ComfyUI Node: Reference ControlNet 🛂🅐🅒🅝

Reference ControlNet 🛂🅐🅒🅝:

The ACN_ReferenceControlNet node is designed to enhance your AI art generation by leveraging advanced control techniques. This node allows you to incorporate reference images or styles into your control network, providing a more nuanced and sophisticated approach to guiding the AI's creative process. By using this node, you can achieve a higher level of fidelity and control over the generated artwork, ensuring that the output aligns more closely with your artistic vision. The node supports various reference types and offers parameters to fine-tune the influence of the reference on the final output, making it a powerful tool for artists looking to push the boundaries of AI-generated art.

Reference ControlNet 🛂🅐🅒🅝 Input Parameters:

reference_type

This parameter specifies the type of reference you want to use in your control network. The available options are predefined in the ReferenceType class, which includes different methods for incorporating reference images or styles. Choosing the right reference type is crucial as it determines how the reference will influence the generated artwork.

style_fidelity

This float parameter controls the degree to which the style of the reference image is applied to the generated artwork. A higher value means that the generated image will closely mimic the style of the reference, while a lower value will result in a more subtle influence. The default value is 0.5, with a minimum of 0.0 and a maximum of 1.0, adjustable in steps of 0.01.

ref_weight

This float parameter determines the overall weight or importance of the reference in the control network. A higher weight means that the reference will have a stronger influence on the generated artwork. The default value is 1.0, with a minimum of 0.0 and a maximum of 1.0, adjustable in steps of 0.01.

Reference ControlNet 🛂🅐🅒🅝 Output Parameters:

CONTROL_NET

The output of this node is a control network (CONTROL_NET) that incorporates the specified reference type, style fidelity, and reference weight. This control network can then be used in subsequent nodes to guide the AI's creative process, ensuring that the generated artwork aligns with the specified reference parameters.

Reference ControlNet 🛂🅐🅒🅝 Usage Tips:

• Experiment with different reference_type options to see how each one influences the generated artwork. This can help you find the best method for incorporating your reference images or styles.
• Adjust the style_fidelity parameter to fine-tune the influence of the reference style. Higher values will result in a more pronounced style transfer, while lower values will keep the influence subtle.
• Use the ref_weight parameter to control the overall impact of the reference on the generated artwork. This can be particularly useful when combining multiple references or when you want to balance the influence of the reference with other control parameters.

Reference ControlNet 🛂🅐🅒🅝 Common Errors and Solutions:

"Invalid reference type"

• Explanation: This error occurs when the specified reference_type is not recognized or is not part of the predefined ReferenceType options.
• Solution: Ensure that you are using a valid reference_type from the ReferenceType class. Double-check the available options and select one that is supported.

"Style fidelity out of range"

• Explanation: This error occurs when the style_fidelity parameter is set outside the allowed range of 0.0 to 1.0.
• Solution: Adjust the style_fidelity parameter to be within the valid range. The value should be between 0.0 and 1.0, inclusive.

"Reference weight out of range"

• Explanation: This error occurs when the ref_weight parameter is set outside the allowed range of 0.0 to 1.0.
• Solution: Adjust the ref_weight parameter to be within the valid range. The value should be between 0.0 and 1.0, inclusive.