ControlNetInpaintingAliMamaApply - ComfyUI Built-in Node Documentation

The ControlNetInpaintingAliMamaApply node applies ControlNet conditioning for inpainting tasks by combining positive and negative conditioning with a control image and mask. It processes the input image and mask to create modified conditioning that guides the generation process, allowing for precise control over which areas of the image are inpainted. The node supports strength adjustment and timing controls to fine-tune the ControlNet’s influence during different stages of the generation process.

Inputs

Parameter	Description	Data Type	Required	Range
`positive`	The positive conditioning that guides the generation toward desired content	CONDITIONING	Yes	-
`negative`	The negative conditioning that guides the generation away from unwanted content	CONDITIONING	Yes	-
`control_net`	The ControlNet model that provides additional control over the generation	CONTROL_NET	Yes	-
`vae`	The VAE (Variational Autoencoder) used for encoding and decoding images	VAE	Yes	-
`image`	The input image that serves as control guidance for the ControlNet	IMAGE	Yes	-
`mask`	The mask that defines which areas of the image should be inpainted	MASK	Yes	-
`strength`	The strength of the ControlNet effect (default: 1.0)	FLOAT	Yes	0.0 to 10.0
`start_percent`	The starting point (as percentage) of when ControlNet influence begins during generation (default: 0.0)	FLOAT	Yes	0.0 to 1.0
`end_percent`	The ending point (as percentage) of when ControlNet influence stops during generation (default: 1.0)	FLOAT	Yes	0.0 to 1.0

Note: When the ControlNet has concat_mask enabled, the mask is inverted and applied to the image before processing, and the mask is included in the extra concatenation data sent to the ControlNet.

Outputs

Output Name	Description	Data Type
`positive`	The modified positive conditioning with ControlNet applied for inpainting	CONDITIONING
`negative`	The modified negative conditioning with ControlNet applied for inpainting	CONDITIONING

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Inputs

Outputs