See the full post here ➡️ https://ubuntu.com//blog/how-to-colourise-black-white-pictures-openvino-containers-part-2
This blog is the last part of a series – don’t miss parts one and zero. We’re on a mission to demonstrate OpenVINO™ on Ubuntu containers; from the consistently outstanding developer experience to the added trust to your software supply chain. In this blog, I’ll guide you on your way to building and deploying an AI colouriser app on MicroK8s. The demo will give you a better feel of the Ubuntu in containers experience and how it makes developers’ lives easier, especially in complex environments like AI/ML.
The story so far: I misplanned my Christmas shopping and had to find a last-minute present for my grandparents (still hoping they’re not reading). Fortunately, I came across this blog. It gave me the best Christmas present idea ever: a handcrafted photo book of their childhood pictures, colourised using deep learning. Easy peasy, you think (sarcastically). But seriously, thanks to OpenVINO™ and Ubuntu containers, it is much easier than it sounds! You’ll see.
“What are you looking at?” (original picture source) Demo architecture
“As a user, I can drag and drop black and white pictures to the browser so that it displays their ready-to-download colourised version.” – said the PM (me).
For that – replied the onetime software engineer (still me) – we only need:
A fancy yet lightweight frontend component.OpenVINO™ Model Server to serve the neural network colourisation predictions.A very light backend component.
Whilst we could target the Model Server directly with the frontend (it exposes a
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