1、deepstream6.0 x86安装

deepstream x86架构安装

1、sudo apt install nvidia-driver-470

2、安装cuda11.4 相对应的cudnn

安装完记得添加环境变量

3、安装依赖

sudo apt install \
libssl1.0.0 \
libgstreamer1.0-0 \
gstreamer1.0-tools \
gstreamer1.0-plugins-good \
gstreamer1.0-plugins-bad \
gstreamer1.0-plugins-ugly \
gstreamer1.0-libav \
libgstrtspserver-1.0-0 \
libjansson4 \
gcc \
make \
git \
python3

4、Install TensorRT 8.0.1

①运行如下命令

echo "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64 /" | sudo tee /etc/apt/sources.list.d/cuda-repo.list
wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/7fa2af80.pub
sudo apt-key add 7fa2af80.pub
sudo apt-get update

②Download TensorRT 8.0.1 GA for Ubuntu 18.04 and CUDA 11.3 DEB local repo package from: https://developer.nvidia.com/compute/machine-learning/tensorrt/secure/8.0.1/local_repos/nv-tensorrt-repo-ubuntu1804-cuda11.3-trt8.0.1.6-ga-20210626_1-1_amd64.deb

③安装

sudo dpkg -i nv-tensorrt-repo-ubuntu1804-cuda11.3-trt8.0.1.6-ga-20210626_1-1_amd64.deb

sudo apt-key add /var/nv-tensorrt-repo-ubuntu1804-cuda11.3-trt8.0.1.6-ga-20210626/7fa2af80.pub

sudo apt-get update

sudo apt-get install libnvinfer8=8.0.1-1+cuda11.3 libnvinfer-plugin8=8.0.1-1+cuda11.3 libnvparsers8=8.0.1-1+cuda11.3 libnvonnxparsers8=8.0.1-1+cuda11.3 libnvinfer-bin=8.0.1-1+cuda11.3 libnvinfer-dev=8.0.1-1+cuda11.3 libnvinfer-plugin-dev=8.0.1-1+cuda11.3 libnvparsers-dev=8.0.1-1+cuda11.3 libnvonnxparsers-dev=8.0.1-1+cuda11.3 libnvinfer-samples=8.0.1-1+cuda11.3 libnvinfer-doc=8.0.1-1+cuda11.3

5、安装librdkafka

1.下载

$ git clone https://github.com/edenhill/librdkafka.git

2.配置

cd librdkafka
git reset --hard 7101c2310341ab3f4675fc565f64f0967e135a6a
./configure
make
sudo make install

3、

 sudo mkdir -p /opt/nvidia/deepstream/deepstream-6.0/lib
 sudo cp /usr/local/lib/librdkafka* /opt/nvidia/deepstream/deepstream-6.0/lib

6、安装deepstream6.0

1、下载源码

https://developer.nvidia.com/deepstream_sdk_v6.0.1_x86_64tbz2

编译：

sudo tar -xvf deepstream_sdk_v6.0.1_x86_64.tbz2 -C /
cd /opt/nvidia/deepstream/deepstream-6.0/
sudo ./install.sh
sudo ldconfig

7、安装gstreamer

 sudo apt-get install libgstreamer-plugins-base1.0-dev libgstreamer1.0-dev    libgstrtspserver-1.0-dev libx11-dev

8、python deepstream安装

   $ sudo apt-get install python-gi-dev
   $ export GST_LIBS="-lgstreamer-1.0 -lgobject-2.0 -lglib-2.0"
   $ export GST_CFLAGS="-pthread -I/usr/include/gstreamer-1.0 -I/usr/include/glib-2.0 -I/usr/lib/x86_64-linux-gnu/glib-2.0/include"
   $ git clone https://github.com/GStreamer/gst-python.git
   $ cd gst-python
   $ git checkout 1a8f48a
   $ ./autogen.sh PYTHON=python3
   $ ./configure PYTHON=python3
   $ make
   $ sudo make install

9、根据官方文档安装完后缺乏一个pyds.so文件

cd deepstream_python_apps/bindings
mkdir build
cd build
cmake ..  -DPYTHON_MAJOR_VERSION=3 -DPYTHON_MINOR_VERSION=6 \
    -DPIP_PLATFORM=linux_aarch64 -DDS_PATH=/opt/nvidia/deepstream/deepstream-6.0/
make

make完后会生成一个pyds.so然后拷贝到/opt/nvidia/deepstream/deepstream/lib目录下
参考资料
https://blog.csdn.net/weixin_41562691/article/details/116793532
https://github.com/NVIDIA-AI-IOT/deepstream_python_apps/blob/master/HOWTO.md
https://docs.nvidia.com/metropolis/deepstream/dev-guide/text/DS_Quickstart.html