gmcolab/cn_bretts – API reference

gmcolab / cn_bretts

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234 runs

Run gmcolab/cn_bretts 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
image	string		Background-removed image
prompt	string		Prompt for the model
num_samples	string (enum)	1 Options: 1, 4	Number of samples (higher values may OOM)
image_resolution	string (enum)	512 Options: 256, 512, 768	Image resolution to be generated
low_threshold	integer	100 Min: 1 Max: 255	Canny line detection low threshold
high_threshold	integer	200 Min: 1 Max: 255	Canny line detection high threshold
ddim_steps	integer	20	Steps
scale	number	9 Min: 0.1 Max: 30	Scale for classifier-free guidance
seed	integer	-1	Seed
eta	number	0	Controls the amount of noise that is added to the input data during the denoising diffusion process. Higher value -> more noise
a_prompt	string	RAW photo, product photography, highres, extremely detailed, best quality, 8k uhd, dslr, soft lighting, high quality, film grain, Fujifilm XT3,	Additional text to be appended to prompt
n_prompt	string	poorly drawn, lowres, bad quality, worst quality, unrealistic, overexposed, underexposed, floating, blurry background	Negative Prompt
detect_resolution	integer	512 Min: 128 Max: 1024	Resolution at which detection method will be applied)

{
  "type": "object",
  "title": "Input",
  "required": [
    "image",
    "prompt"
  ],
  "properties": {
    "eta": {
      "type": "number",
      "title": "Eta",
      "default": 0,
      "x-order": 9,
      "description": "Controls the amount of noise that is added to the input data during the denoising diffusion process. Higher value -> more noise"
    },
    "seed": {
      "type": "integer",
      "title": "Seed",
      "default": -1,
      "x-order": 8,
      "description": "Seed"
    },
    "image": {
      "type": "string",
      "title": "Image",
      "format": "uri",
      "x-order": 0,
      "description": "Background-removed image"
    },
    "scale": {
      "type": "number",
      "title": "Scale",
      "default": 9,
      "maximum": 30,
      "minimum": 0.1,
      "x-order": 7,
      "description": "Scale for classifier-free guidance"
    },
    "prompt": {
      "type": "string",
      "title": "Prompt",
      "x-order": 1,
      "description": "Prompt for the model"
    },
    "a_prompt": {
      "type": "string",
      "title": "A Prompt",
      "default": "RAW photo, product photography, highres, extremely detailed, best quality,  8k uhd, dslr, soft lighting, high quality, film grain, Fujifilm XT3,",
      "x-order": 10,
      "description": "Additional text to be appended to prompt"
    },
    "n_prompt": {
      "type": "string",
      "title": "N Prompt",
      "default": "poorly drawn, lowres, bad quality, worst quality, unrealistic, overexposed, underexposed, floating, blurry background",
      "x-order": 11,
      "description": "Negative Prompt"
    },
    "ddim_steps": {
      "type": "integer",
      "title": "Ddim Steps",
      "default": 20,
      "x-order": 6,
      "description": "Steps"
    },
    "num_samples": {
      "enum": [
        "1",
        "4"
      ],
      "type": "string",
      "title": "num_samples",
      "description": "Number of samples (higher values may OOM)",
      "default": "1",
      "x-order": 2
    },
    "low_threshold": {
      "type": "integer",
      "title": "Low Threshold",
      "default": 100,
      "maximum": 255,
      "minimum": 1,
      "x-order": 4,
      "description": "Canny line detection low threshold"
    },
    "high_threshold": {
      "type": "integer",
      "title": "High Threshold",
      "default": 200,
      "maximum": 255,
      "minimum": 1,
      "x-order": 5,
      "description": "Canny line detection high threshold"
    },
    "image_resolution": {
      "enum": [
        "256",
        "512",
        "768"
      ],
      "type": "string",
      "title": "image_resolution",
      "description": "Image resolution to be generated",
      "default": "512",
      "x-order": 3
    },
    "detect_resolution": {
      "type": "integer",
      "title": "Detect Resolution",
      "default": 512,
      "maximum": 1024,
      "minimum": 128,
      "x-order": 12,
      "description": "Resolution at which detection method will be applied)"
    }
  }
}

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"
}