IndexTTS 1.5 Release: High-Quality Chinese and English Text-to-Speech Model

05/23/2025

Apply ControlNet

💡

This documentation is for the original Apply ControlNet(Advanced) node. The earliest Apply ControlNet node has been renamed to Apply ControlNet(Old). While you may still see the Apply ControlNet(Old) node in many workflow folders you download from comfyui.org for compatibility reasons, you can no longer find the Apply ControlNet(Old) node through search or node list. Please use the Apply ControlNet node instead.

Apply ControlNet

This node applies a ControlNet to a given image and conditioning, adjusting the image’s attributes based on the control network’s parameters and specified strength, such as Depth, OpenPose, Canny, HED, etc.

Documentation

Class name: ControlNetApply
Category: conditioning
Output node: False

Using controlNet requires preprocessing of input images. Since ComfyUI initial nodes do not come with preprocessors and controlNet models, please first install ContrlNet preprocessors download preprocessors here and corresponding controlNet models.

Input Types

Parameter	Data Type	Function
`positive`	`CONDITIONING`	Positive conditioning data, from CLIP Text Encoder or other conditioning inputs
`negative`	`CONDITIONING`	Negative conditioning data, from CLIP Text Encoder or other conditioning inputs
`control_net`	`CONTROL_NET`	The controlNet model to apply, typically input from ControlNet Loader
`image`	`IMAGE`	Image for controlNet application, needs to be processed by preprocessor
`vae`	`VAE`	Vae model input
`strength`	`FLOAT`	Controls the strength of network adjustments, value range 0~~10. Recommended values between 0.5~~1.5 are reasonable. Lower values allow more model freedom, higher values impose stricter constraints. Too high values may result in strange images. You can test and adjust this value to fine-tune the control network’s influence.
`start_percent`	`FLOAT`	Value 0.000~1.000, determines when to start applying controlNet as a percentage, e.g., 0.2 means ControlNet guidance will start influencing image generation at 20% of the diffusion process
`end_percent`	`FLOAT`	Value 0.000~1.000, determines when to stop applying controlNet as a percentage, e.g., 0.8 means ControlNet guidance will stop influencing image generation at 80% of the diffusion process

Output Types

Parameter	Data Type	Function
`positive`	`CONDITIONING`	Positive conditioning data processed by ControlNet, can be output to next ControlNet or K Sampler nodes
`negative`	`CONDITIONING`	Negative conditioning data processed by ControlNet, can be output to next ControlNet or K Sampler nodes

💡

If you want to use T2IAdaptor style models, please use the Apply Style Model node instead

ComfyUI ControlNet Usage Examples

Visit the following pages for examples:

Model Resources: controlNet Model Resources Download
Preprocessor Plugin: ComfyUI ControlNet Auxiliary Preprocessors