Are you still collecting your feedback on paper handouts? Red, yellow, green feedback is faster, but what do you do with that? It’s so time-consuming to go through the feedback forms afterward and maybe you just don’t bother. What if you could collect feedback on a custom form, collate the data and get actionable results before your coffee gets cold?
Join me on the journey from waiting weeks to get feedback from the user group talks to have the results in less than an hour for each event. You’ll see how you can use Form Recognizer to parse the data straight from the page, what you can and can’t do right now, as well as how you can leverage other Cognitive Services to get more details from the user feedback forms!
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From Paper to Power using Azure Form Recognizer (Azure Sydney UG 2020)
1. Sydney Azure User Group
From Paper to Power
using Azure Form
Recognizer
Join the Conversation @AzureSydneyUG @jernej_kavka v3
2. SSW Senior Software Architect
Jernej Kavka (JK)
@Jernej_kavka
github.com/jernejk
jkdev.me
linkedin.com/in/jernejkavka/
.NET Core and EF Core dev at day
Cognitive Services and ML.NET dev at night
Join the Conversation @AzureSydneyUG @jernej_kavka
13. Manual labour
• ~1 hour - Scanning and quick summary
• ~1-3 hours – Manually entering data for a single
event
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14. We have a lot of events!
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15. Brisbane Full Stack User Group
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20. It’s a lot of work
• Up to 100 attendees per event
• Up to 5 cities “road-trip presenting”
• Up to 10 events per month
• Hours stacks up quickly with manual labour
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22. Or they will stack up really quickly
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23. Making forms digital
• Works well on virtual events!
• Doesn’t work on a physical event
• Participants don’t like copying links to their phones
• Most don’t like scanning QR codes
• It can work if you promise rewards (expensive 💸)
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25. What do we do now?
Demo
Azure Form Recognizer
Table of
Contents
26. Azure Form Recognizer
• Allows recognize and tag text in a form
• By default it supports
• US receipts
• Tables
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27. Custom Form Recognizer
• Train using your own forms
• Uses various cognitive services behind the scenes
• OCR
• Positioning of the labelled text
• Is done in 2 phases
• Training
• Usage
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28. Getting started
• Azure account
• https://azure.microsoft.com/en-us/free/
• PowerShell Core
• https://github.com/powershell/powershell
• Azure CLI
• https://docs.microsoft.com/en-us/cli/azure/install-azure-cli?view=azure-cli-latest
• Azure Storage Explorer
• https://azure.microsoft.com/en-au/features/storage-explorer/
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29. Quick start
• Download automation script
• https://gist.github.com/jernejk/fdb42e032a9568d42dc8c2f05bd1fc1
3
• Get started in 2 mins rather than 30+ minutes
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35. What have we learned?
• Hand writing is a challenge for AI and humans
• Form Recognizer works great with printed text
• Initial setup is a bit lengthy
• Don’t use doted lines over solid line
• Checkboxes are not yet supported
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63. Summary
• Recognizing data on Forms is easy
• Recognizing radio/checkboxes is not
• Microsoft is already working on a solution
• It took me 40+ hours for semi-generic solution
• I’ll open source images and ML.NET model
Join the Conversation @AzureSydneyUG @jernej_kavka