add an "squares" sample for ocl module

samples/ocl/squares.cpp

+// 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 "opencv2/ocl/ocl.hpp"
+
+#include <iostream>
+#include <math.h>
+#include <string.h>
+
+using namespace cv;
+using namespace std;
+
+void help()
+{
+	cout <<
+	"\nA program using OCL module pyramid scaling, Canny, dilate functions; cpu 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 = "OpenCL 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;
+    cv::ocl::oclMat pyr_ocl, timg_ocl, gray0_ocl(gray0), gray_ocl;
+
+    // down-scale and upscale the image to filter out the noise
+    ocl::pyrDown(ocl::oclMat(image), pyr_ocl);
+    ocl::pyrUp(pyr_ocl, timg_ocl);
+    timg = Mat(timg_ocl);
+
+    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 )
+            {
+                // do canny on OpenCL device
+                // apply Canny. Take the upper threshold from slider
+                // and set the lower to 0 (which forces edges merging)
+                cv::ocl::Canny(gray0_ocl, gray_ocl, 0, thresh, 5);
+                // dilate canny output to remove potential
+                // holes between edge segments
+                ocl::dilate(gray0_ocl, gray_ocl, Mat(), Point(-1,-1));
+                gray = Mat(gray_ocl);
+            }
+            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 &&
+                    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*/)
+{
+
+    //ocl::setBinpath("F:/kernel_bin");
+    vector<ocl::Info> info;
+    CV_Assert(ocl::getDevice(info));
+
+    static const char* names[] = { "pic1.png", "pic2.png", "pic3.png",
+        "pic4.png", "pic5.png", "pic6.png", 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);
+
+        int c = waitKey();
+        if( (char)c == 27 )
+            break;
+    }
+
+    return 0;
+}