# 是否使用GPU(即是否使用 CUDA) WITH_GPU=OFF # 是否使用MKL or openblas,TX2需要设置为OFF WITH_MKL=ON # 是否集成 TensorRT(仅WITH_GPU=ON 有效) WITH_TENSORRT=OFF # 是否使用2.0rc1预测库 USE_PADDLE_20RC1=OFF # TensorRT 的include路径 TENSORRT_INC_DIR=/path/to/tensorrt/lib # TensorRT 的lib路径 TENSORRT_LIB_DIR=/path/to/tensorrt/include # Paddle 预测库路径 PADDLE_DIR=/path/to/fluid_inference/ # Paddle 的预测库是否使用静态库来编译 # 使用TensorRT时,Paddle的预测库通常为动态库 WITH_STATIC_LIB=OFF # CUDA 的 lib 路径 CUDA_LIB=/path/to/cuda/lib # CUDNN 的 lib 路径 CUDNN_LIB=/path/to/cudnn/lib MACHINE_TYPE=`uname -m` echo "MACHINE_TYPE: "${MACHINE_TYPE} if [ "$MACHINE_TYPE" = "x86_64" ] then echo "set OPENCV_DIR for x86_64" # linux系统通过以下命令下载预编译的opencv mkdir -p $(pwd)/deps && cd $(pwd)/deps wget -c https://bj.bcebos.com/paddleseg/deploy/opencv3.4.6gcc4.8ffmpeg.tar.gz2 tar xvfj opencv3.4.6gcc4.8ffmpeg.tar.gz2 && cd .. # set OPENCV_DIR OPENCV_DIR=$(pwd)/deps/opencv3.4.6gcc4.8ffmpeg/ elif [ "$MACHINE_TYPE" = "aarch64" ] then echo "set OPENCV_DIR for aarch64" # TX2平台通过以下命令下载预编译的opencv mkdir -p $(pwd)/deps && cd $(pwd)/deps wget -c https://paddlemodels.bj.bcebos.com/TX2_JetPack4.3_opencv_3.4.10_gcc7.5.0.zip unzip TX2_JetPack4.3_opencv_3.4.10_gcc7.5.0.zip && cd .. # set OPENCV_DIR OPENCV_DIR=$(pwd)/deps/TX2_JetPack4.3_opencv_3.4.10_gcc7.5.0/ else echo "Please set OPENCV_DIR manually" fi echo "OPENCV_DIR: "$OPENCV_DIR # 以下无需改动 rm -rf build mkdir -p build cd build cmake .. \ -DWITH_GPU=${WITH_GPU} \ -DWITH_MKL=${WITH_MKL} \ -DWITH_TENSORRT=${WITH_TENSORRT} \ -DTENSORRT_LIB_DIR=${TENSORRT_LIB_DIR} \ -DTENSORRT_INC_DIR=${TENSORRT_INC_DIR} \ -DPADDLE_DIR=${PADDLE_DIR} \ -DWITH_STATIC_LIB=${WITH_STATIC_LIB} \ -DCUDA_LIB=${CUDA_LIB} \ -DCUDNN_LIB=${CUDNN_LIB} \ -DOPENCV_DIR=${OPENCV_DIR} make echo "make finished!"