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

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/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 Schema

Input 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"
      }
    }
  }
}