ControlNet HED
Input
Prompt
Steps
Scheduler
Seed
Input Image
Output
ControlNet HED
ControlNet is a neural network architechture that can be used to control pretrained large diffusion models to support additional input conditions. The purpose of ControlNet HED is to use the soft HED Boundary to preserve many details in input images, making this model suitable for recoloring and stylizing.
Weights
The model is trained with HED boundary detection to obtain 3M edge-image-caption pairs.
Features
- Soft edges for recoloring and styling: The soft HED Boundary will preserve many details in input images, making this app suitable for recoloring and stylizing
Applications
ControlNet HED can be utilized in various applications, such as:
- Stylizing images based on a single input
- Recoloring images
Getting Started
For more detailed instructions, refer to the API documentation and resources available on Github.
Github
https://github.com/lllyasviel/ControlNet