Inclusion in software development is important. Changing the name of the "master" branch to "main" is a simple, positive step towards creating a more inclusive environment in software development.

As you know, the default branch of a repository is usually called the "master" branch. This has very serious connotations, and has made me uncomfortable using this terminology. It just makes more sense to call it the "default" branch or the "main" branch. There is really no reason to keep calling it the "master" branch any more.

So, from now on, all my repositories will have "main" be the default branch. Instances will be "Primary" and "Secondary" instead of "master" and "slave".
No more "blacklisting" and "whitelisting". Instead this will be "allow list" and "deny list"

It has been almost a year since Dan Williams posted his message on inclusive terminology on the Linux Kernel Mailing List.  By the time the anniversary of that message comes along, I will have all my repos using the new naming convention.

It really is quite simple!

git branch -m master main

git push -u origin main

Skip the Merge Request, go to Gitlab or Github and change the default branch to "main" in Settings. Once that is done, delete the "master" branch.

If you are using CI, then you might have to modify some YAML files. Same might apply if you are using hard coded settings in third-party apps.

Let’s dump master-slave terms: they’re vague, horrible, and we’re better off without them - CDM Create Digital Music

It’s not waiting for someone to be “offended.” It’s about why anyone would be defensive about clinging to terrible terms based on horrific inhumane things. Let’s just fix this, finally.

CDM Create Digital MusicPeter Kirn - June 15, 2020

A fun project using a Raspberry Pi, cheap webcam, and Deep Learning to identify birds that visit our bird feeder. This is what my son and I decided to work on for his senior year project.

For the project, I helped him think about: how to run the project, the different elements that had to be brought together, how they would have to interact etc. He did an amazing job thinking about it and setting it up.

However, it also pulled me down the rabbit hole, getting me interested in Deep Learning, the power of the small Raspberry Pi, hardware setups, automation etc.

Iterative over engineering as a learning tool

The idea in it's simplest form, was to use an inexpensive device like the Raspberry Pi, with its camera to take pictures of the birds at the feeder, and then run it through a model that we would train, to identify the actual bird in the picture.

Birdland which is still a work-in-progress, consists of the following major parts:
The Picture. This includes taking the picture, detecting motion, reducing false triggers, and highlighting the part of the picture that has the bird.
The Model. This would be the model that is trained to identify the bird from the picture. It also meant getting to know and use Deep Learning as well as Python
Plumbing. Sending the pictures taken to the server where they are processed, and run against the model. Clean up, back up, cron jobs, APIs and all that jazz.

So I went ahead and bought a Raspberry Pi Zero W, and a camera for it. The next few posts will be about how we got Project: "Birdland" up and running.

Part 1: Basic Structure, Framework, etc‌
‌Part 2: Setting up the Raspberry Pi‌
‌Part 3: Setting up the Camera‌
‌Part 4: Setting up the Motion Capture‌
‌Part 5: ....