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Pipeline complet Radiacode 103 - identification automatique d'isotopes

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- 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>
This commit is contained in:
Jacquin Antoine
2026-05-19 12:29:56 +02:00
commit 745a64b342
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train/requirements.txt Normal file
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numpy>=1.24.0
scipy>=1.10.0
pillow>=9.0.0
scikit-learn>=1.3.0