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.

Use-cases

• Determine if there is a cat in an image.

Setup

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

Deploy

In order to deploy the function run:

serverless deploy

The expected result should be similar to:

Deploying "rekognition-analysis-s3-image" to stage "dev" (us-east-1)

✔ Service deployed to stack rekognition-analysis-s3-image-dev (48s)

endpoint: POST - https://6bbhhv5q22.execute-api.us-east-1.amazonaws.com/dev/analysis
functions:
  imageAnalysis: rekognition-analysis-s3-image-dev-imageAnalysis (1.5 kB)

Usage

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"
        }
    ]
}

Scaling

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.