OpenCV编译C++测试程序获取CUDA设备信息

OpenCV编译C++测试程序获取CUDA设备信息

本文介绍如何编译一个OpenCV C++测试程序，以获取CUDA设备信息。测试代码基于OpenCV库，使用g++编译器进行编译，并运行在支持CUDA的设备上。

测试代码

首先，创建一个C++源文件（例如test-cv.cpp），包含以下代码：

#include <opencv2/opencv.hpp>
#include <opencv2/cudaimgproc.hpp>
#include <iostream>

using namespace cv;
using namespace cv::cuda;
using namespace std;

int main(int argc, char **argv) {
    cuda::printCudaDeviceInfo(cuda::getDevice());
    int cnt = getCudaEnabledDeviceCount();
    printf("Now get CUDA device count:%d \r\n", cnt);
    return 0;
}

编译步骤

手动编译的OpenCV安装目录在/usr/local下（根据CMake参数 -DCMAKE_INSTALL_PREFIX=/usr/local 设定）。因此，使用g++编译时需要指定头文件目录和动态库位置：

• 使用 -I 参数指定OpenCV头文件目录，例如 -I/usr/local/include/opencv4。
• 使用 -L 参数指定动态库位置，例如 -L/usr/local/lib。
• 链接必要的OpenCV库，基础库为 -lopencv_core，其他可能用到的库包括 -lopencv_highgui、-lopencv_imgproc 等。

编译命令示例：

g++ test-cv.cpp -o test-cv -I/usr/local/include/opencv4 -L/usr/local/lib -lopencv_core

运行结果

运行编译后的程序，输出CUDA设备信息：

./test-cv 
*** CUDA Device Query (Runtime API) version (CUDART static linking) *** 

Device count: 1

Device 0: "Orin"
  CUDA Driver Version / Runtime Version          11.40 / 11.40
  CUDA Capability Major/Minor version number:    8.7
  Total amount of global memory:                 7471 MBytes (7834177536 bytes)
  GPU Clock Speed:                               0.62 GHz
  Max Texture Dimension Size (x,y,z)             1D=(131072), 2D=(131072,65536), 3D=(16384,16384,16384)
  Max Layered Texture Size (dim) x layers        1D=(32768) x 2048, 2D=(32768,32768) x 2048
  Total amount of constant memory:               65536 bytes
  Total amount of shared memory per block:       49152 bytes
  Total number of registers available per block: 65536
  Warp size:                                     32
  Maximum number of threads per block:           1024
  Maximum sizes of each dimension of a block:    1024 x 1024 x 64
  Maximum sizes of each dimension of a grid:     2147483647 x 65535 x 65535
  Maximum memory pitch:                          2147483647 bytes
  Texture alignment:                             512 bytes
  Concurrent copy and execution:                 Yes with 2 copy engine(s)
  Run time limit on kernels:                     No
  Integrated GPU sharing Host Memory:            Yes
  Support host page-locked memory mapping:       Yes
  Concurrent kernel execution:                   Yes
  Alignment requirement for Surfaces:            Yes
  Device has ECC support enabled:                No
  Device is using TCC driver mode:               No
  Device supports Unified Addressing (UVA):      Yes
  Device PCI Bus ID / PCI location ID:           0 / 0
  Compute Mode:
      Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) 

deviceQuery, CUDA Driver = CUDART, CUDA Driver Version  = 11.40, CUDA Runtime Version = 11.40, NumDevs = 1

Now get CUDA device count:1

以上内容根据原帖子整理，保留了核心逻辑和代码示例。更多详细步骤、视频讲解和其他资源，请阅读 原帖子：OpenCV编译C++测试程序获取cuda设备信息。

原帖子内容来源：https://bbs.eeworld.com.cn/thread-1270395-1-1.html