typed op• Data kinds: lightfield → image
• Call: fullseye.apply(img, "tb_lf_depth_from_focus", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])
*The figure is the actual output on a synthetic 128×128 input. Left: input, right: output. Point clouds are drawn as a top-down scatter (brightness = z), 1-D series as a line plot, volumes as the maximum-intensity projection along z, videos as the middle frame, complex images as magnitude; return values that are not pictures are shown as the values themselves.*
*The output is shown in a viridis-like pseudo-colour (dark purple = low, yellow = high) so that a field of quantities — distance, phase, orientation, depth — can be read.*
*Knob a does not change the output (measured: identical at 0.1 / 0.5 / 0.9).*
*Knob b does not change the output (measured: identical at 0.1 / 0.5 / 0.9).*
Stages (the ops that come before → this op, left to right):
▸ tb_lf_depth_from_focus: stages (docs site)
On other images (synthetic scene / photo / coins. Top row: inputs, bottom row: their outputs. Knobs at default):
▸ tb_lf_depth_from_focus: other inputs (docs site)
Per-pixel slope from the sharpness peak across the refocus sweep.
Refocus at every slope in *slopes*, measure local sharpness (*measure*:
`laplacian` = summed modified Laplacian, the classical depth-from-focus
operator; `variance = local variance; gradient` = local gradient
energy) in a `window x window` neighbourhood, and take the slope at which
each pixel is sharpest. With `subpixel=True` (default) the peak is refined
by fitting a parabola through the winning sample and its two neighbours on a
uniformly spaced sweep — on a non-uniform sweep the refinement is
skipped rather than applied with the wrong spacing.
Unbiased where :func:lf_epi_slope is not: measured 2026-09-01 on a
5x5x64x64 synthetic field over a 121-point sweep from -3 to +3, the argmax
landed exactly on the true slope in 18 of 18 combinations (true slopes
0.0, +0.5, +1.0, +1.5, +2.0, -1.0 crossed with texture sigma 1.5 / 3.0 /
5.0 px), and the sub-pixel refinement left every one of them unmoved. Its
resolution, though, is whatever you put in *slopes* — it cannot see a plane
you never refocused on.
Returns `(slope_map, sharpness): the (H, W)` map of estimated slopes
(in px per angular step) and the `(H, W)` peak focus-measure value, which
is the honest confidence — a textureless pixel has no sharpness peak, gets
an essentially arbitrary slope, and its `sharpness` is ~0. Threshold on it
rather than trusting the map everywhere.
Raises `ValueError`: *lf* not a valid light field, *slopes* empty /
over :data:MAX_STACK_SLICES / over :data:MAX_STACK_ELEMENTS / containing
a non-finite or over-large value, an even or non-positive *window*, unknown
*measure* / *interp* / *edge*.
Typed bridge of the lightfield op `lf_depth_from_focus into the 2-D evolution registry: the same implementation, called under the op(v, a, b) convention. This op has no tunable parameter; a and b` are unused.
• 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 program below has been verified to run (same input as the figure). In Studio's help this block becomes buttons that load and run it on the spot.
img_to_lightfield 0.50 0.50 tb_lf_depth_from_focus 0.50 0.50
▸ Load this pipeline · Load & run
The examples below call the underlying ledger op lf_depth_from_focus. This bridge op is the same implementation adapted to the fn(v, a, b) convention, so the behaviour carries over unchanged (only the call form differs).
• lightfield_depth — py -3.11 examples/lightfield_depth.py
• poc_compound_eye — py -3.11 examples/poc_compound_eye.py
• poc_lightfield_depth — py -3.11 examples/poc_lightfield_depth.py
image as input)identity · gaussian · mean_box · bilateral · unsharp · median · min_filter · max_filter
typed)tb_points_to_voxel · tb_estimate_point_normals · tb_iss_keypoints · tb_project_points · tb_render_point_depth · tb_statistical_outlier_removal · tb_radius_outlier_removal · tb_voxel_grid_downsample
*Provenance: ops.py — 2D 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.