xlabs-ai/flux-dev-controlnet

XLabs v3 canny, depth and soft edge controlnets for Flux.1 Dev

Input
Configure the inputs for the AI model.

Set a seed for reproducibility. Random by default.

1
50

Number of steps

Optional LoRA model to use. Give a URL to a HuggingFace .safetensors file, a Replicate .tar file or a CivitAI download link.

Type of control net

Image to use with control net

-1
3

Strength of LoRA model

Format of the output images

0
5

Guidance scale

0
100

Quality of the output images, from 0 to 100. 100 is best quality, 0 is lowest quality.

Things you do not want to see in your image

0
3

Strength of control net. Different controls work better with different strengths. Canny works best with 0.5, soft edge works best with 0.4, and depth works best between 0.5 and 0.75. If images are low quality, try reducing the strength and try reducing the guidance scale.

Preprocessor to use with depth control net

Preprocessor to use with soft edge control net

0
1

Strength of image to image control. 0 means none of the control image is used. 1 means the control image is returned used as is. Try values between 0 and 0.25 for best results.

Return the preprocessed image used to control the generation process. Useful for debugging.

Output
The generated output will appear here.

No output yet

Click "Generate" to create an output.