• nvidia xavier部署fcos3d

    jetson xavier 部署mmdeploy

    huanyuan

    https://www.jianshu.com/p/0543229dc7b8

    sudo cp /etc/apt/sources.list /etc/apt/sources.list.backup
sudo gedit /etc/apt/sources.list

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    # 默认注释了源码镜像以提高 apt update 速度，如有需要可自行取消注释
deb https://mirrors.tuna.tsinghua.edu.cn/ubuntu-ports/ bionic main restricted universe multiverse
# deb-src https://mirrors.tuna.tsinghua.edu.cn/ubuntu-ports/ bionic main restricted universe multiverse
deb https://mirrors.tuna.tsinghua.edu.cn/ubuntu-ports/ bionic-updates main restricted universe multiverse
# deb-src https://mirrors.tuna.tsinghua.edu.cn/ubuntu-ports/ bionic-updates main restricted universe multiverse
deb https://mirrors.tuna.tsinghua.edu.cn/ubuntu-ports/ bionic-backports main restricted universe multiverse
# deb-src https://mirrors.tuna.tsinghua.edu.cn/ubuntu-ports/ bionic-backports main restricted universe multiverse
deb https://mirrors.tuna.tsinghua.edu.cn/ubuntu-ports/ bionic-security main restricted universe multiverse
# deb-src https://mirrors.tuna.tsinghua.edu.cn/ubuntu-ports/ bionic-security main restricted universe multiverse

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    sudo apt-get update

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    torch+mmcv

    https://www.freesion.com/article/99911008229/

    #cuda环境设置
export PATH="/usr/local/cuda-11.3/bin:$PATH"
export CUDA_PATH=/usr/local/cuda-11.3
export LD_LIBRARY_PATH="/usr/local/cuda-11.3/lib64:$LD_LIBRARY_PATH"

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    sudo pip3 install torch-1.9.0-cp36-cp36m-linux_aarch64.whl 


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    ceshi

    aarch64-linux-gnu-gcc‘ failed with exit status 1

    sudo pip install pyzmq==25.1.0

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    ImportError: libopenblas.so.0: cannot open

    sudo apt-get  install libopenblas-dev

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    Python 3.6.8 (default, Aug 20 2019, 17:12:48) 
[GCC 8.3.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import torch
>>> torch.__version__
'1.3.0'
>>> torch.cuda.is_available()
True
>>> torch.randn(4,4,4).cuda().mean()
tensor(-0.0479, device='cuda:0')

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    dependence

    pip install -i https://pypi.tuna.tsinghua.edu.cn/simple
-i https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple/

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    sudo pip install pyzmq==25.1.0
pip install matplotlib

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    for torchvision

    pip install --upgrade pip setuptools wheel
pip install pycocotools
pip install terminaltables
pip install Cython

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    STEP3 安装MMDETECTOIN、MMCV

    suggestion:
    pip install openmim
    mim install mmcv1.5.3
    mim install mmcls    0.25.0
    mim install mmdet2.25.1
    mim install mmsegmentation    0.25.0
    减速带算法mmdet3d pip install -e .
    for Illegal instruction(core dumped)”: export OPENBLAS_CORETYPE=ARMV8
    sudo apt install llvm
    https://github.com/traveller59/spconv to install spconv and cumm,please read README carefully ,change python version in setup.py

    安装cmake

    agx版本：
sudo chmod +x cmake-3.27.0-rc4-linux-aarch64.sh
xavier:sudo sh cmake-3.27.0-rc4-linux-aarch64.sh
# 安装过程中遇到：
# 选择1
Do you accept the license? [yn]: 
# 输入 y
# 选择2
By default the CMake will be installed in:
  "/usr/cmake-3.23.0-linux-x86_64"
Do you want to include the subdirectory cmake-3.23.0-linux-x86_64?
Saying no will install in: "/usr" [Yn]:
# 输入 n

x86版本：
1、sudo wget https://cmake.org/files/v3.18/cmake-3.18.0-Linux-x86_64.sh
sh cmake-3.18.0-Linux-x86_64.sh
2、安装包解压后
export PATH="/home/sen/motan/cmake-3.20.0-linux-x86_64/bin:$PATH"

可以使用cmake --version 查看 如果输出 cmake的版本号说明已经正确安装了cmake 


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    安装ppl.cv.

    sudo apt-get update
sudo apt-get install -y build-essential
git clone https://github.com/openppl-public/ppl.cv.git
cd ppl.cv
export PPLCV_DIR=/home/sen/motan/ppl.cv
git checkout tags/v0.7.0 -b v0.7.0
./build.sh   aarch64/cuda

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    安装onnx

    x86

    pip install onnxruntime==1.14.0

本地下载onnxruntime
export ONNXRUNTIME_DIR=$(pwd)
export LD_LIBRARY_PATH=$ONNXRUNTIME_DIR/lib:$LD_LIBRARY_PATH
echo '# set env for onnxruntime' >> ~/.bashrc
echo "export ONNXRUNTIME_DIR=${ONNXRUNTIME_DIR}" >> ~/.bashrc
echo "export LD_LIBRARY_PATH=$ONNXRUNTIME_DIR/lib:$LD_LIBRARY_PATH" >> ~/.bashrc
source ~/.bashrc

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    安装cuDNN

    export CUDNN_DIR=/usr/local/cudnn-11.3-linux-x64-v8.2.1.32/cuda
export LD_LIBRARY_PATH=$CUDNN_DIR/lib64:$LD_LIBRARY_PATH
然后解压，把inculde和lib64里的文件复制到cuda中
sudo cp -r /usr/local/cudnn-11.3-linux-x64-v8.2.1.32/cuda/include/cudnn*.h /usr/local/cuda/include
sudo cp -r /usr/local/cudnn-11.3-linux-x64-v8.2.1.32/cuda/lib64/libcudnn* /usr/local/cuda/lib64
sudo chmod a+r /usr/local/cuda/include/cudnn*.h /usr/local/cuda/lib64/libcudnn*
在/usr/local/cuda/include目录下,查看版本
vim cudnn_version.h

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    安装tensorrt

    #tensorrt-选择cp37,cp38,cp39对应python版本

    1、pip install TensorRT-8.2.3.0/python/tensorrt-8.2.3.0-cp38-none-linux_x86_64.whl
2、export TENSORRT_DIR=/usr/local/TensorRT-8.2.3.0
export LD_LIBRARY_PATH=$TENSORRT_DIR/lib:$LD_LIBRARY_PATH
3、复制tensorrt路径下的/lib、/include文件夹到对应的系统文件夹
sudo cp -r ./lib/* /usr/lib
sudo cp -r ./include/* /usr/include
4、使用python的tensorrt接口，安装pycuda
pip install pycuda
此时tensorrt不能导入，cuDNN安装完后可以

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    添加动态库
    sudo gedit /etc/ld.so.conf

    /usr/local/TensorRT-8.2.3.0/lib
/usr/local/cuda-11.3/lib64
sudo ldconfig

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    安转完后，同样可以进入Python环境，然后简单打印下版本号等信息，只要不报错就说明安装成功。
    import tensorrt
    print(tensorrt.version)
    assert tensorrt.Builder(tensorrt.Logger())

    
pip install opencv-contrib-python==4.8.0.74

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    arm

     
sudo apt-get install protobuf-compiler libprotoc-dev
 
export PATH=/usr/local/cuda/bin:${PATH}
export CUDA_PATH=/usr/local/cuda
export cuDNN_PATH=/usr/lib/aarch64-linux-gnu
export CMAKE_ARGS="-DONNX_CUSTOM_PROTOC_EXECUTABLE=/usr/bin/protoc"
 
mkdir /code
cd /code
git clone --recursive https://github.com/Microsoft/onnxruntime
git submodule update --init --recursive --progress
cd /code/onnxruntime
 
./build.sh --update --config Release --enable_pybind --build_shared_lib --build --build_wheel \
--use_openmp --use_tensorrt --tensorrt_home /usr/src/tensorrt --cuda_home /usr/local/cuda --cudnn_home /usr/lib/aarch64-linux-gnu

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    https://onnxruntime.ai/docs/build/eps.html#nvidia-jetson-tx1tx2nanoxavier

    tensorrtppl.cv.算子编译

    1、cd path-to-mmdeploy
mkdir -p build && cd build
   cmake .. \
   		 -DCMAKE_CXX_COMPILER=g++-9 \
       -DMMDEPLOY_BUILD_SDK=ON \
       -DMMDEPLOY_BUILD_SDK_PYTHON_API=ON \
       -DMMDEPLOY_BUILD_EXAMPLES=ON \
       -DMMDEPLOY_TARGET_DEVICES="cuda;cpu" \
       -DMMDEPLOY_TARGET_BACKENDS="trt" \
       -DTENSORRT_DIR=${TENSORRT_DIR} \
			-DCUDNN_DIR=${CUDNN_DIR} \
			-DONNXRUNTIME_DIR=${ONNXRUNTIME_DIR} \
       -Dpplcv_DIR=${PPLCV_DIR}/cuda-build/install/lib/cmake/ppl \
       -DMMDEPLOY_CODEBASES=all 
       
cmake .. -DCMAKE_CXX_COMPILER=g++-7 -DMMDEPLOY_BUILD_SDK=ON -DMMDEPLOY_BUILD_EXAMPLES=ON -DMMDEPLOY_BUILD_SDK_PYTHON_API=ON -DMMDEPLOY_TARGET_DEVICES="cuda;cpu" -DMMDEPLOY_TARGET_BACKENDS="ort;trt" -Dpplcv_DIR=${PPLCV_DIR}/cuda-build/install/lib/cmake/ppl -DTENSORRT_DIR=${TENSORRT_DIR} -DCUDNN_DIR=${CUDNN_DIR} -DONNXRUNTIME_DIR=${ONNXRUNTIME_DIR} -DMMDEPLOY_CODEBASES=all

2、make -j$(nproc) && make install
3、复制build中lib内所有的文件到mmdeploy/mmdeploy/lib的位置
4、编译成功后，返回上一层
cd ..
apt-get install libjpeg-dev zlib1g-dev
pip install Pillow==10.0.0
pip install -v -e .

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    所有环境变量如下：

    #cuda
export PATH="/usr/local/cuda-11.3/bin:$PATH"
export CUDA_PATH=/usr/local/cuda-11.3
export LD_LIBRARY_PATH="/usr/local/cuda-11.3/lib64:$LD_LIBRARY_PATH"

#cmake
export PATH=/home/sen/motan/cmake-3.18.0-Linux-x86_64/bin:$PATH
#ppl.cv
export PPLCV_DIR=/home/sen/motan/ppl.cv
#tensorrt
export TENSORRT_DIR=/usr/local/TensorRT-8.2.3.0
export LD_LIBRARY_PATH=$TENSORRT_DIR/lib:$LD_LIBRARY_PATH
#CUDNN
export CUDNN_DIR=/usr/local/cuda-11.3
export LD_LIBRARY_PATH=$CUDNN_DIR/lib64:$LD_LIBRARY_PATH

export MMDEPLOY_DIR=/home/sen/motan/mmdeploy

export ONNXRUNTIME_DIR=/home/sen/motan/onnxruntime-linux-x64-1.8.1
export LD_LIBRARY_PATH=$ONNXRUNTIME_DIR/lib:$LD_LIBRARY_PATH

export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/home/sen/motan/mmdeploy/mmdeploy/lib
export LIBRARY_PATH=$LIBRARY_PATH:/home/sen/motan/mmdeploy/mmdeploy/lib
export LD_LIBRARY_PATH=/usr/lib/x86_64-linux-gnu:$LD_LIBRARY_PATH

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    使用时改
    转engine文件必须用图片代码
    1、/home/sen/motan/DCMMDet3D/demo/data/nuscenes/1.json里图片的路径
    2、/home/sen/motan/mmdeploy/configs/mmdet3d/monocular-detection/monocular-detection_static.py里json的路径

    • 问题
      在这里插入图片描述
      setup.py有问题，要替换掉
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  • 原文地址：https://blog.csdn.net/qq_45990036/article/details/131936656