File size: 6,968 Bytes
bf0a127
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
b6d7961
bf0a127
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
82f5cc2
b6d7961
82f5cc2
b6d7961
82f5cc2
b6d7961
 
82f5cc2
78e14e1
82f5cc2
bf0a127
b6d7961
bf0a127
ed2ee73
 
 
f2850f7
1c06304
bf0a127
 
 
6080bab
 
 
 
 
 
cc075bf
bcebdbd
4c179ac
4389786
b6d7961
6080bab
bf0a127
 
 
 
 
 
 
 
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
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/Diana/G_4800.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嘉然①】在线语音合成(Bert-Vits2)\n
                作者:Xz乔希 https://space.bilibili.com/5859321\n
                声音归属:嘉然今天吃什么 https://space.bilibili.com/672328094\n
                Bert-VITS2项目:https://github.com/Stardust-minus/Bert-VITS2\n
                【AI嘉然②】https://huggingface.co/spaces/XzJosh/Jiaran-Bert-VITS2\n
                【AI嘉然③】https://huggingface.co/spaces/XzJosh/ranran-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="大家好我是嘉然戴安娜,关注嘉然,顿顿解馋,谢谢!")
                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
                 """)
        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)