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Software stack setup (Open3D-for-Jetson) : JetScan

Jetson Nano setup

  1. Collect Jetson nano and a > 64 gb Class 10 sd Card and other pheripherals for initial setup

  2. Follow the official Nvidia jetpack install steps from the link below:

    https://developer.nvidia.com/embedded/learn/get-started-jetson-nano-devkit#intro

  3. Setup the dev kit by following Jetsonhacks tutorials : Getting started

  4. Make sure you power up at max mode and operate in max mode Jetsonhacks tutorials : use more power

  5. Update & Upgrade

    $ sudo apt-get update & upgrade
$ sudo apt-get install python3-pip
$ sudo apt-get install python-pip

  6. Cuda path setup/check

    $ sudo ln -s /usr/local/cuda-10.2 /usr/local/cuda
$ export CPATH=/usr/local/cuda-10.2/targets/aarch64-linux/include:$CPATH
$ export LD_LIBRARY_PATH=/usr/local/cuda-10.2/targets/aarch64-linux/lib:$LD_LIBRARY_PATH
$ export PATH=/usr/local/cuda-10.2/bin:$PATH

Use More Memory

Pre - setup ( dependency corrections Cmake & EIGEN3 )

1. Purge inbuilt Cmake and install latest

$ cmake --version
$ sudo apt remove --purge cmake
$ wget https://gitlab.kitware.com/cmake/cmake/-/archive/v3.18.2/cmake-v3.18.2.tar.bz2
$ tar xvf cmake-v3.18.2.tar.bz2
$ sudo apt install libssl-dev libcurl4-openssl-dev qt4-qmake
$ sudo apt autoremove
$ cd cmake-v3.18.2/
$ ./bootstrap --system-curl
$ make -j3
$ sudo make install
$ which cmake
$ cmake --version

2. Purge inbuilt eigen3 and install latest

$ wget https://gitlab.com/libeigen/eigen/-/archive/3.3.7/eigen-3.3.7.tar.bz2
$ tar xvf eigen-3.3.7.tar.bz2
$ sudo apt remove --purge libeigen3-dev
$ sudo apt autoremove
$ cd eigen-3.3.7/
$ mkdir build && cd build
$ cmake .. -DCMAKE_INSTALL_PREFIX=/usr/local
$ sudo make install

Eigen3 edit/patch for supressing warning

$ sudo nano /usr/local/include/eigen3/Eigen/Core

in line 257 change

#include <host_defines.h>    to    #include <cuda_runtime_api.h>

Main Software stack setup

Recomended to install python packages compiled below in new Virtual Env

$ pip3 install --upgrade pip
$ pip3 install wheel
$ pip3 install numpy
$ pip3 install matplotlib
$ pip3 install cython
$ pip3 install joblib

Install OpenCV with CUDA ON (python package)

$ git clone https://github.com/mdegans/nano_build_opencv.git
$ cd nano_build_opencv
$ ./build_opencv.sh

#update the global lib path in your venv

$ ln -s /usr/local/lib/python3.6/dist-packages/cv2/python-3.6/cv2.cpython-36m-aarch64-linux-gnu.so cv2.so

Open3D Original (CPU Only) (python package)

pip3 install open3d-0.10.1.0-cp36-cp36m-linux_aarch64.whl

Open3D-for-Jetson Build (CUDA Reconstruction pipeline)

$ git clone --recursive https://github.com/devshank3/Open3D-for-Jetson.git
$ cd Open3D_for_Jetson/
$ cd util/scripts/
$ ./install-deps-ubuntu.sh
$ cd ..
$ mkdir build
$ cd build
$ cmake ..
$ make -j3

Librealsense Install by Jetsonhacks (python package)

Follow this Jetson hacks tutorials : Librealsense Jetson nano

$ git clone https://github.com/JetsonHacksNano/installLibrealsense.git
$ cd installLibrealsense

edit buildLibrealsense.sh with

$ nano  buildLibrealsense.sh

line 6  # Jetson Nano; L4T 32.2.3   to    # Jetson Nano; L4T 32.4.3
line 9  LIBREALSENSE_VERSION=v2.31.0   to   LIBREALSENSE_VERSION=v2.38.1
line 11 NVCC_PATH=/usr/local/cuda-10.0/bin/nvcc  to  NVCC_PATH=/usr/local/cuda-10.2/bin/nvcc

Finally build the Librealsense

$ ./buildLibrealsense.sh

#update the global lib path in your venv

$ ln -s /usr/lib/python3/dist-packages/pyrealsense2/python-3.6/pyrealsense2.cpython-36m-aarch64-linux-gnu.so pyrealsense2.so

Check in virtual env created

$ python3
$ import Open3D
$ import cv2
$ import pyrealsense2

Credits:

Few clean dependencies & installation steps are inspired by Nanotuxi: https://github.com/nanotuxi/jetsonNanoPatches

The Pi