Object Detection

import { JigsawStack } from "jigsawstack";

const jigsaw = JigsawStack({ apiKey: "your-api-key" });

const response = await jigsaw.vision.object_detection({
  "url": "https://rogilvkqloanxtvjfrkm.supabase.co/storage/v1/object/public/demo/Collabo%201080x842.jpg?t=2024-03-22T09%3A22%3A48.442Z"
})

{
  "success": true,
  "width": 1080,
  "height": 842,
  "tags": [
        "clothing",
        "human face",
        "person",
        "man",
        "woman",
        "wall",
        "table",
        "indoor",
        "smile",
        "sharing",
        "food",
        "people",
        "group",
        "eating"
  ],
  "objects": [
        {
              "name": "person",
              "confidence": 0.599,
              "bounds": {
                    "top_left": {
                          "x": 430,
                          "y": 290
                    },
                    "top_right": {
                          "x": 631,
                          "y": 290
                    },
                    "bottom_right": {
                          "x": 631,
                          "y": 523
                    },
                    "bottom_left": {
                          "x": 430,
                          "y": 523
                    },
                    "width": 201,
                    "height": 233
              }
        },
        {
              "name": "person",
              "confidence": 0.542,
              "bounds": {
                    "top_left": {
                          "x": 230,
                          "y": 273
                    },
                    "top_right": {
                          "x": 440,
                          "y": 273
                    },
                    "bottom_right": {
                          "x": 440,
                          "y": 610
                    },
                    "bottom_left": {
                          "x": 230,
                          "y": 610
                    },
                    "width": 210,
                    "height": 337
              }
        },
        {
              "name": "person",
              "confidence": 0.869,
              "bounds": {
                    "top_left": {
                          "x": 16,
                          "y": 279
                    },
                    "top_right": {
                          "x": 397,
                          "y": 279
                    },
                    "bottom_right": {
                          "x": 397,
                          "y": 818
                    },
                    "bottom_left": {
                          "x": 16,
                          "y": 818
                    },
                    "width": 381,
                    "height": 539
              }
        },
        {
              "name": "person",
              "confidence": 0.847,
              "bounds": {
                    "top_left": {
                          "x": 546,
                          "y": 226
                    },
                    "top_right": {
                          "x": 1078,
                          "y": 226
                    },
                    "bottom_right": {
                          "x": 1078,
                          "y": 825
                    },
                    "bottom_left": {
                          "x": 546,
                          "y": 825
                    },
                    "width": 532,
                    "height": 599
              }
        }
  ],
  "_usage": {
        "input_tokens": 34,
        "output_tokens": 244,
        "inference_time_tokens": 1647,
        "total_tokens": 1925
  }
}