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rossjillian /controlnet:795433b1
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 |
|---|---|---|---|
| image |
string
|
Input image
|
|
| prompt |
string
|
Prompt for the model
|
|
| structure |
string
(enum)
|
Options: canny, depth, hed, hough, normal, pose, scribble, seg |
Controlnet structure to condition on
|
| num_outputs |
integer
|
1
Min: 1 Max: 4 |
Number of images to output (higher values may OOM)
|
| image_resolution |
integer
(enum)
|
512
Options: 256, 512, 768 |
Resolution of output image (will be scaled to this as its smaller dimension)
|
| scheduler |
string
(enum)
|
DDIM
Options: DDIM, DPMSolverMultistep, HeunDiscrete, K_EULER_ANCESTRAL, K_EULER, KLMS, PNDM, UniPCMultistep |
Choose a scheduler.
|
| steps |
integer
|
20
|
Steps
|
| scale |
number
|
9
Min: 0.1 Max: 30 |
Scale for classifier-free guidance
|
| seed |
integer
|
Seed
|
|
| eta |
number
|
0
|
Controls the amount of noise that is added to the input data during the denoising diffusion process. Higher value -> more noise
|
| negative_prompt |
string
|
Longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality
|
Negative prompt
|
| return_reference_image |
boolean
|
False
|
whether to return the reference image along with the output
|
| low_threshold |
integer
|
100
Min: 1 Max: 255 |
[canny only] Line detection low threshold
|
| high_threshold |
integer
|
200
Min: 1 Max: 255 |
[canny only] Line detection high threshold
|
Output schema
The shape of the response you’ll get when you run this model with an API.
{'items': {'format': 'uri', 'type': 'string'},
'title': 'Output',
'type': 'array'}