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| 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/Ava/G_14300.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向晚】在线语音合成（Bert-Vits2）\n | |
| 作者：Xz乔希 https://space.bilibili.com/5859321\n | |
| 声音归属：向晚大魔王 https://space.bilibili.com/672346917\n | |
| Bert-VITS2项目：https://github.com/Stardust-minus/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="欸哇哇欸哇，这里是诶嗖的向晚，今天也要跟我一起轻松快乐的看直播。") | |
| 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 | |
| """) | |
| 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) | |