Okay, so I’ve been messing around with this idea of tracking how many people come into a space, and not just counting them, but also getting a feel for where they go once they’re inside. It’s like, how cool would it be to know not just that people came, but what they did?
I started digging around, and man, there’s a ton of fancy (and expensive!) systems out there. But I wanted something I could tinker with, something more… DIY. My first thought was, “Cameras! Gotta use cameras!”
The Camera Setup
I grabbed a couple of old webcams I had lying around. Nothing fancy, just basic ones. The trick was figuring out where to put them. I ended up mounting one at the entrance, pointing straight down. This one’s job was just to count heads – like a digital bouncer.
The second camera I positioned to get a wider view of the area. This one was going to be the key to understanding the “customer journey,” as the fancy reports call it. Think of it like an eye in the sky, watching where people wander.
The Software Side – Getting My Hands Dirty
Now, for the brains of the operation. I’m no coding whiz, but I’m pretty good at following instructions and patching things together. I found some open-source libraries for object detection and tracking. The entrance camera was relatively easy. I used a simple “blob detection” algorithm. Basically, it looks for moving shapes (people!) and counts them as they cross a virtual line I drew on the screen.
- Step 1: Found some Python libraries.
- Step 2: Fiddled with the blob detection code (lots of trial and error here!).
- Step 3: Drew a virtual line on the camera feed.
- Step 4: Boom! It started counting.
The “journey” camera was way harder. I experimented with a bunch of different tracking algorithms. Some were too slow, some were too jumpy, and some just plain didn’t work. It was a mess. Finally, I found one that seemed to do a decent job of following people around, even when they were partially hidden or bunched together.
Visualizing the Data – Making Sense of It All
Counting is one thing, but I wanted to see what was going on. I ended up using a simple heatmap. Basically, the software draws a colored overlay on the camera view. The more time people spend in a particular spot, the “hotter” the color gets – from cool blue to fiery red.
It was awesome! I could actually see where people tended to congregate, which paths they took most often, and even how long they lingered in certain areas. It’s like having a bird’s-eye view of the flow of people.
Still a Work in Progress
This whole thing is still very much a prototype. It’s not perfect, and there are definitely some glitches. Sometimes it loses track of people, and the heatmap can get a little messy. But, it’s mine, and I built it from scratch. That’s pretty satisfying.
Next, I want to try using a better camera, maybe one with a wider field of view. And I’m definitely going to keep tweaking the tracking algorithms to make them more accurate. Maybe even add some machine learning to the mix… who knows? The possibilities are endless!