KitForma field notes

Use estimated roughness and AO honestly

Build a useful starting material while keeping physical assumptions visible.

Roughness is not recoverable from brightness alone

A dark patch may be glossy paint, a shadow or a hole. This tool creates an editable roughness starting map around your base value. It does not estimate a measured BRDF or separate diffuse color from illumination. Check the result against the material you intend to represent.

Local AO is a small-scale approximation

The AO map darkens pixels that lie below nearby brightness samples. It cannot account for surrounding scene objects or long-range occlusion. Use an actual geometry bake when accurate ambient occlusion matters and avoid multiplying AO so strongly that lighting becomes permanently dark.

Wrapping does not make an image seamless

Wrapped sampling calculates derivatives across opposite image edges. If those edges disagree, the discontinuity is still present and may become more visible in the normal map. Prepare a seamless source first, then enable wrapping and inspect a repeated plane under moving light.

Inspect the four outputs separately

The workbench supplies a normal map, the processed height image, an AO estimate and a roughness estimate. Start with the height and normal pair, then add the estimated maps one at a time. This makes it easier to identify whether an unwanted dark edge comes from lighting, the normal direction or the added AO texture.

With a base roughness of 0.65, the current brightness-based variation spans roughly 0.525 at black to 0.775 at white. These values are an editable artistic starting point, not measurements of the photographed surface. A uniform roughness value may be more appropriate when a material’s color pattern does not imply a change in finish.

Test the seam in its actual repeated context

Place the generated maps on a plane tiled several times in each direction. Inspect both joins and corners under a low-angle moving light. Enable wrapped sampling only after preparing compatible opposite image edges. The AO estimate looks at nearby brightness samples; it does not know the dimensions of a cavity, adjacent objects or a distant overhang. For those features, bake occlusion from actual geometry in the scene.

The evidence behind the check

Sources & assumptions

Formats, algorithms and supported features are documented below. Check the stated scope and inspect your output before using it.

Reviewed 2026-10-17. Read our methodology or report an issue.

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