scene op• Data kinds: table × table × table → table
• Call: import optscene; optscene.linescan_capture(scene, camera, lights, velocity_mm_s: 'float' = 100.0, line_rate_hz: 'float' = 10000.0, lines: 'int' = 512, tdi_stages: 'int' = 1, sync_error: 'float' = 0.0, scan_axis=(1.0, 0.0, 0.0), ambient: 'float' = 0.0, depth: 'int' = 1, light_samples: 'int' = None) -> 'dict' (or opsoptics.get("linescan_capture"))
Shoot with a line-scan / TDI camera (stacking one line at a time while the part moves).
> The detailed description below is the original text — the summary and the headings are translated.
エリアセンサの模型では表せない領域。`camera` は高さ 1 のラインセンサ
(`sensor_spec(resolution=(N, 1)) → :func:vision_layout`)を想定するが、
高さ h のカメラを渡した場合は先頭ラインだけを使う。
走査方向の画素実寸は 搬送速度 ÷ ラインレート で決まる。横方向は光学倍率で
決まるので、この 2 つが合っていないと画像の縦横比が崩れる ―― 光学をいくら
詰めても直らない、ラインスキャン固有の故障モードである。
`tdi_stages` を 2 以上にすると TDI(時間遅延積分)。M 段で信号が M 倍になるが、
`sync_error`(搬送とラインレートの相対誤差、0.01 = 1%)があると段ごとに位置が
ずれてM 段ぶんボケる。感度と同期精度のトレードオフがそのまま出る。
返り値 dict: `image(lines, width, 3 の放射輝度)/ depth_mm` /
`part_mask / defect_mask / pixel_mm_scan`(走査方向の画素実寸)/
`pixel_mm_cross(横方向)/ aspect`(縦横比。1.0 が正方画素)。
Every optics op validates its input before computing (nothing slips through silently):
• Units are baked into the argument name — _mm / _um / _deg / _mrad. Confusing mm with µm does not crash; it yields a plausible-looking wrong answer, so the name prevents it. Nothing here guesses the unit from the magnitude.
• **Strings raise ValueError** — float('50') succeeds, so an unparsed configuration value would slip through as a length (measured: thin_lens('50', '200') returned a plausible 66.667 mm). bool is refused too, as the implicit promotion True == 1.
• **complex / masked arrays raise ValueError (real-valued slots only; silently dropping the imaginary part or peeling off the mask is refused). NaN/Inf raises ValueError on every input.**
• Division by zero and its relatives are refused by name: focal length 0, radius of curvature 0, refractive index <= 0, a fully opaque aperture (all zeros, so the normalisation is 0/0), a PSF whose sum is <= 0, a Stokes vector with S0 = 0, and an object sitting at the front focal point (the image is at infinity).
• Only two ops return a non-finite value, and both state it as a contract: depth_of_field returns far_mm = inf beyond the hyperfocal distance (that is what the hyperfocal distance means), and gaussian_beam returns wavefront_radius_mm = inf at the waist (the radius of curvature of a plane wavefront). Both also return a finite companion (far_is_infinite / curvature_per_mm). **Any other silent NaN/Inf is detected internally and raises ValueError** — "float64 overflowed" and "the answer is infinite" are different claims, so the first is never returned wearing the face of the second.
• Size caps: generated grids are capped by optics.MAX_GRID (4096); supplied fields/PSFs/apertures by optics.MAX_FIELD_ELEMENTS (2^24); ABCD element chains by optics.MAX_SYSTEM_ELEMENTS (1024); Zernike by MAX_ZERNIKE_TERMS (512) / MAX_ZERNIKE_ORDER (40) / MAX_ZERNIKE_BASIS (2^25). This closes, fail-closed, the paths where a small argument triggers a huge internal allocation (measured: n_max=40 × 4096² needs 108 GB).
• Physically impossible states are refused too: a Stokes vector with degree of polarisation > 1, negative transmittance, negative intensity, and invalid Zernike indices such as n-|m| odd.
• dataset_conventions — 学習データセット規約の知識 — COCO / YOLO / VOC と外観検査での落とし穴
• mv_cameras — 産業用カメラメーカー（センサとの紐付け・ラインスキャン / TDI）
• mv_illumination_practice — 照明の実務知識 — 波長・偏光・点灯方式・外光・安全
• mv_image_sensors — 産業用イメージセンサ（現行品中心）
• virtual_machine_vision — 仮想マシンビジョン — パラメータの洗い出しとオブジェクト模型
• 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.
• vision_layout_from_catalog — py -3.11 examples/vision_layout_from_catalog.py
table as input)abcd_matrix · wavefront_stats · paraxial_trace · seidel_coefficients · spot_stats · tolerance_analysis · wavefront_from_opd · spot_diagram
scene)scene_material · scene_plane · scene_sphere · scene_box · scene_cylinder · surface_defect · surface_finish · random_defects
*Provenance: optscene.py — OPTICS 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.