| OpenCV 3.4.8 Open Source Computer Vision

samples/tapi/squares.cpp

A program using pyramid scaling, Canny, contours and contour simplification to find squares in the input image.

#include "opencv2/core.hpp"
#include "opencv2/core/ocl.hpp"
#include "opencv2/core/utility.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/imgcodecs.hpp"
#include "opencv2/highgui.hpp"
#include <iostream>
using namespace cv;
using namespace std;
int thresh = 50, N = 11;
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.
static void findSquares( const UMat& image, vector<vector<Point> >& squares )
{
squares.clear();
UMat 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());
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, gray0, 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, 0, thresh, 5);
// dilate canny output to remove potential
// holes between edge segments
dilate(gray, gray, UMat(), Point(-1,-1));
}
else
{
// apply threshold if l!=0:
// tgray(x,y) = gray(x,y) < (l+1)*255/N ? 255 : 0
threshold(gray0, gray, (l+1)*255/N, 255, THRESH_BINARY);
}
// 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(contours[i], approx, arcLength(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(approx)) > 1000 &&
isContourConvex(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( UMat& _image, const vector<vector<Point> >& squares )
{
Mat image = _image.getMat(ACCESS_WRITE);
for( size_t i = 0; i < squares.size(); i++ )
{
const Point* p = &squares[i][0];
int n = (int)squares[i].size();
polylines(image, &p, &n, 1, true, Scalar(0,255,0), 3, LINE_AA);
}
}
// draw both pure-C++ and ocl square results onto a single image
static UMat drawSquaresBoth( const UMat& image,
const vector<vector<Point> >& sqs)
{
UMat imgToShow(Size(image.cols, image.rows), image.type());
image.copyTo(imgToShow);
drawSquares(imgToShow, sqs);
return imgToShow;
}
int main(int argc, char** argv)
{
const char* keys =
"{ i input | ../data/pic1.png | specify input image }"
"{ o output | squares_output.jpg | specify output save path}"
"{ h help | | print help message }"
"{ m cpu_mode | | run without OpenCL }";
CommandLineParser cmd(argc, argv, keys);
if(cmd.has("help"))
{
cout << "Usage : " << argv[0] << " [options]" << endl;
cout << "Available options:" << endl;
cmd.printMessage();
return EXIT_SUCCESS;
}
if (cmd.has("cpu_mode"))
{
ocl::setUseOpenCL(false);
cout << "OpenCL was disabled" << endl;
}
string inputName = samples::findFile(cmd.get<string>("i"));
string outfile = cmd.get<string>("o");
int iterations = 10;
namedWindow( wndname, WINDOW_AUTOSIZE );
vector<vector<Point> > squares;
UMat image;
imread(inputName, IMREAD_COLOR).copyTo(image);
if( image.empty() )
{
cout << "Couldn't load " << inputName << endl;
cmd.printMessage();
return EXIT_FAILURE;
}
int j = iterations;
int64 t_cpp = 0;
//warm-ups
cout << "warming up ..." << endl;
findSquares(image, squares);
do
{
int64 t_start = getTickCount();
findSquares(image, squares);
t_cpp += cv::getTickCount() - t_start;
t_start = getTickCount();
cout << "run loop: " << j << endl;
}
while(--j);
cout << "average time: " << 1000.0f * (double)t_cpp / getTickFrequency() / iterations << "ms" << endl;
UMat result = drawSquaresBoth(image, squares);
imshow(wndname, result);
imwrite(outfile, result);
waitKey(0);
return EXIT_SUCCESS;
}