augmentation op• Data kinds: image → image
• Call: fullseye.apply(img, "aug_jpeg_blocks", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])
JPEG blocking / ringing artefacts. The image (scaled to 0..255) is cut into 8x8 blocks, each transformed with an orthonormal 2-D DCT-II (`scipy.fft.dctn), quantised with the STANDARD JPEG Annex-K luminance table scaled by (1 + 40*a)/16 (a=0 -> near-lossless, a=1 -> heavy quantisation), then reconstructed with the inverse DCT. b shifts the 8x8 block grid phase by int(7*b)` px in both axes, i.e. moves where the block seams fall. Images that are not a multiple of 8 are edge-replicate padded and cropped back to HxW (so 4x4 inputs are handled).
• gallery2d_color_artistic family guide
• 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.
• gallery2d_color_artistic — py -3.11 examples/gallery2d_color_artistic.py
• sim2real_and_alife — py -3.11 examples/sim2real_and_alife.py
image as input)identity · gaussian · mean_box · bilateral · unsharp · median · min_filter · max_filter
augmentation)aug_shot_noise · aug_read_noise · aug_fixed_pattern · aug_motion_blur · aug_vignette · aug_chromatic · aug_rolling_shutter · aug_cutout
*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.