Added sample for object detection with LBP in tutorial_code

samples/cpp/tutorial_code/objectDetection/objectDetection.cpp

@@ -69,9 +69,9 @@ void detectAndDisplay( Mat frame )
 
    cvtColor( frame, frame_gray, CV_BGR2GRAY );
    equalizeHist( frame_gray, frame_gray );
+   //-- Detect faces
    face_cascade.detectMultiScale( frame_gray, faces, 1.1, 2, 0|CV_HAAR_SCALE_IMAGE, Size(30, 30) );
 
-   //-- Detect faces
    for( int i = 0; i < faces.size(); i++ )
     {
       Point center( faces[i].x + faces[i].width*0.5, faces[i].y + faces[i].height*0.5 );
@@ -79,9 +79,10 @@ void detectAndDisplay( Mat frame )
 
       Mat faceROI = frame_gray( faces[i] );
       std::vector<Rect> eyes;
-      eyes_cascade.detectMultiScale( faceROI, eyes, 1.1, 2, 0 |CV_HAAR_SCALE_IMAGE, Size(30, 30) );
 
       //-- In each face, detect eyes
+      eyes_cascade.detectMultiScale( faceROI, eyes, 1.1, 2, 0 |CV_HAAR_SCALE_IMAGE, Size(30, 30) );
+
       for( int j = 0; j < eyes.size(); j++ )
        {
          Point center( faces[i].x + eyes[j].x + eyes[j].width*0.5, faces[i].y + eyes[j].y + eyes[j].height*0.5 ); 

samples/cpp/tutorial_code/objectDetection/objectDetection2.cpp

+/**
+ * @file objectDetection2.cpp
+ * @author A. Huaman ( based in the classic facedetect.cpp in samples/c )
+ * @brief A simplified version of facedetect.cpp, show how to load a cascade classifier and how to find objects (Face + eyes) in a video stream - Using LBP here
+ */
+#include "opencv2/objdetect/objdetect.hpp"
+#include "opencv2/highgui/highgui.hpp"
+#include "opencv2/imgproc/imgproc.hpp"
+
+#include <iostream>
+#include <stdio.h>
+
+using namespace std;
+using namespace cv;
+
+/** Function Headers */
+void detectAndDisplay( Mat frame );
+
+/** Global variables */
+String face_cascade_name = "lbpcascade_frontalface.xml";
+CascadeClassifier face_cascade;
+string window_name = "Capture - Face detection";
+RNG rng(12345);
+
+/**
+ * @function main
+ */
+int main( int argc, const char** argv )
+{
+  CvCapture* capture;
+  Mat frame;
+
+  //-- 1. Load the cascade
+  if( !face_cascade.load( face_cascade_name ) ){ printf("--(!)Error loading\n"); return -1; };
+
+  //-- 2. Read the video stream
+  capture = cvCaptureFromCAM( -1 );
+  if( capture )
+  {
+    while( true )
+    {
+      frame = cvQueryFrame( capture );
+  
+      //-- 3. Apply the classifier to the frame
+      if( !frame.empty() )
+       { detectAndDisplay( frame ); }
+      else
+       { printf(" --(!) No captured frame -- Break!"); break; }
+      
+      int c = waitKey(10);
+      if( (char)c == 'c' ) { break; } 
+
+    }
+  }
+  return 0;
+}
+
+/**
+ * @function detectAndDisplay
+ */
+void detectAndDisplay( Mat frame )
+{
+   std::vector<Rect> faces;
+   Mat frame_gray;
+
+   cvtColor( frame, frame_gray, CV_BGR2GRAY );
+   equalizeHist( frame_gray, frame_gray );
+   //-- Detect faces
+   face_cascade.detectMultiScale( frame_gray, faces, 1.1, 2, 0, Size(80, 80) );
+
+   for( int i = 0; i < faces.size(); i++ )
+    {
+      Point center( faces[i].x + faces[i].width*0.5, faces[i].y + faces[i].height*0.5 );
+      ellipse( frame, center, Size( faces[i].width*0.5, faces[i].height*0.5), 0, 0, 360, Scalar( 255, 0, 0 ), 2, 8, 0 );
+    } 
+   //-- Show what you got
+   imshow( window_name, frame );
+}