meepo-pro-player
/
tt-hoodwink-big
- Public
- 242 runs
Run meepo-pro-player/tt-hoodwink-big 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 |
|---|---|---|---|
| image |
string
|
Input image
|
|
| mask_image |
string
|
Input mask, need to be RGB(255, 255, 255) = filled mask
|
|
| prompt |
string
|
Prompt for the model
|
|
| n_prompt |
string
|
|
Negative prompt for the model
|
| num_images_per_prompt |
integer
|
1
|
Number of images to generate
|
| seed |
integer
|
Seed
|
|
| num_inference_steps |
integer
|
25
|
Num inference steps
|
| controlnet_conditioning_scale |
number
|
1
Max: 1 |
control scale
|
| control_guidance_start |
number
|
0
Max: 1 |
Controlnet guidance start
|
| control_guidance_end |
number
|
1
Max: 1 |
Controlnet guidance end
|
| guidance_scale |
number
|
7
|
Style guidance scale
|
| controlnet |
string
(enum)
|
depth
Options: depth, canny |
Controlnet type
|
{
"type": "object",
"title": "Input",
"required": [
"image",
"mask_image",
"prompt"
],
"properties": {
"seed": {
"type": "integer",
"title": "Seed",
"x-order": 5,
"description": "Seed"
},
"image": {
"type": "string",
"title": "Image",
"format": "uri",
"x-order": 0,
"description": "Input image"
},
"prompt": {
"type": "string",
"title": "Prompt",
"x-order": 2,
"description": "Prompt for the model"
},
"n_prompt": {
"type": "string",
"title": "N Prompt",
"default": "",
"x-order": 3,
"description": "Negative prompt for the model"
},
"controlnet": {
"enum": [
"depth",
"canny"
],
"type": "string",
"title": "controlnet",
"description": "Controlnet type",
"default": "depth",
"x-order": 11
},
"mask_image": {
"type": "string",
"title": "Mask Image",
"format": "uri",
"x-order": 1,
"description": "Input mask, need to be RGB(255, 255, 255) = filled mask"
},
"guidance_scale": {
"type": "number",
"title": "Guidance Scale",
"default": 7,
"x-order": 10,
"description": "Style guidance scale"
},
"num_inference_steps": {
"type": "integer",
"title": "Num Inference Steps",
"default": 25,
"x-order": 6,
"description": "Num inference steps"
},
"control_guidance_end": {
"type": "number",
"title": "Control Guidance End",
"default": 1,
"maximum": 1,
"minimum": 0,
"x-order": 9,
"description": "Controlnet guidance end"
},
"num_images_per_prompt": {
"type": "integer",
"title": "Num Images Per Prompt",
"default": 1,
"x-order": 4,
"description": "Number of images to generate"
},
"control_guidance_start": {
"type": "number",
"title": "Control Guidance Start",
"default": 0,
"maximum": 1,
"minimum": 0,
"x-order": 8,
"description": "Controlnet guidance start"
},
"controlnet_conditioning_scale": {
"type": "number",
"title": "Controlnet Conditioning Scale",
"default": 1,
"maximum": 1,
"minimum": 0,
"x-order": 7,
"description": "control scale"
}
}
}
Output schema
The shape of the response you’ll get when you run this model with an API.
Schema
{
"type": "array",
"items": {
"type": "string",
"format": "uri"
},
"title": "Output"
}