ComfyUI Node: AdaIN (Latent)

AdaIN (Latent):

The AdainLatent node is designed to perform adaptive instance normalization (AdaIN) on latent representations. This technique is particularly useful in style transfer tasks, where the goal is to adjust the style of one image to match the style of another. By normalizing the latent features of an input image to match the statistical properties (mean and standard deviation) of a reference image, this node allows you to blend styles in a controlled manner. The AdainLatent node provides a flexible and powerful way to manipulate latent spaces, enabling you to achieve a wide range of artistic effects by simply adjusting a few parameters.

AdaIN (Latent) Input Parameters:

latents

This parameter represents the latent representation of the input image that you want to modify. It is a tensor containing the latent features that will be normalized to match the reference image's style.

reference

This parameter is the latent representation of the reference image whose style you want to apply to the input image. The node will use the statistical properties (mean and standard deviation) of this reference latent to adjust the input latent.

factor

The factor parameter controls the degree to which the input latent is adjusted to match the reference latent. It is a floating-point value with a default of 1.0, a minimum of -10.0, and a maximum of 10.0. A factor of 1.0 means full application of the reference style, while a factor of 0.0 means no change to the input latent. Negative values and values greater than 1.0 can be used for more extreme adjustments.

AdaIN (Latent) Output Parameters:

LATENT

The output is a modified latent representation that has been normalized to match the style of the reference latent. This output can be used in subsequent nodes to generate images that blend the input and reference styles.

AdaIN (Latent) Usage Tips:

• To achieve a subtle style transfer, use a factor value between 0.0 and 1.0. This will blend the input and reference styles smoothly.
• For more dramatic style changes, experiment with factor values greater than 1.0 or less than 0.0. Be cautious with extreme values as they can lead to unexpected results.
• Use high-quality reference images with distinct styles to get the best results from the AdainLatent node.

AdaIN (Latent) Common Errors and Solutions:

"RuntimeError: The size of tensor a (X) must match the size of tensor b (Y)"

• Explanation: This error occurs when the dimensions of the input and reference latents do not match.
• Solution: Ensure that both the input and reference latents have the same dimensions before passing them to the AdainLatent node.

"TypeError: 'NoneType' object is not subscriptable"

• Explanation: This error may occur if the input or reference latents are not properly loaded or are missing.
• Solution: Verify that both the input and reference latents are correctly loaded and not None before using the node.

"ValueError: Expected more than 1 value per channel when training"

• Explanation: This error can happen if the batch size of the latents is too small.
• Solution: Ensure that the batch size of the input and reference latents is greater than 1 to avoid this error.