qqq

Docker/Dockerfile

@@ -1,12 +0,0 @@
-FROM python:3.9-bullseye
-VOLUME ["/app"]
-WORKDIR /app
-# Set apt to Chinese mirror
-RUN sed -i 's/deb.debian.org/mirrors.ustc.edu.cn/g' /etc/apt/sources.list
-RUN apt-get update && apt-get -y install cmake git
-RUN git clone https://huggingface.co/spaces/ikechan8370/vits-uma-genshin-honkai
-WORKDIR /app/vits-uma-genshin-honkai
-RUN sed -i "s/\.launch()/\.launch(server_name=\"0.0.0.0\")/" /app/vits-uma-genshin-honkai/app.py
-ADD vits.sh /app/vits.sh
-EXPOSE 7860
-ENTRYPOINT [ "/app/vits.sh" ]

Docker/vits.sh

@@ -1,20 +0,0 @@
-#!/bin/bash
-run() {
- echo -e "\033[32m已完成初始化，启动服务...\033[0m"
- python3 /app/vits-uma-genshin-honkai/app.py
-}
-install() {
- echo -e "\033[33m正在初始化：安装依赖....\033[0m"
- pip install -r /app/vits-uma-genshin-honkai/requirements.txt -i https://mirrors.ustc.edu.cn/pypi/web/simple
- echo -e "\033[33m正在下载模型....\033[0m"
- rm -f /app/vits-uma-genshin-honkai/model/G_953000.pth
- wget -O /app/vits-uma-genshin-honkai/model/G_953000.pth https://huggingface.co/spaces/ikechan8370/vits-uma-genshin-honkai/resolve/main/model/G_953000.pth
- echo -e "\033[32m初始化完成！\033[0m"
- run
-}
-
-if [ ! -f "/app/vits-uma-genshin-honkai/model/G_953000.pth" ] || [ "$(stat -c%s "/app/vits-uma-genshin-honkai/model/G_953000.pth")" -lt 10000 ]; then
- install
-else
- run
-fi

app.py

@@ -1,124 +1,123 @@
-import time
-import gradio as gr
-import utils
-import commons
-from models import SynthesizerTrn
-from text import text_to_sequence
-from torch import no_grad, LongTensor
-import torch
-
-hps_ms = utils.get_hparams_from_file(r'./model/config.json')
-device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-net_g_ms = SynthesizerTrn(
- len(hps_ms.symbols),
- hps_ms.data.filter_length // 2 + 1,
- hps_ms.train.segment_size // hps_ms.data.hop_length,
- n_speakers=hps_ms.data.n_speakers,
- **hps_ms.model).to(device)
-_ = net_g_ms.eval()
-speakers = hps_ms.speakers
-model, optimizer, learning_rate, epochs = utils.load_checkpoint(r'./model/G_953000.pth', net_g_ms, None)
-
-def get_text(text, hps):
- text_norm, clean_text = text_to_sequence(text, hps.symbols, hps.data.text_cleaners)
- if hps.data.add_blank:
- text_norm = commons.intersperse(text_norm, 0)
- text_norm = LongTensor(text_norm)
- return text_norm, clean_text
-
-def vits(text, language, speaker_id, noise_scale, noise_scale_w, length_scale):
- start = time.perf_counter()
- if not len(text):
- return "输入文本不能为空！", None, None
- text = text.replace('\n', ' ').replace('\r', '').replace(" ", "")
- if len(text) > 500:
- return f"输入文字过长！{len(text)}>100", None, None
- if language == 0:
- text = f"[ZH]{text}[ZH]"
- elif language == 1:
- text = f"[JA]{text}[JA]"
- else:
- text = f"{text}"
- stn_tst, clean_text = get_text(text, hps_ms)
- with no_grad():
- x_tst = stn_tst.unsqueeze(0)
- x_tst_lengths = LongTensor([stn_tst.size(0)])
- speaker_id = LongTensor([speaker_id])
- audio = net_g_ms.infer(x_tst, x_tst_lengths, sid=speaker_id, noise_scale=noise_scale, noise_scale_w=noise_scale_w,
- length_scale=length_scale)[0][0, 0].data.cpu().float().numpy()
-
- return "生成成功!", (22050, audio), f"生成耗时 {round(time.perf_counter()-start, 2)} s"
-
-def search_speaker(search_value):
- for s in speakers:
- if search_value == s:
- return s
- for s in speakers:
- if search_value in s:
- return s
-
-def change_lang(language):
- if language == 0:
- return 0.6, 0.668, 1.2
- else:
- return 0.6, 0.668, 1.1
-
-download_audio_js = """
-() =>{{
- let root = document.querySelector("body > gradio-app");
- if (root.shadowRoot != null)
- root = root.shadowRoot;
- let audio = root.querySelector("#tts-audio").querySelector("audio");
- let text = root.querySelector("#input-text").querySelector("textarea");
- if (audio == undefined)
- return;
- text = text.value;
- if (text == undefined)
- text = Math.floor(Math.random()*100000000);
- audio = audio.src;
- let oA = document.createElement("a");
- oA.download = text.substr(0, 20)+'.wav';
- oA.href = audio;
- document.body.appendChild(oA);
- oA.click();
- oA.remove();
-}}
-"""
-
-if __name__ == '__main__':
- with gr.Blocks() as app:
- gr.Markdown(
- "# <center> VITS语音在线合成demo\n"
- "<div align='center'>主要有赛马娘，原神中文，原神日语，崩坏3的音色</div>"
- '<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>'
- '<div align="center"><a><font color="#dd0000">标点符号会影响生成的结果</font></a></div>'
- )
-
- with gr.Tabs():
- with gr.TabItem("vits"):
- with gr.Row():
- with gr.Column():
- 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")
- 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）"],
- type="index", value="中文")
- btn = gr.Button(value="Submit")
- with gr.Row():
- search = gr.Textbox(label="Search Speaker", lines=1)
- btn2 = gr.Button(value="Search")
- sid = gr.Dropdown(label="Speaker", choices=speakers, type="index", value=speakers[228])
- with gr.Row():
- 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)
- 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)
- 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)
- with gr.Column():
- o1 = gr.Textbox(label="Output Message")
- o2 = gr.Audio(label="Output Audio", elem_id=f"tts-audio")
- o3 = gr.Textbox(label="Extra Info")
- download = gr.Button("Download Audio")
- btn.click(vits, inputs=[input_text, lang, sid, ns, nsw, ls], outputs=[o1, o2, o3], api_name="generate")
- download.click(None, [], [], _js=download_audio_js.format())
- btn2.click(search_speaker, inputs=[search], outputs=[sid])
- lang.change(change_lang, inputs=[lang], outputs=[ns, nsw, ls])
- with gr.TabItem("可用人物一览"):
- gr.Radio(label="Speaker", choices=speakers, interactive=False, type="index")
- app.queue(concurrency_count=1).launch()
+# coding=utf-8
+import time
+import gradio as gr
+import utils
+import commons
+from models import SynthesizerTrn
+from text import text_to_sequence
+from torch import no_grad, LongTensor
+
+hps_ms = utils.get_hparams_from_file(r'./model/config.json')
+net_g_ms = SynthesizerTrn(
+ len(hps_ms.symbols),
+ hps_ms.data.filter_length // 2 + 1,
+ hps_ms.train.segment_size // hps_ms.data.hop_length,
+ n_speakers=hps_ms.data.n_speakers,
+ **hps_ms.model)
+_ = net_g_ms.eval()
+speakers = hps_ms.speakers
+model, optimizer, learning_rate, epochs = utils.load_checkpoint(r'./model/G_953000.pth', net_g_ms, None)
+
+def get_text(text, hps):
+ text_norm, clean_text = text_to_sequence(text, hps.symbols, hps.data.text_cleaners)
+ if hps.data.add_blank:
+ text_norm = commons.intersperse(text_norm, 0)
+ text_norm = LongTensor(text_norm)
+ return text_norm, clean_text
+
+def vits(text, language, speaker_id, noise_scale, noise_scale_w, length_scale):
+ start = time.perf_counter()
+ if not len(text):
+ return "输入文本不能为空！", None, None
+ text = text.replace('\n', ' ').replace('\r', '').replace(" ", "")
+ if len(text) > 300:
+ return f"输入文字过长！{len(text)}>100", None, None
+ if language == 0:
+ text = f"[ZH]{text}[ZH]"
+ elif language == 1:
+ text = f"[JA]{text}[JA]"
+ else:
+ text = f"{text}"
+ stn_tst, clean_text = get_text(text, hps_ms)
+ with no_grad():
+ x_tst = stn_tst.unsqueeze(0)
+ x_tst_lengths = LongTensor([stn_tst.size(0)])
+ speaker_id = LongTensor([speaker_id])
+ audio = net_g_ms.infer(x_tst, x_tst_lengths, sid=speaker_id, noise_scale=noise_scale, noise_scale_w=noise_scale_w,
+ length_scale=length_scale)[0][0, 0].data.float().numpy()
+
+ return "生成成功!", (22050, audio), f"生成耗时 {round(time.perf_counter()-start, 2)} s"
+
+def search_speaker(search_value):
+ for s in speakers:
+ if search_value == s:
+ return s
+ for s in speakers:
+ if search_value in s:
+ return s
+
+def change_lang(language):
+ if language == 0:
+ return 0.6, 0.668, 1.2
+ else:
+ return 0.6, 0.668, 1.1
+
+download_audio_js = """
+() =>{{
+ let root = document.querySelector("body > gradio-app");
+ if (root.shadowRoot != null)
+ root = root.shadowRoot;
+ let audio = root.querySelector("#tts-audio").querySelector("audio");
+ let text = root.querySelector("#input-text").querySelector("textarea");
+ if (audio == undefined)
+ return;
+ text = text.value;
+ if (text == undefined)
+ text = Math.floor(Math.random()*100000000);
+ audio = audio.src;
+ let oA = document.createElement("a");
+ oA.download = text.substr(0, 20)+'.wav';
+ oA.href = audio;
+ document.body.appendChild(oA);
+ oA.click();
+ oA.remove();
+}}
+"""
+
+if __name__ == '__main__':
+ with gr.Blocks() as app:
+ gr.Markdown(
+ "# <center> VITS语音在线合成demo\n"
+ "<div align='center'>主要有赛马娘，原神中文，原神日语，崩坏3的音色</div>"
+ '<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>'
+ '<div align="center"><a><font color="#dd0000">标点符号会影响生成的结果</font></a></div>'
+ )
+
+ with gr.Tabs():
+ with gr.TabItem("vits"):
+ with gr.Row():
+ with gr.Column():
+ 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")
+ 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）"],
+ type="index", value="中文")
+ btn = gr.Button(value="Submit")
+ with gr.Row():
+ search = gr.Textbox(label="Search Speaker", lines=1)
+ btn2 = gr.Button(value="Search")
+ sid = gr.Dropdown(label="Speaker", choices=speakers, type="index", value=speakers[228])
+ with gr.Row():
+ 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)
+ 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)
+ 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)
+ with gr.Column():
+ o1 = gr.Textbox(label="Output Message")
+ o2 = gr.Audio(label="Output Audio", elem_id=f"tts-audio")
+ o3 = gr.Textbox(label="Extra Info")
+ download = gr.Button("Download Audio")
+ btn.click(vits, inputs=[input_text, lang, sid, ns, nsw, ls], outputs=[o1, o2, o3], api_name="generate")
+ download.click(None, [], [], _js=download_audio_js.format())
+ btn2.click(search_speaker, inputs=[search], outputs=[sid])
+ lang.change(change_lang, inputs=[lang], outputs=[ns, nsw, ls])
+ with gr.TabItem("可用人物一览"):
+ gr.Radio(label="Speaker", choices=speakers, interactive=False, type="index")
+ app.queue(concurrency_count=1).launch()

models.py

@@ -496,10 +496,9 @@ class SynthesizerTrn(nn.Module):
  return o, l_length, attn, ids_slice, x_mask, y_mask, (z, z_p, m_p, logs_p, m_q, logs_q)
 
  def infer(self, x, x_lengths, sid=None, noise_scale=1, length_scale=1, noise_scale_w=1., max_len=None):
- device = next(self.parameters()).device # 获取模型所在的设备
- x, m_p, logs_p, x_mask = self.enc_p(x.to(device), x_lengths.to(device))
+ x, m_p, logs_p, x_mask = self.enc_p(x, x_lengths)
  if self.n_speakers > 0:
- g = self.emb_g(sid.to(device)).unsqueeze(-1) # [b, h, 1]
+ g = self.emb_g(sid).unsqueeze(-1) # [b, h, 1]
  else:
  g = None