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Divide large images into smaller tiles for efficient processing and recombination with overlapping continuity.
The TileSplit node is designed to divide a large image into smaller, more manageable tiles. This is particularly useful for processing high-resolution images that may be too large to handle in a single pass. By splitting the image into tiles, you can apply various image processing techniques to each tile individually and then recombine them if needed. This node ensures that the tiles overlap slightly, which helps in maintaining continuity and avoiding visible seams when the tiles are processed and merged back together. The primary goal of the TileSplit node is to facilitate efficient and effective image processing by breaking down large images into smaller sections.
This parameter represents the input image that you want to split into tiles. The image should be in a format that the node can process, typically a tensor representing the image data.
This parameter specifies the height of each tile in pixels. The default value is 64, with a minimum value of 64 and a maximum value of 4096. Adjusting this value will change the height of the tiles, impacting how the image is divided.
This parameter specifies the width of each tile in pixels. The default value is 64, with a minimum value of 64 and a maximum value of 4096. Adjusting this value will change the width of the tiles, impacting how the image is divided.
This parameter determines the number of pixels by which adjacent tiles will overlap. The default value is 64, with a minimum value of 0 and a maximum value of 4096. Overlapping tiles help maintain continuity and avoid visible seams when the tiles are processed and merged back together.
The output is a tensor containing the tiles generated from the input image. Each tile is a smaller section of the original image, and the tiles are arranged in a way that they can be processed individually and then recombined if needed.
tile_height
and tile_width
parameters based on the resolution of your input image and the capabilities of your processing hardware. Smaller tiles may be easier to process but could increase the number of tiles generated.overlap
parameter to ensure that there are no visible seams when the tiles are recombined. A higher overlap value can help maintain continuity but may result in more redundant data.tile_height
and tile_width
are larger than the dimensions of the input image.tile_height
and tile_width
parameters to be smaller than the dimensions of the input image.overlap
parameter is set to a value that is too high, causing excessive overlap between tiles.overlap
parameter to a more reasonable value that ensures continuity without excessive redundancy.© Copyright 2024 RunComfy. All Rights Reserved.