- 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
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