深度图片对齐到彩色图片"/>
realsense D435学习(二)：深度图片对齐到彩色图片
1.sdk实现
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 <iostream>
using namespace std;
#include <sstream>
#include <iostream>
#include <fstream>
#include <algorithm>
#include <cstring>#include<opencv2/imgproc/imgproc.hpp>
#include<opencv2/core/core.hpp>
#include<opencv2/highgui/highgui.hpp>
using namespace cv;#include<librealsense2/rs.hpp>//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<rs2::stream_profile>& current, const std::vector<rs2::stream_profile>& 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 intializitionconst 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maprs2::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profilers2::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<rs2::video_frame>().get_width();const int depth_h=aligned_depth_frame.as<rs2::video_frame>().get_height();const int color_w=aligned_color_frame.as<rs2::video_frame>().get_width();const int color_h=aligned_color_frame.as<rs2::video_frame>().get_height();const int b_color_w=before_depth_frame.as<rs2::video_frame>().get_width();const int b_color_h=before_depth_frame.as<rs2::video_frame>().get_height();//If one of them is unavailable, continue iterationif (!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 sensorsfor (rs2::sensor& sensor : dev.query_sensors()){// Check if the sensor if a depth sensorif (rs2::depth_sensor dpt = sensor.as<rs2::depth_sensor>()){return dpt.get_depth_scale();}}throw std::runtime_error("Device does not have a depth sensor");
}bool profile_changed(const std::vector<rs2::stream_profile>& current, const std::vector<rs2::stream_profile>& 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 sensorsfor (rs2::sensor& sensor : dev.query_sensors()){// Check if the sensor if a depth sensorif (rs2::depth_sensor dpt = sensor.as<rs2::depth_sensor>()){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
原文链接：
2.代码实现
大概原理
目的：将深度坐标系下的点转换到彩色坐标系下
基本步骤：
（1）将深度图的像素点还原到深度坐标系下
（2）深度坐标系下的深度点还原到世界坐标系
（3）世界坐标系的深度点转换到彩色坐标系下
（4）彩色坐标系的深度点映射到Z=1的平面上，即与彩色图像的像素点对应起来
代码部分：
#include <iostream>using namespace std;
#include <sstream>
#include <iostream>
#include <fstream>
#include <algorithm>
#include <cstring>#include<opencv2/imgproc/imgproc.hpp>
#include<opencv2/core/core.hpp>
#include<opencv2/highgui/highgui.hpp>
using namespace cv;#include<librealsense2/rs.hpp>
#include<librealsense2/rsutil.h>
//获取深度像素对应长度单位（米）的换算比例
float get_depth_scale(rs2::device dev)
{// Go over the device's sensorsfor (rs2::sensor& sensor : dev.query_sensors()){// Check if the sensor if a depth sensorif (rs2::depth_sensor dpt = sensor.as<rs2::depth_sensor>()){return dpt.get_depth_scale();}}throw std::runtime_error("Device does not have a depth sensor");
}
//深度图对齐到彩色图函数
Mat align_Depth2Color(Mat depth,Mat color,rs2::pipeline_profile profile){//声明数据流auto depth_stream=profile.get_stream(RS2_STREAM_DEPTH).as<rs2::video_stream_profile>();auto color_stream=profile.get_stream(RS2_STREAM_COLOR).as<rs2::video_stream_profile>();//获取内参const auto intrinDepth=depth_stream.get_intrinsics();const auto intrinColor=color_stream.get_intrinsics();//直接获取从深度摄像头坐标系到彩色摄像头坐标系的欧式变换矩阵//auto extrinDepth2Color=depth_stream.get_extrinsics_to(color_stream);rs2_extrinsics extrinDepth2Color;rs2_error *error;rs2_get_extrinsics(depth_stream,color_stream,&extrinDepth2Color,&error);//平面点定义float pd_uv[2],pc_uv[2];//空间点定义float Pdc3[3],Pcc3[3];//获取深度像素与现实单位比例（D435默认1毫米）float depth_scale = get_depth_scale(profile.get_device());
// uint16_t depth_max=0;
// for(int row=0;row<depth.rows;row++){
// for(int col=0;col<depth.cols;col++){
// if(depth_max<depth.at<uint16_t>(row,col))
// depth_max=depth.at<uint16_t>(row,col);
// }
// }int y=0,x=0;//初始化结果Mat result=Mat::zeros(color.rows,color.cols,CV_8UC3);//对深度图像遍历for(int row=0;row<depth.rows;row++){for(int col=0;col<depth.cols;col++){//将当前的(x,y)放入数组pd_uv，表示当前深度图的点pd_uv[0]=col;pd_uv[1]=row;//取当前点对应的深度值uint16_t depth_value=depth.at<uint16_t>(row,col);//换算到米float depth_m=depth_value*depth_scale;//将深度图的像素点根据内参转换到深度摄像头坐标系下的三维点rs2_deproject_pixel_to_point(Pdc3,&intrinDepth,pd_uv,depth_m);//将深度摄像头坐标系的三维点转化到彩色摄像头坐标系下rs2_transform_point_to_point(Pcc3,&extrinDepth2Color,Pdc3);//将彩色摄像头坐标系下的深度三维点映射到二维平面上rs2_project_point_to_pixel(pc_uv,&intrinColor,Pcc3);//取得映射后的（u,v)x=(int)pc_uv[0];y=(int)pc_uv[1];
// if(x<0||x>color.cols)
// continue;
// if(y<0||y>color.rows)
// continue;//最值限定x=x<0? 0:x;x=x>depth.cols-1 ? depth.cols-1:x;y=y<0? 0:y;y=y>depth.rows-1 ? depth.rows-1:y;//将成功映射的点用彩色图对应点的RGB数据覆盖for(int k=0;k<3;k++){//这里设置了只显示1米距离内的东西if(depth_m<1)result.at<cv::Vec3b>(y,x)[k]=color.at<cv::Vec3b>(y,x)[k];}}}return result;
}int main()
{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maprs2::colorizer c; // Helper to colorize depth images//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);//start()函数返回数据管道的profilers2::pipeline_profile profile = pipe.start(pipe_config);//定义一个变量去转换深度到距离float depth_clipping_distance = 1.f;//声明数据流auto depth_stream=profile.get_stream(RS2_STREAM_DEPTH).as<rs2::video_stream_profile>();auto color_stream=profile.get_stream(RS2_STREAM_COLOR).as<rs2::video_stream_profile>();//获取内参auto intrinDepth=depth_stream.get_intrinsics();auto intrinColor=color_stream.get_intrinsics();//直接获取从深度摄像头坐标系到彩色摄像头坐标系的欧式变换矩阵auto extrinDepth2Color=depth_stream.get_extrinsics_to(color_stream);while (cvGetWindowHandle(depth_win)&&cvGetWindowHandle(color_win)) // Application still alive?{//堵塞程序直到新的一帧捕获rs2::frameset frameset = pipe.wait_for_frames();//取深度图和彩色图rs2::frame color_frame = frameset.get_color_frame();//processed.first(align_to);rs2::frame depth_frame = frameset.get_depth_frame();rs2::frame depth_frame_4_show = frameset.get_depth_frame().apply_filter(c);//获取宽高const int depth_w=depth_frame.as<rs2::video_frame>().get_width();const int depth_h=depth_frame.as<rs2::video_frame>().get_height();const int color_w=color_frame.as<rs2::video_frame>().get_width();const int color_h=color_frame.as<rs2::video_frame>().get_height();//创建OPENCV类型 并传入数据Mat depth_image(Size(depth_w,depth_h),CV_16U,(void*)depth_frame.get_data(),Mat::AUTO_STEP);Mat depth_image_4_show(Size(depth_w,depth_h),CV_8UC3,(void*)depth_frame_4_show.get_data(),Mat::AUTO_STEP);Mat color_image(Size(color_w,color_h),CV_8UC3,(void*)color_frame.get_data(),Mat::AUTO_STEP);//实现深度图对齐到彩色图Mat result=align_Depth2Color(depth_image,color_image,profile);//显示imshow(depth_win,depth_image_4_show);imshow(color_win,color_image);imshow("result",result);waitKey(10);}return 0;
}
实现效果：
原文链接：
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realsense D435学习(二)：深度图片对齐到彩色图片
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