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The Kandinsky5ImageToVideo node prepares conditioning and latent space data for video generation using the Kandinsky model. It creates an empty video latent tensor and can optionally encode a starting image to guide the initial frames of the generated video, modifying the positive and negative conditioning accordingly.

Inputs

ParameterDescriptionData TypeRequiredRange
positiveThe positive conditioning prompts to guide the video generation.CONDITIONINGYesN/A
negativeThe negative conditioning prompts to steer the video generation away from certain concepts.CONDITIONINGYesN/A
vaeThe VAE model used to encode the optional starting image into the latent space.VAEYesN/A
widthThe width of the output video in pixels (default: 768).INTNo16 to 8192 (step 16)
heightThe height of the output video in pixels (default: 512).INTNo16 to 8192 (step 16)
lengthThe number of frames in the video (default: 121).INTNo1 to 8192 (step 4)
batch_sizeThe number of video sequences to generate simultaneously (default: 1).INTNo1 to 4096
start_imageAn optional starting image. If provided, it is encoded and used to replace the noisy start of the model’s output latents.IMAGENoN/A
Note: When a start_image is provided, it is automatically resized to match the specified width and height using bilinear interpolation. The first length frames of the image batch are used for encoding. The encoded latent is then injected into both the positive and negative conditioning to guide the video’s initial appearance.

Outputs

Output NameDescriptionData Type
positiveThe modified positive conditioning, potentially updated with encoded start image data.CONDITIONING
negativeThe modified negative conditioning, potentially updated with encoded start image data.CONDITIONING
latentAn empty video latent tensor with zeros, shaped for the specified dimensions.LATENT
cond_latentThe clean, encoded latent representation of the provided start images. This is used internally to replace the noisy beginning of the generated video latents.LATENT
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