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Merge pull request #2568 from abilashkumar/rekognition-s3-detectlabels-python
new serverless pattern - rekognition-s3-detectlabels-python
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‎rekognition-s3-detectlabels-python/README.md‎

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# Amazon S3 to Amazon Rekognition through AWS EventBridge
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This pattern demonstrates how to create an Amazon S3 bucket that triggers an AWS Lambda function via Amazon EventBridge upon object upload. The Lambda function detects labels in an image using Amazon Rekognition. The Lambda function is built using Python.
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Learn more about this pattern at Serverless Land Patterns: https://serverlessland.com/patterns/rekognition-s3-detectlabels-python
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Important: this application uses various AWS services and there are costs associated with these services after the Free Tier usage - please see the [AWS Pricing page](https://aws.amazon.com/pricing/) for details. You are responsible for any AWS costs incurred. No warranty is implied in this example.
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## Requirements
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* [Create an AWS account](https://portal.aws.amazon.com/gp/aws/developer/registration/index.html) if you do not already have one and log in. The IAM user that you use must have sufficient permissions to make necessary AWS service calls and manage AWS resources.
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* [AWS CLI](https://docs.aws.amazon.com/cli/latest/userguide/install-cliv2.html) installed and configured
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* [Git Installed](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git)
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* [AWS Serverless Application Model](https://docs.aws.amazon.com/serverless-application-model/latest/developerguide/serverless-sam-cli-install.html) (AWS SAM) installed
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## Deployment Instructions
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1. Create a new directory, navigate to that directory in a terminal and clone the GitHub repository:
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```
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git clone https://github.com/aws-samples/serverless-patterns
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```
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1. Change directory to the pattern directory:
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```
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cd rekognition-s3-detectlabels-python
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```
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1. From the command line, use AWS SAM to deploy the AWS resources for the pattern as specified in the template.yml file:
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```
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sam deploy --guided
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```
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1. During the prompts:
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* Enter a stack name
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* Enter the desired AWS Region
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* Allow SAM CLI to create IAM roles with the required permissions.
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Once you have run `sam deploy --guided` mode once and saved arguments to a configuration file (samconfig.toml), you can use `sam deploy` in future to use these defaults.
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1. Note the outputs from the SAM deployment process. These contain the resource names and/or ARNs which are used for testing.
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## How it works
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The CloudFormation template creates two Amazon S3 buckets (source and destination) along with an AWS Lambda function (written in Python) and an Amazon EventBridge event. The Lambda function is triggered by EventBridge, which listens for object uploads in the S3 source bucket. The Lambda function makes a `DetectLabels` API call to Amazon Rekognition to detect labels in an image and stores the output in the destination S3 bucket.
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## Testing
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Upload the file (document/image) to the input S3 `<STACK_NAME>-input-bucket-<AWS_ACCOUNTID>` bucket via the console or use the `PutObject` API call below:
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```
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aws s3api put-object --bucket <INPUT_BUCKET_NAME> --key <IMAGE_FILE> --body /path/to/your/<IMAGE_FILE>
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```
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The output of the operation can be downloaded from the output S3 bucket <STACK_NAME>-output-bucket-<AWS_ACCOUNTID>.
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Replace the parameters in the above command appropriately.
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## Cleanup
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1. Delete the stack
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```bash
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sam delete
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```
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----
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Copyright 2024 Amazon.com, Inc. or its affiliates. All Rights Reserved.
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SPDX-License-Identifier: MIT-0

‎rekognition-s3-detectlabels-python/example-pattern.json‎

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{
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"title": "S3 to Rekognition using EventBridge",
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"description": "SAM template for S3 trigger to Lambda for detecting labels in an image using Rekognition and EventBridge",
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"language": "python",
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"level": "200",
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"framework": "SAM",
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"introBox": {
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"headline": "How it works",
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"text": [
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"This pattern demonstrates how to creates two S3 buckets (source and destination) which when uploaded with an object invokes a Lambda function through EventBridge and detects labels in an image using Amazon Rekognition.",
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"Once a file is uploaded to an S3 bucket, it is listened by the EventBridge which further invokes the lambda function",
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"The lambda function writes the output of the detected labels using Rekognition to the destination S3 bucket."
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]
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},
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"gitHub": {
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"template": {
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"repoURL": "https://github.com/aws-samples/serverless-patterns/tree/main/rekognition-s3-detectlabels-python",
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"templateURL": "serverless-patterns/rekognition-s3-detectlabels-python",
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"projectFolder": "rekognition-s3-detectlabels-python",
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"templateFile": "template.yaml"
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}
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},
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"resources": {
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"bullets": [
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{
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"text": "Detecting Labels using Rekognition",
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"link": "https://docs.aws.amazon.com/rekognition/latest/dg/labels-detect-labels-image.html"
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},
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{
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"text": "Amazon Rekognition",
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"link": "https://aws.amazon.com/rekognition/"
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}
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]
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},
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"deploy": {
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"text": [
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"sam deploy"
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]
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},
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"testing": {
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"text": [
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"See the GitHub repo for detailed testing instructions."
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]
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},
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"cleanup": {
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"text": [
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"Delete the stack: <code>cdk delete</code>."
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]
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},
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"authors": [
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{
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"name": "Abilashkumar P C",
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"image": "https://drive.google.com/file/d/1bxOh_WBw8J_xEqvT-qRezH8WXqSBPI24/view?usp=sharing",
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"bio": "Sr. Cloud Support Engineer @ AWS",
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"linkedin": "abilashkumar-p-c"
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}
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]
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}
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‎rekognition-s3-detectlabels-python/rekognition-s3-detectlabels-python.json‎

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{
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"title": "S3 to Rekognition using EventBridge",
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"description": "SAM template for Amazon S3 trigger to AWS Lambda for detecting labels in an image using Amazon Rekognition and Amazon EventBridge",
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"language": "Python",
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"level": "200",
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"framework": "SAM",
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"introBox": {
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"headline": "How it works",
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"text": [
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"This pattern demonstrates how to creates two S3 buckets (source and destination) which when uploaded with an object invokes a Lambda function through EventBridge and detects labels in an image using Amazon Rekognition.",
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"Once a file is uploaded to an S3 bucket, it is listened by the EventBridge which further invokes the lambda function",
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"The lambda function writes the output of the detected labels using Rekognition to the destination S3 bucket."
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]
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},
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"gitHub": {
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"template": {
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"repoURL": "https://github.com/aws-samples/serverless-patterns/tree/main/rekognition-s3-detectlabels-python",
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"templateURL": "serverless-patterns/rekognition-s3-detectlabels-python",
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"projectFolder": "rekognition-s3-detectlabels-python",
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"templateFile": "template.yaml"
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}
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},
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"resources": {
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"bullets": [
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{
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"text": "Detecting Labels using Rekognition",
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"link": "https://docs.aws.amazon.com/rekognition/latest/dg/labels-detect-labels-image.html"
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},
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{
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"text": "Amazon Rekognition",
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"link": "https://aws.amazon.com/rekognition/"
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}
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]
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},
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"deploy": {
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"text": ["sam deploy"]
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},
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"testing": {
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"text": ["See the GitHub repo for detailed testing instructions."]
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},
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"cleanup": {
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"text": ["Delete the stack: <code>cdk delete</code>."]
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},
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"authors": [
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{
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"name": "Abilashkumar P C",
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"image": "https://drive.google.com/file/d/1bxOh_WBw8J_xEqvT-qRezH8WXqSBPI24/view?usp=sharing",
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"bio": "Sr. Cloud Support Engineer @ AWS",
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"linkedin": "abilashkumar-p-c"
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}
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],
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"patternArch": {
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"icon1": {
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"x": 20,
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"y": 50,
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"service": "s3",
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"label": "Amazon S3"
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},
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"icon2": {
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"x": 50,
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"y": 50,
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"service": "lambda",
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"label": "AWS Lambda"
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},
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"icon3": {
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"x": 80,
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"y": 50,
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"service": "rekognition",
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"label": "Amazon Rekognition"
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},
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"line1": {
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"from": "icon1",
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"to": "icon2",
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"label": ""
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},
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"line2": {
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"from": "icon2",
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"to": "icon3",
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"label": ""
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}
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}
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}

‎rekognition-s3-detectlabels-python/src/lambda_function.py‎

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import boto3
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import json
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import os
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s3 = boto3.client('s3')
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rekognition = boto3.client('rekognition')
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def handler(event, context):
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# Extract bucket and key from the EventBridge event
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detail = event['detail']
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bucket = detail['bucket']['name']
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key = detail['object']['key']
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# Call Rekognition to detect faces
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response = rekognition.detect_labels(
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Image={
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'S3Object': {
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'Bucket': bucket,
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'Name': key
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}
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},
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MaxLabels=15
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)
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# Write the Rekognition output to the output bucket
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output_key = f"rekognition-output-{key}"
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output_key = output_key[:output_key.rfind('.')]
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output_key = output_key + ".json"
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print(output_key)
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labelDetection=response['Labels']
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print(response)
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s3.put_object(
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Bucket=os.environ['OUTPUT_BUCKET'],
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Key=output_key,
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Body=json.dumps(labelDetection)
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)
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return {
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'statusCode': 200,
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'body': json.dumps('Label detection successfully')
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}

‎rekognition-s3-detectlabels-python/template.yaml‎

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AWSTemplateFormatVersion: '2010-09-09'
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Transform: AWS::Serverless-2016-10-31
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Description: 'SAM template for S3 trigger to Lambda for detecting labels in an image using Rekognition and EventBridge'
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Resources:
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# Input S3 bucket
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InputBucket:
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Type: AWS::S3::Bucket
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Properties:
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BucketName: !Sub '${AWS::StackName}-input-bucket-${AWS::AccountId}'
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NotificationConfiguration:
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EventBridgeConfiguration:
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EventBridgeEnabled: true
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# Output S3 bucket
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OutputBucket:
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Type: AWS::S3::Bucket
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Properties:
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BucketName: !Sub '${AWS::StackName}-output-bucket-${AWS::AccountId}'
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# Lambda function
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RekognitionFunction:
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Type: AWS::Serverless::Function
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Properties:
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FunctionName: !Sub '${AWS::StackName}-rekognition-function'
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Handler: lambda_function.handler
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Runtime: python3.8
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Timeout: 30
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Environment:
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Variables:
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OUTPUT_BUCKET: !Ref OutputBucket
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Policies:
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- S3ReadPolicy:
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BucketName: !Ref InputBucket
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- S3WritePolicy:
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BucketName: !Ref OutputBucket
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- Statement:
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- Effect: Allow
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Action:
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- rekognition:DetectLabels
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Resource: '*'
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CodeUri: src/
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# EventBridge Rule
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S3ObjectCreatedRule:
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Type: AWS::Events::Rule
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Properties:
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Description: "Rule to capture S3 object created events"
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EventPattern:
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source:
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- aws.s3
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detail-type:
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- Object Created
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detail:
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bucket:
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name:
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- !Ref InputBucket
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State: "ENABLED"
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Targets:
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- Arn: !GetAtt RekognitionFunction.Arn
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Id: "RekognitionFunctionTarget"
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# Permission for EventBridge to invoke Lambda
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RekognitionFunctionPermission:
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Type: AWS::Lambda::Permission
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Properties:
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FunctionName: !Ref RekognitionFunction
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Action: "lambda:InvokeFunction"
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Principal: "events.amazonaws.com"
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SourceArn: !GetAtt S3ObjectCreatedRule.Arn
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Outputs:
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InputBucketName:
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Description: 'Name of the input S3 bucket'
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Value: !Ref InputBucket
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OutputBucketName:
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Description: 'Name of the output S3 bucket'
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Value: !Ref OutputBucket
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RekognitionFunctionName:
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Description: 'Name of the Rekognition Lambda function'
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Value: !Ref RekognitionFunction
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RekognitionFunctionArn:
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Description: 'ARN of the Rekognition Lambda function'
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Value: !GetAtt RekognitionFunction.Arn

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