opencv 使用XML和YAML格式来输入输出文件

源码

链接 link

#include <opencv2/core.hpp>
#include <iostream>
#include <string>using namespace cv;
using namespace std;// 帮助信息函数
static void help(char** av)
{cout << endl<< av[0] << " shows the usage of the OpenCV serialization functionality." << endl<< "usage: " << endl<< av[0] << " outputfile.yml.gz" << endl<< "The output file may be either XML (xml) or YAML (yml/yaml). You can even compress it by "<< "specifying this in its extension like xml.gz yaml.gz etc... " << endl<< "With FileStorage you can serialize objects in OpenCV by using the << and >> operators" << endl<< "For example: - create a class and have it serialized" << endl<< " - use it to read and write matrices." << endl;
}// 自定义数据结构 MyData
// 主要提供序列化和反序列化相关的读写功能
class MyData
{
public:MyData() : A(0), X(0), id() {}explicit MyData(int) : A(97), X(CV_PI), id("mydata1234") {}void write(FileStorage& fs) const{fs << "{" << "A" << A << "X" << X << "id" << id << "}";}void read(const FileNode& node){A = (int)node["A"];X = (double)node["X"];id = (string)node["id"];}public:int A;double X;string id;
};// 序列化和反序列化的辅助函数
static void write(FileStorage& fs, const std::string&, const MyData& x)
{x.write(fs);
}static void read(const FileNode& node, MyData& x, const MyData& default_value = MyData())
{if (node.empty())x = default_value;elsex.read(node);
}// 重载输出运算符
static ostream& operator<<(ostream& out, const MyData& m)
{out << "{ id = " << m.id << ", ";out << "X = " << m.X << ", ";out << "A = " << m.A << "}";return out;
}// 主函数
int main(int ac, char** av)
{if (ac != 2){help(av);return 1;}string filename = av[1];{ // 写操作Mat R = Mat_<uchar>::eye(3, 3),T = Mat_<double>::zeros(3, 1);MyData m(1);FileStorage fs(filename, FileStorage::WRITE);fs << "iterationNr" << 100;fs << "strings" << "["; fs << "image1.jpg" << "Awesomeness" << "../data/baboon.jpg";fs << "]"; fs << "Mapping";fs << "{" << "One" << 1;fs << "Two" << 2 << "}";fs << "R" << R; fs << "T" << T;fs << "MyData" << m;fs.release(); cout << "Write Done." << endl;}{ // 读操作cout << endl << "Reading: " << endl;FileStorage fs;fs.open(filename, FileStorage::READ);if (!fs.isOpened()){cerr << "Failed to open " << filename << endl;help(av);return 1;}int itNr;itNr = (int) fs["iterationNr"];cout << itNr << endl;FileNode n = fs["strings"];if (n.type() != FileNode::SEQ){cerr << "strings is not a sequence! FAIL" << endl;return 1;}FileNodeIterator it = n.begin(), it_end = n.end();for (; it != it_end; ++it)cout << (string)*it << endl;n = fs["Mapping"];cout << "Two " << (int)(n["Two"]) << "; ";cout << "One " << (int)(n["One"]) << endl << endl;MyData m;Mat R, T;fs["R"] >> R;fs["T"] >> T;fs["MyData"] >> m;cout << "R = " << R << endl;cout << "T = " << T << endl << endl;cout << "MyData = " << endl << m << endl << endl;cout << "Attempt to read NonExisting (should initialize the data structure with its default).";fs["NonExisting"] >> m;cout << endl << "NonExisting = " << endl << m << endl;}cout << endl<< "Tip: Open up " << filename << " with a text editor to see the serialized data." << endl;return 0;
}

解析

XML/YAML文件的开关。
在Opencv中XML和YAML的数据结构是cv::FileStorage。

 FileStorage fs(filename, FileStorage::WRITE);// or:// FileStorage fs;// fs.open(filename, FileStorage::WRITE);

该文件会在cv::FileStorage对象被销毁时自动关闭，但是你还是需要使用释放函数来额外声明一下。

fs.release(); // explicit close

文本和数字的输入输出。
在c++中，数据结构使用STL库中的<<输出操作符，如下所示。

 fs << "iterationNr" << 100;

读入是一个简单的寻址(通过[]操作符)和强制类型转换操作，或者通过>>操作符进行读操作。

 int itNr;//fs["iterationNr"] >> itNr;itNr = (int) fs["iterationNr"];

Opencv数据结构的输入输出

 Mat R = Mat_<uchar>::eye(3, 3),T = Mat_<double>::zeros(3, 1);fs << "R" << R; // cv::Matfs << "T" << T;fs["R"] >> R; // Read cv::Matfs["T"] >> T;

vector和相关map的输入输出
读写数据结构
举一个数据结构的例子

class MyData
{
public:MyData() : A(0), X(0), id() {}
public: // Data Membersint A;double X;string id;
};

在c++中，可以通过OpenCV I/O XML/YAML接口(就像OpenCV数据结构的情况一样)通过在类内外添加读和写函数来序列化它。

 void write(FileStorage& fs) const //Write serialization for this class{fs << "{" << "A" << A << "X" << X << "id" << id << "}";}void read(const FileNode& node) //Read serialization for this class{A = (int)node["A"];X = (double)node["X"];id = (string)node["id"];}

在C++中，你还需要添加在该类之外的函数定义：

static void write(FileStorage& fs, const std::string&, const MyData& x)
{x.write(fs);
}
static void read(const FileNode& node, MyData& x, const MyData& default_value = MyData()){if(node.empty())x = default_value;elsex.read(node);
}

在这里，您可以观察到，在read部分中，我们定义了如果用户试图读取不存在的节点会发生什么。在这种情况下，我们只返回默认的初始化值，然而，更详细的解决方案是返回例如对象ID的- 1值。

添加了这四个函数后，使用>>操作符进行写操作，使用<<操作符进行读操作。

 MyData m(1);fs << "MyData" << m; // your own data structuresfs["MyData"] >> m; // Read your own structure_

或：

 cout << "Attempt to read NonExisting (should initialize the data structure with its default).";fs["NonExisting"] >> m;cout << endl << "NonExisting = " << endl << m << endl;

结果

Write Done.Reading:
100image1.jpg
Awesomeness
baboon.jpg
Two 2; One 1R = [1, 0, 0;0, 1, 0;0, 0, 1]
T = [0; 0; 0]MyData =
{ id = mydata1234, X = 3.14159, A = 97}Attempt to read NonExisting (should initialize the data structure with its default).
NonExisting =
{ id = , X = 0, A = 0}Tip: Open up output.xml with a text editor to see the serialized data.

输出

XML

<?xml version="1.0"?>
<opencv_storage>
<iterationNr>100</iterationNr>
<strings>image1.jpg Awesomeness baboon.jpg</strings>
<Mapping><One>1</One><Two>2</Two></Mapping>
<R type_id="opencv-matrix"><rows>3</rows><cols>3</cols><dt>u</dt><data>1 0 0 0 1 0 0 0 1</data></R>
<T type_id="opencv-matrix"><rows>3</rows><cols>1</cols><dt>d</dt><data>0. 0. 0.</data></T>
<MyData><A>97</A><X>3.1415926535897931e+000</X><id>mydata1234</id></MyData>
</opencv_storage>

YAML

%YAML:1.0
iterationNr: 100
strings:- "image1.jpg"- Awesomeness- "baboon.jpg"
Mapping:One: 1Two: 2
R: !!opencv-matrixrows: 3cols: 3dt: udata: [ 1, 0, 0, 0, 1, 0, 0, 0, 1 ]
T: !!opencv-matrixrows: 3cols: 1dt: ddata: [ 0., 0., 0. ]
MyData:A: 97X: 3.1415926535897931e+000id: mydata1234