contour op• Data kinds: mask → table
• Call: import fullseye as fs; fs.ledger.curvature_flow(phi, *, t_end: 'float' = 50.0, dt: 'float' = 0.2, eta: 'float' = 1e-08, record_every: 'int' = 0) -> 'Dict[str, object]' (to call the implementation directly, import segcontour; segcontour.curvature_flow(phi, *, t_end: 'float' = 50.0, dt: 'float' = 0.2, eta: 'float' = 1e-08, record_every: 'int' = 0) -> 'Dict[str, object]'; from the registry, opssegmentation.get("curvature_flow"))
Level-set form of mean curvature flow (curve-shortening flow) φ_t = |∇φ| div(∇φ/|∇φ|) (inside where φ < 0; shrinks from the convex parts) (curvature_flow).
> The detailed description below is the original text — the summary and the headings are translated.
陽的な中心差分: φ_t = (φ_xx φ_y² − 2 φ_x φ_y φ_xy + φ_yy φ_x²) / (φ_x² + φ_y² + η)、刻み dt ≤ 0.25(安定条件)。
`phi = φ か bool のマスク(符号付き距離に直す)。面積は各刻みで clip(0.5 − φ/|∇φ|, 0, 1)` の和。
門: 単純閉曲線の囲む面積は dA/dt = −∮ κ ds = −2π(回転数 1、凸でなくても)。円なら r(t)² = r0² − 2t。
返り値: `phi、mask、times、areas、area_rate(面積 vs 時間の最小二乗の傾き)、area_rate_theory` = −2π、
`history(record_every 刻みごとのマスク)、n_steps`。
• halcon_segmentation family guide
• active_contours_and_level_sets — 変分・動的輪郭とレベルセット — どの輪郭がどこで止まり、何を保証するか
• 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.
• poc_active_contours — py -3.11 examples/poc_active_contours.py
table as input)contour)snake_evolve · gvf_field · chan_vese_energy · chan_vese_evolve · morph_chan_vese · morph_geodesic_ac · edge_stop_g · level_set_reinit
*Provenance: segcontour.py — SEGMENTATION 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.