typed op• Data kinds: points → image
• Call: fullseye.apply(img, "tb_synthesize_silhouette", 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.*
*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_synthesize_silhouette: stages (docs site)
On other images (synthetic scene / photo / coins. Top row: inputs, bottom row: their outputs. Knobs at default):
▸ tb_synthesize_silhouette: other inputs (docs site)
Projects a 3-D point cloud onto a (K,R,t) camera and returns a silhouette (H,W bool) where occupied pixels are True.
> The detailed description below is the original text — the summary and the headings are translated.
GT 生成用。`points (N,3) を X_cam = R X + t` で射影し、depth>0 かつ画像内に
落ちた画素を True にする。疎な点群では射影像に穴が空くため、既定で穴埋め
(`fill`, scipy.ndimage.binary_fill_holes)して中身の詰まった前景マスクにする。
さらに `dilate` 画素だけ膨張させ「pixel が少しでも物体に触れれば前景」という
被覆(coverage)意味のシルエットにする — これが visual hull の recall(物体 voxel を
取りこぼさない)を離散化誤差の下でも保証するための保守側の丸め。
Parameters
----------
points : (N, 3) array_like ワールド座標の点群(物体表面/内部のサンプル)。
K : (3, 3) 内部パラメータ。
R, t : (3, 3), (3,) ワールド->カメラの回転・並進。
size : (H, W) 出力画像サイズ。
fill : bool 射影像の穴を埋めて solid にする(既定 True)。
dilate : int 被覆マージンとして膨張させる画素数(既定 1、0 で無効)。
Returns
-------
(H, W) bool ndarray 前景 True のシルエット。
2-D 進化レジストリへ橋渡しした 3d の op `synthesize_silhouette。実装は同じで、呼び出し規約だけ op(v, a, b) に合わせてある。この op に調整点は無く、a も b` も使われない。
• 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_points 0.50 0.50 tb_synthesize_silhouette 0.50 0.50
▸ Load this pipeline · Load & run
The examples below call the underlying ledger op synthesize_silhouette. 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).
• space_carving — py -3.11 examples_3d/space_carving.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.