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Open Source Computer Vision Library
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107 lines
3.2 KiB
107 lines
3.2 KiB
#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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