Pipeline complet Radiacode 103 - identification automatique d'isotopes
- VegaModel CNN-FCNN 34.5M params, 82 isotopes, val acc 99.89% - Generation 50k spectres synthetiques 1D (12-24h durees) - Entrainement 100 epochs sur RTX 5060 Ti (CUDA 12.8, Blackwell) - Detection continue avec soustraction du background - Capture background 24h avec gestion deconnexion - Docker Compose : conteneur train (GPU) + detect (CPU/USB) - Modele entraite inclus (vega_best.pt, 395 Mo) Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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# Modeles entraines
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models/vega_epoch_*.pt
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models/vega_final.pt
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# Donnees synthetiques (4+ Go)
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data/synthetic/
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# Background (genere en cours de capture)
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data/background_24h.npy
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data/background_snapshot.json
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# Logs
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logs/*.log
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logs/*.json
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# Python
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__pycache__/
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*.pyc
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*.pyo
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*.egg-info/
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.eggs/
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dist/
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build/
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*.egg
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# Docker
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*.tar
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# IDE
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.vscode/
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.idea/
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*.swp
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*.swo
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# OS
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.DS_Store
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Thumbs.db
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# Environnement
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.env
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