SLAM实践：ORB_SLAM2与D435(二)

程序修改与运行---构建实时系统

源文件下载：

https://download.csdn.net/download/ly1997th/10394408
https://download.csdn.net/download/ly1997th/1039440

1. 从D435中获取color和depth数据，在librealSense/examples/save-to-disk中，可以看到数据是如何获取的。首先得到depth数据，然后获得color数据，然后存入磁盘。在这里，我们可以使用这种方法获得数据（可以尝试不去存磁盘，直接把realsense的数据流转变为Mat类型，传给ORB_SLAM，但是我没有做出来）同时，需要注意的是，ORB_SLAM还需要时间戳，在veido_frame类(其实是在基类frame)中可以找到函数get_timestamp()，获得时间戳。最后，将这部分内容转化为函数

double LoadImages(cv::Mat &imRGB,cv::Mat &imD)

            1.1 原始示例中代码

    for (auto&& frame : pipe.wait_for_frames())
    {
        // We can only save video frames as pngs, so we skip the rest
        if (auto vf = frame.as<rs2::video_frame>())
        {
            auto stream = frame.get_profile().stream_type();
            // Use the colorizer to get an rgb image for the depth stream
            if (vf.is<rs2::depth_frame>()) vf = color_map(frame);

            // Write images to disk
            std::stringstream png_file;
            png_file << "rs-save-to-disk-output-" << vf.get_profile().stream_name() << ".png";
            stbi_write_png(png_file.str().c_str(), vf.get_width(), vf.get_height(),
                           vf.get_bytes_per_pixel(), vf.get_data(), vf.get_stride_in_bytes());
            std::cout << "Saved " << png_file.str() << std::endl;

            // Record per-frame metadata for UVC streams
            // std::stringstream csv_file;
            // csv_file << "rs-save-to-disk-output-" << vf.get_profile().stream_name()
            //          << "-metadata.csv";
            // metadata_to_csv(vf, csv_file.str());
        }
    }

            1.2  double LoadImages(cv::Mat &imRGB,cv::Mat &imD)

double LoadImages(cv::Mat &imRGB,cv::Mat &imD)
{
    // Declare depth colorizer for pretty visualization of depth data
    rs2::colorizer color_map;

    // Declare RealSense pipeline, encapsulating the actual device and sensors
    rs2::pipeline pipe;
    // Start streaming with default recommended configuration
    pipe.start();

    // Wait for the next set of frames from the camera. Now that autoexposure, etc.
    // has settled, we will write these to disk
    int flag=0;
    double timestamp=0.0;
    int ping=1000;
    for (auto&& frame : pipe.wait_for_frames(ping))
    {
        // We can only save video frames as pngs, so we skip the rest
        if (auto vf = frame.as<rs2::video_frame>())
        {
            // Use the colorizer to get an rgb image for the depth stream
            if (vf.is<rs2::depth_frame>()) vf = color_map(frame);

            // Write images to disk
            timestamp = static_cast<double>(vf.get_timestamp());
            std::stringstream png_file;
            //png_file << n<<"_"<<vf.get_profile().stream_name() << ".png";
            png_file <<timestamp<<vf.get_profile().stream_name() << ".png";
            stbi_write_png(png_file.str().c_str(), vf.get_width(), vf.get_height(),
                           vf.get_bytes_per_pixel(), vf.get_data(), vf.get_stride_in_bytes());
            if(flag==0) 
            {
                imD = cv::imread(png_file.str().c_str(),CV_LOAD_IMAGE_UNCHANGED);
                flag=1;
            }
            else
            {
                imRGB = cv::imread(png_file.str().c_str(),CV_LOAD_IMAGE_UNCHANGED);
                flag=0;
            }
        }
    }
    return timestamp; 
}

2. ORB_SLAM需要修改的部分包括CMakelist.txt和rgbd_tum.cc，这部分需要较大改动。首先看rgbd_tum.cc，由于我们打算完成一个实时系统，所以不在需要数据的读取、color和depth的匹配；可以省去相当部分的工作。最后展示所有的rgbd_tum.cc代码。

#include <iostream>
#include <algorithm>
#include <fstream>
#include <sstream>   
#include <chrono>

#include <librealsense2/rs.hpp>
#include <opencv2/core/core.hpp>
#include <System.h>

using namespace std;

// 3rd party header for writing png files
#define STB_IMAGE_WRITE_IMPLEMENTATION
#include "stb_image_write.h"

double LoadImages(cv::Mat &imRGB,cv::Mat &imD);

int main(int argc, char **argv)
{
    // Create SLAM system. It initializes all system threads and gets ready to process frames.
    ORB_SLAM2::System SLAM(argv[1],argv[2],ORB_SLAM2::System::RGBD,true);

    // Vector for tracking time statistics
    vector<float> vTimesTrack;

    cout << endl << "-------" << endl;
    cout << "Start processing sequence ..." << endl;
    // Main loop
    cv::Mat imRGB, imD;
    const int Max_size=INT_MAX;
    for(int ni=0; ni<Max_size; ni++)
    {
        // load image,depthmap,timestamp 
        double tframe = LoadImages(imRGB,imD);
        if(imRGB.empty())
        {
            cerr << endl << "Failed to load color mage"<<endl;
            return 1;
        }
        if(imD.empty())
        {
            cerr << endl << "Failed to load depth image"<<endl;
            return 1;
        }

#ifdef COMPILEDWITHC11
        std::chrono::steady_clock::time_point t1 = std::chrono::steady_clock::now();
#else
        std::chrono::monotonic_clock::time_point t1 = std::chrono::monotonic_clock::now();
#endif

        // Pass the image to the SLAM system
        SLAM.TrackRGBD(imRGB,imD,tframe);

#ifdef COMPILEDWITHC11
        std::chrono::steady_clock::time_point t2 = std::chrono::steady_clock::now();
#else
        std::chrono::monotonic_clock::time_point t2 = std::chrono::monotonic_clock::now();
#endif

        double ttrack= std::chrono::duration_cast<std::chrono::duration<double> >(t2 - t1).count();

        vTimesTrack.push_back(ttrack);
    }

    // Stop all threads
    SLAM.Shutdown();

    // Tracking time statistics
    sort(vTimesTrack.begin(),vTimesTrack.end());
    float totaltime = 0;
    for(int ni=0; ni<Max_size; ni++)
    {
        totaltime+=vTimesTrack[ni];
    }
    cout << "-------" << endl << endl;
    cout << "median tracking time: " << vTimesTrack[Max_size/2] << endl;
    cout << "mean tracking time: " << totaltime/Max_size << endl;

    // Save camera trajectory
    SLAM.SaveTrajectoryTUM("CameraTrajectory.txt");
    SLAM.SaveKeyFrameTrajectoryTUM("KeyFrameTrajectory.txt");   

    return 0;
}

double LoadImages(cv::Mat &imRGB,cv::Mat &imD)
{
    // Declare depth colorizer for pretty visualization of depth data
    rs2::colorizer color_map;

    // Declare RealSense pipeline, encapsulating the actual device and sensors
    rs2::pipeline pipe;
    // Start streaming with default recommended configuration
    pipe.start();

    int flag=0;
    double timestamp=0.0;
    int ping=1000;
    for (auto&& frame : pipe.wait_for_frames(ping))
    {
        // We can only save video frames as pngs, so we skip the rest
        if (auto vf = frame.as<rs2::video_frame>())
        {
            // Use the colorizer to get an rgb image for the depth stream
            if (vf.is<rs2::depth_frame>()) vf = color_map(frame);

            // Write images to disk
            timestamp = static_cast<double>(vf.get_timestamp());
            std::stringstream png_file;
            //png_file << n<<"_"<<vf.get_profile().stream_name() << ".png";
            png_file <<timestamp<<vf.get_profile().stream_name() << ".png";
            stbi_write_png(png_file.str().c_str(), vf.get_width(), vf.get_height(),
                           vf.get_bytes_per_pixel(), vf.get_data(), vf.get_stride_in_bytes());
            if(flag==0) 
            {
                imD = cv::imread(png_file.str().c_str(),CV_LOAD_IMAGE_UNCHANGED);
                flag=1;
            }
            else
            {
                imRGB = cv::imread(png_file.str().c_str(),CV_LOAD_IMAGE_UNCHANGED);
                flag=0;
            }
        }
    }
    return timestamp; 
}

3.修改CMakeList.txt文件，因为我们此处只关心rgbd部分，同时加入libealsense部分，所以需要进行相当大的修改，主要的工作是需要将save-to-disk的CMakeList.txt融合到ORB_SLAM中去，包括第三方库等等。完整代码如下：

cmake_minimum_required(VERSION 2.8)
project(ORB_SLAM2)

IF(NOT CMAKE_BUILD_TYPE)
  SET(CMAKE_BUILD_TYPE Release)
ENDIF()

MESSAGE("Build type: " ${CMAKE_BUILD_TYPE})

set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS}  -Wall  -O3 -march=native ")
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -Wall   -O3 -march=native")

# Check C++11 or C++0x support
include(CheckCXXCompilerFlag)
CHECK_CXX_COMPILER_FLAG("-std=c++11" COMPILER_SUPPORTS_CXX11)
CHECK_CXX_COMPILER_FLAG("-std=c++0x" COMPILER_SUPPORTS_CXX0X)
if(COMPILER_SUPPORTS_CXX11)
   set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11")
   add_definitions(-DCOMPILEDWITHC11)
   message(STATUS "Using flag -std=c++11.")
elseif(COMPILER_SUPPORTS_CXX0X)
   set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++0x")
   add_definitions(-DCOMPILEDWITHC0X)
   message(STATUS "Using flag -std=c++0x.")
else()
   message(FATAL_ERROR "The compiler ${CMAKE_CXX_COMPILER} has no C++11 support. Please use a different C++ compiler.")
endif()

LIST(APPEND CMAKE_MODULE_PATH ${PROJECT_SOURCE_DIR}/cmake_modules)

find_package(OpenCV 3.0 QUIET)
if(NOT OpenCV_FOUND)
   find_package(OpenCV 2.4.3 QUIET)
   if(NOT OpenCV_FOUND)
      message(FATAL_ERROR "OpenCV > 2.4.3 not found.")
   endif()
endif()

find_package(Eigen3 3.1.0 REQUIRED)
find_package(Pangolin REQUIRED)


if(true)
    find_package(OpenGL)
    if(NOT OPENGL_FOUND)
        message(FATAL_ERROR "\n\n OpenGL package is missing!\n\n")
    endif()

    set(DEPENDENCIES realsense2 ${OPENGL_LIBRARIES})

    if(WIN32)
        list(APPEND DEPENDENCIES glfw3)
    else()
        # Find glfw header
        find_path(GLFW_INCLUDE_DIR NAMES GLFW/glfw3.h
            PATHS /usr/X11R6/include
                  /usr/include/X11
                  /opt/graphics/OpenGL/include
                  /opt/graphics/OpenGL/contrib/libglfw
                  /usr/local/include
                  /usr/include/GL
                  /usr/include
        )
        # Find glfw library
        find_library(GLFW_LIBRARIES NAMES glfw glfw3
                PATHS /usr/lib64
                      /usr/lib
                      /usr/lib/${CMAKE_LIBRARY_ARCHITECTURE}
                      /usr/local/lib64
                      /usr/local/lib
                      /usr/local/lib/${CMAKE_LIBRARY_ARCHITECTURE}
                      /usr/X11R6/lib
        )
        if(APPLE)
            find_library(COCOA_LIBRARY Cocoa)
            find_library(IOKIT_LIBRARY IOKit)
            find_library(COREVIDEO_LIBRARY CoreVideo)
            LIST(APPEND DEPENDENCIES ${COCOA_LIBRARY} ${IOKIT_LIBRARY} ${COREVIDEO_LIBRARY})
        endif()
        list(APPEND DEPENDENCIES m ${GLFW_LIBRARIES} ${LIBUSB1_LIBRARIES})
        include_directories(${GLFW_INCLUDE_DIR})
    endif()
else()
    set(DEPENDENCIES realsense2)
    if(NOT WIN32)
        list(APPEND DEPENDENCIES m ${LIBUSB1_LIBRARIES})
    endif()
endif()

include_directories(
${PROJECT_SOURCE_DIR}
${PROJECT_SOURCE_DIR}/include
${EIGEN3_INCLUDE_DIR}
${Pangolin_INCLUDE_DIRS}
${PROJECT_SOURCE_DIR}/Examples/RGB-D/common 
${PROJECT_SOURCE_DIR}/Examples/RGB-D/third-party 
${PROJECT_SOURCE_DIR}/Examples/RGB-D/third-party/tclap/include
)

set(CMAKE_LIBRARY_OUTPUT_DIRECTORY ${PROJECT_SOURCE_DIR}/lib)

add_library(${PROJECT_NAME} SHARED
src/System.cc
src/Tracking.cc
src/LocalMapping.cc
src/LoopClosing.cc
src/ORBextractor.cc
src/ORBmatcher.cc
src/FrameDrawer.cc
src/Converter.cc
src/MapPoint.cc
src/KeyFrame.cc
src/Map.cc
src/MapDrawer.cc
src/Optimizer.cc
src/PnPsolver.cc
src/Frame.cc
src/KeyFrameDatabase.cc
src/Sim3Solver.cc
src/Initializer.cc
src/Viewer.cc
)

target_link_libraries(${PROJECT_NAME}
${OpenCV_LIBS}
${EIGEN3_LIBS}
${Pangolin_LIBRARIES}
${PROJECT_SOURCE_DIR}/Thirdparty/DBoW2/lib/libDBoW2.so
${PROJECT_SOURCE_DIR}/Thirdparty/g2o/lib/libg2o.so
${DEPENDENCIES}
)

# Build examples

set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${PROJECT_SOURCE_DIR}/Examples/RGB-D)

add_executable(rgbd_ly
Examples/RGB-D/rgbd_tum.cc)
target_link_libraries(rgbd_ly ${PROJECT_NAME})

3. 移动部分文件和第三方库，在save-to-disk中可以看到需要的第三方库，包括common，third-party等，复制到Examples/RGB-D中，同时需要讲用来保存数据的头文件stb_image_write.h在common中找出，放在RGB_D中（理论上放在common或者是ORB_SLAM2/include中也行，但是我没有成功，大家可以都试试，顺便告诉我原因）

4. 最后再次cmake和make整个工程，然后尝试运行(标定部分一直未能完成，有解决的话希望大家周知一下，这个地方我直接采用了组里其他人的数据）

./Examples/RGB-D/rgbd_ly Vocabulary/ORBvoc.txt Examples/RGB-D/D435.yaml

5. 运行成功的话（一般都要折腾好久才行），可以看到以下画面（保存下来的视频截图）。