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安装

1. 安装依赖项

 sudo apt-get install cmake sudo apt-get install libgoogle-glog-dev libgflags-dev sudo apt-get install libatlas-base-dev sudo apt-get install libeigen3-dev sudo apt-get install libsuitesparse-dev 

2. 下载安装

讯享网git clone https://github.com/ceres-solver/ceres-solver.git mkdir ceres-bin cd ceres-bin cmake .. sudo make install 

3. cmakelist.txt配置

方法一：

add_compile_options(-std=c++14) find_package(Ceres REQUIRED) include_directories(${ 
   Ceres_INCLUDE_DIRS}) add_executable(ceres_1 ${ 
   ceres_1_src}) target_link_libraries(ceres_1 ${ 
   Ceres_INCLUDE_DIRS}) 

方法2：
如果使用方式一配置编译时出现如下错误：

讯享网
使用如下方式配置：

讯享网add_compile_options(-std=c++14) #指定库路径 file(GLOB_RECURSE Opencv2.7_LIB "/usr/lib/python2.7/config-x86_64-linux-gnu/*.so") file(GLOB_RECURSE Creres_LIB "/usr/local/lib/libceres.a") file(GLOB_RECURSE cholmod_LIB "/usr/lib/x86_64-linux-gnu/libcholmod.so") file(GLOB_RECURSE lapack_LIB "/usr/lib/lapack/liblapack.so") file(GLOB_RECURSE f77blas_LIB "/usr/lib/libf77blas.so") file(GLOB_RECURSE cxsparse_LIB "/usr/lib/x86_64-linux-gnu/libcxsparse.so") file(GLOB_RECURSE glog_LIB "/usr/lib/x86_64-linux-gnu/libglog.so") file(GLOB_RECURSE pthread_LIB "/usr/lib/x86_64-linux-gnu/libpthread.so") #指定头文件路径 set(Opencv2.7_INLCUDE_DIRS "/usr/include/python2.7") set(Creres_INLCUDE_DIRS "/usr/local/include/ceres") set(suitespars_INLCUDE_DIRS "/usr/include/suitespars") set(lapack_INLCUDE_DIRS "/usr/include/eigen3/Eigen/src/misc") set(glog_INLCUDE_DIRS "/usr/include/glog") set(pthread_INLCUDE_DIRS "/usr/include/boost/thread") #添加头文件到工程 include_directories(include ${ 
   Opencv2.7_INLCUDE_DIRS} ) include_directories(include ${ 
   Creres_INLCUDE_DIRS} ) include_directories(include ${ 
   suitespars_INLCUDE_DIRS} ) include_directories(include ${ 
   lapack_INLCUDE_DIRS} ) include_directories(include ${ 
   glog_INLCUDE_DIRS} ) include_directories(include ${ 
   pthread_INLCUDE_DIRS} ) # include_directories("/usr/local/include/eigen3") AUX_SOURCE_DIRECTORY(${ 
   PROJECT_SOURCE_DIR}/1 ceres_1_src) # Declare the executable target built from your sources add_executable(ceres_1 ${ 
   ceres_1_src}) # Link your application with OpenCV libraries # target_link_libraries(undistort ${ 
   Pangolin_LIBRARIES}) target_link_libraries(ceres_1 ${ 
   Creres_LIB} ${ 
   cholmod_LIB} ${ 
   lapack_LIB} ${ 
   f77blas_LIB} ${ 
   cxsparse_LIB} ${ 
   pthread_LIB} ${ 
   glog_LIB} ) 

一个例子

一个目标函数如下

 #include "/usr/local/include/ceres/ceres.h" #include <glog/logging.h> using ceres::AutoDiffCostFunction; using ceres::CostFunction; using ceres::Problem; using ceres::Solve; using ceres::Solver; using namespace ceres; //定义代价函数 struct CostFunctor { 
    template <typename T> bool operator()(const T* x, T* residual) const { 
    residual[0] = 10.0 - x[0]; return true; } }; int main(int argc, char** argv) { 
    //初始画参数 double x = 0.5; const double initial_x = x; //构建问题 Problem problem; //设置残差 CostFunction* cost_function = new AutoDiffCostFunction<CostFunctor, 1, 1>(new CostFunctor); //AutoDiffCostFunction 求导 //CostFunctor 代价函数 //1 惨差的维数 //1 输入数据的维数 problem.AddResidualBlock(cost_function, NULL, &x); //目标函数 //cost_function：代价函数 //NULL：核函数，这里不使用用 //x:待优化参数 //进行求解 Solver::Options options;//建议一个求解问题类 options.linear_solver_type=ceres::DENSE_QR;//配置增量方程的解法 options.minimizer_progress_to_stdout = true;//是否在打印输出 Solver::Summary summary;//优化信息 Solve(options, &problem, &summary);//求解 std::cout << summary.BriefReport() << "\n";//输出优化的简要信息 std::cout << "x : " << initial_x << " -> " << x << "\n";//输出优化结果 return 0; } 

1. 步骤1：定义代价函数：

讯享网//定义代价函数 struct CostFunctor{ 
    template <typename T>//模板类T bool operator()(const T* x,T* residual) const { 
    residual[0]=10.0-x[0]; return true; } }; 

2. 构建问题

 //构建问题 Problem problem; //设置残差 CostFunction* cost_function = new AutoDiffCostFunction<CostFunctor, 1, 1>(new CostFunctor); //AutoDiffCostFunction 求导 //CostFunctor 代价函数 //1 输入数据的个数 //1 每个输入数据的维数 problem.AddResidualBlock(cost_function, NULL, &x); //目标函数 //cost_function：代价函数 //NULL：核函数，这里不使用用 

问题求解

讯享网 //进行求解 Solver::Options options;//建议一个求解问题类 options.linear_solver_type=ceres::DENSE_QR;//配置增量方程的解法 options.minimizer_progress_to_stdout = true;//是否在打印输出 Solver::Summary summary;//优化信息 Solve(options, &problem, &summary);//求解