This node specializes in enhancing the resolution of images through a 4x upscale process, incorporating conditioning elements to refine the output. It leverages diffusion techniques to upscale images while allowing for the adjustment of scale ratio and noise augmentation to fine-tune the enhancement process.Documentation Index
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Inputs
| Parameter | Comfy dtype | Description |
|---|---|---|
images | IMAGE | The input images to be upscaled. This parameter is crucial as it directly influences the quality and resolution of the output images. |
positive | CONDITIONING | Positive conditioning elements that guide the upscale process towards desired attributes or features in the output images. |
negative | CONDITIONING | Negative conditioning elements that the upscale process should avoid, helping to steer the output away from undesired attributes or features. |
scale_ratio | FLOAT | Determines the factor by which the image resolution is increased. A higher scale ratio results in a larger output image, allowing for greater detail and clarity. |
noise_augmentation | FLOAT | Controls the level of noise augmentation applied during the upscale process. This can be used to introduce variability and improve the robustness of the output images. |
Outputs
| Parameter | Data Type | Description |
|---|---|---|
positive | CONDITIONING | The refined positive conditioning elements resulting from the upscale process. |
negative | CONDITIONING | The refined negative conditioning elements resulting from the upscale process. |
latent | LATENT | A latent representation generated during the upscale process, which can be utilized in further processing or model training. |