我很困惑为什么可以在命令行中使用cmake来构建C ++程序，但是不能在具有其“ build”功能的CLion中构建该程序。
这是我的CMakeLists.txt文件。我正在尝试使用OpenCV构建一个简单的图像分类程序，该教程是here。
cmake_minimum_required(VERSION 3.5.1)
project(opencvdnn )
set(CMAKE_CXX_STANDARD 14)
find_package( OpenCV REQUIRED )
include_directories( ${OpenCV_INCLUDE_DIRS} )
add_executable(caffe caffe.cpp)
target_link_libraries(caffe ${OpenCV_LIBS} )
情况1：
我成功使用以下命令和结果直接在命令行中构建：
user:/DATA/opencvdnn/build$ cmake ../CMakeLists.txt
-- The C compiler identification is GNU 5.4.0
-- The CXX compiler identification is GNU 5.4.0
-- Check for working C compiler: /usr/bin/cc
-- Check for working C compiler: /usr/bin/cc -- works
-- Detecting C compiler ABI info
-- Detecting C compiler ABI info - done
-- Detecting C compile features
-- Detecting C compile features - done
-- Check for working CXX compiler: /usr/bin/c++
-- Check for working CXX compiler: /usr/bin/c++ -- works
-- Detecting CXX compiler ABI info
-- Detecting CXX compiler ABI info - done
-- Detecting CXX compile features
-- Detecting CXX compile features - done
-- Configuring done
-- Generating done
-- Build files have been written to: /media/yuqiong/DATA/opencvdnn
案例2
我在我的CLion IDE中使用了build功能，但失败了，原因是它找不到特定的库。
/opt/clion-2018.2.5/bin/cmake/linux/bin/cmake --build /media/yuqiong/DATA/opencvdnn --target caffe -- -j 6
Scanning dependencies of target caffe
[ 50%] Building CXX object CMakeFiles/caffe.dir/caffe.cpp.o
/media/yuqiong/DATA/opencvdnn/caffe.cpp:5:27: fatal error: opencv2/dnn.hpp: No such file or directory
compilation terminated.
CMakeFiles/caffe.dir/build.make:62: recipe for target 'CMakeFiles/caffe.dir/caffe.cpp.o' failed
make[3]: *** [CMakeFiles/caffe.dir/caffe.cpp.o] Error 1
CMakeFiles/Makefile2:67: recipe for target 'CMakeFiles/caffe.dir/all' failed
make[2]: *** [CMakeFiles/caffe.dir/all] Error 2
CMakeFiles/Makefile2:79: recipe for target 'CMakeFiles/caffe.dir/rule' failed
make[1]: *** [CMakeFiles/caffe.dir/rule] Error 2
Makefile:118: recipe for target 'caffe' failed
make: *** [caffe] Error 2
我的问题是为什么会这样？ CLion是否没有通过cmake工具使用相同的CMake？谢谢！
如果有帮助，这是我的目录结构：
├── build
├── bvlc_googlenet.caffemodel
├── bvlc_googlenet.prototxt
├── caffe.cpp
├── cmake-build-debug
│ ├── CMakeCache.txt
│ ├── CMakeFiles
│ │ ├── 3.12.3
│ │ │ ├── CMakeCCompiler.cmake
│ │ │ ├── CMakeCXXCompiler.cmake
│ │ │ ├── CMakeDetermineCompilerABI_C.bin
│ │ │ ├── CMakeDetermineCompilerABI_CXX.bin
│ │ │ ├── CMakeSystem.cmake
│ │ │ ├── CompilerIdC
│ │ │ │ ├── a.out
│ │ │ │ ├── CMakeCCompilerId.c
│ │ │ │ └── tmp
│ │ │ ├── CompilerIdCUDA
│ │ │ │ ├── CMakeCUDACompilerId.cu
│ │ │ │ └── tmp
│ │ │ └── CompilerIdCXX
│ │ │ ├── a.out
│ │ │ ├── CMakeCXXCompilerId.cpp
│ │ │ └── tmp
│ │ ├── caffe.dir
│ │ │ ├── build.make
│ │ │ ├── cmake_clean.cmake
│ │ │ ├── CXX.includecache
│ │ │ ├── DependInfo.cmake
│ │ │ ├── depend.internal
│ │ │ ├── depend.make
│ │ │ ├── flags.make
│ │ │ ├── link.txt
│ │ │ └── progress.make
│ │ ├── clion-environment.txt
│ │ ├── clion-log.txt
│ │ ├── cmake.check_cache
│ │ ├── CMakeDirectoryInformation.cmake
│ │ ├── CMakeError.log
│ │ ├── CMakeOutput.log
│ │ ├── CMakeTmp
│ │ ├── feature_tests.bin
│ │ ├── feature_tests.c
│ │ ├── feature_tests.cxx
│ │ ├── Makefile2
│ │ ├── Makefile.cmake
│ │ ├── opencvdnn.dir
│ │ │ ├── build.make
│ │ │ ├── cmake_clean.cmake
│ │ │ ├── DependInfo.cmake
│ │ │ ├── depend.make
│ │ │ ├── flags.make
│ │ │ ├── link.txt
│ │ │ └── progress.make
│ │ ├── Progress
│ │ │ ├── 1
│ │ │ └── count.txt
│ │ ├── progress.marks
│ │ └── TargetDirectories.txt
│ ├── cmake_install.cmake
│ ├── Makefile
│ └── opencvdnn.cbp
├── CMakeCache.txt
├── CMakeFiles
│ ├── 3.12.3
│ │ ├── CMakeCCompiler.cmake
│ │ ├── CMakeCXXCompiler.cmake
│ │ ├── CMakeDetermineCompilerABI_C.bin
│ │ ├── CMakeDetermineCompilerABI_CXX.bin
│ │ ├── CMakeSystem.cmake
│ │ ├── CompilerIdC
│ │ │ ├── a.out
│ │ │ ├── CMakeCCompilerId.c
│ │ │ └── tmp
│ │ └── CompilerIdCXX
│ │ ├── a.out
│ │ ├── CMakeCXXCompilerId.cpp
│ │ └── tmp
│ ├── 3.5.1
│ │ ├── CMakeCCompiler.cmake
│ │ ├── CMakeCXXCompiler.cmake
│ │ ├── CMakeDetermineCompilerABI_C.bin
│ │ ├── CMakeDetermineCompilerABI_CXX.bin
│ │ ├── CMakeSystem.cmake
│ │ ├── CompilerIdC
│ │ │ ├── a.out
│ │ │ └── CMakeCCompilerId.c
│ │ └── CompilerIdCXX
│ │ ├── a.out
│ │ └── CMakeCXXCompilerId.cpp
│ ├── caffe.dir
│ │ ├── build.make
│ │ ├── cmake_clean.cmake
│ │ ├── DependInfo.cmake
│ │ ├── depend.make
│ │ ├── flags.make
│ │ ├── link.txt
│ │ └── progress.make
│ ├── clion-environment.txt
│ ├── cmake.check_cache
│ ├── CMakeDirectoryInformation.cmake
│ ├── CMakeOutput.log
│ ├── CMakeTmp
│ ├── feature_tests.bin
│ ├── feature_tests.c
│ ├── feature_tests.cxx
│ ├── Makefile2
│ ├── Makefile.cmake
│ ├── progress.marks
│ └── TargetDirectories.txt
├── cmake_install.cmake
├── CMakeLists.txt
├── Makefile
├── opencvdnn.cbp
├── space_shuttle.jpg
└── synset_words.txt
这是源代码，它基本上只是读取caffe模型并在图像上使用它。
#include <opencv2/dnn.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/highgui.hpp>
#include <opencv2/core/utils/trace.hpp>
using namespace cv;
using namespace cv::dnn;
#include <fstream>
#include <iostream>
#include <cstdlib>
using namespace std;
/* Find best class for the blob (i. e. class with maximal probability) */
static void getMaxClass(const Mat &probBlob, int *classId, double *classProb)
{
Mat probMat = probBlob.reshape(1, 1); //reshape the blob to 2x1000 matrix
Point classNumber;
minMaxLoc(probMat, NULL, classProb, NULL, &classNumber);
*classId = classNumber.x;
}
static std::vector<String> readClassNames(const char *filename = "synset_words.txt")
{
std::vector<String> classNames;
std::ifstream fp(filename);
if (!fp.is_open())
{
std::cerr << "File with classes labels not found: " << filename << std::endl;
exit(-1);
}
std::string name;
while (!fp.eof())
{
std::getline(fp, name);
if (name.length())
classNames.push_back( name.substr(name.find(' ')+1) );
}
fp.close();
return classNames;
}
int main(int argc, char **argv)
{
CV_TRACE_FUNCTION();
String modelTxt = "bvlc_googlenet.prototxt";
String modelBin = "bvlc_googlenet.caffemodel";
String imageFile = (argc > 1) ? argv[1] : "space_shuttle.jpg";
Net net;
try {
net = dnn::readNetFromCaffe(modelTxt, modelBin);
}
catch (cv::Exception& e) {
std::cerr << "Exception: " << e.what() << std::endl;
if (net.empty())
{
std::cerr << "Can't load network by using the following files: " << std::endl;
std::cerr << "prototxt: " << modelTxt << std::endl;
std::cerr << "caffemodel: " << modelBin << std::endl;
std::cerr << "bvlc_googlenet.caffemodel can be downloaded here:" << std::endl;
std::cerr << "http://dl.caffe.berkeleyvision.org/bvlc_googlenet.caffemodel" << std::endl;
exit(-1);
}
}
Mat img = imread(imageFile);
if (img.empty())
{
std::cerr << "Can't read image from the file: " << imageFile << std::endl;
exit(-1);
}
//GoogLeNet accepts only 224x224 BGR-images
Mat inputBlob = blobFromImage(img, 1.0f, Size(224, 224),
Scalar(104, 117, 123), false); //Convert Mat to batch of images
Mat prob;
cv::TickMeter t;
for (int i = 0; i < 10; i++)
{
CV_TRACE_REGION("forward");
net.setInput(inputBlob, "data"); //set the network input
t.start();
prob = net.forward("prob"); //compute output
t.stop();
}
int classId;
double classProb;
getMaxClass(prob, &classId, &classProb);//find the best class
std::vector<String> classNames = readClassNames();
std::cout << "Best class: #" << classId << " '" << classNames.at(classId) << "'" << std::endl;
std::cout << "Probability: " << classProb * 100 << "%" << std::endl;
std::cout << "Time: " << (double)t.getTimeMilli() / t.getCounter() << " ms (average from " << t.getCounter() << " iterations)" << std::endl;
return 0;
} //main
答案 0 :(得分：1)
恐怕您使用命令行的第一种方法无效。 cmake只会创建make文件。实际上是建立目标的make命令。您的clion输出表明clion能够成功生成make文件，但是无法生成。如果您尝试通过命令行手动进行制作，我会期望出现相同的错误。
如果您可以通过命令行构建camke项目，那么应该也100％地将其构建在clion中。
我还建议您检查系统上是否安装了opencv2。检查您是否有一个文件夹/ usr / include / opencv或它是/ usr / include / opencv2。由于您的find_package（需要OpenCV）成功，因此可以确定您具有本地安装。
另一种方法是查找文件CMakeCache.txt。如果在其中搜索opencv，则会在其中找到一些OpenCV变量集。那应该给你一个线索。