Added Fast Image to Noise node, which generates a new image that is effectively a remix of the pixels in a source image.
This is all done on the GPU and is lightning fast in comparison with the WAS Node Suite Image to Noise node.

February 2nd, 2024

Initial release. Added Image Match Normalize and Latent Match Normalize nodes.

Nodes

Image Match Normalize

This node returns a normalized version of the target image using the mean and standard deviation of each color channel of the source image. If you want the color and brightness of your image to match the colour and brightness of another image, this is the node for you.

Latent Match Normalize

This node returns a normalized version of the target latent using the mean and standard deviation of each channel of the source latent. Latents encode color information differently than images and you may find that normalizing an image by instead normalizing its latent representation results in a "better" result that is closer to the coloring of the source.

Fast Image to Noise

Generates a new image by remixing the pixels of the source image randomly, with several customization options:

num_colors: Number of colors to sample for the noise palette (2-256)
black_mix: Probability of replacing pixels with black (0-1)
gaussian_mix: Amount of Gaussian blur to apply (0-1024)
brightness: Brightness adjustment factor (0-2)
mask: Optional mask input that restricts color palette selection to masked areas only
output_mode: Choose between "batch" or "list" output format
seed: Random seed for reproducible results

The node is intended to match the functionality of the Image to Noise node in the WAS Node Suite but operates entirely on the GPU for significantly faster processing. When a mask is provided, the node will only sample colors from the masked (white) areas of the image to create the noise palette, allowing for more targeted noise generation.