import io import gradio as gr import librosa import numpy as np import soundfile import torch from inference.infer_tool import Svc import logging logging.getLogger('numba').setLevel(logging.WARNING) model_name = "logs/32k/G_25000.pth" config_name = "configs/config.json" svc_model = Svc(model_name, config_name) sid_map = { "高峯翠": "cui" } def vc_fn(sid, input_audio, vc_transform): if input_audio is None: return "You need to upload an audio", None sampling_rate, audio = input_audio # print(audio.shape,sampling_rate) duration = audio.shape[0] / sampling_rate if duration > 45: return "请上传小于45s的音频,需要转换长音频请本地进行转换", None audio = (audio / np.iinfo(audio.dtype).max).astype(np.float32) if len(audio.shape) > 1: audio = librosa.to_mono(audio.transpose(1, 0)) if sampling_rate != 16000: audio = librosa.resample(audio, orig_sr=sampling_rate, target_sr=16000) print(audio.shape) out_wav_path = io.BytesIO() soundfile.write(out_wav_path, audio, 16000, format="wav") out_wav_path.seek(0) sid = sid_map[sid] out_audio, out_sr = svc_model.infer(sid, vc_transform, out_wav_path) _audio = out_audio.cpu().numpy() return "Success", (32000, _audio) app = gr.Blocks() with app: with gr.Tabs(): with gr.TabItem("Basic"): gr.Markdown(value=""" 高峯翠Sovits3.0模型 如果要在本地使用该demo,请使用git lfs clone 该仓库,安装requirements.txt后运行app.py即可 项目改写基于 https://huggingface.co/spaces/innnky/nyaru-svc-3.0 本地合成可以删除26、27两行代码以解除合成45s长度限制""") sid = gr.Dropdown(label="音色", choices=["高峯翠"], value="cui") vc_input3 = gr.Audio(label="上传音频(长度小于45秒)") vc_transform = gr.Number(label="变调(整数,可以正负,半音数量,升高八度就是12)", value=0) vc_submit = gr.Button("转换", variant="primary") vc_output1 = gr.Textbox(label="Output Message") vc_output2 = gr.Audio(label="Output Audio") vc_submit.click(vc_fn, [sid, vc_input3, vc_transform], [vc_output1, vc_output2]) app.launch()