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Open Source Computer Vision Library
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191 lines
5.8 KiB
191 lines
5.8 KiB
/*M/////////////////////////////////////////////////////////////////////////////////////// |
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// |
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. |
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// |
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// By downloading, copying, installing or using the software you agree to this license. |
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// If you do not agree to this license, do not download, install, |
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// copy or use the software. |
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// |
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// |
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// License Agreement |
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// For Open Source Computer Vision Library |
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// |
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. |
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// Copyright (C) 2008-2012, Willow Garage Inc., all rights reserved. |
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// Third party copyrights are property of their respective owners. |
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// |
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// Redistribution and use in source and binary forms, with or without modification, |
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// are permitted provided that the following conditions are met: |
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// |
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// * Redistribution's of source code must retain the above copyright notice, |
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// this list of conditions and the following disclaimer. |
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// |
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// * Redistribution's in binary form must reproduce the above copyright notice, |
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// this list of conditions and the following disclaimer in the documentation |
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// and/or other materials provided with the distribution. |
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// |
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// * The name of the copyright holders may not be used to endorse or promote products |
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// derived from this software without specific prior written permission. |
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// |
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// This software is provided by the copyright holders and contributors "as is" and |
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// any express or implied warranties, including, but not limited to, the implied |
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// warranties of merchantability and fitness for a particular purpose are disclaimed. |
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// In no event shall the Intel Corporation or contributors be liable for any direct, |
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// indirect, incidental, special, exemplary, or consequential damages |
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// (including, but not limited to, procurement of substitute goods or services; |
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// loss of use, data, or profits; or business interruption) however caused |
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// and on any theory of liability, whether in contract, strict liability, |
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// or tort (including negligence or otherwise) arising in any way out of |
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// the use of this software, even if advised of the possibility of such damage. |
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// |
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//M*/ |
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#include <sft/fpool.hpp> |
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#include <sft/random.hpp> |
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#include <glob.h> |
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#include <queue> |
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// ========= FeaturePool ========= // |
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sft::ICFFeaturePool::ICFFeaturePool(cv::Size m, int n) : FeaturePool(), model(m), nfeatures(n) |
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{ |
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CV_Assert(m != cv::Size() && n > 0); |
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fill(nfeatures); |
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} |
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void sft::ICFFeaturePool::preprocess(cv::InputArray frame, cv::OutputArray integrals) const |
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{ |
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preprocessor.apply(frame, integrals); |
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} |
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float sft::ICFFeaturePool::apply(int fi, int si, const Mat& integrals) const |
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{ |
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return pool[fi](integrals.row(si), model); |
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} |
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void sft::ICFFeaturePool::write( cv::FileStorage& fs, int index) const |
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{ |
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CV_Assert((index > 0) && (index < (int)pool.size())); |
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fs << pool[index]; |
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} |
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void sft::write(cv::FileStorage& fs, const string&, const ICF& f) |
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{ |
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fs << "{" << "channel" << f.channel << "rect" << f.bb << "}"; |
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} |
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sft::ICFFeaturePool::~ICFFeaturePool(){} |
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void sft::ICFFeaturePool::fill(int desired) |
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{ |
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int mw = model.width; |
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int mh = model.height; |
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int maxPoolSize = (mw -1) * mw / 2 * (mh - 1) * mh / 2 * N_CHANNELS; |
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nfeatures = std::min(desired, maxPoolSize); |
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dprintf("Requeste feature pool %d max %d suggested %d\n", desired, maxPoolSize, nfeatures); |
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pool.reserve(nfeatures); |
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sft::Random::engine eng(8854342234L); |
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sft::Random::engine eng_ch(314152314L); |
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sft::Random::uniform chRand(0, N_CHANNELS - 1); |
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sft::Random::uniform xRand(0, model.width - 2); |
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sft::Random::uniform yRand(0, model.height - 2); |
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sft::Random::uniform wRand(1, model.width - 1); |
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sft::Random::uniform hRand(1, model.height - 1); |
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while (pool.size() < size_t(nfeatures)) |
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{ |
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int x = xRand(eng); |
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int y = yRand(eng); |
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int w = 1 + wRand(eng, model.width - x - 1); |
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int h = 1 + hRand(eng, model.height - y - 1); |
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CV_Assert(w > 0); |
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CV_Assert(h > 0); |
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CV_Assert(w + x < model.width); |
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CV_Assert(h + y < model.height); |
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int ch = chRand(eng_ch); |
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sft::ICF f(x, y, w, h, ch); |
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if (std::find(pool.begin(), pool.end(),f) == pool.end()) |
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{ |
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pool.push_back(f); |
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} |
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} |
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} |
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std::ostream& sft::operator<<(std::ostream& out, const sft::ICF& m) |
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{ |
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out << m.channel << " " << m.bb; |
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return out; |
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} |
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// ============ Dataset ============ // |
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namespace { |
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using namespace sft; |
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string itoa(long i) |
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{ |
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char s[65]; |
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sprintf(s, "%ld", i); |
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return std::string(s); |
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} |
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void glob(const string& path, svector& ret) |
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{ |
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glob_t glob_result; |
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glob(path.c_str(), GLOB_TILDE, 0, &glob_result); |
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ret.clear(); |
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ret.reserve(glob_result.gl_pathc); |
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for(uint i = 0; i < glob_result.gl_pathc; ++i) |
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{ |
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ret.push_back(std::string(glob_result.gl_pathv[i])); |
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dprintf("%s\n", ret[i].c_str()); |
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} |
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globfree(&glob_result); |
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} |
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} |
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// in the default case data folders should be alligned as following: |
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// 1. positives: <train or test path>/octave_<octave number>/pos/*.png |
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// 2. negatives: <train or test path>/octave_<octave number>/neg/*.png |
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ScaledDataset::ScaledDataset(const string& path, const int oct) |
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{ |
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dprintf("%s\n", "get dataset file names..."); |
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dprintf("%s\n", "Positives globbing..."); |
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glob(path + "/pos/octave_" + itoa(oct) + "/*.png", pos); |
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dprintf("%s\n", "Negatives globbing..."); |
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glob(path + "/neg/octave_" + itoa(oct) + "/*.png", neg); |
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// Check: files not empty |
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CV_Assert(pos.size() != size_t(0)); |
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CV_Assert(neg.size() != size_t(0)); |
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} |
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cv::Mat ScaledDataset::get(SampleType type, int idx) const |
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{ |
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const std::string& src = (type == POSITIVE)? pos[idx]: neg[idx]; |
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return cv::imread(src); |
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} |
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int ScaledDataset::available(SampleType type) const |
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{ |
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return (int)((type == POSITIVE)? pos.size():neg.size()); |
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} |
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ScaledDataset::~ScaledDataset(){} |