Open Source Computer Vision Library https://opencv.org/
You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
 
 
 
 
 
 

91 lines
3.1 KiB

/*
* Copyright (c) 2011. Philipp Wagner <bytefish[at]gmx[dot]de>.
* Released to public domain under terms of the BSD Simplified license.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions are met:
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
* * Neither the name of the organization nor the names of its contributors
* may be used to endorse or promote products derived from this software
* without specific prior written permission.
*
* See <http://www.opensource.org/licenses/bsd-license>
*/
#include "opencv2/opencv.hpp"
#include <iostream>
#include <fstream>
#include <sstream>
using namespace cv;
using namespace std;
void read_csv(const string& filename, vector<Mat>& images, vector<int>& labels, char separator = ';') {
std::ifstream file(filename.c_str(), ifstream::in);
if (!file)
throw std::exception();
string line, path, classlabel;
while (getline(file, line)) {
stringstream liness(line);
getline(liness, path, separator);
getline(liness, classlabel);
images.push_back(imread(path, 0));
labels.push_back(atoi(classlabel.c_str()));
}
}
int main(int argc, const char *argv[]) {
// check for command line arguments
if (argc != 2) {
cout << "usage: " << argv[0] << " <csv.ext>" << endl;
exit(1);
}
// path to your CSV
string fn_csv = string(argv[1]);
// images and corresponding labels
vector<Mat> images;
vector<int> labels;
// read in the data
try {
read_csv(fn_csv, images, labels);
} catch (exception& e) {
cerr << "Error opening file \"" << fn_csv << "\"." << endl;
exit(1);
}
// get width and height
//int width = images[0].cols;
int height = images[0].rows;
// get test instances
Mat testSample = images[images.size() - 1];
int testLabel = labels[labels.size() - 1];
// ... and delete last element
images.pop_back();
labels.pop_back();
// build the Fisherfaces model
Ptr<FaceRecognizer> model = createFisherFaceRecognizer();
model->train(images, labels);
// test model
int predicted = model->predict(testSample);
cout << "predicted class = " << predicted << endl;
cout << "actual class = " << testLabel << endl;
// get the eigenvectors
Mat W = model->eigenvectors();
// show first 10 fisherfaces
for (int i = 0; i < min(10, W.cols); i++) {
// get eigenvector #i
Mat ev = W.col(i).clone();
// reshape to original site
Mat grayscale, cgrayscale;
cvtColor(ev.reshape(1, height), grayscale, COLOR_BGR2GRAY);
// show image (with Jet colormap)
applyColorMap(grayscale, cgrayscale, COLORMAP_JET);
imshow(format("%d", i), cgrayscale);
}
waitKey(0);
return 0;
}