photometric op• データ種: images → image2d
• 呼び出し: import fullseye as fs; fs.ledger.photometric_residual(images, lights, normals=None, albedo=None, normalize=True) (実装を直接呼ぶなら import specularity; specularity.photometric_residual(images, lights, normals=None, albedo=None, normalize=True)、台帳から引くなら opsspecular.get("photometric_residual"))
Lambert モデルが画素ごとにどれだけ外れているか。→ (H, W) の RMS 残差。
> 以下の詳細説明は原文のままです —— 要約と見出しは訳出済み。
sqrt(mean_n (albedo * (n.L_n) - I_n)^2) — the root-mean-square disagreement between the linear model and the measurements, in the units of the input radiance. On a synthetic Lambertian surface with the true float64 normals and albedo supplied it measures 1.4e-16 at worst; with them omitted the floor rises to 4.5e-08, because photometric.photometric_stereo returns float32 and that is its precision, not a modelling error (supplying the *same* truth cast to float32 reproduces 4.5e-08 exactly). It is large where the assumption actually broke: 0.50 at worst on the same scene with 3 of 8 lights blocked by a cast shadow — fifteen orders of magnitude above the clean floor. All four numbers measured in tests/test_specularity.py.
This is the diagnostic that tells you *whether* you need photometric_stereo_robust before you reach for it, and it is the map an inspection routine thresholds to find glossy defects.
With *normals* and *albedo* omitted it solves them first with photometric.photometric_stereo and reports the residual of that fit — the honest self-assessment of the plain estimator. Pass them to score an estimate that came from somewhere else (a robust fit, a CAD model, a previous frame).
Note the residual uses n.L without the max(., 0) clamp, because that is the linear system the solver actually inverted; a pixel in attached shadow therefore shows a residual, which is the intended signal rather than an artefact.
Raises ValueError: *images* / *lights* problems as in photometric_stereo_robust; *normals* is not (H, W, 3) matching the images; *albedo* is not (H, W); exactly one of *normals* / *albedo* is given (the pair is meaningless apart — the model is albedo * n).
• specular_photometric ファミリ ガイド
• サンプルデータ カタログ(DL URL / ライセンス) — 2-D は skimage.data(BSD/public)+ 合成、3-D は実データ源(Stanford/PDS 等)の DL URL。
• 演算子の来歴・参考文献 — この op 族の元になった研究/手法の出典。
• アルゴリズムの正典(著者・年)と用途は上記ファミリ使い方ガイドに記載。
• specular_photometric — py -3.11 examples/specular_photometric.py
image2d を入力に取れる)photometric)*Provenance: specularity.py — SPECULAR operator registry. この per-op ノートは tools/opdocs.py md が自動生成(手編集しない)。*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.