You're looking at a specific version of this model. Jump to the model overview.

usamaehsan /flux-multi-controlnet:538edfba

Input schema

The fields you can use to run this model with an API. If you don’t give a value for a field its default value will be used.

Field Type Default value Description
prompt
string
A girl in city, 25 years old, cool, futuristic style
The text prompt that guides image generation. Be detailed and specific about the image you want to create. Include style, mood, colors, and specific details.
canny_image
string
Input image for edge detection control. The Canny ControlNet will use the edges detected in this image to guide the generation. Best for preserving structural elements and outlines.
depth_image
string
Input image for depth control. The Depth ControlNet will preserve the spatial relationships and 3D structure of this image in the generated result. Excellent for maintaining perspective and spatial layout.
lineart_image
string
Input image for line art control. The Lineart ControlNet will follow the artistic lines and sketches in this image. Perfect for turning sketches into detailed artwork while maintaining the original composition.
upscaler_image
string
Input image for upscaling control. The Upscaler ControlNet will enhance and improve the resolution of this image while maintaining its core details and structure. Ideal for improving image quality and adding details.
canny_strength
number
0.6

Max: 2

Controls how strongly the edge detection influences the final image. Higher values (closer to 2.0) follow edge guidance more strictly, lower values (closer to 0) allow more creative freedom.
depth_strength
number
0.6

Max: 2

Determines how strictly the depth information influences the generation. Higher values preserve spatial relationships more faithfully, lower values allow more artistic interpretation.
lineart_strength
number
0.6

Max: 2

Controls how closely the generated image follows the input line art. Higher values stick closer to the original lines, lower values allow more artistic freedom while maintaining basic composition.
upscaler_strength
number
0.6

Max: 2

Determines how much the upscaler influences the final result. Higher values preserve more details from the original image, lower values allow more creative reinterpretation while upscaling.
guidance_scale
number
3.5

Max: 20

Controls how closely the image follows the prompt. Higher values (7-20) result in images that more strictly follow the prompt but may be less natural. Lower values (1-7) allow more creative freedom but may stray from the prompt.
steps
integer
8

Min: 1

Max: 50

Number of denoising steps. More steps generally result in higher quality images but take longer to generate. 8-15 steps for quick results, 20-50 for higher quality. Diminishing returns after 30 steps.
seed
integer
Random seed for reproducible results. Using the same seed with identical parameters will generate the same image. Leave as None for random results.
hyperflex_lora_weight
number
0.125

Max: 1

Weight of the HyperFlex LoRA adaptation. Higher values enhance the model's flexibility in interpreting prompts. Recommended range 0.1-0.3 for balanced results.
add_details_lora_weight
number
0

Max: 1

Weight of the Add Details LoRA adaptation. Higher values enhance fine details and textures in the generated image. Recommended range 0.2-0.5 for enhanced detail.
realism_lora_weight
number
0

Max: 1

Weight of the Realism LoRA adaptation. Higher values enhance photorealistic qualities in the generated image. Recommended range 0.3-0.7 for balanced realism.
widthh
integer
0

Max: 5000

Output image width in pixels. Must be divisible by 8. Higher values create wider images but require more memory. Set to 0 to use input image width. Recommended: 512-1024 for optimal quality.
heightt
integer
0

Max: 5000

Output image height in pixels. Must be divisible by 8. Higher values create taller images but require more memory. Set to 0 to use input image height. Recommended: 512-1024 for optimal quality.

Output schema

The shape of the response you’ll get when you run this model with an API.

Schema
{'format': 'uri', 'title': 'Output', 'type': 'string'}