Supercon 2017 Badge – Software Orientation

With the focus on getting the panning base up and running before Supercon weekend, I haven’t spent as much time as I had wanted on software side. The camera badge source code was released a few weeks ago and were constantly getting updated as the weekend got closer. (Differences between the prototype and production boards, plus other fixes.) I had wanted to keep up to date with the software but my project investigation and the pan base took up all the time I had to spend on this project.

As soon as I had two bases up and running, I went to the early check-in and badge hacking session Friday afternoon. It started at noon and I thought showing up at 3pm would still allow some time to work. I did get some time to work, but I also found that plenty of people arrived before I did and there were no table space remaining.


Oh well. At least I have the badge in hand now. The first thing I did was to perform a quick test. The camera badge came with a video record option, which I intend to dissect for my time-lapse video app. But until then, I could do a real-time video captured while panning on my base to show the basic concept works.

Another bonus of getting the badge in hand is that I was immediately more productive learning the code. The source code was informative, the documentation online was helpful, but my brain needed the anchor of actually seeing the code running. It’s was a great help to play with a menu with my hands, then go back to read the code drawing that menu. The code made a lot more sense after seeing it in action.

I dove into the basic app support framework, and after I understood the basic structure, switched to analyzing the camera app. By the end of the evening I understood enough to know how to modify the camera app to restrict the video recording frame rate to one frame per second. This artificially limited rate much more closely resembles what I would want to do in my time lapse app.

Unfortunately the playback frame rate is “accurate” in the sense it tries to play one frame per second. I have more learning ahead of me before I start writing my own time-lapse app. As a short term workaround, just to see things work with what I have, I copied the file to my computer and used ffmpeg to convert the frame rate of my end-of-evening milestone video.

(The project discussed in this blog post is publicly available on Github)

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