编译安装opencv with cuda

JetPack预装的opencv没有启用cuda，需要自行编译安装。

1. 脚本一键安装

#!/bin/bash
#opencv_install.# opencv_install.sh
#修改自# Modified from https://github.com/AastaNV/JEP/blob/master/script/install_opencv4.10.0_Jetpack6.1.sh

version="4.10.0"
folder="workspace"
remove_old=""

set -e

# Parse command-line arguments
for arg in "$@"; do
    case $arg in
        --version=*)
            version="${arg#*=}"
            ;;
        --folder=*)
            folder="${arg#*=}"
            ;;
        --remove-old=*)
            remove_old="${arg#*=}"
            ;;
        --help|-h)
            echo "用法:Usage: $0 [--version=4.x.x] [--folder=dir] [--remove-old=yes/no]"
            exit 0
            ;;
        *)
            echo "未知参数:Unknown parameter: $arg"
            echo "用法:Usage: $0 [--version=4.x.x] [--folder=dir] [--remove-old=yes/no]"
            exit 1
            ;;
    esac
done

# 交互式移除旧Create installation directory if it doesn't exist
if [ ! -d "$folder" ]; then
    echo "Creating directory: $folder"
    mkdir -p "$folder"
fi
cd "$folder" || exit

# Old OpenCV whileremoval true;logic
doif echo[ -z "$remove_old" ]; then
    read -rp "Do you want to remove thesystem-installed default OpenCVOpenCV? (yes/no)?: " readremove_old
rm_oldfi

if [case "$rm_old"remove_old" =in
    "yes"[yY] ];| then[yY][eE][sS])
        echo "** RemoveRemoving othersystem OpenCV first"packages"
        sudo apt -y purge *libopencv*
        breaksudo elifapt [-y autoremove
        ;;
    *)
        echo "$rm_old"** =Skipping "no"system ]OpenCV removal"
        ;;
then
        break
    fi
doneesac

echo "------------------------------------"
echo "** InstallInstalling requirementdependencies (1/4)"
echo "------------------------------------"
sudo apt-get update
sudo apt-get install -y build-essential cmake git libgtk2.0-dev pkg-config \
    libavcodec-dev libavformat-dev libswscale-dev sudo apt-get install -y libgstreamer1.0-dev \
    libgstreamer-plugins-base1.0-dev python3.10-python3-dev python3-numpy sudolibtbb2 apt-get install -y libtbb2\
    libtbb-dev libjpeg-dev libpng-dev libtiff-dev libv4l-dev v4l-utils qv4l2 sudocurl

apt-get# installVerify essential dependencies installed
for dep in g++ cmake git pkg-config; do
    if ! command -yv curl"$dep" > /dev/null; then
        echo "Error: $dep installation failed"
        exit 1
    fi
done

echo "------------------------------------"
echo "** DownloadDownloading opencvOpenCV "${version}" (2/4)"
echo "------------------------------------"

mkdir# $folderCheck cdif source files already exist
download_opencv=false
download_contrib=false

if [ ! -f "opencv-${folder}version}.zip" ]; then
    echo "Downloading opencv-${version}.zip"
    wget -O opencv-${version}.zip https://github.com/opencv/opencv/archive/${version}.zip || {
        echo "Download failed! Check your internet connection or verify the version exists"
        exit 1
    }
    download_opencv=true
else
    echo "opencv-${version}.zip exists, skipping download"
fi

if [ ! -f "opencv_contrib-${version}.zip" ]; then
    echo "Downloading opencv_contrib-${version}.zip"
    wget -O opencv_contrib-${version}.zip https://github.com/opencv/opencv_contrib/archive/${version}.zip || {
        echo "Download failed! Check your internet connection or verify the version exists"
        exit 1
    }
    download_contrib=true
else
    echo "opencv_contrib-${version}.zip exists, skipping download"
fi

# Unpack source files
if [ ! -d "opencv-${version}" ] || $download_opencv; then
    if [ -d "opencv-${version}" ]; then
        echo "Removing existing opencv-${version} directory"
        rm -rf "opencv-${version}"
    fi
    echo "Unpacking opencv-${version}.zip"
    unzip -q opencv-${version}.zip || {
        echo "Extraction failed! File may be corrupt"
        exit 1
    }
fi

if [ ! -d "opencv_contrib-${version}" ] || $download_contrib; then
    if [ -d "opencv_contrib-${version}" ]; then
        echo "Removing existing opencv_contrib-${version} directory"
        rm -rf "opencv_contrib-${version}"
    fi
    echo "Unpacking opencv_contrib-${version}.zip"
    unzip -q opencv_contrib-${version}.zip || {
        echo "Extraction failed! File may be corrupt"
        exit 1
    }
fi

# Clean up zip files after successful extraction
if [ $? -eq 0 ]; then
    rm -f opencv-${version}.zip opencv_contrib-${version}.zip
fi

cd opencv-${version}/ || exit

echo "------------------------------------"
echo "** BuildBuilding opencvOpenCV "${version}" (3/4)"
echo "------------------------------------"
mkdir -p release
cd release/release

# Auto-detect CUDA architecture
cuda_arch=""
if command -v nvidia-smi &> /dev/null; then
    gpu_name=$(nvidia-smi --query-gpu=name --format=csv,noheader | head -n1)
    if [[ $gpu_name == *"Orin"* ]] || [[ $gpu_name == *"Jetson"* ]]; then
        cuda_arch="8.7"
    elif [[ $gpu_name == *"A100"* ]]; then
        cuda_arch="8.0"
    fi
fi

cmake_cmd="cmake -D WITH_CUDA=ON -D WITH_CUDNN=ON -D CUDA_ARCH_BIN="8.7" -D CUDA_ARCH_PTX="" -D OPENCV_GENERATE_PKGCONFIG=ON "
cmake_cmd+="-D OPENCV_EXTRA_MODULES_PATH=../../opencv_contrib-${version}/modules "
cmake_cmd+="-D WITH_GSTREAMER=ON -D WITH_LIBV4L=ON -D BUILD_opencv_python3=ON "
cmake_cmd+="-D BUILD_TESTS=OFF -D BUILD_PERF_TESTS=OFF -D BUILD_EXAMPLES=OFF "
cmake_cmd+="-D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local "

# Add CUDA architecture if detected
if [ -n "$cuda_arch" ]; then
    echo "Detected NVIDIA GPU: ${gpu_name}, using CUDA_ARCH_BIN=${cuda_arch}"
    cmake_cmd+="-D CUDA_ARCH_BIN=${cuda_arch} -D CUDA_ARCH_PTX=\"\" "
else
    echo "No supported GPU detected, skipping CUDA architecture flags"
fi

# Execute CMake configuration
echo "CMake command: $cmake_cmd .."
$cmake_cmd .. || {
    echo "CMake configuration failed"
    exit 1
}

# Parallel build (leave one core for system stability)
cpu_cores=$(($(nproc) - 1))
[ $cpu_cores -lt 1 ] && cpu_cores=1
echo "Building with ${cpu_cores} CPU cores"
make -j$(nproc){cpu_cores} || {
    echo "Compilation failed"
    exit 1
}

echo "------------------------------------"
echo "** InstallInstalling opencvOpenCV "${version}" (4/4)"
echo "------------------------------------"
sudo make install || {
    echo '"Installation failed"
    exit 1
}

# Add environment variables to .bashrc (only if not already present)
bashrc=~/.bashrc
env_lines=(
    "export LD_LIBRARY_PATH=/usr/local/lib:\$LD_LIBRARY_PATH'LD_LIBRARY_PATH"
    >> ~/.bashrc
echo '"export PYTHONPATH=/usr/local/lib/python3.10/site-packages/:\$PYTHONPATH'PYTHONPATH"
)

for line in "${env_lines[@]}"; do
    if ! grep -Fxq "$line" "$bashrc"; then
        echo "Adding to .bashrc: $line"
        echo "$line" >> ~/.bashrc"$bashrc"
    else
        echo "Environment variable already exists: $line"
    fi
done

source ~/.bashrc

echo "** InstallOpenCV opencv "${version} installation completed"
echo "Verification commands:"
successfully"echo "  pkg-config --modversion opencv4"
echo "  python3 -c 'import cv2; print(cv2.__version__)'"

echo "** ByeInstallation :)successful!"

2. 手动安装

2.1 卸载自带opencv

sudo apt-get purge libopencv*
sudo apt autoremove
sudo apt-get update

2.2 安装前置软件包

sudo apt-get update
sudo apt-get install -y build-essential cmake git libgtk2.0-dev pkg-config libavcodec-dev libavformat-dev libswscale-dev
sudo apt-get install -y libgstreamer1.0-dev libgstreamer-plugins-base1.0-dev python3.10-dev python3-numpy
sudo apt-get install -y libtbb2 libtbb-dev libjpeg-dev libpng-dev libtiff-dev libv4l-dev v4l-utils qv4l2
sudo apt-get install -y curl

2.3 获取opencv源码(以4.10.0版本为例)

version=4.10.0
wget -O "opencv-${version}.zip" "https://github.com/opencv/opencv/archive/${version}.zip"
wget -O "opencv_contrib-${version}.zip" "https://github.com/opencv/opencv_contrib/archive/${version}.zip"
unzip "opencv-${version}.zip"
unzip "opencv_contrib-${version}.zip"
rm "opencv-${version}.zip" "opencv_contrib-${version}.zip"
cd "opencv-${version}/"

2.4 编译源码

此步骤至少需要半小时以上。

中途可能会下载第三方软件包，建议提前确认网络环境。

mkdir build
cd build/
cmake -D WITH_CUDA=ON -D WITH_CUDNN=ON -D CUDA_ARCH_BIN="8.7" -D CUDA_ARCH_PTX="" -D OPENCV_GENERATE_PKGCONFIG=ON -D OPENCV_EXTRA_MODULES_PATH=../../opencv_contrib-${version}/modules -D WITH_GSTREAMER=ON -D WITH_LIBV4L=ON -D BUILD_opencv_python3=ON -D BUILD_TESTS=OFF -D BUILD_PERF_TESTS=OFF -D BUILD_EXAMPLES=OFF -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local ..
make -j$(nproc)

2.5 安装

sudo make install
echo 'export LD_LIBRARY_PATH=/usr/local/lib:$LD_LIBRARY_PATH' >> ~/.bashrc
echo 'export PYTHONPATH=/usr/local/lib/python3.10/site-packages/:$PYTHONPATH' >> ~/.bashrc
source ~/.bashrc

三、验证测试

#--test_cuda.cpp

#include <opencv2/opencv.hpp>
#include <opencv2/core/cuda.hpp>
#include <opencv2/cudaarithm.hpp>
#include <iostream>
#include <chrono>

// CPU 矩阵乘法
void cpu_matrix_mult(cv::Mat& a, cv::Mat& b, cv::Mat& result) {
    for (int i = 0; i < 50; i++) {
        result = a * b;
    }
}

// GPU 矩阵乘法
void gpu_matrix_mult(cv::cuda::GpuMat& d_a, cv::cuda::GpuMat& d_b, cv::cuda::GpuMat& d_result) {
    cv::cuda::Stream stream;
    
    for (int i = 0; i < 50; i++) {
        cv::cuda::gemm(d_a, d_b, 1.0, cv::cuda::GpuMat(), 0, d_result, 0, stream);
        stream.waitForCompletion();
    }
}

int main() {
    try {
        std::cout << "--- OpenCV CUDA Matrix Multiplication Test ---\n";
        
        // 创建两个 1000x1000 的随机矩阵
        cv::Mat mat_a(1000, 1000, CV_32FC1);
        cv::Mat mat_b(1000, 1000, CV_32FC1);
        cv::randu(mat_a, 0.0f, 1.0f);
        cv::randu(mat_b, 0.0f, 1.0f);
        
        cv::Mat cpu_result;
        
        // CPU 测试
        auto start_cpu = std::chrono::high_resolution_clock::now();
        cpu_matrix_mult(mat_a, mat_b, cpu_result);
        auto end_cpu = std::chrono::high_resolution_clock::now();
        double cpu_time = std::chrono::duration_cast<std::chrono::milliseconds>(end_cpu - start_cpu).count();
        
        // GPU 测试
        cv::cuda::GpuMat d_mat_a, d_mat_b, d_result;
        d_mat_a.upload(mat_a);
        d_mat_b.upload(mat_b);
        
        auto start_gpu = std::chrono::high_resolution_clock::now();
        gpu_matrix_mult(d_mat_a, d_mat_b, d_result);
        auto end_gpu = std::chrono::high_resolution_clock::now();
        double gpu_time = std::chrono::duration_cast<std::chrono::milliseconds>(end_gpu - start_gpu).count();
        
        // 下载结果进行验证
        cv::Mat gpu_result;
        d_result.download(gpu_result);
        
        // 计算误差(一般为空)
        double diff = cv::norm(cpu_result, gpu_result, cv::NORM_L2);
        std::cout << "Result difference: " << diff << "\n";
        
        std::cout << "Performance Results:\n"
                  << " - CPU time: " << cpu_time << " ms\n"
                  << " - GPU time: " << gpu_time << " ms\n"
                  << " - Speedup: " << cpu_time / gpu_time << "x\n";
        
        std::cout << "\n✅ CUDA matrix multiplication test completed\n";
        return 0;
        
    } catch (const cv::Exception& e) {
        std::cerr << "OpenCV Error (" << e.err << "): " << e.what() << "\n";
        return -1;
    } catch (const std::exception& e) {
        std::cerr << "Standard Error: " << e.what() << "\n";
        return -2;
    }
}

编译运行

jetson@jetson-desktop:~/work$ g++ test_cuda.cpp -o test_cuda `pkg-config --cflags --libs opencv4`
jetson@jetson-desktop:~/work$ ./test_cuda
--- OpenCV CUDA Performance Test ---
Performance Results:
 - CPU time: 2451 ms
 - GPU time: 918 ms
 - Speedup: 2.66993x

✅ CUDA performance test completed