/* * Author: Samyak Datta (datta[dot]samyak[at]gmail.com) * * A program to detect facial feature points using * Haarcascade classifiers for face, eyes, nose and mouth * */ #include "opencv2/objdetect.hpp" #include "opencv2/highgui.hpp" #include "opencv2/imgproc.hpp" #include #include #include #include using namespace std; using namespace cv; // Functions for facial feature detection static void help(char** argv); static void detectFaces(Mat&, vector >&, string); static void detectEyes(Mat&, vector >&, string); static void detectNose(Mat&, vector >&, string); static void detectMouth(Mat&, vector >&, string); static void detectFacialFeaures(Mat&, const vector >, string, string, string); string input_image_path; string face_cascade_path, eye_cascade_path, nose_cascade_path, mouth_cascade_path; int main(int argc, char** argv) { cv::CommandLineParser parser(argc, argv, "{eyes||}{nose||}{mouth||}{help h||}{@image||}{@facexml||}"); if (parser.has("help")) { help(argv); return 0; } input_image_path = parser.get("@image"); face_cascade_path = parser.get("@facexml"); eye_cascade_path = parser.has("eyes") ? parser.get("eyes") : ""; nose_cascade_path = parser.has("nose") ? parser.get("nose") : ""; mouth_cascade_path = parser.has("mouth") ? parser.get("mouth") : ""; if (input_image_path.empty() || face_cascade_path.empty()) { cout << "IMAGE or FACE_CASCADE are not specified"; return 1; } // Load image and cascade classifier files Mat image; image = imread(samples::findFile(input_image_path)); // Detect faces and facial features vector > faces; detectFaces(image, faces, face_cascade_path); detectFacialFeaures(image, faces, eye_cascade_path, nose_cascade_path, mouth_cascade_path); imshow("Result", image); waitKey(0); return 0; } static void help(char** argv) { cout << "\nThis file demonstrates facial feature points detection using Haarcascade classifiers.\n" "The program detects a face and eyes, nose and mouth inside the face." "The code has been tested on the Japanese Female Facial Expression (JAFFE) database and found" "to give reasonably accurate results. \n"; cout << "\nUSAGE: " << argv[0] << " [IMAGE] [FACE_CASCADE] [OPTIONS]\n" "IMAGE\n\tPath to the image of a face taken as input.\n" "FACE_CASCSDE\n\t Path to a haarcascade classifier for face detection.\n" "OPTIONS: \nThere are 3 options available which are described in detail. There must be a " "space between the option and it's argument (All three options accept arguments).\n" "\t-eyes= : Specify the haarcascade classifier for eye detection.\n" "\t-nose= : Specify the haarcascade classifier for nose detection.\n" "\t-mouth= : Specify the haarcascade classifier for mouth detection.\n"; cout << "EXAMPLE:\n" "(1) " << argv[0] << " image.jpg face.xml -eyes=eyes.xml -mouth=mouth.xml\n" "\tThis will detect the face, eyes and mouth in image.jpg.\n" "(2) " << argv[0] << " image.jpg face.xml -nose=nose.xml\n" "\tThis will detect the face and nose in image.jpg.\n" "(3) " << argv[0] << " image.jpg face.xml\n" "\tThis will detect only the face in image.jpg.\n"; cout << " \n\nThe classifiers for face and eyes can be downloaded from : " " \nhttps://github.com/opencv/opencv/tree/master/data/haarcascades"; cout << "\n\nThe classifiers for nose and mouth can be downloaded from : " " \nhttps://github.com/opencv/opencv_contrib/tree/master/modules/face/data/cascades\n"; } static void detectFaces(Mat& img, vector >& faces, string cascade_path) { CascadeClassifier face_cascade; face_cascade.load(samples::findFile(cascade_path)); if (!face_cascade.empty()) face_cascade.detectMultiScale(img, faces, 1.15, 3, 0|CASCADE_SCALE_IMAGE, Size(30, 30)); return; } static void detectFacialFeaures(Mat& img, const vector > faces, string eye_cascade, string nose_cascade, string mouth_cascade) { for(unsigned int i = 0; i < faces.size(); ++i) { // Mark the bounding box enclosing the face Rect face = faces[i]; rectangle(img, Point(face.x, face.y), Point(face.x+face.width, face.y+face.height), Scalar(255, 0, 0), 1, 4); // Eyes, nose and mouth will be detected inside the face (region of interest) Mat ROI = img(Rect(face.x, face.y, face.width, face.height)); // Check if all features (eyes, nose and mouth) are being detected bool is_full_detection = false; if( (!eye_cascade.empty()) && (!nose_cascade.empty()) && (!mouth_cascade.empty()) ) is_full_detection = true; // Detect eyes if classifier provided by the user if(!eye_cascade.empty()) { vector > eyes; detectEyes(ROI, eyes, eye_cascade); // Mark points corresponding to the centre of the eyes for(unsigned int j = 0; j < eyes.size(); ++j) { Rect e = eyes[j]; circle(ROI, Point(e.x+e.width/2, e.y+e.height/2), 3, Scalar(0, 255, 0), -1, 8); /* rectangle(ROI, Point(e.x, e.y), Point(e.x+e.width, e.y+e.height), Scalar(0, 255, 0), 1, 4); */ } } // Detect nose if classifier provided by the user double nose_center_height = 0.0; if(!nose_cascade.empty()) { vector > nose; detectNose(ROI, nose, nose_cascade); // Mark points corresponding to the centre (tip) of the nose for(unsigned int j = 0; j < nose.size(); ++j) { Rect n = nose[j]; circle(ROI, Point(n.x+n.width/2, n.y+n.height/2), 3, Scalar(0, 255, 0), -1, 8); nose_center_height = (n.y + n.height/2); } } // Detect mouth if classifier provided by the user double mouth_center_height = 0.0; if(!mouth_cascade.empty()) { vector > mouth; detectMouth(ROI, mouth, mouth_cascade); for(unsigned int j = 0; j < mouth.size(); ++j) { Rect m = mouth[j]; mouth_center_height = (m.y + m.height/2); // The mouth should lie below the nose if( (is_full_detection) && (mouth_center_height > nose_center_height) ) { rectangle(ROI, Point(m.x, m.y), Point(m.x+m.width, m.y+m.height), Scalar(0, 255, 0), 1, 4); } else if( (is_full_detection) && (mouth_center_height <= nose_center_height) ) continue; else rectangle(ROI, Point(m.x, m.y), Point(m.x+m.width, m.y+m.height), Scalar(0, 255, 0), 1, 4); } } } return; } static void detectEyes(Mat& img, vector >& eyes, string cascade_path) { CascadeClassifier eyes_cascade; eyes_cascade.load(samples::findFile(cascade_path, !cascade_path.empty())); if (!eyes_cascade.empty()) eyes_cascade.detectMultiScale(img, eyes, 1.20, 5, 0|CASCADE_SCALE_IMAGE, Size(30, 30)); return; } static void detectNose(Mat& img, vector >& nose, string cascade_path) { CascadeClassifier nose_cascade; nose_cascade.load(samples::findFile(cascade_path, !cascade_path.empty())); if (!nose_cascade.empty()) nose_cascade.detectMultiScale(img, nose, 1.20, 5, 0|CASCADE_SCALE_IMAGE, Size(30, 30)); return; } static void detectMouth(Mat& img, vector >& mouth, string cascade_path) { CascadeClassifier mouth_cascade; mouth_cascade.load(samples::findFile(cascade_path, !cascade_path.empty())); if (!mouth_cascade.empty()) mouth_cascade.detectMultiScale(img, mouth, 1.20, 5, 0|CASCADE_SCALE_IMAGE, Size(30, 30)); return; }