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Samples generation utilities managed with uv

Project description

KC-DATA-SAMPLING

Installation rapide

uv venv .venv
source .venv/bin/activate
uv sync 

Lancement

1. Génération d'images augmentées et adversariales

# Images corrompues (augmentations)
python augment_run.py --config examples/augment_all.yml

# Images adversariales (FGSM, PGD, C&W, APGD)
python adversarial_run.py --config examples/adversarial_fgsm.yml
python adversarial_run.py --config examples/adversarial_all.yml

Note: Ces scripts génèrent maintenant les images sans inférence. Les colonnes générées sont :

  • sample_uuid (nouveau UUID unique)
  • parent_sample_uuid (lien vers l'échantillon d'origine)
  • image_hash (hash SHA256)
  • sample_id, sample_type, class_id, class_name, split
  • transform_id, transform_name, transform_level, transform_params
  • image_bytes

2. Inférence sur les images

# Inférence de base (garde toutes les colonnes + ajoute prédictions)
python kc_inference.py --config examples/kc_inference.yaml

# mode in-place (onmodifie le fichier directement)
python kc_inference.py --config examples/kc_inference.yaml --in-place

Options d'inférence disponibles :

Modes de sortie :

  • label_only : Seulement le label prédit
  • label_prob : Label + probabilité
  • top_k : Label + prob + top-K labels et probs
  • all_probs : Label + prob + toutes les probabilités
  • logits : Label + prob + logits
  • extended : Label + prob + all_probs + logits (recommandé)
  • full : Tout (label + prob + top_k + all_probs + logits)

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