This document provides an overview of a workshop on using Amazon Rekognition to build a facial recognition system. It describes the services that will be used, including Amazon Rekognition, Amazon EC2, Amazon Kinesis Data Firehose, AWS Lambda, Amazon DynamoDB, and Amazon S3. It outlines a scenario where these services will be used to build an application to find missing persons by scanning social media images with Amazon Rekognition facial recognition. The workshop will provide steps to set up a Twitter application, launch an AWS CloudFormation stack, and validate and start the application.

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Use Amazon Rekognition to Build a Facial Recognition System
Kashif Imran, Sr. Solutions Architect

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What to expect?
• Overview of Amazon Rekognition
• Introduction to AWS services used in workshop
• Outline of the Workshop Scenario
• Preview of the Lab/Instructions

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A Long History of Machine Learning at Amazon
Personalized
recommendations
Inventing entirely
new customer
experiences
Fulfillment
automation and
inventory
management
Drones Voice driven
interactions

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Put machine learning in the hands
of every developer and data scientist
Machine Learning at AWS
Our mission:

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The Amazon Machine Learning Stack
PLATFORM SERVICES
APPLICATION SERVICES
FRAMEWORKS & INTERFACES
Caffe2 CNTK
Apache
MXNet
PyTorch TensorFlow Torch Keras Gluon
AWS Deep Learning AMIs
Amazon SageMaker AWS DeepLens
Rekognition Transcribe Translate Polly Comprehend Lex

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Amazon Rekognition
VideoImage &

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Amazon Rekognition Image
Object and Scene
Detection
Facial
Analysis
Face
Recognition
Text in Image
Deep learning-based image analysis service
Unsafe Image
Detection
Celebrity
Recognition

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Amazon Rekognition Video
Deep learning-based video analysis service
Object and Activity
Detection
Person Tracking Face Detection &
Recognition
Real-time Live
Stream
Unsafe Video
Detection
Celebrity
Recognition

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DetectLabels
{
"Image": {
"Bytes": blob,
"S3Object": {
"Bucket": "string",
"Name": "string",
"Version": "string"
}
},
"MaxLabels": number,
"MinConfidence": number
}
Image API – Request and Response
{
"Labels": [
{
"Confidence": number,
"Name": "string”
}
],
"OrientationCorrection": "string"
}

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GetLabelDetection
StartLabelDetection
{
“ClientRequestToken": "string",
"JobTag": "string",
"MinConfidence": number,
"NotificationChannel": {
"RoleArn": "string",
"SNSTopicArn": "string”
},
"Video": {
"S3Object": {
"Bucket": "string",
"Name": "string",
"Version": "string”
}
}
}
Video API - Request and Response
{
"JobStatus": string,
"StatusMessage": string,
"VideoMetadata": {
"Format": string,
"Codec": string,
"DurationMillis": number,
"FrameRate": float,
"FrameWidth": number,
"FrameHeight": number
},
"NextToken": string,
"Labels": [
{
"Timestamp": number,
"Label":
{
"Name": string,
"Confidence": float
}
}
],
...
JobId

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Object, Scene and Activity Detection

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Searchable Image Library

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Searchable Video Library

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Detect Labels

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Facial Recognition

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Face-based User Verification

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Immediate Response for Pubic Safety and Security

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Search Faces by Image

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Compare Faces

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Facial Analysis

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Sentiment Analysis

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Detect Faces

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Unsafe Content Detection

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Image Moderation

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Detect Unsafe Video

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Detect Moderation Labels

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Celebrity Recognition

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Celebrity Recognition

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Recognize Celebrities

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Text in Images

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License Plate Verification

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Detect Text

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Person Tracking

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"Persons": [
{
"Timestamp": number,
"Person":
{
"Index": number,
"BoundingBox":
{
"Width": number,
"Top": number,
"Height": number,
"Left": number
},
"Face":
{
"BoundingBox": { ... },
"Landmarks": { ... },
"Pose": { ... },
"Quality": { ... },
"Confidence": number
}
},
...
GetPersonTracking
StartPersonTracking
Person Tracking

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Other AWS Services You Will Use Today

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Amazon Elastic Compute Cloud (EC2)
Match Capacity and
Demand
Global Footprint Elasticity
Provision Servers in
Minutes
Infrastructure as
Code
Programmatic
Networking

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Amazon Kinesis Data Firehose

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AWS Lambda
No Servers to Manage Continuous Scaling Don’t Pay for Idle Capacity
Lambda allows you to run
application logic without
provisioning servers or worrying
about the health or security of
underlying resources
Lambda scales infrastructure
beneath your application logic;
just send requests and events
and Lambda will automatically
scale to accommodate it
With Lambda, you’re billed in
100ms increments of execution
time and number of requests
and you’re never charged for
anything when your code isn’t
running

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Amazon DynamoDB
• Fast and flexible NoSQL database service
for any scale
Dead Simple
• GetItem(primaryKey)
• PutItem(item)
Robust Depth
• Fine-Grained Access Control
• Streams
• Triggers
• Global Tables
• Encryption
• DynamoDB local
• Free-text search
• Strong consistency option
• Atomic counters

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Amazon Simple Storage Service (S3)
• Durable, massively scalable object storage
• Designed for 99.999999999% durability and
99.99% availability
• Stores trillions of objects and regularly handles millions of requests per
second
• Effectively infinite storage without provisioning capacity

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Workshop Overview

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Finding Missing Persons by Scanning Social Media with
Amazon Rekognition

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What you need before starting
• An AWS Account
• Twitter developer account
• Reference missing person image
• Twitter web/mobile app

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Setup Twitter Application
Go to https://apps.twitter.com

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AWS Global Infrastructure

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AWS Region for this lab
• Ireland (eu-west-1)

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Create EC2 Key Pair

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Launch AWS CloudFormation Stack

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Validate and Start Application
• Upload your reference missing person image to S3
• SSH into EC2 instance and start python application
• Upload image to Twitter to start Twitter streaming data

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Extension

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• https://github.com/aws-samples/finding-missing-persons-using-social-media-
and-amazon-rekognition
https://tinyurl.com/ya94lwpz

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aws.amazon.com/activate
Everything and Anything Startups
Need to Get Started on AWS