refactoring

apps/sft/fpool.cpp

@@ -0,0 +1,191 @@
+/*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 <sft/fpool.hpp>
+#include <sft/random.hpp>
+
+#include <glob.h>
+#include <queue>
+
+// ========= FeaturePool ========= //
+
+sft::ICFFeaturePool::ICFFeaturePool(cv::Size m, int n) : FeaturePool(), model(m), nfeatures(n)
+{
+    CV_Assert(m != cv::Size() && n > 0);
+    fill(nfeatures);
+}
+
+void sft::ICFFeaturePool::preprocess(const Mat& frame, Mat& integrals) const
+{
+    preprocessor.apply(frame, integrals);
+}
+
+float sft::ICFFeaturePool::apply(int fi, int si, const Mat& integrals) const
+{
+    return pool[fi](integrals.row(si), model);
+}
+
+void sft::ICFFeaturePool::write( cv::FileStorage& fs, int index) const
+{
+    CV_Assert((index > 0) && (index < (int)pool.size()));
+    fs << pool[index];
+}
+
+void sft::write(cv::FileStorage& fs, const string&, const ICF& f)
+{
+    fs << "{" << "channel" << f.channel << "rect" << f.bb << "}";
+}
+
+sft::ICFFeaturePool::~ICFFeaturePool(){}
+
+void sft::ICFFeaturePool::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);
+    dprintf("Requeste feature pool %d max %d suggested %d\n", desired, maxPoolSize, nfeatures);
+
+    pool.reserve(nfeatures);
+
+    sft::Random::engine eng(8854342234L);
+    sft::Random::engine eng_ch(314152314L);
+
+    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);
+        }
+    }
+}
+
+std::ostream& sft::operator<<(std::ostream& out, const sft::ICF& m)
+{
+    out << m.channel << " " << m.bb;
+    return out;
+}
+
+// ============ Dataset ============ //
+namespace {
+using namespace sft;
+
+string itoa(long i)
+{
+    char s[65];
+    sprintf(s, "%ld", i);
+    return std::string(s);
+}
+
+void glob(const string& path, svector& ret)
+{
+    glob_t glob_result;
+    glob(path.c_str(), GLOB_TILDE, 0, &glob_result);
+
+    ret.clear();
+    ret.reserve(glob_result.gl_pathc);
+
+    for(uint i = 0; i < glob_result.gl_pathc; ++i)
+    {
+        ret.push_back(std::string(glob_result.gl_pathv[i]));
+        dprintf("%s\n", ret[i].c_str());
+    }
+
+    globfree(&glob_result);
+}
+}
+// in the default case data folders should be alligned as following:
+// 1. positives: <train or test path>/octave_<octave number>/pos/*.png
+// 2. negatives: <train or test path>/octave_<octave number>/neg/*.png
+ScaledDataset::ScaledDataset(const string& path, const int oct)
+{
+    dprintf("%s\n", "get dataset file names...");
+
+    dprintf("%s\n", "Positives globbing...");
+    glob(path + "/pos/octave_" + itoa(oct) + "/*.png", pos);
+
+    dprintf("%s\n", "Negatives globbing...");
+    glob(path + "/neg/octave_" + itoa(oct) + "/*.png", neg);
+
+    // Check: files not empty
+    CV_Assert(pos.size() != size_t(0));
+    CV_Assert(neg.size() != size_t(0));
+}
+
+cv::Mat ScaledDataset::get(SampleType type, int idx) const
+{
+    const std::string& src = (type == POSITIVE)? pos[idx]: neg[idx];
+    return cv::imread(src);
+}
+
+int ScaledDataset::available(SampleType type) const
+{
+    return (int)((type == POSITIVE)? pos.size():neg.size());
+}
+
+ScaledDataset::~ScaledDataset(){}