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The HunyuanImageToVideo node converts images into video latent representations using the Hunyuan video model. It takes conditioning inputs and optional starting images to generate video latents that can be further processed by video generation models. The node supports different guidance types for controlling how the starting image influences the video generation process.

Inputs

ParameterDescriptionData TypeRequiredRange
positivePositive conditioning input for guiding the video generationCONDITIONINGYes-
vaeVAE model used for encoding images into latent spaceVAEYes-
widthWidth of the output video in pixels (default: 848, step: 16)INTYes16 to MAX_RESOLUTION
heightHeight of the output video in pixels (default: 480, step: 16)INTYes16 to MAX_RESOLUTION
lengthNumber of frames in the output video (default: 53, step: 4)INTYes1 to MAX_RESOLUTION
batch_sizeNumber of videos to generate simultaneously (default: 1)INTYes1 to 4096
guidance_typeMethod for incorporating the starting image into video generation (default: “v1 (concat)“)COMBOYes”v1 (concat)"
"v2 (replace)"
"custom”
start_imageOptional starting image to initialize the video generationIMAGENo-
Note: When start_image is provided, the node uses different guidance methods based on the selected guidance_type:
  • “v1 (concat)”: Concatenates the image latent with the video latent and applies a mask to blend the image into the video
  • “v2 (replace)”: Replaces initial video frames with the image latent and applies a noise mask
  • “custom”: Uses the image as a reference latent for guidance

Outputs

Output NameDescriptionData Type
positiveModified positive conditioning with image guidance applied when start_image is providedCONDITIONING
latentVideo latent representation ready for further processing by video generation modelsLATENT
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