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Refines and smooths mask edges for enhanced image quality and natural transitions.
The Mask Smooth Region node is designed to refine and smooth the edges of mask regions in your images. This node is particularly useful for AI artists who need to enhance the quality of their masks by reducing jagged edges and creating a more polished look. By applying a smoothing algorithm, this node helps in achieving a more natural transition between masked and unmasked areas, which is essential for high-quality image processing and editing tasks. The primary goal of this node is to improve the visual appeal and accuracy of masks, making it an invaluable tool for tasks that require precise and aesthetically pleasing results.
This parameter accepts the input masks that you want to smooth. The masks should be in a format that the node can process, typically as a tensor. The masks represent the regions in your image that you want to refine. The quality and structure of the input masks directly impact the effectiveness of the smoothing process.
The sigma parameter controls the extent of the smoothing applied to the mask regions. It is a floating-point value that determines the standard deviation of the Gaussian filter used for smoothing. A higher sigma value results in more significant smoothing, while a lower value provides finer control with less smoothing. The default value is 5.0, with a minimum of 0.0 and a maximum of 128.0, adjustable in steps of 0.1. Adjusting this parameter allows you to fine-tune the smoothness of the mask edges to match your specific needs.
The output parameter MASKS provides the smoothed masks as a tensor. These masks have undergone the smoothing process, resulting in refined edges and a more polished appearance. The output masks can be used in subsequent image processing tasks, ensuring that the refined regions blend seamlessly with the rest of the image.
Input masks must be a tensor
Sigma value out of range
Mask dimensions not supported
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