detr-resnet-50
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Model ID: @cf/facebook/detr-resnet-50
DEtection TRansformer (DETR) model trained end-to-end on COCO 2017 object detection (118k annotated images).
Properties
Task Type: Object Detection
Code Examples
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"
Response
This task returns a list of detected objects, each one containing a label, a probability score, and its surrounding box coordinates.
[ { "label":"cat" ,"score":0.4071170687675476, "box": { "xmin": 0, "ymin": 0, "xmax": 10, "ymax": 10 } }, { "label":"face", "score":0.22562485933303833, "box": { "xmin": 15, "ymin": 22, "xmax": 25, "ymax": 35 } }, { "label":"car", "score":0.033316344022750854, "box": { "xmin": 72, "ymin": 55, "xmax": 95, "ymax": 72 } }]
API Schema
The following schema is based on JSON Schema
Input JSON Schema
{ "oneOf": [ { "type": "string", "format": "binary" }, { "type": "object", "properties": { "image": { "type": "array", "items": { "type": "number" } } } } ]}
Output JSON Schema
{ "type": "array", "contentType": "application/json", "items": { "type": "object", "properties": { "score": { "type": "number" }, "label": { "type": "string" }, "box": { "type": "object", "properties": { "xmin": { "type": "number" }, "ymin": { "type": "number" }, "xmax": { "type": "number" }, "ymax": { "type": "number" } } } } }}