sd-webui-controlnet
WebUI extension for ControlNet
A plugin for the AUTOMATIC1111 Stable Diffusion web UI that lets you guide image generation with a reference image, a sketch, depth map, or pose, so results match a specific composition rather than being random.
This project is an extension for AUTOMATIC1111's Stable Diffusion web UI that plugs ControlNet, and other injection-based controls, into the image-generation workflow. Stable Diffusion on its own takes a text prompt and produces an image, but you have limited say over composition, pose, depth, or layout. ControlNet lets you guide generation with an extra input image, like a sketch or a depth map, so the result follows that shape. This extension brings that capability directly into the web UI as an on-the-fly addition that does not require merging anything into the base model.
You install it from inside the web UI by pasting its git URL into the Install from URL tab, restarting the UI, then downloading the ControlNet models into the extension's models folder. Once loaded, ControlNet appears as a panel where you pick a model and a preprocessor, feed in a control image, and the extension handles the rest. It supports a Pixel-Perfect mode that picks the preprocessor resolution automatically, integrates with the web UI's high-resolution fix by producing both a small and a large control image, and works with the different img2img and inpainting mask types. Control Modes let you bias generation toward your prompt or toward the control image, and there is support for upscaling scripts such as Ultimate SD upscale and Tiled VAE/Diffusion.
People reach for this when they want repeatable, controllable image generation rather than the lottery of pure text-to-image. It is built in Python for the AUTOMATIC1111 web UI environment, and the README's news section lists ongoing additions like Depth Anything V2, IP-Adapter features, and a ControlNet union model.
Where it fits
- Guide AI image generation to reproduce a specific pose from a reference photo without modifying or merging any base model.
- Turn a rough pencil sketch into a detailed illustration by feeding it as a ControlNet control image instead of relying on a text prompt alone.
- Generate consistent character layouts or product compositions across many images by reusing the same depth map or lineart as the control signal.