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detr-resnet-50

Beta

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

Worker - TypeScript
export interface Env {
AI: Ai;
}
export default {
async fetch(request: Request, env: Env) {
const res: any = 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 }));
},
};
curl
curl https://api.cloudflare.com/client/v4/accounts/$CLOUDFLARE_ACCOUNT_ID/ai/run/@cf/meta/detr-resnet-50 \
-X POST \
-H "Authorization: Bearer $CLOUDFLARE_API_TOKEN" \
--data-binary "@pedestrian-boulevard-manhattan-crossing.jpg"

​​ Responses

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"
}
}
}
}
}
}