This is a simplified guide to an AI model called Flux-Controlnet maintained by Xlabs-Ai. If you like these kinds of analysis, you should join AImodels.fyi or follow us on Twitter.
Model overview
The flux-controlnet model, developed by the XLabs-AI team, is a ControlNet model fine-tuned on the FLUX.1-dev model by Black Forest Labs. It includes a Canny edge detection ControlNet checkpoint that can be used to generate images based on provided control images and text prompts. This model builds upon similar flux-dev-controlnet, flux-controlnet-canny, and flux-controlnet-canny-v3 models released by XLabs-AI.
Model inputs and outputs
The flux-controlnet model takes in a text prompt, a control image, and optional parameters like CFG scale and seed. It outputs a generated image based on the provided inputs.
Inputs
- Prompt: A text description of the desired image
- Image: A control image, such as a Canny edge map, that guides the generation process
- CFG Scale: The Classifier-Free Guidance Scale, which controls the influence of the text prompt
- Seed: The random seed, which controls the stochastic elements of the generation process
Outputs
- Image: A generated image that matches the provided prompt and control image
Capabilities
The flux-controlnet model can genera...
Top comments (0)