Getting Started with Counting Folks
So, I started looking into this whole people counting thing a while back. Wasn’t for some big corporation, more for understanding what’s happening on the ground, you know? I had this space, and I always wondered when people actually showed up, like, really. Guesses are one thing, but seeing the actual numbers, that felt like it could be useful.
First off, I looked around at the fancy stuff. You got those beam counters, thermal sensors, super expensive camera systems. Honestly, most of it felt like overkill for what I needed, and the price tags were just… wow. Didn’t make sense for me. I thought, there has to be a simpler way, maybe something I could put together myself.
My DIY Attempt
I already had a spare webcam lying around, one of those cheap USB ones. Figured I could hook it up to a small computer, maybe one of those Raspberry Pi things I’d been playing with. So, I grabbed the Pi, dusted off the webcam, and started tinkering.
Getting the camera pointing the right way took some doing. Tried taping it here, propping it there. Wanted a clear view of the entrance without being too obvious or getting blocked when things got busy. Ended up mounting it high up, angled down. That seemed to work okay after a bit of fiddling with cables and power.
Making the Computer See People
Next big step was actually getting the computer to count. This is where it got interesting. I wasn’t about to sit there watching the video feed all day, clicking a counter! I needed software.
I started looking into computer vision stuff. Sounded complicated, but I found some guides online. My first try was super basic, just looking for any movement. That was a disaster. It counted shadows, bags people put down, even a big fly once! Clearly, that wasn’t gonna work.
So, I dug deeper. Found out about things called ‘object detection models’. Basically, you can teach the computer what a person looks like. I grabbed one of these pre-trained models – didn’t have time to teach it from scratch myself. Hooked it up with some code I found and modified. It wasn’t perfect right away. Sometimes it missed people if they walked too close together, sometimes it counted someone twice if they lingered by the door. Took a lot of tweaking settings, adjusting the detection area on the screen, that sort of thing. Felt more like art than science sometimes.
Collecting and Looking at the Numbers
Once it started counting somewhat reliably, I needed to actually keep the counts. At first, I just had it writing to a simple text file every minute. Like: `Timestamp, CountIn, CountOut`. Crude, but it worked!
After running it for a few days, I started pulling that data into a spreadsheet. Just simple stuff, really. Made graphs showing people coming in hour by hour. Right away, I saw patterns. The morning rush was obvious, but there was also this weird lull mid-afternoon I hadn’t really noticed before, and then a smaller peak later on.
- Checked counts against daily sales. Yep, more people generally meant more sales, but not always! Some busy periods had low sales value. Interesting.
- Compared weekdays versus weekends. Big difference, as expected, but the shape of the traffic flow during the day was different too.
- Noticed the door area got crowded during peak times, maybe needed to rearrange things near the entrance.
This was the gold, really. Not the fancy tech, but these simple insights from basic counting. It wasn’t about complex algorithms; it was about seeing my own space in a new way, backed by actual numbers, not just gut feeling.
Was it Worth It?
Yeah, setting it up took time and some frustration. Things didn’t always work. The counting was never 100% accurate, maybe 90-95% on a good day after all the tweaks. But honestly? It didn’t need to be perfect. It just needed to be good enough to show the trends.
For me, fiddling with the tech was part of the fun, but the real payoff was understanding the rhythm of the place better. Helped make small decisions about staffing, layout, even when to schedule cleaning or restocking. Simple data, simple insights, but really useful stuff. You don’t always need the most expensive tools to get value.