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212 lines
7.7 KiB
C++
212 lines
7.7 KiB
C++
/*
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* Author: Samyak Datta (datta[dot]samyak[at]gmail.com)
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*
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* A program to detect facial feature points using
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* Haarcascade classifiers for face, eyes, nose and mouth
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*
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*/
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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 <iostream>
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#include <cstdio>
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#include <vector>
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#include <algorithm>
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using namespace std;
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using namespace cv;
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// Functions for facial feature detection
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static void help();
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static void detectFaces(Mat&, vector<Rect_<int> >&, string);
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static void detectEyes(Mat&, vector<Rect_<int> >&, string);
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static void detectNose(Mat&, vector<Rect_<int> >&, string);
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static void detectMouth(Mat&, vector<Rect_<int> >&, string);
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static void detectFacialFeaures(Mat&, const vector<Rect_<int> >, string, string, string);
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string input_image_path;
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string face_cascade_path, eye_cascade_path, nose_cascade_path, mouth_cascade_path;
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int main(int argc, char** argv)
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{
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cv::CommandLineParser parser(argc, argv,
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"{eyes||}{nose||}{mouth||}{help h||}");
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if (parser.has("help"))
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{
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help();
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return 0;
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}
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input_image_path = parser.get<string>(0);
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face_cascade_path = parser.get<string>(1);
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eye_cascade_path = parser.has("eyes") ? parser.get<string>("eyes") : "";
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nose_cascade_path = parser.has("nose") ? parser.get<string>("nose") : "";
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mouth_cascade_path = parser.has("mouth") ? parser.get<string>("mouth") : "";
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if (input_image_path.empty() || face_cascade_path.empty())
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{
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cout << "IMAGE or FACE_CASCADE are not specified";
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return 1;
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}
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// Load image and cascade classifier files
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Mat image;
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image = imread(input_image_path);
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// Detect faces and facial features
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vector<Rect_<int> > faces;
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detectFaces(image, faces, face_cascade_path);
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detectFacialFeaures(image, faces, eye_cascade_path, nose_cascade_path, mouth_cascade_path);
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imshow("Result", image);
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waitKey(0);
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return 0;
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}
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static void help()
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{
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cout << "\nThis file demonstrates facial feature points detection using Haarcascade classifiers.\n"
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"The program detects a face and eyes, nose and mouth inside the face."
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"The code has been tested on the Japanese Female Facial Expression (JAFFE) database and found"
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"to give reasonably accurate results. \n";
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cout << "\nUSAGE: ./cpp-example-facial_features [IMAGE] [FACE_CASCADE] [OPTIONS]\n"
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"IMAGE\n\tPath to the image of a face taken as input.\n"
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"FACE_CASCSDE\n\t Path to a haarcascade classifier for face detection.\n"
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"OPTIONS: \nThere are 3 options available which are described in detail. There must be a "
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"space between the option and it's argument (All three options accept arguments).\n"
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"\t-eyes=<eyes_cascade> : Specify the haarcascade classifier for eye detection.\n"
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"\t-nose=<nose_cascade> : Specify the haarcascade classifier for nose detection.\n"
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"\t-mouth=<mouth-cascade> : Specify the haarcascade classifier for mouth detection.\n";
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cout << "EXAMPLE:\n"
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"(1) ./cpp-example-facial_features image.jpg face.xml -eyes=eyes.xml -mouth=mouth.xml\n"
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"\tThis will detect the face, eyes and mouth in image.jpg.\n"
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"(2) ./cpp-example-facial_features image.jpg face.xml -nose=nose.xml\n"
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"\tThis will detect the face and nose in image.jpg.\n"
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"(3) ./cpp-example-facial_features image.jpg face.xml\n"
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"\tThis will detect only the face in image.jpg.\n";
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cout << " \n\nThe classifiers for face and eyes can be downloaded from : "
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" \nhttps://github.com/opencv/opencv/tree/master/data/haarcascades";
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cout << "\n\nThe classifiers for nose and mouth can be downloaded from : "
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" \nhttps://github.com/opencv/opencv_contrib/tree/master/modules/face/data/cascades\n";
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}
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static void detectFaces(Mat& img, vector<Rect_<int> >& faces, string cascade_path)
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{
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CascadeClassifier face_cascade;
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face_cascade.load(cascade_path);
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face_cascade.detectMultiScale(img, faces, 1.15, 3, 0|CASCADE_SCALE_IMAGE, Size(30, 30));
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return;
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}
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static void detectFacialFeaures(Mat& img, const vector<Rect_<int> > faces, string eye_cascade,
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string nose_cascade, string mouth_cascade)
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{
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for(unsigned int i = 0; i < faces.size(); ++i)
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{
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// Mark the bounding box enclosing the face
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Rect face = faces[i];
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rectangle(img, Point(face.x, face.y), Point(face.x+face.width, face.y+face.height),
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Scalar(255, 0, 0), 1, 4);
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// Eyes, nose and mouth will be detected inside the face (region of interest)
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Mat ROI = img(Rect(face.x, face.y, face.width, face.height));
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// Check if all features (eyes, nose and mouth) are being detected
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bool is_full_detection = false;
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if( (!eye_cascade.empty()) && (!nose_cascade.empty()) && (!mouth_cascade.empty()) )
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is_full_detection = true;
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// Detect eyes if classifier provided by the user
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if(!eye_cascade.empty())
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{
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vector<Rect_<int> > eyes;
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detectEyes(ROI, eyes, eye_cascade);
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// Mark points corresponding to the centre of the eyes
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for(unsigned int j = 0; j < eyes.size(); ++j)
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{
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Rect e = eyes[j];
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circle(ROI, Point(e.x+e.width/2, e.y+e.height/2), 3, Scalar(0, 255, 0), -1, 8);
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/* rectangle(ROI, Point(e.x, e.y), Point(e.x+e.width, e.y+e.height),
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Scalar(0, 255, 0), 1, 4); */
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}
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}
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// Detect nose if classifier provided by the user
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double nose_center_height = 0.0;
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if(!nose_cascade.empty())
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{
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vector<Rect_<int> > nose;
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detectNose(ROI, nose, nose_cascade);
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// Mark points corresponding to the centre (tip) of the nose
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for(unsigned int j = 0; j < nose.size(); ++j)
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{
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Rect n = nose[j];
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circle(ROI, Point(n.x+n.width/2, n.y+n.height/2), 3, Scalar(0, 255, 0), -1, 8);
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nose_center_height = (n.y + n.height/2);
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}
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}
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// Detect mouth if classifier provided by the user
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double mouth_center_height = 0.0;
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if(!mouth_cascade.empty())
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{
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vector<Rect_<int> > mouth;
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detectMouth(ROI, mouth, mouth_cascade);
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for(unsigned int j = 0; j < mouth.size(); ++j)
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{
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Rect m = mouth[j];
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mouth_center_height = (m.y + m.height/2);
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// The mouth should lie below the nose
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if( (is_full_detection) && (mouth_center_height > nose_center_height) )
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{
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rectangle(ROI, Point(m.x, m.y), Point(m.x+m.width, m.y+m.height), Scalar(0, 255, 0), 1, 4);
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}
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else if( (is_full_detection) && (mouth_center_height <= nose_center_height) )
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continue;
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else
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rectangle(ROI, Point(m.x, m.y), Point(m.x+m.width, m.y+m.height), Scalar(0, 255, 0), 1, 4);
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}
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}
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}
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return;
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}
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static void detectEyes(Mat& img, vector<Rect_<int> >& eyes, string cascade_path)
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{
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CascadeClassifier eyes_cascade;
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eyes_cascade.load(cascade_path);
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eyes_cascade.detectMultiScale(img, eyes, 1.20, 5, 0|CASCADE_SCALE_IMAGE, Size(30, 30));
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return;
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}
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static void detectNose(Mat& img, vector<Rect_<int> >& nose, string cascade_path)
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{
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CascadeClassifier nose_cascade;
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nose_cascade.load(cascade_path);
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nose_cascade.detectMultiScale(img, nose, 1.20, 5, 0|CASCADE_SCALE_IMAGE, Size(30, 30));
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return;
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}
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static void detectMouth(Mat& img, vector<Rect_<int> >& mouth, string cascade_path)
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{
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CascadeClassifier mouth_cascade;
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mouth_cascade.load(cascade_path);
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mouth_cascade.detectMultiScale(img, mouth, 1.20, 5, 0|CASCADE_SCALE_IMAGE, Size(30, 30));
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return;
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}
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