zlacker

>>theamk+(OP)
I keep wanting to see the "Rainbows End" style experiment.

The common reaction to surveillance seems to be similar to how we diet. We allow/validate a little bit of the negative agent, but try to limit it and then discuss endlessly how to keep the amount tamped down.

One aspect explored/hypothesized in Rainbows End, is what happens when surveillance becomes so ubiquitous that it's not a privilege of the "haves". I wonder if rather than "deflocking", the counter point is to surround every civic building with a raft of flock cameras that are in the public domain.

Just thinking the contrarian thoughts.

>>travis+zh
I started building ALPR and speed detection systems for my house based on RTSP feed. I kind of want to finish this with an outdoor TV that has a leaderboard of the drivers that drive the fastest and their license plate in public display on my property, but visible to the street. In part to make my neighbors aware of how powerful ALPR technology is now, but also many of my neighbors should slow the heck down. I am not sure how popular this would be, but also I kind of like starting the right kind of trouble :)

>>bitexp+Ty
I'm curious what does your hardware/software stack look like for your ALPR system?

>>AdamJa+B21
It is very janky. The speed camera I have an old Core i5 that is running YOLOv8 on the integrated GPU and it can just /barely/ handle 30FPS of inference. The code is all Python and vibe coded (for science). The speed camera needs a perpendicular view to work best for how I set it up (measuring two reference points with a known distance). So the ALPR camera is separate and I basically just buffer video and built this ultra janky scheme where I call an HTTP endpoint and it saves the last few seconds and then I batch process to associate the plate later in the web app. It is all CSV and plain files; this is a perfect append only DB scenario. Eventually it will need the wonders of the big data format SQLite probably, but I am sure Claude will know what to do ;) The long term solution would be to have a proper radar circuit and two cameras facing both road directions to capture the rear plate as people often don't use front plates here even though they are required to by law.

(the point, though, is you don't need a lot of GPU power to do say YOLOv8 inference on the pre-trained models) and OpenCV makes this all pretty darn easy.