---------------------------------------------
// 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;
void help()
{
cout <<
"\nA program using pyramid scaling, Canny, contours, contour
simpification and\n"
"memory storage (it's got it all folks) to find\n"
"squares in a list of images pic1-6.png\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 = 11;
const char* wndname = "Square Detection Demo";
// helper function:
// finds a cosine of angle between vectors
// from pt0->pt1 and from pt0->pt2
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
void findSquares( const Mat& image, vector<vector<Point> >& squares )
{
squares.clear();
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());
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, 0, thresh, 5);
// dilate canny output to remove potential
// holes between edge segments
dilate(gray, gray, Mat(), Point(-1,-1));
imshow("Canny", gray);
}
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, CV_RETR_LIST,
CV_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 &&
fabs(contourArea(Mat(approx))) < 50000 &&
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
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();
polylines(image, &p, &n, 1, true, Scalar(0,255,0), 3, CV_AA);
}
imshow(wndname, image);
}
int main(int /*argc*/, char** /*argv*/)
{
/*
static const char* names[] = { "pic1.png", "pic2.png", "pic3.png",
"pic4.png", "pic5.png", "pic6.png", 0 };
*/
help();
namedWindow(wndname, CV_WINDOW_NORMAL);
namedWindow("Canny", CV_WINDOW_NORMAL);
//namedWindow("threshold", CV_WINDOW_NORMAL);
vector<vector<Point> > squares;
CvCapture* capture = cvCaptureFromCAM(0);
cvSetCaptureProperty(capture,CV_CAP_PROP_FRAME_WIDTH,320);
cvSetCaptureProperty(capture,CV_CAP_PROP_FRAME_HEIGHT,240);
//cvNamedWindow("test",CV_WINDOW_AUTOSIZE);
for(;;) {
Mat image = cvQueryFrame(capture);
findSquares(image, squares);
drawSquares(image, squares);
if((cvWaitKey(10) & 255)==27)break;
}
cvReleaseCapture(&capture);
cvDestroyWindow(wndname);
/*
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);
int c = waitKey();
if( (char)c == 27 )
break;
}
*/
return 0;
}
You're probably better to port the equivalent sample in C:
https://code.ros.org/trac/opencv/browser/trunk/opencv/samples/c/squares.c?rev=1429
The C API of OpenCV maps better to Java, so that's what I use in JavaCV
Samuel
thx again
Il 29/02/12 12:28, Samuel Audet ha scritto:
Samuel
// read 4 sequence elements at a time (all vertices of
a square)
for( i = 0; i < squares.total(); i += 4 )
{
CvPoint[] pt = new CvPoint[4];
CvPoint[] rect = pt;
int[] count=new int[4];
// read 4 vertices
CV_READ_SEQ_ELEM( pt[0], reader );
CV_READ_SEQ_ELEM( pt[1], reader );
CV_READ_SEQ_ELEM( pt[2], reader );
CV_READ_SEQ_ELEM( pt[3], reader );
// draw the square as a closed polyline
cvPolyLine(cpy, rect, count, 1, 1, CV_RGB(0,255,0),
3, CV_AA, 0);
}
// show the resultant image
cvShowImage( wndname, cpy );
cvReleaseImage( cpy );
}
i got this error:
Exception in thread "main" java.lang.NullPointerException: Pointer
address of parameter 0 is NULL.
Il 29/02/12 12:41, Samuel Audet ha scritto: