fermatresearch / magic-image-refiner

A better alternative to SDXL refiners, providing a lot of quality and detail. Can also be used for inpainting or upscaling.

  • Public
  • 926.4K runs
  • L40S
  • GitHub

Input

string
Shift + Return to add a new line

Prompt for the model

file
Preview
image

Image to refine

file

When provided, refines some section of the image. Must be the same size as the image

string

Image resolution

Default: "original"

number
(minimum: 0, maximum: 1)

Conditioning scale for controlnet

Default: 0.75

number
(minimum: 0, maximum: 1)

Denoising strength. 1 means total destruction of the original image

Default: 0.25

number
(minimum: 0, maximum: 1)

HDR improvement over the original image

Default: 0

string

Choose a scheduler.

Default: "DDIM"

integer

Steps

Default: 20

number
(minimum: 0.1, maximum: 30)

Scale for classifier-free guidance

Default: 7

integer

Seed

string
Shift + Return to add a new line

Negative prompt

Default: "teeth, tooth, open mouth, longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, mutant"

boolean

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.

Default: false

Output

We were unable to load these images. Please make sure the URLs are valid.

{
  "input": "https://replicate.delivery/pbxt/KA9yP9n3ZX5A5mkoPz3gsPzKTH1NA7LqVkQRTg7Sov46lOfo/0_1.webp",
  "outut": "https://replicate.delivery/pbxt/H3ZmqoAgsBonKFilPafiEsvYsc2FnjD8EW3vMt6KpkYfd0ISA/out-0.png"
}
Generated in

This example was created by a different version, fermatresearch/magic-image-refiner:3064c8a3.

Run time and cost

This model costs approximately $0.020 to run on Replicate, or 50 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker.

This model runs on Nvidia L40S GPU hardware. Predictions typically complete within 21 seconds. The predict time for this model varies significantly based on the inputs.

Readme

This model doesn't have a readme.