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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

ParameterDescriptionData TypeRequiredRange
positiveThe positive conditioning that guides the generation toward desired contentCONDITIONINGYes-
negativeThe negative conditioning that guides the generation away from unwanted contentCONDITIONINGYes-
control_netThe ControlNet model that provides additional control over the generationCONTROL_NETYes-
vaeThe VAE (Variational Autoencoder) used for encoding and decoding imagesVAEYes-
imageThe input image that serves as control guidance for the ControlNetIMAGEYes-
maskThe mask that defines which areas of the image should be inpaintedMASKYes-
strengthThe strength of the ControlNet effect (default: 1.0)FLOATYes0.0 to 10.0
start_percentThe starting point (as percentage) of when ControlNet influence begins during generation (default: 0.0)FLOATYes0.0 to 1.0
end_percentThe ending point (as percentage) of when ControlNet influence stops during generation (default: 1.0)FLOATYes0.0 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 NameDescriptionData Type
positiveThe modified positive conditioning with ControlNet applied for inpaintingCONDITIONING
negativeThe modified negative conditioning with ControlNet applied for inpaintingCONDITIONING
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