detr-resnet-50 Beta

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detr-resnet-50 Beta

Object Detection • facebook

@cf/facebook/detr-resnet-50

DEtection TRansformer (DETR) model trained end-to-end on COCO 2017 object detection (118k annotated images).

Usage

Workers - TypeScript

export interface Env {
  AI: Ai;
}

export default {
  async fetch(request, env): Promise<Response> {
    const res = await fetch("https://cataas.com/cat");
    const blob = await res.arrayBuffer();

    const inputs = {
      image: [...new Uint8Array(blob)],
    };

    const response = await env.AI.run(
      "@cf/facebook/detr-resnet-50",
      inputs
    );

    return new Response(JSON.stringify({ inputs: { image: [] }, response }));
  },
} satisfies ExportedHandler<Env>;

curl

curl https://api.cloudflare.com/client/v4/accounts/$CLOUDFLARE_ACCOUNT_ID/ai/run/@cf/facebook/detr-resnet-50  \
    -X POST  \
    -H "Authorization: Bearer $CLOUDFLARE_API_TOKEN"  \
    --data-binary "@pedestrian-boulevard-manhattan-crossing.jpg"

Parameters

Input

• 0 string

  The image to use for detection

• 1 object
  • image array

    An array of integers that represent the image data constrained to 8-bit unsigned integer values

    • items number

      A value between 0 and 255 (unsigned 8bit)

Output

• items object
  • score number

    Confidence score indicating the likelihood that the detection is correct

  • label string

    The class label or name of the detected object

  • box object

    Coordinates defining the bounding box around the detected object

    • xmin number

      The x-coordinate of the top-left corner of the bounding box

    • ymin number

      The y-coordinate of the top-left corner of the bounding box

    • xmax number

      The x-coordinate of the bottom-right corner of the bounding box

    • ymax number

      The y-coordinate of the bottom-right corner of the bounding box

API Schemas

The following schemas are based on JSON Schema

Input

{
    "oneOf": [
        {
            "type": "string",
            "format": "binary",
            "description": "The image to use for detection"
        },
        {
            "type": "object",
            "properties": {
                "image": {
                    "type": "array",
                    "description": "An array of integers that represent the image data constrained to 8-bit unsigned integer values",
                    "items": {
                        "type": "number",
                        "description": "A value between 0 and 255 (unsigned 8bit)"
                    }
                }
            }
        }
    ]
}

Output

{
    "type": "array",
    "contentType": "application/json",
    "description": "An array of detected objects within the input image",
    "items": {
        "type": "object",
        "properties": {
            "score": {
                "type": "number",
                "description": "Confidence score indicating the likelihood that the detection is correct"
            },
            "label": {
                "type": "string",
                "description": "The class label or name of the detected object"
            },
            "box": {
                "type": "object",
                "description": "Coordinates defining the bounding box around the detected object",
                "properties": {
                    "xmin": {
                        "type": "number",
                        "description": "The x-coordinate of the top-left corner of the bounding box"
                    },
                    "ymin": {
                        "type": "number",
                        "description": "The y-coordinate of the top-left corner of the bounding box"
                    },
                    "xmax": {
                        "type": "number",
                        "description": "The x-coordinate of the bottom-right corner of the bounding box"
                    },
                    "ymax": {
                        "type": "number",
                        "description": "The y-coordinate of the bottom-right corner of the bounding box"
                    }
                }
            }
        }
    }
}