windows环境下visual studio驱动微软Azure kinect 并显示图像(IR+RGB+depth)和一些坑

发光的小豆芽

已于 2024-06-13 15:32:40 修改

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分类专栏： Azure Kinect 文章标签： microsoft windows visual studio

于 2024-06-13 15:24:07 首次发布

本文链接：https://blog.youkuaiyun.com/learner_jj/article/details/139653815

今天又来写笔记了，最近玩Azure kinect 。记录一下用VS 驱动这个相机的代码和坑。具体如下：
（1）整体代码块（代码是在网上下载的参考，我修改了个别语句，已实测可用可出图）

//C++
#include <iostream>
#include <fstream>
#include <chrono>
#include <string>

 //OpenCV
#include <opencv2/opencv.hpp>
#include <opencv2/core.hpp>
#include <opencv2/imgcodecs.hpp>
#include <opencv2/highgui.hpp>
#include <opencv2/video.hpp>

 //Kinect DK
#include <k4a/k4a.hpp>
#include <math.h>
#include <sstream>

using namespace cv;
using namespace std;

//宏
//方便控制是否 std::cout 信息
#define DEBUG_std_cout 0


static void create_xy_table(const k4a_calibration_t* calibration, k4a_image_t xy_table)
{
   
   
	k4a_float2_t* table_data = (k4a_float2_t*)(void*)k4a_image_get_buffer(xy_table);

	int width = calibration->depth_camera_calibration.resolution_width;
	int height = calibration->depth_camera_calibration.resolution_height;

	k4a_float2_t p;
	k4a_float3_t ray;
	int valid;

	for (int y = 0, idx = 0; y < height; y++)
	{
   
   
		p.xy.y = (float)y;
		for (int x = 0; x < width; x++, idx++)
		{
   
   
			p.xy.x = (float)x;

			k4a_calibration_2d_to_3d(
				calibration, &p, 1.f, K4A_CALIBRATION_TYPE_DEPTH, K4A_CALIBRATION_TYPE_DEPTH, &ray, &valid);

			if (valid)
			{
   
   
				table_data[idx].xy.x = ray.xyz.x;
				table_data[idx].xy.y = ray.xyz.y;
			}
			else
			{
   
   
				table_data[idx].xy.x = nanf("");
				table_data[idx].xy.y = nanf("");
			}
		}
	}
}

static void generate_point_cloud(const k4a::image depth_image, const k4a_image_t xy_table, k4a_image_t point_cloud, int* point_count)
{
   
   
	int width = depth_image.get_width_pixels();
	int height = depth_image.get_height_pixels();
	//int height = k4a_image_get_height_pixels(depth_image);

	uint16_t* depth_data = (uint16_t*)(void*)depth_image.get_buffer();
	k4a_float2_t* xy_table_data = (k4a_float2_t*)(void*)k4a_image_get_buffer(xy_table);
	k4a_float3_t* point_cloud_data = (k4a_float3_t*)(void*)k4a_image_get_buffer(point_cloud);

	*point_count = 0;
	for (int i = 0; i < width * height; i++)
	{
   
   
		if (depth_data[i] != 0 && !isnan(xy_table_data[i].xy.x) && !isnan(xy_table_data[i].xy.y))
		{
   
   
			point_cloud_data[i].xyz.x = xy_table_data[i].xy.x * (float)depth_data[i];
			point_cloud_data[i].xyz.y = xy_table_data[i].xy.y * (float)depth_data[i];
			point_cloud_data[i].xyz.z = (float)depth_data[i];
			(*point_count)++;
		}
		else
		{
   
   
			point_cloud_data[i].xyz.x = nanf("");
			point_cloud_data[i].xyz.y = nanf("");
			point_cloud_data[i].xyz.z = nanf("");
		}
	}
}

static void write_point_cloud(const char* file_name, const k4a_image_t point_cloud, int point_count)