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Jetson Docker OpenCV CUDA

  • Added support Jetpack 4.6
  • Build tested on Jetson Nano & Jetson Xavier
  • Set nvidia as default Docker runtime,
sudo nano /etc/docker/daemon.json
  • Change daemon.json to look like this,
{
    "runtimes": {
        "nvidia": {
            "path": "/usr/bin/nvidia-container-runtime",
            "runtimeArgs": []
         } 
    },
    "default-runtime": "nvidia" 
}
  • Restart Docker Service,
sudo systemctl restart docker



  • Clone repo :
cd ~
mkdir -p Github
cd Github
git clone https://github.com/Muhammad-Yunus/Jetson-Docker-OpenCV-CUDA.git
  • Build image,
cd Jetson-Docker-OpenCV-CUDA/docker
sudo chmod +x build.sh
./build.sh
  • Run Image using NVIDIA Container Runtime,
sudo docker run --rm --net=host --runtime nvidia  opencv-cuda:latest



  • Or, Pull image from Docker Hub :
docker pull yunusdev/jetson-opencv-cuda
  • Run Image using NVIDIA Container Runtime,
sudo docker run --rm --net=host --runtime nvidia  yunusdev/jetson-opencv-cuda:latest

Building on a different base container

By default, the build script builds on top of a container matching the version of Jetpack running on the host. To build with a specific base image instead, use:

./docker/build.sh --image <your base image>

For example, to build on the tensorflow-l4t container use a command like:

./docker/build.sh --image nvcr.io/nvidia/l4t-tensorflow:r32.7.1-tf2.7-py3