repose_angle_silhouette — DRIVE `granular` op

• Data kinds: image2d → table

• Call: import fullseye as fs; fs.ledger.repose_angle_silhouette(side, *, threshold: 'float' = 0.5, toe_frac: 'float' = 0.15, apex_frac: 'float' = 0.15, min_points: 'int' = 8, correct_ground: 'bool' = False, method: 'str' = 'edge') -> 'dict' (to call the implementation directly, import granular; granular.repose_angle_silhouette(side, *, threshold: 'float' = 0.5, toe_frac: 'float' = 0.15, apex_frac: 'float' = 0.15, min_points: 'int' = 8, correct_ground: 'bool' = False, method: 'str' = 'edge') -> 'dict'; from the registry, opsdrive.get("repose_angle_silhouette"))

Usage

Reads the angle of repose φ from a side image (powder coverage) — fits a line separately to the left and right slopes, excluding the toe and the apex.

> The detailed description below is the original text — the summary and the headings are translated.

手順(Sunday ほか 2020 §5.3 の作法を規則化): ①列ごとの粉面の高さ = 被覆率が threshold を切る縁の画素の位置 + その被覆率(副画素; method="edge"、既定)②地面 = 各列の最下の交差(同じ補間)→ measure.fit_line で地面の傾き β。method="column_sum" は被覆率の列和(縁が反エイリアスなら厳密な副画素だが、粉の画素値が 1 からずれると その比で tan φ がずれる: 一様雑音 ±0.1 を [0, 1] に切っただけで 0.62 度低く出た、実測) ③頂 = 高さの最大列 ④地面からの高さが toe_frac·H 以上・(1 − apex_frac)·H 以下の点だけを左右別々に fit_line(全最小二乗)⑤φ = 左右の平均。

• correct_ground: 基準面の傾き β を tan の引き算で外す(tan φ' = tan θ ∓ tan β; せん断型 datum の傾きに対して厳密)。カメラのロールなら角の引き算が正しく、両者は β = 5 度で 1 度以上違うので既定は外さない。左右の差 asymmetry_deg が大きいときだけ基準面を疑う。

• 返り: phi_deg, phi_left_deg, phi_right_deg, asymmetry_deg, ground_deg, height_px, base_px, apex_col, left_cols / right_cols(当てた列の範囲)、rms_left / rms_right(直線からの残差 [px])、n_left / n_right。

• Raises ValueError: 画像でない / 被覆率が [0, 1] の外 / 粉が写っていない / 山が画像の上・左・右の縁に触れている(切れている)/ 当てる点が min_points 未満(山が小さすぎる)/ toe_frac + apex_frac ≥ 1 / method の綴り違い。

分解能の目安(被覆率に一様雑音 ±0.1、4 角度 × 6 seed の実測): 山の幅 400 px で 0.007 度、50 px で 0.2 度、25 px で 0.6 度。

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)

• poc_granular_heap_repose — py -3.11 examples/poc_granular_heap_repose.py

Ops the type connects to (they accept `table` as input)

course_layout · course_occupancy · course_contains · world_build · world_camera · world_move · lidar_scan · rss_longitudinal_same

Same category (`granular`)

heap_volume_cone · heap_mass · heap_volume_heightmap · beverloo_rate · beverloo_fit · discharge_synth · dispense_mass_from_video · hopper_discharge_rate

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

repose_angle_silhouette — DRIVE granular op