108 lines
3.2 KiB
C++
108 lines
3.2 KiB
C++
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#include "opencv2/objdetect.hpp"
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#include "opencv2/highgui.hpp"
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#include "opencv2/imgproc.hpp"
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#include "opencv2/videoio.hpp"
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#include <iostream>
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using namespace std;
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using namespace cv;
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/** Function Headers */
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void detectAndDisplay( Mat frame );
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/** Global variables */
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CascadeClassifier face_cascade;
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CascadeClassifier eyes_cascade;
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/** @function main */
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int main( int argc, const char** argv )
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{
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CommandLineParser parser(argc, argv,
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"{help h||}"
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"{face_cascade|data/haarcascades/haarcascade_frontalface_alt.xml|Path to face cascade.}"
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"{eyes_cascade|data/haarcascades/haarcascade_eye_tree_eyeglasses.xml|Path to eyes cascade.}"
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"{camera|0|Camera device number.}");
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parser.about( "\nThis program demonstrates using the cv::CascadeClassifier class to detect objects (Face + eyes) in a video stream.\n"
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"You can use Haar or LBP features.\n\n" );
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parser.printMessage();
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String face_cascade_name = samples::findFile( parser.get<String>("face_cascade") );
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String eyes_cascade_name = samples::findFile( parser.get<String>("eyes_cascade") );
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//-- 1. Load the cascades
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if( !face_cascade.load( face_cascade_name ) )
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{
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cout << "--(!)Error loading face cascade\n";
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return -1;
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};
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if( !eyes_cascade.load( eyes_cascade_name ) )
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{
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cout << "--(!)Error loading eyes cascade\n";
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return -1;
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};
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int camera_device = parser.get<int>("camera");
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VideoCapture capture;
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//-- 2. Read the video stream
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capture.open( camera_device );
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if ( ! capture.isOpened() )
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{
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cout << "--(!)Error opening video capture\n";
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return -1;
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}
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Mat frame;
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while ( capture.read(frame) )
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{
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if( frame.empty() )
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{
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cout << "--(!) No captured frame -- Break!\n";
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break;
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}
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//-- 3. Apply the classifier to the frame
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detectAndDisplay( frame );
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if( waitKey(10) == 27 )
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{
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break; // escape
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}
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}
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return 0;
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}
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/** @function detectAndDisplay */
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void detectAndDisplay( Mat frame )
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{
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Mat frame_gray;
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cvtColor( frame, frame_gray, COLOR_BGR2GRAY );
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equalizeHist( frame_gray, frame_gray );
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//-- Detect faces
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std::vector<Rect> faces;
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face_cascade.detectMultiScale( frame_gray, faces );
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for ( size_t i = 0; i < faces.size(); i++ )
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{
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Point center( faces[i].x + faces[i].width/2, faces[i].y + faces[i].height/2 );
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ellipse( frame, center, Size( faces[i].width/2, faces[i].height/2 ), 0, 0, 360, Scalar( 255, 0, 255 ), 4 );
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Mat faceROI = frame_gray( faces[i] );
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//-- In each face, detect eyes
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std::vector<Rect> eyes;
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eyes_cascade.detectMultiScale( faceROI, eyes );
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for ( size_t j = 0; j < eyes.size(); j++ )
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{
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Point eye_center( faces[i].x + eyes[j].x + eyes[j].width/2, faces[i].y + eyes[j].y + eyes[j].height/2 );
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int radius = cvRound( (eyes[j].width + eyes[j].height)*0.25 );
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circle( frame, eye_center, radius, Scalar( 255, 0, 0 ), 4 );
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}
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}
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//-- Show what you got
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imshow( "Capture - Face detection", frame );
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}
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