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Convert PIL images to masks for image processing and AI art, enabling precise transparency control.
The PILToMask
node is designed to convert images in the PIL (Python Imaging Library) format into mask representations, which are useful in various image processing and AI art applications. This node is particularly beneficial for artists and developers who need to manipulate image transparency or create masks for compositing tasks. By transforming the alpha channel of an image into a mask, it allows for precise control over which parts of an image are visible or affected by subsequent operations. The node handles images with or without an alpha channel, ensuring that even images lacking transparency information are processed into a default mask. This functionality is crucial for workflows that require consistent mask outputs regardless of the input image's properties.
The images
parameter expects a collection of images in the PIL format. This input is crucial as it provides the raw image data that the node will process to generate masks. The images should be in a format that PIL can handle, and they may or may not contain an alpha channel. If an image includes an alpha channel, it will be used to create the mask; otherwise, a default mask will be generated. This parameter does not have specific minimum, maximum, or default values, as it depends on the images you provide.
The output parameter, IMAGE
, represents the mask generated from the input images. This mask is a tensor that encodes the transparency information of the images, with values typically ranging from 0 to 1, where 0 indicates full transparency and 1 indicates full opacity. The output is crucial for tasks that require precise control over image visibility, such as compositing or blending operations. The mask can be used in subsequent nodes to influence how images are combined or manipulated.
convert
method before passing them to the node.© Copyright 2024 RunComfy. All Rights Reserved.
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