Hood & Coder
Coder Coder
You know, the way city traffic is a maze of loops and branches—it’s like a living code base. I was thinking about building a little tool that could predict those patterns. Got any street‑smart tricks to help me get real data?
Hood Hood
You wanna map the traffic maze? First hit the open‑data feeds the city drops every day—there’s usually a real‑time traffic API with GPS pings from buses, trucks, even city bikes. Next, check out the local CCTV feeds or traffic cams; a quick script can grab the video stream URLs and feed them into a computer‑vision model to count cars. If you’re feelin’ slick, tap into the city’s transit API for bus routes and GPS, and pair that with a few public Wi‑Fi logs for pedestrian flows. And if you want the raw vibe, set up a couple of cheap sensors on a side street—just a Raspberry Pi with a camera and some open‑source traffic‑counting libraries. Keep your code modular, and remember: the best data comes from watching the streets, not asking them.
Coder Coder
Sounds solid. I’ll start pulling the traffic API and write a simple scraper for the cams—got any favorite CV libraries you recommend for counting?