Merge branch '4.0' of https://github.com/svc-develop-team/so-vits-svc into 4.0
This commit is contained in:
ylzz1997
commit
ffe4800aaf
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@ -205,7 +205,9 @@ Introduction: The mean filtering of F0 can effectively reduce the hoarse sound c
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### [](https://colab.research.google.com/drive/1kv-3y2DmZo0uya8pEr1xk7cSB-4e_Pct?usp=sharing) [sovits4_for_colab.ipynb](https://colab.research.google.com/drive/1kv-3y2DmZo0uya8pEr1xk7cSB-4e_Pct?usp=sharing)
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#### [23/03/16] No longer need to download hubert manually
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**[23/03/16] No longer need to download hubert manually**
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**[23/04/14] Support NSF_HIFIGAN enhancer**
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## 📤 Exporting to Onnx
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@ -205,7 +205,9 @@ python inference_main.py -m "logs/44k/G_30400.pth" -c "configs/config.json" -n "
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### [](https://colab.research.google.com/drive/1kv-3y2DmZo0uya8pEr1xk7cSB-4e_Pct?usp=sharing) [sovits4_for_colab.ipynb](https://colab.research.google.com/drive/1kv-3y2DmZo0uya8pEr1xk7cSB-4e_Pct?usp=sharing)
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#### [23/03/16] 不再需要手动下载hubert
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**[23/03/16] 不再需要手动下载hubert**
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**[23/04/14] 支持NSF_HIFIGAN增强器**
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## 📤 Onnx导出
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@ -31,13 +31,13 @@ def main():
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parser.add_argument('-s', '--spk_list', type=str, nargs='+', default=['nen'], help='合成目标说话人名称')
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# 可选项部分
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parser.add_argument('-a', '--auto_predict_f0', action='store_true', default=False,help='语音转换自动预测音高，转换歌声时不要打开这个会严重跑调')
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parser.add_argument('-a', '--auto_predict_f0', type=bool, default=False, help='语音转换自动预测音高，转换歌声时不要打开这个会严重跑调')
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parser.add_argument('-cm', '--cluster_model_path', type=str, default="logs/44k/kmeans_10000.pt", help='聚类模型路径，如果没有训练聚类则随便填')
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parser.add_argument('-cr', '--cluster_infer_ratio', type=float, default=0, help='聚类方案占比，范围0-1，若没有训练聚类模型则默认0即可')
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parser.add_argument('-lg', '--linear_gradient', type=float, default=0, help='两段音频切片的交叉淡入长度，如果强制切片后出现人声不连贯可调整该数值，如果连贯建议采用默认值0，单位为秒')
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parser.add_argument('-fmp', '--f0_mean_pooling', type=bool, default=False, help='是否对F0使用均值滤波器(池化)，对部分哑音有改善。注意，启动该选项会导致推理速度下降，默认关闭')
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parser.add_argument('-eh', '--enhance', type=bool, default=False, help='是否使用NSF_HIFIGAN增强器,该选项对部分训练集少的模型有一定的音质增强效果，但是对训练好的模型有反面效果，默认关闭')
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# 不用动的部分
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parser.add_argument('-sd', '--slice_db', type=int, default=-40, help='默认-40，嘈杂的音频可以-30，干声保留呼吸可以-50')
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parser.add_argument('-d', '--device', type=str, default=None, help='推理设备，None则为自动选择cpu和gpu')
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33
webUI.py
33
webUI.py
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@ -93,17 +93,18 @@ def vc_fn(sid, input_audio, vc_transform, auto_f0,cluster_ratio, slice_db, noise
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return f"推理成功，音频文件保存为results/{filename}", (model.target_sample, _audio)
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except Exception as e:
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if debug: traceback.print_exc()
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raise gr.Error(e)
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raise gr.Error(e)
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except Exception as e:
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if debug: traceback.print_exc()
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raise gr.Error(e)
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def tts_func(_text,_rate):
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def tts_func(_text,_rate,_voice):
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#使用edge-tts把文字转成音频
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# voice = "zh-CN-XiaoyiNeural"#女性，较高音
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# voice = "zh-CN-YunxiNeural"#男性
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voice = "zh-CN-YunxiNeural"#男性
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if ( _voice == "女" ) : voice = "zh-CN-XiaoyiNeural"
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output_file = _text[0:10]+".wav"
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# communicate = edge_tts.Communicate(_text, voice)
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# await communicate.save(output_file)
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@ -112,21 +113,24 @@ def tts_func(_text,_rate):
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elif _rate<0:
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ratestr="{:.0%}".format(_rate)#减号自带
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p=subprocess.Popen(["edge-tts",
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"--text",_text,
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"--write-media",output_file,
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"--voice",voice,
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"--rate="+ratestr]
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p=subprocess.Popen("edge-tts "+
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" --text "+_text+
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" --write-media "+output_file+
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" --voice "+voice+
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" --rate="+ratestr
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,shell=True,
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stdout=subprocess.PIPE,
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stdin=subprocess.PIPE)
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p.wait()
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p.wait()
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return output_file
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def text_clear(text):
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return re.sub(r"[\n\,\(\) ]", "", text)
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def vc_fn2(sid, input_audio, vc_transform, auto_f0,cluster_ratio, slice_db, noise_scale,pad_seconds,cl_num,lg_num,lgr_num,text2tts,tts_rate,F0_mean_pooling,enhancer_adaptive_key):
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def vc_fn2(sid, input_audio, vc_transform, auto_f0,cluster_ratio, slice_db, noise_scale,pad_seconds,cl_num,lg_num,lgr_num,text2tts,tts_rate,tts_voice,F0_mean_pooling,enhancer_adaptive_key):
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#使用edge-tts把文字转成音频
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output_file=tts_func(text2tts,tts_rate)
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text2tts=text_clear(text2tts)
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output_file=tts_func(text2tts,tts_rate,tts_voice)
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#调整采样率
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sr2=44100
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@ -136,7 +140,7 @@ def vc_fn2(sid, input_audio, vc_transform, auto_f0,cluster_ratio, slice_db, nois
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wavfile.write(save_path2,sr2,
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(wav2 * np.iinfo(np.int16).max).astype(np.int16)
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)
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#读取音频
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sample_rate, data=gr_pu.audio_from_file(save_path2)
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vc_input=(sample_rate, data)
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@ -181,7 +185,7 @@ with gr.Blocks(
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sid = gr.Dropdown(label="音色（说话人）")
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sid_output = gr.Textbox(label="Output Message")
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with gr.Row(variant="panel"):
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with gr.Column():
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gr.Markdown(value="""
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@ -193,7 +197,7 @@ with gr.Blocks(
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cluster_ratio = gr.Number(label="聚类模型混合比例，0-1之间，0即不启用聚类。使用聚类模型能提升音色相似度，但会导致咬字下降（如果使用建议0.5左右）", value=0)
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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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with gr.Column():
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with gr.Column():
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pad_seconds = gr.Number(label="推理音频pad秒数，由于未知原因开头结尾会有异响，pad一小段静音段后就不会出现", value=0.5)
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cl_num = gr.Number(label="音频自动切片，0为不切片，单位为秒(s)", value=0)
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lg_num = gr.Number(label="两端音频切片的交叉淡入长度，如果自动切片后出现人声不连贯可调整该数值，如果连贯建议采用默认值0，注意，该设置会影响推理速度，单位为秒/s", value=0)
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@ -206,6 +210,7 @@ with gr.Blocks(
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with gr.TabItem("文字转音频"):
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text2tts=gr.Textbox(label="在此输入要转译的文字。注意，使用该功能建议打开F0预测，不然会很怪")
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tts_rate = gr.Number(label="tts语速", value=0)
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tts_voice = gr.Radio(label="性别",choices=["男","女"], value="男")
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vc_submit2 = gr.Button("文字转换", variant="primary")
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with gr.Row():
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with gr.Column():
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@ -219,7 +224,7 @@ with gr.Blocks(
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""")
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debug_button = gr.Checkbox(label="Debug模式，如果向社区反馈BUG需要打开，打开后控制台可以显示具体错误提示", value=debug)
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vc_submit.click(vc_fn, [sid, vc_input3, vc_transform,auto_f0,cluster_ratio, slice_db, noise_scale,pad_seconds,cl_num,lg_num,lgr_num,F0_mean_pooling,enhancer_adaptive_key], [vc_output1, vc_output2])
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vc_submit2.click(vc_fn2, [sid, vc_input3, vc_transform,auto_f0,cluster_ratio, slice_db, noise_scale,pad_seconds,cl_num,lg_num,lgr_num,text2tts,tts_rate,F0_mean_pooling,enhancer_adaptive_key], [vc_output1, vc_output2])
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vc_submit2.click(vc_fn2, [sid, vc_input3, vc_transform,auto_f0,cluster_ratio, slice_db, noise_scale,pad_seconds,cl_num,lg_num,lgr_num,text2tts,tts_rate,tts_voice,F0_mean_pooling,enhancer_adaptive_key], [vc_output1, vc_output2])
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debug_button.change(debug_change,[],[])
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model_load_button.click(modelAnalysis,[model_path,config_path,cluster_model_path,device,enhance],[sid,sid_output])
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model_unload_button.click(modelUnload,[],[sid,sid_output])
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