/*M/////////////////////////////////////////////////////////////////////////////////////// // // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. // // By downloading, copying, installing or using the software you agree to this license. // If you do not agree to this license, do not download, install, // copy or use the software. // // // License Agreement // For Open Source Computer Vision Library // // Copyright (C) 2000-2008, Intel Corporation, all rights reserved. // Copyright (C) 2008-2012, Willow Garage Inc., all rights reserved. // Third party copyrights are property of their respective owners. // // Redistribution and use in source and binary forms, with or without modification, // are permitted provided that the following conditions are met: // // * Redistribution's of source code must retain the above copyright notice, // this list of conditions and the following disclaimer. // // * Redistribution's 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. // // * The name of the copyright holders may not be used to endorse or promote products // derived from this software without specific prior written permission. // // This software is provided by the copyright holders and contributors "as is" and // any express or implied warranties, including, but not limited to, the implied // warranties of merchantability and fitness for a particular purpose are disclaimed. // In no event shall the Intel Corporation or contributors be liable for any direct, // indirect, incidental, special, exemplary, or consequential damages // (including, but not limited to, procurement of substitute goods or services; // loss of use, data, or profits; or business interruption) however caused // and on any theory of liability, whether in contract, strict liability, // or tort (including negligence or otherwise) arising in any way out of // the use of this software, even if advised of the possibility of such damage. // //M*/ #include #include #if defined VISUALIZE_GENERATION # include # define show(a, b) \ do { \ cv::imshow(a,b); \ cv::waitkey(0); \ } while(0) #else # define show(a, b) #endif // ============ Octave ============ // sft::Octave::Octave(){} sft::Octave::~Octave(){} bool sft::Octave::train( const cv::Mat& trainData, const cv::Mat& responses, const cv::Mat& varIdx, const cv::Mat& sampleIdx, const cv::Mat& varType, const cv::Mat& missingDataMask) { bool update = false; return cv::Boost::train(trainData, CV_COL_SAMPLE, responses, varIdx, sampleIdx, varType, missingDataMask, params, update); } // ========= FeaturePool ========= // sft::FeaturePool::FeaturePool(cv::Size m, int n) : model(m), nfeatures(n) { CV_Assert(m != cv::Size() && n > 0); fill(nfeatures); } sft::FeaturePool::~FeaturePool(){} void sft::FeaturePool::fill(int desired) { int mw = model.width; int mh = model.height; int maxPoolSize = (mw -1) * mw / 2 * (mh - 1) * mh / 2 * N_CHANNELS; nfeatures = std::min(desired, maxPoolSize); pool.reserve(nfeatures); sft::Random::engine eng(seed); sft::Random::engine eng_ch(seed); sft::Random::uniform chRand(0, N_CHANNELS - 1); sft::Random::uniform xRand(0, model.width - 2); sft::Random::uniform yRand(0, model.height - 2); sft::Random::uniform wRand(1, model.width - 1); sft::Random::uniform hRand(1, model.height - 1); while (pool.size() < size_t(nfeatures)) { int x = xRand(eng); int y = yRand(eng); int w = 1 + wRand(eng, model.width - x - 1); int h = 1 + hRand(eng, model.height - y - 1); CV_Assert(w > 0); CV_Assert(h > 0); CV_Assert(w + x < model.width); CV_Assert(h + y < model.height); int ch = chRand(eng_ch); sft::ICF f(x, y, w, h, ch); if (std::find(pool.begin(), pool.end(),f) == pool.end()) pool.push_back(f); } }