Open Source Computer Vision Library https://opencv.org/
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/*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 <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(cv::InputArray frame, cv::OutputArray 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(){}
#if defined _WIN32 && (_WIN32 || _WIN64)
# if _WIN64
# define USE_LONG_SEEDS
# endif
#endif
#if defined (__GNUC__) &&__GNUC__
# if defined(__x86_64__) || defined(__ppc64__)
# define USE_LONG_SEEDS
# endif
#endif
#if defined USE_LONG_SEEDS
# define FEATURE_RECT_SEED 8854342234LU
#else
# define FEATURE_RECT_SEED 88543422LU
#endif
# define DCHANNELS_SEED 314152314LU
#undef USE_LONG_SEEDS
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(FEATURE_RECT_SEED);
sft::Random::engine eng_ch(DCHANNELS_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);
std::cout << f << std::endl;
}
}
}
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);
}
}
#if !defined (_WIN32) && ! defined(__MINGW32__)
#include <glob.h>
namespace {
using namespace sft;
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(unsigned int 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);
}
}
#else
#include <windows.h>
namespace {
using namespace sft;
void glob(const string& refRoot, const string& refExt, svector &refvecFiles)
{
std::string strFilePath; // Filepath
std::string strExtension; // Extension
std::string strPattern = refRoot + "\\*.*";
WIN32_FIND_DATA FileInformation; // File information
HANDLE hFile = ::FindFirstFile(strPattern.c_str(), &FileInformation);
if(hFile == INVALID_HANDLE_VALUE)
CV_Error(CV_StsBadArg, "Your dataset search path is incorrect");
do
{
if(FileInformation.cFileName[0] != '.')
{
strFilePath.erase();
strFilePath = refRoot + "\\" + FileInformation.cFileName;
if( !(FileInformation.dwFileAttributes & FILE_ATTRIBUTE_DIRECTORY) )
{
// Check extension
strExtension = FileInformation.cFileName;
strExtension = strExtension.substr(strExtension.rfind(".") + 1);
if(strExtension == refExt)
// Save filename
refvecFiles.push_back(strFilePath);
}
}
}
while(::FindNextFile(hFile, &FileInformation) == TRUE);
// Close handle
::FindClose(hFile);
DWORD dwError = ::GetLastError();
if(dwError != ERROR_NO_MORE_FILES)
CV_Error(CV_StsBadArg, "Your dataset search path is incorrect");
}
}
#endif
// 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...");
#if !defined (_WIN32) && ! defined(__MINGW32__)
glob(path + "/pos/octave_" + itoa(oct) + "/*.png", pos);
#else
glob(path + "/pos/octave_" + itoa(oct), "png", pos);
#endif
dprintf("%s\n", "Negatives globbing...");
#if !defined (_WIN32) && ! defined(__MINGW32__)
glob(path + "/neg/octave_" + itoa(oct) + "/*.png", neg);
#else
glob(path + "/neg/octave_" + itoa(oct), "png", neg);
#endif
// 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(){}