Okay, so I’ve been wanting to track how many people come in and out of my buddy’s retail store. He’s been having trouble figuring out his peak hours and staffing correctly, you know? So I thought, “Hey, I can build something to help with that!” I started poking around, looking for a good, simple way to do this. I don’t need anything super fancy, just something reliable.
Getting Started
I decided to go with a basic setup. Here’s what I gathered:
- A Camera: I grabbed an old webcam I had lying around. Nothing special, just something that could capture a decent image of the doorway.
- A Computer: I used a Raspberry Pi – those little things are awesome for projects like this. Plus, they’re cheap and don’t use much power.
- Some Software: This is where it got a little tricky. I needed something that could process the video feed and count people. After some digging, I found some open-source options, mostly based around OpenCV. That’s a powerful computer vision library.
The Messy Middle
Setting up the hardware was pretty straightforward. I mounted the camera above the door, making sure it had a clear view of everyone entering and exiting. I connected the camera to the Raspberry Pi, and plugged the Pi into a power outlet. Easy peasy.
The software, though… that was a different story. I’m not a coder, not really. I can hack things together, but I’m no expert. I spent a lot of time Googling, reading forums, and trying different code snippets. It was frustrating, to say the least.
First, I had to get OpenCV installed and working on the Raspberry Pi. That involved a bunch of command-line stuff that I barely understood. Then, I had to find a script that would actually do the people counting. I found a few examples online, but they were all a bit… rough. They’d count the same person multiple times, or miss people entirely, or get confused by shadows. It was a mess.
I had to modify some scripts that are already in the internet, change this and that!
Making it Work (Finally!)
After a lot of trial and error (and a few curse words), I finally got something that worked reasonably well. I tweaked the code to be more sensitive to changes in the video feed, and I added some filters to reduce false positives. It wasn’t perfect, but it was good enough.
Now when I look at the output of system, I can get the number of people who are get in or get out my store!
I set up the Raspberry Pi to save the data to a simple text file. Every hour, it would record the number of people who had entered and exited. My buddy could then take that file and plug it into a spreadsheet to see his traffic patterns. Simple, but effective!
The Result
It took a while, and it wasn’t always pretty, but I finally got a working people counting system! My buddy was thrilled. He could finally see when his store was busiest, and he could adjust his staffing accordingly. He even said it helped him optimize his store layout! That made it use this to track and see how effective the change will be.
It’s not a perfect system, of course. It still makes mistakes sometimes. But it’s a huge improvement over having no data at all. And it was a fun project to work on. I learned a lot about computer vision, and I got to help out a friend. Win-win!