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Analyse Image from S3 with Amazon Rekognition Example

This example shows how to analyze an image in an S3 bucket with Amazon Rekognition and return a list of labels.


  • Determine if there is a cat in an image.


You need to create an S3 bucket and upload at least one file. Be sure the permissions on the folder and file allow public access and that CORS is configured to allow access.

npm install


In order to deploy the function run:

serverless deploy

The expected result should be similar to:

Serverless: Packaging service...
Serverless: Uploading CloudFormation file to S3...
Serverless: Uploading service .zip file to S3 (3.78 MB)...
Serverless: Updating Stack...
Serverless: Checking Stack update progress...
Serverless: Stack update finished...
Service Information
service: rekognition-analysis-s3-image
stage: dev
region: us-east-1
api keys:
  POST - https://6bbhhv5q22.execute-api.us-east-1.amazonaws.com/dev/analysis
  imageAnalysis: rekognition-analysis-s3-image-dev-imageAnalysis


You can now send an HTTP POST request directly to the endpoint using a tool like curl

  "bucket": "mycatphotos",
  "imageName": "cat.jpg"
serverless invoke local -f imageAnalysis -p post.json

The expected result should be similar to:

    "Labels": [
            "Confidence": 96.59198760986328,
            "Name": "Animal"
            "Confidence": 96.59198760986328,
            "Name": "Cat"
            "Confidence": 96.59198760986328,
            "Name": "Pet"
            "Confidence": 96.59198760986328,
            "Name": "Siamese"


By default, AWS Lambda limits the total concurrent executions across all functions within a given region to 100. The default limit is a safety limit that protects you from costs due to potential runaway or recursive functions during initial development and testing. To increase this limit above the default, follow the steps in To request a limit increase for concurrent executions.