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Merge pull request #643 from cuda-geek:refactor-softcascade-globbing

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cuda-geek 2013-03-13 17:00:53 +04:00 committed by OpenCV Buildbot
commit 061dd7e84e
5 changed files with 54 additions and 362 deletions
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96
apps/sft/dataset.cpp
View File

@ -46,116 +46,32 @@
#include <iostream>
#include <queue>
inline std::string itoa(long i) { return cv::format("%ld", i); }
#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; // File path
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 aligned 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)
sft::ScaledDataset::ScaledDataset(const string& path, const int oct)
{
dprintf("%s\n", "get dataset file names...");
dprintf("%s\n", "Positives globing...");
#if !defined (_WIN32) && ! defined(__MINGW32__)
glob(path + "/pos/octave_" + itoa(oct) + "/*.png", pos);
#else
glob(path + "/pos/octave_" + itoa(oct), "png", pos);
#endif
cv::glob(path + "/pos/octave_" + cv::format("%d", oct) + "/*.png", pos);
dprintf("%s\n", "Negatives globing...");
#if !defined (_WIN32) && ! defined(__MINGW32__)
glob(path + "/neg/octave_" + itoa(oct) + "/*.png", neg);
#else
glob(path + "/neg/octave_" + itoa(oct), "png", neg);
#endif
cv::glob(path + "/neg/octave_" + cv::format("%d", 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
cv::Mat sft::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
int sft::ScaledDataset::available(SampleType type) const
{
return (int)((type == POSITIVE)? pos.size():neg.size());
}
ScaledDataset::~ScaledDataset(){}
sft::ScaledDataset::~ScaledDataset(){}

162
modules/softcascade/src/_random.hpp
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@ -1,162 +0,0 @@
/*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*/
#ifndef __SFT_RANDOM_HPP__
#define __SFT_RANDOM_HPP__
#if defined(_MSC_VER) && _MSC_VER >= 1600
# include <random>
namespace cv { namespace softcascade { namespace internal
{
struct Random
{
typedef std::mt19937 engine;
typedef engine::result_type seed_type;
typedef std::uniform_int<int> uniform;
};
}}}
#elif (__GNUC__) && __GNUC__ > 3 && __GNUC_MINOR__ > 1 && !defined(__ANDROID__)
# if defined (__cplusplus) && __cplusplus > 201100L
# include <random>
namespace cv { namespace softcascade { namespace internal
{
struct Random
{
typedef std::mt19937 engine;
typedef engine::result_type seed_type;
// True if we're using C++11.
#if __cplusplus >= 201103L
// C++11 removes uniform_int.
typedef std::uniform_int_distribution<int> uniform;
#else
typedef std::uniform_int<int> uniform;
#endif
};
}}}
# else
# include <tr1/random>
namespace cv { namespace softcascade { namespace internal
{
struct Random
{
typedef std::tr1::mt19937 engine;
typedef engine::result_type seed_type;
typedef std::tr1::uniform_int<int> uniform;
};
}}}
# endif
#else
# include <opencv2/core/core.hpp>
namespace cv { namespace softcascade { namespace internal
{
namespace rnd {
typedef cv::RNG engine;
template<typename T>
struct uniform_int
{
uniform_int(const int _min, const int _max) : min(_min), max(_max) {}
T operator() (engine& eng, const int bound) const
{
return (T)eng.uniform(min, bound);
}
T operator() (engine& eng) const
{
return (T)eng.uniform(min, max);
}
private:
int min;
int max;
};
}
struct Random
{
typedef rnd::engine engine;
typedef uint64 seed_type;
typedef rnd::uniform_int<int> uniform;
};
}}}
#endif
#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
# define INDEX_ENGINE_SEED 764224349868LU
#else
# define FEATURE_RECT_SEED 88543422LU
# define INDEX_ENGINE_SEED 76422434LU
#endif
#undef USE_LONG_SEEDS
#define DCHANNELS_SEED 314152314LU
#define DX_DY_SEED 65633343LU
#endif

14
modules/softcascade/src/integral_channel_builder.cpp
View File

@ -238,22 +238,8 @@ void ChannelFeaturePool::fill(int desired)
int x = xRand(eng);
int y = yRand(eng);
#if __cplusplus >= 201103L
// The interface changed slightly going from uniform_int to
// uniform_int_distribution. See this page to understand
// the old behavior:
// http://www.boost.org/doc/libs/1_47_0/boost/random/uniform_int.hpp
int w = 1 + wRand(
eng,
// This extra "- 1" appears to be necessary, based on the Boost docs.
Random::uniform::param_type(0, (model.width - x - 1) - 1));
int h = 1 + hRand(
eng,
Random::uniform::param_type(0, (model.height - y - 1) - 1));
#else
int w = 1 + wRand(eng, model.width - x - 1);
int h = 1 + hRand(eng, model.height - y - 1);
#endif
CV_Assert(w > 0);
CV_Assert(h > 0);

42
modules/softcascade/src/precomp.hpp
View File

@ -53,6 +53,46 @@
#include "opencv2/core/core_c.h"
#include "opencv2/core/internal.hpp"
#include "opencv2/ml/ml.hpp"
#include "_random.hpp"
namespace cv { namespace softcascade { namespace internal
{
namespace rnd {
typedef cv::RNG_MT19937 engine;
template<typename T>
struct uniform_int
{
uniform_int(const int _min, const int _max) : min(_min), max(_max) {}
T operator() (engine& eng, const int bound) const
{
return (T)eng.uniform(min, bound);
}
T operator() (engine& eng) const
{
return (T)eng.uniform(min, max);
}
private:
int min;
int max;
};
}
struct Random
{
typedef rnd::engine engine;
typedef uint64 seed_type;
typedef rnd::uniform_int<int> uniform;
};
}}}
#define FEATURE_RECT_SEED 88543422U
#define INDEX_ENGINE_SEED 76422434U
#define DCHANNELS_SEED 314152314U
#define DX_DY_SEED 65633343U
#endif

102
modules/softcascade/test/test_training.cpp
View File

@ -42,17 +42,11 @@
#if !defined(ANDROID)
#include <test_precomp.hpp>
#include <string>
#include <fstream>
#include <vector>
#include "test_precomp.hpp"
#if !defined (_WIN32) && ! defined(__MINGW32__)
# include <glob.h>
#else
# include <windows.h>
#endif
using namespace std;
namespace {
@ -74,92 +68,10 @@ private:
svector neg;
};
string itoa(long i)
{
char s[65];
sprintf(s, "%ld", i);
return std::string(s);
}
#if !defined (_WIN32) && ! defined(__MINGW32__)
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]));
}
globfree(&glob_result);
}
#else
void glob(const string& refRoot, const string& refExt, svector &refvecFiles)
{
std::string strFilePath; // File path
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
ScaledDataset::ScaledDataset(const string& path, const int oct)
{
#if !defined (_WIN32) && ! defined(__MINGW32__)
glob(path + "/pos/octave_" + itoa(oct) + "/*.png", pos);
#else
glob(path + "/pos/octave_" + itoa(oct), "png", pos);
#endif
#if !defined (_WIN32) && ! defined(__MINGW32__)
glob(path + "/neg/octave_" + itoa(oct) + "/*.png", neg);
#else
glob(path + "/neg/octave_" + itoa(oct), "png", neg);
#endif
cv::glob(path + cv::format("/octave_%d/*.png", oct), pos);
cv::glob(path + "/*.png", neg);
// Check: files not empty
CV_Assert(pos.size() != size_t(0));
@ -181,7 +93,7 @@ ScaledDataset::~ScaledDataset(){}
}
TEST(DISABLED_SoftCascade, training)
TEST(SoftCascade, training)
{
// // 2. check and open output file
string outXmlPath = cv::tempfile(".xml");
@ -214,8 +126,8 @@ TEST(DISABLED_SoftCascade, training)
cv::Ptr<FeaturePool> pool = FeaturePool::create(model, nfeatures, 10);
nfeatures = pool->size();
int npositives = 20;
int nnegatives = 40;
int npositives = 10;
int nnegatives = 20;
cv::Rect boundingBox = cv::Rect( cvRound(20 * octave), cvRound(20 * octave),
cvRound(64 * octave), cvRound(128 * octave));
@ -223,7 +135,7 @@ TEST(DISABLED_SoftCascade, training)
cv::Ptr<ChannelFeatureBuilder> builder = ChannelFeatureBuilder::create("HOG6MagLuv");
cv::Ptr<Octave> boost = Octave::create(boundingBox, npositives, nnegatives, *it, shrinkage, builder);
std::string path = cvtest::TS::ptr()->get_data_path() + "softcascade/sample_training_set";
std::string path = cvtest::TS::ptr()->get_data_path() + "cascadeandhog/sample_training_set";
ScaledDataset dataset(path, *it);
if (boost->train(&dataset, pool, 3, 2))