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TheStinger
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458da1c
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Parent(s):
56d3f1c
Update app.py
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app.py
CHANGED
@@ -1,52 +1,21 @@
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import gradio as gr
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from tts_voice import tts_order_voice
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import edge_tts
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import gradio as gr
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import tempfile
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import anyio
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communicate = edge_tts.Communicate(text, voice)
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with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as tmp_file:
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tmp_path = tmp_file.name
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await communicate.save(tmp_path)
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input_text = gr.inputs.Textbox(lines=5, label="Text")
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output_text = gr.outputs.Textbox(label="Text input")
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output_audio = gr.outputs.Audio(type="filepath", label="Audio output")
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default_language = list(language_dict.keys())[0]
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language = gr.inputs.Dropdown(choices=list(language_dict.keys()), default=default_language, label="Choose the language and the model")
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interface = gr.Interface(fn=text_to_speech_edge, inputs=[input_text, language], outputs=[output_text, output_audio], title="Ilaria TTS 💖")
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if __name__ == "__main__":
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anyio.run(interface.launch, backend="asyncio")
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pass
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elif app_name == 'App 2':
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# Codice per l'applicazione 2
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pass
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elif app_name == 'App 3':
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# Codice per l'applicazione 3
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pass
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elif app_name == 'App 4':
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# Codice per l'applicazione 4
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pass
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# Crea l'interfaccia principale con la selezione dell'applicazione
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iface = gr.Interface(fn=select_app, inputs="dropdown", outputs="textbox")
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iface.launch()
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import gradio as gr
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import matplotlib.pyplot as plt
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import numpy as np
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from scipy.io import wavfile
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def create_spectrogram(audio_file):
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# Leggi il file audio
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sample_rate, data = wavfile.read(audio_file.name)
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# Crea lo spettrogramma
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plt.specgram(data, Fs=sample_rate)
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# Salva lo spettrogramma in un file PNG
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plt.savefig('spectrogram.png')
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# Ritorna il file PNG dello spettrogramma
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return 'spectrogram.png'
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# Crea l'interfaccia Gradio
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iface = gr.Interface(fn=create_spectrogram, inputs=gr.inputs.Audio(type="file"), outputs="image")
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iface.launch()
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