anotherjesse
/
control-paul
this should be same as multi-control but testing different inputs
- Public
- 26 runs
Run anotherjesse/control-paul 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
|
Prompt for the model
|
|
| negative_prompt |
string
|
Longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality
|
Negative prompt
|
| controlnet_1 |
string
(enum)
|
Options: canny, depth, normal, hed, scribble, hough, seg, pose, qr |
Structure of controlnet
|
| controlnet_1_image |
string
|
Control image for controlnet
|
|
| controlnet_1_conditioning_scale |
number
|
override scale for controlnet
|
|
| controlnet_2 |
string
(enum)
|
Options: canny, depth, normal, hed, scribble, hough, seg, pose, qr |
Structure of controlnet
|
| controlnet_2_image |
string
|
Control image for controlnet
|
|
| controlnet_2_conditioning_scale |
number
|
override scale for controlnet
|
|
| controlnet_3 |
string
(enum)
|
Options: canny, depth, normal, hed, scribble, hough, seg, pose, qr |
Structure of controlnet
|
| controlnet_3_image |
string
|
Control image for controlnet
|
|
| controlnet_3_conditioning_scale |
number
|
override scale for controlnet
|
|
| controlnet_4 |
string
(enum)
|
Options: canny, depth, normal, hed, scribble, hough, seg, pose, qr |
Structure of controlnet
|
| controlnet_4_image |
string
|
Control image for controlnet
|
|
| controlnet_4_conditioning_scale |
number
|
override scale for controlnet
|
|
| num_outputs |
integer
|
1
Min: 1 Max: 10 |
Number of images to generate
|
| image_resolution |
integer
(enum)
|
512
Options: 256, 512, 768 |
Resolution of image (smallest dimension)
|
| scheduler |
string
(enum)
|
KerrasDPM
Options: DDIM, DPMSolverMultistep, HeunDiscrete, KerrasDPM, K_EULER_ANCESTRAL, K_EULER, KLMS, PNDM, UniPCMultistep |
Choose a scheduler.
|
| num_inference_steps |
integer
|
20
|
Steps to run denoising
|
| guidance_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
|
| 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
|
| guess_mode |
boolean
|
False
|
In this mode, the ControlNet encoder will try best to recognize the content of the input image even if you remove all prompts. The `guidance_scale` between 3.0 and 5.0 is recommended.
|
| disable_safety_check |
boolean
|
False
|
Disable safety check. Use at your own risk!
|
{
"type": "object",
"title": "Input",
"required": [
"prompt"
],
"properties": {
"eta": {
"type": "number",
"title": "Eta",
"default": 0,
"x-order": 20,
"description": "Controls the amount of noise that is added to the input data during the denoising diffusion process. Higher value -> more noise"
},
"seed": {
"type": "integer",
"title": "Seed",
"x-order": 19,
"description": "Seed"
},
"prompt": {
"type": "string",
"title": "Prompt",
"x-order": 0,
"description": "Prompt for the model"
},
"scheduler": {
"enum": [
"DDIM",
"DPMSolverMultistep",
"HeunDiscrete",
"KerrasDPM",
"K_EULER_ANCESTRAL",
"K_EULER",
"KLMS",
"PNDM",
"UniPCMultistep"
],
"type": "string",
"title": "scheduler",
"description": "Choose a scheduler.",
"default": "KerrasDPM",
"x-order": 16
},
"guess_mode": {
"type": "boolean",
"title": "Guess Mode",
"default": false,
"x-order": 23,
"description": "In this mode, the ControlNet encoder will try best to recognize the content of the input image even if you remove all prompts. The `guidance_scale` between 3.0 and 5.0 is recommended."
},
"num_outputs": {
"type": "integer",
"title": "Num Outputs",
"default": 1,
"maximum": 10,
"minimum": 1,
"x-order": 14,
"description": "Number of images to generate"
},
"controlnet_1": {
"enum": [
"canny",
"depth",
"normal",
"hed",
"scribble",
"hough",
"seg",
"pose",
"qr"
],
"type": "string",
"title": "controlnet_1",
"description": "Structure of controlnet",
"x-order": 2
},
"controlnet_2": {
"enum": [
"canny",
"depth",
"normal",
"hed",
"scribble",
"hough",
"seg",
"pose",
"qr"
],
"type": "string",
"title": "controlnet_2",
"description": "Structure of controlnet",
"x-order": 5
},
"controlnet_3": {
"enum": [
"canny",
"depth",
"normal",
"hed",
"scribble",
"hough",
"seg",
"pose",
"qr"
],
"type": "string",
"title": "controlnet_3",
"description": "Structure of controlnet",
"x-order": 8
},
"controlnet_4": {
"enum": [
"canny",
"depth",
"normal",
"hed",
"scribble",
"hough",
"seg",
"pose",
"qr"
],
"type": "string",
"title": "controlnet_4",
"description": "Structure of controlnet",
"x-order": 11
},
"low_threshold": {
"type": "integer",
"title": "Low Threshold",
"default": 100,
"maximum": 255,
"minimum": 1,
"x-order": 21,
"description": "[canny only] Line detection low threshold`"
},
"guidance_scale": {
"type": "number",
"title": "Guidance Scale",
"default": 9,
"maximum": 30,
"minimum": 0.1,
"x-order": 18,
"description": "Scale for classifier-free guidance"
},
"high_threshold": {
"type": "integer",
"title": "High Threshold",
"default": 200,
"maximum": 255,
"minimum": 1,
"x-order": 22,
"description": "[canny only] Line detection high threshold"
},
"negative_prompt": {
"type": "string",
"title": "Negative Prompt",
"default": "Longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality",
"x-order": 1,
"description": "Negative prompt"
},
"image_resolution": {
"enum": [
256,
512,
768
],
"type": "integer",
"title": "image_resolution",
"description": "Resolution of image (smallest dimension)",
"default": 512,
"x-order": 15
},
"controlnet_1_image": {
"type": "string",
"title": "Controlnet 1 Image",
"format": "uri",
"x-order": 3,
"description": "Control image for controlnet"
},
"controlnet_2_image": {
"type": "string",
"title": "Controlnet 2 Image",
"format": "uri",
"x-order": 6,
"description": "Control image for controlnet"
},
"controlnet_3_image": {
"type": "string",
"title": "Controlnet 3 Image",
"format": "uri",
"x-order": 9,
"description": "Control image for controlnet"
},
"controlnet_4_image": {
"type": "string",
"title": "Controlnet 4 Image",
"format": "uri",
"x-order": 12,
"description": "Control image for controlnet"
},
"num_inference_steps": {
"type": "integer",
"title": "Num Inference Steps",
"default": 20,
"x-order": 17,
"description": "Steps to run denoising"
},
"disable_safety_check": {
"type": "boolean",
"title": "Disable Safety Check",
"default": false,
"x-order": 24,
"description": "Disable safety check. Use at your own risk!"
},
"controlnet_1_conditioning_scale": {
"type": "number",
"title": "Controlnet 1 Conditioning Scale",
"x-order": 4,
"description": "override scale for controlnet"
},
"controlnet_2_conditioning_scale": {
"type": "number",
"title": "Controlnet 2 Conditioning Scale",
"x-order": 7,
"description": "override scale for controlnet"
},
"controlnet_3_conditioning_scale": {
"type": "number",
"title": "Controlnet 3 Conditioning Scale",
"x-order": 10,
"description": "override scale for controlnet"
},
"controlnet_4_conditioning_scale": {
"type": "number",
"title": "Controlnet 4 Conditioning Scale",
"x-order": 13,
"description": "override scale for controlnet"
}
}
}
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"
}