WanPhantomSubjectToVideo - ComfyUI Built-in Node Documentation

The WanPhantomSubjectToVideo node generates video content by processing conditioning inputs and optional reference images. It creates latent representations for video generation and can incorporate visual guidance from input images when provided. The node prepares conditioning data with time-dimensional concatenation for video models and outputs modified conditioning along with generated latent video data.

Inputs

Parameter	Description	Data Type	Required	Range
`positive`	Positive conditioning input for guiding video generation	CONDITIONING	Yes	-
`negative`	Negative conditioning input to avoid certain characteristics	CONDITIONING	Yes	-
`vae`	VAE model for encoding images when provided	VAE	Yes	-
`width`	Output video width in pixels (default: 832, must be divisible by 16)	INT	Yes	16 to MAX_RESOLUTION
`height`	Output video height in pixels (default: 480, must be divisible by 16)	INT	Yes	16 to MAX_RESOLUTION
`length`	Number of frames in the generated video (default: 81, must be divisible by 4)	INT	Yes	1 to MAX_RESOLUTION
`batch_size`	Number of videos to generate simultaneously (default: 1)	INT	Yes	1 to 4096
`images`	Optional reference images for time-dimensional conditioning	IMAGE	No	-

Note: When images are provided, they are automatically upscaled to match the specified width and height, and only the first length frames are used for processing.

Outputs

Output Name	Description	Data Type
`positive`	Modified positive conditioning with time-dimensional concatenation when images are provided	CONDITIONING
`negative_text`	Modified negative conditioning with time-dimensional concatenation when images are provided	CONDITIONING
`negative_img_text`	Negative conditioning with zeroed time-dimensional concatenation when images are provided	CONDITIONING
`latent`	Generated latent video representation with specified dimensions and length	LATENT

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