asdrolf
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Commit
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a221e42
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7194d34
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Browse files- app.py +11 -4
- requirements.txt +1 -1
app.py
CHANGED
@@ -1,5 +1,5 @@
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import streamlit as st
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from
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from faster_whisper import WhisperModel
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from pyannote.audio import Pipeline
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import pyannote.core
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@@ -63,12 +63,16 @@ def main():
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by Wallner Group
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""", unsafe_allow_html=True)
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-
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-
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# Guardar el archivo de audio grabado
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with open("audio_temp.wav", "wb") as f:
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f.write(
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# Opción para cargar archivo de audio
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audio_file = st.file_uploader("Cargar archivo de audio", type=['wav'])
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@@ -77,7 +81,10 @@ def main():
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# Guardar el archivo de audio cargado
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with open("audio_temp.wav", "wb") as f:
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f.write(audio_file.getbuffer())
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# Cargar y ejecutar los modelos
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speaker_segments = process_audio("audio_temp.wav")
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import streamlit as st
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from audio_recorder_streamlit import audio_recorder
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from faster_whisper import WhisperModel
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from pyannote.audio import Pipeline
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import pyannote.core
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by Wallner Group
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""", unsafe_allow_html=True)
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audio_ready = False # Variable para indicar si el audio está listo para ser procesado
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# Widget de grabación de audio
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audio_bytes = audio_recorder()
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if audio_bytes:
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# Guardar el archivo de audio grabado
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with open("audio_temp.wav", "wb") as f:
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f.write(audio_bytes)
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audio_ready = True
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# Opción para cargar archivo de audio
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audio_file = st.file_uploader("Cargar archivo de audio", type=['wav'])
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# Guardar el archivo de audio cargado
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with open("audio_temp.wav", "wb") as f:
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f.write(audio_file.getbuffer())
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audio_ready = True
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# Procesar el audio si está listo
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if audio_ready:
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# Cargar y ejecutar los modelos
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speaker_segments = process_audio("audio_temp.wav")
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requirements.txt
CHANGED
@@ -1,4 +1,4 @@
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faster_whisper
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pyannote.audio
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pyannote.core
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-
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faster_whisper
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pyannote.audio
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pyannote.core
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audio-recorder-streamlit
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