits-models\n"
"\n\n"
)
with gr.Tabs():
with gr.TabItem("EN"):
for (sid, name_en, name_zh, title, cover, 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="先生。今日も全力であなたをアシストしますね。", elem_id=f"input-text")
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="Japanese")
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, interactive=True)
with gr.Column():
o1 = gr.Textbox(label="Output Message")
o2 = gr.Audio(label="Output Audio", elem_id=f"tts-audio")
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())
lang.change(change_lang, inputs=[lang], outputs=[ns, nsw, ls])
with gr.TabItem("中文"):
for (sid, name_en, name_zh, title, cover, 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="先生。今日も全力であなたをアシストしますね。", elem_id=f"input-text")
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="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, 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")
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())
lang.change(change_lang, inputs=[lang], outputs=[ns, nsw, ls])
app.queue(concurrency_count=1).launch()
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