wrap cv.HOGDescriptor.detectMultiScale

Objdetect/classes.pl

@@ -1,5 +1,22 @@
 (
 ['CascadeClassifier',[],'@brief Cascade classifier class for object detection.',0,'cv::CascadeClassifier',[],''],
+['HOGDescriptor',[],'@brief Implementation of HOG (Histogram of Oriented Gradients) descriptor and object detector.
+
+the HOG descriptor algorithm introduced by Navneet Dalal and Bill Triggs @cite Dalal2005 .
+
+useful links:
+
+https://hal.inria.fr/inria-00548512/document/
+
+https://en.wikipedia.org/wiki/Histogram_of_oriented_gradients
+
+https://software.intel.com/en-us/ipp-dev-reference-histogram-of-oriented-gradients-hog-descriptor
+
+http://www.learnopencv.com/histogram-of-oriented-gradients
+
+http://www.learnopencv.com/handwritten-digits-classification-an-opencv-c-python-tutorial',0,'cv::HOGDescriptor',[],'@brief Creates the HOG descriptor and detector with default params.
+
+    aqual to HOGDescriptor(Size(64,128), Size(16,16), Size(8,8), Size(8,8), 9 )'],
 ['QRCodeDetector',[],'@brief Groups the object candidate rectangles.
     @param rectList  Input/output vector of rectangles. Output vector includes retained and grouped rectangles. (The Python list is not modified in place.)
     @param weights Input/output vector of weights of rectangles. Output vector includes weights of retained and grouped rectangles. (The Python list is not modified in place.)

Objdetect/funclist.pl

@@ -53,6 +53,19 @@
     @param filename Name of the file from which the classifier is loaded. The file may contain an old
     HAAR classifier trained by the haartraining application or a new cascade classifier trained by the
     traincascade application.',1,'bool',['String','filename','',['/C','/Ref']]],
+['HOGDescriptor','detectMultiScale','@brief Detects objects of different sizes in the input image. The detected objects are returned as a list
+    of rectangles.
+    @param img Matrix of the type CV_8U or CV_8UC3 containing an image where objects are detected.
+    @param foundLocations Vector of rectangles where each rectangle contains the detected object.
+    @param foundWeights Vector that will contain confidence values for each detected object.
+    @param hitThreshold Threshold for the distance between features and SVM classifying plane.
+    Usually it is 0 and should be specified in the detector coefficients (as the last free coefficient).
+    But if the free coefficient is omitted (which is allowed), you can specify it manually here.
+    @param winStride Window stride. It must be a multiple of block stride.
+    @param padding Padding
+    @param scale Coefficient of the detection window increase.
+    @param finalThreshold Final threshold
+    @param useMeanshiftGrouping indicates grouping algorithm',1,'void',['Mat','img','',[]],['vector_Rect','foundLocations','',['/O','/Ref']],['vector_double','foundWeights','',['/O','/Ref']],['double','hitThreshold','0',[]],['Size','winStride','Size()',[]],['Size','padding','Size()',[]],['double','scale','1.05',[]],['double','finalThreshold','2.0',[]],['bool','useMeanshiftGrouping','false',[]]],
 ['QRCodeDetector','detectAndDecodeMulti','@brief Both detects and decodes QR codes
     @param img grayscale or color (BGR) image containing QR codes.
     @param decoded_info UTF8-encoded output vector of string or empty vector of string if the codes cannot be decoded.

maint/genlists

@@ -84,13 +84,15 @@ my %force = map +($_=>1), qw(
   cv.groupRectangles
   cv.CascadeClassifier.load
   cv.CascadeClassifier.detectMultiScale
+  cv.HOGDescriptor.detectMultiScale
   cv.Tracker.init
   cv.Tracker.update
 );
 my %class = map +($_=>1), qw(
   LineSegmentDetector Tracker VideoCapture VideoWriter QRCodeDetector
   CascadeClassifier Subdiv2D TrackerKCF TrackerCSRT TrackerMIL
   FileNode FileStorage DMatch KeyPoint Algorithm CLAHE GeneralizedHough
+  HOGDescriptor
 );
 my $no_want = qr/^(TermCriteria|RNG|RotatedRect)/;
 
@@ -114,7 +116,7 @@ print "enum: $name\n";
         $pname =~ s#\.#::#g;
         push @{$dest2enums{$dest}}, $pname;
       }
-    } elsif ($name =~ /^class cv\.(.*)/) {
+    } elsif ($name =~ /^(?:class|struct) cv\.(.*)/) {
       my $cname = $1;
       next if !$class{$cname};
       $ret =~ s/^:\s*//;