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# flake8: noqa: E402 | |
import logging | |
logging.getLogger("numba").setLevel(logging.WARNING) | |
logging.getLogger("markdown_it").setLevel(logging.WARNING) | |
logging.getLogger("urllib3").setLevel(logging.WARNING) | |
logging.getLogger("matplotlib").setLevel(logging.WARNING) | |
logging.basicConfig( | |
level=logging.INFO, format="| %(name)s | %(levelname)s | %(message)s" | |
) | |
logger = logging.getLogger(__name__) | |
import datetime | |
import numpy as np | |
import torch | |
import zipfile | |
import shutil | |
import sys, os | |
import json | |
import argparse | |
import commons | |
import utils | |
from models import SynthesizerTrn | |
from text.symbols import symbols | |
from text import cleaned_text_to_sequence, get_bert | |
from text.cleaner import clean_text | |
import gradio as gr | |
import webbrowser | |
import re | |
from scipy.io.wavfile import write | |
net_g = None | |
import soundfile | |
BandList = { | |
"乃木坂46":["AKIMOTO_MANATSU" ,"ENDO_SAKURA" ,"ETO_MISA" ,"FUKAGAWA_MAI" ,"HARUKA_KUROMI" ,"HASHIMOTO_NANAMI" ,"HAYAKAWA_SEIRA" ,"HIGUCHI_HINA" ,"HORI_MIONA" ,"HOSHINO_MINAMI" , | |
"ICHINOSE_MIKU" ,"IKEDA_TERESA" ,"IKOMA_RINA" ,"IKUTA_ERIKA" ,"INOUE_NAGI" ,"INOUE_SAYURI" ,"IOKI_MAO" ,"ITO_JUNNA" ,"ITO_KARIN" ,"ITO_MARIKA" ,"ITO_RIRIA" ,"IWAMOTO_RENKA" , | |
"KAKEHASHI_SAYAKA" ,"KAKI_HARUKA" ,"KANAGAWA_SAYA" ,"KAWAGO_HINA" ,"KAWAMURA_MAHIRO" ,"KAWASAKI_SAKURA" ,"KITAGAWA_YURI" ,"KITANO_HINAKO" ,"KUBO_SHIORI" ,"MATSUMURA_SAYURI" , | |
"MIYU_MATSUO" ,"MUKAI_HAZUKI" ,"NAKADA_KANA" ,"NAKAMOTO_HIMEKA" ,"NAKAMURA_RENO" ,"NAKANISHI_ARUNO" ,"NAO_YUMIKI" ,"NISHINO_NANASE" ,"NOUJO_AMI" ,"OGAWA_AYA" ,"OKAMOTO_HINA" , | |
"OKUDA_IROHA" ,"OZONO_MOMOKO" ,"RIKA_SATO" ,"RUNA_HAYASHI" ,"SAGARA_IORI" ,"SAITO_ASUKA" ,"SAITO_CHIHARU" ,"SAKAGUCHI_TAMAMI" ,"SAKURAI_REIKA" ,"SASAKI_KOTOKO" ,"SATO_KAEDE" , | |
"SATO_YUURI" ,"SEIMIYA_REI" ,"SHIBATA_YUNA" ,"SHINUCHI_MAI" ,"SHIRAISHI_MAI" ,"SUGAWARA_SATSUKI" ,"SUZUKI_AYANE" ,"TAKAYAMA_KAZUMI" ,"TAMURA_MAYU" ,"TERADA_RANZE", | |
"TOMISATO_NAO" ,"TSUTSUI_AYAME" ,"UMEZAWA_MINAMI" ,"WADA_MAAYA" ,"WAKATSUKI_YUMI" ,"WATANABE_MIRIA" ,"YAKUBO_MIO" ,"YAMASHITA_MIZUKI" ,"YAMAZAKI_RENA" ,"YODA_YUUKI" ,"YOSHIDA_AYANO_CHRISTIE" | |
], | |
} | |
if sys.platform == "darwin" and torch.backends.mps.is_available(): | |
device = "mps" | |
os.environ["PYTORCH_ENABLE_MPS_FALLBACK"] = "1" | |
else: | |
device = "cuda" | |
def is_japanese(string): | |
for ch in string: | |
if ord(ch) > 0x3040 and ord(ch) < 0x30FF: | |
return True | |
return False | |
def extrac(text): | |
text = re.sub("<[^>]*>","",text) | |
result_list = re.split(r'\n', text) | |
final_list = [] | |
for i in result_list: | |
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.append(i) | |
''' | |
final_list = [x for x in final_list if x != ''] | |
return final_list | |
def get_text(text, language_str, hps): | |
norm_text, phone, tone, word2ph = clean_text(text, language_str) | |
phone, tone, language = cleaned_text_to_sequence(phone, tone, language_str) | |
if hps.data.add_blank: | |
phone = commons.intersperse(phone, 0) | |
tone = commons.intersperse(tone, 0) | |
language = commons.intersperse(language, 0) | |
for i in range(len(word2ph)): | |
word2ph[i] = word2ph[i] * 2 | |
word2ph[0] += 1 | |
bert = get_bert(norm_text, word2ph, language_str, device) | |
del word2ph | |
assert bert.shape[-1] == len(phone), phone | |
if language_str == "ZH": | |
bert = bert | |
ja_bert = torch.zeros(768, len(phone)) | |
elif language_str == "JA": | |
ja_bert = bert | |
bert = torch.zeros(1024, len(phone)) | |
else: | |
bert = torch.zeros(1024, len(phone)) | |
ja_bert = torch.zeros(768, len(phone)) | |
assert bert.shape[-1] == len( | |
phone | |
), f"Bert seq len {bert.shape[-1]} != {len(phone)}" | |
phone = torch.LongTensor(phone) | |
tone = torch.LongTensor(tone) | |
language = torch.LongTensor(language) | |
return bert, ja_bert, phone, tone, language | |
def infer(text, sdp_ratio, noise_scale, noise_scale_w, length_scale, sid, language): | |
print(text, sdp_ratio, noise_scale, noise_scale_w, length_scale, sid, language) | |
global net_g | |
bert, ja_bert, phones, tones, lang_ids = get_text(text, language, hps) | |
with torch.no_grad(): | |
x_tst = phones.to(device).unsqueeze(0) | |
tones = tones.to(device).unsqueeze(0) | |
lang_ids = lang_ids.to(device).unsqueeze(0) | |
bert = bert.to(device).unsqueeze(0) | |
ja_bert = ja_bert.to(device).unsqueeze(0) | |
x_tst_lengths = torch.LongTensor([phones.size(0)]).to(device) | |
del phones | |
speakers = torch.LongTensor([hps.data.spk2id[sid]]).to(device) | |
audio = ( | |
net_g.infer( | |
x_tst, | |
x_tst_lengths, | |
speakers, | |
tones, | |
lang_ids, | |
bert, | |
ja_bert, | |
sdp_ratio=sdp_ratio, | |
noise_scale=noise_scale, | |
noise_scale_w=noise_scale_w, | |
length_scale=length_scale, | |
)[0][0, 0] | |
.data.cpu() | |
.float() | |
.numpy() | |
) | |
del x_tst, tones, lang_ids, bert, x_tst_lengths, speakers | |
return audio | |
def tts_fn( | |
text, speaker, sdp_ratio, noise_scale, noise_scale_w, length_scale,LongSentence | |
): | |
if not LongSentence: | |
with torch.no_grad(): | |
audio = infer( | |
text, | |
sdp_ratio=sdp_ratio, | |
noise_scale=noise_scale, | |
noise_scale_w=noise_scale_w, | |
length_scale=length_scale, | |
sid=speaker, | |
language= "JP" if is_japanese(text) else "ZH", | |
) | |
torch.cuda.empty_cache() | |
return (hps.data.sampling_rate, audio) | |
else: | |
audiopath = 'voice.wav' | |
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 = [] | |
for sentence in final_list: | |
with torch.no_grad(): | |
audio = infer( | |
sentence, | |
sdp_ratio=sdp_ratio, | |
noise_scale=noise_scale, | |
noise_scale_w=noise_scale_w, | |
length_scale=length_scale, | |
sid=speaker, | |
language= "JP" if is_japanese(text) else "ZH", | |
) | |
audio_fin.append(audio) | |
soundfile.write("tts_output.mp3", np.concatenate(audio_fin), 44100, format="mp3") | |
return ("tts_output.mp3" ) | |
def split_into_sentences(text): | |
"""将文本分割为句子,基于中文的标点符号""" | |
sentences = re.split(r'(?<=[。!?…\n])', text) | |
return [sentence.strip() for sentence in sentences if sentence] | |
def seconds_to_ass_time(seconds): | |
"""将秒数转换为ASS时间格式""" | |
hours = int(seconds / 3600) | |
minutes = int((seconds % 3600) / 60) | |
seconds = int(seconds) % 60 | |
milliseconds = int((seconds - int(seconds)) * 1000) | |
return "{:01d}:{:02d}:{:02d}.{:02d}".format(hours, minutes, seconds, int(milliseconds / 10)) | |
if __name__ == "__main__": | |
parser = argparse.ArgumentParser() | |
parser.add_argument( | |
"-m", "--model", default="./N/G_51000.pth", help="path of your model" | |
) | |
parser.add_argument( | |
"-c", | |
"--config", | |
default="./N/config.json", | |
help="path of your config file", | |
) | |
parser.add_argument( | |
"--share", default=True, help="make link public", action="store_true" | |
) | |
parser.add_argument( | |
"-d", "--debug", action="store_true", help="enable DEBUG-LEVEL log" | |
) | |
args = parser.parse_args() | |
if args.debug: | |
logger.info("Enable DEBUG-LEVEL log") | |
logging.basicConfig(level=logging.DEBUG) | |
hps = utils.get_hparams_from_file(args.config) | |
device = ( | |
"cuda:0" | |
if torch.cuda.is_available() | |
else ( | |
"mps" | |
if sys.platform == "darwin" and torch.backends.mps.is_available() | |
else "cpu" | |
) | |
) | |
net_g = SynthesizerTrn( | |
len(symbols), | |
hps.data.filter_length // 2 + 1, | |
hps.train.segment_size // hps.data.hop_length, | |
n_speakers=hps.data.n_speakers, | |
**hps.model, | |
).to(device) | |
_ = net_g.eval() | |
_ = utils.load_checkpoint(args.model, net_g, None, skip_optimizer=True) | |
speaker_ids = hps.data.spk2id | |
speakers = list(speaker_ids.keys()) | |
languages = ["ZH", "JP"] | |
with gr.Blocks() as app: | |
gr.Markdown( | |
f"其他玩具:乃 木 坂 4 6 Sovits音色转换ai翻唱:<a href='https://sovits4.nogizaka46.cc/'>sovits4.nogizaka46.cc" | |
) | |
gr.Markdown( | |
f"【乃 木 坂 4 6全员TTS】,使用本模型请严格遵守法律法规!\n 发布二创作品请标注本项目网址<a href='https://vits.nogizaka46.cc/'>vits.nogizaka46.cc</a>" | |
) | |
for band in BandList: | |
with gr.TabItem(band): | |
for name in BandList[band]: | |
with gr.TabItem(name): | |
with gr.Row(): | |
#with gr.Column(): | |
#with gr.Row(): | |
#gr.Markdown( | |
#'<div align="center">' | |
#f'<img style="width:auto;height:400px;" src="file/image/SAITO_ASUKA.png">' | |
#'</div>' | |
#) | |
with gr.Column(): | |
text = gr.TextArea( | |
label="输入纯日语或者中文", | |
placeholder="输入纯日语或者中文", | |
value="純粋な日本語または中国語を入力してください。", | |
) | |
btn = gr.Button("点击生成", variant="primary") | |
audio_output = gr.Audio(label="Output Audio") | |
LongSentence = gr.Checkbox(value=True, label="Generate LongSentence") | |
with gr.Accordion(label="TTS设定", open=True): | |
sdp_ratio = gr.Slider( | |
minimum=0, maximum=1, value=0.2, step=0.01, label="SDP/DP混合比" | |
) | |
noise_scale = gr.Slider( | |
minimum=0.1, maximum=2, value=0.6, step=0.01, label="感情调节" | |
) | |
noise_scale_w = gr.Slider( | |
minimum=0.1, maximum=2, value=0.8, step=0.01, label="音素长度" | |
) | |
length_scale = gr.Slider( | |
minimum=0.1, maximum=2, value=1.05, step=0.01, label="生成长度" | |
) | |
speaker = gr.Dropdown( | |
choices=speakers, value=name, label="说话人(在这选择说话人将保留输入文本)" | |
) | |
btn.click( | |
tts_fn, | |
inputs=[ | |
text, | |
speaker, | |
sdp_ratio, | |
noise_scale, | |
noise_scale_w, | |
length_scale, | |
LongSentence, | |
], | |
outputs=[audio_output], | |
) | |
app.launch() | |