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xlabs-ai /flux-dev-controlnet:f2c31c31

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
None
negative_prompt
string
Things you do not want to see in your image
guidance_scale
number
3.5

Max: 5

Guidance scale
steps
integer
28

Min: 1

Max: 50

Number of steps
control_type
string (enum)
depth

Options:

canny, soft_edge, depth

Type of control net
control_strength
number
0.5

Max: 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.
control_image
string
Image to use with control net
image_to_image_strength
number
0

Max: 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.
depth_preprocessor
string (enum)
DepthAnything

Options:

Midas, Zoe, DepthAnything, Zoe-DepthAnything

Preprocessor to use with depth control net
soft_edge_preprocessor
string (enum)
HED

Options:

HED, TEED, PiDiNet

Preprocessor to use with soft edge control net
lora_url
string
Optional LoRA model to use. Give a URL to a HuggingFace .safetensors file, a Replicate .tar file or a CivitAI download link.
lora_strength
number
1

Min: -1

Max: 3

Strength of LoRA model
return_preprocessed_image
boolean
False
Return the preprocessed image used to control the generation process. Useful for debugging.
output_format
string (enum)
webp

Options:

webp, jpg, png

Format of the output images
output_quality
integer
80

Max: 100

Quality of the output images, from 0 to 100. 100 is best quality, 0 is lowest quality.
seed
integer
Set a seed for reproducibility. Random by default.

Output schema

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

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