Example of AWS Rekognition

1. AWSome Day 2018
AWS Rekognition -
Riconoscimento Facciale
PUG Torino - Marzo 2019

2. Walter Dal Mut
Solution Architect - AWS Certified
SysOps Administrator - AWS Certified
Docker Certified Associate
@walterdalmut
walter.dalmut@corley.it
corley.it

3. 28 Marzo 2019
Codice Sconto: pug-sconto

4. Scalability and cost optimization with Container Services
CloudConf2019 - General
Setup
AWS Rekognition
Summary

5. Get the APP
https://u.corley.it/s/b4

6. ➢ Receive the CloudConf email with the web
application endpoint
➢ The barcode is used on the web application
➢ The user upload its own picture connecting the
identification number
➢ The pictures is checked to drop common mistakes
○ Drop multiple users (too many people)
○ Dark or too bright pictures
○ Low quality pictures
○ etc.
■ We believe that users are somehow polite
➢ AWS Rekognition tear apart the picture in favor of
raw information
○ (no images are stored)
The user upload its own picture

7. ➢ Locally runs a simple face recognition algorithm
➢ When a face is detected a frame is captured
➢ The captured frame is processed by AWS
Rekognition Service
➢ The External Image Identification number is
used to get the user information
➢ The user information is stored as PDF file
➢ The file is printed using a thermal printer
Local algorithm

8. Local configuration

9. AWS Rekognition
$ aws rekognition list-collections
{
"CollectionIds": [
"collection-10",
"corley-test"
],
"FaceModelVersions": [
"4.0",
"4.0"
]
}

10. AWS Rekognition
$ aws rekognition create-collection --collection-id collection-11
{
"StatusCode": 200,
"CollectionArn":
"aws:rekognition:eu-west-1:xxxxxxxxxxxx:collection/collection-11",
"FaceModelVersion": "4.0"
}

11. Upload pictures on s3
$aws s3 cp wdm1.jpg s3://faces.walterdalmut.com/
$ aws s3 ls s3://faces.walterdalmut.com
2019-02-15 17:46:24 6753 thor1.jpg
2019-02-15 17:40:00 44897 wdm1.jpg

12. Detect faces (when you upload a picture)
$ aws rekognition detect-faces --image 'S3Object={Bucket=faces.walterdalmut.com,Name=wdm1.jpg}'
{
"FaceDetails": [
{
"Landmarks": [
{
"Type": "eyeLeft",
"X": 0.4940113127231598,
"Y": 0.28493359684944153
},
{
"Type": "eyeRight",
"X": 0.5633826851844788,
"Y": 0.2943187952041626
},
{
"Type": "mouthLeft",
"X": 0.4960087239742279,
"Y": 0.41778162121772766
},
{
"Type": "mouthRight",
"X": 0.5530909895896912,
"Y": 0.42552411556243896
},
{
"Type": "nose",
"X": 0.5306091904640198,
"Y": 0.34477418661117554
}
],
}
]
}
// continue...
{
"FaceDetails": [
{
"BoundingBox": {
"Width": 0.1618916094303131,
"Height": 0.4021730124950409,
"Left": 0.43909329175949097,
"Top": 0.12676428258419037
},
"Pose": {
"Roll": 3.8218839168548584,
"Yaw": 5.0268073081970215,
"Pitch": 5.38221549987793
},
"Quality": {
"Brightness": 64.7296142578125,
"Sharpness": 32.20803451538086
},
"Confidence": 99.9999771118164
}
]
}

13. Index faces (when you upload a picture)
$ aws rekognition index-faces
--collection-id collection-11
--image 'S3Object={Bucket=faces.walterdalmut.com,Name=wdm1.jpg}'
{
"FaceRecords": [
{
"Face": {
"FaceId": "310b383e-66c1-43b8-918a-75388619ee7b",
"BoundingBox": {
"Width": 0.1618916094303131,
"Height": 0.4021730124950409,
"Left": 0.43909329175949097,
"Top": 0.12676428258419037
},
"ImageId": "da1ae019-db88-3713-8e9e-7d01238ea609",
"Confidence": 99.9999771118164
},
}
]
…
}

14. Index faces (when you upload a picture)
$ aws rekognition index-faces
--collection-id collection-11
--image 'S3Object={Bucket=faces.walterdalmut.com,Name=wdm1.jpg}'
--external-image-id my-user-id
{
"FaceRecords": [
{
"Face": {
"FaceId": "my-user-id",
"BoundingBox": {
"Width": 0.1618916094303131,
"Height": 0.4021730124950409,
"Left": 0.43909329175949097,
"Top": 0.12676428258419037
},
"ImageId": "da1ae019-db88-3713-8e9e-7d01238ea609",
"Confidence": 99.9999771118164
},
}
]
…
}

15. Search faces (when you upload a picture)
$ aws rekognition search-faces-by-image
--collection-id collection-11
--image 'S3Object={Bucket=faces.walterdalmut.com,Name=wdm1.jpg}'
{
"SearchedFaceBoundingBox": {
"Width": 0.1618916094303131,
"Height": 0.4021730124950409,
"Left": 0.43909329175949097,
"Top": 0.12676428258419037
},
"SearchedFaceConfidence": 99.9999771118164,
"FaceMatches": [
{
"Similarity": 99.99999237060547,
"Face": {
"FaceId": "my-user-id",
"BoundingBox": {
"Width": 0.16189199686050415,
"Height": 0.4021730124950409,
"Left": 0.4390929937362671,
"Top": 0.12676399946212769
},
"ImageId": "da1ae019-db88-3713-8e9e-7d01238ea609",
"Confidence": 100.0
}
}
],
"FaceModelVersion": "4.0"
}

16. List existing faces (management)
$ aws rekognition list-faces --collection-id collection-16
{
"Faces": [
{
"FaceId": "18215496-3282-46ae-a265-aecf140fba65",
"BoundingBox": {
"Width": 0.37553301453590393,
"Height": 0.3338260054588318,
"Left": 0.43626898527145386,
"Top": 0.289465993642807
},
"ImageId": "ea5e78fc-3fdb-32d3-b053-5a22f95dbd55",
"ExternalImageId": "6639219",
"Confidence": 100.0
},
{
"FaceId": "2b85a18f-7570-4568-9fe0-b770ace00745",
"BoundingBox": {
"Width": 0.47415900230407715,
"Height": 0.3649649918079376,
"Left": 0.34846198558807373,
"Top": 0.28914299607276917
},
"ImageId": "c601ee26-224b-308a-a25c-ecd56ad0a400",
"ExternalImageId": "6639219",
"Confidence": 100.0
},
],
"FaceModelVersion": "4.0"
}

17. Drop existing faces (management)
$ aws rekognition delete-faces --collection-id collection-16
--face-ids 2b85a18f-7570-4568-9fe0-b770ace00745
{
"DeletedFaces": [
"2b85a18f-7570-4568-9fe0-b770ace00745"
]
}

18. Thanks for listening.
Torino 2018 - walter.dalmut@corley.it