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Update app.py
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app.py
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# coding=utf-8
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import time
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import gradio as gr
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import utils
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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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from torch import no_grad, LongTensor
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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()
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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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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:
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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)
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x_tst_lengths = LongTensor([stn_tst.size(0)])
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speaker_id = LongTensor([speaker_id])
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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.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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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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"<
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'<div align="center"><a><font color="#dd0000"
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# coding=utf-8
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import time
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import gradio as gr
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import utils
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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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from torch import no_grad, LongTensor
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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()
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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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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:
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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)
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x_tst_lengths = LongTensor([stn_tst.size(0)])
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speaker_id = LongTensor([speaker_id])
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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.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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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)", 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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app.queue(concurrency_count=1).launch()
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