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Enhance image resolution by 4x with advanced conditioning for high-quality upscaling without artifacts.
The SD_4XUpscale_Conditioning
node is designed to enhance the resolution of images by a factor of four using advanced upscaling techniques. This node leverages sophisticated conditioning methods to ensure that the upscaled images maintain high quality and detail. It is particularly useful for AI artists who need to upscale images without losing the original quality or introducing artifacts. The node works by taking an input image and applying a series of transformations and noise augmentations to produce a higher resolution output. This process is guided by both positive and negative conditioning inputs, which help to refine the final result. The main goal of this node is to provide a seamless and efficient way to upscale images, making it an essential tool for anyone looking to improve the resolution of their digital artwork.
This parameter accepts the input images that you want to upscale. The images should be in a format that the node can process, typically standard image formats like JPEG or PNG. The quality of the input image will directly affect the quality of the upscaled output.
This is a conditioning input that provides positive guidance to the upscaling process. It helps the model understand what features to enhance or preserve in the upscaled image. This input is crucial for maintaining the desired characteristics of the original image.
This is another conditioning input that provides negative guidance to the upscaling process. It helps the model understand what features to suppress or avoid in the upscaled image. This input is useful for removing unwanted artifacts or noise from the final output.
This parameter determines the factor by which the input image will be upscaled. The default value is 4.0, meaning the image will be upscaled by a factor of four. The minimum value is 0.0, and the maximum value is 10.0, with a step size of 0.01. Adjusting this parameter allows you to control the level of upscaling applied to the image.
This parameter controls the amount of noise augmentation applied during the upscaling process. The default value is 0.0, meaning no noise augmentation is applied. The minimum value is 0.0, and the maximum value is 1.0, with a step size of 0.001. Increasing this value can help in reducing artifacts and improving the overall quality of the upscaled image.
This output provides the positively conditioned result of the upscaling process. It reflects the features and details that were enhanced based on the positive conditioning input.
This output provides the negatively conditioned result of the upscaling process. It reflects the features and details that were suppressed or removed based on the negative conditioning input.
This output provides the latent representation of the upscaled image. It is an intermediate form that can be used for further processing or analysis within the AI pipeline.
scale_ratio
parameter to find the optimal upscaling factor for your images.noise_augmentation
parameter to reduce artifacts and improve the overall quality of the upscaled image.scale_ratio
parameter is set to a value outside the allowed range.scale_ratio
is between 0.0 and 10.0.noise_augmentation
parameter is set to a value outside the allowed range.noise_augmentation
is between 0.0 and 1.0.© Copyright 2024 RunComfy. All Rights Reserved.