oak-examples

I happen to use a few of their cameras, and they generally work as advertised (satisfied Kickstarter backer for OAK D and OAK D lite, probably going to buy the OAK D pro at some point). But, while I did indeed pay less than 250 for them individually, their current active depth offerings are $350(and while my oak d is fine for my lit, varied environment, I do often wish it was a little more accurate). I thought the Lite was also around $200 but it's actually $150 as you said. It's a pretty good little platform for the price. Be sure to check out the experimental repo too : https://github.com/luxonis/depthai-experiments/tree/master/

I use DepthAI cameras for a bunch of CV/ML stuff [https://shop.luxonis.com/] (the models run on-camera the most part) with a Jetson Nano Orin as the microcontroller. I used to use just the Jetson Nano but Nvidia is trying hard to get people on the new Orin, so I finally paid the Nvidia tax and developing for it became exciting again. But in your case, any raspberry pi would work since the detection events are not processed on the raspberry pi and the camera processor is relatively beefy. Check out their gen 2 examples for some of the models related to your task. Although looking at crowd counting example [https://github.com/luxonis/depthai-experiments] it may not run fast enough for your needs. But if you had the processing power freed up on the raspberry pi, possibly you could just display the 30fps frames and loosely sync the person bou