🚀 Smart Ultimate SD Upscale (Custom Sample)

Enhances images by intelligently upscaling with custom sampling for detailed, high-quality results.

🚀 Smart Ultimate SD Upscale (Custom Sample):

The ArchAi3D_Smart_Ultimate_SD_Upscale_CustomSample node is designed to enhance your images by intelligently upscaling them using a custom sampling method. This node is part of the ArchAi3D suite, which focuses on providing advanced upscaling capabilities for AI-generated art. By leveraging custom samplers and sigma values, this node allows you to fine-tune the upscaling process, resulting in higher quality and more detailed images. The primary goal of this node is to offer flexibility and control over the upscaling process, enabling you to achieve the desired level of detail and sharpness in your images. Whether you're working on intricate designs or large-scale artworks, this node provides the tools necessary to enhance your creations effectively.

🚀 Smart Ultimate SD Upscale (Custom Sample) Input Parameters:

image

The image parameter is the input image that you wish to upscale. It serves as the base for the upscaling process, and the quality of the input image can significantly impact the final result. Ensure that the image is of good quality to achieve optimal upscaling results.

model

The model parameter specifies the AI model used for the upscaling process. Different models can produce varying results, so selecting the appropriate model is crucial for achieving the desired output. The choice of model can affect the style and quality of the upscaled image.

conditionings

The conditionings parameter allows you to apply specific conditions or constraints during the upscaling process. This can include factors like color balance, contrast, or other image attributes that you want to maintain or enhance in the final output.

negative

The negative parameter is used to specify any negative conditions or attributes that should be minimized or avoided during the upscaling process. This helps in refining the output by reducing unwanted artifacts or features.

vae

The vae parameter refers to the Variational Autoencoder used in the upscaling process. It plays a role in encoding and decoding the image data, contributing to the overall quality and detail of the upscaled image.

upscale_by

The upscale_by parameter determines the scale factor for the upscaling process. It defines how much larger the output image will be compared to the input image. Common values include 2x, 4x, etc., depending on the desired level of enlargement.

seed

The seed parameter is used to initialize the random number generator for the upscaling process. By setting a specific seed value, you can ensure consistent and reproducible results across multiple runs.

steps

The steps parameter defines the number of iterations or steps the upscaling process will take. More steps can lead to higher quality results but may also increase processing time.

cfg

The cfg parameter, or configuration, allows you to adjust various settings and parameters for the upscaling process. This can include options like noise reduction, detail enhancement, and other image processing techniques.

sampler_name

The sampler_name parameter specifies the custom sampler to be used during the upscaling process. Different samplers can produce varying results, so selecting the appropriate one is crucial for achieving the desired output.

scheduler

The scheduler parameter manages the scheduling of the upscaling process, determining the order and timing of operations. This can impact the efficiency and speed of the upscaling process.

denoise

The denoise parameter controls the level of noise reduction applied during the upscaling process. Adjusting this parameter can help in achieving a cleaner and more polished final image.

mode_type

The mode_type parameter specifies the mode or method used for the upscaling process. Different modes can produce varying results, so selecting the appropriate one is crucial for achieving the desired output.

tile_width

The tile_width parameter defines the width of the tiles used in the upscaling process. Tiling can help in managing memory usage and processing large images more efficiently.

tile_height

The tile_height parameter defines the height of the tiles used in the upscaling process. Similar to tile width, this helps in managing memory usage and processing large images more efficiently.

mask_blur

The mask_blur parameter controls the level of blur applied to the mask used in the upscaling process. This can help in achieving smoother transitions and reducing artifacts in the final image.

tile_padding

The tile_padding parameter specifies the amount of padding added to each tile during the upscaling process. Padding can help in reducing edge artifacts and ensuring seamless transitions between tiles.

seam_fix_mode

The seam_fix_mode parameter determines the method used to fix seams or edges between tiles during the upscaling process. This can help in achieving a more cohesive and seamless final image.

seam_fix_denoise

The seam_fix_denoise parameter controls the level of noise reduction applied to seams or edges between tiles. This can help in achieving a cleaner and more polished final image.

seam_fix_mask_blur

The seam_fix_mask_blur parameter controls the level of blur applied to the mask used for fixing seams or edges between tiles. This can help in achieving smoother transitions and reducing artifacts.

seam_fix_width

The seam_fix_width parameter defines the width of the area used for fixing seams or edges between tiles. This can help in achieving a more cohesive and seamless final image.

seam_fix_padding

The seam_fix_padding parameter specifies the amount of padding added to the area used for fixing seams or edges between tiles. Padding can help in reducing edge artifacts and ensuring seamless transitions.

force_uniform_tiles

The force_uniform_tiles parameter determines whether to enforce uniform tile sizes during the upscaling process. This can help in achieving consistent results and reducing artifacts.

tiled_decode

The tiled_decode parameter specifies whether to use tiled decoding during the upscaling process. Tiled decoding can help in managing memory usage and processing large images more efficiently.

upscale_model

The upscale_model parameter allows you to specify a custom upscaling model to be used during the process. This provides flexibility in choosing the model that best suits your needs and desired output.

custom_sampler

The custom_sampler parameter allows you to specify a custom sampler to be used during the upscaling process. Different samplers can produce varying results, so selecting the appropriate one is crucial for achieving the desired output.

custom_sigmas

The custom_sigmas parameter allows you to specify custom sigma values to be used during the upscaling process. Adjusting sigma values can help in achieving the desired level of detail and sharpness in the final image.