arunarupa
/
instantid-image-size-increase
Same instant model multricontrolnet that already existed just with the 1024px limit removed when using a reference image
- Public
- 738 runs
Run arunarupa/instantid-image-size-increase 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 face image
|
|
| pose_image |
string
|
(Optional) reference pose image
|
|
| prompt |
string
|
a person
|
Input prompt
|
| negative_prompt |
string
|
|
Input Negative Prompt
|
| sdxl_weights |
string
(enum)
|
stable-diffusion-xl-base-1.0
Options: stable-diffusion-xl-base-1.0, juggernaut-xl-v8, afrodite-xl-v2, albedobase-xl-20, albedobase-xl-v13, animagine-xl-30, anime-art-diffusion-xl, anime-illust-diffusion-xl, dreamshaper-xl, dynavision-xl-v0610, guofeng4-xl, nightvision-xl-0791, omnigen-xl, pony-diffusion-v6-xl, protovision-xl-high-fidel, RealVisXL_V3.0_Turbo, RealVisXL_V4.0_Lightning |
Pick which base weights you want to use
|
| scheduler |
string
(enum)
|
EulerDiscreteScheduler
Options: DEISMultistepScheduler, HeunDiscreteScheduler, EulerDiscreteScheduler, DPMSolverMultistepScheduler, DPMSolverMultistepScheduler-Karras, DPMSolverMultistepScheduler-Karras-SDE |
Scheduler
|
| max_side_input |
integer
|
Height of the output if reference picture is used
|
|
| num_inference_steps |
integer
|
30
Min: 1 Max: 500 |
Number of denoising steps
|
| guidance_scale |
number
|
7.5
Min: 1 Max: 50 |
Scale for classifier-free guidance
|
| ip_adapter_scale |
number
|
0.8
Max: 1.5 |
Scale for image adapter strength (for detail)
|
| controlnet_conditioning_scale |
number
|
0.8
Max: 1.5 |
Scale for IdentityNet strength (for fidelity)
|
| enable_pose_controlnet |
boolean
|
True
|
Enable Openpose ControlNet, overrides strength if set to false
|
| pose_strength |
number
|
0.4
Max: 1 |
Openpose ControlNet strength, effective only if `enable_pose_controlnet` is true
|
| enable_canny_controlnet |
boolean
|
False
|
Enable Canny ControlNet, overrides strength if set to false
|
| canny_strength |
number
|
0.3
Max: 1 |
Canny ControlNet strength, effective only if `enable_canny_controlnet` is true
|
| enable_depth_controlnet |
boolean
|
False
|
Enable Depth ControlNet, overrides strength if set to false
|
| depth_strength |
number
|
0.5
Max: 1 |
Depth ControlNet strength, effective only if `enable_depth_controlnet` is true
|
| enable_lcm |
boolean
|
False
|
Enable Fast Inference with LCM (Latent Consistency Models) - speeds up inference steps, trade-off is the quality of the generated image. Performs better with close-up portrait face images
|
| lcm_num_inference_steps |
integer
|
5
Min: 1 Max: 10 |
Only used when `enable_lcm` is set to True, Number of denoising steps when using LCM
|
| lcm_guidance_scale |
number
|
1.5
Min: 1 Max: 20 |
Only used when `enable_lcm` is set to True, Scale for classifier-free guidance when using LCM
|
| enhance_nonface_region |
boolean
|
True
|
Enhance non-face region
|
| output_format |
string
(enum)
|
webp
Options: webp, jpg, png |
Format of the output images
|
| output_quality |
integer
|
80
Max: 100 |
Quality of the output images, from 0 to 100. 100 is best quality, 0 is lowest quality.
|
| seed |
integer
|
Random seed. Leave blank to randomize the seed
|
|
| num_outputs |
integer
|
1
Min: 1 Max: 8 |
Number of images to output
|
| disable_safety_checker |
boolean
|
False
|
Disable safety checker for generated images
|
{
"type": "object",
"title": "Input",
"required": [
"image"
],
"properties": {
"seed": {
"type": "integer",
"title": "Seed",
"x-order": 23,
"description": "Random seed. Leave blank to randomize the seed"
},
"image": {
"type": "string",
"title": "Image",
"format": "uri",
"x-order": 0,
"description": "Input face image"
},
"prompt": {
"type": "string",
"title": "Prompt",
"default": "a person",
"x-order": 2,
"description": "Input prompt"
},
"scheduler": {
"enum": [
"DEISMultistepScheduler",
"HeunDiscreteScheduler",
"EulerDiscreteScheduler",
"DPMSolverMultistepScheduler",
"DPMSolverMultistepScheduler-Karras",
"DPMSolverMultistepScheduler-Karras-SDE"
],
"type": "string",
"title": "scheduler",
"description": "Scheduler",
"default": "EulerDiscreteScheduler",
"x-order": 5
},
"enable_lcm": {
"type": "boolean",
"title": "Enable Lcm",
"default": false,
"x-order": 17,
"description": "Enable Fast Inference with LCM (Latent Consistency Models) - speeds up inference steps, trade-off is the quality of the generated image. Performs better with close-up portrait face images"
},
"pose_image": {
"type": "string",
"title": "Pose Image",
"format": "uri",
"x-order": 1,
"description": "(Optional) reference pose image"
},
"num_outputs": {
"type": "integer",
"title": "Num Outputs",
"default": 1,
"maximum": 8,
"minimum": 1,
"x-order": 24,
"description": "Number of images to output"
},
"sdxl_weights": {
"enum": [
"stable-diffusion-xl-base-1.0",
"juggernaut-xl-v8",
"afrodite-xl-v2",
"albedobase-xl-20",
"albedobase-xl-v13",
"animagine-xl-30",
"anime-art-diffusion-xl",
"anime-illust-diffusion-xl",
"dreamshaper-xl",
"dynavision-xl-v0610",
"guofeng4-xl",
"nightvision-xl-0791",
"omnigen-xl",
"pony-diffusion-v6-xl",
"protovision-xl-high-fidel",
"RealVisXL_V3.0_Turbo",
"RealVisXL_V4.0_Lightning"
],
"type": "string",
"title": "sdxl_weights",
"description": "Pick which base weights you want to use",
"default": "stable-diffusion-xl-base-1.0",
"x-order": 4
},
"output_format": {
"enum": [
"webp",
"jpg",
"png"
],
"type": "string",
"title": "output_format",
"description": "Format of the output images",
"default": "webp",
"x-order": 21
},
"pose_strength": {
"type": "number",
"title": "Pose Strength",
"default": 0.4,
"maximum": 1,
"minimum": 0,
"x-order": 12,
"description": "Openpose ControlNet strength, effective only if `enable_pose_controlnet` is true"
},
"canny_strength": {
"type": "number",
"title": "Canny Strength",
"default": 0.3,
"maximum": 1,
"minimum": 0,
"x-order": 14,
"description": "Canny ControlNet strength, effective only if `enable_canny_controlnet` is true"
},
"depth_strength": {
"type": "number",
"title": "Depth Strength",
"default": 0.5,
"maximum": 1,
"minimum": 0,
"x-order": 16,
"description": "Depth ControlNet strength, effective only if `enable_depth_controlnet` is true"
},
"guidance_scale": {
"type": "number",
"title": "Guidance Scale",
"default": 7.5,
"maximum": 50,
"minimum": 1,
"x-order": 8,
"description": "Scale for classifier-free guidance"
},
"max_side_input": {
"type": "integer",
"title": "Max Side Input",
"x-order": 6,
"description": "Height of the output if reference picture is used"
},
"output_quality": {
"type": "integer",
"title": "Output Quality",
"default": 80,
"maximum": 100,
"minimum": 0,
"x-order": 22,
"description": "Quality of the output images, from 0 to 100. 100 is best quality, 0 is lowest quality."
},
"negative_prompt": {
"type": "string",
"title": "Negative Prompt",
"default": "",
"x-order": 3,
"description": "Input Negative Prompt"
},
"ip_adapter_scale": {
"type": "number",
"title": "Ip Adapter Scale",
"default": 0.8,
"maximum": 1.5,
"minimum": 0,
"x-order": 9,
"description": "Scale for image adapter strength (for detail)"
},
"lcm_guidance_scale": {
"type": "number",
"title": "Lcm Guidance Scale",
"default": 1.5,
"maximum": 20,
"minimum": 1,
"x-order": 19,
"description": "Only used when `enable_lcm` is set to True, Scale for classifier-free guidance when using LCM"
},
"num_inference_steps": {
"type": "integer",
"title": "Num Inference Steps",
"default": 30,
"maximum": 500,
"minimum": 1,
"x-order": 7,
"description": "Number of denoising steps"
},
"disable_safety_checker": {
"type": "boolean",
"title": "Disable Safety Checker",
"default": false,
"x-order": 25,
"description": "Disable safety checker for generated images"
},
"enable_pose_controlnet": {
"type": "boolean",
"title": "Enable Pose Controlnet",
"default": true,
"x-order": 11,
"description": "Enable Openpose ControlNet, overrides strength if set to false"
},
"enhance_nonface_region": {
"type": "boolean",
"title": "Enhance Nonface Region",
"default": true,
"x-order": 20,
"description": "Enhance non-face region"
},
"enable_canny_controlnet": {
"type": "boolean",
"title": "Enable Canny Controlnet",
"default": false,
"x-order": 13,
"description": "Enable Canny ControlNet, overrides strength if set to false"
},
"enable_depth_controlnet": {
"type": "boolean",
"title": "Enable Depth Controlnet",
"default": false,
"x-order": 15,
"description": "Enable Depth ControlNet, overrides strength if set to false"
},
"lcm_num_inference_steps": {
"type": "integer",
"title": "Lcm Num Inference Steps",
"default": 5,
"maximum": 10,
"minimum": 1,
"x-order": 18,
"description": "Only used when `enable_lcm` is set to True, Number of denoising steps when using LCM"
},
"controlnet_conditioning_scale": {
"type": "number",
"title": "Controlnet Conditioning Scale",
"default": 0.8,
"maximum": 1.5,
"minimum": 0,
"x-order": 10,
"description": "Scale for IdentityNet strength (for fidelity)"
}
}
}
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"
}