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/*
* 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 <iostream>
#include <cstdio>
#include <vector>
#include <algorithm>
using namespace std;
using namespace cv;
// Functions for facial feature detection
static void help(char** argv);
static void detectFaces(Mat&, vector<Rect_<int> >&, string);
static void detectEyes(Mat&, vector<Rect_<int> >&, string);
static void detectNose(Mat&, vector<Rect_<int> >&, string);
static void detectMouth(Mat&, vector<Rect_<int> >&, string);
static void detectFacialFeaures(Mat&, const vector<Rect_<int> >, 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<string>("@image");
face_cascade_path = parser.get<string>("@facexml");
eye_cascade_path = parser.has("eyes") ? parser.get<string>("eyes") : "";
nose_cascade_path = parser.has("nose") ? parser.get<string>("nose") : "";
mouth_cascade_path = parser.has("mouth") ? parser.get<string>("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<Rect_<int> > 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=<eyes_cascade> : Specify the haarcascade classifier for eye detection.\n"
"\t-nose=<nose_cascade> : Specify the haarcascade classifier for nose detection.\n"
"\t-mouth=<mouth-cascade> : 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/4.x/data/haarcascades";
cout << "\n\nThe classifiers for nose and mouth can be downloaded from : "
" \nhttps://github.com/opencv/opencv_contrib/tree/4.x/modules/face/data/cascades\n";
}
static void detectFaces(Mat& img, vector<Rect_<int> >& 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<Rect_<int> > 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<Rect_<int> > 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<Rect_<int> > 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<Rect_<int> > 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<Rect_<int> >& 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<Rect_<int> >& 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<Rect_<int> >& 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;
}
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