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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 for img2img or inpaint mode
|
|
prompt |
string
|
aerial view, a futuristic research complex in a bright foggy jungle, hard lighting
|
Input prompt
|
negative_prompt |
string
|
low quality, bad quality, sketches
|
Input Negative Prompt
|
model_type |
string
(enum)
|
canny
Options: canny, openpose, scribble |
ControlNet model type to use
|
width |
integer
|
1024
|
Width of output image
|
height |
integer
|
1024
|
Height of output image
|
num_outputs |
integer
|
1
Min: 1 Max: 4 |
Number of images to output.
|
num_inference_steps |
integer
|
50
Min: 1 Max: 500 |
Number of denoising steps
|
guidance_scale |
number
|
7.5
Min: 1 Max: 20 |
Scale for classifier-free guidance
|
scheduler |
string
(enum)
|
K_EULER
Options: PNDM, KLMS, DDIM, K_EULER, K_EULER_ANCESTRAL, DPMSolverMultistep, DEISMultistepScheduler |
scheduler
|
condition_scale |
number
|
0.5
Max: 1 |
controlnet conditioning scale for generalization
|
adapter_conditioning_factor |
number
|
1
Max: 1 |
Factor to scale image by
|
low_threshold |
integer
|
100
Min: 1 Max: 255 |
Canny line detection low threshold
|
high_threshold |
integer
|
200
Min: 1 Max: 255 |
Canny line detection high threshold
|
seed |
integer
|
0
|
Random seed. Set to 0 to randomize the seed
|
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'}