Science Art in the Cloud: How Microsoft Azure helped me to Express Myself
summary
A cloud pipeline assembles facial landmarks from Azure Cognitive Services, aligns faces with OpenCV and blends about 13 images via Python to produce an averaged “cognitive portrait.” Images and results live in blob storage; processing runs in Azure Functions triggered by HTTP, with a 20-per-minute trial cap (20 per minute). A UWP kiosk and a Bot Framework/Telegram bot call the same backend; the exhibit runs in a museum and a public web/Telegram endpoint, producing live blended portraits successfully.
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chapters (7)
- 0:00Introduction and background
- 7:55Cloud building blocks overview
- 13:34Creating cognitive portraits
- 21:40Museum exhibit architecture
- 31:38Azure Functions implementation
- 40:09Virtual exhibit and chat bot
- 48:14Demo and conclusion
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