Jetson Zoo

Revision as of 19:12, 10 June 2019 by Dusty-nv (talk | contribs) (TensorFlow)
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This page contains instructions for installing various open source add-on packages and frameworks on NVIDIA Jetson, in addition to a collection of DNN models for inferencing.

Below are links to precompiled binaries built for aarch64 (arm64) architecture, including support for CUDA where applicable. These are intended to be installed on top of JetPack.

Refer to the listed forum topics for the latest updates or if you need help. Feel free to contribute to the list below if you have working software to add that is known to support Jetson.

Machine Learning

Jetson is able to natively run the full versions of popular machine learning frameworks, including TensorFlow, PyTorch, Caffe2, Keras, and MXNet.

There are also helpful deep learning examples and tutorials available, created specifically for Jetson - like Hello AI World and JetBot.


TensorFlow Logo.png
# install prerequisites
$ sudo apt-get install libhdf5-serial-dev hdf5-tools libhdf5-dev python3-pip
$ pip3 install --extra-index-url tensorflow-gpu==1.13.1+nv19.5 --user

PyTorch (Caffe2)

PyTorch Logo.png
Python 2.7 Python 3.6
v1.0.0 pip wheel pip wheel
v1.1.0 pip wheel pip wheel

note — the PyTorch and Caffe2 projects have merged, so installing PyTorch will also install Caffe2

# Python 2.7 (download pip wheel from above)
$ pip install torch-1.1.0-cp27-cp27mu-linux_aarch64.whl

# Python 3.6 (download pip wheel from above)
$ pip3 install numpy torch-1.1.0-cp36-cp36m-linux_aarch64.whl


MXNet Logo.png
# Python 2.7
sudo apt-get install -y git build-essential libatlas-base-dev libopencv-dev graphviz python-pip
sudo pip install mxnet-1.4.0-cp27-cp27mu-linux_aarch64.whl

# Python 3.6
sudo apt-get install -y git build-essential libatlas-base-dev libopencv-dev graphviz python3-pip
sudo pip install mxnet-1.4.0-cp36-cp36m-linux_aarch64.whl


Keras Logo.png

First, install TensorFlow from above.

# beforehand, install TensorFlow (
$ sudo apt-get install -y build-essential libatlas-base-dev
$ sudo pip install keras

Hello AI World

# download the repo
$ git clone
$ cd jetson-inference
$ git submodule update --init

# configure build tree
$ mkdir build
$ cd build
$ cmake ../

# build and install
$ make 
$ sudo make install



Ros logo.png
# enable all Ubuntu packages:
$ sudo apt-add-repository universe
$ sudo apt-add-repository multiverse
$ sudo apt-add-repository restricted

# add ROS repository to apt sources
$ sudo sh -c 'echo "deb $(lsb_release -sc) main" > /etc/apt/sources.list.d/ros-latest.list'
$ sudo apt-key adv --keyserver 'hkp://' --recv-key C1CF6E31E6BADE8868B172B4F42ED6FBAB17C654

# install ROS Base
$ sudo apt-get update
$ sudo apt-get install ros-melodic-ros-base

# add ROS paths to environment
sudo sh -c 'echo "source /opt/ros/melodic/setup.bash" >> ~/.bashrc'

IoT / Edge

AWS Greengrass