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Progressively upscale latent images with high-quality results using iterative scaling techniques for AI artists.
The IterativeLatentUpscale
node is designed to progressively upscale latent images through multiple steps, ensuring high-quality results by leveraging iterative scaling techniques. This node is particularly useful for AI artists who need to enhance the resolution of their latent images while maintaining the integrity and details of the original content. By breaking down the upscaling process into smaller, manageable steps, IterativeLatentUpscale
minimizes artifacts and produces smoother, more refined images. This method is beneficial for achieving precise control over the upscaling process, allowing for both geometric and simple step modes to cater to different artistic needs and preferences.
This parameter represents the latent image data that you want to upscale. It is the core input for the node and contains the initial image information in a latent space format.
This parameter determines the overall scaling factor by which the image will be upscaled. It is a floating-point value with a default of 1.5, a minimum of 0.01, and a maximum of 8.0. Adjusting this value will directly impact the final resolution of the upscaled image.
This parameter specifies the number of iterative steps to perform during the upscaling process. More steps can lead to finer control and potentially higher quality results, but may also increase processing time.
This parameter defines the method used for scaling in each step. It can be set to either "geometric" or "simple". The geometric mode scales the image by a consistent factor in each step, while the simple mode adds a fixed amount to the scale in each step.
This optional parameter allows you to specify a prefix for saving temporary images during the upscaling process. If left empty, no temporary images will be saved.
This parameter is used internally to track the status of the upscaling process. It helps in updating the node status and providing progress feedback.
The primary output of the node is the upscaled latent image. This output retains the enhanced resolution and details achieved through the iterative upscaling process, ready for further processing or final rendering.
temp_prefix
parameter to save intermediate results and monitor the progress of the upscaling process.© Copyright 2024 RunComfy. All Rights Reserved.