SD_4XUpscale_Conditioning - ComfyUI Built-in Node Documentation

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The SD_4XUpscale_Conditioning node prepares conditioning data for upscaling images using diffusion models. It takes input images and conditioning data, then applies scaling and noise augmentation to create modified conditioning that guides the upscaling process. The node outputs both positive and negative conditioning along with latent representations for the upscaled dimensions.

Inputs

Parameter	Data Type	Required	Range	Description
`images`	IMAGE	Yes	-	Input images to be upscaled
`positive`	CONDITIONING	Yes	-	Positive conditioning data that guides the generation toward desired content
`negative`	CONDITIONING	Yes	-	Negative conditioning data that steers the generation away from unwanted content
`scale_ratio`	FLOAT	No	0.0 - 10.0	Scaling factor applied to the input images (default: 4.0)
`noise_augmentation`	FLOAT	No	0.0 - 1.0	Amount of noise to add during the upscaling process (default: 0.0)

Outputs

Output Name	Data Type	Description
`positive`	CONDITIONING	Modified positive conditioning with upscaling information applied
`negative`	CONDITIONING	Modified negative conditioning with upscaling information applied
`latent`	LATENT	Empty latent representation matching the upscaled dimensions

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