Images to Linear

A flag up front: this node isn't actually named in WAS's own README node list, so what follows leans on how people in the community have actually reported using it rather than the pack's own documentation. On r/comfyui, someone asked for a built-in way to convert a colored image to black and white inside a workflow, and the answer that got upvoted pointed straight here: "It's called 'Images to Linear'." So in practice, that's the job this node does - it takes a batch of color images and converts them to a linear/grayscale luminance representation.

Why "linear," not just "grayscale"

The name is a hint at the mechanism rather than a separate feature: converting to linear color space means working with brightness values that scale proportionally with actual light intensity, rather than the gamma-corrected values a normal image stores. Collapsing an image down through that linear representation is a legitimate way to arrive at grayscale - it's just doing it via a color-science route rather than a simple "average the channels" desaturation. The plural "Images" in the name suggests it's built to operate on a batch, not a single image at a time.

The inputs and outputs that matter

A batch of images in, a converted (grayscale/linear) image batch out. I can't confirm additional parameters beyond that from a schema, so I'm describing the confirmed behavior rather than guessing at extra widgets.

How to install it

Bundled with the full WAS Node Suite:

• ComfyUI Manager - search "WAS Node Suite", install, restart.
• Manual - cd ComfyUI/custom_nodes && git clone https://github.com/WASasquatch/was-node-suite-comfyui, install requirements.txt (portable: python_embeded\python.exe -s -m pip install -r requirements.txt), restart.

No model download - a color-space conversion, not a generative step.

Common issues & troubleshooting

It breaks when wired straight into a ControlNet/conditioning chain. This is a real, documented report, not a hypothetical: a user ran this node's output straight into an Apply ControlNet step and got a tuple index out of range error at the KSampler. The working theory in that thread was that ControlNet's apply node expects a standard RGB image, and whatever format this node's output actually is doesn't satisfy that assumption cleanly. If you hit a shape or index error downstream of this node, test its output in isolation (save it, look at it) before assuming the problem is somewhere else in your graph.

You just wanted a plain desaturate and this feels like overkill. It might be - the same thread pointed out that Image Filter Adjustments (also in this pack) with saturation set to 0 gets you a straightforward black-and-white result with a much more ordinary image output, and it's a node this batch has already covered in detail if you want the gentler route.

Standard pack caveat: WAS Node Suite has been unmaintained since December 2023, and the recurring issue is the whole suite failing to import after a ComfyUI update. Reinstall requirements.txt against the right Python environment if that hits you.