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Merge sigma schedules with specified weights for blending in AI animations, offering control over interpolation.
The ADE_SigmaScheduleSplitAndCombine node is designed to merge two sigma schedules by interpolating between them based on specified weights. This node is particularly useful in scenarios where you need to blend different sampling schedules to achieve a desired effect in your AI-generated animations. By allowing you to specify the starting and ending weights for the interpolation, as well as the interpolation method, this node provides a high degree of control over the blending process. The primary goal of this node is to create a new sigma schedule that combines the characteristics of two input schedules, enabling more nuanced and customized sampling strategies.
This parameter represents the first sigma schedule to be combined. It is a required input and should be of type SIGMA_SCHEDULE
. The sigma schedule contains the sampling information that will be blended with the second schedule.
This parameter represents the second sigma schedule to be combined. It is also a required input and should be of type SIGMA_SCHEDULE
. This schedule will be blended with the first schedule based on the specified weights.
This parameter specifies the starting weight for the first sigma schedule (schedule_A
) in the interpolation process. It is a floating-point value with a default of 0.5, a minimum of 0.0, and a maximum of 1.0. This weight determines the influence of schedule_A
at the beginning of the interpolation.
This parameter specifies the ending weight for the first sigma schedule (schedule_A
) in the interpolation process. It is a floating-point value with a default of 0.5, a minimum of 0.0, and a maximum of 1.0. This weight determines the influence of schedule_A
at the end of the interpolation.
This parameter defines the method of interpolation to be used when blending the two sigma schedules. It is a required input and should be selected from the available interpolation methods provided by InterpolationMethod._LIST
. The choice of interpolation method affects how smoothly the transition between the two schedules occurs.
The output of this node is a new sigma schedule that combines the characteristics of the two input schedules based on the specified weights and interpolation method. This combined sigma schedule can be used in subsequent nodes to guide the sampling process in AI-generated animations, providing a customized and blended sampling strategy.
weight_A_Start
and weight_A_End
parameters to control the influence of each sigma schedule at different points in the interpolation. This can help you achieve the desired balance between the two schedules.schedule_A
and schedule_B
) are compatible by having the same number of sigmas. This is crucial for the interpolation to work correctly.schedule_A
and schedule_B
have the same number of sigmas before attempting to combine them. You may need to adjust the schedules or select different ones that are compatible.InterpolationMethod._LIST
. Double-check the method name to ensure it is correctly specified.© Copyright 2024 RunComfy. All Rights Reserved.