aug_cutout — 2D augmentation op

• Data kinds: image → image

• Call: fullseye.apply(img, "aug_cutout", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])

Usage

Cutout / random-erasing occlusion (DeVries & Taylor 2017; Zhong et al. 2020): a square patch of side `max(1, a*min(H,W)) is erased from the image, forcing a pipeline to survive partial occlusion instead of relying on one salient blob. b` selects the (deterministic, seeded-from-b) patch position AND the fill value: b <= 0.5 -> black (0.0), b > 0.5 -> mid-gray (0.5). The patch is always fully inside the frame.

Detailed usage guide

• gallery2d_color_artistic family guide

References (sample data, literature)

• Sample-data catalog (download URLs / licences) — 2-D uses skimage.data (BSD/public domain) plus synthetic images; 3-D lists download URLs for real data sources (Stanford, PDS, …).

• Operator provenance and references — the sources of the research/methods this op family came from.

• The canonical algorithm (author, year) and its uses are named in the family usage guide above.

Runnable examples (verified samples that actually call this op)

• gallery2d_color_artistic — py -3.11 examples/gallery2d_color_artistic.py

Ops the type connects to (they accept image as input)

identity · gaussian · mean_box · bilateral · unsharp · median · min_filter · max_filter

Same category (augmentation)

aug_shot_noise · aug_read_noise · aug_fixed_pattern · aug_motion_blur · aug_vignette · aug_chromatic · aug_rolling_shutter · aug_jpeg_blocks

*Provenance: ops.py — 2D operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*

© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.