ZImageFunControlnet - ComfyUI Built-in Node Documentation

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

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

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​Inputs

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Inputs

Outputs