schemats VS megadetector-gui

This is really cool, will look into using it in future projects!

I also made a tool (https://github.com/vramework/schemats) that generates the types directly from the db, which means whenever you do a DB migration your database types automatically update. Was forked from the original schemats library a couple years ago.

I also created a lightweight library ontop of pg that is less of a query builder and more of a typed CRUD + SQL for non trivial queries (https://github.com/vramework/postgres-typed). Most queries I deal with in a day to day is usually crud so I find it a little easier, but it's much less powerful then Kysely! I fall more into the camp of writing complex queries in SQL with small helpers and writing simple ones with util functions and typescript

I'm working on a few projects, from one/two days to platforms.

The first is OS and is a simple nodeJS environment to deploy applications via lambda and express quickly. Sort of like nestJS except less decorators and more functional (https://vramework.io/). I already know of a few other colleagues that rolled their own propriety versions of this to support enterprise and cloud deployments so decided to OS it.

The other OS project is a strongly typed postgres/mysql driver. The idea is to generate typescript definitions directly from postgres (https://github.com/vramework/schemats) and then have a think layer ontop of pg-node that gives you strongly typed queries (https://github.com/vramework/postgres-typed).

An open-source project I spent a few years on the core team is https://deepstream.io/, a realtime-server that allows you to mix and match multiple streaming protocols (mqtt/websocket/others) and allow those clients to talk to each other using pub-sub and records. I'm not longer working for it but wanted to give it a shout out!

On a non OS project, I have been working on an immersive audio platform for a while now. The main goal is to allow users to pick and choose how audio books progress, and also have a live session mode which allows users to record their pulse / answer questions and a few other metrics and associate it with sentences. I pretty much built and deployed all of it but require some advice/brainstorming on how to proceed now. I built it to satisfy an itch when I was practicing shamanism during the first lockdown when I was in-between contracts / taking time off.

I also want to build a simple web-pages strategy game based around eco-education, but don't have the bandwidth . If anyone is interested in mixing together gamification and eco-village building might be a fun conversion to bounce ideas!

All the OS projects above were used to support my personal/a couple professional projects over the last few years.

Email in profile

- Elderly care / Matching platforms (marta.de)

Recently (2021) have spent my time between my own product enjamon.com (almost at launch stage), working part-time for marta.de where I built their backend office, matching algorithm and two client facing apps (as the sole developer + intern) and some open-source projects around deployment strategies and postgres/typescript node interfaces (https://github.com/vramework/schemats).

Currently looking for a job where I can work part-time (20 hours a week) or for on-demand tasks (like optimising APIs, CI pipelines, AWS infrastructure).

Contact: [email protected]

On (some) weekends I work on Megadetector GUI [0]. Megadetector [1] is an object detection model trained on millions of camera trap images and is widely used by conservationists. The issue is that it's rather technical to set up, so I made a GUI for it.

Currently working on a brand new version (not public just yet) that will use the latest MD version (v5 is way faster), better UI and most importantly GPU support out of the box.

[0] https://github.com/petargyurov/megadetector-gui

[1] https://github.com/microsoft/CameraTraps/blob/main/megadetec...

> ML to identify gorillas by their unique nose prints

Really cool stuff. I wonder if face detection is sufficient too? It has been proven to work for brown bears [0].

I have also been doing some open source work [1] to democratise object detection in this space but I haven't had the time to make improvements to the project in a while.

* [0] http://bearresearch.org/

* [1] https://github.com/petargyurov/megadetector-gui

In case any camera trap folk are here, I'm currently volunteering with the NZ Department of Conservation to build an AI-assisted image sorting tool that speeds up the weeding out of empty images.

https://github.com/petargyurov/megadetector-gui

This currently used to assist the conservation efforts of various endemic species such as the kakapo, kea and takahe. (The ML model used is not limited to just these species!)