43 lines
1.8 KiB
Plaintext
43 lines
1.8 KiB
Plaintext
import gradio as gr
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import torch
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import scipy.io.wavfile
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import numpy as np
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import tempfile
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from audiocraft.models import MusicGen, AudioGen
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print("🔄 Chargement des modèles...")
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music_model = MusicGen.get_pretrained("facebook/musicgen-small")
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audio_model = AudioGen.get_pretrained("facebook/audiogen-medium")
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def generate_music(prompt, duration=10):
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music_model.set_generation_params(duration=duration)
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wav = music_model.generate([prompt])
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wav_np = wav[0, 0].cpu().numpy()
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with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as f:
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scipy.io.wavfile.write(f.name, music_model.sample_rate, (wav_np * 32767).astype(np.int16))
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return f.name
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def generate_sound(prompt, duration=5):
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audio_model.set_generation_params(duration=duration)
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wav = audio_model.generate([prompt])
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wav_np = wav[0, 0].cpu().numpy()
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with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as f:
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scipy.io.wavfile.write(f.name, audio_model.sample_rate, (wav_np * 32767).astype(np.int16))
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return f.name
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with gr.Blocks(title="🎙️ Studio Audio IA") as demo:
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gr.Markdown("## 🎙️ Studio Audio IA")
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with gr.Tab("🎵 Musique"):
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p1 = gr.Textbox(label="Prompt")
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d1 = gr.Slider(5, 30, value=10, step=5, label="Durée (s)")
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b1 = gr.Button("Générer")
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o1 = gr.Audio(label="Résultat")
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b1.click(generate_music, inputs=[p1, d1], outputs=o1)
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with gr.Tab("🔊 Bruitages"):
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p2 = gr.Textbox(label="Prompt")
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d2 = gr.Slider(2, 15, value=5, label="Durée (s)")
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b2 = gr.Button("Générer")
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o2 = gr.Audio(label="Résultat")
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b2.click(generate_sound, inputs=[p2, d2], outputs=o2)
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demo.launch(server_name="0.0.0.0", server_port=7860, share=False) |