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