oranzino/controlnet-openpose-template

oranzino / controlnet-openpose-template

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Run oranzino/controlnet-openpose-template 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
control_image	string		Optional Image to use for guidance based on posenet
image	string		Optional Image to use for img2img guidance
mask	string		Optional Mask to use for legacy inpainting
prompt	string	photo of cjw person	Input prompt
negative_prompt	string		Specify things to not see in the output
width	integer (enum)	512 Options: 128, 256, 384, 448, 512, 576, 640, 704, 768, 832, 896, 960, 1024	Width of output image. Maximum size is 1024x768 or 768x1024 because of memory limits
height	integer (enum)	512 Options: 128, 256, 384, 448, 512, 576, 640, 704, 768, 832, 896, 960, 1024	Height of output image. Maximum size is 1024x768 or 768x1024 because of memory limits
num_outputs	integer	1 Min: 1 Max: 10	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
prompt_strength	number	0.8	Prompt strength when using init image. 1.0 corresponds to full destruction of information in init image
scheduler	string (enum)	KarrasDPM Options: DDIM, DPMSolverMultistep, HeunDiscrete, K_EULER_ANCESTRAL, K_EULER, KLMS, PNDM, UniPCMultistep, KarrasDPM	Choose a scheduler.
disable_safety_check	boolean	False	Disable safety check. Use at your own risk!
seed	integer		Random seed. Leave blank to randomize the seed

{
  "type": "object",
  "title": "Input",
  "properties": {
    "mask": {
      "type": "string",
      "title": "Mask",
      "format": "uri",
      "x-order": 2,
      "description": "Optional Mask to use for legacy inpainting"
    },
    "seed": {
      "type": "integer",
      "title": "Seed",
      "x-order": 13,
      "description": "Random seed. Leave blank to randomize the seed"
    },
    "image": {
      "type": "string",
      "title": "Image",
      "format": "uri",
      "x-order": 1,
      "description": "Optional Image to use for img2img guidance"
    },
    "width": {
      "enum": [
        128,
        256,
        384,
        448,
        512,
        576,
        640,
        704,
        768,
        832,
        896,
        960,
        1024
      ],
      "type": "integer",
      "title": "width",
      "description": "Width of output image. Maximum size is 1024x768 or 768x1024 because of memory limits",
      "default": 512,
      "x-order": 5
    },
    "height": {
      "enum": [
        128,
        256,
        384,
        448,
        512,
        576,
        640,
        704,
        768,
        832,
        896,
        960,
        1024
      ],
      "type": "integer",
      "title": "height",
      "description": "Height of output image. Maximum size is 1024x768 or 768x1024 because of memory limits",
      "default": 512,
      "x-order": 6
    },
    "prompt": {
      "type": "string",
      "title": "Prompt",
      "default": "photo of cjw person",
      "x-order": 3,
      "description": "Input prompt"
    },
    "scheduler": {
      "enum": [
        "DDIM",
        "DPMSolverMultistep",
        "HeunDiscrete",
        "K_EULER_ANCESTRAL",
        "K_EULER",
        "KLMS",
        "PNDM",
        "UniPCMultistep",
        "KarrasDPM"
      ],
      "type": "string",
      "title": "scheduler",
      "description": "Choose a scheduler.",
      "default": "KarrasDPM",
      "x-order": 11
    },
    "num_outputs": {
      "type": "integer",
      "title": "Num Outputs",
      "default": 1,
      "maximum": 10,
      "minimum": 1,
      "x-order": 7,
      "description": "Number of images to output."
    },
    "control_image": {
      "type": "string",
      "title": "Control Image",
      "format": "uri",
      "x-order": 0,
      "description": "Optional Image to use for guidance based on posenet"
    },
    "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": 4,
      "description": "Specify things to not see in the output"
    },
    "prompt_strength": {
      "type": "number",
      "title": "Prompt Strength",
      "default": 0.8,
      "x-order": 10,
      "description": "Prompt strength when using init image. 1.0 corresponds to full destruction of information in init image"
    },
    "num_inference_steps": {
      "type": "integer",
      "title": "Num Inference Steps",
      "default": 50,
      "maximum": 500,
      "minimum": 1,
      "x-order": 8,
      "description": "Number of denoising steps"
    },
    "disable_safety_check": {
      "type": "boolean",
      "title": "Disable Safety Check",
      "default": false,
      "x-order": 12,
      "description": "Disable safety check. Use at your own risk!"
    }
  }
}

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",
  "x-cog-array-type": "iterator"
}