support RotatedRect

Imgproc/funclist.pl

@@ -263,6 +263,47 @@
 @param offset Optional offset by which every contour point is shifted. This is useful if the
 contours are extracted from the image ROI and then they should be analyzed in the whole image
 context.',0,'void',['Mat','image','',[]],['vector_Mat','contours','',['/O']],['Mat','hierarchy','',['/O']],['int','mode','',[]],['int','method','',[]],['Point','offset','Point()',[]]],
+['','fitEllipseDirect','@brief Fits an ellipse around a set of 2D points.
+
+ The function calculates the ellipse that fits a set of 2D points.
+ It returns the rotated rectangle in which the ellipse is inscribed.
+ The Direct least square (Direct) method by @cite Fitzgibbon1999 is used.
+
+ For an ellipse, this basis set is \\f$ \\chi= \\left(x^2, x y, y^2, x, y, 1\\right) \\f$,
+ which is a set of six free coefficients \\f$ A^T=\\left\\{A_{\\text{xx}},A_{\\text{xy}},A_{\\text{yy}},A_x,A_y,A_0\\right\\} \\f$.
+ However, to specify an ellipse, all that is needed is five numbers; the major and minor axes lengths \\f$ (a,b) \\f$,
+ the position \\f$ (x_0,y_0) \\f$, and the orientation \\f$ \\theta \\f$. This is because the basis set includes lines,
+ quadratics, parabolic and hyperbolic functions as well as elliptical functions as possible fits.
+ The Direct method confines the fit to ellipses by ensuring that \\f$ 4 A_{xx} A_{yy}- A_{xy}^2 > 0 \\f$.
+ The condition imposed is that \\f$ 4 A_{xx} A_{yy}- A_{xy}^2=1 \\f$ which satisfies the inequality
+ and as the coefficients can be arbitrarily scaled is not overly restrictive.
+
+ \\f{equation*}{
+ \\epsilon ^2= A^T D^T D A \\quad \\text{with} \\quad A^T C A =1 \\quad \\text{and} \\quad C=\\left(\\begin{matrix}
+ 0 & 0  & 2  & 0  & 0  &  0  \\\\
+ 0 & -1  & 0  & 0  & 0  &  0 \\\\
+ 2 & 0  & 0  & 0  & 0  &  0 \\\\
+ 0 & 0  & 0  & 0  & 0  &  0 \\\\
+ 0 & 0  & 0  & 0  & 0  &  0 \\\\
+ 0 & 0  & 0  & 0  & 0  &  0
+ \\end{matrix} \\right)
+ \\f}
+
+ The minimum cost is found by solving the generalized eigenvalue problem.
+
+ \\f{equation*}{
+ D^T D A = \\lambda  \\left( C\\right) A
+ \\f}
+
+ The system produces only one positive eigenvalue \\f$ \\lambda\\f$ which is chosen as the solution
+ with its eigenvector \\f$\\mathbf{u}\\f$. These are used to find the coefficients
+
+ \\f{equation*}{
+ A = \\sqrt{\\frac{1}{\\mathbf{u}^T C \\mathbf{u}}}  \\mathbf{u}
+ \\f}
+ The scaling factor guarantees that  \\f$A^T C A =1\\f$.
+
+ @param points Input 2D point set, stored in std::vector\\<\\> or Mat',0,'RotatedRect',['Mat','points','',[]]],
 ['','rectangle','@brief Draws a simple, thick, or filled up-right rectangle.
 
 The function cv::rectangle draws a rectangle outline or a filled rectangle whose two opposite corners

classes.pl

@@ -1,4 +1,18 @@
 (
+['RotatedRect',[],'@brief The class represents rotated (i.e. not up-right) rectangles on a plane.
+
+Each rectangle is specified by the center point (mass center), length of each side (represented by
+#Size2f structure) and the rotation angle in degrees.
+
+The sample below demonstrates how to use RotatedRect:
+@snippet snippets/core_various.cpp RotatedRect_demo
+![image](pics/rotatedrect.png)
+
+@sa CamShift, fitEllipse, minAreaRect, CvBox2D',0,'cv::RotatedRect',[[[],''],[[['Point2f','center','',['/C','/Ref']],['Size2f','size','',['/C','/Ref']],['float','angle','',[]]],'full constructor
+    @param center The rectangle mass center.
+    @param size Width and height of the rectangle.
+    @param angle The rotation angle in a clockwise direction. When the angle is 0, 90, 180, 270 etc.,
+    the rectangle becomes an up-right rectangle.']]],
 ['KeyPoint',[],'@brief Data structure for salient point detectors.
 
 The class instance stores a keypoint, i.e. a point feature found by one of many available keypoint

funclist.pl

@@ -1,4 +1,6 @@
 (
+['RotatedRect','boundingRect','returns 4 vertices of the rectangle
+    @param pts The points array for storing rectangle vertices. The order is bottomLeft, topLeft, topRight, bottomRight.',1,'Rect'],
 ['KeyPoint','convert','This method converts vector of keypoints to vector of points or the reverse, where each keypoint is
     assigned the same size and the same orientation.
 

genpp.pl

@@ -50,6 +50,7 @@ package PP::OpenCV;
   Rect=>[map ['ptrdiff_t', $_], qw(x y width height)],
   Scalar=>[map ['double', "v$_", "val[$_]"], 0..3],
   Size=>[map ['ptrdiff_t', $_], qw(width height)],
+  Size2f=>[map ['float', $_], qw(width height)],
   Vec4f=>[map ['float', "v$_", "val[$_]"], 0..3],
   Vec6f=>[map ['float', "v$_", "val[$_]"], 0..5],
 );

maint/genlists

@@ -5,6 +5,9 @@ use warnings;
 use JSON::PP;
 use File::Basename;
 use File::Spec::Functions;
+use File::Temp qw(tempdir);
+use File::Path qw(make_path);
+use File::Basename qw(dirname);
 use Cwd;
 use IPC::Open2;
 use Data::Dumper;
@@ -21,12 +24,28 @@ EOF
 my @HEADERS_FILES = do { local @ARGV = $HEADERS; grep !/^\s*#/, <> };
 chomp @HEADERS_FILES;
 
+my $tdir = tempdir(CLEANUP=>1);
+sub process_header {
+  my ($dir, $file) = @_;
+  open my $fh, '<', catfile($dir, $file) or die "$file: $!";
+  my $outfile = catfile($tdir, $file);
+  my $outdir = dirname $outfile;
+  make_path $outdir or die "$outdir: $!" if !-d $outdir;
+  open my $outfh, '>', $outfile or die "$outfile: $!";
+  my $intext = do { local $/; <$fh> };
+  $intext =~ s/(class\s+)(CV_EXPORTS)(\s+RotatedRect)/$1${2}_W$3/;
+  $intext =~ s/^(\s*)(RotatedRect\((?:.*angle|\)))/${1}CV_WRAP $2/gm;
+  $intext =~ s/^(\s*)(.*?boundingRect\()/${1}CV_WRAP $2/m;
+  print $outfh $intext;
+  $outfile;
+}
+
 my $json_data;
 {
 my $old_dir = getcwd();
 chdir $CVDIR or die "chdir: $!";
 my $pid = open2(my $child_out, my $child_in, qw(python3 -c), $PYSCRIPT);
-print $child_in map catfile($HEADERS_DIR, $_)."\n", @HEADERS_FILES;
+print $child_in map process_header($HEADERS_DIR, $_)."\n", @HEADERS_FILES;
 close $child_in;
 $json_data = decode_json do { local $/; <$child_out> };
 chdir $old_dir or die "chdir: $!";
@@ -45,11 +64,13 @@ my %force = map +($_=>1), qw(
   cv.FileStorage.operator[]
   cv.KeyPoint.overlap
   cv.KeyPoint.convert
+  cv.RotatedRect.boundingRect
   cv.cvtColor
   cv.rectangle
   cv.ellipse2Poly
   cv.getAffineTransform
   cv.getGaborKernel
+  cv.fitEllipseDirect
   cv.drawContours
   cv.findContours
   cv.threshold
@@ -98,8 +119,9 @@ my %class = map +($_=>1), qw(
   CascadeClassifier Subdiv2D TrackerKCF TrackerCSRT TrackerMIL
   FileNode FileStorage DMatch KeyPoint Algorithm CLAHE GeneralizedHough
   HOGDescriptor SparsePyrLKOpticalFlow DISOpticalFlow SparseOpticalFlow
+  TermCriteria RNG RotatedRect
 );
-my $no_want = qr/^(TermCriteria|RNG|RotatedRect)/;
+my $no_want = qr/^(TermCriteria|RNG)/;
 my $skip_re = join '|',
   qr/^cv\.ipp/,
   qr/^cv\.moments/,

typemap

@@ -6,6 +6,7 @@ vector_KeyPointWrapper* T_OPENCV_VECTOR
 vector_MatWrapper* T_OPENCV_VECTOR
 vector_StringWrapper* T_OPENCV_VECTOR
 vector_vector_Point2fWrapper* T_OPENCV_VECTOR
+RotatedRectWrapper* T_PTROBJ_SPECIAL
 KeyPointWrapper* T_PTROBJ_SPECIAL
 DMatchWrapper* T_PTROBJ_SPECIAL
 FileStorageWrapper* T_PTROBJ_SPECIAL