ComfyUI  >  Nodes  >  ComfyUI Impact Pack >  ControlNetApplyAdvanced (SEGS)

ComfyUI Node: ControlNetApplyAdvanced (SEGS)

Class Name

ImpactControlNetApplyAdvancedSEGS

Category
ImpactPack/Util
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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ControlNetApplyAdvanced (SEGS) Description

Enhance AI art projects with advanced ControlNet techniques for segmented elements.

ControlNetApplyAdvanced (SEGS):

The ImpactControlNetApplyAdvancedSEGS node is designed to enhance your AI art projects by applying advanced ControlNet techniques to SEGS (Segmented Elements). This node allows you to integrate ControlNet with segmented elements, providing more control and precision over the manipulation and transformation of these elements. By leveraging advanced parameters such as strength, start percent, and end percent, you can fine-tune the influence of ControlNet on your segmented elements, resulting in more refined and detailed outputs. This node is particularly useful for tasks that require high levels of customization and control over segmented image regions, making it an essential tool for AI artists looking to push the boundaries of their creative projects.

ControlNetApplyAdvanced (SEGS) Input Parameters:

segs

This parameter represents the segmented elements (SEGS) that you want to apply the advanced ControlNet techniques to. It is a required input and serves as the primary data that will be manipulated by the node.

control_net

This parameter specifies the ControlNet model to be used. It is a required input and determines the underlying neural network that will influence the segmented elements.

strength

This parameter controls the intensity of the ControlNet's influence on the segmented elements. It is a required input with a default value of 1.0, a minimum value of 0.0, and a maximum value of 10.0. Adjusting this value allows you to fine-tune the effect of ControlNet, with higher values resulting in stronger influence.

start_percent

This parameter defines the starting point of the ControlNet's influence as a percentage of the process. It is a required input and allows you to control when the ControlNet begins to affect the segmented elements.

end_percent

This parameter defines the ending point of the ControlNet's influence as a percentage of the process. It is a required input and allows you to control when the ControlNet stops affecting the segmented elements.

segs_preprocessor

This optional parameter allows you to specify a preprocessor for the segmented elements. The preprocessor can modify the SEGS before they are passed to the ControlNet, providing an additional layer of customization.

control_image

This optional parameter allows you to provide a control image that can be used by the ControlNet. The control image can guide the transformation of the segmented elements, offering more precise control over the final output.

ControlNetApplyAdvanced (SEGS) Output Parameters:

segs

The output parameter is the modified segmented elements (SEGS) after applying the advanced ControlNet techniques. This output retains the original structure of the input SEGS but with the transformations and manipulations applied by the ControlNet, resulting in enhanced and refined segmented elements.

ControlNetApplyAdvanced (SEGS) Usage Tips:

  • To achieve subtle effects, start with a lower strength value and gradually increase it until you reach the desired level of influence.
  • Utilize the start_percent and end_percent parameters to control the timing of the ControlNet's influence, which can be particularly useful for animations or progressive transformations.
  • Experiment with different control images to see how they affect the segmented elements, providing unique and varied results.

ControlNetApplyAdvanced (SEGS) Common Errors and Solutions:

"Invalid control_net model"

  • Explanation: This error occurs when the specified ControlNet model is not recognized or is incompatible.
  • Solution: Ensure that you are using a valid and compatible ControlNet model. Verify the model's path and format.

"Strength value out of range"

  • Explanation: This error occurs when the strength parameter is set outside the allowed range (0.0 to 10.0).
  • Solution: Adjust the strength parameter to be within the valid range, ensuring it is between 0.0 and 10.0.

"Missing required input: segs"

  • Explanation: This error occurs when the required segs input is not provided.
  • Solution: Ensure that you have supplied the segmented elements (SEGS) as input to the node.

"Invalid start_percent or end_percent value"

  • Explanation: This error occurs when the start_percent or end_percent values are not within the valid range or are incorrectly set.
  • Solution: Verify that both start_percent and end_percent are set correctly and within the range of 0 to 100. Ensure that start_percent is less than or equal to end_percent.

ControlNetApplyAdvanced (SEGS) Related Nodes

Go back to the extension to check out more related nodes.
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