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,splittransform_id,transform_name,transform_level,transform_paramsimage_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 préditlabel_prob: Label + probabilitétop_k: Label + prob + top-K labels et probsall_probs: Label + prob + toutes les probabilitéslogits: Label + prob + logitsextended: Label + prob + all_probs + logits (recommandé)full: Tout (label + prob + top_k + all_probs + logits)
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