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import romajitable
import re
import numpy as np
import logging
logging.getLogger('numba').setLevel(logging.WARNING)
import IPython.display as ipd
import torch
import commons
import utils
from models import SynthesizerTrn
from text.symbols import symbols
from text import text_to_sequence
import gradio as gr
import time
import datetime
import os
def get_text(text, hps):
text_norm = text_to_sequence(text, symbols, hps.data.text_cleaners)
if hps.data.add_blank:
text_norm = commons.intersperse(text_norm, 0)
text_norm = torch.LongTensor(text_norm)
return text_norm
dev = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
def selection(speaker):
if speaker == "高咲侑":
spk = 0
return spk
elif speaker == "歩夢":
spk = 1
return spk
elif speaker == "かすみ":
spk = 2
return spk
elif speaker == "しずく":
spk = 3
return spk
elif speaker == "果林":
spk = 4
return spk
elif speaker == "愛":
spk = 5
return spk
elif speaker == "彼方":
spk = 6
return spk
elif speaker == "せつ菜":
spk = 7
return spk
elif speaker == "エマ":
spk = 8
return spk
elif speaker == "璃奈":
spk = 9
return spk
elif speaker == "栞子":
spk = 10
return spk
elif speaker == "ランジュ":
spk = 11
return spk
elif speaker == "ミア":
spk = 12
return spk
elif speaker == "三色绘恋1":
spk = 13
return spk
elif speaker == "三色绘恋2":
spk = 15
elif speaker == "派蒙":
spk = 16
return spk
def is_japanese(string):
for ch in string:
if ord(ch) > 0x3040 and ord(ch) < 0x30FF:
return True
return False
def is_english(string):
import re
pattern = re.compile('^[A-Za-z0-9.,:;!?()_*"\' ]+$')
if pattern.fullmatch(string):
return True
else:
return False
def sle(language,tts_input0):
if language == "中文":
tts_input1 = "[ZH]" + tts_input0.replace('\n','。').replace(' ',',') + "[ZH]"
return tts_input1
if language == "自动":
tts_input1 = f"[JA]{tts_input0}[JA]" if is_japanese(tts_input0) else f"[ZH]{tts_input0}[ZH]"
return tts_input1
elif language == "日文":
tts_input1 = "[JA]" + tts_input0.replace('\n','。').replace(' ',',') + "[JA]"
return tts_input1
def extrac(text):
text = re.sub("<[^>]*>","",text)
result_list = re.split(r'\n', text)
final_list = []
for i in result_list:
if is_english(i):
i = romajitable.to_kana(i).katakana
i = i.replace('\n','').replace(' ','')
#Current length of single sentence: 20
if len(i)>1:
if len(i) > 20:
try:
cur_list = re.split(r'。|!', i)
for i in cur_list:
if len(i)>1:
final_list.append(i+'。')
except:
pass
else:
final_list.append(i)
final_list = [x for x in final_list if x != '']
print(final_list)
return final_list
def infer(text ,language, speaker_id,n_scale= 0.667,n_scale_w = 0.8, l_scale = 1):
speaker_id = int(selection(speaker_id))
a = ['【','[','(','(']
b = ['】',']',')',')']
for i in a:
text = text.replace(i,'<')
for i in b:
text = text.replace(i,'>')
final_list = extrac(text.replace('“','').replace('”',''))
audio_fin = []
c = 0
t = datetime.timedelta(seconds=0)
f1 = open("subtitles.srt",'w',encoding='utf-8')
for sentence in final_list:
c +=1
stn_tst = get_text(sle(language,sentence), hps_ms)
with torch.no_grad():
x_tst = stn_tst.unsqueeze(0).to(dev)
x_tst_lengths = torch.LongTensor([stn_tst.size(0)]).to(dev)
sid = torch.LongTensor([speaker_id]).to(dev)
t1 = time.time()
audio = net_g_ms.infer(x_tst, x_tst_lengths, sid=sid, noise_scale=n_scale, noise_scale_w=n_scale_w, length_scale=l_scale)[0][0,0].data.cpu().float().numpy()
t2 = time.time()
spending_time = "第"+str(c)+"句的推理时间为:"+str(t2-t1)+"s"
print(spending_time)
time_start = str(t).split(".")[0] + "," + str(t.microseconds)[:3]
last_time = datetime.timedelta(seconds=len(audio)/float(22050))
t+=last_time
time_end = str(t).split(".")[0] + "," + str(t.microseconds)[:3]
print(time_end)
f1.write(str(c-1)+'\n'+time_start+' --> '+time_end+'\n'+sentence+'\n\n')
audio_fin.append(audio)
file_path = "subtitles.srt"
return (hps_ms.data.sampling_rate, np.concatenate(audio_fin)),file_path
lan = ["中文","日文","自动"]
idols = ["高咲侑","歩夢","かすみ","しずく","果林","愛","せつ菜","璃奈","栞子","エマ","ランジュ","ミア","派蒙"]
hps_ms = utils.get_hparams_from_file("lovelive/config.json")
net_g_ms = SynthesizerTrn(
len(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).to(dev)
_ = net_g_ms.eval()
_ = utils.load_checkpoint("lovelive/G_936000.pth", net_g_ms)
inputs = [gr.TextArea(label="如需实现快速合成,建议在colab上克隆后运行本仓库", value="为什么你会那么熟练啊?你和雪菜亲过多少次了?我想做只属于你一个人的学院偶像,所以,请只注视我一个人,好吗?【中文】\nなんでそんなに慣れてんだよっ?せつ菜と…何回キスしたんだよ?どこまであたしを置いてきぼりにすれば気が済むんだよ?[日文]\nI can't choose just one(English)"),
gr.Dropdown(label="选择语言,目前勉强可以做到自动识别",choices=lan, value="自动", interactive=True),
gr.Dropdown(label="选择说话人",choices=idols, value="歩夢", interactive=True),
gr.Slider(minimum= 0,maximum=1.0,label="更改噪声比例,以控制情感", value=0.267),
gr.Slider(minimum= 0,maximum=1.0,label="更改噪声偏差,以控制音素长短", value=0.7),
gr.Slider(minimum= 0.1,maximum=10,label="更改时间比例", value=1)]
outputs=[gr.Audio(label="采样率22050"), gr.outputs.File(label="字幕文件:subtitles.srt")]
iface = gr.Interface(
fn=infer,
inputs=inputs,
outputs=outputs,
title="Vits",
description="虹团11人模型",
)
iface.launch()