scene op• Data kinds: none → table (an op determined by its arguments alone — it takes no image or data input)
• Call: import fullseye as fs; fs.ledger.optical_camera(focal_mm: 'float' = 25.0, pixel_um: 'float' = 3.45, resolution=(256, 256), working_distance_mm: 'float' = 200.0, look_at_mm=(0.0, 0.0, 0.0), tilt_deg: 'float' = 0.0, azimuth_deg: 'float' = 0.0, image_distance_mm: 'float' = None, telecentric: 'bool' = False) -> 'dict' (to call the implementation directly, import optscene; optscene.optical_camera(focal_mm: 'float' = 25.0, pixel_um: 'float' = 3.45, resolution=(256, 256), working_distance_mm: 'float' = 200.0, look_at_mm=(0.0, 0.0, 0.0), tilt_deg: 'float' = 0.0, azimuth_deg: 'float' = 0.0, image_distance_mm: 'float' = None, telecentric: 'bool' = False) -> 'dict'; from the registry, opsoptics.get("optical_camera"))
Build an ideal pinhole from real specifications (focal length, pixel pitch, resolution, working distance).
tilt_deg is the tilt from straight overhead (0°), azimuth_deg its azimuth. The camera looks down at look_at_mm. The return value contains the intrinsic matrix K [px] and the pose (R, t) ―― the same conventions as the calib / calibration3d ops, so it can be passed as is to reprojection or calibration verification.
The field of view is set by tan of the half angle = (pixel count/2 · pixel pitch) / image distance. The field-of-view width [mm] at the working distance is stored in fov_mm, so you can check whether the part fits before taking the image.
image_distance_mm is the distance from the pinhole to the sensor (the image distance v). When omitted it is focal_mm (the focused-at-infinity approximation). ★With the lens focused at the working distance, v = f·WD/(WD − f) and the magnification is v/WD = f/(WD − f) (the same thin-lens formula as optical_budget). Until 2026-10-15 vision_layout and observe_surface passed f instead of v, so the rendered image had magnification f/WD while the budget had f/(WD − f) — two models mixed in one setup (the field of view was 14 % too wide at f 25 mm, WD 200 mm). focal_mm stays the lens focal length (defocus_blur uses it).
telecentric=True is object-side telecentric: the chief rays are parallel to the optical axis, so rays do not radiate from 1 point (the viewpoint) but leave parallel to the optical axis (orthographic projection). The physical pixel size on the object side is fixed at the value at the working distance, pixel · WD / v, so lifting the part does not change the size of its image (the very reason telecentric lenses are used for dimensional measurement). In this case K is a nominal value valid only on the working-distance plane, and projection becomes "orthographic" (it cannot be used for perspective reprojection). Until 2026-10-15 no code read lens_spec(telecentric=True), so even with the flag set, lifting the part by 20 mm made the image 11 % larger.
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 — Training-dataset conventions — COCO / YOLO / VOC and pitfalls in visual inspection
• mv_cameras — Industrial camera makers (sensor mapping, line scan / TDI)
• mv_illumination_practice — Lighting in practice — wavelength, polarisation, drive modes, ambient light, safety
• mv_image_sensors — Industrial image sensors (mainly current products)
• virtual_machine_vision — Virtual machine vision — enumerating the parameters and an object model
• 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_focus_stacking — py -3.11 examples/poc_focus_stacking.py
• poc_pocket_interreflection — py -3.11 examples/poc_pocket_interreflection.py
• studio_raytrace_scene — py -3.11 examples/studio_raytrace_scene.py
• virtual_machine_vision — py -3.11 examples/virtual_machine_vision.py
• vision_layout_from_catalog — py -3.11 examples/vision_layout_from_catalog.py
table as input)abcd_matrix · wavefront_stats · sfr_from_edge · paraxial_trace · seidel_coefficients · spot_stats · tolerance_analysis · wavefront_from_opd
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.