forked from PulseFocusPlatform/PulseFocusPlatform
80 lines
2.1 KiB
Bash
80 lines
2.1 KiB
Bash
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# 是否使用GPU(即是否使用 CUDA)
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WITH_GPU=OFF
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# 是否使用MKL or openblas，TX2需要设置为OFF
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WITH_MKL=ON
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# 是否集成 TensorRT(仅WITH_GPU=ON 有效)
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WITH_TENSORRT=OFF
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# paddle 预测库lib名称，由于不同平台不同版本预测库lib名称不同，请查看所下载的预测库中`paddle_inference/lib/`文件夹下`lib`的名称
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PADDLE_LIB_NAME=libpaddle_inference
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# TensorRT 的include路径
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TENSORRT_INC_DIR=/path/to/tensorrt/include
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# TensorRT 的lib路径
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TENSORRT_LIB_DIR=/path/to/tensorrt/lib
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# Paddle 预测库路径
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PADDLE_DIR=/path/to/paddle_inference
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# CUDA 的 lib 路径
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CUDA_LIB=/path/to/cuda/lib
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# CUDNN 的 lib 路径
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CUDNN_LIB=/path/to/cudnn/lib
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MACHINE_TYPE=`uname -m`
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echo "MACHINE_TYPE: "${MACHINE_TYPE}
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if [ "$MACHINE_TYPE" = "x86_64" ]
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then
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echo "set OPENCV_DIR for x86_64"
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# linux系统通过以下命令下载预编译的opencv
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mkdir -p $(pwd)/deps && cd $(pwd)/deps
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wget -c https://paddledet.bj.bcebos.com/data/opencv3.4.6gcc8.2ffmpeg.zip
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unzip opencv3.4.6gcc8.2ffmpeg.zip && cd ..
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# set OPENCV_DIR
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OPENCV_DIR=$(pwd)/deps/opencv3.4.6gcc8.2ffmpeg
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elif [ "$MACHINE_TYPE" = "aarch64" ]
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then
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echo "set OPENCV_DIR for aarch64"
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# TX2平台通过以下命令下载预编译的opencv
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mkdir -p $(pwd)/deps && cd $(pwd)/deps
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wget -c https://paddlemodels.bj.bcebos.com/TX2_JetPack4.3_opencv_3.4.10_gcc7.5.0.zip
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unzip TX2_JetPack4.3_opencv_3.4.10_gcc7.5.0.zip && cd ..
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# set OPENCV_DIR
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OPENCV_DIR=$(pwd)/deps/TX2_JetPack4.3_opencv_3.4.10_gcc7.5.0/
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else
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echo "Please set OPENCV_DIR manually"
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fi
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echo "OPENCV_DIR: "$OPENCV_DIR
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# 以下无需改动
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rm -rf build
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mkdir -p build
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cd build
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cmake .. \
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-DWITH_GPU=${WITH_GPU} \
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-DWITH_MKL=${WITH_MKL} \
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-DWITH_TENSORRT=${WITH_TENSORRT} \
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-DTENSORRT_LIB_DIR=${TENSORRT_LIB_DIR} \
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-DTENSORRT_INC_DIR=${TENSORRT_INC_DIR} \
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-DPADDLE_DIR=${PADDLE_DIR} \
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-DWITH_STATIC_LIB=${WITH_STATIC_LIB} \
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-DCUDA_LIB=${CUDA_LIB} \
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-DCUDNN_LIB=${CUDNN_LIB} \
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-DOPENCV_DIR=${OPENCV_DIR} \
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-DPADDLE_LIB_NAME=${PADDLE_LIB_NAME}
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make
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echo "make finished!"
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