varad-13/sam-3 | API reference

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Run varad-13/sam-3 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		Image to segment
prompt	string		Concept to find — a short noun phrase, e.g. 'logo', 'person', 'red car'. Every matching instance is returned.
threshold	number	0.5 Max: 1	Min confidence score to keep a detection
mask_threshold	number	0.5 Max: 1	Probability cutoff for binarising each mask
return_masks	boolean	True	Include the base64 PNG segment in each detection

{
  "type": "object",
  "title": "Input",
  "required": [
    "image",
    "prompt"
  ],
  "properties": {
    "image": {
      "type": "string",
      "title": "Image",
      "format": "uri",
      "x-order": 0,
      "description": "Image to segment"
    },
    "prompt": {
      "type": "string",
      "title": "Prompt",
      "x-order": 1,
      "description": "Concept to find \u2014 a short noun phrase, e.g. 'logo', 'person', 'red car'. Every matching instance is returned."
    },
    "threshold": {
      "type": "number",
      "title": "Threshold",
      "default": 0.5,
      "maximum": 1,
      "minimum": 0,
      "x-order": 2,
      "description": "Min confidence score to keep a detection"
    },
    "return_masks": {
      "type": "boolean",
      "title": "Return Masks",
      "default": true,
      "x-order": 4,
      "description": "Include the base64 PNG segment in each detection"
    },
    "mask_threshold": {
      "type": "number",
      "title": "Mask Threshold",
      "default": 0.5,
      "maximum": 1,
      "minimum": 0,
      "x-order": 3,
      "description": "Probability cutoff for binarising each mask"
    }
  }
}

Output schema

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

Schema

{
  "type": "object",
  "title": "Output",
  "required": [
    "count",
    "detections"
  ],
  "properties": {
    "count": {
      "type": "integer",
      "title": "Count"
    },
    "detections": {
      "type": "array",
      "items": {
        "type": "object",
        "title": "Detection",
        "required": [
          "score",
          "box",
          "rotated_box",
          "area",
          "mask"
        ],
        "properties": {
          "box": {
            "type": "array",
            "items": {
              "type": "number"
            },
            "title": "Box"
          },
          "area": {
            "type": "integer",
            "title": "Area"
          },
          "mask": {
            "type": "string",
            "title": "Mask"
          },
          "score": {
            "type": "number",
            "title": "Score"
          },
          "rotated_box": {
            "type": "object",
            "title": "RotatedBox",
            "required": [
              "center",
              "size",
              "angle",
              "points"
            ],
            "properties": {
              "size": {
                "type": "array",
                "items": {
                  "type": "number"
                },
                "title": "Size"
              },
              "angle": {
                "type": "number",
                "title": "Angle"
              },
              "center": {
                "type": "array",
                "items": {
                  "type": "number"
                },
                "title": "Center"
              },
              "points": {
                "type": "array",
                "items": {
                  "type": "array",
                  "items": {
                    "type": "number"
                  }
                },
                "title": "Points"
              }
            }
          }
        }
      },
      "title": "Detections"
    }
  }
}