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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 = "configs/config.json" | |
| model = Svc("logs/44k/G_9600.pth", "configs/config.json", cluster_model_path="logs/44k/checkpoint_best_legacy_500.pt") | |
| 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 > 100: | |
| return "请上传小于100s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=""" | |
| 风又音理 sovits4.0 在线demo | |
| 此demo为瞎做的 | |
| """) | |
| 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() | |