Full Code of alyssaq/opencv for AI

Repository: alyssaq/opencv
Branch: master
Commit: 76191301ee25
Files: 5
Total size: 12.1 KB

Directory structure:
gitextract_ishih8ed/

├── .gitignore
├── CMakeLists.txt
├── Makefile
├── README.md
└── squares.cpp

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FILE CONTENTS
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FILE: .gitignore
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CMakeFiles
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squares


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FILE: CMakeLists.txt
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cmake_minimum_required(VERSION 2.8)
project( squares )
find_package( OpenCV REQUIRED )
add_executable( squares squares.cpp )
target_link_libraries( squares ${OpenCV_LIBS} )

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FILE: Makefile
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================================================
FILE: README.md
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# Playing with C++ OpenCV

**Aim:** Find squares in an image

## To compile and run

    > cmake .  
    > make
    > ./squares


### Sample input and output images in /imgs


<img src="https://raw.github.com/alyssaq/opencv/master/imgs/2stickies.jpg" width="45%" /> 
&nbsp;&nbsp;&nbsp; 
<img src="https://raw.github.com/alyssaq/opencv/master/imgs/out-2stickies.jpg" width="45%"/>

<br>

<img src="https://raw.github.com/alyssaq/opencv/master/imgs/manyStickies.jpg" width="45%" /> 
&nbsp;&nbsp;&nbsp; 
<img src="https://raw.github.com/alyssaq/opencv/master/imgs/out-manyStickies.jpg" width="45%"/>

### References - To improve results

* http://stackoverflow.com/questions/8667818/opencv-c-obj-c-detecting-a-sheet-of-paper-square-detection   
* http://stackoverflow.com/questions/10533233/opencv-c-obj-c-advanced-square-detection    
* http://stackoverflow.com/questions/14221591/detection-square-opencv-and-c    
* http://stackoverflow.com/questions/7755647/opencv-extract-area-of-an-image-from-a-vector-of-squares/7756000#7756000    
* http://stackoverflow.com/questions/13523837/find-corner-of-papers/13532779#13532779    
* [Automatic perspective correction for quadrilateral objects](https://web.archive.org/web/20160316131624/http://opencv-code.com/tutorials/automatic-perspective-correction-for-quadrilateral-objects/) - [Code on github](https://github.com/bsdnoobz/opencv-code/blob/master/quad-segmentation.cpp)
* [Detecting simple shapes in an image](https://web.archive.org/web/20150317002418/http://opencv-code.com/tutorials/detecting-simple-shapes-in-an-image/) - [Code on github](https://github.com/bsdnoobz/opencv-code/blob/master/shape-detect.cpp)


================================================
FILE: squares.cpp
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// The "Square Detector" program.
// It loads several images sequentially and tries to find squares in
// each image

#include "opencv2/core/core.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"

#include <iostream>
#include <math.h>
#include <string.h>

using namespace cv;
using namespace std;

static void help()
{
    cout <<
    "\nA program using pyramid scaling, Canny, contours, contour simpification and\n"
    "memory storage to find squares in a list of images\n"
    "Returns sequence of squares detected on the image.\n"
    "the sequence is stored in the specified memory storage\n"
    "Call:\n"
    "./squares\n"
    "Using OpenCV version %s\n" << CV_VERSION << "\n" << endl;
}


int thresh = 50, N = 5;
const char* wndname = "Square Detection Demo";

// helper function:
// finds a cosine of angle between vectors
// from pt0->pt1 and from pt0->pt2
static double angle( Point pt1, Point pt2, Point pt0 )
{
    double dx1 = pt1.x - pt0.x;
    double dy1 = pt1.y - pt0.y;
    double dx2 = pt2.x - pt0.x;
    double dy2 = pt2.y - pt0.y;
    return (dx1*dx2 + dy1*dy2)/sqrt((dx1*dx1 + dy1*dy1)*(dx2*dx2 + dy2*dy2) + 1e-10);
}

// returns sequence of squares detected on the image.
// the sequence is stored in the specified memory storage
static void findSquares( const Mat& image, vector<vector<Point> >& squares )
{
    squares.clear();

//s    Mat pyr, timg, gray0(image.size(), CV_8U), gray;

    // down-scale and upscale the image to filter out the noise
    //pyrDown(image, pyr, Size(image.cols/2, image.rows/2));
    //pyrUp(pyr, timg, image.size());


    // blur will enhance edge detection
    Mat timg(image);
    medianBlur(image, timg, 9);
    Mat gray0(timg.size(), CV_8U), gray;

    vector<vector<Point> > contours;

    // find squares in every color plane of the image
    for( int c = 0; c < 3; c++ )
    {
        int ch[] = {c, 0};
        mixChannels(&timg, 1, &gray0, 1, ch, 1);

        // try several threshold levels
        for( int l = 0; l < N; l++ )
        {
            // hack: use Canny instead of zero threshold level.
            // Canny helps to catch squares with gradient shading
            if( l == 0 )
            {
                // apply Canny. Take the upper threshold from slider
                // and set the lower to 0 (which forces edges merging)
                Canny(gray0, gray, 5, thresh, 5);
                // dilate canny output to remove potential
                // holes between edge segments
                dilate(gray, gray, Mat(), Point(-1,-1));
            }
            else
            {
                // apply threshold if l!=0:
                //     tgray(x,y) = gray(x,y) < (l+1)*255/N ? 255 : 0
                gray = gray0 >= (l+1)*255/N;
            }

            // find contours and store them all as a list
            findContours(gray, contours, RETR_LIST, CHAIN_APPROX_SIMPLE);

            vector<Point> approx;

            // test each contour
            for( size_t i = 0; i < contours.size(); i++ )
            {
                // approximate contour with accuracy proportional
                // to the contour perimeter
                approxPolyDP(Mat(contours[i]), approx, arcLength(Mat(contours[i]), true)*0.02, true);

                // square contours should have 4 vertices after approximation
                // relatively large area (to filter out noisy contours)
                // and be convex.
                // Note: absolute value of an area is used because
                // area may be positive or negative - in accordance with the
                // contour orientation
                if( approx.size() == 4 &&
                    fabs(contourArea(Mat(approx))) > 1000 &&
                    isContourConvex(Mat(approx)) )
                {
                    double maxCosine = 0;

                    for( int j = 2; j < 5; j++ )
                    {
                        // find the maximum cosine of the angle between joint edges
                        double cosine = fabs(angle(approx[j%4], approx[j-2], approx[j-1]));
                        maxCosine = MAX(maxCosine, cosine);
                    }

                    // if cosines of all angles are small
                    // (all angles are ~90 degree) then write quandrange
                    // vertices to resultant sequence
                    if( maxCosine < 0.3 )
                        squares.push_back(approx);
                }
            }
        }
    }
}


// the function draws all the squares in the image
static void drawSquares( Mat& image, const vector<vector<Point> >& squares )
{
    for( size_t i = 0; i < squares.size(); i++ )
    {
        const Point* p = &squares[i][0];

        int n = (int)squares[i].size();
        //dont detect the border
        if (p-> x > 3 && p->y > 3)
          polylines(image, &p, &n, 1, true, Scalar(0,255,0), 3, LINE_AA);
    }

    imshow(wndname, image);
}


int main(int /*argc*/, char** /*argv*/)
{
    static const char* names[] = { "imgs/2Stickies.jpg", "imgs/manyStickies.jpg",0 };
    help();
    namedWindow( wndname, 1 );
    vector<vector<Point> > squares;

    for( int i = 0; names[i] != 0; i++ )
    {
        Mat image = imread(names[i], 1);
        if( image.empty() )
        {
            cout << "Couldn't load " << names[i] << endl;
            continue;
        }

        findSquares(image, squares);
        drawSquares(image, squares);
        //imwrite( "out", image );
        int c = waitKey();
        if( (char)c == 27 )
            break;
    }

    return 0;
}