replicategithubwc/nightvision-sdxl

replicategithubwc / nightvision-sdxl

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13.3K runs

Run replicategithubwc/nightvision-sdxl 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
prompt	string	a photo of an astronaut riding a horse on mars	Input prompt
negative_prompt	string		Specify things to not see in the output
image_prompt	string		Input image prompt for image_prompt mode
image	string		Input image for img2img or inpaint mode
mask	string		Input mask for inpaint mode. Black areas will be preserved, white areas will be inpainted.
width	integer	1024	Width of output image
height	integer	1024	Height of output image
num_outputs	integer	1 Min: 1 Max: 4	Number of images to output.
num_inference_steps	integer	50 Min: 1 Max: 500	Number of denoising steps
guidance_scale	number	7.5 Min: 1 Max: 20	Scale for classifier-free guidance
scheduler	string (enum)	DPMSolverMultistep Options: DDIM, K_EULER, DPMSolverMultistep, K_EULER_ANCESTRAL, PNDM, KLMS, DEISMultistepScheduler, DPM++_2M_Karras	Choose a scheduler.
prompt_strength	number	0.8 Max: 1	Prompt strength when using img2img / inpaint. 1.0 corresponds to full destruction of information in image
seed	integer		Random seed. Leave blank to randomize the seed
prompt_mode	string (enum)	prompt Options: prompt, image_prompt	Choose a prompt mode. Default value prompt uses regular generation while image_prompt uses IP-Adapter to do image prompting.
image_prompt_method	string (enum)	style_and_layout Options: style_and_layout, style	Choose a image prompt method: Style only or Style and layout.

{
  "type": "object",
  "title": "Input",
  "properties": {
    "mask": {
      "type": "string",
      "title": "Mask",
      "format": "uri",
      "x-order": 4,
      "description": "Input mask for inpaint mode. Black areas will be preserved, white areas will be inpainted."
    },
    "seed": {
      "type": "integer",
      "title": "Seed",
      "x-order": 12,
      "description": "Random seed. Leave blank to randomize the seed"
    },
    "image": {
      "type": "string",
      "title": "Image",
      "format": "uri",
      "x-order": 3,
      "description": "Input image for img2img or inpaint mode"
    },
    "width": {
      "type": "integer",
      "title": "Width",
      "default": 1024,
      "x-order": 5,
      "description": "Width of output image"
    },
    "height": {
      "type": "integer",
      "title": "Height",
      "default": 1024,
      "x-order": 6,
      "description": "Height of output image"
    },
    "prompt": {
      "type": "string",
      "title": "Prompt",
      "default": "a photo of an astronaut riding a horse on mars",
      "x-order": 0,
      "description": "Input prompt"
    },
    "scheduler": {
      "enum": [
        "DDIM",
        "K_EULER",
        "DPMSolverMultistep",
        "K_EULER_ANCESTRAL",
        "PNDM",
        "KLMS",
        "DEISMultistepScheduler",
        "DPM++_2M_Karras"
      ],
      "type": "string",
      "title": "scheduler",
      "description": "Choose a scheduler.",
      "default": "DPMSolverMultistep",
      "x-order": 10
    },
    "num_outputs": {
      "type": "integer",
      "title": "Num Outputs",
      "default": 1,
      "maximum": 4,
      "minimum": 1,
      "x-order": 7,
      "description": "Number of images to output."
    },
    "prompt_mode": {
      "enum": [
        "prompt",
        "image_prompt"
      ],
      "type": "string",
      "title": "prompt_mode",
      "description": "Choose a prompt mode. Default value prompt uses regular generation while image_prompt uses IP-Adapter to do image prompting.",
      "default": "prompt",
      "x-order": 13
    },
    "image_prompt": {
      "type": "string",
      "title": "Image Prompt",
      "format": "uri",
      "x-order": 2,
      "description": "Input image prompt for image_prompt mode"
    },
    "guidance_scale": {
      "type": "number",
      "title": "Guidance Scale",
      "default": 7.5,
      "maximum": 20,
      "minimum": 1,
      "x-order": 9,
      "description": "Scale for classifier-free guidance"
    },
    "negative_prompt": {
      "type": "string",
      "title": "Negative Prompt",
      "x-order": 1,
      "description": "Specify things to not see in the output"
    },
    "prompt_strength": {
      "type": "number",
      "title": "Prompt Strength",
      "default": 0.8,
      "maximum": 1,
      "minimum": 0,
      "x-order": 11,
      "description": "Prompt strength when using img2img / inpaint. 1.0 corresponds to full destruction of information in image"
    },
    "image_prompt_method": {
      "enum": [
        "style_and_layout",
        "style"
      ],
      "type": "string",
      "title": "image_prompt_method",
      "description": "Choose a image prompt method: Style only or Style and layout.",
      "default": "style_and_layout",
      "x-order": 14
    },
    "num_inference_steps": {
      "type": "integer",
      "title": "Num Inference Steps",
      "default": 50,
      "maximum": 500,
      "minimum": 1,
      "x-order": 8,
      "description": "Number of denoising steps"
    }
  }
}

Output schema

The shape of the response you’ll get when you run this model with an API.

Schema

{
  "type": "array",
  "items": {
    "type": "string",
    "format": "uri"
  },
  "title": "Output"
}