Spaces:
Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
@@ -44,133 +44,28 @@ def convert_yt_to_wav(url):
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return str(e), None
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with gr.Blocks() as app:
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gr.HTML("<h1> Simple RVC Inference - by Juuxn 💻 </h1>")
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gr.HTML("<h4> El espacio actual usa solo cpu, así que es solo para inferencia. Se recomienda duplicar el espacio para no tener problemas con las colas de procesamiento. </h4>")
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gr.Markdown("Simple RVC GPU Inference on colab: [](https://colab.research.google.com/drive/1NKqqTR04HujeBxzwe7jbYEvNi8LbxD_N?usp=sharing)")
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gr.Markdown(
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"[](https://huggingface.co/spaces/juuxn/SimpleRVC?duplicate=true)\n\n"
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)
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gr.Markdown("Recopilación de modelos que puedes usar: RVC + Kits ai. **[RVC Community Models](https://docs.google.com/spreadsheets/d/1owfUtQuLW9ReiIwg6U9UkkDmPOTkuNHf0OKQtWu1iaI)**")
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with gr.Tab("Inferencia"):
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model_url = gr.Textbox(placeholder="https://huggingface.co/AIVER-SE/BillieEilish/resolve/main/BillieEilish.zip", label="Url del modelo", show_label=True)
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with gr.Row():
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with gr.Column():
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audio_path = gr.Audio(label="Archivo de audio", show_label=True, type="filepath",)
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index_rate = gr.Slider(minimum=0, maximum=1, label="Search feature ratio:", value=0.75, interactive=True,)
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filter_radius1 = gr.Slider(minimum=0, maximum=7, label="Filtro (reducción de asperezas respiración)", value=3, step=1, interactive=True,)
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with gr.Column():
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f0_method = gr.Dropdown(choices=["harvest", "pm", "crepe", "crepe-tiny", "mangio-crepe", "mangio-crepe-tiny", "rmvpe"],
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value="rmvpe",
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label="Algoritmo", show_label=True)
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vc_transform0 = gr.Slider(minimum=-12, label="Número de semitonos, subir una octava: 12, bajar una octava: -12", value=0, maximum=12, step=1)
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protect0 = gr.Slider(
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minimum=0, maximum=0.5, label="Protejer las consonantes sordas y los sonidos respiratorios. 0.5 para desactivarlo.", value=0.33,
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step=0.01,
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interactive=True,
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)
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resample_sr1 = gr.Slider(
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minimum=0,
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maximum=48000,
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label="Re-muestreo sobre el audio de salida hasta la frecuencia de muestreo final. 0 para no re-muestrear.",
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value=0,
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step=1,
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interactive=True,
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)
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# Salida
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with gr.Row():
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vc_output1 = gr.Textbox(label="Salida")
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vc_output2 = gr.Audio(label="Audio de salida")
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btn = gr.Button(value="Convertir")
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btn.click(infer, inputs=[model_url, f0_method, audio_path, index_rate, vc_transform0, protect0, resample_sr1, filter_radius1], outputs=[vc_output1, vc_output2])
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with gr.TabItem("TTS"):
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with gr.Row():
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tts_text = gr.Textbox(
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label="Texto:",
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placeholder="Texto que deseas convertir a voz...",
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lines=6,
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)
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with gr.Row():
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tts_method = gr.Dropdown(choices=VOICE_METHODS, value="Edge-tts", label="Método TTS:", visible=True)
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tts_model = gr.Dropdown(choices=EDGE_VOICES, label="Modelo TTS:", visible=True, interactive=True)
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tts_api_key = gr.Textbox(label="ElevenLabs Api key", show_label=True, placeholder="4a4afce72349680c8e8b6fdcfaf2b65a",interactive=True, visible=False)
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tts_coqui_languages = gr.Radio(
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label="Language",
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choices=COQUI_LANGUAGES,
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value="en",
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visible=False
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)
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tts_btn = gr.Button(value="Convertir")
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with gr.Row():
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tts_vc_output1 = gr.Textbox(label="Salida")
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tts_vc_output2 = gr.Audio(label="Audio de salida")
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tts_btn.click(fn=tts_infer, inputs=[tts_text, tts_model_url, tts_method, tts_model, tts_api_key, tts_coqui_languages], outputs=[tts_vc_output1, tts_vc_output2])
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tts_msg = gr.Markdown("""**Recomiendo que te crees una cuenta de eleven labs y pongas tu clave de api, es gratis y tienes 10k caracteres de limite al mes.** <br/>
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""", visible=False)
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tts_method.change(fn=update_tts_methods_voice, inputs=[tts_method], outputs=[tts_model, tts_msg, tts_api_key, tts_coqui_languages])
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with gr.TabItem("Youtube"):
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gr.Markdown("## Convertir video de Youtube a audio")
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with gr.Row():
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yt_url = gr.Textbox(
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label="Url del video:",
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placeholder="https://www.youtube.com/watch?v=3vEiqil5d3Q"
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)
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yt_btn = gr.Button(value="Convertir")
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with gr.Row():
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yt_output1 = gr.Textbox(label="Salida")
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yt_output2 = gr.Audio(label="Audio de salida")
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yt_btn.click(fn=convert_yt_to_wav, inputs=[yt_url], outputs=[yt_output1, yt_output2])
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# with gr.TabItem("Mejora de audio"):
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# enhance_input_audio = gr.Audio(label="Audio de entrada")
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# enhance_output_audio = gr.Audio(label="Audio de salida")
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# btn_enhance_audio = gr.Button()
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# # btn_enhance_audio.click(fn=audio_enhance, inputs=[enhance_input_audio], outputs=[enhance_output_audio])
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with gr.Tab("Modelos"):
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gr.HTML("<h4>Buscar modelos</h4>")
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search_name = gr.Textbox(placeholder="Billie Eillish (RVC v2 - 100 epoch)", label="Nombre", show_label=True)
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# Salida
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with gr.Row():
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sarch_output = gr.Markdown(label="
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btn_search_model = gr.Button(value="
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btn_search_model.click(fn=search_model, inputs=[search_name], outputs=[sarch_output])
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gr.HTML("<
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post_name = gr.Textbox(placeholder="
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post_model_url = gr.Textbox(placeholder="https://huggingface.co/
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post_creator = gr.Textbox(placeholder="
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post_version = gr.Dropdown(choices=["RVC v1", "RVC v2"], value="RVC
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# Salida
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with gr.Row():
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post_output = gr.Markdown(label="
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btn_post_model = gr.Button(value="
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btn_post_model.click(fn=post_model, inputs=[post_name, post_model_url, post_version, post_creator], outputs=[post_output])
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# with gr.Column():
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return str(e), None
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with gr.Blocks() as app:
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with gr.Tab("模型搜索及上传"):
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gr.HTML("<h3>搜索AI歌手模型</h3>")
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search_name = gr.Textbox(placeholder="孙燕姿", label="请填写模型名称进行搜索", show_label=True)
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# Salida
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with gr.Row():
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sarch_output = gr.Markdown(label="搜索结果")
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btn_search_model = gr.Button(value="开始搜索吧💖")
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btn_search_model.click(fn=search_model, inputs=[search_name], outputs=[sarch_output])
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gr.HTML("<h3>上传AI歌手模型至社区,上传完成后您立即可以搜索到您上传的模型</h3>")
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post_name = gr.Textbox(placeholder="滔滔歌姬", label="请填写模型名称", show_label=True)
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post_model_url = gr.Textbox(placeholder="https://huggingface.co/kevinwang676/RVC-models/resolve/main/talktalkgirl.zip", label="模型链接", info="1.推荐使用Hugging Face存放模型 2.复制Hugging Face模型链接后,需要将链接中的blob四个字母替换成resolve,使模型可以通过链接直接下载", show_label=True)
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post_creator = gr.Textbox(placeholder="滔滔AI", label="模型贡献者", info="可填写您的昵称或任何有趣的ID", show_label=True)
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post_version = gr.Dropdown(choices=["RVC v1", "RVC v2"], value="RVC v2", label="RVC模型版本", show_label=True)
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# Salida
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with gr.Row():
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post_output = gr.Markdown(label="模型上传状态")
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btn_post_model = gr.Button(value="开始上传吧💕")
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btn_post_model.click(fn=post_model, inputs=[post_name, post_model_url, post_version, post_creator], outputs=[post_output])
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# with gr.Column():
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