ComfyUI Node: ControlNet Stacker Adv.

ControlNet Stacker Adv.:

The AV_ControlNetEfficientStacker node is designed to streamline the process of stacking multiple ControlNet models efficiently. This node is particularly useful for AI artists who want to apply various ControlNet models to an image in a sequential manner, allowing for complex and layered effects. By leveraging this node, you can easily manage and apply different ControlNet models with varying strengths and preprocessing steps, all within a single workflow. This node simplifies the integration of multiple ControlNet models, ensuring that your creative process remains smooth and efficient.

ControlNet Stacker Adv. Input Parameters:

control_net_name

This parameter specifies the name of the ControlNet model to be used. You can choose from predefined options like None, Auto: sd15, Auto: sdxl, Auto: sdxl_t2i, or any other ControlNet models available in your setup. The Auto options automatically detect the appropriate ControlNet model based on the selected preprocessor and Stable Diffusion version.

image

This parameter accepts the input image that you want to process using the ControlNet models. The image should be in a compatible format that the node can handle.

strength

This parameter controls the intensity of the ControlNet model's effect on the input image. It is a floating-point value with a default of 1.0, a minimum of 0.0, and a maximum of 10.0. Adjusting this value allows you to fine-tune the influence of the ControlNet model on the final output.

preprocessor

This parameter specifies the preprocessor to be applied to the input image before passing it to the ControlNet model. You can choose from options like None or any other available preprocessors in your setup. The preprocessor helps in preparing the image for optimal results with the ControlNet model.

cnet_stack

This optional parameter allows you to provide an existing stack of ControlNet models. If not provided, a new stack will be initialized.

control_net_override

This optional parameter allows you to override the default ControlNet model with a specific one by providing its name as a string. The default value is None.

timestep_keyframe

This optional parameter allows you to specify keyframes for timesteps, which can be useful for animations or time-based effects.

resolution

This optional parameter sets the resolution for the preprocessed image. It is an integer value with a default of 512, a minimum of 64, and a maximum of 2048, adjustable in steps of 64. Adjusting the resolution can impact the quality and detail of the final output.

enabled

This optional boolean parameter determines whether the ControlNet model should be applied. The default value is True. Setting it to False will skip the application of the ControlNet model.

ControlNet Stacker Adv. Output Parameters:

cnet_stack

This output parameter returns the updated stack of ControlNet models. The stack includes tuples of the ControlNet model, the preprocessed image, the strength, and the start and end percentages. This stack can be used for further processing or for applying additional ControlNet models.

ControlNet Stacker Adv. Usage Tips:

• To achieve complex and layered effects, experiment with different combinations of ControlNet models and preprocessors.
• Adjust the strength parameter to fine-tune the influence of each ControlNet model on your image.
• Use the resolution parameter to control the level of detail in the preprocessed image, balancing quality and performance.
• Utilize the control_net_override parameter to quickly switch between different ControlNet models without changing the entire setup.

ControlNet Stacker Adv. Common Errors and Solutions:

AssertionError: preprocessor must be set when using Auto mode

• Explanation: This error occurs when you select an Auto ControlNet model but do not specify a preprocessor.
• Solution: Ensure that you select a valid preprocessor when using an Auto ControlNet model.

Warning: Not found ControlNet preprocessor <preprocessor_override>. Use <preprocessor> instead.

• Explanation: This warning indicates that the specified preprocessor override is not found in the available preprocessors.
• Solution: Verify the name of the preprocessor override and ensure it matches one of the available preprocessors. If the override is not necessary, you can ignore this warning and proceed with the default preprocessor.