The IntelligentEdgeHOL walks through the process of deploying an Azure IoT Edge module to an Nvidia Jetson Nano device to allow for detection of objects in YouTube videos, RTSP streams, or an attached web cam
Hi,
I have an darknet application which I want to containerize, It has cuda dependencies so I was looking for some cuda docker image which I can use as a base image while writing the Dockerfile. I came across this repository.
I pulled the docker image toolboc/jetson-nano-l4t-cuda-cudnn-opencv on Xavier and ran It. Then did the following steps manually inside the docker container of the image:
RUN apt update && apt install -y libcanberra-gtk-module && \
rm -rf /var/lib/apt/lists/*
#GET Darknet sources
WORKDIR /usr/local/src
RUN git clone https://github.com/AlexeyAB/darknet.git && \
cd darknet && \
sed -i 's/GPU=0/GPU=1/g' Makefile && \
sed -i 's/CUDNN=0/CUDNN=1/g' Makefile && \
sed -i 's/CUDNN_HALF=0/CUDNN_HALF=1/g' Makefile && \
sed -i 's/OPENCV=0/OPENCV=1/g' Makefile && \
sed -i 's/LIBSO=0/LIBSO=1/g' Makefile && \
sed -i '/arch=compute_53/s/^#.//g' Makefile && \
make
Hi, I have an darknet application which I want to containerize, It has cuda dependencies so I was looking for some cuda docker image which I can use as a base image while writing the Dockerfile. I came across this repository.
I pulled the docker image toolboc/jetson-nano-l4t-cuda-cudnn-opencv on Xavier and ran It. Then did the following steps manually inside the docker container of the image:
But I am facing following issues: