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Enhance and combine conditioning data with masks, LoRA hooks, and timesteps for precise AI art effects.
The ADE_ConditioningSetMaskAndCombine node is designed to enhance and combine conditioning data in your AI art projects. This node allows you to apply additional conditioning data to existing conditioning, with the option to use masks, LoRA hooks, and timesteps to fine-tune the results. By adjusting the strength and area of the conditioning, you can achieve more precise and controlled effects in your animations. This node is particularly useful for artists looking to blend multiple conditioning sources seamlessly, ensuring that the final output is a well-balanced combination of the inputs.
This parameter represents the initial conditioning data that you want to enhance and combine with additional conditioning. It is a required input and serves as the base for the final conditioning output.
This parameter is the additional conditioning data that you want to combine with the initial conditioning. It is also a required input and allows you to introduce new conditioning elements to the existing data.
This parameter controls the intensity of the additional conditioning applied to the initial conditioning. It is a float value with a default of 1.0, a minimum of 0.0, and a maximum of 10.0, with a step of 0.01. Adjusting this value allows you to fine-tune the influence of the additional conditioning.
This parameter specifies the area where the conditioning should be applied. It is a required input and can take values from a predefined list of conditioning areas. This allows you to target specific regions for conditioning application.
This optional parameter allows you to provide a mask that defines the specific areas where the additional conditioning should be applied. If not provided, the conditioning will be applied uniformly.
This optional parameter allows you to apply a LoRA (Low-Rank Adaptation) hook to the additional conditioning. This can be used to introduce more complex conditioning transformations.
This optional parameter allows you to specify timesteps for the conditioning, enabling time-based conditioning effects. If not provided, the conditioning will be applied uniformly over time.
The output of this node is the final conditioning data, which is a combination of the initial and additional conditioning, modified according to the specified parameters. This output can be used in subsequent nodes to influence the behavior and appearance of your AI-generated animations.
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