usamaehsan / multi-controlnet-x-consistency-decoder-x-realestic-vision-v5

Multi-Controlnet + consistency-decoder + INPAINTING + realestic-vision-v5 + Prompt-Weight + Single-Controlnet

  • Public
  • 3.4K runs
  • L40S
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Input

*string
Shift + Return to add a new line
file
Preview
lineart_image

Control image for canny controlnet

number

Conditioning scale for canny controlnet

Default: 1

file

Control image for tile controlnet

number

Conditioning scale for tile controlnet

Default: 1

file

Control image for brightness controlnet

number

Conditioning scale for brightness controlnet

Default: 1

file

Control image for inpainting controlnet

file

mask image for inpainting controlnet

number

Conditioning scale for brightness controlnet

Default: 1

integer
(minimum: 1, maximum: 10)

Number of images to generate

Default: 1

integer

Max width/Resolution of image

Default: 512

integer

Max height/Resolution of image

Default: 512

string

Choose a scheduler.

Default: "DDIM"

integer

Steps to run denoising

Default: 20

number
(minimum: 0.1, maximum: 30)

Scale for classifier-free guidance

Default: 7

integer

Seed

number

Controls the amount of noise that is added to the input data during the denoising diffusion process. Higher value -> more noise

Default: 0

string
Shift + Return to add a new line

Negative prompt - using compel, use +++ to increase words weight

Default: "Longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality"

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

boolean

Disable safety check. Use at your own risk!

Default: false

string
Shift + Return to add a new line

Comma seperated string of controlnet names, list of names: tile, inpainting, lineart,depth ,scribble , brightness /// example value: tile, inpainting, lineart

Default: "tile, inpainting, lineart"

boolean

Using controlnet tile- after image generation

Default: false

integer

controlnet tile resolution- after image generation

Default: 768

integer

controlnet tile resolution- after image generation

Default: 10

string
Shift + Return to add a new line

Default: "best quality"

string
Shift + Return to add a new line

Default: "blur, lowres, bad anatomy, bad hands, cropped, worst quality"

boolean

low res fix - guess mode

Default: false

number

Default: 1

Output

Generated in

This output was created using a different version of the model, usamaehsan/multi-controlnet-x-consistency-decoder-x-realestic-vision-v5:59c1f5ce.

Run time and cost

This model costs approximately $0.0099 to run on Replicate, or 101 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

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