70 lines
3.1 KiB
Python
70 lines
3.1 KiB
Python
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import io
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import os
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# os.system("wget -P cvec/ https://huggingface.co/spaces/innnky/nanami/resolve/main/checkpoint_best_legacy_500.pt")
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import gradio as gr
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import librosa
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import numpy as np
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import soundfile
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from inference.infer_tool import Svc
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import logging
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logging.getLogger('numba').setLevel(logging.WARNING)
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logging.getLogger('markdown_it').setLevel(logging.WARNING)
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logging.getLogger('urllib3').setLevel(logging.WARNING)
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logging.getLogger('matplotlib').setLevel(logging.WARNING)
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config_path = "configs/config.json"
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model = Svc("logs/44k/G_114400.pth", "configs/config.json", cluster_model_path="logs/44k/kmeans_10000.pt")
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def vc_fn(sid, input_audio, vc_transform, auto_f0,cluster_ratio, slice_db, noise_scale):
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if input_audio is None:
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return "You need to upload an audio", None
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sampling_rate, audio = input_audio
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# print(audio.shape,sampling_rate)
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duration = audio.shape[0] / sampling_rate
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if duration > 90:
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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
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audio = (audio / np.iinfo(audio.dtype).max).astype(np.float32)
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if len(audio.shape) > 1:
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audio = librosa.to_mono(audio.transpose(1, 0))
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if sampling_rate != 16000:
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audio = librosa.resample(audio, orig_sr=sampling_rate, target_sr=16000)
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print(audio.shape)
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out_wav_path = "temp.wav"
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soundfile.write(out_wav_path, audio, 16000, format="wav")
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print( cluster_ratio, auto_f0, noise_scale)
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_audio = model.slice_inference(out_wav_path, sid, vc_transform, slice_db, cluster_ratio, auto_f0, noise_scale)
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return "Success", (44100, _audio)
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app = gr.Blocks()
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with app:
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with gr.Tabs():
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with gr.TabItem("Basic"):
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gr.Markdown(value="""
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sovits4.0 在线demo
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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
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""")
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spks = list(model.spk2id.keys())
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sid = gr.Dropdown(label="音色", choices=spks, value=spks[0])
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vc_input3 = gr.Audio(label="上传音频（长度小于90秒）")
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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)
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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)
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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)
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slice_db = gr.Number(label="切片阈值", value=-40)
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noise_scale = gr.Number(label="noise_scale 建议不要动，会影响音质，玄学参数", value=0.4)
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vc_submit = gr.Button("转换", variant="primary")
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vc_output1 = gr.Textbox(label="Output Message")
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vc_output2 = gr.Audio(label="Output Audio")
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vc_submit.click(vc_fn, [sid, vc_input3, vc_transform,auto_f0,cluster_ratio, slice_db, noise_scale], [vc_output1, vc_output2])
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app.launch()
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