The type of control input of segmentation ControlNet?

Hi! Thanks for this awesome work!

I read through your paper on arXiv but I have a small confusion about the segmentation ControlNet.

Specifically, what is the type of the control input (i.e., segmentation)? Is it an ordinary segmentation image, in which each pixel has a class label that is either one-hot encoded or an integer? Or, is it a colorful image, in which the class label of each pixel is color coded?

I presumed, when I read the paper, that an ordinary segmentation image is used to be the direct input control (without preprocessing), but I saw in a community news, some artists changed the color of the segmentation to change the generated artifacts. That makes me speculate that the control of segmentation ControlNet may be color-coded segmentation and it was also trained with color-coded segmentation images? But this does not make sense to me since some labels such as "wall" and "road" in ADE20K have visually similar color code (RGB:787878 and RGB: 8C8C8C) while they have little semantic similarity.

No repository file or test is named. Start by comparing the segmentation ControlNet description in the paper with the repository's segmentation preprocessing and examples; done means documenting whether inputs are integer or one-hot masks or color-coded images, including the label-to-color mapping.