C++ libopencv_gpu.so.2.4:无法打开共享对象文件:没有此类文件或目录
我正在尝试编译该代码(来自gpu示例的houghlines.cpp):C++ libopencv_gpu.so.2.4:无法打开共享对象文件:没有此类文件或目录,c++,linux,opencv,gpu,C++,Linux,Opencv,Gpu,我正在尝试编译该代码(来自gpu示例的houghlines.cpp): #包括 #包括 #包括“opencv2/core/core.hpp” #包括“opencv2/highgui/highgui.hpp” #包括“opencv2/imgproc/imgproc.hpp” #包括“opencv2/gpu/gpu.hpp” #包括 #包括 使用名称空间std; 使用名称空间cv; 使用名称空间cv::gpu; 静态void帮助() { cout似乎与此处的问题相同:,请正确配置所有内容并使其运行。
#包括
#包括
#包括“opencv2/core/core.hpp”
#包括“opencv2/highgui/highgui.hpp”
#包括“opencv2/imgproc/imgproc.hpp”
#包括“opencv2/gpu/gpu.hpp”
#包括
#包括
使用名称空间std;
使用名称空间cv;
使用名称空间cv::gpu;
静态void帮助()
{
cout似乎与此处的问题相同:,请正确配置所有内容并使其运行。我发现了问题,这正是我所期望的:
我在源文件中添加:
cv::gpu::printShortCudaDeviceInfo(cv::gpu::getDevice());
它返回:
OpenCV错误:getDevice文件/build/buildd/OpenCV-2.4.2+dfsg/modules/core/src/gpumat.cpp第182行中不支持GPU(该库在编译时不支持CUDA)
在引发“cv::Exception”的实例后调用terminate
what():/build/buildd/opencv-2.4.2+dfsg/modules/core/src/gpumat.cpp:182:错误:(-216)在函数getDevice中编译库时不支持CUDA
现在我必须用cuda(CMAKE)编译opencv。但是我曾经做过这部分…正如上面提到的,构建日志返回库的路径位置。所以它看起来很好,因为所有其他库都工作得很好。所以它来自于从opencv加载gpu库。
#include <cmath>
#include <iostream>
#include "opencv2/core/core.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/gpu/gpu.hpp"
#include <stdlib.h>
#include <stdio.h>
using namespace std;
using namespace cv;
using namespace cv::gpu;
static void help()
{
cout << "This program demonstrates line finding with the Hough transform." << endl;
cout << "Usage:" << endl;
cout << "./gpu-example-houghlines <image_name>, Default is pic1.png\n" << endl;
}
int main(int argc, const char* argv[])
{
const string filename = argc >= 2 ? argv[1] : "~/Images/skorn00.png";
Mat src = imread(filename, IMREAD_GRAYSCALE);
if (src.empty())
{
help();
cout << "can not open " << filename << endl;
return -1;
}
Mat mask;
Canny(src, mask, 100, 200, 3);
Mat dst_cpu;
cvtColor(mask, dst_cpu, CV_GRAY2BGR);
Mat dst_gpu = dst_cpu.clone();
vector<Vec4i> lines_cpu;
{
const int64 start = getTickCount();
HoughLinesP(mask, lines_cpu, 1, CV_PI / 180, 50, 60, 5);
const double timeSec = (getTickCount() - start) / getTickFrequency();
cout << "CPU Time : " << timeSec * 1000 << " ms" << endl;
cout << "CPU Found : " << lines_cpu.size() << endl;
}
for (size_t i = 0; i < lines_cpu.size(); ++i)
{
Vec4i l = lines_cpu[i];
line(dst_cpu, Point(l[0], l[1]), Point(l[2], l[3]), Scalar(0, 0, 255), 3, CV_AA);
}
GpuMat d_src(mask);
GpuMat d_lines;
HoughLinesBuf d_buf;
{
const int64 start = getTickCount();
gpu::HoughLinesP(d_src, d_lines, d_buf, 1.0f, (float) (CV_PI / 180.0f), 50, 5);
const double timeSec = (getTickCount() - start) / getTickFrequency();
cout << "GPU Time : " << timeSec * 1000 << " ms" << endl;
cout << "GPU Found : " << d_lines.cols << endl;
}
vector<Vec4i> lines_gpu;
if (!d_lines.empty())
{
lines_gpu.resize(d_lines.cols);
Mat h_lines(1, d_lines.cols, CV_32SC4, &lines_gpu[0]);
d_lines.download(h_lines);
}
for (size_t i = 0; i < lines_gpu.size(); ++i)
{
Vec4i l = lines_gpu[i];
line(dst_gpu, Point(l[0], l[1]), Point(l[2], l[3]), Scalar(0, 0, 255), 3, CV_AA);
}
imshow("source", src);
imshow("detected lines [CPU]", dst_cpu);
imshow("detected lines [GPU]", dst_gpu);
waitKey();
return 0;
}