- 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>
17 lines
364 B
Docker
17 lines
364 B
Docker
FROM pytorch/pytorch:2.7.0-cuda12.8-cudnn9-runtime
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ENV DEBIAN_FRONTEND=noninteractive
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ENV PYTHONUNBUFFERED=1
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ENV PYTHONDONTWRITEBYTECODE=1
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WORKDIR /app
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COPY requirements.txt .
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RUN pip install --no-cache-dir -r requirements.txt
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COPY vega_ml/ /app/vega_ml/
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COPY entrypoint.sh /app/entrypoint.sh
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RUN chmod +x /app/entrypoint.sh
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ENTRYPOINT ["/app/entrypoint.sh"] |