RidgeRun and Arducam NVIDIA Jetson Demo - Installing Instructions - Docker instructions
RidgeRun and Arducam NVIDIA®Jetson™Demo |
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Installing Instructions |
Executing the demo |
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Docker instructions
This guide provides instructions to run a docker container that has the evaluation products of RidgeRun and all the dependencies required for the demo already installed.
The images are available in the docker hub, to run these images on your target board, you only require docker and Nvidia run time.
Docker Hub
Download the Docker image on the Jetson Orin NX as follows.
- For Orin NX:
sudo docker pull ridgerun/products-evals-demos:jp_5x_with_ds_6.2
Running the image
For this step, you need to have Nvidia run time.
sudo docker run --device /dev/video0 --name jetson_demo --net=host --runtime nvidia --ipc=host -v /tmp/.X11-unix/:/tmp/.X11-unix/ -v /tmp/argus_socket:/tmp/argus_socket --cap-add SYS_PTRACE --privileged -v /dev:/dev -v /proc:/writable_proc -e DISPLAY=$DISPLAY -it ridgerun/products-evals-demos:jp_5x_with_ds_6.2 /demo.sh
Whenever you need to run the image again, please use the following commands.
sudo docker start jetson_demo
sudo docker attach jetson_demo
Output:
nvidia@ubuntu:~$ sudo docker attach jetson_demo (rr-eval) root@ubuntu:/opt/nvidia/deepstream/deepstream-6.2$
Afterwards, you can run any evaluation version of RidgeRun's products.
(rr-eval) root@ubuntu:/$ ls RR_EVALS/ cuda-stitching-v0.8.5-gst-1.16-jetson-t234-r35.1.0-eval cuda-undistort-v0.2.4-gst-1.16-jetson-t234-r35.1.0-eval gst-emboverlay-v1.0.0-gst-1.16-jetson-t234-r35.1.0-eval gst-prerecord-v1.6.0-gst-1.16-jetson-t234-r35.1.0-eval gst-ptzr-v0.7.0-gst-1.16-jetson-t234-r35.1.0-eval gst-qt-overlay-v0.6.0-gst-1.16-jetson-t234-r35.1.0-eval gst-rtsp-sink-v0.11.2-gst-1.16-jetson-t234-r35.1.0-eval gst-sei-v0.3.1-gst-1.16-jetson-t234-r35.1.0-eval gst-webrtc-wrapper-v0.9.0-gst-1.16-jetson-t234-r35.1.0-eval libcudaisp-v0.1.1-gst-1.16-jetson-t234-r35.1.0-eval libmisb-v0.1.0-gst-1.16-jetson-t234-r35.1.0-eval librrmotiondetection-develop-gst-1.16-jetson-t234-r35.1.0-eval
After following all the steps the result should be a working docker container all set for executing the demo.