You're looking at a specific version of this model. Jump to the model overview.
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 |
|---|---|---|---|
| model_name |
string
(enum)
|
SUPIR-v0Q
Options: SUPIR-v0Q, SUPIR-v0F |
Choose a model. SUPIR-v0Q is the default training settings with paper. SUPIR-v0F is high generalization and high image quality in most cases. Training with light degradation settings. Stage1 encoder of SUPIR-v0F remains more details when facing light degradations.
|
| image |
string
|
Low quality input image.
|
|
| upscale |
integer
|
1
|
Upsampling ratio of given inputs.
|
| min_size |
number
|
1024
|
Minimum resolution of output images.
|
| edm_steps |
integer
|
50
Min: 1 Max: 500 |
Number of steps for EDM Sampling Schedule.
|
| use_llava |
boolean
|
True
|
Use LLaVA model to get captions.
|
| a_prompt |
string
|
Cinematic, High Contrast, highly detailed, taken using a Canon EOS R camera, hyper detailed photo - realistic maximum detail, 32k, Color Grading, ultra HD, extreme meticulous detailing, skin pore detailing, hyper sharpness, perfect without deformations.
|
Additive positive prompt for the inputs.
|
| n_prompt |
string
|
painting, oil painting, illustration, drawing, art, sketch, oil painting, cartoon, CG Style, 3D render, unreal engine, blurring, dirty, messy, worst quality, low quality, frames, watermark, signature, jpeg artifacts, deformed, lowres, over-smooth
|
Negative prompt for the inputs.
|
| color_fix_type |
string
(enum)
|
Wavelet
Options: None, AdaIn, Wavelet |
Color Fixing Type..
|
| s_stage1 |
integer
|
-1
|
Control Strength of Stage1 (negative means invalid).
|
| s_churn |
number
|
5
|
Original churn hy-param of EDM.
|
| s_noise |
number
|
1.003
|
Original noise hy-param of EDM.
|
| s_cfg |
number
|
7.5
Min: 1 Max: 20 |
Classifier-free guidance scale for prompts.
|
| s_stage2 |
number
|
1
|
Control Strength of Stage2.
|
| linear_CFG |
boolean
|
False
|
Linearly (with sigma) increase CFG from 'spt_linear_CFG' to s_cfg.
|
| linear_s_stage2 |
boolean
|
False
|
Linearly (with sigma) increase s_stage2 from 'spt_linear_s_stage2' to s_stage2.
|
| spt_linear_CFG |
number
|
1
|
Start point of linearly increasing CFG.
|
| spt_linear_s_stage2 |
number
|
0
|
Start point of linearly increasing s_stage2.
|
| seed |
integer
|
Random seed. Leave blank to randomize the seed
|
Output schema
The shape of the response you’ll get when you run this model with an API.
Schema
{'format': 'uri', 'title': 'Output', 'type': 'string'}