1Cascade Classifier {#tutorial_cascade_classifier}
2==================
3
4Goal
5----
6
7In this tutorial you will learn how to:
8
9-   Use the @ref cv::CascadeClassifier class to detect objects in a video stream. Particularly, we
10    will use the functions:
11    -   @ref cv::CascadeClassifier::load to load a .xml classifier file. It can be either a Haar or a LBP classifer
12    -   @ref cv::CascadeClassifier::detectMultiScale to perform the detection.
13
14Theory
15------
16
17Code
18----
19
20This tutorial code's is shown lines below. You can also download it from
21[here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/objectDetection/objectDetection.cpp)
22. The second version (using LBP for face detection) can be [found
23here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/objectDetection/objectDetection2.cpp)
24@code{.cpp}
25#include "opencv2/objdetect.hpp"
26#include "opencv2/highgui.hpp"
27#include "opencv2/imgproc.hpp"
28
29#include <iostream>
30#include <stdio.h>
31
32using namespace std;
33using namespace cv;
34
35/* Function Headers */
36void detectAndDisplay( Mat frame );
37
38/* Global variables */
39String face_cascade_name = "haarcascade_frontalface_alt.xml";
40String eyes_cascade_name = "haarcascade_eye_tree_eyeglasses.xml";
41CascadeClassifier face_cascade;
42CascadeClassifier eyes_cascade;
43String window_name = "Capture - Face detection";
44
45/* @function main */
46int main( void )
47{
48    VideoCapture capture;
49    Mat frame;
50
51    //-- 1. Load the cascades
52    if( !face_cascade.load( face_cascade_name ) ){ printf("--(!)Error loading face cascade\n"); return -1; };
53    if( !eyes_cascade.load( eyes_cascade_name ) ){ printf("--(!)Error loading eyes cascade\n"); return -1; };
54
55    //-- 2. Read the video stream
56    capture.open( -1 );
57    if ( ! capture.isOpened() ) { printf("--(!)Error opening video capture\n"); return -1; }
58
59    while (  capture.read(frame) )
60    {
61        if( frame.empty() )
62        {
63            printf(" --(!) No captured frame -- Break!");
64            break;
65        }
66
67        //-- 3. Apply the classifier to the frame
68        detectAndDisplay( frame );
69
70        int c = waitKey(10);
71        if( (char)c == 27 ) { break; } // escape
72    }
73    return 0;
74}
75
76/* @function detectAndDisplay */
77void detectAndDisplay( Mat frame )
78{
79    std::vector<Rect> faces;
80    Mat frame_gray;
81
82    cvtColor( frame, frame_gray, COLOR_BGR2GRAY );
83    equalizeHist( frame_gray, frame_gray );
84
85    //-- Detect faces
86    face_cascade.detectMultiScale( frame_gray, faces, 1.1, 2, 0|CASCADE_SCALE_IMAGE, Size(30, 30) );
87
88    for( size_t i = 0; i < faces.size(); i++ )
89    {
90        Point center( faces[i].x + faces[i].width/2, faces[i].y + faces[i].height/2 );
91        ellipse( frame, center, Size( faces[i].width/2, faces[i].height/2), 0, 0, 360, Scalar( 255, 0, 255 ), 4, 8, 0 );
92
93        Mat faceROI = frame_gray( faces[i] );
94        std::vector<Rect> eyes;
95
96        //-- In each face, detect eyes
97        eyes_cascade.detectMultiScale( faceROI, eyes, 1.1, 2, 0 |CASCADE_SCALE_IMAGE, Size(30, 30) );
98
99        for( size_t j = 0; j < eyes.size(); j++ )
100        {
101            Point eye_center( faces[i].x + eyes[j].x + eyes[j].width/2, faces[i].y + eyes[j].y + eyes[j].height/2 );
102            int radius = cvRound( (eyes[j].width + eyes[j].height)*0.25 );
103            circle( frame, eye_center, radius, Scalar( 255, 0, 0 ), 4, 8, 0 );
104        }
105    }
106    //-- Show what you got
107    imshow( window_name, frame );
108}
109@endcode
110Explanation
111-----------
112
113Result
114------
115
116-#  Here is the result of running the code above and using as input the video stream of a build-in
117    webcam:
118
119    ![](images/Cascade_Classifier_Tutorial_Result_Haar.jpg)
120
121    Remember to copy the files *haarcascade_frontalface_alt.xml* and
122    *haarcascade_eye_tree_eyeglasses.xml* in your current directory. They are located in
123    *opencv/data/haarcascades*
124
125-#  This is the result of using the file *lbpcascade_frontalface.xml* (LBP trained) for the face
126    detection. For the eyes we keep using the file used in the tutorial.
127
128    ![](images/Cascade_Classifier_Tutorial_Result_LBP.jpg)
129