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import io | |
import os | |
# os.system("wget -P cvec/ 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) | |
config_path = "models/Arknights/config.json" | |
model = Svc("models/Arknights/G_10400.pth", "models/Arknights/config.json") | |
# model = Svc("E:/Items/so-vits-svc/models/Arknights/G_10400.pth", "E:/Items/so-vits-svc/models/Arknights/config.json") | |
def vc_fn(sid, input_audio, vc_transform, auto_f0,cluster_ratio, slice_db, noise_scale): | |
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 > 90: | |
return "请上传小于90s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) | |
_audio = model.slice_inference(out_wav_path, sid, vc_transform, slice_db, cluster_ratio, auto_f0, noise_scale) | |
return "Success", (44100, _audio) | |
app = gr.Blocks() | |
with app: | |
with gr.Tabs(): | |
with gr.TabItem("Basic"): | |
gr.Markdown(value=""" | |
sovits4.0 Arknights | |
自练模型,内有 伊芙利特 凯尔希 桃金娘 塞雷娅 斯卡蒂 | |
""") | |
spks = list(model.spk2id.keys()) | |
sid = gr.Dropdown(label="音色", choices=spks, value=spks[0]) | |
vc_input3 = gr.Audio(label="上传音频(长度小于90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) | |
slice_db = gr.Number(label="切片阈值", value=-40) | |
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, slice_db, noise_scale], [vc_output1, vc_output2]) | |
app.launch() | |