fottoai / ad-inpaint-pro
Ad-Inpaint pro version with best quality. this version work just with transparent object.
- Public
- 326 runs
Run fottoai/ad-inpaint-pro 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 |
---|---|---|---|
input_image |
string
|
Original Image Url
|
|
prompt |
string
|
a photo of an astronaut riding a horse on mars
|
Input prompt
|
negative_prompt |
string
|
low quality, out of frame, illustration, 3d, sepia, painting, cartoons, sketch, watermark, text, Logo, advertisement, products
|
Default is: low quality, out of frame, illustration, 3d, sepia, painting, cartoons, sketch, watermark, text, Logo, advertisement, products
|
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
|
num_outputs |
integer
|
1
Min: 1 Max: 4 |
Number of images to output.
|
object_fill_percent |
integer
(enum)
|
80
Options: 30, 40, 50, 60, 70, 80, 90, 100 |
Object fill percentage
|
adapter_condition_scale |
number
|
0.8
Min: 0.1 Max: 1 |
Scale for classifier-free guidance
|
scheduler |
string
(enum)
|
K_EULER_ANCESTRAL
Options: DDIM, K_EULER, DPMSolverMultistep, K_EULER_ANCESTRAL, PNDM, KLMS |
Choose a scheduler.
|
seed |
integer
|
Random seed. Leave blank to randomize the seed
|
{
"type": "object",
"title": "Input",
"required": [
"input_image"
],
"properties": {
"seed": {
"type": "integer",
"title": "Seed",
"x-order": 9,
"description": "Random seed. Leave blank to randomize the seed"
},
"prompt": {
"type": "string",
"title": "Prompt",
"default": "a photo of an astronaut riding a horse on mars",
"x-order": 1,
"description": "Input prompt"
},
"scheduler": {
"enum": [
"DDIM",
"K_EULER",
"DPMSolverMultistep",
"K_EULER_ANCESTRAL",
"PNDM",
"KLMS"
],
"type": "string",
"title": "scheduler",
"description": "Choose a scheduler.",
"default": "K_EULER_ANCESTRAL",
"x-order": 8
},
"input_image": {
"type": "string",
"title": "Input Image",
"format": "uri",
"x-order": 0,
"description": "Original Image Url"
},
"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": 4,
"description": "Scale for classifier-free guidance"
},
"negative_prompt": {
"type": "string",
"title": "Negative Prompt",
"default": "low quality, out of frame, illustration, 3d, sepia, painting, cartoons, sketch, watermark, text, Logo, advertisement, products",
"x-order": 2,
"description": "Default is: low quality, out of frame, illustration, 3d, sepia, painting, cartoons, sketch, watermark, text, Logo, advertisement, products"
},
"num_inference_steps": {
"type": "integer",
"title": "Num Inference Steps",
"default": 50,
"maximum": 500,
"minimum": 1,
"x-order": 3,
"description": "Number of denoising steps"
},
"object_fill_percent": {
"enum": [
30,
40,
50,
60,
70,
80,
90,
100
],
"type": "integer",
"title": "object_fill_percent",
"description": "Object fill percentage",
"default": 80,
"x-order": 6
},
"adapter_condition_scale": {
"type": "number",
"title": "Adapter Condition Scale",
"default": 0.8,
"maximum": 1,
"minimum": 0.1,
"x-order": 7,
"description": "Scale for classifier-free guidance"
}
}
}
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"
}