//M*/
#include <sft/fpool.hpp>
-#include <sft/random.hpp>
#include <iostream>
-
#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);
-}
-
-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];
-}
-
-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);
-
- cv::ChannelFeature 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;
- }
- }
-}
-
// ============ Dataset ============ //
namespace {
using namespace sft;
namespace sft
{
-using cv::FeaturePool;
using cv::Dataset;
-class ICFFeaturePool : public cv::FeaturePool
-{
-public:
- ICFFeaturePool(cv::Size model, int nfeatures);
-
- virtual int size() const { return (int)pool.size(); }
- virtual float apply(int fi, int si, const cv::Mat& integrals) const;
- virtual void write( cv::FileStorage& fs, int index) const;
-
- virtual ~ICFFeaturePool();
-
-private:
-
- void fill(int desired);
-
- cv::Size model;
- int nfeatures;
-
- std::vector<cv::ChannelFeature> pool;
-
- static const unsigned int seed = 0;
-
- enum { N_CHANNELS = 10 };
-};
-
-
-
class ScaledDataset : public Dataset
{
public:
+++ /dev/null
-/*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 sft {
-struct Random
-{
- typedef std::mt19937 engine;
- typedef std::uniform_int<int> uniform;
-};
-}
-
-#elif (__GNUC__) && __GNUC__ > 3 && __GNUC_MINOR__ > 1 && !defined(__ANDROID__)
-
-# if defined (__cplusplus) && __cplusplus > 201100L
-# include <random>
-namespace sft {
-struct Random
-{
- typedef std::mt19937 engine;
- typedef std::uniform_int<int> uniform;
-};
-}
-# else
-# include <tr1/random>
-
-namespace sft {
-struct Random
-{
- typedef std::tr1::mt19937 engine;
- typedef std::tr1::uniform_int<int> uniform;
-};
-}
-# endif
-
-#else
-#include <opencv2/core/core.hpp>
-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;
-};
-
-}
-
-namespace sft {
-struct Random
-{
- typedef rnd::engine engine;
- typedef rnd::uniform_int<int> uniform;
-};
-}
-
-#endif
-
-#endif
\ No newline at end of file
int nfeatures = cfg.poolSize;
cv::Size model = cfg.model(it);
std::cout << "Model " << model << std::endl;
- sft::ICFFeaturePool pool(model, nfeatures);
- nfeatures = pool.size();
+ cv::Ptr<cv::FeaturePool> pool = cv::FeaturePool::create(model, nfeatures);
+ nfeatures = pool->size();
int npositives = cfg.positives;
std::string path = cfg.trainPath;
sft::ScaledDataset dataset(path, *it);
- if (boost->train(&dataset, &pool, cfg.weaks, cfg.treeDepth))
+ if (boost->train(&dataset, pool, cfg.weaks, cfg.treeDepth))
{
CvFileStorage* fout = cvOpenFileStorage(cfg.resPath(it).c_str(), 0, CV_STORAGE_WRITE);
boost->write(fout, cfg.cascadeName);
cv::Mat thresholds;
boost->setRejectThresholds(thresholds);
- boost->write(fso, &pool, thresholds);
+ boost->write(fso, pool, thresholds);
cv::FileStorage tfs(("thresholds." + cfg.resPath(it)).c_str(), cv::FileStorage::WRITE);
tfs << "thresholds" << thresholds;
int kind;
};
-class CV_EXPORTS FeaturePool
-{
-public:
- virtual int size() const = 0;
- virtual float apply(int fi, int si, const Mat& integrals) const = 0;
- virtual void write( cv::FileStorage& fs, int index) const = 0;
- virtual ~FeaturePool();
-};
class CV_EXPORTS Dataset
{
};
// ========================================================================== //
+// Public interface feature pool.
+// ========================================================================== //
+
+class CV_EXPORTS FeaturePool
+{
+public:
+
+ virtual int size() const = 0;
+ virtual float apply(int fi, int si, const Mat& channels) const = 0;
+ virtual void write( cv::FileStorage& fs, int index) const = 0;
+ virtual ~FeaturePool();
+
+ static cv::Ptr<FeaturePool> create(const cv::Size& model, int nfeatures);
+};
+
+// ========================================================================== //
// First order channel feature.
// ========================================================================== //
//M*/
#include "precomp.hpp"
+#include "_random.hpp"
namespace {
}
cv::ChannelFeature::~ChannelFeature(){}
+
+namespace {
+
+class ChannelFeaturePool : public cv::FeaturePool
+{
+public:
+ ChannelFeaturePool(cv::Size m, int n) : FeaturePool(), model(m)
+ {
+ CV_Assert(m != cv::Size() && n > 0);
+ fill(n);
+ }
+
+ virtual int size() const { return (int)pool.size(); }
+ virtual float apply(int fi, int si, const cv::Mat& integrals) const;
+ virtual void write( cv::FileStorage& fs, int index) const;
+
+ virtual ~ChannelFeaturePool() {}
+
+private:
+
+ void fill(int desired);
+
+ cv::Size model;
+ std::vector<cv::ChannelFeature> pool;
+ enum { N_CHANNELS = 10 };
+};
+
+float ChannelFeaturePool::apply(int fi, int si, const cv::Mat& integrals) const
+{
+ return pool[fi](integrals.row(si), model);
+}
+
+void ChannelFeaturePool::write( cv::FileStorage& fs, int index) const
+{
+ CV_Assert((index > 0) && (index < (int)pool.size()));
+ fs << pool[index];
+}
+
+#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 ChannelFeaturePool::fill(int desired)
+{
+ int mw = model.width;
+ int mh = model.height;
+
+ int maxPoolSize = (mw -1) * mw / 2 * (mh - 1) * mh / 2 * N_CHANNELS;
+
+ int 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);
+
+ cv::ChannelFeature 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;
+ }
+ }
+}
+
+}
+
+cv::Ptr<cv::FeaturePool> cv::FeaturePool::create(const cv::Size& model, int nfeatures)
+{
+ cv::Ptr<cv::FeaturePool> pool(new ChannelFeaturePool(model, nfeatures));
+ return pool;
+}
projects / profile / ivi / opencv.git / commitdiff