OpenCV CUDA - Jetpack 6 Support

[starlight-traveler]

Hello,

With the advent of Jetpack 6.0 and with it Ubuntu LTS 22.04, I was inquiring whether or not the scripts would be updated to support the newest edition.

Some of the packages have been superseded or are not available, though I think running the commands manually still works.

[Qengineering]

Noted. I will address the issue soon. Update 2-11-2023: I can't install the pre-released JetPack 6 on my Jetson Orin Nano. It loops during bootup. Let's wait a few weeks for the official version 6 release.

[starlight-traveler]

Ahh, you would need to follow this thread, if you installed via SD Image or regular Nvidia SDK then the QSPI won't recognize it. Been an error for months:

https://forums.developer.nvidia.com/t/unable-to-flash-r36-on-orin-nano-8gb-dev-kit-using-external-storage/275185

No problem though!

[robbiesrobotics1]

Hey there @starlight-traveler and @Qengineering, I have the AGX Orin running Jetpack 6-dp and was able to update the 4.9 script to work. Jetpack 6 uses Cuda 12.2 and I believe that is why 4.8 wouldn't work for me when I tried. Below is the updated script for 4.9. I hope this is helpful!

!/bin/bash

set -e install_opencv () {

Check if the file /proc/device-tree/model exists

if [ -e "/proc/device-tree/model" ]; then

Read the model information from /proc/device-tree/model and remove null bytes

  model=$(tr -d '\0' < /proc/device-tree/model)
  # Check if the model information contains "Orin"
  echo ""
  if [[ $model == *"Orin"* ]]; then
      echo "Detecting an NVIDIA Orin Device."
  # Use always "-j 4"
      NO_JOB=4
      ARCH=8.7
      PTX="sm_87"
  elif [[ $model == *"Jetson Nano"* ]]; then
      echo "Detecting a regular Jetson Nano."
      ARCH=5.3
      PTX="sm_53"
  # Use "-j 4" only swap space is larger than 5.5GB
  FREE_MEM="$(free -m | awk '/^Swap/ {print $2}')"
  if [[ "FREE_MEM" -gt "5500" ]]; then
    NO_JOB=4
  else
    echo "Due to limited swap, make only uses 1 core"
    NO_JOB=1
  fi
  else
      echo "Unable to determine the Jetson model."
      exit 1
  fi
  echo ""

else echo "Error: /proc/device-tree/model not found. Are you sure this is a Jetson Product?" exit 1 fi

echo "Installing OpenCV 4.9.0 on your AGX Orin" echo "It will take 3.5 hours !"

reveal the CUDA location

cd ~ sudo sh -c "echo '/usr/local/cuda/lib64' >> /etc/ld.so.conf.d/nvidia-tegra.conf" sudo ldconfig

install the Jetson Nano dependencies first

if [[ $model == "Jetson Nano" ]]; then sudo apt-get install -y build-essential git unzip pkg-config zlib1g-dev sudo apt-get install -y python3-dev python3-numpy sudo apt-get install -y python-dev python-numpy sudo apt-get install -y gstreamer1.0-tools libgstreamer-plugins-base1.0-dev sudo apt-get install -y libgstreamer-plugins-good1.0-dev sudo apt-get install -y libtbb2 libgtk-3-dev v4l2ucp libxine2-dev fi

install the common dependencies

sudo apt-get install -y cmake sudo apt-get install -y libjpeg-dev libjpeg8-dev libjpeg-turbo8-dev sudo apt-get install -y libpng-dev libtiff-dev libglew-dev sudo apt-get install -y libavcodec-dev libavformat-dev libswscale-dev sudo apt-get install -y libgtk2.0-dev libgtk-3-dev libcanberra-gtk* sudo apt-get install -y python3-pip sudo apt-get install -y libxvidcore-dev libx264-dev sudo apt-get install -y libtbb-dev libdc1394-dev libxine2-dev sudo apt-get install -y libv4l-dev v4l-utils qv4l2 sudo apt-get install -y libtesseract-dev libpostproc-dev sudo apt-get install -y libswresample-dev libvorbis-dev sudo apt-get install -y libfaac-dev libmp3lame-dev libtheora-dev sudo apt-get install -y libopencore-amrnb-dev libopencore-amrwb-dev sudo apt-get install -y libopenblas-dev libatlas-base-dev libblas-dev sudo apt-get install -y liblapack-dev liblapacke-dev libeigen3-dev gfortran sudo apt-get install -y libhdf5-dev libprotobuf-dev protobuf-compiler sudo apt-get install -y libgoogle-glog-dev libgflags-dev

remove old versions or previous builds

cd ~ sudo rm -rf opencv*

download the latest version

git clone --depth=1 https://github.com/opencv/opencv.git git clone --depth=1 https://github.com/opencv/opencv_contrib.git

set install dir

cd ~/opencv mkdir build cd build

run cmake

cmake -D CMAKE_BUILD_TYPE=RELEASE \ -D CMAKE_INSTALL_PREFIX=/usr \ -D OPENCV_EXTRA_MODULES_PATH=~/opencv_contrib/modules \ -D EIGEN_INCLUDE_PATH=/usr/include/eigen3 \ -D WITH_OPENCL=OFF \ -D CUDA_ARCH_BIN=${ARCH} \ -D CUDA_ARCH_PTX=${PTX} \ -D WITH_CUDA=ON \ -D WITH_CUDNN=ON \ -D WITH_CUBLAS=ON \ -D ENABLE_FAST_MATH=ON \ -D CUDA_FAST_MATH=ON \ -D OPENCV_DNN_CUDA=ON \ -D ENABLE_NEON=ON \ -D WITH_QT=OFF \ -D WITH_OPENMP=ON \ -D BUILD_TIFF=ON \ -D WITH_FFMPEG=ON \ -D WITH_GSTREAMER=ON \ -D WITH_TBB=ON \ -D BUILD_TBB=ON \ -D BUILD_TESTS=OFF \ -D WITH_EIGEN=ON \ -D WITH_V4L=ON \ -D WITH_LIBV4L=ON \ -D WITH_PROTOBUF=ON \ -D OPENCV_ENABLE_NONFREE=ON \ -D INSTALL_C_EXAMPLES=OFF \ -D INSTALL_PYTHON_EXAMPLES=OFF \ -D PYTHON3_PACKAGES_PATH=/usr/lib/python3/dist-packages \ -D OPENCV_GENERATE_PKGCONFIG=ON \ -D BUILD_EXAMPLES=OFF \ -D CMAKE_CXX_FLAGS="-march=native -mtune=native" \ -D CMAKE_C_FLAGS="-march=native -mtune=native" ..

make -j ${NO_JOB}

directory="/usr/include/opencv4/opencv2" if [ -d "$directory" ]; then

Directory exists, so delete it

sudo rm -rf "$directory"

fi

sudo make install sudo ldconfig

cleaning (frees 320 MB)

make clean sudo apt-get update

echo "Congratulations!" echo "You've successfully installed OpenCV 4.9.0 on your NVIDIA Embedded Device" }

cd ~

if [ -d ~/opencv/build ]; then echo " " echo "You have a directory ~/opencv/build on your disk." echo "Continuing the installation will replace this folder." echo " "

printf "Do you wish to continue (Y/n)?" read answer

if [ "$answer" != "${answer#[Nn]}" ] ;then echo "Leaving without installing OpenCV" else install_opencv fi else install_opencv fi

[Qengineering]

@robbiesrobotics1 ,

Thanks for your contribution.

One question. Where is the difference? Both scripts look identical to me.

[robbiesrobotics1]

@Qengineering no problem at all! I just made a couple changes to the packages installed because there were two in the old script that aren't available for 22.04.

1. libdc1394-22-dev wasn't available so I used libdc1394-dev

2. libavresample-dev wasn't available so replaced with libswresample-dev

3. At first the script wouldn't run on my AGX because it wasn't a Nano so in the if statement when checking for device I just changed the device or "Orin" so that any orin series device would be detected. Post install I was able to verify opencv 4.9.0-dev with cuda in jtop. Additionally, after exposing the path to python3.10 I'm also able to see opencv with cuda in python.

[Qengineering]

@robbiesrobotics1 I've updated the script with your suggestions. Thanks!

[robbiesrobotics1]

@Qengineering no problem at all! I'm glad it was helpful.

[Qengineering]

Question. Are you using JetPack 6? And have you installed OpenCV with the script? It seems quite an ordeal to get it running. See issue #24. And https://forums.developer.nvidia.com/t/build-python-opencv2-with-cuda-support-for-jetpack-6-0/289016/3