yamlcpp遍历_OpenCV文件输入和输出使用XML和YAML文件
目標
您會找到以下問題的答案：如何使用YAML或XML文件打印和讀取文本和OpenCV文本條目？
OpenCV數據結構如何做同樣的操作？
如何為您的數據結構做這個？
源代碼
您可以從這里下載，也可以在samples/cpp/tutorial_code/core/file_input_output/file_input_output.cppOpenCV源代碼庫中找到它。
以下是如何實現目標列表中枚舉的所有內容的示例代碼。#include
#include
#include
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<
{
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_::eye(3, 3),
T = Mat_::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;
}
說明
這里我們僅談論XML和YAML文件輸入。您的輸出(及其相應的輸入)文件可能只有這些擴展中的一個和結構來自此。它們是可以序列化的兩種數據結構：映射(如STL映射)和元素序列(如STL向量)。這些之間的區別是，在地圖中，每個元素都有一個唯一的名稱，通過您可以訪問它。對于序列，您需要通過它們查詢特定項目。XML / YAML文件打開和關閉。在將任何內容寫入此類文件之前，您需要將其打開并結束關閉。OpenCV中的XML / YAML數據結構是cv :: FileStorage。要指定文件在硬盤驅動器上綁定的結構，您可以使用其構造函數或open()函數：string filename = "I.xml";
FileStorage fs(filename, FileStorage::WRITE);
//...
fs.open(filename, FileStorage::READ);
您使用第二個參數中的任何一個是一個常數，指定您可以在其上執行的操作類型：WRITE，READ或APPEND。文件名中指定的擴展名也可以確定要使用的輸出格式。如果指定擴展名，例如* .xml.gz *，輸出可能會被壓縮。
當cv :: FileStorage對象被銷毀時，文件會自動關閉。但是，您可以使用發布功能顯式地調用此功能：fs.release(); // explicit close文本和數字的輸入和輸出。數據結構使用與STL庫相同的<
讀入是一個簡單的尋址(通過[]操作符)和轉換操作或通過>>操作符讀取：int itNr;
fs["iterationNr"] >> itNr;
itNr = (int) fs["iterationNr"];
OpenCV數據結構的輸入/輸出。那么這些行為就像基本的C ++類型一樣：Mat R = Mat_::eye (3, 3),
T = Mat_::zeros(3, 1);
fs << "R" << R; // Write cv::Mat
fs << "T" << T;
fs["R"] >> R; // Read cv::Mat
fs["T"] >> T;
向量(數組)和關聯圖的輸入/輸出。如前所述，我們可以輸出地圖和序列(數組，向量)。再次，我們首先打印變量的名稱，然后我們必須指定我們的輸出是序列還是地圖。對于第一個元素之前的序列打印“[”字符，最后一個“]”字符后：fs << "strings" << "["; // text - string sequence
fs << "image1.jpg" << "Awesomeness" << "baboon.jpg";
fs << "]"; // close sequence
對于地圖，鉆頭是一樣的，現在我們使用“{”和“}”分隔符：fs << "Mapping"; // text - mapping
fs << "{" << "One" << 1;
fs << "Two" << 2 << "}";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;
對于地圖，您可以再次使用[]運算符來訪問給定項目(或>>運算符)：n = fs["Mapping"]; // Read mappings from a sequence
cout << "Two " << (int)(n["Two"]) << "; ";
cout << "One " << (int)(n["One"]) << endl << endl;
讀寫自己的數據結構。假設你有一個數據結構，如：class MyData
{
public:
MyData() : A(0), X(0), id() {}
public: // Data Members
int A;
double X;
string id;
};
通過OpenCV I / O XML / YAML接口(就像OpenCV數據結構一樣)，可以通過在類中添加一個讀取和寫入函數來對其進行序列化。對于內部：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"];
}
那么你需要在類之外添加以下函數定義：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);
}
在這里您可以看到，在閱讀部分中，我們定義了如果用戶嘗試讀取不存在的節點會發生什么。在這種情況下，我們只返回默認的初始化值，但是更詳細的解決方案是返回一個對象ID的減號值。
一旦添加了這四個函數，就可以使用>>操作符進行寫操作，而<
fs << "MyData" << m; // your own data structures
fs["MyData"] >> m; // Read your own structure_
或嘗試閱讀一個不存在的閱讀：fs["NonExisting"] >> m; // Do not add a fs << "NonExisting" << m command for this to work
cout << endl << "NonExisting = " << endl << m << endl;
結果
主要是我們打印出定義的數字。您可以在控制臺的屏幕上看到：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.
不過，輸出xml文件中可能會看到的更有趣：<?xml version="1.0"?>
100
image1.jpg Awesomeness baboon.jpg
1
2
3
3
u1 0 0 0 1 0 0 0 1
3
1
d0. 0. 0.
97
3.1415926535897931e+000
mydata1234
或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
總結
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