ComfyUI  >  Nodes  >  ComfyUI Impact Pack >  ImpactConditionalBranch

ComfyUI Node: ImpactConditionalBranch

Class Name

ImpactConditionalBranch

Category
ImpactPack/Logic
Author
Dr.Lt.Data (Account age: 458 days)
Extension
ComfyUI Impact Pack
Latest Updated
6/19/2024
Github Stars
1.4K

How to Install ComfyUI Impact Pack

Install this extension via the ComfyUI Manager by searching for  ComfyUI Impact Pack
  • 1. Click the Manager button in the main menu
  • 2. Select Custom Nodes Manager button
  • 3. Enter ComfyUI Impact Pack in the search bar
After installation, click the  Restart button to restart ComfyUI. Then, manually refresh your browser to clear the cache and access the updated list of nodes.

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ImpactConditionalBranch Description

Facilitates conditional logic for dynamic decision-making in AI art workflows.

ImpactConditionalBranch:

The ImpactConditionalBranch node is designed to facilitate conditional logic within your AI art workflows. This node allows you to direct the flow of execution based on a boolean condition, enabling dynamic and flexible decision-making processes. By evaluating a given condition, the node selects one of two possible values to output, making it a powerful tool for creating complex, responsive art generation pipelines. This capability is particularly useful for scenarios where different actions or values are required based on specific criteria, enhancing the adaptability and intelligence of your AI-driven art projects.

ImpactConditionalBranch Input Parameters:

cond

The cond parameter is a boolean input that determines the branch of execution. If cond is True, the node will output the value specified by tt_value; if False, it will output the value specified by ff_value. This parameter is crucial for controlling the flow of logic based on dynamic conditions within your workflow.

tt_value

The tt_value parameter represents the value to be output if the cond parameter is True. This can be of any type, allowing for flexible and varied outputs depending on the condition. The specific type and content of tt_value will depend on the needs of your workflow and the data being processed.

ff_value

The ff_value parameter represents the value to be output if the cond parameter is False. Similar to tt_value, this can be of any type, providing flexibility in the output based on the condition. The specific type and content of ff_value will depend on the requirements of your workflow and the data being processed.

ImpactConditionalBranch Output Parameters:

any_typ

The output of the ImpactConditionalBranch node is a single value of any type, determined by the evaluation of the cond parameter. If cond is True, the output will be the value of tt_value; if False, the output will be the value of ff_value. This output is essential for directing the subsequent steps in your workflow based on the evaluated condition.

ImpactConditionalBranch Usage Tips:

  • Use the ImpactConditionalBranch node to create dynamic workflows that can adapt to different conditions and scenarios, enhancing the flexibility and responsiveness of your AI art projects.
  • Ensure that the tt_value and ff_value parameters are appropriately set to handle the possible outcomes of the cond parameter, providing meaningful and contextually relevant outputs for both true and false conditions.

ImpactConditionalBranch Common Errors and Solutions:

Missing or invalid cond parameter

  • Explanation: The cond parameter is either missing or not a boolean value.
  • Solution: Ensure that the cond parameter is provided and is a valid boolean value (True or False).

Incompatible tt_value or ff_value types

  • Explanation: The types of tt_value and ff_value are not compatible with the expected output type.
  • Solution: Verify that both tt_value and ff_value are of the correct type and compatible with the expected output type for your workflow.

Unexpected output behavior

  • Explanation: The output does not match the expected value based on the cond parameter.
  • Solution: Double-check the logic of your condition and ensure that the cond, tt_value, and ff_value parameters are correctly set to produce the desired output.

ImpactConditionalBranch Related Nodes

Go back to the extension to check out more related nodes.
ComfyUI Impact Pack
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