ZImageFunControlnet - ComfyUI Built-in Node Documentation

Complete documentation for the ZImageFunControlnet node in ComfyUI. Learn its inputs, outputs, parameters and usage.

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The ZImageFunControlnet node applies a specialized control network to influence the image generation or editing process. It uses a base model, a model patch, and a VAE, allowing you to adjust the strength of the control effect. This node can work with a base image, an inpainting image, and a mask for more targeted edits.

Inputs

Parameter	Data Type	Required	Range	Description
model	MODEL	Yes	-	The base model used for the generation process.
model_patch	MODEL_PATCH	Yes	-	A specialized patch model that applies the control network’s guidance.
vae	VAE	Yes	-	The Variational Autoencoder used for encoding and decoding images.
strength	FLOAT	Yes	-10.0 to 10.0	The strength of the control network’s influence. Positive values apply the effect, while negative values can invert it (default: 1.0).
image	IMAGE	No	-	An optional base image to guide the generation process.
inpaint_image	IMAGE	No	-	An optional image used specifically for inpainting areas defined by a mask.
mask	MASK	No	-	An optional mask that defines which areas of an image should be edited or inpainted.

Note: The inpaint_image parameter is typically used in conjunction with a mask to specify the content for inpainting. The node’s behavior may change based on which optional inputs are provided (e.g., using image for guidance or using image, mask, and inpaint_image for inpainting).

Outputs

Output Name	Data Type	Description
model	MODEL	The model with the control network patch applied, ready for use in a sampling pipeline.
positive	CONDITIONING	The positive conditioning, potentially modified by the control network inputs.
negative	CONDITIONING	The negative conditioning, potentially modified by the control network inputs.