Raspberry PI

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Raspberry PI's (RPI) are low cost and very popular ARM devices hobby projects. BoofCV is very easy to set up and run on RPI's. Just compare my experience getting OpenCV and BoofCV up and running (article). Basically hours in a best case scenario vs minutes for BoofCV. Things change constantly so maybe it has gotten better since then. It also runs quite fast and well. Check out this these benchmark results.

As is often the case with a RPI to get everything working well and working with your hardware (i.e. a camera) there will be some assembly required. Just as an example, let's say you want to use a RPI to scan QR codes using the RPI camera you need to do the following:

  1. Replace the JDK
  2. Setup the RPI Camera
  3. Build and Run The Example Project

Got an RPI running as a desktop machine? You should run the BoofCV demonstration applications! They mostly work. Cameras can be a bit of an issue though. RPI camera requires injecting special code that the demo application's don't have. USB cameras also work but USB is slow on a RPI. Here are the steps you need to follow

  1. Replace the JDK
  2. Download and Run Demonstrations



Replacing Default Java

The default Java installation on Raspberry PI is not optimized for running on ARM and runs much, much slower than it should. You will need to download another version and use that.

  1. Download JDK built for Raspberry PI
  2. Decompress `tar -xzf jdk.tar.gz`
  3. Move to a location you like `sudo mv jdk-11 /opt`
  4. Add it to your path

Simple Example Application

Want a minimalist example? Want to scan for QR codes? Got you covered!

https://github.com/lessthanoptimal/ExampleWebcamRPI

Instructions are in the README.MD and it starts by saying to follow the instructions here... You do NOT need to build BoofCV to build that application. It will download all dependencies for you automatically.

Building BoofCV

You can build BoofCV the usual way, just make sure you use Java 11 or newer to do so and install the ARM optimized JDK! On a regular desktop it takes about 1 minute to build, but on a Raspberry PI it can take 10 minutes or so.

To build and install into your local Maven repository:

cd boofcv
./gradlew install

If you are running your Raspberry PI as a Desktop you can run the demonstration apps. Might also want to plug a camera in or setup your Raspberry PI camera as discussed below.

cd boofcv
./gradlew demonstrations
java -jar demonstrations/demonstrations.jar

Trouble Shooting:

If the `./gradlew` command fails and complains about Java 11 that means you didn't download Java 11 yet or your path is incorrect. One way to get around that is to force Gradle to use a specific JDK.

/gradlew -Dorg.gradle.java.home=/path/to/jdk-11/ demonstrations

How do I get webcams to work?

BoofCV uses Webcam Capture and in it's default configuration it doesn't work on Raspberry PI. The good news is that there is a simple fix that needs to be added to your source code to get it to run on Raspberry PI! https://github.com/sarxos/webcam-capture/wiki/How-To-Configure-Raspberry-Pi

It should also be pointed out that you don't have to use any of built in tools. You just need a way to convert the image into format that BoofCV understands. Once you got the bytes for an image that is often "simple" if you understand image formats.

The Simple Example has working code that contains the modification you need to do.


How do I use the Raspberry PI Camera?

The easiest way to access the camera is to treat it as a UVC device. This way WebcamCapture will recognize it and all the example code will work. Unfortunately, you have to tell your Raspberry PI to load the UVC driver each time you boot by doing the following (Stack Exchange):

sudo modprobe bcm2835-v4l2

It should now show up in the list of cameras if you type v4l2-ctl --list-devices. This is what I see on my system. I also have a webcam plugged in to USB that's why there are two devices:

mmal service 16.1 (platform:bcm2835-v4l2):
	/dev/video1

Logitech Webcam C930e (usb-3f980000.usb-1.1.3.1):
	/dev/video0

/dev/video1 is the device associated with the Raspberry PI camera.