LineartStandard

✅ verified (run, but not used)

What it is. Not a learned model: it takes the edge response of the luminance after a Gaussian blur and keeps what passes a threshold. It is edge detection. The ComfyUI node is LineartStandardPreprocessor, needs no model, and takes a smoothing sigma (6) and a strength threshold (8).

How it works. With \(L\) the luminance and \(G_\sigma\) a Gaussian kernel, the response is

\[ E = \max\big(0,\ L - G_\sigma * L\big), \]

and anything below the threshold is set to zero. \(L - G_\sigma * L\) is “how much brighter than its surroundings”: a thin line disappears in the blur, so there is a response only at large-scale transitions between light and dark. That is an edge, not a line.

What it produces. A thick, glowing outline (the response is strong where the two sides differ a lot in luminance), with the internal structure smeared into grey bands and no single-pixel lines at all.

Why it is not used. An edge detector does not know what a line is; a blur of sigma 6 removes every thin line and leaves only the large-scale outline; and after skeletonizing the candidates are few and thick. Its use is as a fallback that needs no model: on a machine with no weights it can at least produce the outline.

Reference. The node’s implementation is in https://github.com/Fannovel16/comfyui_controlnet_aux.