/* * Copyright (c) 2011. Philipp Wagner . * 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 */ #include "opencv2/opencv.hpp" #include #include #include using namespace cv; using namespace std; void read_csv(const string& filename, vector& images, vector& 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] << " " << endl; exit(1); } // path to your CSV string fn_csv = string(argv[1]); // images and corresponding labels vector images; vector labels; // read in the data try { read_csv(fn_csv, images, labels); } catch (exception&) { 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 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; }