R2-D2 analysed your collection images and here’s what he found

Paul Rowe

National Digital Forum, Nov 2017

Why do it?Provide access to data already there.

Create text data that we don’t have time to enter manually

Find patterns: Colours, lines, light, space

Facial recognition

Youtube – Closed Captions

IBM Watson speech to text

Image analysis isn’t easy

Cogapp test siteMicrosoft / Google / Clarifai

Nationalmuseum, Sweden: Painting - "Hedvig Sofia, princess of Sweden"

Captioning is the weakest link

Nationalmuseum, Sweden: Painting

Madonna with child

Google Vision tags

Unexpected new connections

… and the captions can be surprisingly precise

Nationalmuseum, Sweden - Painting, Landskap met kor

Text analysis

http://ketechristchurch.peoplesnetworknz.info/places_and_streets/images/show/

18306-action-figure-paste-ups-greedo#.WgtonXZpHs0

Colour Analysis

Mapping to smaller palette

Combine it all and find “house AND white AND landscape”

These are the droids you’re looking forWebsites

Barnes Foundation: https://collection.barnesfoundation.org/

Cogapp image tagging test site: http://labs.cogapp.com/iiif-ml/

Invisible Australians: http://invisibleaustralians.org/faces/

Sarjeant Gallery: https://collection.sarjeant.org.nz

Tools

Artrendex ArtPI: http://www.artrendex.com/

Clarifai: https://www.clarifai.com/demo

Color Thief: http://lokeshdhakar.com/projects/color-thief/

Google Cloud Vision API: https://cloud.google.com/vision/docs/

IBM Watson Speech to Text: https://www.ibm.com/watson/services/speech-to-text/

Microsoft Azure Cognitive Services: https://azure.microsoft.com/en-us/try/cognitive-services/

OpenCV Library: https://sourceforge.net/projects/opencvlibrary/

“That’s no moon”

Paul Rowe, Vernon Systems

@armchair_caver

Generated Subject Tags:

Moon Planet

Satellite Space