batouresearch / magic-style-transfer

Restyle an image with the style of another one. I strongly suggest to upscale the results with Clarity AI

  • Public
  • 29.1K runs
  • L40S
  • GitHub

Input

string
Shift + Return to add a new line

Input prompt

Default: "An astronaut riding a rainbow unicorn"

file
Preview
image

Input image

file
Preview
ip_image

Input image for img2img or inpaint mode

number
(minimum: 0, maximum: 2)

The bigger this number is, the more ControlNet interferes

Default: 0.35

number
(minimum: 0, maximum: 2)

The bigger this number is, the more ControlNet interferes

Default: 0.15

number
(minimum: 0, maximum: 1)

LoRA additive scale. Only applicable on trained models.

Default: 0.9

number
(minimum: 0, maximum: 1)

IP Adapter strength.

Default: 0.3

number
(minimum: 0, maximum: 1)

When img2img is active, the denoising strength. 1 means total destruction of the input image.

Default: 0.9

string
Shift + Return to add a new line

Input Negative Prompt

Default: ""

string
Shift + Return to add a new line

When passing an image with alpha channel, it will be replaced with this color

Default: "#A2A2A2"

number
(minimum: 1, maximum: 10)

If you want the image to have a solid margin. Scale of the solid margin. 1.0 means no resizing.

Default: 1

integer
(minimum: 1, maximum: 500)

Number of denoising steps

Default: 30

integer
(minimum: 1, maximum: 4)

Number of images to output

Default: 1

string

scheduler

Default: "K_EULER"

number
(minimum: 1, maximum: 50)

Scale for classifier-free guidance

Default: 4

integer

Random seed. Leave blank to randomize the seed

boolean

Applies a watermark to enable determining if an image is generated in downstream applications. If you have other provisions for generating or deploying images safely, you can use this to disable watermarking.

Default: true

string
Shift + Return to add a new line

Replicate LoRA weights to use. Leave blank to use the default weights.

Output

output
Generated in

Run time and cost

This model costs approximately $0.010 to run on Replicate, or 100 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 11 seconds. The predict time for this model varies significantly based on the inputs.

Readme

This model doesn't have a readme.