halcon_ext op• Data kinds: image → image
• Call: fullseye.apply(img, "hx_disparity_to_xyz", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])
• HALCON equivalent: disparity_image_to_xyz (the HALCON reference is a useful guide to its meaning and parameters)
*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.*
Sweeping knob a (0.1 / 0.5 / 0.9, the other knob at its default):
▸ hx_disparity_to_xyz: knob a sweep (docs site)
Sweeping knob b (0.1 / 0.5 / 0.9, the other knob at its default):
▸ hx_disparity_to_xyz: knob b sweep (docs site)
On other images (synthetic scene / photo / coins. Top row: inputs, bottom row: their outputs. Knobs at default):
▸ hx_disparity_to_xyz: other inputs (docs site)
*The 4th column is a colour (H,W,3) input. This op handles colour without crossing channels (it does not convolve the colour channel as a third spatial axis).*
Compute depth Z = f*baseline/disparity from a disparity image (focal length and baseline vary with a, b). Normalised Z.
> The detailed description below is the original text — the summary and the headings are translated.
`v(0〜1)を視差 disp = v*63 + 0.5 画素相当に写し、Z = f * baseline / disp` を計算して min-max で
[0,1] に正規化した画像を返す。X, Y は計算しない(Z のみ)。
• `a → 焦点距離 f = 200 + 600*a`。
• `b → 基線長 baseline = 0.05 + 0.15*b`。
• 視差の下限を 0.5 に置いているのでゼロ除算は起きない。
注意: `f * baseline は全画素共通の定数倍で、最後の min-max 正規化で打ち消されるため、a, b` を変えても
出力は変わらない(実測で完全一致)。出力は実質「視差の逆数を正規化したもの」で、視差最大(`v = 1`)が 0、
視差最小(`v = 0`)が 1 になる(近い物ほど暗い)。絶対的な深度が要る用途には使えない。逆数変換で遠方の
量子化が粗くなるので、`v` が小さい領域の値は不安定。
Knobs (measured): sweeping `a` from 0 to 1 does not change the output (measured on five different inputs).
Blank frame (measured): feeding an image of uniform brightness gives an empty result — every pixel is background (0) — regardless of the brightness. Pure white and pure black behave alike; brightness by itself detects nothing.
• gallery2d_halcon_ext family guide
• 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.
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.
hx_disparity_to_xyz 0.50 0.50
▸ Load this pipeline · Load & run
• gallery2d_halcon_ext — py -3.11 examples/gallery2d_halcon_ext.py
image as input)identity · gaussian · mean_box · bilateral · unsharp · median · min_filter · max_filter
halcon_ext)hx_gen_circle · hx_gen_ellipse · hx_gen_rectangle2 · hx_gen_checker_region · hx_gen_grid_region · hx_gabor · hx_fit_surface1 · hx_fit_surface2
*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.