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Facilitates loading images with transparency, retains alpha channels, converts to RGBA for seamless integration in projects.
The Bjornulf_LoadImageWithTransparency
node is designed to facilitate the loading of images while preserving their transparency attributes. This node is particularly beneficial for AI artists who work with images that include alpha channels, as it ensures that the transparency information is retained throughout the processing pipeline. By converting images to the RGBA format, this node allows for seamless integration of images with varying transparency levels into your projects. The primary goal of this node is to provide a reliable method for handling images with transparency, making it easier to manipulate and utilize them in creative workflows without losing essential transparency data.
The image
parameter is the path to the image file you wish to load. This parameter is crucial as it specifies the source image that the node will process. The image should be in a format that supports transparency, such as PNG, to fully utilize the node's capabilities. There are no explicit minimum or maximum values for this parameter, but it must be a valid file path to an image that exists on your system.
The output_image
is a tensor representation of the loaded image, including its RGB and alpha channels. This output is essential for further processing or manipulation within your AI art projects, as it retains the original transparency information of the image.
The output_mask
is a tensor that represents the alpha channel of the image, indicating the transparency levels across the image. This mask is useful for operations that require knowledge of which parts of the image are transparent or opaque.
The image_path
is the file path of the loaded image, returned as part of the output. This is useful for tracking and referencing the source of the image within your workflow.
output_mask
to apply additional effects or transformations selectively based on the transparency of the image.<file_path>
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