You're looking at a specific version of this model. Jump to the model overview.
xlabs-ai /flux-dev-controlnet:56ac7b66
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 1, 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
|
| 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'}