zedge/pulid
Public
2.5M
runs
Run zedge/pulid 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
|
ID image (main)
|
|
| prompt |
string
|
man sportrait,cinematic,in garden,soft light
|
Prompt
|
| negative_prompt |
string
|
flaws in the eyes, flaws in the face, flaws, lowres, non-HDRi, low quality, worst quality,artifacts noise, text, watermark, glitch, deformed, mutated, ugly, disfigured, low resolution, partially rendered objects, deformed or partially rendered eyes, deformed, deformed eyeballs, cross-eyed, blurry
|
Negative Prompt
|
| guidance_scale |
number
|
1.2
Min: 1 Max: 1.5 |
CFG, recommend value range [1, 1.5], 1 will be faster
|
| num_steps |
integer
|
4
Min: 1 Max: 100 |
Steps
|
| identity_scale |
number
|
0.8
Max: 5 |
ID scale
|
| generation_mode |
None
|
fidelity
|
mode
|
| img2img_canny_strength |
number
|
0.1
Max: 1 |
ONLY FOR 0 or 2+ FACES: Canny ControlNet strength, effective only if > 0
|
| img2img_depth_strength |
number
|
0.7
Max: 1 |
ONLY FOR 0 or 2+ FACES: Depth ControlNet strength, effective only if > 0
|
| seed |
integer
|
Random seed. Leave blank to randomize the seed
|
|
| num_samples |
integer
|
1
Min: 1 Max: 4 |
Num samples
|
| input_zip |
string
|
ZIP file containing input images.
|
|
| megapixel_count |
number
|
1
|
Megapixel count for image downscaling. 1024x1024 resolution is equal to 1 megapixel
|
| disable_nsfw_checker |
boolean
|
False
|
Disable safety checker for generated images.
|
| verbose |
boolean
|
False
|
Print detailed timing information
|
| debug_images |
boolean
|
False
|
(PARAMETER ONLY RELEVANT IN DEVELOPMENT) Save debug images
|
| force_clip |
boolean
|
False
|
Force using CLIP for captioning
|
| warm_delay |
integer
|
Parameter for warming the model. If set, returns empty dict after specified seconds
|
{
"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": "man sportrait,cinematic,in garden,soft light",
"x-order": 1,
"description": "Prompt"
},
"verbose": {
"type": "boolean",
"title": "Verbose",
"default": false,
"x-order": 14,
"description": "Print detailed timing information"
},
"input_zip": {
"type": "string",
"title": "Input Zip",
"format": "uri",
"x-order": 11,
"description": "ZIP file containing input images."
},
"num_steps": {
"type": "integer",
"title": "Num Steps",
"default": 4,
"maximum": 100,
"minimum": 1,
"x-order": 4,
"description": "Steps"
},
"force_clip": {
"type": "boolean",
"title": "Force Clip",
"default": false,
"x-order": 16,
"description": "Force using CLIP for captioning"
},
"warm_delay": {
"type": "integer",
"title": "Warm Delay",
"x-order": 17,
"description": "Parameter for warming the model. If set, returns empty dict after specified seconds"
},
"input_image": {
"type": "string",
"title": "Input Image",
"format": "uri",
"x-order": 0,
"description": "ID image (main)"
},
"num_samples": {
"type": "integer",
"title": "Num Samples",
"default": 1,
"maximum": 4,
"minimum": 1,
"x-order": 10,
"description": "Num samples"
},
"debug_images": {
"type": "boolean",
"title": "Debug Images",
"default": false,
"x-order": 15,
"description": "(PARAMETER ONLY RELEVANT IN DEVELOPMENT) Save debug images"
},
"guidance_scale": {
"type": "number",
"title": "Guidance Scale",
"default": 1.2,
"maximum": 1.5,
"minimum": 1,
"x-order": 3,
"description": "CFG, recommend value range [1, 1.5], 1 will be faster"
},
"identity_scale": {
"type": "number",
"title": "Identity Scale",
"default": 0.8,
"maximum": 5,
"minimum": 0,
"x-order": 5,
"description": "ID scale"
},
"generation_mode": {
"enum": [
"fidelity",
"extremely style"
],
"type": "string",
"title": "generation_mode",
"description": "mode",
"default": "fidelity",
"x-order": 6
},
"megapixel_count": {
"type": "number",
"title": "Megapixel Count",
"default": 1,
"x-order": 12,
"description": "Megapixel count for image downscaling. 1024x1024 resolution is equal to 1 megapixel"
},
"negative_prompt": {
"type": "string",
"title": "Negative Prompt",
"default": "flaws in the eyes, flaws in the face, flaws, lowres, non-HDRi, low quality, worst quality,artifacts noise, text, watermark, glitch, deformed, mutated, ugly, disfigured, low resolution, partially rendered objects, deformed or partially rendered eyes, deformed, deformed eyeballs, cross-eyed, blurry",
"x-order": 2,
"description": "Negative Prompt"
},
"disable_nsfw_checker": {
"type": "boolean",
"title": "Disable Nsfw Checker",
"default": false,
"x-order": 13,
"description": "Disable safety checker for generated images."
},
"img2img_canny_strength": {
"type": "number",
"title": "Img2Img Canny Strength",
"default": 0.1,
"maximum": 1,
"minimum": 0,
"x-order": 7,
"description": "ONLY FOR 0 or 2+ FACES: Canny ControlNet strength, effective only if > 0"
},
"img2img_depth_strength": {
"type": "number",
"title": "Img2Img Depth Strength",
"default": 0.7,
"maximum": 1,
"minimum": 0,
"x-order": 8,
"description": "ONLY FOR 0 or 2+ FACES: Depth ControlNet strength, effective only if > 0"
}
}
}
Output schema
The shape of the response you’ll get when you run this model with an API.
Schema
{
"type": "object",
"title": "Output"
}