typed op• 数据种类:counts → feature
• 调用:fullseye.apply(img, "tb_dtof_depth", a=0.5, b=0.5)(2-D 的模型是一张图 + 两个标量旋钮 a,b∈[0,1])
*图为在 128×128 合成输入上实际运行的输出。左为输入，右为输出。点云以俯视散点显示(亮度 = z)，一维序列为折线，体数据为沿 z 的最大值投影，视频为中间帧，复数图像为幅值；无法成像的返回值直接显示数值。*
扫描旋钮 a(0.1 / 0.5 / 0.9，另一旋钮取默认):
▸ tb_dtof_depth: 旋钮 a 扫描 (文档网站)
*旋钮 b 不改变输出(实测: 0.1 / 0.5 / 0.9 相同)。*
阶段(前置算子 → 本算子，从左到右):
▸ tb_dtof_depth: 处理阶段 (文档网站)
由光子到达时间直方图得到的距离：d = c*t/2。
> 以下的详细说明为原文 —— 摘要与标题已翻译。
Direct time-of-flight. The light travels to the target and back, so the one-way distance is half the round-trip time times the speed of light. *bin_ps* is the width of one time bin (a 100 ps bin is 1.50 cm of depth).
Four estimators, from crudest to sharpest:
• "peak" — the centre of the fullest bin. Quantised to the bin grid; the error is uniform in +-half a bin (+-0.75 cm at 100 ps).
• "centroid" — the first moment of the whole histogram. Exact for a symmetric pulse *with no background*, and badly biased toward the middle of the window with one — pass subtract_background=True.
• "parabolic" — a parabola through the peak bin and its two neighbours. Sub-bin, cheap, and biased for a Gaussian pulse.
• "gaussian" — the same parabola fitted to the log of those three samples, which is the exact vertex for a Gaussian pulse.
Measured on a noiseless simulated return at 2.4371 m (256 bins x 100 ps, 500 ps IRF), absolute error: peak 1.29 mm, centroid 4.4e-16 m, parabolic 0.067 mm, gaussian 9.4e-9 m — three orders of magnitude between the crudest and the sharpest.
With Poisson noise (200 signal + 200 ambient photons, seed 0) the same four give 13.7 mm, 146.5 mm (with subtract_background=True), 8.5 mm and 8.0 mm. Two honest readings of that: once shot noise dominates the sub-bin estimators buy about 1.6x, not three orders of magnitude, and the centroid collapses because a median-subtracted ambient floor still leaves noise across the whole window that drags the first moment toward the centre. Use "gaussian" or "parabolic" on noisy data; use "centroid" only when the background is genuinely gone.
*offset_ps* is a system delay to remove: t_flight = t_measured - offset_ps, so a positive offset makes the answer *closer*. Returns the distance in metres as a float.
Raises ValueError: negative, non-finite, non-1-D or all-zero *hist*, a non-positive *bin_ps*, an unknown *mode*, a non-finite *offset_ps*, a flat histogram in a peak-based mode (argmax would silently pick bin 0 and report the first bin's depth), a peak in the first or last bin with a sub-bin *mode* (there is no neighbour to fit to — use "peak"), a degenerate three-sample fit, and — instead of returning a negative distance — an *offset_ps* larger than the measured arrival time.
Typed bridge of the photon op dtof_depth into the 2-D evolution registry: the same implementation, called under the op(v, a, b) convention. a drives bin_ps (default 100); b is unused.
• 示例数据目录(下载 URL / 许可证) —— 2-D 用 skimage.data(BSD/公有领域)加合成图,3-D 给出真实数据源(Stanford/PDS 等)的下载 URL。
• 算子来历与参考文献 —— 该算子族所依据的研究/方法出处。
下面的程序已确认可以运行(与图相同的输入)。在 Studio 帮助中，此块会变成按钮，可当场加载并运行。
img_to_counts 0.50 0.50 tb_dtof_depth 0.50 0.50
下面的示例调用的是底层账本算子 dtof_depth。此桥接算子只是把同一实现适配为 fn(v, a, b) 约定，行为完全相同(只是调用形式不同)。
• photon_timeresolved — py -3.11 examples/photon_timeresolved.py
• poc_dtof_ranging — py -3.11 examples/poc_dtof_ranging.py
feature 作为输入)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 算子登记表。本条目由 tools/opdocs.py md 自动生成(请勿手工编辑)。*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.