101 lines
3.6 KiB
C++
101 lines
3.6 KiB
C++
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#include "opencv2/face.hpp"
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#include "opencv2/videoio.hpp"
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#include "opencv2/highgui.hpp"
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#include "opencv2/imgcodecs.hpp"
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#include "opencv2/objdetect.hpp"
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#include "opencv2/imgproc.hpp"
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#include <iostream>
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#include <vector>
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#include <string>
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using namespace std;
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using namespace cv;
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using namespace cv::face;
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static bool myDetector(InputArray image, OutputArray faces, CascadeClassifier *face_cascade)
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{
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Mat gray;
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if (image.channels() > 1)
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cvtColor(image, gray, COLOR_BGR2GRAY);
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else
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gray = image.getMat().clone();
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equalizeHist(gray, gray);
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std::vector<Rect> faces_;
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face_cascade->detectMultiScale(gray, faces_, 1.4, 2, CASCADE_SCALE_IMAGE, Size(30, 30));
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Mat(faces_).copyTo(faces);
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return true;
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}
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int main(int argc,char** argv){
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//Give the path to the directory containing all the files containing data
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CommandLineParser parser(argc, argv,
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"{ help h usage ? | | give the following arguments in following format }"
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"{ model_filename f | | (required) path to binary file storing the trained model which is to be loaded [example - /data/file.dat]}"
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"{ image i | | (required) path to image in which face landmarks have to be detected.[example - /data/image.jpg] }"
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"{ face_cascade c | | Path to the face cascade xml file which you want to use as a detector}"
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);
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// Read in the input arguments
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if (parser.has("help")){
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parser.printMessage();
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cerr << "TIP: Use absolute paths to avoid any problems with the software!" << endl;
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return 0;
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}
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string filename(parser.get<string>("model_filename"));
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if (filename.empty()){
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parser.printMessage();
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cerr << "The name of the model file to be loaded for detecting landmarks is not found" << endl;
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return -1;
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}
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string image(parser.get<string>("image"));
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if (image.empty()){
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parser.printMessage();
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cerr << "The name of the image file in which landmarks have to be detected is not found" << endl;
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return -1;
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}
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string cascade_name(parser.get<string>("face_cascade"));
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if (cascade_name.empty()){
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parser.printMessage();
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cerr << "The name of the cascade classifier to be loaded to detect faces is not found" << endl;
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return -1;
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}
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Mat img = imread(image);
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//pass the face cascade xml file which you want to pass as a detector
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CascadeClassifier face_cascade;
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face_cascade.load(cascade_name);
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FacemarkKazemi::Params params;
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Ptr<FacemarkKazemi> facemark = FacemarkKazemi::create(params);
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facemark->setFaceDetector((FN_FaceDetector)myDetector, &face_cascade);
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facemark->loadModel(filename);
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cout<<"Loaded model"<<endl;
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vector<Rect> faces;
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resize(img,img,Size(460,460), 0, 0, INTER_LINEAR_EXACT);
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facemark->getFaces(img,faces);
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vector< vector<Point2f> > shapes;
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// Check if faces detected or not
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// Helps in proper exception handling when writing images to the directories.
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if(faces.size() != 0) {
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if(facemark->fit(img,faces,shapes))
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{
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for( size_t i = 0; i < faces.size(); i++ )
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{
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cv::rectangle(img,faces[i],Scalar( 255, 0, 0 ));
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}
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for(unsigned long i=0;i<faces.size();i++){
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for(unsigned long k=0;k<shapes[i].size();k++)
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cv::circle(img,shapes[i][k],5,cv::Scalar(0,0,255),FILLED);
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}
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namedWindow("Detected_shape");
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imshow("Detected_shape",img);
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waitKey(0);
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}
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} else {
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cout << "Faces not detected." << endl;
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}
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return 0;
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}
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