Spaces:
Build error
Build error
File size: 9,346 Bytes
b875bd7 3fd0c0d b875bd7 3fd0c0d b875bd7 b54579f b875bd7 3fd0c0d b875bd7 b54579f b875bd7 3fd0c0d b875bd7 3fd0c0d b875bd7 3fd0c0d b875bd7 d95ac39 b875bd7 3fd0c0d b875bd7 3fd0c0d b54579f b875bd7 3fd0c0d b54579f b875bd7 b3bac56 b54579f 4133e57 b875bd7 b54579f b875bd7 f4da48c b875bd7 b54579f b875bd7 b54579f b875bd7 a974a24 b875bd7 d95ac39 b875bd7 d95ac39 b875bd7 b54579f b875bd7 f4da48c b875bd7 b54579f b875bd7 b54579f b875bd7 a974a24 b875bd7 d95ac39 b875bd7 d95ac39 b875bd7 b3bac56 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 |
# 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"
"![visitor badge](https://visitor-badge.glitch.me/badge?page_id=sayashi.vits-models)\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"
"[Finetune your own model](https://github.com/SayaSS/vits-finetuning)"
)
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)
|