realsense SDK2.0学习：：（二）D435深度图片对齐到彩色图片-SDK实现

D435深度图片对齐到彩色图片

---

开发环境：

• ubuntu 16.04LTS
• Intel Realsense SDK2.0
• C++
• Opencv3.4
• CMake

Intel Realsense SDK2.0 貌似已经有了红外摄像头和RBG摄像头的标定数据，本例参照example里面的例程Align进行简化和修改，注释翻译。这里是直接用SDK的对齐了，迟点会出自己实现的对齐方案。

程序流程：

（1） 创建窗口

（2）创建数据管道以及配置信息

（3）打开数据管道，并传入配置信息，打开的函数返回一个profile对象

（4）选择要将深度图对齐到什么数据流（这里选择对齐到RS2_STREAM_COLOR流）

（6）定义一个align对象

（7）取新的一帧，通过align对象即可获得对齐后的帧（再重复一遍，这个例子是将深度图对齐到彩色图，即彩色图不变，深度图发生变化）

（8）将对应的帧输出（详细可参见 ----）

（10）注意：这里虽然有个 rs2::等待捕获下一帧，但是opencv的waitkey()函数不能少，否则不能显示

全部代码及原版英文注释和翻译注释：

#include 
using namespace std;
#include 
#include 
#include 
#include 
#include 

#include
#include
#include
using namespace cv;

#include

//获取深度像素对应长度单位转换
float get_depth_scale(rs2::device dev);

//检查摄像头数据管道设置是否改变
bool profile_changed(const std::vector& current, const std::vector& prev);

int main(int argc, char * argv[]) try
{
    // Create and initialize GUI related objects
    //创建gui窗口
    //window app(1280, 720, "CPP - Align Example"); // Simple window handling
    //ImGui_ImplGlfw_Init(app, false);      // ImGui library intializition
    const char* depth_win="depth_Image";
    namedWindow(depth_win,WINDOW_AUTOSIZE);
    const char* color_win="color_Image";
    namedWindow(color_win,WINDOW_AUTOSIZE);

    //深度图像颜色map
    rs2::colorizer c;                          // Helper to colorize depth images
    //helper用于渲染图片
    //texture renderer;                     // Helper for renderig images

    // Create a pipeline to easily configure and start the camera
    //创建数据管道
    rs2::pipeline pipe;
    rs2::config pipe_config;
    pipe_config.enable_stream(RS2_STREAM_DEPTH,640,480,RS2_FORMAT_Z16,30);
    pipe_config.enable_stream(RS2_STREAM_COLOR,640,480,RS2_FORMAT_BGR8,30);
    //Calling pipeline's start() without any additional parameters will start the first device
    //直接start()，不添加配置参数，则默认打开第一个设备
    // with its default streams.
    //以及以默认的配置进行流输出
    //The start function returns the pipeline profile which the pipeline used to start the device
    //start()函数返回数据管道的profile
    rs2::pipeline_profile profile = pipe.start(pipe_config);

    // Each depth camera might have different units for depth pixels, so we get it here
    //每个深度摄像头有不同单元的像素，我们这里获取
    // Using the pipeline's profile, we can retrieve the device that the pipeline uses
    //使用数据管道的profile获取深度图像像素对应于长度单位（米）的转换比例
    float depth_scale = get_depth_scale(profile.get_device());

    //Pipeline could choose a device that does not have a color stream
    //数据管道可以选择一个没有彩色图像数据流的设备
    //If there is no color stream, choose to align depth to another stream
    //选择彩色图像数据流来作为对齐对象
    rs2_stream align_to = RS2_STREAM_COLOR;//find_stream_to_align(profile.get_stream());

    /*

     @这里的对齐是改变深度图，而不改变color图

    */
    // Create a rs2::align object.
    //创建一个rs2::align的对象
    // rs2::align allows us to perform alignment of depth frames to others frames
    //rs2::align 允许我们去实现深度图像对齐其他图像
    //The "align_to" is the stream type to which we plan to align depth frames.
    // "align_to"是我们打算用深度图像对齐的图像流
    rs2::align align(align_to);

    // Define a variable for controlling the distance to clip
    //定义一个变量去转换深度到距离
    float depth_clipping_distance = 1.f;

    while (cvGetWindowHandle(depth_win)&&cvGetWindowHandle(color_win)) // Application still alive?
    {
        // Using the align object, we block the application until a frameset is available
        //堵塞程序直到新的一帧捕获
        rs2::frameset frameset = pipe.wait_for_frames();

        // rs2::pipeline::wait_for_frames() can replace the device it uses in case of device error or disconnection.
        // Since rs2::align is aligning depth to some other stream, we need to make sure that the stream was not changed
        //因为rs2::align 正在对齐深度图像到其他图像流，我们要确保对齐的图像流不发生改变
        //  after the call to wait_for_frames();
        if (profile_changed(pipe.get_active_profile().get_streams(), profile.get_streams()))
        {
            //If the profile was changed, update the align object, and also get the new device's depth scale
            //如果profile发生改变，则更新align对象，重新获取深度图像像素到长度单位的转换比例
            profile = pipe.get_active_profile();
            align = rs2::align(align_to);
            depth_scale = get_depth_scale(profile.get_device());
        }

        //Get processed aligned frame
        //获取对齐后的帧
        auto processed = align.process(frameset);

        // Trying to get both other and aligned depth frames
        //尝试获取对齐后的深度图像帧和其他帧
        rs2::frame aligned_color_frame = processed.get_color_frame();//processed.first(align_to);
        rs2::frame aligned_depth_frame = processed.get_depth_frame().apply_filter(c);;

        //获取对齐之前的color图像
        rs2::frame before_depth_frame=frameset.get_depth_frame().apply_filter(c);
        //获取宽高
        const int depth_w=aligned_depth_frame.as().get_width();
        const int depth_h=aligned_depth_frame.as().get_height();
        const int color_w=aligned_color_frame.as().get_width();
        const int color_h=aligned_color_frame.as().get_height();
        const int b_color_w=before_depth_frame.as().get_width();
        const int b_color_h=before_depth_frame.as().get_height();
        //If one of them is unavailable, continue iteration
        if (!aligned_depth_frame || !aligned_color_frame)
        {
            continue;
        }
        //创建OPENCV类型 并传入数据
        Mat aligned_depth_image(Size(depth_w,depth_h),CV_8UC3,(void*)aligned_depth_frame.get_data(),Mat::AUTO_STEP);
        Mat aligned_color_image(Size(color_w,color_h),CV_8UC3,(void*)aligned_color_frame.get_data(),Mat::AUTO_STEP);
        Mat before_color_image(Size(b_color_w,b_color_h),CV_8UC3,(void*)before_depth_frame.get_data(),Mat::AUTO_STEP);
        //显示
        imshow(depth_win,aligned_depth_image);
        imshow(color_win,aligned_color_image);
        imshow("before aligned",before_color_image);
        waitKey(10);
    }
    return EXIT_SUCCESS;
}
catch (const rs2::error & e)
{
    std::cerr << "RealSense error calling " << e.get_failed_function() << "(" << e.get_failed_args() << "):\n    " << e.what() << std::endl;
    return EXIT_FAILURE;
}
catch (const std::exception & e)
{
    std::cerr << e.what() << std::endl;
    return EXIT_FAILURE;
}

float get_depth_scale(rs2::device dev)
{
    // Go over the device's sensors
    for (rs2::sensor& sensor : dev.query_sensors())
    {
        // Check if the sensor if a depth sensor
        if (rs2::depth_sensor dpt = sensor.as())
        {
            return dpt.get_depth_scale();
        }
    }
    throw std::runtime_error("Device does not have a depth sensor");
}

bool profile_changed(const std::vector& current, const std::vector& prev)
{
    for (auto&& sp : prev)
    {
        //If previous profile is in current (maybe just added another)
        auto itr = std::find_if(std::begin(current), std::end(current), [&sp](const rs2::stream_profile& current_sp) { return sp.unique_id() == current_sp.unique_id(); });
        if (itr == std::end(current)) //If it previous stream wasn't found in current
        {
            return true;
        }
    }
    return false;
}
float get_depth_scale(rs2::device dev)
{
    // Go over the device's sensors
    for (rs2::sensor& sensor : dev.query_sensors())
    {
        // Check if the sensor if a depth sensor
        if (rs2::depth_sensor dpt = sensor.as())
        {
            return dpt.get_depth_scale();
        }
    }
    throw std::runtime_error("Device does not have a depth sensor");
}

CMakeLists.txt

project(align_test)
cmake_minimum_required(VERSION 2.8)
aux_source_directory(. SRC_LIST)
add_executable(${PROJECT_NAME} ${SRC_LIST})

set(CMAKE_CXX_FLAGS "-std=c++11")
#寻找opencv库
find_package(OpenCV REQUIRED)
#message(STATUS ${OpenCV_INCLUDE_DIRS})
#添加头文件
include_directories(${OpenCV_INCLUDE_DIRS})
#链接Opencv库
target_link_libraries(align_test ${OpenCV_LIBS} )
#添加后可进行调试
set( CMAKE_BUILD_TYPE Debug )
set(DEPENDENCIES realsense2 )
target_link_libraries(align_test ${DEPENDENCIES})

实现效果：

左上为对齐之前的深度图，

左下为对齐后的深度图