preprocessing/README.md

Preprocessing

generate_masks.py produces the guarded background masks used by the hand-crafted feature extractor.

Museum photographs often include a backdrop, mount or frame around the artwork. Removing it helps color/light statistics — but salient-object segmentation (U^2-Net) applied blindly also eats painted borders, halos and dark backgrounds that ARE the artwork. So every mask must pass five checks before it is applied (see the module docstring); otherwise the full image is used. On the gold set this accepts ~10% of images.

Downstream use (in features/extract_handcrafted.py):

• applied images: spatial features see the mask's bounding-box crop; color/light statistics additionally exclude background pixels inside it. Background is never zero-filled — that would create fake edges.
• rejected images: full image everywhere.

Outputs: data/masks/<stem>.png + data/masks/verdicts.csv.