SimpleRVC / app.py
xJuuzouYTx
[ADD] error messages
46a6192
import gradio as gr
import os
from constants import VOICE_METHODS, BARK_VOICES, EDGE_VOICES
import platform
from models.model import *
from tts.conversion import COQUI_LANGUAGES
import pytube
import os
import traceback
from pydub import AudioSegment
# from audio_enhance.functions import audio_enhance
def convert_yt_to_wav(url):
if not url:
return "Primero introduce el enlace del video", None
try:
print(f"Convirtiendo video {url}...")
# Descargar el video utilizando pytube
video = pytube.YouTube(url)
stream = video.streams.filter(only_audio=True).first()
video_output_folder = os.path.join(f"yt_videos") # Ruta de destino de la carpeta
audio_output_folder = 'audios'
print("Downloading video")
video_file_path = stream.download(output_path=video_output_folder)
print(video_file_path)
file_name = os.path.basename(video_file_path)
audio_file_path = os.path.join(audio_output_folder, file_name.replace('.mp4','.wav'))
# convert mp4 to wav
print("Converting to wav")
sound = AudioSegment.from_file(video_file_path,format="mp4")
sound.export(audio_file_path, format="wav")
if os.path.exists(video_file_path):
os.remove(video_file_path)
return "Success", audio_file_path
except ConnectionResetError as cre:
return "Se ha perdido la conexi贸n, recarga o reintentalo nuevamente m谩s tarde.", None
except Exception as e:
return str(e), None
with gr.Blocks() as app:
gr.HTML("<h1> Simple RVC Inference - by Juuxn 馃捇 </h1>")
gr.HTML("<h4> El espacio actual usa solo cpu, as铆 que es solo para inferencia. Se recomienda duplicar el espacio para no tener problemas con las colas de procesamiento. </h4>")
gr.Markdown("Simple RVC GPU Inference on colab: [![Open In Colab](https://img.shields.io/badge/Colab-F9AB00?style=for-the-badge&logo=googlecolab&color=525252)](https://colab.research.google.com/drive/1NKqqTR04HujeBxzwe7jbYEvNi8LbxD_N?usp=sharing)")
gr.Markdown(
"[![Duplicate this Space](https://huggingface.co/datasets/huggingface/badges/raw/main/duplicate-this-space-sm-dark.svg)](https://huggingface.co/spaces/juuxn/SimpleRVC?duplicate=true)\n\n"
)
gr.Markdown("Recopilaci贸n de modelos que puedes usar: RVC + Kits ai. **[RVC Community Models](https://docs.google.com/spreadsheets/d/1owfUtQuLW9ReiIwg6U9UkkDmPOTkuNHf0OKQtWu1iaI)**")
with gr.Tab("Inferencia"):
model_url = gr.Textbox(placeholder="https://huggingface.co/AIVER-SE/BillieEilish/resolve/main/BillieEilish.zip", label="Url del modelo", show_label=True)
with gr.Row():
with gr.Column():
audio_path = gr.Audio(label="Archivo de audio", show_label=True, type="filepath",)
index_rate = gr.Slider(minimum=0, maximum=1, label="Search feature ratio:", value=0.75, interactive=True,)
filter_radius1 = gr.Slider(minimum=0, maximum=7, label="Filtro (reducci贸n de asperezas respiraci贸n)", value=3, step=1, interactive=True,)
with gr.Column():
f0_method = gr.Dropdown(choices=["harvest", "pm", "crepe", "crepe-tiny", "mangio-crepe", "mangio-crepe-tiny", "rmvpe"],
value="rmvpe",
label="Algoritmo", show_label=True)
vc_transform0 = gr.Slider(minimum=-12, label="N煤mero de semitonos, subir una octava: 12, bajar una octava: -12", value=0, maximum=12, step=1)
protect0 = gr.Slider(
minimum=0, maximum=0.5, label="Protejer las consonantes sordas y los sonidos respiratorios. 0.5 para desactivarlo.", value=0.33,
step=0.01,
interactive=True,
)
resample_sr1 = gr.Slider(
minimum=0,
maximum=48000,
label="Re-muestreo sobre el audio de salida hasta la frecuencia de muestreo final. 0 para no re-muestrear.",
value=0,
step=1,
interactive=True,
)
# Salida
with gr.Row():
vc_output1 = gr.Textbox(label="Salida")
vc_output2 = gr.Audio(label="Audio de salida")
btn = gr.Button(value="Convertir")
btn.click(infer, inputs=[model_url, f0_method, audio_path, index_rate, vc_transform0, protect0, resample_sr1, filter_radius1], outputs=[vc_output1, vc_output2])
with gr.TabItem("TTS"):
with gr.Row():
tts_text = gr.Textbox(
label="Texto:",
placeholder="Texto que deseas convertir a voz...",
lines=6,
)
with gr.Column():
with gr.Row():
tts_model_url = gr.Textbox(placeholder="https://huggingface.co/AIVER-SE/BillieEilish/resolve/main/BillieEilish.zip", label="Url del modelo RVC", show_label=True)
with gr.Row():
tts_method = gr.Dropdown(choices=VOICE_METHODS, value="Edge-tts", label="M茅todo TTS:", visible=True)
tts_model = gr.Dropdown(choices=EDGE_VOICES, label="Modelo TTS:", visible=True, interactive=True)
tts_api_key = gr.Textbox(label="ElevenLabs Api key", show_label=True, placeholder="4a4afce72349680c8e8b6fdcfaf2b65a",interactive=True, visible=False)
tts_coqui_languages = gr.Radio(
label="Language",
choices=COQUI_LANGUAGES,
value="en",
visible=False
)
tts_btn = gr.Button(value="Convertir")
with gr.Row():
tts_vc_output1 = gr.Textbox(label="Salida")
tts_vc_output2 = gr.Audio(label="Audio de salida")
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])
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/>
![Imgur](https://imgur.com/HH6YTu0.png)
""", visible=False)
tts_method.change(fn=update_tts_methods_voice, inputs=[tts_method], outputs=[tts_model, tts_msg, tts_api_key, tts_coqui_languages])
with gr.TabItem("Youtube"):
gr.Markdown("## Convertir video de Youtube a audio")
with gr.Row():
yt_url = gr.Textbox(
label="Url del video:",
placeholder="https://www.youtube.com/watch?v=3vEiqil5d3Q"
)
yt_btn = gr.Button(value="Convertir")
with gr.Row():
yt_output1 = gr.Textbox(label="Salida")
yt_output2 = gr.Audio(label="Audio de salida")
yt_btn.click(fn=convert_yt_to_wav, inputs=[yt_url], outputs=[yt_output1, yt_output2])
# with gr.TabItem("Mejora de audio"):
# enhance_input_audio = gr.Audio(label="Audio de entrada")
# enhance_output_audio = gr.Audio(label="Audio de salida")
# btn_enhance_audio = gr.Button()
# # btn_enhance_audio.click(fn=audio_enhance, inputs=[enhance_input_audio], outputs=[enhance_output_audio])
with gr.Tab("Modelos"):
gr.HTML("<h4>Buscar modelos</h4>")
search_name = gr.Textbox(placeholder="Billie Eillish (RVC v2 - 100 epoch)", label="Nombre", show_label=True)
# Salida
with gr.Row():
sarch_output = gr.Markdown(label="Salida")
btn_search_model = gr.Button(value="Buscar")
btn_search_model.click(fn=search_model, inputs=[search_name], outputs=[sarch_output])
gr.HTML("<h4>Publica tu modelo</h4>")
post_name = gr.Textbox(placeholder="Billie Eillish (RVC v2 - 100 epoch)", label="Nombre", show_label=True)
post_model_url = gr.Textbox(placeholder="https://huggingface.co/AIVER-SE/BillieEilish/resolve/main/BillieEilish.zip", label="Url del modelo", show_label=True)
post_creator = gr.Textbox(placeholder="ID de discord o enlace al perfil del creador", label="Creador", show_label=True)
post_version = gr.Dropdown(choices=["RVC v1", "RVC v2"], value="RVC v1", label="Versi贸n", show_label=True)
# Salida
with gr.Row():
post_output = gr.Markdown(label="Salida")
btn_post_model = gr.Button(value="Publicar")
btn_post_model.click(fn=post_model, inputs=[post_name, post_model_url, post_version, post_creator], outputs=[post_output])
# with gr.Column():
# model_voice_path07 = gr.Dropdown(
# label=i18n("RVC Model:"),
# choices=sorted(names),
# value=default_weight,
# )
# best_match_index_path1, _ = match_index(
# model_voice_path07.value
# )
# file_index2_07 = gr.Dropdown(
# label=i18n("Select the .index file:"),
# choices=get_indexes(),
# value=best_match_index_path1,
# interactive=True,
# allow_custom_value=True,
# )
# with gr.Row():
# refresh_button_ = gr.Button(i18n("Refresh"), variant="primary")
# refresh_button_.click(
# fn=change_choices2,
# inputs=[],
# outputs=[model_voice_path07, file_index2_07],
# )
# with gr.Row():
# original_ttsvoice = gr.Audio(label=i18n("Audio TTS:"))
# ttsvoice = gr.Audio(label=i18n("Audio RVC:"))
# with gr.Row():
# button_test = gr.Button(i18n("Convert"), variant="primary")
# button_test.click(
# tts.use_tts,
# inputs=[
# text_test,
# tts_test,
# model_voice_path07,
# file_index2_07,
# # transpose_test,
# vc_transform0,
# f0method8,
# index_rate1,
# crepe_hop_length,
# f0_autotune,
# ttsmethod_test,
# ],
# outputs=[ttsvoice, original_ttsvoice],
# )
app.queue(concurrency_count=200, max_size=1022).launch()
#share=True