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import time |
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import os |
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import gradio as gr |
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import utils |
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import argparse |
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import commons |
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from models import SynthesizerTrn |
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from text import text_to_sequence |
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import torch |
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from torch import no_grad, LongTensor |
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import webbrowser |
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import logging |
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import gradio.processing_utils as gr_processing_utils |
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logging.getLogger('numba').setLevel(logging.WARNING) |
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limitation = os.getenv("SYSTEM") == "spaces" |
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audio_postprocess_ori = gr.Audio.postprocess |
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def audio_postprocess(self, y): |
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data = audio_postprocess_ori(self, y) |
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if data is None: |
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return None |
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return gr_processing_utils.encode_url_or_file_to_base64(data["name"]) |
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gr.Audio.postprocess = audio_postprocess |
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def get_text(text, hps): |
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text_norm, clean_text = text_to_sequence(text, hps.symbols, hps.data.text_cleaners) |
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if hps.data.add_blank: |
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text_norm = commons.intersperse(text_norm, 0) |
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text_norm = LongTensor(text_norm) |
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return text_norm, clean_text |
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def vits(text, language, speaker_id, noise_scale, noise_scale_w, length_scale): |
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start = time.perf_counter() |
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if not len(text): |
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return "输入文本不能为空！", None, None |
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text = text.replace('\n', ' ').replace('\r', '').replace(" ", "") |
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if len(text) > 100 and limitation: |
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return f"输入文字过长！{len(text)}>100", None, None |
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if language == 0: |
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text = f"[ZH]{text}[ZH]" |
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elif language == 1: |
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text = f"[JA]{text}[JA]" |
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else: |
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text = f"{text}" |
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stn_tst, clean_text = get_text(text, hps_ms) |
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with no_grad(): |
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x_tst = stn_tst.unsqueeze(0).to(device) |
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x_tst_lengths = LongTensor([stn_tst.size(0)]).to(device) |
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speaker_id = LongTensor([speaker_id]).to(device) |
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audio = net_g_ms.infer(x_tst, x_tst_lengths, sid=speaker_id, noise_scale=noise_scale, noise_scale_w=noise_scale_w, |
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length_scale=length_scale)[0][0, 0].data.cpu().float().numpy() |
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return "生成成功!", (22050, audio), f"生成耗时 {round(time.perf_counter()-start, 2)} s" |
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def search_speaker(search_value): |
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for s in speakers: |
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if search_value == s: |
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return s |
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for s in speakers: |
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if search_value in s: |
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return s |
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def change_lang(language): |
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if language == 0: |
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return 0.6, 0.668, 1.2 |
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else: |
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return 0.6, 0.668, 1.1 |
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download_audio_js = """ |
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() =>{{ |
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let root = document.querySelector("body > gradio-app"); |
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if (root.shadowRoot != null) |
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root = root.shadowRoot; |
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let audio = root.querySelector("#tts-audio").querySelector("audio"); |
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let text = root.querySelector("#input-text").querySelector("textarea"); |
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if (audio == undefined) |
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return; |
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text = text.value; |
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if (text == undefined) |
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text = Math.floor(Math.random()*100000000); |
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audio = audio.src; |
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let oA = document.createElement("a"); |
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oA.download = text.substr(0, 20)+'.wav'; |
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oA.href = audio; |
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document.body.appendChild(oA); |
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oA.click(); |
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oA.remove(); |
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}} |
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""" |
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if __name__ == '__main__': |
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parser = argparse.ArgumentParser() |
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parser.add_argument('--device', type=str, default='cpu') |
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parser.add_argument('--api', action="store_true", default=False) |
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parser.add_argument("--share", action="store_true", default=False, help="share gradio app") |
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parser.add_argument("--colab", action="store_true", default=False, help="share gradio app") |
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args = parser.parse_args() |
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device = torch.device(args.device) |
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hps_ms = utils.get_hparams_from_file(r'./model/config.json') |
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net_g_ms = SynthesizerTrn( |
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len(hps_ms.symbols), |
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hps_ms.data.filter_length // 2 + 1, |
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hps_ms.train.segment_size // hps_ms.data.hop_length, |
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n_speakers=hps_ms.data.n_speakers, |
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**hps_ms.model) |
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_ = net_g_ms.eval().to(device) |
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speakers = hps_ms.speakers |
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model, optimizer, learning_rate, epochs = utils.load_checkpoint(r'./model/G_953000.pth', net_g_ms, None) |
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with gr.Blocks() as app: |
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gr.Markdown( |
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"# <center> VITS语音在线合成demo\n" |
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"# <center> 严禁将模型用于任何商业项目，否则后果自负\n" |
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"<div align='center'>主要有赛马娘，原神中文，原神日语，崩坏3的音色</div>" |
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'<div align="center"><a><font color="#dd0000">结果有随机性，语调可能很奇怪，可多次生成取最佳效果</font></a></div>' |
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'<div align="center"><a><font color="#dd0000">标点符号会影响生成的结果</font></a></div>' |
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) |
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with gr.Tabs(): |
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with gr.TabItem("vits"): |
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with gr.Row(): |
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with gr.Column(): |
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input_text = gr.Textbox(label="Text (100 words limitation) " if limitation else "Text", lines=5, value="今天晚上吃啥好呢。", elem_id=f"input-text") |
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lang = gr.Dropdown(label="Language", choices=["中文", "日语", "中日混合（中文用[ZH][ZH]包裹起来，日文用[JA][JA]包裹起来）"], |
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type="index", value="中文") |
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btn = gr.Button(value="Submit") |
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with gr.Row(): |
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search = gr.Textbox(label="Search Speaker", lines=1) |
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btn2 = gr.Button(value="Search") |
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sid = gr.Dropdown(label="Speaker", choices=speakers, type="index", value=speakers[228]) |
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with gr.Row(): |
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ns = gr.Slider(label="noise_scale(控制感情变化程度)", minimum=0.1, maximum=1.0, step=0.1, value=0.6, interactive=True) |
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nsw = gr.Slider(label="noise_scale_w(控制音素发音长度)", minimum=0.1, maximum=1.0, step=0.1, value=0.668, interactive=True) |
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ls = gr.Slider(label="length_scale(控制整体语速)", minimum=0.1, maximum=2.0, step=0.1, value=1.2, interactive=True) |
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with gr.Column(): |
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o1 = gr.Textbox(label="Output Message") |
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o2 = gr.Audio(label="Output Audio", elem_id=f"tts-audio") |
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o3 = gr.Textbox(label="Extra Info") |
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download = gr.Button("Download Audio") |
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btn.click(vits, inputs=[input_text, lang, sid, ns, nsw, ls], outputs=[o1, o2, o3]) |
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download.click(None, [], [], _js=download_audio_js.format()) |
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btn2.click(search_speaker, inputs=[search], outputs=[sid]) |
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lang.change(change_lang, inputs=[lang], outputs=[ns, nsw, ls]) |
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with gr.TabItem("可用人物一览"): |
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gr.Radio(label="Speaker", choices=speakers, interactive=False, type="index") |
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if args.colab: |
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webbrowser.open("http://127.0.0.1:7860") |
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app.queue(concurrency_count=1, api_open=args.api).launch(share=args.share) |
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