Opencv将数据保存到xml、yaml / 从xml、yaml读取数据
- Opencv提供了读写
xml、yaml的类实现：
- 本文重点参考：https://blog.csdn.net/cd_yourheart/article/details/122705776?spm=1001.2014.3001.5506，并将给出文件读写的具体使用实例。
1. 官方例程
1.1 写数据
#include "opencv2/core.hpp"
#include <time.h>
using namespace cv;
int main(int, char** argv)
{
FileStorage fs("test.yml", FileStorage::WRITE);
fs << "frameCount" << 5;
time_t rawtime; time(&rawtime);
fs << "calibrationDate" << asctime(localtime(&rawtime));
Mat cameraMatrix = (Mat_<double>(3,3) << 1000, 0, 320, 0, 1000, 240, 0, 0, 1);
Mat distCoeffs = (Mat_<double>(5,1) << 0.1, 0.01, -0.001, 0, 0);
fs << "cameraMatrix" << cameraMatrix << "distCoeffs" << distCoeffs;
fs << "features" << "[";
for( int i = 0; i < 3; i++ )
{
int x = rand() % 640;
int y = rand() % 480;
uchar lbp = rand() % 256;
fs << "{:" << "x" << x << "y" << y << "lbp" << "[:";
for( int j = 0; j < 8; j++ )
fs << ((lbp >> j) & 1);
fs << "]" << "}";
}
fs << "]";
fs.release();
return 0;
}
output :
%YAML:1.0
frameCount: 5
calibrationDate: "Fri Jun 17 14:09:29 2011\n"
cameraMatrix: !!opencv-matrix
rows: 3
cols: 3
dt: d
data: [ 1000., 0., 320., 0., 1000., 240., 0., 0., 1. ]
distCoeffs: !!opencv-matrix
rows: 5
cols: 1
dt: d
data: [ 1.0000000000000001e-01, 1.0000000000000000e-02,
-1.0000000000000000e-03, 0., 0. ]
features:
- { x:167, y:49, lbp:[ 1, 0, 0, 1, 1, 0, 1, 1 ] }
- { x:298, y:130, lbp:[ 0, 0, 0, 1, 0, 0, 1, 1 ] }
- { x:344, y:158, lbp:[ 1, 1, 0, 0, 0, 0, 1, 0 ] }
1.2 读数据
FileStorage fs2("test.yml", FileStorage::READ);
// first method: use (type) operator on FileNode.
int frameCount = (int)fs2["frameCount"];
String date;
// second method: use FileNode::operator >>
fs2["calibrationDate"] >> date;
Mat cameraMatrix2, distCoeffs2;
fs2["cameraMatrix"] >> cameraMatrix2;
fs2["distCoeffs"] >> distCoeffs2;
cout << "frameCount: " << frameCount << endl
<< "calibration date: " << date << endl
<< "camera matrix: " << cameraMatrix2 << endl
<< "distortion coeffs: " << distCoeffs2 << endl;
FileNode features = fs2["features"];
FileNodeIterator it = features.begin(), it_end = features.end();
int idx = 0;
std::vector<uchar> lbpval;
// iterate through a sequence using FileNodeIterator
for( ; it != it_end; ++it, idx++ )
{
cout << "feature #" << idx << ": ";
cout << "x=" << (int)(*it)["x"] << ", y=" << (int)(*it)["y"] << ", lbp: (";
// you can also easily read numerical arrays using FileNode >> std::vector operator.
(*it)["lbp"] >> lbpval;
for( int i = 0; i < (int)lbpval.size(); i++ )
cout << " " << (int)lbpval[i];
cout << ")" << endl;
}
fs2.release();
2. 读写xml
#include <iostream>
#include "opencv2/opencv.hpp"
using namespace std;
#define WRITE_OR_READ
int main() {
//===========将数据写入到xml文件中================
#ifdef WRITE_OR_READ
string name = "insomnia";
int age = 18;
float height = 1.83;
char sex = 'M';
cv::Mat matrix_eye = cv::Mat::eye(3, 3, CV_64F);
cv::FileStorage fs("./test.xml", cv::FileStorage::WRITE);//会覆盖当前文件，不存在则新建文件
if (fs.isOpened())
{
fs << "name" << name << "age" << age << "height" << height << "sex" << sex;//可以连续写入
fs << "matrix_eye" << matrix_eye;//也可以依次写入
fs.release();//release after used
}
//===========从xml文件中读取数据================
#else
string name;
int age;
float height;
char sex;
cv::Mat matrix_eye;
cv::FileStorage fs("./test.xml", cv::FileStorage::READ);
if (fs.isOpened()) {
fs["name"] >> name;
fs["age"] >> age;
fs["height"] >> height;
int temp;
fs["sex"] >> temp;//这里不能直接读到char，所以转换了一下
sex = (char)temp;
fs["matrix_eye"] >> matrix_eye;
fs.release();
cout << "name: " << name << endl;
cout << "age: " << age << endl;
cout << "height: " << height << endl;
cout << "sex: " << sex << endl;
cout << "matrix_eye: " << endl << matrix_eye << endl;
cout << "matrix_eye.size().height: " << matrix_eye.size().height << endl;
cout << "matrix_eye.at<double>(1, 0): " << matrix_eye.at<double>(1, 0) << endl;
}
#endif
return 0;
}
将数据写入到xml文件后，打开查看一下
格式是自动生成的，只是将数据填充了进去。可以看到第一行是xml版本信息，不用考虑。第二行和最后一行是最外层的标签。
然后所有保存的数据都是一个并列的关系，同等级。只是像Mat这种数据类型，又有细分属性而已。
从xml文件中读取一下数据，看下输出结果
3. 读写yaml
#include<opencv2/opencv.hpp>
#include<iostream>
using namespace std;
using namespace cv;
//#define WRITE_OR_READ
int main()
{
#ifdef WRITE_OR_READ
//1.创建文件
cv::FileStorage fwrite("./test.yaml", cv::FileStorage::WRITE);
//2.写入数据
string name = "insomnia";
int age = 18;
float height = 1.83;
char sex = 'M';
cv::Mat matrix_eye = cv::Mat::eye(3, 3, CV_64F);
fwrite << "name " << name;
fwrite << "age " << age;
fwrite << "height " << height;
fwrite << "sex " << sex;
fwrite << "matrix_eye " << matrix_eye;
//3.关闭文件
fwrite.release();
return 0;
#else
//1.读取文件指针
string strSettingsFile = "./test.yaml";
cv::FileStorage fread(strSettingsFile.c_str(), cv::FileStorage::READ);
//2.判断是否打开成功
if (!fread.isOpened())
{
cout << "Failed to open settings file at: " << strSettingsFile << endl;
return 0;
}
else cout << "success to open file at: " << strSettingsFile << endl;
//3.打开文件后读取数据
string name;
int age;
float height;
char sex;
cv::Mat matrix_eye;
fread["name"] >> name;
fread["age"] >> age;
fread["height"] >> height;
int temp;
fread["sex"] >> temp;
sex = (char)temp;
fread["matrix_eye"] >> matrix_eye;
cout << "name=" << name << endl;
cout << "age=" << age << endl;
cout << "height=" << height << endl;
cout << "sex=" << sex << endl;
cout << "matrix_eye=" << endl << matrix_eye << endl;
cout << matrix_eye.size().height << endl;
//4.关闭文件
fread.release();
return 0;
#endif
}
保存的yaml文件
读取文件的结果
文章来源：https://www.toymoban.com/news/detail-639093.html
4. 保存矩阵与点集
//写数据
cv::FileStorage fs;
std::string label_ = "abc.xml";
fs.open(label_.c_str(), cv::FileStorage::WRITE);
std::string str_ = "image" + std::to_string(i+1);
cv::Mat _pts(p_result); //p_result define:std::vector<cv::Point2f>p_result;
fs << str_ << _pts;
fs.release();
//**************************
//读数据
cv::FileStorage fs;
fs.open( "abc.xml", cv::FileStorage::READ);
cv::Mat m_pts;
fs[str] >> m_pts;
std::vector<cv::Point2f>pts;
for (int i = 1; i < m_pts.rows; ++i)
{
cv::Point2f _pt(m_pts.ptr<float>(i, 0)[0], m_pts.ptr<float>(i, 0)[1]);
pts.push_back(_pt);
std::cout << _pt << "\n";
}
5.读写 xml/yaml使用实例
5.1 写入
使用以下过程将内容写入 XML、YAML 或 JSON：
- 创建新的 FileStorage 并打开它进行写入。可以通过对采用文件名的 FileStorage：：FileStorage 构造函数的单个调用来完成此操作，
也可以使用默认构造函数，然后调用 FileStorage：：open。文件的格式（XML、YAML 或 JSON）由文件扩展名确定（分别为“.xml”、
“.yml”/“.yaml”和“.json”）。
- 使用 streaming operator 写入所需的所有数据，就像在 STL 流中一样。
- 使用 FileStorage：：release 关闭文件。FileStorage 析构函数也会关闭该文件。
#include<opencv2\opencv.hpp>
#include<opencv2\highgui\highgui.hpp>
using namespace std;
using namespace cv;
typedef struct
{
int x;
int y;
string s;
}test_t;
int main(int argc, char** argv)
{
FileStorage fs("test.xml", FileStorage::WRITE); //填入写操作
//测试数据
int a1 = 2;
char a2 = -1;
string str = "hello sysu!";
int arr[10] = { 1,2,3,4,5,6,7,8,9,10 };
test_t t = { 3,4,"hi sysu" };
map<string, int> m;
m["kobe"] = 100;
m["james"] = 99;
m["curry"] = 98;
//写入文件操作,先写标注在写数据
fs << "int_data" << a1;
fs << "char_data" << a2;
fs << "string_data" << str;
//写入数组
fs <<"array_data"<< "["; //数组开始
for (int i = 0; i < 10; i++)
{
fs << arr[i];
}
fs << "]"; //数组结束
//写入结构体
fs << "struct_data" << "{"; //结构体开始
fs << "x" << t.x;
fs << "y" << t.y;
fs << "s" << t.s;
fs << "}"; //结构结束
//map的写入
fs << "map_data" << "{"; //map的开始写入
map<string, int>::iterator it = m.begin();
for (; it != m.end(); it++)
{
fs << it->first << it->second;
}
fs << "}"; //map写入结束
return 0;
}
- 其结果：
%YAML:1.0
frameCount: 5
calibrationDate: "Fri Jun 17 14:09:29 2011\n"
cameraMatrix: !!opencv-matrix
rows: 3
cols: 3
dt: d
data: [ 1000., 0., 320., 0., 1000., 240., 0., 0., 1. ]
distCoeffs: !!opencv-matrix
rows: 5
cols: 1
dt: d
data: [ 1.0000000000000001e-01, 1.0000000000000000e-02,
-1.0000000000000000e-03, 0., 0. ]
features:
- { x:167, y:49, lbp:[ 1, 0, 0, 1, 1, 0, 1, 1 ] }
- { x:298, y:130, lbp:[ 0, 0, 0, 1, 0, 0, 1, 1 ] }
- { x:344, y:158, lbp:[ 1, 1, 0, 0, 0, 0, 1, 0 ] }
5.2 读取
要读取以前编写的 XML、YAML 或 JSON 文件，请执行以下操作：
- 使用 FileStorage：：FileStorage 构造函数或 FileStorage：：open 方法打开文件存储。在当前实现中，
整个文件被解析，文件存储的整个表示形式作为文件节点的层次结构构建在内存中（参见 FileNode)
- 读取您感兴趣的数据。使用 FileStorage：：operator []、FileNode：：operator [] 和/或 FileNodeIterator。
- 使用 FileStorage：：release 关闭存储。
- 代码实现：
#include<opencv2\opencv.hpp>
#include<opencv2\highgui\highgui.hpp>
using namespace std;
using namespace cv;
typedef struct
{
int x;
int y;
string s;
}test_t;
int main(int argc, char** argv)
{
FileStorage fs2("test.yml", FileStorage::READ);
// first method: use (type) operator on FileNode.
int frameCount = (int)fs2["frameCount"];
String date;
// second method: use FileNode::operator >>
fs2["calibrationDate"] >> date;
Mat cameraMatrix2, distCoeffs2;
fs2["cameraMatrix"] >> cameraMatrix2;
fs2["distCoeffs"] >> distCoeffs2;
cout << "frameCount: " << frameCount << endl
<< "calibration date: " << date << endl
<< "camera matrix: " << cameraMatrix2 << endl
<< "distortion coeffs: " << distCoeffs2 << endl;
FileNode features = fs2["features"];
FileNodeIterator it = features.begin(), it_end = features.end();
int idx = 0;
std::vector<uchar> lbpval;
// iterate through a sequence using FileNodeIterator
for( ; it != it_end; ++it, idx++ )
{
cout << "feature #" << idx << ": ";
cout << "x=" << (int)(*it)["x"] << ", y=" << (int)(*it)["y"] << ", lbp: (";
// you can also easily read numerical arrays using FileNode >> std::vector operator.
(*it)["lbp"] >> lbpval;
for( int i = 0; i < (int)lbpval.size(); i++ )
cout << " " << (int)lbpval[i];
cout << ")" << endl;
}
fs2.release();
return 0;
}
参考：
1.OpenCV 读写xml和yml文件文章来源地址https://www.toymoban.com/news/detail-639093.html
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