A Raspberry Pi motion-detecting wildlife camera (Shallow Thoughts)

A Raspberry Pi motion-detecting wildlife camera

I've been working on an automated wildlife camera, to catch birds at the feeder, and the coyotes, deer, rabbits and perhaps roadrunners (we haven't seen one yet, but they ought to be out there) that roam the juniper woodland.

This is a similar project to the PiDoorbell project presented at PyCon, and my much earlier proximity camera project that used an Arduino and a plug computer but for a wildlife camera I didn't want to use a sonar rangefinder. For one thing, it won't work with a bird feeder -- the feeder is always there, so the addition of a bird won't change anything as far as a sonar rangefinder is concerned. For another, the rangefinders aren't very accurate beyond about six feet.

Starting with a Raspberry Pi was fairly obvious. It's low power, cheap, it even has an optional integrated camera module that has reasonable resolution, and I could re-use a lot of the camera code I'd already written for PiDoorbell.

I patched together some software for testing. I'll write in more detail about the software in a separate article, but I started with the simple motion detection code posted by "brainflakes" in the Raspberry Pi forums. It's a slick little piece of code you'll find in various versions all over the net; it uses PIL, the Python Imaging Library, to compare a specified region from successive photos to see how much has changed.

One aside about the brainflakes code: most of the pages you'll find referencing it tell you to install python-imaging-tk. But there's nothing in the code that uses tk, and python-imaging is really all you need to install. I wrote a GUI wrapper for my motion detection code using gtk, so I had no real need to learn the Tk equivalent.

Once I had some software vaguely working, it was time for testing.

The hardware

One big problem I had to solve was the enclosure. I needed something I could put the Pi in that was moderately waterproof -- maybe not enough to handle a raging thunderstorm, but rain or snow can happen here at any time without much warning. I didn't want to have to spend a lot of time building and waterproofing it, because this is just a test run and I might change everything in the final version.

I looked around the house for plastic objects that could be repurposed into a camera enclosure. A cookie container from the local deli looked possible, but I wasn't quite happy with it. I was putting the last of the milk into my morning coffee when I realized I held in my hand a perfect first-draft camera enclosure.

A milk carton must be at least somewhat waterproof, right? Even if it's theoretically made of paper.

I could use the flat bottom as a place to mount the Pi camera with its two tiny screw holes,

and then cut a visor to protect the camera from rain.

It didn't take long to whip it all together: a little work with an X-acto knife, a little duct tape. Then I put the Pi inside it, took it outside and bungeed it to the fence, pointing at the bird feeder.

A few issues I had to resolve:

Raspbian has rather complicated networking. I was using a USB wi-fi dongle, but I had trouble getting the Pi to boot configured properly to talk to our WPA router. In Raspbian networking is configured in about six different places, any one of which might do something like prioritize the not-connected eth0 over the wi-fi dongle, making it impossible to connect anywhere. I ended up uninstalling Network Manager and turning off ifplugd and everything else I could find so it would use my settings in /etc/network/interfaces, and in the end, even though ifconfig says it's still prioritizing eth0 over wlan0, I got it talking to the wi-fi.

I also had to run everything as root. The python-picamera module imports RPi.GPIO and needs access to /dev/mem, and even if you chmod /dev/mem to give yourself adequate permissions, it still won't work except as root. But if I used ssh -X to the Pi and then ran my GUI program with sudo, I couldn't display any windows because the ssh permission is for the "pi" user, not root.

Eventually I gave up on sudo, set a password for root, and used ssh -X root@pi to enable X.

The big issue: camera quality

But the real problem turned out to be camera quality.

The Raspberry Pi camera module has a resolution of 2592 x 1944, or 5 megapixels. That's terrific, far better than any USB webcam. Clearly it should be perfect for this tast.

Update: see below. It's not a good camera, but it turns out I had a lens problem and it's not this bad.

So, the Pi camera module might be okay if all I want is a record of what animals visit the house. This image is good enough, just barely, to tell that we're looking at a house finch (only if we already rule out similar birds like purple finch and Cassin's finch -- the photo could never give us enough information to distinguish among similar birds). But what good is that? I want decent photos that I can put on my web site.

I have a USB camera, but it's only one megapixel and gives lousy images, though at least they're roughly in focus so they're better than the Pi cam.

So now I'm working on a setup where I drive an external camera from the Pi using gphoto2. I have most of the components working, but the code was getting ugly handling three types of cameras instead of just two, so I'm refactoring it. With any luck I'll have something to write about in a week or two.

Meanwhile, the temporary code is in my github rpi directory -- but it will probably move from there soon.

I'm very sad that the Pi camera module turned out to be so bad. I was really looking forward to buying one of the No-IR versions and setting up a night wildlife camera. I've lost enthusiasm for that project after seeing how bad the images were. I may have to investigate how to remove the IR filter from a point-and-shoot camera, after I get the daylight version working.

Update, a few days later: It turns out I had some spooge on the lens. It's not quite as bad as I made it out to be. Here's a sample. It's still not a great camera, and it can't focus anywhere near as close as the 2 feet I've seen claimed -- 5 feet is about the closest mine can focus, which means I can't get very close to the wildlife, which was a lot of the point of building a wildlife camera. I've seen suggestions of putting reading glasses in front of the lens as a cheap macro adaptor.

Instead, I'm going ahead with the gphoto2 option, which is about ready to test -- but the noIR Pi camera module might be marginally acceptable for a night wildlife camera.