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Generate unique tiling layouts with random patterns for AI art projects.
The RandomTillingLayouts
node is designed to generate random tiling layouts for your AI art projects. This node allows you to create complex and varied patterns by specifying ranges for rows and columns, as well as weights for different cuts. By leveraging randomization, it ensures that each generated layout is unique, adding an element of unpredictability and creativity to your designs. The primary goal of this node is to provide a flexible and dynamic way to create intricate tiling patterns that can be used in various artistic applications, enhancing the visual complexity and appeal of your work.
This parameter defines the minimum number of rows that the generated layout can have. It ensures that the layout will have at least this many rows, providing a lower bound for the vertical complexity of the pattern. The value should be a non-negative integer.
This parameter sets the maximum number of rows that the generated layout can have. It acts as an upper bound for the vertical complexity, ensuring that the layout does not exceed this number of rows. The value should be a non-negative integer and should be greater than or equal to min_rows
.
This parameter specifies the minimum number of columns that the generated layout can have. It ensures that the layout will have at least this many columns, providing a lower bound for the horizontal complexity of the pattern. The value should be a non-negative integer.
This parameter sets the maximum number of columns that the generated layout can have. It acts as an upper bound for the horizontal complexity, ensuring that the layout does not exceed this number of columns. The value should be a non-negative integer and should be greater than or equal to min_colums
.
This parameter defines the maximum weight for the global cuts in the layout. The weight influences the distribution and size of the cuts, with higher values leading to more significant variations. The value should be a positive number.
This parameter specifies the maximum weight for the nested cuts in the layout. Similar to max_weights_gcuts
, this weight affects the distribution and size of the nested cuts, adding another layer of complexity to the pattern. The value should be a positive number.
This parameter sets the seed for the random number generator used in creating the layout. By providing a specific seed, you can ensure that the same layout is generated consistently, which is useful for reproducibility. The value should be an integer.
The layout
output is a string that represents the generated tiling pattern. This string encodes the structure of the layout, including the number of rows and columns, as well as the weights of the cuts. It can be used as input for other nodes or processes that require a tiling layout.
min_rows
, max_rows
, min_colums
, and max_colums
. Larger ranges will generally result in more complex layouts.rnd_seed
parameter to generate reproducible layouts. This is particularly useful if you want to recreate a specific pattern or share it with others.max_weights_gcuts
and max_weights_ncuts
parameters to control the distribution and size of the cuts. Higher weights will lead to more pronounced variations in the pattern.min_colums
parameter is set to a value greater than max_colums
.min_colums
is less than or equal to max_colums
.min_rows
parameter is set to a value greater than max_rows
.min_rows
is less than or equal to max_rows
.max_colums
and max_rows
are set to zero, which would result in an invalid layout.max_colums
or max_rows
to a non-zero value.rnd_seed
parameter is not set to a valid integer.rnd_seed
is an integer value.© Copyright 2024 RunComfy. All Rights Reserved.