Tagraspberry pi

The Smart(er) Cat Feeder – Tying it Together With Code

Now that I have a Raspberry Pi that can take pictures and turn electrical sockets on and off, as well as a trained image classifier that knows my cats, it was time to stitch everything together.

The Lola Detector

The following steps were taken to construct a small program that would scan an image on demand and identify Lola (or not):

  1. Install TensorFlow on the Raspberry Pi as a Python library.
  2. Refactor the example image label Python script to start TensorFlow, load the model, and wait.
  3. Use Flask to create a URL that would kick off the image analysis function, and return a JSON object with the Lola/Maddie label probabilities.
  4. Keep this program running.

The code for the Lola Detector can be found in a Gist.

Please note, this is the first Python script I’ve ever written. Feedback (maybe) appreciated.

The Lola Feeder

Rather than use Python for the whole app (like a sane person), I opted for Node to do the rest of the stuff. A big, convoluted Node script does the following:

  1. Takes a picture with raspistill and saves it as rpicam.jpg.
  2. Sends an http request to the Lola Detector service, and waits for a response.
  3. Checks the response for a high Lola probability.
  4. If Lola is NOT found, go back to step 1.
  5. If Lola is found, send a signal via the FM transmitter to power on the cat feeder.
  6. Send a tweet with the recently taken picture to a hidden Twitter account.
  7. Send a message to IFTTT which sends me a push notification.
  8. Wait 60 seconds and send another signal to power off the feeder.
  9. Wait 90 minutes and go back to step 1.

Additionally, I have a small lamp attached to another RF power socket, and have a “cron job” that turns the lamp on for a few hours in the evening, and a few hours in the early morning.

Here’s the code for the RF thing. I also have a white noise machine, another lamp, and some Christmas lights hooked up to other RF outlets. Unfortunately, the Xmas lights outlet stopped working :(

To run and monitor both scripts, I use PM2. It’s awesome. You should use it, too.

The Smart(er) Cat Feeder – The Raspberry Pi

This is part 2 of a series describing modifications to an automatic cat feeder used to selectively feed cats. The overview can be found here:
The Smart(er) Cat Feeder Starring TensorFlow and Raspberry Pi

The Raspberry Pi 3

image curtesy raspberrypi.org

image curtesy raspberrypi.org

A Raspberry Pi 3 has just enough horsepower to run pre-trained TensorFlow apps, and a bunch of code for getting up and running on the Pi. There’s also a burgeoning IoT and hacking community, which makes is a great hub for controlling internet connected stuff.

A basic Pi setup needs a bit of hardware:

  • A SD Card. I recommend 32GB – 64GB to have plenty of room for TensorFlow models, pictures, and video.
  • 5V Power. There’s no power cord, so I got a 10ft. micro USB cable and 5V adapter.
  • A RPi case. Plenty of these out there. I got a cheap plastic one for a couple bucks on eBay.

And the basic software setup:

  • Raspbian & Pixel Desktop. I went with the new desktop GUI rather than headless to try out Pixel, and to do development and testing right on the Pi itself without another computer.
  • Add a hidden network to the Wifi list:
    sudo iwlist wlan0 scan essid [yourSSID]
  • Less cruft. Raspbian comes with too much stuff. Easy to remove, though.
  • Node.js 7
  • VNC. In case I did want to log in remotely, I had to fiddle with the video settings in

    to get a decent sized window. Using hdmi_group=2 and hdmi_mode=27 did the trick.

The Raspberry Pi Camera

Pi Camera

I read a few places that the version 1 (5MP) camera module is better with auto focus than the v2 (8MP) module, so I got a v1 from eBay for about $15. I’m not dissappointed. I ended up using 600×600 pictures in the project anyway, so extra megapixels would have been wasted, and all the features (focus, white balance, filters, rotation, etc…) work great.

There are some clones of the camera module from China for a few dollars less, but why risk it? I did, however, order a protective camera covering from China for $1. I’m still waiting on it as of this writing, though.

Remote Control Sockets and RF Transmitter


Here’s where the real fun begins. To turn the feeder (and accompanying lamp) on and off, I used remote controlled outlets, but spoofed the remote control frequencies with the Rapsberry Pi and a radio frequency (RF) transmitter attachment. In order to get the RF codes to activate the outlets, a RF receiver attachment is necessary as well. Luckily, the receiver and transmitter are sold in pairs, and are really cheap.

I followed a couple great guides for inspiration and to set up the proper tooling;

The guides above go a few extra steps and set up a web server with PHP, but I skipped that in favor of using Node (more on that in the next article). The basic steps for the setup are as follows:

  1. Install WiringPi and RFSniffer
  2. Plug in the reciever to the Raspberry Pi. Wiring Diagram
  3. Start RFSniffer.
  4. Push all the buttons on the remote control, and write down all the codes. It will look something like
    Received 21811
    Received pulse 192
    Received 21813
    Received pulse 192
  5. Plug in the transmitter to the Raspberry Pi.
  6. Test the codes with codesend. Be sure to substitute in your own code and pulse values read from RFSniffer.
    ./codesend 21811 -l 192 -p 0

When buying outlets, the popular choice is ETekCity. Amazon was sold out of these when I was looking, so I got another brand. One of the outlets broke a day later, so I’d recommend ETekCity.

Also, the first RF Transmitter I got was busted. I noticed that the circuitboard was slightly different than those pictured in the guides I used. Instead of ‘data’ printed on the transmitter, it said ‘ADAT’. I returned the set, and ordered a receiver/transmitter with ‘DATA’ and everything worked fine.

BAD! Avoid this one!

BAD! Avoid this one!

GOOD! Buy this kind!

GOOD! Buy this kind!

Good to Go!

With the Raspberry Pi set up with a working camera and the ability to turn electronic devices on and off, the stage was set. The rest was just a simple matter of programming…

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