replicategithubwc
/
flux-dev-inpainting-controlnet
- Public
- 19 runs
Run replicategithubwc/flux-dev-inpainting-controlnet with an API
Use one of our client libraries to get started quickly. Clicking on a library will take you to the Playground tab where you can tweak different inputs, see the results, and copy the corresponding code to use in your own project.
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 photo of an astronaut riding a horse on mars
|
Input prompt
|
image |
string
|
Input image for img2img or inpaint mode
|
|
mask |
string
|
Input mask for inpaint mode. Black areas will be preserved, white areas will be inpainted.
|
|
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: 50 |
Number of denoising steps
|
guidance_scale |
number
|
7.5
Min: 1 Max: 20 |
Scale for classifier-free guidance
|
prompt_strength |
number
|
0.8
Max: 1 |
Prompt strength when using img2img / inpaint. 1.0 corresponds to full destruction of information in image
|
condition_scale |
number
|
0.7
Max: 1 |
Condition scale
|
control_guidance_start |
number
|
0.2
Max: 1 |
Condition scale
|
control_guidance_end |
number
|
0.8
Max: 1 |
Condition scale
|
seed |
integer
|
Random seed. Leave blank to randomize the seed
|
|
output_quality |
integer
|
80
Max: 100 |
Quality of the output image, from 0 to 100. 100 is best quality, 0 is lowest quality.
|
{
"type": "object",
"title": "Input",
"properties": {
"mask": {
"type": "string",
"title": "Mask",
"format": "uri",
"x-order": 2,
"description": "Input mask for inpaint mode. Black areas will be preserved, white areas will be inpainted."
},
"seed": {
"type": "integer",
"title": "Seed",
"x-order": 12,
"description": "Random seed. Leave blank to randomize the seed"
},
"image": {
"type": "string",
"title": "Image",
"format": "uri",
"x-order": 1,
"description": "Input image for img2img or inpaint mode"
},
"width": {
"type": "integer",
"title": "Width",
"default": 1024,
"x-order": 3,
"description": "Width of output image"
},
"height": {
"type": "integer",
"title": "Height",
"default": 1024,
"x-order": 4,
"description": "Height of output image"
},
"prompt": {
"type": "string",
"title": "Prompt",
"default": "a photo of an astronaut riding a horse on mars",
"x-order": 0,
"description": "Input prompt"
},
"num_outputs": {
"type": "integer",
"title": "Num Outputs",
"default": 1,
"maximum": 4,
"minimum": 1,
"x-order": 5,
"description": "Number of images to output."
},
"guidance_scale": {
"type": "number",
"title": "Guidance Scale",
"default": 7.5,
"maximum": 20,
"minimum": 1,
"x-order": 7,
"description": "Scale for classifier-free guidance"
},
"output_quality": {
"type": "integer",
"title": "Output Quality",
"default": 80,
"maximum": 100,
"minimum": 0,
"x-order": 13,
"description": "Quality of the output image, from 0 to 100. 100 is best quality, 0 is lowest quality."
},
"condition_scale": {
"type": "number",
"title": "Condition Scale",
"default": 0.7,
"maximum": 1,
"minimum": 0,
"x-order": 9,
"description": "Condition scale"
},
"prompt_strength": {
"type": "number",
"title": "Prompt Strength",
"default": 0.8,
"maximum": 1,
"minimum": 0,
"x-order": 8,
"description": "Prompt strength when using img2img / inpaint. 1.0 corresponds to full destruction of information in image"
},
"num_inference_steps": {
"type": "integer",
"title": "Num Inference Steps",
"default": 50,
"maximum": 50,
"minimum": 1,
"x-order": 6,
"description": "Number of denoising steps"
},
"control_guidance_end": {
"type": "number",
"title": "Control Guidance End",
"default": 0.8,
"maximum": 1,
"minimum": 0,
"x-order": 11,
"description": "Condition scale"
},
"control_guidance_start": {
"type": "number",
"title": "Control Guidance Start",
"default": 0.2,
"maximum": 1,
"minimum": 0,
"x-order": 10,
"description": "Condition scale"
}
}
}
Output schema
The shape of the response you’ll get when you run this model with an API.
{
"type": "array",
"items": {
"type": "string",
"format": "uri"
},
"title": "Output"
}