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Update app.py
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app.py
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import gradio as gr
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import requests
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import tempfile
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# Preset audio URLs
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INPUT_ROOT = 'https://adasp.telecom-paris.fr/rc-ext/demos_companion-pages/vqvae_examples/'
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@@ -137,7 +186,7 @@ with gr.Blocks(title="VQ-VAE Timbre Transfer", theme=gr.themes.Soft()) as demo:
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Transfer the timbre (tone/texture) from one audio source to another while preserving the musical content.
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**Content**: Musical notes/melody that will be preserved
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**Style**: Instrument timbre/texture that will be applied
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### How It Works:
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outputs=[output_audio, status_msg]
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)
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import os
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import tempfile
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import requests
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import gradio as gr
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import torch
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import librosa
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import numpy as np
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import subprocess
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import sys
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def install_dependencies():
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"""Install required packages for deployment"""
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try:
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if not os.path.exists('ss-vq-vae'):
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print("Cloning ss-vq-vae repository...")
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subprocess.run(['git', 'clone', 'https://github.com/cifkao/ss-vq-vae.git'], check=True)
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subprocess.run([sys.executable, '-m', 'pip', 'install', './ss-vq-vae/src'], check=True)
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print("Dependencies installed successfully!")
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except Exception as e:
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print(f"Error installing dependencies: {e}")
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raise
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# Install dependencies for deployment
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try:
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install_dependencies()
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import confugue
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from ss_vq_vae.models.vqvae_oneshot import Experiment
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except ImportError:
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print("ss-vq-vae not found. Please install manually or run in Colab.")
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sys.exit(1)
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def download_model():
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"""Download model files if they don't exist"""
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model_dir = 'ss-vq-vae/experiments/model'
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os.makedirs(model_dir, exist_ok=True)
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model_path = os.path.join(model_dir, 'model_state.pt')
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if not os.path.exists(model_path):
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print("Downloading model...")
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url = 'https://adasp.telecom-paris.fr/rc-ext/demos_companion-pages/vqvae_examples/ssvqvae_model_state.pt'
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response = requests.get(url)
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with open(model_path, 'wb') as f:
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f.write(response.content)
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print("Model downloaded successfully!")
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# Initialize model
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download_model()
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logdir = 'ss-vq-vae/experiments/model'
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cfg = confugue.Configuration.from_yaml_file(os.path.join(logdir, 'config.yaml'))
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exp = cfg.configure(Experiment, logdir=logdir, device='cpu')
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exp.model.load_state_dict(torch.load(os.path.join(logdir, 'model_state.pt'), map_location=exp.device))
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exp.model.train(False)
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# Preset audio URLs
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INPUT_ROOT = 'https://adasp.telecom-paris.fr/rc-ext/demos_companion-pages/vqvae_examples/'
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Transfer the timbre (tone/texture) from one audio source to another while preserving the musical content.
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**Content**: Musical notes/melody that will be preserved
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**Style**: Instrument timbre/texture that will be applied
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### How It Works:
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outputs=[output_audio, status_msg]
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)
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gr.Markdown("""
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### 🔧 Troubleshooting
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- **Poor transfer quality?** Try different instrument combinations or adjust max duration
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- **Audio doesn't load?** Check internet connection or try different presets
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- **Processing slow?** Reduce max duration or try shorter audio clips
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### 📖 Citation
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Original work by Ondřej Cífka (InterDigital R&D and Télécom Paris, 2020).
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Demo by Ali Dulaimi.
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""")
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if __name__ == "__main__":
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demo.launch(share=True, debug=True, height=1400)
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