booster VS axis-aws-rekognition

⚠️The abstractions proposed in this paper will be soon implemented in booster, the algorithms proposed are proven correct in this repository. A solution to a real world problem with these abstractions will be soon shared.

The Booster version 0.24.0 is capable of creating Multi Provider Rockets. Multi-provider Rockets could include implementations for different vendors in the same npm package.

Once again the standards to the rescue. Even if we were using JWT, Booster was tightly coupled to Cognito to verify the token and get the information associated with it. We decided to extract that part and use a standard token verification inside the Booster core, which works with the JWT tokens, no matter which provider you are using.

To summarize, by writing highly semantic code and letting the machine do the heavy lifting, Booster allows you to build fully functioning real-time APIs in a breeze, making everything else work out of the box, and saving a ton of time that you can use to add new use cases, write better tests, or manage elusive corner cases.

I encourage you all to try out Booster and modeling your systems around events. Learn more by visiting Booster's website, GitHub repo, or join the conversation on the Booster Discord server!

booster Booster is a high-level framework for TypeScript to build Serverless applications with built-in business-logic-level abstractions. Booster is highly opinionated and still under heavy development so be aware of that as you explore this project. I had a look a the documentation, and it is very detailed and comprehensive. This could be a project to watch.

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.