|
import io |
|
import os |
|
|
|
os.system("wget -P hubert/ https://huggingface.co/spaces/innnky/nanami/resolve/main/checkpoint_best_legacy_500.pt") |
|
import gradio as gr |
|
import librosa |
|
import numpy as np |
|
import soundfile |
|
from inference.infer_tool import Svc |
|
import logging |
|
|
|
logging.getLogger('numba').setLevel(logging.WARNING) |
|
logging.getLogger('markdown_it').setLevel(logging.WARNING) |
|
logging.getLogger('urllib3').setLevel(logging.WARNING) |
|
logging.getLogger('matplotlib').setLevel(logging.WARNING) |
|
|
|
model = Svc("logs/44k/G_0.pth", "configs/config.json", cluster_model_path="logs/44k/kmeans_10000.pt") |
|
|
|
|
|
|
|
def vc_fn(sid, input_audio, vc_transform, auto_f0,cluster_ratio, noise_scale): |
|
if input_audio is None: |
|
return "You need to upload an audio", None |
|
sampling_rate, audio = input_audio |
|
|
|
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 = "temp.wav" |
|
soundfile.write(out_wav_path, audio, 16000, format="wav") |
|
print( cluster_ratio, auto_f0, noise_scale) |
|
out_audio, out_sr = model.infer(sid, vc_transform, out_wav_path, |
|
cluster_infer_ratio=cluster_ratio, |
|
auto_predict_f0=auto_f0, |
|
noice_scale=noise_scale |
|
) |
|
audio = out_audio.numpy() |
|
rms = librosa.feature.rms(audio, frame_length=2048, hop_length=512)[0] |
|
target_rms = 0.1 |
|
current_rms = np.mean(rms) |
|
gain = target_rms / current_rms |
|
audio *= gain |
|
return "Success", (44100, audio) |
|
|
|
|
|
app = gr.Blocks() |
|
with app: |
|
with gr.Tabs(): |
|
with gr.TabItem("Basic"): |
|
gr.Markdown(value=""" |
|
sovits4.0 在线demo |
|
|
|
此demo为预训练底模在线demo，使用数据：云灏 即霜 辉宇·星AI 派蒙 绫地宁宁 |
|
""") |
|
spks = list(model.spk2id.keys()) |
|
sid = gr.Dropdown(label="音色", choices=["nen", "yunhao","paimon", "huiyu","jishuang"], value="paimon") |
|
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) |
|
cluster_ratio = gr.Number(label="聚类模型混合比例，0-1之间，默认为0不启用聚类，能提升音色相似度，但会导致咬字下降（如果使用建议0.5左右）", value=0) |
|
auto_f0 = gr.Checkbox(label="自动f0预测，配合聚类模型f0预测效果更好,会导致变调功能失效（仅限转换语音，歌声不要勾选此项会究极跑调）", value=False) |
|
noise_scale = gr.Number(label="noise_scale 建议不要动，会影响音质，玄学参数", value=0.4) |
|
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,auto_f0,cluster_ratio, noise_scale], [vc_output1, vc_output2]) |
|
|
|
app.launch() |
|
|
|
|
|
|
|
|
