| 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_150000.pth" |
| config_name = "configs/config.json" |
|
|
| svc_model = Svc(model_name, config_name) |
| sid_map = { |
| "i": "i" |
| } |
|
|
|
|
| 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 |
| |
| |
| 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=""" |
| |
| |
| i7000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=["i"], value="i") |
| 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() |
|
|
