nyaru-svc2.0 / app.py
innnky's picture
Revert "fix"
c65497b
raw
history blame
4.75 kB
import gradio as gr
import soundfile
import torch
import infer_tool
convert_cnt = [0]
dev = torch.device("cuda" if torch.cuda.is_available() else "cpu")
model_name = "83_epochs.pth"
config_name = "nyarumul.json"
net_g_ms, hubert_soft, feature_input, hps_ms = infer_tool.load_model(f"{model_name}", f"configs/{config_name}")
# 获取config参数
target_sample = hps_ms.data.sampling_rate
spk_dict = {
"猫雷2.0": 0,
"云灏": 2,
"即霜": 3,
"奕兰秋": 4
}
def vc_fn(sid, audio_record, audio_upload, tran):
print(sid)
if audio_upload is not None:
audio_path = audio_upload
elif audio_record is not None:
audio_path = audio_record
else:
return "你需要上传wav文件或使用网页内置的录音!", None
audio, sampling_rate = infer_tool.format_wav(audio_path, target_sample)
duration = audio.shape[0] / sampling_rate
if duration > 60:
return "请上传小于60s的音频,需要转换长音频请使用colab", None
o_audio, out_sr = infer_tool.infer(audio_path, spk_dict[sid], tran, net_g_ms, hubert_soft, feature_input)
out_path = f"./out_temp.wav"
soundfile.write(out_path, o_audio, target_sample)
infer_tool.f0_plt(audio_path, out_path, tran, hubert_soft, feature_input)
mistake, var = infer_tool.calc_error(audio_path, out_path, tran, feature_input)
return f"半音偏差:{mistake}\n半音方差:{var}", (
target_sample, o_audio), gr.Image.update("temp.jpg")
app = gr.Blocks()
with app:
with gr.Tabs():
with gr.TabItem("Basic"):
gr.Markdown(value="""
本模型为sovits_f0(含AI猫雷2.0音色),支持**60s以内**的**无伴奏**wav、mp3(单声道)格式,或使用**网页内置**的录音(二选一)
转换效果取决于源音频语气、节奏是否与目标音色相近,以及音域是否超出目标音色音域范围
猫雷音色低音音域效果不佳,如转换男声歌声,建议变调升 **6-10key**
该模型的 [github仓库链接](https://github.com/innnky/so-vits-svc),如果想自己制作并训练模型可以访问这个 [github仓库](https://github.com/IceKyrin/sovits_guide)
""")
speaker_id = gr.Dropdown(label="音色", choices=['猫雷2.0', '云灏', '即霜', "奕兰秋"], value="猫雷2.0")
record_input = gr.Audio(source="microphone", label="录制你的声音", type="filepath", elem_id="audio_inputs")
upload_input = gr.Audio(source="upload", label="上传音频(长度小于45秒)", type="filepath",
elem_id="audio_inputs")
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")
out_audio = gr.Audio(label="Output Audio")
gr.Markdown(value="""
输出信息为音高平均偏差半音数量,体现转换音频的跑调情况(一般平均小于0.5个半音)
f0曲线可以直观的显示跑调情况,蓝色为输入音高,橙色为合成音频的音高
若**只看见橙色**,说明蓝色曲线被覆盖,转换效果较好
""")
out_message = gr.Textbox(label="跑调误差信息")
gr.Markdown(value="""f0曲线可以直观的显示跑调情况,蓝色为输入音高,橙色为合成音频的音高
若**只看见橙色**,说明蓝色曲线被覆盖,转换效果较好
""")
f0_image = gr.Image(label="f0曲线")
vc_submit.click(vc_fn, [speaker_id, record_input, upload_input, vc_transform],
[out_message, out_audio, f0_image])
with gr.TabItem("使用说明"):
gr.Markdown(value="""
0、合集:https://github.com/IceKyrin/sovits_guide/blob/main/README.md
1、仅支持sovit_f0(sovits2.0)模型
2、自行下载hubert-soft-0d54a1f4.pt改名为hubert.pt放置于pth文件夹下(已经下好了)
https://github.com/bshall/hubert/releases/tag/v0.1
3、pth文件夹下放置sovits2.0的模型
4、与模型配套的xxx.json,需有speaker项——人物列表
5、放无伴奏的音频、或网页内置录音,不要放奇奇怪怪的格式
6、仅供交流使用,不对用户行为负责
""")
app.launch()