docker环境部署

1. 拉取基础镜像

项目所需cuda10.2+cudnn7.6.5+ubuntu18.04

cpp 复制代码

docker pull docker.1ms.run/misterlong/cuda:cuda10.2-cudnn7.6.5-torch1.10-miniconda3-devel-ubuntu18.04

镜像地址：cuda10.2

找了一个镜像源地址拉取成功毫秒镜像

2.运行docker

拉取成功后

bash 复制代码

docker image ls

查看拉取的image

bash 复制代码

docker run --gpus all -it --name my_base_env \
  docker.1ms.run/misterlong/cuda:cuda10.2-cudnn7.6.5-torch1.10-miniconda3-devel-ubuntu18.04

即进入docker中

3.更新cudnn

拉去的镜像为7.6.5，tensorrt需要8+，所以更新cudnn

卸载cudnn

bash 复制代码

dpkg -r libcudnn7-dev libcudnn7
apt autoremove
sudo rm -rf /usr/local/cuda/include/cudnn*.h
sudo rm -rf /usr/local/cuda/lib64/libcudnn*

验证

bash 复制代码

dpkg -l | grep cudnn

安装cudnn

bash 复制代码

tar -zxvf cudnn-10.2-linux-x64-v8.1.1.33.tgz   
cp cuda/include/cudnn*.h /usr/local/cuda/include/
cp cuda/lib64/libcudnn* /usr/local/cuda/lib64/
chmod a+r /usr/local/cuda/include/cudnn*.h /usr/local/cuda/lib64/libcudnn*
ldconfig

验证

bash 复制代码

cat /usr/local/cuda/include/cudnn_version.h | grep CUDNN_MAJOR -A 2

3. 安装opencv

本地opencv文件传入docker

在宿主机新建终端后

bash 复制代码

docker cp /home/yfzx/下载/opencv4.2.0.zip my_base_env:/home/yfzx/env/

bash 复制代码

unzip opencv4.2.0.zip
cd opencv4.2.0
mkdir build

编译

bash 复制代码

 cmake -DCMAKE_BUILD_TYPE=Release -DCMAKE_INSTALL_PREFIX=/usr/local/opencv4.2 -DOPENCV_EXTRA_MODULES_PATH=/home/yfzx/env/opencv4.2.0/opencv_contrib-4.2.0/modules -DOPENCV_GENERATE_PKGCONFIG=ON -DWITH_CUDA=ON -DOPENCV_DNN_CUDA=ON -DOPENCV_ENABLE_NONFREE=ON -DBUILD_EXAMPLES=OFF -DBUILD_TESTS=OFF -DBUILD_PERF_TESTS=OFF -DCUDA_ARCH_BIN=5.3 ..

bash 复制代码

make -j6
make install

4. 安装tensorrt

bash 复制代码

docker cp ./TensorRT-7.2.3.4.Ubuntu-18.04.x86_64-gnu.cuda-10.2.cudnn8.1.tar.gz my_base_env:/home/yfzx/env/
tar -zxvf TensorRT-7.2.3.4.Ubuntu-18.04.x86_64-gnu.cuda-10.2.cudnn8.1.tar.gz
cd TensorRT-7.2.3.4
sudo cp -r include/* /usr/local/cuda/include/
sudo cp -r lib/* /usr/local/cuda/lib64/

5.seetaface

宿主机

bash 复制代码

docker cp ./seetaface6_ubuntu.zip my_base_env:/home/yfzx/env/

docker：

bash 复制代码

cp -r ./seetaface6_ubuntu /usr/local/seetaface6

5.环境变量

bash 复制代码

export PATH=/usr/local/cuda-10.2/bin:$PATH
export LD_LIBRARY_PATH=/usr/local/cuda-10.2/lib64:$LD_LIBRARY_PATH 
export LD_LIBRARY_PATH=/home/yfzx/env/TensorRT-7.2.3.4/lib:$LD_LIBRARY_PATH

6. 动态库配置

cd /etc/ld.so.conf.d
sudo vim cuda.conf
- 添加/usr/local/cuda-10.0/lib64
sudo vim darknet.conf
- 添加/usr/local/darknet/lib
sudo vim opencv4.conf
- 添加/usr/local/opencv4.2/lib
sudo vim seetaface6.conf
- 添加/usr/local/seetaface6/lib64