resnet-50
Model ID: @cf/microsoft/resnet-50
50 layers deep image classification CNN trained on more than 1M images from ImageNet
Properties
Task Type: Image Classification
Code Examples
Worker - 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/microsoft/resnet-50", inputs );
return new Response(JSON.stringify(response)); },
} satisfies ExportedHandler<Env>;
curl
curl https://api.cloudflare.com/client/v4/accounts/$CLOUDFLARE_ACCOUNT_ID/ai/run/@cf/microsoft/resnet-50 \ -X POST \ -H "Authorization: Bearer $CLOUDFLARE_API_TOKEN" \ --data-binary "@orange-llama.png"
Response
[ { "label":"PERSIAN CAT" ,"score":0.4071170687675476 }, { "label":"PEKINESE", "score":0.23444877564907074 }, { "label":"FEATHER BOA", "score":0.22562485933303833 }, { "label":"POMERANIAN", "score":0.033316344022750854 }, { "label":"JAPANESE SPANIEL", "score":0.024184171110391617 }
]
API Schema
The following schema is based on JSON SchemaInput JSON Schema
{
"oneOf": [ { "type": "string", "format": "binary" }, { "type": "object", "properties": { "image": { "type": "array", "items": { "type": "number" } } }, "required": [ "image" ] }
]
}
Output JSON Schema
{
"type": "array",
"contentType": "application/json",
"items": { "type": "object", "properties": { "score": { "type": "number" }, "label": { "type": "string" } }
}
}