automated-garden VS axis-aws-rekognition

I created babyapi with the goal of providing the simplest path to a full REST API. It started as a humble package that used generics to reduce code duplication in my automated-garden API. After breaking it out into its own repository, I added the optional HATEOAS extension which sets up automatic hypermedia linking. Now you can easily create a REST API which achieves all levels in the Richardson maturity model using babyapi.

When thinking about duplicated code in my automated-garden project, the first thing that comes to mind is all of my API handlers. The server side of this application implements a few straightforward CRUD APIs following RESTful principles. Each resource type implements handlers for the different HTTP verbs and mostly interacts with the storage layer. I created a very simple setup for the API handlers following this formula:

For us, this is a big step towards bringing AWS into our assembly process to enable other use cases with the same setup, at the same time, gain quick wins for us. To support the community and the speed of transformation at manufacturers, we will also release our POC (proof of concept) code at GitHub that brings the powerful OCR function from Rekognition and the result delivered over MQTT together with powerful cameras. With some simple code changes, you could quickly get the object Rekognition with thousands of supported objects/scenes and custom labels to train it for your own object detection with a few images.

axis-aws-rekognition Lezgin Bakircioglu got in touch this week to tell me about this project and how they are integrating AI services such as AWS Rekognition into the Axis range of cameras in order to do OCR. He has put together this blog post, Boosting the assembly process with AWS serverless & Axis camera to help you understand how this all fits together. This is still experimental, so get in touch with Lezgin if you think this is something you would like to contribute to.