概述代币增发模式DAPP系统开发搭建(现成演示版)

2022-10-27 15:34:30 浏览数 (2)

  Heco是火币开放平台的公链基础设施,heco链智能合约dapp系统开发,未来将成为承载用户、资产和应用的基础平台。

  概述RISC-V service为Huobi Chain提供了一个支持RISC-V指令集的虚拟机服务。用户可以通过该服务自行部署和运行合约,实现强大的自定义功能。

代码语言:javascript复制
 /*************************************************************************
 2     > File Name: src/jointPointCloud.cpp
 3     > Author: Xiang gao
 4     > Mail: gaoxiang12@mails.tsinghua.edu.cn 
 5     > Created Time: 2015年07月22日 星期三 20时46分08秒
 6  ************************************************************************/
 7 
 8 #include<iostream>
 9 using namespace std;
10 
11 #include "slamBase.h"
12 
13 #include <opencv2/core/eigen.hpp>
14 
15 #include <pcl/common/transforms.h>
16 #include <pcl/visualization/cloud_viewer.h>
17 
18 // Eigen !
19 #include <Eigen/Core>
20 #include <Eigen/Geometry>
21 
22 int main( int argc, char** argv )
23 {
24     //本节要拼合data中的两对图像
25     ParameterReader pd;
26     // 声明两个帧,FRAME结构请见include/slamBase.h
27     FRAME frame1, frame2;
28     
29     //读取图像
30     frame1.rgb = cv::imread( "./data/rgb1.png" );
31     frame1.depth = cv::imread( "./data/depth1.png", -1);
32     frame2.rgb = cv::imread( "./data/rgb2.png" );
33     frame2.depth = cv::imread( "./data/depth2.png", -1 );
34 
35     // 提取特征并计算描述子
36     cout<<"extracting features"<<endl;
37     string detecter = pd.getData( "detector" );
38     string descriptor = pd.getData( "descriptor" );
39 
40     computeKeyPointsAndDesp( frame1, detecter, descriptor );
41     computeKeyPointsAndDesp( frame2, detecter, descriptor );
42 
43     // 相机内参
44     CAMERA_INTRINSIC_PARAMETERS camera;
45     camera.fx = atof( pd.getData( "camera.fx" ).c_str());
46     camera.fy = atof( pd.getData( "camera.fy" ).c_str());
47     camera.cx = atof( pd.getData( "camera.cx" ).c_str());
48     camera.cy = atof( pd.getData( "camera.cy" ).c_str());
49     camera.scale = atof( pd.getData( "camera.scale" ).c_str() );
50 
51     cout<<"solving pnp"<<endl;
52     // 求解pnp
53     RESULT_OF_PNP result = estimateMotion( frame1, frame2, camera );
54 
55     cout<<result.rvec<<endl<<result.tvec<<endl;
56 
57     // 处理result
58     // 将旋转向量转化为旋转矩阵
59     cv::Mat R;
60     cv::Rodrigues( result.rvec, R );
61     Eigen::Matrix3d r;
62     cv::cv2eigen(R, r);
63   
64     // 将平移向量和旋转矩阵转换成变换矩阵
65     Eigen::Isometry3d T = Eigen::Isometry3d::Identity();
66 
67     Eigen::AngleAxisd angle(r);
68     cout<<"translation"<<endl;
69     Eigen::Translation<double,3> trans(result.tvec.at<double>(0,0), result.tvec.at<double>(0,1), result.tvec.at<double>(0,2));
70     T = angle;
71     T(0,3) = result.tvec.at<double>(0,0); 
72     T(1,3) = result.tvec.at<double>(0,1); 
73     T(2,3) = result.tvec.at<double>(0,2);
74 
75     // 转换点云
76     cout<<"converting image to clouds"<<endl;
77     PointCloud::Ptr cloud1 = image2PointCloud( frame1.rgb, frame1.depth, camera );
78     PointCloud::Ptr cloud2 = image2PointCloud( frame2.rgb, frame2.depth, camera );
79 
80     // 合并点云
81     cout<<"combining clouds"<<endl;
82     PointCloud::Ptr output (new PointCloud());
83     pcl::transformPointCloud( *cloud1, *output, T.matrix() );
84     *output  = *cloud2;
85     pcl::io::savePCDFile("data/result.pcd", *output);
86     cout<<"Final result saved."<<endl;
87 
88     pcl::visualization::CloudViewer viewer( "viewer" );
89     viewer.showCloud( output );
90     while( !viewer.wasStopped() )
91     {
92         
93     }
94     return 0;
95 }

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