image_conditioning

Generate images matching the layout and composition of a reference image using text prompts and control modes. Specify attributes to include or exclude for precise output customization.

Instructions

Generate an image that follows the layout and composition of a reference image.

Args:
    image_path: File path of the reference image
    prompt: Text describing the image to be generated
    negative_prompt: Text specifying attributes to exclude from generation
    control_mode: Control mode (CANNY_EDGE, etc.)
    height: Output image height (pixels)
    width: Output image width (pixels)
    cfg_scale: Prompt matching degree (1-20)
    
Returns:
    Dict: Dictionary containing the file path of the generated image

Input Schema

Name	Required	Default
`cfg_scale`	No
`control_mode`	No	CANNY_EDGE
`height`	No
`image_path`	Yes
`negative_prompt`	No
`prompt`	Yes
`width`	No

Input Schema (JSON Schema)

{
  "properties": {
    "cfg_scale": {
      "default": 8,
      "title": "Cfg Scale",
      "type": "number"
    },
    "control_mode": {
      "default": "CANNY_EDGE",
      "title": "Control Mode",
      "type": "string"
    },
    "height": {
      "default": 512,
      "title": "Height",
      "type": "integer"
    },
    "image_path": {
      "title": "Image Path",
      "type": "string"
    },
    "negative_prompt": {
      "default": "",
      "title": "Negative Prompt",
      "type": "string"
    },
    "prompt": {
      "title": "Prompt",
      "type": "string"
    },
    "width": {
      "default": 512,
      "title": "Width",
      "type": "integer"
    }
  },
  "required": [
    "image_path",
    "prompt"
  ],
  "title": "image_conditioningArguments",
  "type": "object"
}

AWS Nova Canvas MCP Server

image_conditioning

Instructions

Input Schema

Input Schema (JSON Schema)

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