app.py

from utils.hparams import hparams
import scipy.io.wavfile as wav
import numpy as np
import matplotlib.pyplot as plt
import IPython.display as ipd
import utils
import librosa
import torch
import torchcrepe
from infer import *
import logging
from infer_tools.infer_tool import *
import gradio as gr
import json

logging.getLogger('numba').setLevel(logging.WARNING)
svc_model = None
project_name = "aqua"
wave_name = f"./temp.wav"
model_path = f'./aqua/clean_model_ckpt_steps_100000.ckpt'
config_path = f'./aqua/config.yaml'
spk_id = "aqua"

def infer(wav_fn, tran, accelerate, auto_key):
    model = Svc(project_name, config_path, hubert_gpu=False, model_path=model_path, onnx=False)

    if wav_fn is not None:
        audio_path = wav_fn
    else:
        return "请先上传wav格式的音频文件", None, None
    run_clip(raw_audio_path=audio_path, svc_model=model, key=tran, acc=accelerate, use_crepe=True,
                 spk_id=spk_id, auto_key=auto_key, project_name=project_name, out_path=wave_name)

    au_out = wave_name

    return "转换成功", au_out

app = gr.Blocks()
with app:
    with gr.Tabs():
        with gr.TabItem("推理"):
            with gr.Blocks():
                with gr.Blocks():
                    with gr.Box():
                        gr.Markdown(value="""**上传音频**""")
                        with gr.Row():
                            upload_input = gr.Audio(source="upload", label="源音频", type="filepath", elem_id="audio_inputs")
                            out_audio = gr.Audio(label="输出音频")
                with gr.Blocks():
                    with gr.Box():
                        gr.Markdown(value="""**参数设置**""")
                        with gr.Row():
                            auto = gr.Checkbox(label="启用自动变调", value=False)
                        with gr.Row():
                            acc_vaule = gr.Slider(1, 50, value=20, interactive=True, label="加速倍率")
                        with gr.Row():
                            pitch_vaule = gr.Slider(-96, 96, value=0, interactive=True, label="变调（半音）")
                        with gr.Row():
                            with gr.Column(scale=1):
                                infer_md = gr.Button("转换音频", variant="primary")
                with gr.Blocks():
                    with gr.Box():
                        gr.Markdown(value="""**输出日志**""")
                        infer_msg = gr.Textbox(label="日志")
            infer_md.click(infer, [upload_input, pitch_vaule, acc_vaule, auto], [infer_msg, out_audio])
        with gr.TabItem("说明"):
            gr.Markdown(value="""
                自改cpu推理版，无音频长度限制，无降噪功能，请确保输入音频的质量\n
                有本地cpu推理的需求可以下载全部文件\n
                原项目地址：https://github.com/openvpi/diff-svc\n
                代码修改：@ChrisPreston\n
                模型训练：@ChrisPreston\n
                音源：Aqua Ch. 湊あくあ https://www.youtube.com/@MinatoAqua カバー株式会社\n
                模型使用协议（重要）：\n
                1.请勿用于商业目的\n
                2.请勿用于会影响主播本人的行为（比如冒充本人发表争议言论）\n
                3.请勿用于血腥、暴力、性相关、政治相关内容\n
                4.不允许二次分发模型\n
                5.非个人使用场合请注明模型作者@ChrisPreston以及diff-svc原项目\n
                6.允许用于个人娱乐场景下的游戏语音、直播活动，不得用于低创内容，用于直播前请与本人联系\n
                联系方式：电邮：kameiliduo0825@gmail.com, b站：https://space.bilibili.com/18801308\n
                免责声明：由于使用本模型造成的法律纠纷本人概不负责
            """)

    app.launch(share=False)