garg-aayush
/
clarity-upscaler
- Public
- 1 run
Run garg-aayush/clarity-upscaler 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
|
|
| prompt |
string
|
masterpiece, best quality, highres, <lora:more_details:0.5> <lora:SDXLrender_v2.0:1>
|
Prompt
|
| negative_prompt |
string
|
(worst quality, low quality, normal quality:2) JuggernautNegative-neg
|
Negative Prompt
|
| scale_factor |
number
|
2
|
Scale factor
|
| dynamic |
number
|
6
Min: 1 Max: 50 |
HDR, try from 3 - 9
|
| creativity |
number
|
0.35
Max: 1 |
Creativity, try from 0.3 - 0.9
|
| resemblance |
number
|
0.6
Max: 3 |
Resemblance, try from 0.3 - 1.6
|
| tiling_width |
integer
(enum)
|
112
Options: 16, 32, 48, 64, 80, 96, 112, 128, 144, 160, 176, 192, 208, 224, 240, 256 |
Fractality, set lower tile width for a high Fractality
|
| tiling_height |
integer
(enum)
|
144
Options: 16, 32, 48, 64, 80, 96, 112, 128, 144, 160, 176, 192, 208, 224, 240, 256 |
Fractality, set lower tile height for a high Fractality
|
| sd_model |
string
(enum)
|
juggernaut_reborn.safetensors [338b85bc4f]
Options: epicrealism_naturalSinRC1VAE.safetensors [84d76a0328], juggernaut_reborn.safetensors [338b85bc4f], flat2DAnimerge_v45Sharp.safetensors |
Stable Diffusion model checkpoint
|
| scheduler |
string
(enum)
|
DPM++ 3M SDE Karras
Options: DPM++ 2M Karras, DPM++ SDE Karras, DPM++ 2M SDE Exponential, DPM++ 2M SDE Karras, Euler a, Euler, LMS, Heun, DPM2, DPM2 a, DPM++ 2S a, DPM++ 2M, DPM++ SDE, DPM++ 2M SDE, DPM++ 2M SDE Heun, DPM++ 2M SDE Heun Karras, DPM++ 2M SDE Heun Exponential, DPM++ 3M SDE, DPM++ 3M SDE Karras, DPM++ 3M SDE Exponential, DPM fast, DPM adaptive, LMS Karras, DPM2 Karras, DPM2 a Karras, DPM++ 2S a Karras, Restart, DDIM, PLMS, UniPC |
scheduler
|
| num_inference_steps |
integer
|
18
Min: 1 Max: 100 |
Number of denoising steps
|
| seed |
integer
|
1337
|
Random seed. Leave blank to randomize the seed
|
| multistep_factor |
number
|
0.8
Max: 2 |
Multiplier for the number of denoising steps. 0.9 for 90% less steps, 1.1 for 10% more steps
|
| downscaling |
boolean
|
False
|
Downscale the image before upscaling. Can improve quality and speed for images with high resolution but lower quality
|
| downscaling_resolution |
integer
|
768
|
Downscaling resolution
|
| lora_links |
string
|
|
Link to a lora file you want to use in your upscaling. Multiple links possible, seperated by comma
|
| custom_sd_model |
string
|
|
None
|
| sharpen |
number
|
0
Max: 10 |
Sharpen the image after upscaling. The higher the value, the more sharpening is applied. 0 for no sharpening
|
| mask |
string
|
Mask image to mark areas that should be preserved during upscaling
|
|
| handfix |
string
(enum)
|
disabled
Options: disabled, hands_only, image_and_hands |
Use clarity to fix hands in the image
|
| pattern |
boolean
|
False
|
Upscale a pattern with seamless tiling
|
| output_format |
string
(enum)
|
png
Options: webp, jpg, png |
Format of the output images
|
{
"type": "object",
"title": "Input",
"required": [
"image"
],
"properties": {
"mask": {
"type": "string",
"title": "Mask",
"format": "uri",
"x-order": 19,
"description": "Mask image to mark areas that should be preserved during upscaling"
},
"seed": {
"type": "integer",
"title": "Seed",
"default": 1337,
"x-order": 12,
"description": "Random seed. Leave blank to randomize the seed"
},
"image": {
"type": "string",
"title": "Image",
"format": "uri",
"x-order": 0,
"description": "input image"
},
"prompt": {
"type": "string",
"title": "Prompt",
"default": "masterpiece, best quality, highres, <lora:more_details:0.5> <lora:SDXLrender_v2.0:1>",
"x-order": 1,
"description": "Prompt"
},
"dynamic": {
"type": "number",
"title": "Dynamic",
"default": 6,
"maximum": 50,
"minimum": 1,
"x-order": 4,
"description": "HDR, try from 3 - 9"
},
"handfix": {
"enum": [
"disabled",
"hands_only",
"image_and_hands"
],
"type": "string",
"title": "handfix",
"description": "Use clarity to fix hands in the image",
"default": "disabled",
"x-order": 20
},
"pattern": {
"type": "boolean",
"title": "Pattern",
"default": false,
"x-order": 21,
"description": "Upscale a pattern with seamless tiling"
},
"sharpen": {
"type": "number",
"title": "Sharpen",
"default": 0,
"maximum": 10,
"minimum": 0,
"x-order": 18,
"description": "Sharpen the image after upscaling. The higher the value, the more sharpening is applied. 0 for no sharpening"
},
"sd_model": {
"enum": [
"epicrealism_naturalSinRC1VAE.safetensors [84d76a0328]",
"juggernaut_reborn.safetensors [338b85bc4f]",
"flat2DAnimerge_v45Sharp.safetensors"
],
"type": "string",
"title": "sd_model",
"description": "Stable Diffusion model checkpoint",
"default": "juggernaut_reborn.safetensors [338b85bc4f]",
"x-order": 9
},
"scheduler": {
"enum": [
"DPM++ 2M Karras",
"DPM++ SDE Karras",
"DPM++ 2M SDE Exponential",
"DPM++ 2M SDE Karras",
"Euler a",
"Euler",
"LMS",
"Heun",
"DPM2",
"DPM2 a",
"DPM++ 2S a",
"DPM++ 2M",
"DPM++ SDE",
"DPM++ 2M SDE",
"DPM++ 2M SDE Heun",
"DPM++ 2M SDE Heun Karras",
"DPM++ 2M SDE Heun Exponential",
"DPM++ 3M SDE",
"DPM++ 3M SDE Karras",
"DPM++ 3M SDE Exponential",
"DPM fast",
"DPM adaptive",
"LMS Karras",
"DPM2 Karras",
"DPM2 a Karras",
"DPM++ 2S a Karras",
"Restart",
"DDIM",
"PLMS",
"UniPC"
],
"type": "string",
"title": "scheduler",
"description": "scheduler",
"default": "DPM++ 3M SDE Karras",
"x-order": 10
},
"creativity": {
"type": "number",
"title": "Creativity",
"default": 0.35,
"maximum": 1,
"minimum": 0,
"x-order": 5,
"description": "Creativity, try from 0.3 - 0.9"
},
"lora_links": {
"type": "string",
"title": "Lora Links",
"default": "",
"x-order": 16,
"description": "Link to a lora file you want to use in your upscaling. Multiple links possible, seperated by comma"
},
"downscaling": {
"type": "boolean",
"title": "Downscaling",
"default": false,
"x-order": 14,
"description": "Downscale the image before upscaling. Can improve quality and speed for images with high resolution but lower quality"
},
"resemblance": {
"type": "number",
"title": "Resemblance",
"default": 0.6,
"maximum": 3,
"minimum": 0,
"x-order": 6,
"description": "Resemblance, try from 0.3 - 1.6"
},
"scale_factor": {
"type": "number",
"title": "Scale Factor",
"default": 2,
"x-order": 3,
"description": "Scale factor"
},
"tiling_width": {
"enum": [
16,
32,
48,
64,
80,
96,
112,
128,
144,
160,
176,
192,
208,
224,
240,
256
],
"type": "integer",
"title": "tiling_width",
"description": "Fractality, set lower tile width for a high Fractality",
"default": 112,
"x-order": 7
},
"output_format": {
"enum": [
"webp",
"jpg",
"png"
],
"type": "string",
"title": "output_format",
"description": "Format of the output images",
"default": "png",
"x-order": 22
},
"tiling_height": {
"enum": [
16,
32,
48,
64,
80,
96,
112,
128,
144,
160,
176,
192,
208,
224,
240,
256
],
"type": "integer",
"title": "tiling_height",
"description": "Fractality, set lower tile height for a high Fractality",
"default": 144,
"x-order": 8
},
"custom_sd_model": {
"type": "string",
"title": "Custom Sd Model",
"default": "",
"x-order": 17
},
"negative_prompt": {
"type": "string",
"title": "Negative Prompt",
"default": "(worst quality, low quality, normal quality:2) JuggernautNegative-neg",
"x-order": 2,
"description": "Negative Prompt"
},
"multistep_factor": {
"type": "number",
"title": "Multistep Factor",
"default": 0.8,
"maximum": 2,
"minimum": 0,
"x-order": 13,
"description": "Multiplier for the number of denoising steps. 0.9 for 90% less steps, 1.1 for 10% more steps"
},
"num_inference_steps": {
"type": "integer",
"title": "Num Inference Steps",
"default": 18,
"maximum": 100,
"minimum": 1,
"x-order": 11,
"description": "Number of denoising steps"
},
"downscaling_resolution": {
"type": "integer",
"title": "Downscaling Resolution",
"default": 768,
"x-order": 15,
"description": "Downscaling resolution"
}
}
}
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"
}