What does your Instagram say about you? Exploring Google Cloud Vision

by Christine

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@tech_christine @ryanhos What does your Christine Seeman and Ryan Hochstetler say about you?

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@tech_christine @ryanhos What is in an image?

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@tech_christine @ryanhos What is in an image?

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@tech_christine @ryanhos What do you focus on?

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@tech_christine @ryanhos What do you focus on?

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@tech_christine @ryanhos What is in it that you see?

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@tech_christine @ryanhos What is in it that you see?

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@tech_christine @ryanhos But what does an application see in them?

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@tech_christine @ryanhos Meet Google Cloud Vision

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@tech_christine @ryanhos

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@tech_christine @ryanhos

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@tech_christine @ryanhos Little bit different vision

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@tech_christine @ryanhos Cloud Vision API Landmarks Face detection Image labeling Optical character recognition Explicit content detection Logo detection Web entities Crop hint detection

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@tech_christine @ryanhos But how can we use it?

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@tech_christine @ryanhos Let's look at the client library

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@tech_christine @ryanhos Let's combine accounts with

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@tech_christine @ryanhos

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@tech_christine @ryanhos So that got us from this

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@tech_christine @ryanhos To this

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@tech_christine @ryanhos Aggregate the results into histograms Labels Landmarks Logos

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@tech_christine @ryanhos Then finally the tag cloud

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@tech_christine @ryanhos Let's explore the different detections

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@tech_christine @ryanhos Face detection

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@tech_christine @ryanhos What’s a “gnathion”?

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@tech_christine @ryanhos Sentiment Detection Probably should be called “Sentiment Best Guestimation”

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@tech_christine @ryanhos Joy

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@tech_christine @ryanhos Surprise

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@tech_christine @ryanhos Anger?

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@tech_christine @ryanhos Sorrow?

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@tech_christine @ryanhos Image Composition

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@tech_christine @ryanhos Label detection

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@tech_christine @ryanhos @expertvagabond

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@tech_christine @ryanhos @expertvagabond

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@tech_christine @ryanhos @ripleyandrue

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@tech_christine @ryanhos @ripleyandrue

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@tech_christine @ryanhos Safe Search detection

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@tech_christine @ryanhos Yes it knows if it is a hotdog

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@tech_christine @ryanhos ...and when it's not

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@tech_christine @ryanhos Seems accurate…

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@tech_christine @ryanhos Oh, there might be a bit of bias…

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@tech_christine @ryanhos Violence is difficult too…

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@tech_christine @ryanhos Racy but not violent?!?

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@tech_christine @ryanhos Doctored images are hit and miss We chose not to include the image of a former US president photoshopped to look like a dictator and war criminal. Google labeled it “Possibly” a spoof; i.e. altered to be funny or oﬀensive

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@tech_christine @ryanhos Text detection

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@tech_christine @ryanhos @letterfolk

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@tech_christine @ryanhos @letterfolk MY BRAIN HAS TO0 MANY TABS OPEN Dechtlatte THIS WEEK pt de C CAit s pg

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@tech_christine @ryanhos @letterfolk

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@tech_christine @ryanhos @letterfolk YOURE NOT THE BOSS OF ME.. IWHISPER UNDER MY BREATH AS I CLEAN UP ALL OF MY CHILDREN'S MESSES. TRE

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@tech_christine @ryanhos @letterfolk

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@tech_christine @ryanhos @letterfolk Seth Elizabeth Mat IT'S BEGINNING TO amazon Prime LOOK A LOT LIKE... vmazon Prime echo I GOT MY MONEY'S WORTH FROM MY 1t\nare en a ton Prime AMAZON PRIME MEMBERSHIP Nany echo eciro

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@tech_christine @ryanhos Logo detection

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@tech_christine @ryanhos

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@tech_christine @ryanhos @nike

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@tech_christine @ryanhos @nike

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@tech_christine @ryanhos @nike 1. nike 2. nike plus 3. nike azul 4. blue nike 5. nike store

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@tech_christine @ryanhos @christine_seeman

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@tech_christine @ryanhos @christine_seeman

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@tech_christine @ryanhos @christine_seeman 1. etelä suomen sanomat 2. rogue status 3. american horror story 4. delta skymiles 5. deník !"!"

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@tech_christine @ryanhos Landmark detection

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@tech_christine @ryanhos @visit_nebraska

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@tech_christine @ryanhos @iloveny

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@tech_christine @ryanhos @iloveny

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@tech_christine @ryanhos @expertvagabond

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@tech_christine @ryanhos Have you been to London, NE?

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@tech_christine @ryanhos The British Museum there is lovely

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@tech_christine @ryanhos British Museum, alternate photo

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@tech_christine @ryanhos So much alike

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@tech_christine @ryanhos This wasn’t even a building…

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@tech_christine @ryanhos But what does my instagram say about me?

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@tech_christine @ryanhos

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@tech_christine @ryanhos @christineseeman

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@tech_christine @ryanhos Blooper cloud

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@tech_christine @ryanhos Cloud AutoML Vision •Train ML models to classify images •Use your own deﬁned labels. •Graphical user interface to train, evaluate, improve, and deploy models

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@tech_christine @ryanhos @visit_nebraska

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@tech_christine @ryanhos Vs @visitcalifornia

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@tech_christine @ryanhos Vs @iloveny

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@tech_christine @ryanhos Sydney, Australia  Bangkok, Thailand Paris, France

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@tech_christine @ryanhos

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@tech_christine @ryanhos Evaluating Model Accuracy

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@tech_christine @ryanhos Confusion Matrix

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@tech_christine @ryanhos Skyline Predictions

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@tech_christine @ryanhos More training required…

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@tech_christine @ryanhos Urban Scenery Predictions

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@tech_christine @ryanhos Outdoor Scenery Predictions

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@tech_christine @ryanhos Where to go from here? What to do next with Google Cloud Vision

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@tech_christine @ryanhos Explore bias in Machine Learning?

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@tech_christine @ryanhos How much will this cost you? For us, about $65

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@tech_christine @ryanhos 905.33!

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@tech_christine @ryanhos $40 for the Training Compute Hours 

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@tech_christine @ryanhos Technology Used •Ruby (No Rails) •Rspec •Ruby Vision API Client Libraries •Google Cloud Storage •Rmagick (Ruby binding to Imagemagick) •MagicCloud tag cloud gem

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@tech_christine @ryanhos All the code https://github.com/hi-christine/cloud-vision-insta

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@tech_christine @ryanhos Reference Links •https://cloud.google.com/vision/ •https://cloud.google.com/vision/docs/ •https://googleapis.github.io/google-cloud-ruby/docs/ •https://github.com/GoogleCloudPlatform/ruby-docs- samples/blob/master/vision/quickstart.rb •https://github.com/zverok/magic_cloud

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@tech_christine @ryanhos All the instagram accounts* @ripleyandrue @visit_nebraska @wolffolins @expertvagabond @iloveny @letterfolk @myraswim @visitcalifornia @nationalportraitgallery @nike * and none were harmed in the making of this talk