Skip to content

Instantly share code, notes, and snippets.

Embed
What would you like to do?
How to Set Up the NVIDIA Jetson Nano for openFrameworks

How to Set Up the NVIDIA Jetson Nano for openFrameworks

A Step-By-Step Guide from Unboxing to Creative Coding

Getting Started

  1. Set up and Configure the Nano
  2. Set up and Configure openFrameworks

Working with Addons

  1. ofxKinect
  2. ofxKinectV2

Additional Info

Getting Started

Hardware Requirements

  1. NVIDIA Jetson Nano Developer Kit
  2. 64 GB MicroSD Card
  3. 5V, 4A Power Supply
    • The J25 power jack is 9.5 mm deep, and accepts positive polarity plugs with 2.1 mm inner diameter and 5.5 mm outer diameter.
  4. Keyboard and Mouse
  5. Monitor and HDMI or DP cable

1. Set up and Configure the Nano

Follow NVIDIA's official Getting Started With Jetson Nano Developer Kit to setup and boot the Jetson Nano.

  • There's also a Troubleshooting section if you run into any issues.
  • Remeber that if you're powering the Nano from the barrel jack, you need to add a jumper to the J48 Power Select Header pins to disable power supply via Micro-USB and enable 5V⎓4A via the J25 power jack.
  • Full hardware specs for the Jetson Nano can be found here.

After setup, there are few optional, but useful settings you might want to configure for your Nano:

2. Set up and Configure openFrameworks

Next, we need to download, configure, and build openFrameworks on the Nano.

Hat tip to Jason Van Cleave for his thorough instructions (expounded on below):

Getting the Nightly Build

openFrameworks for linuxarmv7 is currently supported in the nightly build found at the bottom of the Downloads page.

  • Get the package name that corresponds with of_v2019XXXX_linuxarmv7l_nightly.tar.gz.
  • At the time of this tutorial, the package name was of_v20190324_linuxarmv7l_nightly.tar.gz.

To download and unpack openFrameworks:

> cd ~
> wget https://openframeworks.cc/ci_server/versions/nightly/of_v20190324_linuxarmv7l_nightly.tar.gz
> tar -zxvf of_v20190324_linuxarmv7l_nightly.tar.gz

Editing MAKE files

Next, we need to edit some of openFrameworks' make files to work with the Jetson Nano.

Edit the config.shared.mk file:

> cd ~
> gedit of_v20190324_linuxarmv7l_nightly/libs/openFrameworksCompiled/project/makefileCommon/config.shared.mk

Change the line:

else ifeq ($(PLATFORM_ARCH),armv7l)

to

else ifeq ($(PLATFORM_ARCH),aarch64)

Then save and close.

Next edit the config.linuxarmv7l.default.mk file:

> gedit of_v20190324_linuxarmv7l_nightly/libs/openFrameworksCompiled/project/linuxarmv7l/config.linuxarmv7l.default.mk

Comment out the following flags:

#PLATFORM_CFLAGS += -march=armv7
#PLATFORM_CFLAGS += -mtune=cortex-a8
#PLATFORM_CFLAGS += -mfpu=neon
#PLATFORM_CFLAGS += -mfloat-abi=hard
PLATFORM_CFLAGS + = -fPIC
PLATFORM_CFLAGS + = -ftree-vectorize
PLATFORM_CFLAGS + = -Wno-psabi
PLATFORM_CFLAGS + = -pipe

and

#PLATFORM_PKG_CONFIG_LIBRARIES += glesv1_cm
#PLATFORM_PKG_CONFIG_LIBRARIES += glesv2
#PLATFORM_PKG_CONFIG_LIBRARIES += egl

Then save and close.

Recompile with New Configs

Next, we need to recompile and build the kiss and tess2 libraries with these modified settings. You can download oF's apothecary tool to recompile the libraries:

> git clone https://github.com/openframeworks/apothecary.git
> cd apothecary/apothecary
> ./apothecary -t linux download kiss
> ./apothecary -t linux prepare kiss
> ./apothecary -t linux build kiss
> ./apothecary -t linux download tess2
> ./apothecary -t linux prepare tess2
> ./apothecary -t linux build tess2

Replace oF's kiss and tess2 libraries with these newly created static libraries:

> cd ~
> sudo cp apothecary/apothecary/build/kiss/lib/linux/libkiss.a of_v20190324_linuxarmv7l_release/libs/kiss/lib/linuxarmv7l/
> sudo cp apothecary/apothecary/build/tess2_patched/build/libtess2.a of_v20190324_linuxarmv7l_release/libs/tess2/lib/linuxarmv7l/

You can also just download the libs libkiss.a and libtess.a that Jason von Cleave properly recompiled.

Finish openFrameworks Linux Setup

Now we are all set up to do openFrameworks's normal Linux Install Instructions:

> cd of_v20190324_linuxarmv7l_release/scripts/linux/ubuntu
> sudo ./install_dependencies.sh
> cd ..
> ./compileOf.sh

Test openFrameworks

You can Build and Run the allAddonsExample to test whether the built-in addons are working out of the box:

> cd of_v20190324_linuxarmv7l_release/examples/templates/allAddonsExample
> make && make run

In my nightly build, ofxSvg fails with the following error:

/home/nano/of_v20190324_linuxarmv7l_release/addons/ofxSvg/libs/svgtiny/lib/linuxarmv7l/libsvgtiny.a: error adding symbols: File in wrong format

If you comment out lines relating to ofxSvg in addons.make and then in ofApp.h, then the app should run.

Working with Addons

Here is a setup guide for working with some of the more popular addons and sensors for openFrameworks.

1. ofxKinect

openFramework's addon for the v1 Microsoft Kinect should build and run out-of-the-box (with root privilages):

> cd ~/of_v20190324_linuxarmv7l_release/examples/computer_vision/kinectExample
> make
> sudo make run

To run a ofxKinect app without root privilages, copy over libfreenect's udev rules for device access:

> cd ~/of_v20190324_linuxarmv7l_release/addons/ofxKinect
> sudo cp libs\libfreenect\platform\linux\udev\51-kinect.rules /etc/udev/rules.d

You may need to restart your system for the rules to take effect.

The Jetson Nano will run one Kinect, but it does not support running multiple Kinects.

2. ofxKinectV2

To work with the v2 Microsoft Kinect in openFrameworks, you need to first install libfreenect2. You can find their Linux Installation instructions here.

The Jetson Nano image already comes loaded with libusb >= 1.0.20, OpenGL version 4.6.0 NVIDIA 32.1.0, and CUDA 10.0.166

Install libfreenect2

> cd ~
> git clone https://github.com/OpenKinect/libfreenect2.git
> cd libfreenect2
> sudo apt-get install build-essential cmake pkg-config
> sudo apt-get install libturbojpeg0-dev

Configure OpenCL

By default, Jetson boards don't support OpenCL. So we need to add and reconfigure a few things to get libfreenect2 (and ofxKinectV2) to build with OpenCL enabled.

Start by downloading and extracting Khronos Group's OpenCL Headers from github.

Once extracted move the CL/ directory into /usr/include:

> sudo mv ~/Downloads/CL /usr/include

Now if you go into /usr/lib/aarch64-linux-gnu you can find the OpenCL library as libOpenCL.so.1. We need to add a symbolic link from libOpenCL.so.1 to libOpenCL.so:

> cd /usr/lib/aarch64-linux-gnu
> sudo ln -s libOpenCL.so.1 libOpenCL.so

Now we should be all set up to build libfreenect2 with OpenCL enabled.

Building the Shared Library

The following commands make and install libfreenect2 system-wide:

mkdir build && cd build
cmake ..
make
make install

After running cmake .., verify in the console that the Feature List has OpenCL enabled (you should see -- OpenCL yes printed out).

Set up udev rules for device access:

sudo cp ../platform/linux/udev/90-kinect2.rules /etc/udev/rules.d/

Plug in the v2 Kinect, and then run the libfreect2's example app:

./bin/Protonect

With the Protonect example, should now see RGB, Depth, and IR feeds streaming from the Kinect. If not, look through libfreenect2's Troubleshooting section.

This step needs to be working before moving forward.

Which ofxKinectV2

There are a few addons out there for working with the KinectV2 in openFrameworks, but Linux support is rare. I modifed Theo Watson's ofxKinectV2 to work for Linux. Download my fork to start:

> cd ~/of/addons
> cd git clone https://github.com/madelinegannon/ofxKinectV2.git

By default, when an openFrameworks app builds, it links to the libraries in its local libs folder. But we want libfreenect2 and libusb-1.0 to link against our system wide installations. To resolve this, move or delete these folders in ofxKinectV2/libs:

> cd ofxKinectV2/libs
> mv libfreenect2 ~/Desktop
> mv libusb ~/Desktop

Now you should only see a protonect folder in libs.

Next, we want to make sure our LD_LIBRARY_PATH is set properly, so openFrameworks knows where to search for ofKinectV2's linked libraries.

Add CUDA paths to the system environment (you should also to add these lines to your ~/.bashrc):

> export LD_LIBRARY_PATH="/usr/local/cuda/lib64:${LD_LIBRARY_PATH}"
> export PATH="/usr/local/cuda/bin:${PATH}"

A system-wide configuration of the libary path can be created with the following commands:

> echo "/usr/local/cuda/lib64" | sudo tee /etc/ld.so.conf.d/cuda.conf
> sudo ldconfig

Also add the libfreenect2 path to the system environment (you should also add this path to your ~/.bashrc):

> export LD_LIBRARY_PATH="/usr/local/lib:${$LD_LIBRARY_PATH}"

Build the example app

Everything should be set up to build and run the example app included of ofxKinectV2.

But first, just a quick note on how things get linked and built in openFrameworks on linuxarmv7:

  • When building from command line, openFramework uses the ofxKinectV2/addons_config.mk file to add all the compiler flags for the project.
    • You'll notice I've added libfreenect2 and cuda package names to the variable ADDON_PKG_CONFIG_LIBRARIES.
    • The build process looks for .pc files with the corresponding names in /usr/lib/pkgconfig.

Now we can make and run:

> make -j
> make run

Now you should see something very similar to libfreenect2 Protonect example, but with the addition of some sliders that let you easily do depth thresholding.

The framerate was not great on this. I need to see if there are ways to optimize the example app for the Nano.

Troubleshooting

I had one runtime error that really tripped me up for a bit. The ofxKinectV2 example app would build and run, and in the console it would acknowledge that it detected and opened the Kinect. However, the stream wouldn't start, and the following error would print out:

[Error] [protocol::CommandTransaction] bulk transfer failed: LIBUSB_ERROR_TIMEOUT Operation timed out

What was happening was that openFrameworks wasn't actually linking to libfreenect2.so at runtime. I fixed this by making sure that I removed the local libfreenect2 directory in ofxKinectV2/libs, and that the system-wide path to libfreenect2.so (/usr/local/lib) was also added to the LD_LIBRARY_PATH in my ~/.bashrc.

Additional Info

Helpful Resources

Tutorials

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
You can’t perform that action at this time.