OpenCV中XML文件和YAML文件的读写
OpenCV中XML文件和YAML文件的读写
代码如下：
#include <opencv2/core/core.hpp>
#include <iostream>
#include <string>
using namespace cv;
using namespace std;
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;
}
class MyData
{
public:
MyData() : A(0), X(0), id()
{}
explicit MyData(int) : A(97), X(CV_PI), id("mydata1234") // explicit to avoid implicit conversion
{}
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"];
}
public: // Data Members
int A;
double X;
string id;
};
//These write and read functions must be defined for the serialization in FileStorage to work
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;
else
x.read(node);
}
// This function will print our custom class to the console
static ostream& operator<<(ostream& out, const MyData& m)
{
out << "{ id = " << m.id << ", ";
out << "X = " << m.X << ", ";
out << "A = " << m.A << "}";
return out;
}
int main(int ac, char** av)
{
if (ac != 2)
{
help(av);
return 1;
}
string filename = av[1];
{ //write
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" << "["; // text - string sequence
fs << "image1.jpg" << "Awesomeness" << "../data/baboon.jpg";
fs << "]"; // close sequence
fs << "Mapping"; // text - mapping
fs << "{" << "One" << 1;
fs << "Two" << 2 << "}";
fs << "R" << R; // cv::Mat
fs << "T" << T;
fs << "MyData" << m; // your own data structures
fs.release(); // explicit close
cout << "Write Done." << endl;
}
{//read
cout << endl << "Reading: " << endl;
FileStorage fs;
fs.open(filename, FileStorage::READ);
int itNr;
//fs["iterationNr"] >> itNr;
itNr = (int) fs["iterationNr"];
cout << itNr;
if (!fs.isOpened())
{
cerr << "Failed to open " << filename << endl;
help(av);
return 1;
}
FileNode n = fs["strings"]; // Read string sequence - Get node
if (n.type() != FileNode::SEQ)
{
cerr << "strings is not a sequence! FAIL" << endl;
return 1;
}
FileNodeIterator it = n.begin(), it_end = n.end(); // Go through the node
for (; it != it_end; ++it)
cout << (string)*it << endl;
n = fs["Mapping"]; // Read mappings from a sequence
cout << "Two " << (int)(n["Two"]) << "; ";
cout << "One " << (int)(n["One"]) << endl << endl;
MyData m;
Mat R, T;
fs["R"] >> R; // Read cv::Mat
fs["T"] >> T;
fs["MyData"] >> m; // Read your own structure_
cout << endl
<< "R = " << R << endl;
cout << "T = " << T << endl << endl;
cout << "MyData = " << endl << m << endl << endl;
//Show default behavior for non existing nodes
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;
}
Explanation
这里只讨论XML 和 YAML 文件的读取，这是两种不同的可能会序列化的数据结构: mappings (类似STL的map) 和 element sequence (类似STL的vector). 两种结构的区别为 map 的每一个元素都有一个具有唯一性的名字，通过具有唯一性的名字（键）可以访问对应的元素值.对于序列，你需要通过他们来查询一个特定的项目.
１ XML/YAML 文件的代开和关闭
OpenCV中XML/YAML数据结构类型为cv::FileStorage，要打开硬盘上的文件，可以基于构造函数或者open()函数
string filename = "I.xml"; FileStorage fs(filename, FileStorage::WRITE); //... fs.open(filename, FileStorage::READ);
函数中的第二个参数为： WRITE, READ 或 APPEND，表示不同的操作类型（写，读或追加）。文件的扩展名表明输出文件的格式，当时用扩展名*.xml.gz*.时文件会被压缩。
当cv::FileStorage对象销毁时，文件会被自动关闭，可以通过显式调用关闭文件。
fs.release(); // explicit close
２ 文本和数字的输入输出 数据结构采用和ＳＴＬ标准库一样的输出操作符<< ，输出任何类型的数据结构首先需要指定文件名.
fs << "iterationNr" << 100;读入是一个简单的通过 [] 操作符实现的地址和映射操作 或者 通过 >> 操作符读 :
int itNr; fs["iterationNr"] >> itNr; itNr = (int) fs["iterationNr"];３ OpenCV 数据结构的读入和输出. C++风格的方法:
Mat R = Mat_<uchar >::eye (3, 3),
T = Mat_<double>::zeros(3, 1);
fs << "R" << R; // Write cv::Mat
fs << "T" << T;
fs["R"] >> R; // Read cv::Mat
fs["T"] >> T;
４ vectors (arrays) 和 associative maps的输入输出
向前面说的，我们可以输出maps 和 sequences (array, vector) 。首先我们输出变量的名字，然后指定类型为 sequence 或者 map.
对于 sequence在第一个元素前输出 "[" 字符 并且在最后一个元素后输出 "]" 字符:
fs << "strings" << "["; // text - string sequence fs << "image1.jpg" << "Awesomeness" << "baboon.jpg"; fs << "]"; // close sequence
对于 maps the drill是同样的，但是使用 "{" 和 "}" 分割字符:
fs << "Mapping"; // text - mapping
fs << "{" << "One" << 1;
fs << "Two" << 2 << "}";
读取操作使用 cv::FileNode 和 cv::FileNodeIterator 数据结构. cv::FileStorage 的操作符[]返回的是 cv::FileNode 数据类型. If the node is sequential we can use the cv::FileNodeIterator to iterate through the items:
FileNode n = fs["strings"]; // Read string sequence - Get node
if (n.type() != FileNode::SEQ)
{
cerr << "strings is not a sequence! FAIL" << endl;
return 1;
}
FileNodeIterator it = n.begin(), it_end = n.end(); // Go through the node
for (; it != it_end; ++it)
cout << (string)*it << endl;
对于 maps 使用[] 操作符访问给定的条目（或者 >> 操作符):
n = fs["Mapping"]; // Read mappings from a sequence cout << "Two " << (int)(n["Two"]) << "; "; cout << "One " << (int)(n["One"]) << endl << endl;５ 读写自己的数据结构 假设有如下结构：
class MyData
{
public:
MyData() : A(0), X(0), id() {}
public: // Data Members
int A;
double X;
string id;
};
通过 在自定义类的内部和外部添加读写函数，借助OpenCV I/O XML/YAML 接口序列化是可能的 (就像 OpenCV的数据结构一样 ) 。
类内部的部分:
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"];
}
类外部的部分：
void write(FileStorage& fs, const std::string&, const MyData& x)
{
x.write(fs);
}
void read(const FileNode& node, MyData& x, const MyData& default_value = MyData())
{
if(node.empty())
x = default_value;
else
x.read(node);
}
接下来将会定义读取不存在的节点将会发生的情况. 这种情况下返回默认的初始化值, 然而，一个更详细的解决办法是对于实例返回一个负值作为object ID.
一旦添加了使用 >>作为写操作符，使用 <<为读操作符的４个函数:
MyData m(1); fs << "MyData" << m; // your own data structures fs["MyData"] >> m;或者执行一个不存在读:
fs["NonExisting"] >> m; // Do not add a fs << "NonExisting" << m command for this to work cout << endl << "NonExisting = " << endl << m << endl;
结果
只打印出定义的数字。在控制台屏幕上看到：
Write Done.
Reading:
100image1.jpg
Awesomeness
baboon.jpg
Two 2; One 1
R = [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.
输出的XML文件
<?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>
输出的 YAML 文件:
%YAML:1.0 iterationNr: 100 strings: - "image1.jpg" - Awesomeness - "baboon.jpg" Mapping: One: 1 Two: 2 R: !!opencv-matrix rows: 3 cols: 3 dt: u data: [ 1, 0, 0, 0, 1, 0, 0, 0, 1 ] T: !!opencv-matrix rows: 3 cols: 1 dt: d data: [ 0., 0., 0. ] MyData: A: 97 X: 3.1415926535897931e+000 id: mydata1234