ControlNet Canny
Input
Prompt
Steps
Scheduler
Seed
Input Image
Output
ControlNet Canny
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 Canny is to detect and preserve canny edges in input images, making this model suitable for generating images which can preserve the boundaries and fine features of the original image.
Weights
The model is trained on images and their corresponding white canny edges monochrome images.
Features
- Canny Edge detection: The Canny Edge will preserve the boundaries and feature details in input images, making these models suitable for generating images with fine tune control of the input image features.
Applications
ControlNet Canny can be utilized in various applications, such as:
- Generating images with finer features like facial expressions etc.
Getting Started
For more detailed instructions, refer to the API documentation and resources available on Github.
Github
https://github.com/lllyasviel/ControlNet