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Manipulate latent representations by mirroring in specified directions for creative AI art outputs with adjustable intensity.
The LatentMirror node is designed to manipulate latent representations by mirroring them in specified directions. This node is particularly useful in the field of AI art, where altering the symmetry of latent images can lead to creative and unique outputs. By mirroring the latent data either vertically, horizontally, or in both directions, you can explore new artistic possibilities and enhance the visual appeal of generated images. The node also allows for the adjustment of the mirrored effect's intensity through a multiplier, providing further control over the transformation. This flexibility makes LatentMirror a powerful tool for artists looking to experiment with symmetry and balance in their AI-generated artworks.
The latent
parameter represents the latent data that you wish to transform. This data is typically a high-dimensional representation of an image, which the node will process to apply the mirroring effect. It is essential for the node's operation as it serves as the input that will be manipulated.
The direction
parameter determines the axis along which the latent data will be mirrored. You can choose from three options: "vertically," "horizontally," or "both." Selecting "vertically" will flip the image along the vertical axis, "horizontally" will flip it along the horizontal axis, and "both" will apply both transformations. This parameter is crucial for defining the symmetry of the output.
The multiplier
parameter controls the intensity of the mirroring effect. It is a floating-point value with a default of 1.0, a minimum of -10.0, and a maximum of 10.0. Adjusting this value allows you to amplify or diminish the mirrored effect, providing a way to fine-tune the visual outcome. A higher multiplier will enhance the mirrored features, while a lower one will reduce their prominence.
The vae_optional
parameter is an optional input that, if provided, allows the node to decode the mirrored latent samples into an image using a Variational Autoencoder (VAE). This can be useful for previewing the results of the mirroring operation directly as an image, offering a more intuitive understanding of the transformation's impact.
The output of the LatentMirror node is a transformed latent representation, denoted as LATENT
. This output retains the original structure of the input latent data but with the specified mirroring effect applied. The transformed latent can be further processed or decoded into an image, depending on your workflow. This output is essential for continuing the creative process, allowing you to build upon the mirrored latent representation.
direction
settings to discover unique symmetrical patterns in your latent images. Combining vertical and horizontal mirroring can yield particularly interesting results.multiplier
parameter to adjust the strength of the mirroring effect. A subtle multiplier can create gentle symmetry, while a stronger one can produce bold, mirrored features.vae_optional
parameter to preview the mirrored latent as an image. This can help you quickly assess the visual impact of your adjustments.© Copyright 2024 RunComfy. All Rights Reserved.
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