القائمة
Use when editing src/explainability/gradcam.py, adding a new model to MODEL_REGISTRY, or asked about the Grad-CAM panel in explainability reports for the corn leaf disease project.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
Use when reading or editing src/data/*, src/config.py, src/models/input_sizes.py, or config/dataset.yaml - covers image loading, dataset/output root resolution, target_size convention, and minority-class derivation for the corn leaf disease project.
Use when running or editing scripts/pipeline/explain_lime.py, scripts/pipeline/explain_report.py, or scripts/checks/lime_stability.py, or when asked about LIME visual reports, fidelity, or error analysis for the corn leaf disease project.
Use when reading or editing src/training/*, scripts/pipeline/train.py, or scripts/pipeline/train_baselines.py - covers class-balancing via WeightedRandomSampler, shared training utilities, and run/output versioning for the corn leaf disease project.
استنادا إلى تصنيف SOC المهني
| name | corn-gradcam |
| description | Use when editing src/explainability/gradcam.py, adding a new model to MODEL_REGISTRY, or asked about the Grad-CAM panel in explainability reports for the corn leaf disease project. |
src/explainability/gradcam.py añade un 4to panel opcional (config/dataset.yaml -> gradcam.enabled) vía hooks nativos de PyTorch, sin dependencias nuevas.
GRADCAM_TARGET_LAYERS mapea cada modelo del registry a su última capa con salida espacial.
Al añadir un modelo nuevo a MODEL_REGISTRY, agregar también su entrada en GRADCAM_TARGET_LAYERS - si no, Grad-CAM se omite con warning (fallback a 3 paneles).
