import sys, os
if sys.platform == "darwin":
os.environ["PYTORCH_ENABLE_MPS_FALLBACK"] = "1"
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 torch
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
net_g = None
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)
del word2ph
assert bert.shape[-1] == len(phone)
phone = torch.LongTensor(phone)
tone = torch.LongTensor(tone)
language = torch.LongTensor(language)
return bert, phone, tone, language
def infer(text, sdp_ratio, noise_scale, noise_scale_w, length_scale, sid):
global net_g
bert, phones, tones, lang_ids = get_text(text, "ZH", 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)
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, 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):
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)
return "Success", (hps.data.sampling_rate, audio)
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--model_dir", default="./logs/Aatrox/G_1800.pth", help="path of your model")
parser.add_argument("--config_dir", default="./configs/config.json", help="path of your config file")
parser.add_argument("--share", default=False, help="make link public")
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_dir)
device = "cuda:0" if torch.cuda.is_available() else "cpu"
'''
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_dir, net_g, None, skip_optimizer=True)
speaker_ids = hps.data.spk2id
speakers = list(speaker_ids.keys())
with gr.Blocks() as app:
with gr.Row():
with gr.Column():
gr.Markdown(value="""
【AI剑魔③】在线语音合成（Bert-Vits2）\n
作者：Xz乔希 https://space.bilibili.com/5859321\n
声音归属：《英雄联盟》暗裔剑魔·亚托克斯\n
Bert-VITS2项目：https://github.com/Stardust-minus/Bert-VITS2\n
【AI剑魔①】https://huggingface.co/spaces/XzJosh/Aatrox-Bert-VITS2\n
【AI剑魔②】https://huggingface.co/spaces/XzJosh/Jianmo-Bert-VITS2\n
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作者及链接、作品使用Bert-VITS2 AI生成！\n
""")
text = gr.TextArea(label="Text", placeholder="Input Text Here",
value="我是亚托克斯！我是世界的终结者！")
speaker = gr.Dropdown(choices=speakers, value=speakers[0], label='Speaker')
sdp_ratio = gr.Slider(minimum=0.1, maximum=1, value=0.2, step=0.01, label='SDP/DP混合比')
noise_scale = gr.Slider(minimum=0.1, maximum=1, value=0.5, step=0.01, label='感情调节')
noise_scale_w = gr.Slider(minimum=0.1, maximum=1, value=0.9, step=0.01, label='音素长度')
length_scale = gr.Slider(minimum=0.1, maximum=2, value=1, step=0.01, label='生成长度')
btn = gr.Button("点击生成", variant="primary")
with gr.Column():
text_output = gr.Textbox(label="Message")
audio_output = gr.Audio(label="Output Audio")
gr.Markdown(value="""
【AI塔菲】https://huggingface.co/spaces/XzJosh/Taffy-Bert-VITS2\n
【AI东雪莲】https://huggingface.co/spaces/XzJosh/Azuma-Bert-VITS2\n
【AI奶绿】https://huggingface.co/spaces/XzJosh/LAPLACE-Bert-VITS2\n
【AI尼奈】https://huggingface.co/spaces/XzJosh/nine1-Bert-VITS2\n
【AI珈乐】https://huggingface.co/spaces/XzJosh/Carol-Bert-VITS2\n
【AI电棍】https://huggingface.co/spaces/XzJosh/otto-Bert-VITS2\n
【AI七海】https://huggingface.co/spaces/XzJosh/Nana7mi-Bert-VITS2\n
【AI阿梓】https://huggingface.co/spaces/XzJosh/Azusa-Bert-VITS2\n
【AI星瞳】https://huggingface.co/spaces/XzJosh/XingTong-Bert-VITS2\n
【AI向晚】https://huggingface.co/spaces/XzJosh/Ava-Bert-VITS2\n
【AI嘉然】https://huggingface.co/spaces/XzJosh/Diana-Bert-VITS2\n
""")
btn.click(tts_fn,
inputs=[text, speaker, sdp_ratio, noise_scale, noise_scale_w, length_scale],
outputs=[text_output, audio_output])
# webbrowser.open("http://127.0.0.1:6006")
# app.launch(server_port=6006, show_error=True)
app.launch(show_error=True)