JSON files#


Original author	Bernát Gábor
Compatibility	OpenCV >= 3.0

Goal#

You’ll find answers to the following questions:

How do you print and read text entries to a file in OpenCV using YAML, XML, or JSON files?
How can you perform the same operations for OpenCV data structures?
How can this be done for your custom data structures?
How do you use OpenCV data structures, such as [cv::FileStorage](#cv::FileStorage) , [cv::FileNode](#cv::FileNode) or [cv::FileNodeIterator](#cv::FileNodeIterator) .

Source code#

C++

You can download this from here or find it in the samples/cpp/tutorial_code/core/file_input_output/file_input_output.cpp of the OpenCV source code library.

Here’s a sample code of how to achieve all the stuff enumerated at the goal list.

#include <opencv2/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 << endl
        << "usage: "                                                                      << endl
        <<  av[0] << " [output file name] (default outputfile.yml.gz)"                    << endl << endl
        << "The output file may be XML (xml), YAML (yml/yaml), or JSON (json)." << endl
        << "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 << 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)
{
    string filename;

    if (ac != 2)
    {
        help(av);
        filename = "outputfile.yml.gz";
    }
    else
        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);
        // or:
        // FileStorage fs;
        // fs.open(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 operation to file:" << filename << " completed successfully." << 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;
}

Python

You can download this from here or find it in the samples/python/tutorial_code/core/file_input_output/file_input_output.py of the OpenCV source code library.

Here’s a sample code of how to achieve all the stuff enumerated at the goal list.

from __future__ import print_function

import numpy as np
import cv2 as cv
import sys

def help(filename):
    print (
        '''
        {0} shows the usage of the OpenCV serialization functionality. \n\n
        usage:\n
            python3 {0} [output file name] (default outputfile.yml.gz)\n\n
        The output file may be XML (xml), YAML (yml/yaml), or JSON (json).\n
        You can even compress it by specifying this in its extension like xml.gz yaml.gz etc...\n
        With FileStorage you can serialize objects in OpenCV.\n\n
        For example: - create a class and have it serialized\n
                     - use it to read and write matrices.\n
        '''.format(filename)
    )

class MyData:
    A = 97
    X = np.pi
    name = 'mydata1234'

    def __repr__(self):
        s = '{ name = ' + self.name + ', X = ' + str(self.X)
        s = s + ', A = ' +  str(self.A) + '}'
        return s

    def write(self, fs, name):
        fs.startWriteStruct(name, cv.FileNode_MAP|cv.FileNode_FLOW)
        fs.write('A', self.A)
        fs.write('X', self.X)
        fs.write('name', self.name)
        fs.endWriteStruct()

    def read(self, node):
        if (not node.empty()):
            self.A = int(node.getNode('A').real())
            self.X = node.getNode('X').real()
            self.name = node.getNode('name').string()
        else:
            self.A = self.X = 0
            self.name = ''

def main(argv):
    if len(argv) != 2:
        help(argv[0])
        filename = 'outputfile.yml.gz'
    else :
        filename = argv[1]

    # write
    R = np.eye(3,3)
    T = np.zeros((3,1))
    m = MyData()

    s = cv.FileStorage(filename, cv.FileStorage_WRITE)
    # or:
    # s = cv.FileStorage()
    # s.open(filename, cv.FileStorage_WRITE)

    s.write('iterationNr', 100)

    s.startWriteStruct('strings', cv.FileNode_SEQ)
    for elem in ['image1.jpg', 'Awesomeness', '../data/baboon.jpg']:
        s.write('', elem)
    s.endWriteStruct()

    s.startWriteStruct('Mapping', cv.FileNode_MAP)
    s.write('One', 1)
    s.write('Two', 2)
    s.endWriteStruct()

    s.write('R_MAT', R)
    s.write('T_MAT', T)

    m.write(s, 'MyData')
    s.release()
    print ('Write operation to file:', filename, 'completed successfully.')

    # read
    print ('\nReading: ')
    s = cv.FileStorage()
    s.open(filename, cv.FileStorage_READ)

    n = s.getNode('iterationNr')
    itNr = int(n.real())
    print (itNr)

    if (not s.isOpened()):
        print ('Failed to open ', filename, file=sys.stderr)
        help(argv[0])
        exit(1)

    n = s.getNode('strings')
    if (not n.isSeq()):
        print ('strings is not a sequence! FAIL', file=sys.stderr)
        exit(1)

    for i in range(n.size()):
        print (n.at(i).string())

    n = s.getNode('Mapping')
    print ('Two',int(n.getNode('Two').real()),'; ')
    print ('One',int(n.getNode('One').real()),'\n')

    R = s.getNode('R_MAT').mat()
    T = s.getNode('T_MAT').mat()
    m.read(s.getNode('MyData'))

    print ('\nR =',R)
    print ('T =',T,'\n')
    print ('MyData =','\n',m,'\n')

    print ('Attempt to read NonExisting (should initialize the data structure',
            'with its default).')
    m.read(s.getNode('NonExisting'))
    print ('\nNonExisting =','\n',m)

    print ('\nTip: Open up',filename,'with a text editor to see the serialized data.')

if __name__ == '__main__':
    main(sys.argv)

Result#

Well mostly we just print out the defined numbers. On the screen of your console you could see:

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.

Nevertheless, it’s much more interesting what you may see in the output xml file:

<?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>

Or the YAML file:

%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

You may observe a runtime instance of this on the YouTube here .

File Input and Output using XML / YAML / JSON files#

Goal#

Source code#

Explanation#

Result#