resnet-50
Image Classification • Microsoft50 layers deep image classification CNN trained on more than 1M images from ImageNet
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/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"Parameters
Input
-  0stringThe image to classify 
-  1object-  imagearrayAn array of integers that represent the image data constrained to 8-bit unsigned integer values -  itemsnumberA value between 0 and 255 (unsigned 8bit) 
 
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Output
-  itemsobject-  scorenumberA confidence value, between 0 and 1, indicating how certain the model is about the predicted label 
-  labelstringThe predicted category or class for the input image based on analysis 
 
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API Schemas
The following schemas are based on JSON Schema
{    "oneOf": [        {            "type": "string",            "format": "binary",            "description": "The image to classify"        },        {            "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)"                    }                }            },            "required": [                "image"            ]        }    ]}{    "type": "array",    "contentType": "application/json",    "items": {        "type": "object",        "properties": {            "score": {                "type": "number",                "description": "A confidence value, between 0 and 1, indicating how certain the model is about the predicted label"            },            "label": {                "type": "string",                "description": "The predicted category or class for the input image based on analysis"            }        }    }}