ControlNet MLSD
Input
Prompt
Steps
Scheduler
Seed
Input Image
Output
ControlNet MLSD
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 MLSD is to detect and preserve straight lines in input images, making this model suitable for generating images with straight line edges.
Weights
The model is trained on images and their corresponding MLSD detected monochrome images.
Features
- Straight Line detection: The MLSD Boundary will preserve straight lines and edge details in input images, making these models suitable for generating architecture and interior designs.
Applications
ControlNet MLSD can be utilized in various applications, such as:
- Generating buildings and other architectures.
- Generating interior designs based on straight line sketches.
Getting Started
For more detailed instructions, refer to the API documentation and resources available on Github.
Github
https://github.com/lllyasviel/ControlNet