How I Fought a Feathered Fish Thief (An AI and Zero-Violence Approach)#
You know those problems that sneak up on you when you’re just trying to enjoy your peaceful backyard? Mine came with wings—and a taste for my beloved fish.
For months, a certain gray heron had been helping itself to my garden pond like it was a free buffet. Elegant? Yes. Annoying? Also yes. As much as I admire wildlife, this bird was seriously testing my koi budget.
I wanted to solve the problem like an engineer, not like Elmer Fudd. So no nets, no spikes, no scarecrows. Definitely no harm to animals. My goal? Build a smart detection system that could identify the heron with high accuracy—and then gently (but firmly) encourage it to leave. Think: a burst of water, a sound cue, or maybe just turning on the fountain.
⚠️ Heads-up: This post kicks off a mini-series where I develop this heron-hunting (non-lethally, of course) detection system from scratch. It’s both a passion project and a technical showcase—demonstrating real-world software development techniques in the wild. Expect more deep dives, diagrams, code snippets, and caffeinated troubleshooting over the coming days and weeks.
🧠 The Plan#
Here’s what I needed:
- An IP webcam overlooking the pond
- A custom-trained object detection model
- A bit of automation to trigger a sprinkler or fountain
- Zero false positives (sorry dogs, sorry family)
Simple enough. But as always with AI, the devil is in the data.
🎥 Capturing the Culprit#
Over the course of several days (fine, weeks), I collected footage from my webcam. A lot of it was exactly what you’d expect from backyard surveillance—dogs trotting by, family members doing some casual gardening, and the occasional dramatic leaf blowing across the lens.
But for every dozen mundane clips, there was that one golden moment: bam—the gray heron, elegantly sneaking in like it owned the place.
I trimmed and annotated both the exciting and the uneventful: clear heron sightings, yes, but also frames without any animals (background images), and others featuring dogs or humans. This variety was crucial for training the model to recognize the heron and ignore non-targets. Was this annotation process thrilling? Not in the slightest. Was it absolutely essential? 100%.
🏋️♂️ Training the Model#
Once I had a solid dataset, I trained a custom object detection model using YOLO. Why YOLO? Because it’s fast, accurate, and works well for smaller datasets when fine-tuned properly.
I made sure to include plenty of negative examples—footage of my dogs, people, birds that aren’t herons—so the model would learn to ignore them. False positives would be more than annoying; they’d mean surprise water showers for innocent bystanders. Not ideal.
After a few rounds of hyperparameter tuning and some overfitting drama (classic), the model started performing chef’s kiss well. The heron was reliably detected, and the model learned to leave everyone else alone.
Here is a sample of the model in action:
⚙️ Putting It All Together#
With the model running live via a small server on my local network, it now constantly analyzes the webcam feed. If a heron is detected, the system sends a signal to trigger a sprinkler system (or turns on the fountain). No yelling. No chasing. Just a gentle reminder to the heron that it’s time to move on.
I also set up a dashboard with logs and detection previews—because let’s be honest, watching the system catch the heron in real-time is deeply satisfying.
🧘 Final Thoughts#
This project was a fun (and oddly personal) application of AI in the wild—literally. It was a great reminder that sometimes, our most annoying real-world problems can be solved with a bit of code, a decent dataset, and a touch of creativity.
Most importantly: no animals were harmed. The heron lives on—just not at my pond.
If you’re interested in building something similar, or if you’re being outsmarted by an unusually clever bird, feel free to reach out. AI’s not just for the cloud—sometimes, it’s for your backyard.
Got questions? Want to see the code or model details? Let’s connect!
Fun fact: YOLO originally stood for “You Only Look Once” — which is exactly how many chances my fish get when that heron shows up.