FisherFace detect me even if my image is note in database
System information (version) - OpenCV => 2.4.9.1 - Operating System / Platform => Linux Ubuntu 64 Bit - Compiler => CMake 3.5.1
Detailed description
I use imgshow to prompt the webcam capture and add a rectangle and the subject found with FisherFace algorithm AT&T orl_face photo base. The problem is FisherFace algorithm detect me even if I am not in the database, it confuses me with 2 subjects... I changed the minNeighbours parameter but it doesn't change anything.
Thanks to the FaceRecognizer() Thresholds documentation, I updated the code :
// Create a FaceRecognizer and train it on the given images:
Ptr<FaceRecognizer> model = createFisherFaceRecognizer(10,0.0);
model->train(images, labels);
// The following line reads the threshold from the Eigenfaces model:
double current_threshold = model->getDouble("threshold");
// And this line sets the threshold to 0.0:
model->set("threshold", 0.0);
.
.
.
haar_cascade.detectMultiScale(gray, faces, 1.1, 5,0, cvSize(30,30), cvSize(30,30));
.
.
.
Mat face_resized;
cv::resize(face, face_resized, Size(im_width, im_height), 1.0, 1.0, INTER_CUBIC);
// Now perform the prediction, see how easy that is:
int prediction = model->predict(face_resized);
// And finally write all we've found out to the original image!
// First of all draw a green rectangle around the detected face:
cout << prediction << endl;
(See full code just below)
Steps to reproduce
#include "opencv2/core/core.hpp"
#include "opencv2/contrib/contrib.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/objdetect/objdetect.hpp"
#include <iostream>
#include <fstream>
#include <sstream>
using namespace cv;
using namespace std;
static void read_csv(const string& filename, vector<Mat>& images, vector<int>& labels, char separator = ';') {
std::ifstream file(filename.c_str(), ifstream::in);
if (!file) {
string error_message = "No valid input file was given, please check the given filename.";
CV_Error(CV_StsBadArg, error_message);
}
string line, path, classlabel;
while (getline(file, line)) {
stringstream liness(line);
getline(liness, path, separator);
getline(liness, classlabel);
if(!path.empty() && !classlabel.empty()) {
Mat m = imread(path, 1);
if (m.empty())
{
cerr << path << " could not be read." << endl;
continue;
}
Mat m2;
cvtColor(m,m2,CV_BGR2GRAY);
images.push_back(m2);
labels.push_back(atoi(classlabel.c_str()));
}
}
cout << endl << "Read finish";
}
int main(int argc, const char *argv[]) {
if (argc != 4) {
cout << "usage: " << argv[0] << " </path/to/haar_cascade> </path/to/csv.ext> </path/to/device id>" << endl;
cout << "\t </path/to/haar_cascade> -- Path to the Haar Cascade for face detection." << endl;
cout << "\t </path/to/csv.ext> -- Path to the CSV file with the face database." << endl;
cout << "\t <device id> -- The webcam device id to grab frames from." << endl;
exit(1);
}
string fn_haar = string(argv[1]);
string fn_csv = string(argv[2]);
int deviceId = atoi(argv[3]);
vector<Mat> images;
vector<int> labels;
try {
read_csv(fn_csv, images, labels);
} catch (cv::Exception& e) {
cerr << "Error opening file \"" << fn_csv << "\". Reason: " << e.msg << endl;
// nothing more we can do
exit(1);
}
int im_width = images[0].cols;
int im_height = images[0].rows;
Ptr<FaceRecognizer> model = createFisherFaceRecognizer(10,0.0);
model->train(images, labels);
double current_threshold = model->getDouble("threshold");
model->set("threshold", 0.0);
CascadeClassifier haar_cascade;
haar_cascade.load(fn_haar ...