Olena-patches November 2010

olena-patches@lrde.epita.fr

7 participants
370 discussions

last-svn-commit-39-gb050ed7 Simple integration test.

by Yann Jacquelet

* ok/mln/img_path.hh: New header file. * ok/mln/accu/histo/histo1d.hh: New header file. * ok/mln/accu/histo/histo2d.hh: New header file. * ok/mln/accu/histo/histo3d.hh: New header file. * ok/test/accu/histo/gaussian.sh: New gnuplot script file. * ok/test/accu/histo/histo1d.cc: New source file. --- scribo/sandbox/green/ChangeLog | 12 + scribo/sandbox/green/README | 32 + .../sandbox/green/ok/mln/accu/histo}/histo1d.hh | 100 ++-- .../sandbox/green/ok/mln/accu/histo}/histo2d.hh | 0 .../sandbox/green/ok/mln/accu/histo/histo3d.hh | 0 .../sandbox/green/ok}/mln/img_path.hh | 0 .../sandbox/green/ok/test/accu/histo}/gaussian.sh | 0 scribo/sandbox/green/ok/test/accu/histo/histo1d | Bin 0 -> 802920 bytes scribo/sandbox/green/ok/test/accu/histo/histo1d.cc | 726 ++++++++++++++++++++ 9 files changed, 813 insertions(+), 57 deletions(-) create mode 100644 scribo/sandbox/green/README copy {milena/sandbox/green/mln/accu/stat => scribo/sandbox/green/ok/mln/accu/histo}/histo1d.hh (74%) copy {milena/sandbox/green/mln/accu/stat => scribo/sandbox/green/ok/mln/accu/histo}/histo2d.hh (100%) copy milena/sandbox/green/mln/accu/stat/histo3d_rgb.hh => scribo/sandbox/green/ok/mln/accu/histo/histo3d.hh (100%) copy {milena/sandbox/green => scribo/sandbox/green/ok}/mln/img_path.hh (100%) copy {milena/sandbox/green/tests/accu/stat/histo1d => scribo/sandbox/green/ok/test/accu/histo}/gaussian.sh (100%) create mode 100755 scribo/sandbox/green/ok/test/accu/histo/histo1d create mode 100644 scribo/sandbox/green/ok/test/accu/histo/histo1d.cc diff --git a/scribo/sandbox/green/ChangeLog b/scribo/sandbox/green/ChangeLog index e69de29..ed399c5 100644 --- a/scribo/sandbox/green/ChangeLog +++ b/scribo/sandbox/green/ChangeLog @@ -0,0 +1,12 @@ +2010-06-21 Yann Jacquelet <jacquelet(a)lrde.epita.fr> + + Simple integration test. + + * README: New text file. + * ok/mln/img_path.hh: New header file. + * ok/mln/accu/histo/histo1d.hh: New header file. + * ok/mln/accu/histo/histo2d.hh: New header file. + * ok/mln/accu/histo/histo3d.hh: New header file. + * ok/test/accu/histo/gaussian.sh: New gnuplot script file. + * ok/test/accu/histo/histo1d.cc: New source file. + diff --git a/scribo/sandbox/green/README b/scribo/sandbox/green/README new file mode 100644 index 0000000..4eb71b7 --- /dev/null +++ b/scribo/sandbox/green/README @@ -0,0 +1,32 @@ +Le travail est classé dans deux répertoires ok et ko. +Le répertoire ok correspond aux sources qui ont été reprises et retestées. +Le répertoire ko correspond aux sources qui ont été juste transférées. + +La première brique logicielle importante sur laquelle s'appuie mes travaux est +la création d'histogrammes sous forme d'image. + + +CREATION DES HISTOGRAMMES +------------------------- + +ko/mln/accu/stat/histo1d.hh: histogramme image valeur scalaire. +ko/mln/accu/stat/histo2d.hh: histogramme image valeur vectorielle 2d. +ko/mln/accu/stat/histo3d_hsl.hh: histogramme image valeur vectorielle 3d (HSL). +ko/mln/accu/stat/histo3d_rgb.hh: histogramme image valeur vectorielle 3d (RGB). + + + + +ok/mln/accu/histo/histo1d.hh: histogramme image valeur scalaire entière. +ok/mln/accu/histo/histo2d.hh: histogramme image valeur vectorielle 2d entière. +ok/mln/accu/histo/histo3d.hh: histogramme image valeur vectorielle 3d entière. + + +SAUVEGARDE DES HISTOGRAMMES +--------------------------- + + + + +VISUALISATION DES HISTOGRAMMES +------------------------------ \ No newline at end of file diff --git a/milena/sandbox/green/mln/accu/stat/histo1d.hh b/scribo/sandbox/green/ok/mln/accu/histo/histo1d.hh similarity index 74% copy from milena/sandbox/green/mln/accu/stat/histo1d.hh copy to scribo/sandbox/green/ok/mln/accu/histo/histo1d.hh index 57d6103..139cf39 100644 --- a/milena/sandbox/green/mln/accu/stat/histo1d.hh +++ b/scribo/sandbox/green/ok/mln/accu/histo/histo1d.hh @@ -1,6 +1,5 @@ -// Copyright (C) 2007 EPITA Research and Development Laboratory (LRDE) -// Copyright (C) 2008 EPITA Research and Development Laboratory (LRDE) -// Copyright (C) 2009 EPITA Research and Development Laboratory (LRDE) +// Copyright (C) 2007,2008,2009,2010 EPITA Research and Development +// Laboratory (LRDE) // // This file is part of Olena. // @@ -25,35 +24,41 @@ // exception does not however invalidate any other reasons why the // executable file might be covered by the GNU General Public License. -#ifndef MLN_ACCU_STAT_HISTO1D_HH -#define MLN_ACCU_STAT_HISTO1D_HH +#ifndef MLN_ACCU_HISTO_HISTO1D_HH +#define MLN_ACCU_HISTO_HISTO1D_HH /// \file /// -/// \brief Define a histogram as an accumulator which returns an image1d . +/// \brief Define a histogram as accumulator which returns an image1d. +/// +/// This source implements the discrete histogram version. It was +/// created for images which the values are derived from integer +/// type. The number of beans is directly infered from the cardinality +/// of the image value. So the int_u8 image has got 256 bins, the +/// int_u<14> image has got 16384 bins. But, this code doesn't work +/// for that quantification because of the coord limitation (signed +/// short, as it is defined in mln/core/def/coord.hh). /// -/// This source implements the discrete histogram version. The number of beans -/// is infer from the number of graylevels. A typical int_u8 image has got -/// 256 bins. An int_u<14> image has got 16384 bins. /// The following sample is a typical use of the histogram. /// -/// #include <mln/value/int_u8.hh> +/// #include <mln/accu/histo/histo1d.hh> +/// #include <mln/data/compute.hh> /// #include <mln/core/image/image1d.hh> /// #include <mln/core/image/image2d.hh> +/// #include <mln/img_path.hh> /// #include <mln/io/pgm/load.hh> -/// #include <mln/accu/stat/histo1d.hh> -/// #include <mln/data/compute.hh> -/// -/// #define OLENA_LENA "/usr/local/share/olena/images/lena.pgm" +/// #include <mln/value/int_u8.hh> /// -/// void test() +/// int main() /// { -/// typedef mln::value::int_u8 int_u8; -/// mln::image2d<int_u8> img_ref; -/// mln::image1d<unsigned> img_res; +/// typedef mln::value::int_u8 t_int_u8; +/// mln::image2d<t_int_u8> img; +/// mln::image1d<unsigned> histo; +/// +/// mln::io::pgm::load(img, OLENA_IMG_PATH"/lena.pgm"); +/// histo = mln::data::compute(mln::accu::meta::histo::histo1d(), img); /// -/// mln::io::pgm::load(img_ref, OLENA_LENA); -/// img_res = mln::data::compute(mln::accu::meta::stat::histo1d(), img_ref); +/// return 0; /// } @@ -80,20 +85,20 @@ namespace mln namespace accu { - namespace stat + namespace histo { // Forward declaration template <typename V> struct histo1d; - } // end of namespace mln::accu::stat + } // end of namespace mln::accu::histo namespace meta { - namespace stat + namespace histo { struct histo1d : public Meta_Accumulator<histo1d> @@ -101,11 +106,11 @@ namespace mln template <typename V> struct with { - typedef accu::stat::histo1d<V> ret; + typedef accu::histo::histo1d<V> ret; }; }; - } // end of namespace mln::accu::meta::stat + } // end of namespace mln::accu::meta::histo } // end of namespace mln::accu::meta @@ -115,7 +120,7 @@ namespace mln { template <typename V> - struct accumulator_< mln::accu::stat::histo1d<V> > + struct accumulator_< mln::accu::histo::histo1d<V> > { typedef accumulator::has_untake::no has_untake; typedef accumulator::has_set_value::no has_set_value; @@ -125,8 +130,8 @@ namespace mln template <typename V> struct set_precise_binary_<op::eq, - accu::stat::histo1d<V>, - accu::stat::histo1d<V> > + accu::histo::histo1d<V>, + accu::histo::histo1d<V> > { typedef bool ret; }; @@ -136,7 +141,7 @@ namespace mln namespace accu { - namespace stat + namespace histo { /// \brief Define an histogram which returns an image1d . @@ -152,7 +157,7 @@ namespace mln template <typename V> struct histo1d : - public mln::accu::internal::base<image1d<unsigned>, histo1d<V> > + public mln::accu::internal::base< image1d<unsigned>,histo1d<V> > { typedef V argument; typedef image1d<unsigned> result; @@ -230,7 +235,7 @@ namespace mln inline histo1d<V>::histo1d() { - trace::entering("mln::accu::stat::histo1d<V>::histo1d"); + trace::entering("mln::accu::histo::histo1d::cstor"); typedef mln_trait_value_comp(V,0) comp; typedef point<grid::tick, V> v_point1d; typedef box<v_point1d> v_box1d; @@ -242,33 +247,26 @@ namespace mln count_.init_(box1d(point1d(mln_min(comp)), point1d(mln_max(comp)))); -// std::cout << "min : " << mln_min(comp) << std::endl; -// std::cout << "max : " << mln_max(comp) << std::endl; + // std::cout << "min : " << mln_min(comp) << std::endl; + // std::cout << "max : " << mln_max(comp) << std::endl; - trace::exiting("mln::accu::stat::histo1d<V>::histo1d"); + trace::exiting("mln::accu::histo::histo1d::cstor"); } template <typename V> inline void histo1d<V>::init() { - trace::entering("mln::accu::stat::histo1d<V>::init"); - data::fill(count_, 0); - trace::exiting("mln::accu::stat::histo1d<V>::init"); } template <typename V> inline void histo1d<V>::take(const argument& t) { - trace::entering("mln::accu::stat::histo1d<V>::take"); - // Just convert a graylevel value (int_u8 like) to a position for an // iterator on the resulting image. ++count_(point1d(t)); - - trace::exiting("mln::accu::stat::histo1d<V>::take"); } @@ -276,20 +274,13 @@ namespace mln inline void histo1d<V>::take(const histo1d<V>& other) { - trace::entering("mln::accu::stat::histo1d<V>::take"); - count_ += other.count_; - - trace::exiting("mln::accu::stat::histo1d<V>::take"); } template <typename V> inline typename histo1d<V>::result histo1d<V>::to_result() const { - trace::entering("mln::accu::stat::histo1d<V>::to_result"); - - trace::exiting("mln::accu::stat::histo1d<V>::to_result"); return count_; } @@ -297,9 +288,6 @@ namespace mln inline histo1d<V>::operator result() const { - trace::entering("mln::accu::stat::histo1d<V>::operator result"); - - trace::exiting("mln::accu::stat::histo1d<V>::operator result"); return count_; } @@ -307,17 +295,15 @@ namespace mln inline bool histo1d<V>::is_valid() const { - trace::entering("mln::accu::stat::histo1d<V>::is_valid"); bool result = count_.is_valid(); - trace::exiting("mln::accu::stat::histo1d<V>::is_valid"); return result; } template <typename V> bool operator==(const histo1d<V>& histo1, const histo1d<V>& histo2) { - trace::entering("mln::accu::stat::operator=="); + trace::entering("mln::accu::histo::histo1d::operator=="); bool result = true; const image1d<unsigned>& res1 = histo1.to_result(); @@ -332,17 +318,17 @@ namespace mln for_all_2(p1, p2) result &= (res1(p1) == res2(p2)); - trace::exiting("mln::accu::stat::operator=="); + trace::exiting("mln::accu::histo::histo1d::operator=="); return result; } #endif // ! MLN_INCLUDE_ONLY - } // end of namespace mln::accu::stat + } // end of namespace mln::accu::histo } // end of namespace mln::accu } // end of namespace mln -#endif // ! MLN_ACCU_STAT_HISTO1D_HH +#endif // ! MLN_ACCU_HISTO_HISTO1D_HH diff --git a/milena/sandbox/green/mln/accu/stat/histo2d.hh b/scribo/sandbox/green/ok/mln/accu/histo/histo2d.hh similarity index 100% copy from milena/sandbox/green/mln/accu/stat/histo2d.hh copy to scribo/sandbox/green/ok/mln/accu/histo/histo2d.hh diff --git a/milena/sandbox/green/mln/accu/stat/histo3d_rgb.hh b/scribo/sandbox/green/ok/mln/accu/histo/histo3d.hh similarity index 100% copy from milena/sandbox/green/mln/accu/stat/histo3d_rgb.hh copy to scribo/sandbox/green/ok/mln/accu/histo/histo3d.hh diff --git a/milena/sandbox/green/mln/img_path.hh b/scribo/sandbox/green/ok/mln/img_path.hh similarity index 100% copy from milena/sandbox/green/mln/img_path.hh copy to scribo/sandbox/green/ok/mln/img_path.hh diff --git a/milena/sandbox/green/tests/accu/stat/histo1d/gaussian.sh b/scribo/sandbox/green/ok/test/accu/histo/gaussian.sh similarity index 100% copy from milena/sandbox/green/tests/accu/stat/histo1d/gaussian.sh copy to scribo/sandbox/green/ok/test/accu/histo/gaussian.sh diff --git a/scribo/sandbox/green/ok/test/accu/histo/histo1d b/scribo/sandbox/green/ok/test/accu/histo/histo1d new file mode 100755 index 0000000000000000000000000000000000000000..59d59e91c6f3c2db1b88ad6445e44797bdfcdd69 GIT binary patch literal 802920 zcmdqK3t(MS+CO~KrWJ(5sH#!pRD)Ej7mBu8;&NzTYC;?85^0*Gnvo`zoK%ZalXl)7 zM@$(V9plof8O*p(hqyMqXp1675p*bu6A6OQpyd1gp7pGKIXNf2jQPI*|0^eZuiJB9 z&wAEn?|n_^%+pd*QUdm0w?Ov*QxD&inl>EQi_YCciiQV*fwVw&U_juoKu_ebZ1`N% z!A}~XQ4i#$;@6#JNDsdj<@oK3G=D53Z2sgQ+u}Ftnv?*4Y#+$f^0}<lGmXDi+~xo& z@v^)dE`3nm2W9-lkmir&#KGTKv>6NB{GEz4f3__5qi}KVc`1S1H+!V<m%1Cu_|rOP zqa3%L{#p1#%1WmUDJwp*thBs(*5Im&!AF_4AWe8X{j5A`OFG%+7x)o&FZ?JQmjAZb z>`kZTH}C(z!w=l>w@1?6*lo=2|8pqHM&ieRl-FVS0d(M(`1QwcD1Q7m48McrE)W=u z>w)+U!0!Of<At!Y@H+;-5%>l1I|9Gn`0b5fKl~2IZ%_Pwh2K8-4Z)B9j>8Y)3mlE# zAp8d6w=@5C*UC_y{7c7Qh}ZeI7w#wz(KoL9X-S4&kJYR9LVN4u$)H>h!f$`gqpbVt zz4vk?64{zT{TzZHEt)#9`oOLHqi)Ev)msXTtzThg3iF7cbR9Z9{gnI9_^`g;k8QhW 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+#include <mln/core/image/image2d.hh> +#include <mln/img_path.hh> +#include <mln/io/pgm/load.hh> +#include <mln/value/int_u8.hh> + +int main() +{ + typedef mln::value::int_u8 t_int_u8; + mln::image2d<t_int_u8> img; + mln::image1d<unsigned> histo; + + mln::io::pgm::load(img, OLENA_IMG_PATH"/lena.pgm"); + histo = mln::data::compute(mln::accu::meta::histo::histo1d(), img); + + return 0; +} + +// #include <mln/img_path.hh> + +// #include <mln/io/plot/save_histo_sh.hh> +// #include <mln/accu/stat/histo1d.hh> +// #include <mln/fun/v2v/int_u16_to_int_u14.hh> + +// #include <mln/io/pgm/load.hh> +// #include <mln/io/pgm/save.hh> +// #include <mln/io/ppm/save.hh> +// #include <mln/io/plot/save.hh> + +// #include <mln/data/compute.hh> +// #include <mln/data/transform.hh> +// #include <mln/data/fill.hh> + +// #include <mln/value/int_u8.hh> +// #include <mln/value/int_u16.hh> +// #include <mln/value/int_u.hh> +// #include <mln/value/label_8.hh> +// #include <mln/value/rgb8.hh> + +// #include <mln/core/alias/neighb1d.hh> +// #include <mln/core/alias/box1d.hh> +// #include <mln/core/alias/point1d.hh> + +// #include <mln/core/routine/initialize.hh> +// #include <mln/core/contract.hh> +// #include <mln/core/grids.hh> + +// #include <mln/accu/math/sum.hh> +// #include <mln/accu/math/count.hh> +// #include <mln/accu/stat/mean.hh> +// #include <mln/accu/stat/variance.hh> + +// #include <mln/morpho/watershed/flooding.hh> +// #include <mln/morpho/elementary/dilation.hh> +// #include <mln/morpho/elementary/closing.hh> + +// #include <mln/linear/convolve.hh> +// #include <mln/linear/gaussian.hh> +// #include <mln/labeling/regional_maxima.hh> +// #include <mln/labeling/colorize.hh> +// #include <mln/labeling/mean_values.hh> + +// #include <mln/make/w_window1d.hh> + +// #include <mln/math/sqr.hh> +// #include <mln/math/pi.hh> +// #include <mln/math/abs.hh> + +// #include <mln/core/image/dmorph/image_if.hh> +// #include <mln/pw/value.hh> + +// //------------------------------------------------------------------------------ +// // TEST IN 8 BITS +// //------------------------------------------------------------------------------ + + +// void test_8bits_operator_equal() +// { +// using namespace mln::accu::stat; + +// typedef mln::value::int_u8 int_u8; +// mln::accu::stat::histo1d<int_u8> histo1; +// mln::accu::stat::histo1d<int_u8> histo2; +// int_u8 val = 3; + +// histo1.init(); +// histo2.init(); + +// mln_assertion(histo1 == histo2); + +// histo1.take(val); + +// mln_assertion(histo1 != histo2); + +// histo2.take(val); + +// mln_assertion(histo1 == histo2); + +// std::cout << "(08 bits) histo == histo : ok" << std::endl; +// } + +// void test_8bits_instantiation_without_argument() +// { +// typedef mln::value::int_u8 int_u8; +// const mln::accu::stat::histo1d<int_u8> histo; +// const mln::image1d<unsigned>& res = histo.to_result(); +// const mln::point1d& min = mln::point1d(mln_min(int_u8)); +// const mln::point1d& max = mln::point1d(mln_max(int_u8)); +// const mln::box1d& ref = mln::box1d(min, max); + +// mln_assertion(ref == res.domain()); +// mln_assertion(res.is_valid()); + +// std::cout << "(08 bits) histo<T> histo : ok" << std::endl; +// } + + +// void test_8bits_initialization() +// { +// typedef mln::value::int_u8 int_u8; +// mln::accu::stat::histo1d<int_u8> histo; +// mln::image1d<unsigned> img_res = histo.to_result(); +// mln::image1d<unsigned> img_ref; + +// mln::initialize(img_ref, img_res); +// mln::data::fill(img_ref, 0); +// histo.init(); + +// unsigned res = mln::data::compute(mln::accu::math::sum<int_u8>(), img_res); +// unsigned ref = mln::data::compute(mln::accu::math::sum<int_u8>(), img_ref); + +// mln_assertion(ref == res); + +// std::cout << "(08 bits) histo.init() : ok" << std::endl; +// } + + +// void test_8bits_take_argument() +// { +// typedef mln::value::int_u8 int_u8; +// mln::accu::stat::histo1d<int_u8> histo1; +// mln::accu::stat::histo1d<int_u8> histo2; +// int_u8 val = 3; + +// histo1.init(); +// histo2.init(); +// histo1.take(val); + +// const mln::image1d<unsigned> img1 = histo1.to_result(); +// const mln::image1d<unsigned> img2 = histo2.to_result(); + +// const unsigned res = mln::data::compute(mln::accu::math::sum<int_u8>(), img1); +// const unsigned ref = mln::data::compute(mln::accu::math::sum<int_u8>(), img2); + +// mln_assertion(ref == res-1); +// mln_assertion(1 == img1(mln::point1d(val))); + +// std::cout << "(08 bits) histo.take(argument) : ok" << std::endl; +// } + + +// void test_8bits_take_other() +// { +// typedef mln::value::int_u8 int_u8; +// mln::accu::stat::histo1d<int_u8> histo1; +// mln::accu::stat::histo1d<int_u8> histo2; +// mln::accu::stat::histo1d<int_u8> histo3; +// int_u8 val = 3; + +// histo1.init(); +// histo2.init(); +// histo3.init(); + +// histo1.take(val); +// histo1.take(val); +// histo3.take(val); +// histo2.take(val); +// histo2.take(histo3); + +// mln_assertion(histo1 == histo2); + +// std::cout << "(08 bits) histo.take(other) : ok" << std::endl; +// } + +// double count_histo(mln::image1d<unsigned> img) +// { +// mln_precondition(img.is_valid()); + +// double result = 0.0; +// mln_piter_(mln::image1d<unsigned>) p(img.domain()); + +// for_all(p) +// result += img(p); + +// return result; +// } + +// double mean_histo(mln::image1d<unsigned> img) +// { +// mln_precondition(img.is_valid()); + +// double count = 0.0; +// double sum = 0.0; +// double result = 0.0; +// mln_piter_(mln::image1d<unsigned>) p(img.domain()); + +// for_all(p) +// { +// count += img(p); +// sum += p[0] * img(p); +// } + +// result = sum / count; + +// return result; +// } + + +// double var_histo(mln::image1d<unsigned> img) +// { +// mln_precondition(img.is_valid()); + +// double count = 0.0; +// double sum = 0.0; +// double sum2 = 0.0; +// double result = 0.0; +// mln_piter_(mln::image1d<unsigned>) p(img.domain()); + +// for_all(p) +// { +// count += img(p); +// sum += p[0] * img(p); +// sum2 += p[0] * p[0] * img(p); +// } + +// result = sum2 / count - (sum / count) * (sum / count); + +// return result; +// } + +// double var_histo2(mln::image1d<unsigned> img) +// { +// mln_precondition(img.is_valid()); + +// double count = count_histo(img); +// double mean = mean_histo(img); +// double result = 0.0; +// mln_piter_(mln::image1d<unsigned>) p(img.domain()); + +// for_all(p) +// { +// result += img(p) * (p[0] - mean) * (p[0] - mean); +// } + +// result /= count; + +// return result; +// } + +// void test_8bits_integration() +// { +// typedef mln::value::int_u8 int_u8; +// typedef mln::accu::math::count<double> count; +// typedef mln::accu::math::sum<double> sum; +// typedef mln::accu::stat::mean<double> mean; +// typedef mln::accu::stat::variance<double> variance; + +// mln::image2d<int_u8> img_ref; +// mln::image1d<unsigned> img_res; + +// mln::io::pgm::load(img_ref, OLENA_IMG_PATH"/lena.pgm"); + +// const double count_ref = mln::data::compute(count(), img_ref); +// const double mean_ref = mln::data::compute(mean(), img_ref); +// const double var_ref = mln::data::compute(variance(), img_ref); + +// img_res = mln::data::compute(mln::accu::meta::stat::histo1d(), img_ref); +// // img_res = mln::data::compute(mln::accu::stat::histo1d<int_u8>(), img_ref); + +// const double count_res = count_histo(img_res); +// const double mean_res = mean_histo(img_res); +// const double var_res = var_histo(img_res); + +// mln_assertion(count_ref == count_res); +// mln_assertion( mean_ref == mean_res ); +// mln_assertion(0.0001 > abs(var_ref - var_res)); + +// std::cout << "(08 bits) test integration : ok" << std::endl; +// } + +// double gaussian_distribution(double x, double mean, double sigma) +// { +// double num = exp(-0.5*mln::math::sqr((x - mean)/sigma)); +// double denom = sigma*mln::math::sqrt(2*mln::math::pi); +// double result = num/denom; + +// return result; +// } + +// /// To calibrate with gnuplot (see gaussian.sh) +// /// square(x) = x*x +// /// gaussian(x,mean,sigma)=exp(-0.5*square((x-mean)/sigma))/(sigma*sqrt(2*pi)) +// /// plot [-20:20] gaussian(x,0,6.0) + +// void gaussian_filter(double ws[], unsigned size, double sigma) +// { +// int h = size/2; + +// for (int i = -h; i <= h; ++i) +// { +// ws[i+h] = gaussian_distribution(i, 0.0, sigma); +// } + +// double sum = 0.0; + +// for (unsigned i = 0; i < size; ++i) +// sum += ws[i]; + +// for (unsigned i = 0; i < size; ++i) +// ws[i] /= sum; +// } + +// /// The aim of this function is to rebuild an label image2d from the segmenting +// /// image of the histogram (label) and the original image (input). +// /// label_image2d / for each grey tone, associate its label. + +// mln::image2d<mln::value::label_8> +// build_8bits(const mln::image2d<mln::value::int_u8>& input, +// const mln::image1d<mln::value::label_8>& label) +// { +// mln::trace::entering("build_8bits"); +// mln_precondition(label.is_valid()); +// mln_precondition(input.is_valid()); + +// mln::image2d<mln::value::label_8> output; + +// mln::initialize(output, input); + +// mln_piter_(mln::image2d<mln::value::int_u8>) pi(input.domain()); +// mln_piter_(mln::image2d<mln::value::label_8>) po(output.domain()); + +// for_all_2(pi, po) +// { +// mln::value::int_u8 val = input(pi); +// unsigned grp = label(mln::point1d(val)); + +// output(po) = grp; +// } + +// mln::trace::exiting("build_8bits"); +// return output; +// } + + +// void test_8bits_classifying() +// { +// typedef mln::value::int_u8 int_u8; +// typedef mln::value::label_8 label_8; +// typedef mln::value::rgb8 rgb8; +// typedef mln::accu::stat::mean<double> mean; + +// mln::image2d<int_u8> img_ref; +// mln::image2d<int_u8> img_out; +// mln::image2d<rgb8> img_rgb; +// mln::image1d<unsigned> img_res; +// mln::image1d<double> img_smooth; +// mln::image1d<label_8> labels; +// label_8 nlabels; + +// //----------------------------------------------------- +// // Loading the scribo image and computing its histogram +// //----------------------------------------------------- + +// std::cout << "(08 bits) LOADING HISTOGRAM" << std::endl; + +// // mln::io::pgm::load(img_ref, OLENA_IMG_PATH"/lena.pgm"); +// mln::io::pgm::load(img_ref, SCRIBO_IMG_PATH"/mp00082c_50p_8bits.pgm"); +// img_res = mln::data::compute(mln::accu::stat::histo1d<int_u8>(), img_ref); +// mln::io::plot::save_histo_sh(img_res, "histo0_8bits.sh"); + + +// //----------------------------------------------------- +// // Smoothing the histogram with a gaussian filter +// //----------------------------------------------------- + +// std::cout << "(08 bits) SMOOTHING HISTOGRAM" << std::endl; + +// double ws[41]; +// gaussian_filter(ws, 41, 6.0); +// img_smooth = mln::linear::convolve(img_res, mln::make::w_window1d(ws)); +// mln::io::plot::save_histo_sh(img_smooth, "histo1_8bits.sh"); + + +// //----------------------------------------------------- +// // Segmenting the histogram with the watershed method +// //----------------------------------------------------- + +// std::cout << "SEGMENTING HISTOGRAM" << std::endl; + +// /* +// labels = mln::labeling::regional_maxima(img_smooth, mln::c2(), nlabels); +// std::cout << "N labels : " << nlabels << std::endl; +// mln::io::plot::save_histo_sh(labels, "histo2_8bits.sh"); +// */ + + +// labels = mln::morpho::watershed::flooding(img_smooth, mln::c2(), nlabels); +// std::cout << "N labels : " << nlabels << std::endl; +// mln::io::plot::save_histo_sh(labels, "histo2_8bits.sh"); + + +// //----------------------------------------------------- +// // Rebuilding the image with the mean of each region +// //----------------------------------------------------- + +// std::cout << "(08 bits) BUILDING OUTPUT" << std::endl; + +// mln::image2d<label_8>img_label = build_8bits(img_ref, labels); + +// std::cout << "(08 bits) COLORING OUTPUT" << std::endl; + +// img_out = mln::labeling::mean_values(img_ref, img_label, nlabels); +// img_rgb = mln::labeling::colorize(rgb8(), img_label); + +// mln::io::pgm::save(img_out, "out_8bits.pgm"); +// mln::io::ppm::save(img_rgb, "color_8bits.pgm"); + +// //labels = mln::morpho::elementary::dilation(labels, mln::c2()); +// //mln::io::plot::save_histo_sh(labels, "histo3.sh"); +// //mln::io::plot::save(labels, "labelized.data"); +// } + +// //------------------------------------------------------------------------------ +// // TEST IN 15 BITS +// //------------------------------------------------------------------------------ + +// void test_14bits_operator_equal() +// { +// using namespace mln::accu::stat; + +// typedef mln::value::int_u<14> int_u14; +// mln::accu::stat::histo1d<int_u14> histo1; +// mln::accu::stat::histo1d<int_u14> histo2; +// int_u14 val = 3; + +// histo1.init(); +// histo2.init(); + +// mln_assertion(histo1 == histo2); + +// histo1.take(val); + +// /// FIXME mln_assertion(histo1 != histo2); doesn't work!! +// mln_assertion(!(histo1 == histo2)); + +// histo2.take(val); + +// mln_assertion(histo1 == histo2); + +// std::cout << "(14 bits) histo == histo : ok" << std::endl; +// } + +// void test_14bits_instantiation_without_argument() +// { +// typedef mln::value::int_u<14> int_u14; +// const mln::accu::stat::histo1d<int_u14> histo; +// const mln::image1d<unsigned>& res = histo.to_result(); +// const mln::point1d& min =mln::point1d(mln_min(int_u14)); +// const mln::point1d& max =mln::point1d(mln_max(int_u14)); +// const mln::box1d& ref = mln::box1d(min, max); + +// mln_assertion(ref == res.domain()); +// mln_assertion(res.is_valid()); + +// std::cout << "(14 bits) histo<T> histo : ok" << std::endl; +// } + + +// void test_14bits_initialization() +// { +// typedef mln::value::int_u<14> int_u14; +// mln::accu::stat::histo1d<int_u14> histo; +// mln::image1d<unsigned> img_res = histo.to_result(); +// mln::image1d<unsigned> img_ref; + +// mln::initialize(img_ref, img_res); +// mln::data::fill(img_ref, 0); +// histo.init(); + +// unsigned res = mln::data::compute(mln::accu::math::sum<int_u14>(), img_res); +// unsigned ref = mln::data::compute(mln::accu::math::sum<int_u14>(), img_ref); + +// mln_assertion(ref == res); + +// std::cout << "(14 bits) histo.init() : ok" << std::endl; +// } + + +// void test_14bits_take_argument() +// { +// typedef mln::value::int_u<14> int_u14; +// mln::accu::stat::histo1d<int_u14> histo1; +// mln::accu::stat::histo1d<int_u14> histo2; +// int_u14 val = 3; + +// histo1.init(); +// histo2.init(); +// histo1.take(val); + +// const mln::image1d<unsigned> img1 = histo1.to_result(); +// const mln::image1d<unsigned> img2 = histo2.to_result(); + +// const unsigned res = mln::data::compute(mln::accu::math::sum<int_u14>(),img1); +// const unsigned ref = mln::data::compute(mln::accu::math::sum<int_u14>(),img2); + +// mln_assertion(ref == res-1); +// mln_assertion(1 == img1(mln::point1d(val))); + +// std::cout << "(14 bits) histo.take(argument) : ok" << std::endl; +// } + + +// void test_14bits_take_other() +// { +// typedef mln::value::int_u<14> int_u14; +// mln::accu::stat::histo1d<int_u14> histo1; +// mln::accu::stat::histo1d<int_u14> histo2; +// mln::accu::stat::histo1d<int_u14> histo3; +// int_u14 val = 3; + +// histo1.init(); +// histo2.init(); +// histo3.init(); + +// histo1.take(val); +// histo1.take(val); +// histo3.take(val); +// histo2.take(val); +// histo2.take(histo3); + +// mln_assertion(histo1 == histo2); + +// std::cout << "(14 bits) histo.take(other) : ok" << std::endl; +// } + +// void test_14bits_integration() +// { +// typedef mln::value::int_u16 int_u16; +// typedef mln::value::int_u<14> int_u14; +// typedef mln::accu::math::count<double> count; +// typedef mln::accu::math::sum<double> sum; +// typedef mln::accu::stat::mean<double> mean; +// typedef mln::accu::stat::variance<double> variance; + +// mln::image2d<int_u16> img_fst; +// mln::image2d<int_u14> img_ref; +// mln::image1d<unsigned> img_res; + +// mln::io::pgm::load(img_fst, OLENA_IMG_PATH"/lena_16.pgm"); +// img_ref = mln::data::transform(img_fst, mln::fun::v2v::int_u16_to_int_u14()); + +// const double count_ref = mln::data::compute(count(), img_ref); +// const double mean_ref = mln::data::compute(mean(), img_ref); +// const double var_ref = mln::data::compute(variance(), img_ref); + +// img_res = mln::data::compute(mln::accu::stat::histo1d<int_u14>(), img_ref); + +// const double count_res = count_histo(img_res); +// const double mean_res = mean_histo(img_res); +// const double var_res = var_histo2(img_res); + +// //std::cout << "var_res : " << var_res << std::endl; +// //std::cout << "var_ref : " << var_ref << std::endl; + +// mln_assertion(count_ref == count_res); +// mln_assertion( mean_ref == mean_res ); +// mln_assertion(0.0001 > abs(var_ref - var_res)); + +// std::cout << "(14 bits) test integration : ok" << std::endl; +// } + +// /// The aim of this function is to rebuild an label image2d from the segmenting +// /// image of the histogram (label) and the original image (input). +// /// label_image2d / for each grey tone, associate its label. + +// mln::image2d<mln::value::label_8> +// build_14bits(const mln::image2d<mln::value::int_u<14> >& input, +// const mln::image1d<mln::value::label_8>& label) +// { +// mln::trace::entering("build_14bits"); +// mln_precondition(label.is_valid()); +// mln_precondition(input.is_valid()); + +// mln::image2d<mln::value::label_8> output; + +// mln::initialize(output, input); + +// mln_piter_(mln::image2d<mln::value::int_u<14> >) pi(input.domain()); +// mln_piter_(mln::image2d<mln::value::label_8>) po(output.domain()); + +// for_all_2(pi, po) +// { +// mln::value::int_u<14> val = input(pi); +// unsigned grp = label(mln::point1d(val)); + +// output(po) = grp; +// } + +// mln::trace::exiting("build_14bits"); +// return output; +// } + + +// void test_14bits_classifying() +// { +// typedef mln::value::int_u16 int_u16; +// typedef mln::value::int_u<14> int_u14; +// typedef mln::value::label_8 label_8; +// typedef mln::value::rgb8 rgb8; +// typedef mln::accu::stat::mean<double> mean; + +// mln::image2d<int_u16> img_fst; +// mln::image2d<int_u14> img_ref; +// mln::image2d<int_u14> img_out; +// mln::image2d<rgb8> img_rgb; +// mln::image1d<unsigned> img_res; +// mln::image1d<double> img_smooth; +// mln::image1d<label_8> labels; +// label_8 nlabels; + +// //----------------------------------------------------- +// // Loading the scribo image and computing its histogram +// //----------------------------------------------------- + +// std::cout << "(14 bits) LOADING HISTOGRAM" << std::endl; + +// //mln::io::pgm::load(img_fst, OLENA_IMG_PATH"/lena_16.pgm"); +// mln::io::pgm::load(img_fst, SCRIBO_IMG_PATH"/mp00082c_50p_16bits.pgm"); +// img_ref = mln::data::transform(img_fst, mln::fun::v2v::int_u16_to_int_u14()); +// img_res = mln::data::compute(mln::accu::stat::histo1d<int_u14>(), img_ref); +// mln::io::plot::save_histo_sh(img_res, "histo0_14bits.sh"); + + +// //----------------------------------------------------- +// // Smoothing the histogram with a gaussian filter +// //----------------------------------------------------- + +// std::cout << "(14 bits) SMOOTHING HISTOGRAM" << std::endl; + +// double ws[401]; +// gaussian_filter(ws, 401, 50.0); +// img_smooth = mln::linear::convolve(img_res, mln::make::w_window1d(ws)); +// mln::io::plot::save_histo_sh(img_smooth, "histo1_14bits.sh"); + + +// //----------------------------------------------------- +// // Segmenting the histogram with the watershed method +// //----------------------------------------------------- + +// std::cout << "(14 bits) SEGMENTING HISTOGRAM" << std::endl; + +// /* +// labels = mln::labeling::regional_maxima(img_smooth, mln::c2(), nlabels); +// std::cout << "N labels : " << nlabels << std::endl; +// mln::io::plot::save_histo_sh(labels, "histo2.sh"); +// */ + + +// labels = mln::morpho::watershed::flooding(img_smooth, mln::c2(), nlabels); +// std::cout << "N labels : " << nlabels << std::endl; +// mln::io::plot::save_histo_sh(labels, "histo2_14bits.sh"); + + +// //----------------------------------------------------- +// // Rebuilding the image with the mean of each region +// //----------------------------------------------------- + +// std::cout << "(14 bits) BUILDING OUTPUT" << std::endl; + +// mln::image2d<label_8>img_label = build_14bits(img_ref, labels); + +// std::cout << "(14 bits) COLORING OUTPUT" << std::endl; + +// img_out = mln::labeling::mean_values(img_ref, img_label, nlabels); +// img_rgb = mln::labeling::colorize(rgb8(), img_label); + +// mln::io::pgm::save(img_out, "out_14bits.pgm"); +// mln::io::ppm::save(img_rgb, "color_14bits.pgm"); + +// //labels = mln::morpho::elementary::dilation(labels, mln::c2()); +// //mln::io::plot::save_histo_sh(labels, "histo3.sh"); +// //mln::io::plot::save(labels, "labelized.data"); +// } + +// int main() +// { +// test_8bits_operator_equal(); +// /* +// test_8bits_instantiation_without_argument(); +// test_8bits_initialization(); +// test_8bits_take_argument(); +// test_8bits_take_other(); +// test_8bits_operator_equal(); +// */ +// //test_8bits_integration(); + +// //test_8bits_classifying(); + +// // PROBLEME AVEC LES COORDONNEES PAR DEFAUT QUI SONT EN SIGNED SHORT +// // SEE mln/core/def/coord.hh +// /* +// test_14bits_instantiation_without_argument(); +// test_14bits_initialization(); +// test_14bits_take_argument(); +// test_14bits_take_other(); +// test_14bits_operator_equal(); +// test_14bits_integration(); +// */ +// //test_14bits_classifying(); + +// return 0; +// } -- 1.5.6.5

14 years, 1 month

last-svn-commit-38-g97cf182 Fix the way to convert unsigned to float.

by Yann Jacquelet

* mln/convert/from_to.hxx: New conversion utilities. * mln/convert/impl/from_unsigned_to_value.hh: New conversion utilities. --- milena/ChangeLog | 7 +++++++ milena/mln/convert/from_to.hxx | 4 ++++ milena/mln/convert/impl/from_unsigned_to_value.hh | 10 ++++++++++ 3 files changed, 21 insertions(+), 0 deletions(-) diff --git a/milena/ChangeLog b/milena/ChangeLog index 10c5def..3804c90 100644 --- a/milena/ChangeLog +++ b/milena/ChangeLog @@ -1,3 +1,10 @@ +2010-06-21 Yann Jacquelet <jacquelet(a)lrde.epita.fr> + + Fix the way to convert unsigned to float. + + * mln/convert/from_to.hxx: New conversion utilities. + * mln/convert/impl/from_unsigned_to_value.hh: New conversion utilities. + 2009-12-02 Yann Jacquelet <jacquelet(a)lrde.epita.fr> Fix the outside template use case for the convolve macros. diff --git a/milena/mln/convert/from_to.hxx b/milena/mln/convert/from_to.hxx index ebc30cd..8334b14 100644 --- a/milena/mln/convert/from_to.hxx +++ b/milena/mln/convert/from_to.hxx @@ -261,6 +261,10 @@ namespace mln void from_to_(const Value<F>& from, Value<T>& to); + // unsigned -> float + void + from_to_(const unsigned& from, float& to); + // double-> Value template <typename V> void diff --git a/milena/mln/convert/impl/from_unsigned_to_value.hh b/milena/mln/convert/impl/from_unsigned_to_value.hh index ad54cff..fe09a3e 100644 --- a/milena/mln/convert/impl/from_unsigned_to_value.hh +++ b/milena/mln/convert/impl/from_unsigned_to_value.hh @@ -118,6 +118,16 @@ namespace mln internal::from_unsigned_to_value_dispatch(from, to); } + + // Facades. + // unsigned-> float + void + from_to_(const unsigned& from, float& to) + { + to = from; + } + + } // end of namespace mln::convert::over_load -- 1.5.6.5

14 years, 1 month

last-svn-commit-37-ga7832fe Add milena library components.

by Yann Jacquelet

* green/mln/accu/stat/histo1d.hh: New header component. * green/mln/fun/p2b/achromatic.hh: New header component. * green/mln/fun/p2b/component_equals.hh: New header component. * green/mln/fun/v2v/achromatism.hh: New header component. * green/mln/fun/v2v/hue_concentration.hh: New header component. * green/mln/fun/v2v/rgb_to_achromatism_map.hh: New header component. * green/mln/fun/v2v/rgb_to_hsv.hh: New header component. * green/mln/fun/v2v/rgb_to_hue_map.hh: New header component. * green/mln/fun/v2v/rgb_to_saturation_map.hh: New header component. * green/mln/fun/v2v/rgb_to_value_map.hh: New header component. * green/mln/img_path.hh: New header component. * green/mln/math/ceil.hh: New header component. * green/mln/math/floor.hh: New header component. * green/mln/math/hsv.hh: New header component. --- milena/sandbox/ChangeLog | 32 ++- milena/sandbox/green/mln/accu/stat/histo1d.hh | 66 ++-- milena/sandbox/green/mln/fun/p2b/achromatic.hh | 112 +++++ .../sandbox/green/mln/fun/p2b/component_equals.hh | 99 +++++ milena/sandbox/green/mln/fun/v2v/achromatism.hh | 64 +++ .../sandbox/green/mln/fun/v2v/hue_concentration.hh | 100 +++++ .../green/mln/fun/v2v/rgb_to_achromatism_map.hh | 77 ++++ milena/sandbox/green/mln/fun/v2v/rgb_to_hsv.hh | 149 +++++++ milena/sandbox/green/mln/fun/v2v/rgb_to_hue_map.hh | 96 +++++ .../green/mln/fun/v2v/rgb_to_saturation_map.hh | 83 ++++ .../sandbox/green/mln/fun/v2v/rgb_to_value_map.hh | 75 ++++ milena/sandbox/green/mln/img_path.hh | 227 +++++++++-- milena/sandbox/green/mln/math/ceil.hh | 64 +++ milena/sandbox/green/mln/math/floor.hh | 64 +++ milena/sandbox/green/mln/value/hsv.hh | 424 ++++++++++++++++++++ 15 files changed, 1670 insertions(+), 62 deletions(-) create mode 100644 milena/sandbox/green/mln/fun/p2b/achromatic.hh create mode 100644 milena/sandbox/green/mln/fun/p2b/component_equals.hh create mode 100644 milena/sandbox/green/mln/fun/v2v/achromatism.hh create mode 100644 milena/sandbox/green/mln/fun/v2v/hue_concentration.hh create mode 100644 milena/sandbox/green/mln/fun/v2v/rgb_to_achromatism_map.hh create mode 100644 milena/sandbox/green/mln/fun/v2v/rgb_to_hsv.hh create mode 100644 milena/sandbox/green/mln/fun/v2v/rgb_to_hue_map.hh create mode 100644 milena/sandbox/green/mln/fun/v2v/rgb_to_saturation_map.hh create mode 100644 milena/sandbox/green/mln/fun/v2v/rgb_to_value_map.hh create mode 100644 milena/sandbox/green/mln/math/ceil.hh create mode 100644 milena/sandbox/green/mln/math/floor.hh create mode 100644 milena/sandbox/green/mln/value/hsv.hh diff --git a/milena/sandbox/ChangeLog b/milena/sandbox/ChangeLog index c41ef7c..62c6e21 100644 --- a/milena/sandbox/ChangeLog +++ b/milena/sandbox/ChangeLog @@ -1,6 +1,36 @@ 2010-06-21 Yann Jacquelet <jacquelet(a)lrde.epita.fr> - Work on Millet saturation descriptor. + Add milena library components. + + * green/mln/accu/stat/histo1d.hh: New header component. + * green/mln/fun/p2b/achromatic.hh: New header component. + * green/mln/fun/p2b/component_equals.hh: New header component. + * green/mln/fun/v2v/achromatism.hh: New header component. + * green/mln/fun/v2v/hue_concentration.hh: New header component. + * green/mln/fun/v2v/rgb_to_achromatism_map.hh: New header component. + * green/mln/fun/v2v/rgb_to_hsv.hh: New header component. + * green/mln/fun/v2v/rgb_to_hue_map.hh: New header component. + * green/mln/fun/v2v/rgb_to_saturation_map.hh: New header component. + * green/mln/fun/v2v/rgb_to_value_map.hh: New header component. + * green/mln/img_path.hh: New header component. + * green/mln/math/ceil.hh: New header component. + * green/mln/math/floor.hh: New header component. + * green/mln/math/hsv.hh: New header component. + +2010-06-21 Yann Jacquelet <jacquelet(a)lrde.epita.fr> + + Work on Millet value descriptor. + + * green/exp/annotating/value: New directory. + * green/exp/annotating/value/Makefile.am: New Makefile. + * green/exp/annotating/value/value.cc: New source file. + * green/exp/annotating/value/text-color.txt: New image class. + * green/exp/annotating/value/text-img.txt: New image class. + * green/exp/annotating/value/text-only.txt: New image class. + +2010-06-21 Yann Jacquelet <jacquelet(a)lrde.epita.fr> + + Work on Millet hue descriptor. * green/exp/annotating/hue: New directory. * green/exp/annotating/hue/Makefile.am: New Makefile. diff --git a/milena/sandbox/green/mln/accu/stat/histo1d.hh b/milena/sandbox/green/mln/accu/stat/histo1d.hh index 807f3bd..57d6103 100644 --- a/milena/sandbox/green/mln/accu/stat/histo1d.hh +++ b/milena/sandbox/green/mln/accu/stat/histo1d.hh @@ -76,26 +76,26 @@ namespace mln { - + namespace accu { - + namespace stat { - + // Forward declaration template <typename V> struct histo1d; } // end of namespace mln::accu::stat - + namespace meta { - + namespace stat { - + struct histo1d : public Meta_Accumulator<histo1d> { template <typename V> @@ -104,16 +104,16 @@ namespace mln typedef accu::stat::histo1d<V> ret; }; }; - + } // end of namespace mln::accu::meta::stat - + } // end of namespace mln::accu::meta - + } // end of namespace mln::accu namespace trait { - + template <typename V> struct accumulator_< mln::accu::stat::histo1d<V> > { @@ -124,34 +124,34 @@ namespace mln }; template <typename V> - struct set_precise_binary_<op::eq, + struct set_precise_binary_<op::eq, accu::stat::histo1d<V>, accu::stat::histo1d<V> > { typedef bool ret; }; - + } // end of namespace mln::trait namespace accu { - + namespace stat - { + { - /// \brief Define an histogram which returns an image1d . + /// \brief Define an histogram which returns an image1d . /// /// Param V defines the space in which we count the values. /// For instance, this histogram works with image2d<int_u8> or with /// image1d<int_u<14> >. The histogram count the occurrence of each value. /// The number of bins depends of the graylevel values, for 8 bits there - /// is 256 bins, for 14 bits there is 16384 bins. Note that over + /// is 256 bins, for 14 bits there is 16384 bins. Note that over /// quantification works too (up to 14 bits). /// /// \ingroup modaccuvalues template <typename V> - struct histo1d : + struct histo1d : public mln::accu::internal::base<image1d<unsigned>, histo1d<V> > { typedef V argument; @@ -162,22 +162,22 @@ namespace mln /// \{ /// \brief Initialize the size of the resulting image1d. /// - /// Initialize the size the resulting image from the theorical dynamic + /// Initialize the size the resulting image from the theorical dynamic /// of the graylevel values (Use V to manage it). histo1d(); /// \} - + /// Manipulators. /// \{ /// \brief Initialize the histogram with zero value. /// - /// This method must be called just before starting the use of the - /// histogram. If it's not, resulting values won't converge to the + /// This method must be called just before starting the use of the + /// histogram. If it's not, resulting values won't converge to the /// density. void init(); - + /// \brief Update the histogram with the graylevel of the pixel t. /// \param[in] t a graylevel pixel of type V. /// @@ -189,7 +189,7 @@ namespace mln /// \brief Update the histogram with an other histogram. /// \param[in] other the other histogram. /// - /// The end user shouldn't call this method. This is part of + /// The end user shouldn't call this method. This is part of /// data compute interface mechanism. void take(const histo1d<V>& other); @@ -234,7 +234,7 @@ namespace mln typedef mln_trait_value_comp(V,0) comp; typedef point<grid::tick, V> v_point1d; typedef box<v_point1d> v_box1d; - + // comp keep a trace of the dimension of the theorical image. // mln_min(comp) --> 0 // mln_max(comp) --> 2^(n-1) [127 for n=7][255 for n=8] ... @@ -242,8 +242,8 @@ namespace mln count_.init_(box1d(point1d(mln_min(comp)), point1d(mln_max(comp)))); - // std::cout << "min : " << mln_min(comp) << std::endl; - // std::cout << "max : " << mln_max(comp) << std::endl; +// std::cout << "min : " << mln_min(comp) << std::endl; +// std::cout << "max : " << mln_max(comp) << std::endl; trace::exiting("mln::accu::stat::histo1d<V>::histo1d"); } @@ -264,14 +264,14 @@ namespace mln { trace::entering("mln::accu::stat::histo1d<V>::take"); - // Just convert a graylevel value (int_u8 like) to a position for an + // Just convert a graylevel value (int_u8 like) to a position for an // iterator on the resulting image. ++count_(point1d(t)); trace::exiting("mln::accu::stat::histo1d<V>::take"); } - + template <typename V> inline void histo1d<V>::take(const histo1d<V>& other) @@ -282,7 +282,7 @@ namespace mln trace::exiting("mln::accu::stat::histo1d<V>::take"); } - + template <typename V> inline typename histo1d<V>::result histo1d<V>::to_result() const @@ -292,7 +292,7 @@ namespace mln trace::exiting("mln::accu::stat::histo1d<V>::to_result"); return count_; } - + template <typename V> inline histo1d<V>::operator result() const @@ -301,7 +301,7 @@ namespace mln trace::exiting("mln::accu::stat::histo1d<V>::operator result"); return count_; - } + } template <typename V> inline @@ -309,7 +309,7 @@ namespace mln { trace::entering("mln::accu::stat::histo1d<V>::is_valid"); bool result = count_.is_valid(); - + trace::exiting("mln::accu::stat::histo1d<V>::is_valid"); return result; } @@ -322,7 +322,7 @@ namespace mln bool result = true; const image1d<unsigned>& res1 = histo1.to_result(); const image1d<unsigned>& res2 = histo2.to_result(); - + mln_precondition(res1.is_valid()); mln_precondition(res2.is_valid()); diff --git a/milena/sandbox/green/mln/fun/p2b/achromatic.hh b/milena/sandbox/green/mln/fun/p2b/achromatic.hh new file mode 100644 index 0000000..1f45b2d --- /dev/null +++ b/milena/sandbox/green/mln/fun/p2b/achromatic.hh @@ -0,0 +1,112 @@ +// Copyright (C) 2008, 2009 EPITA Research and Development Laboratory (LRDE) +// +// This file is part of Olena. +// +// Olena is free software: you can redistribute it and/or modify it under +// the terms of the GNU General Public License as published by the Free +// Software Foundation, version 2 of the License. +// +// Olena is distributed in the hope that it will be useful, +// but WITHOUT ANY WARRANTY; without even the implied warranty of +// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU +// General Public License for more details. +// +// You should have received a copy of the GNU General Public License +// along with Olena. If not, see <http://www.gnu.org/licenses/>. +// +// As a special exception, you may use this file as part of a free +// software project without restriction. Specifically, if other files +// instantiate templates or use macros or inline functions from this +// file, or you compile this file and link it with other files to produce +// an executable, this file does not by itself cause the resulting +// executable to be covered by the GNU General Public License. This +// exception does not however invalidate any other reasons why the +// executable file might be covered by the GNU General Public License. + +#ifndef MLN_FUN_P2B_ACHROMATIC_HH +# define MLN_FUN_P2B_ACHROMATIC_HH + +/// \file +/// +/// In the vectorial image context (as RGB, HSL, HSV), compare one component +/// to a specific value. + +# include <mln/core/alias/point2d.hh> +# include <mln/core/concept/function.hh> +# include <mln/trait/value/comp.hh> + + +namespace mln +{ + + namespace fun + { + + namespace p2b + { + /// \brief Functor that compare the i-th component of a value. + // V is for the type of the value received + // i is the ith component to select + template <typename T_rgb> + struct achromatic : public Function_v2b< achromatic<T_rgb> > + { + typedef bool result; + bool operator()(const point2d& p) const; + + achromatic(const image2d<T_rgb>& img, const float threshold); + + const float threshold_; + const image2d<T_rgb>& img_; + }; + + +# ifndef MLN_INCLUDE_ONLY + + template <typename T_rgb> + achromatic<T_rgb>::achromatic(const image2d<T_rgb>& img, + const float threshold) + : threshold_(threshold), img_(img) + { + } + + template <typename T_rgb> + bool achromatic<T_rgb>::operator()(const point2d& p) const + { + typedef typename T_rgb::red_t t_red; + typedef typename T_rgb::green_t t_green; + typedef typename T_rgb::blue_t t_blue; + + const T_rgb rgb = img_(p); + + // To obtain red between 0 and 1 + const float max_red = mln_max(t_red); + const float min_red = mln_min(t_red); + const float red = (rgb.red() - min_red)/(max_red - min_red); + + // To obtain green between 0 and 1 + const float max_green = mln_max(t_green); + const float min_green = mln_min(t_green); + const float green = (rgb.green()-min_green)/(max_green-min_green); + + // To obtain blue between 0 and 1 + const float max_blue = mln_max(t_blue); + const float min_blue = mln_min(t_blue); + const float blue = (rgb.blue()-min_blue)/(max_blue-min_blue); + + bool result = (threshold_ > math::abs(red - green) && + threshold_ > math::abs(red - blue) && + threshold_ > math::abs(green - blue)); + + return result; + } + +# endif // ! MLN_INCLUDE_ONLY + + } // end of namespace mln::fun::p2b + + } // end of namespace mln::fun + +} // end of namespace mln + + +#endif // ! MLN_FUN_P2B_ACHROMATIC_HH diff --git a/milena/sandbox/green/mln/fun/p2b/component_equals.hh b/milena/sandbox/green/mln/fun/p2b/component_equals.hh new file mode 100644 index 0000000..2a4c62c --- /dev/null +++ b/milena/sandbox/green/mln/fun/p2b/component_equals.hh @@ -0,0 +1,99 @@ +// Copyright (C) 2008, 2009 EPITA Research and Development Laboratory (LRDE) +// +// This file is part of Olena. +// +// Olena is free software: you can redistribute it and/or modify it under +// the terms of the GNU General Public License as published by the Free +// Software Foundation, version 2 of the License. +// +// Olena is distributed in the hope that it will be useful, +// but WITHOUT ANY WARRANTY; without even the implied warranty of +// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU +// General Public License for more details. +// +// You should have received a copy of the GNU General Public License +// along with Olena. If not, see <http://www.gnu.org/licenses/>. +// +// As a special exception, you may use this file as part of a free +// software project without restriction. Specifically, if other files +// instantiate templates or use macros or inline functions from this +// file, or you compile this file and link it with other files to produce +// an executable, this file does not by itself cause the resulting +// executable to be covered by the GNU General Public License. This +// exception does not however invalidate any other reasons why the +// executable file might be covered by the GNU General Public License. + +#ifndef MLN_FUN_P2B_COMPONENT_EQUALS_HH +# define MLN_FUN_P2B_COMPONENT_EQUALS_HH + +/// \file +/// +/// In the vectorial image context (as RGB, HSL, HSV), compare one component +/// to a specific value. + +# include <mln/core/alias/point2d.hh> +# include <mln/core/concept/function.hh> +# include <mln/trait/value/comp.hh> + + +namespace mln +{ + + namespace fun + { + + namespace p2b + { + + /// \brief Functor that compare the i-th component of a value. + // V is for the type of the value received + // i is the ith component to select + template <typename I, unsigned i> + struct component_equals : public Function_v2b< component_equals<I,i> > + { + typedef bool result; + bool operator()(const point2d& p) const; + + component_equals(const I& img, + const mln_trait_value_comp(mln_value(I),i)& ref); + + const mln_trait_value_comp(mln_value(I),i) _ref; + const I& _img; + }; + + +# ifndef MLN_INCLUDE_ONLY + + template <typename I, unsigned i> + inline + component_equals<I,i>:: + component_equals(const I& img, + const mln_trait_value_comp(mln_value(I),i)& ref) + : _ref(ref), _img(img) + { + } + + template <typename I, unsigned i> + inline + bool + component_equals<I,i>::operator()(const point2d& p) const + { + typedef mln_value(I) t_value; + typedef mln_trait_value_comp(t_value,i) mln_value_comp; + + t_value v = _img(p); + mln_value_comp c = trait::value::internal::comp<t_value,i>::on(v); + + return (c == _ref); + } + +# endif // ! MLN_INCLUDE_ONLY + + } // end of namespace mln::fun::p2b + + } // end of namespace mln::fun + +} // end of namespace mln + + +#endif // ! MLN_FUN_P2B_COMPONENT_EQUALS_HH diff --git a/milena/sandbox/green/mln/fun/v2v/achromatism.hh b/milena/sandbox/green/mln/fun/v2v/achromatism.hh new file mode 100644 index 0000000..72b545c --- /dev/null +++ b/milena/sandbox/green/mln/fun/v2v/achromatism.hh @@ -0,0 +1,64 @@ +// Copyright (C) 2008, 2009 EPITA Research and Development Laboratory (LRDE) +// +// This file is part of Olena. +// +// Olena is free software: you can redistribute it and/or modify it under +// the terms of the GNU General Public License as published by the Free +// Software Foundation, version 2 of the License. +// +// Olena is distributed in the hope that it will be useful, +// but WITHOUT ANY WARRANTY; without even the implied warranty of +// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU +// General Public License for more details. +// +// You should have received a copy of the GNU General Public License +// along with Olena. If not, see <http://www.gnu.org/licenses/>. +// +// As a special exception, you may use this file as part of a free +// software project without restriction. Specifically, if other files +// instantiate templates or use macros or inline functions from this +// file, or you compile this file and link it with other files to produce +// an executable, this file does not by itself cause the resulting +// executable to be covered by the GNU General Public License. This +// exception does not however invalidate any other reasons why the +// executable file might be covered by the GNU General Public License. + +#ifndef MLN_FUN_V2V_ACHROMATISM_HH +# define MLN_FUN_V2V_ACHROMATISM_HH + +# include <mln/value/rgb8.hh> + +namespace mln +{ + + namespace fun + { + + namespace v2v + { + + struct achromatism : public Function_v2v< achromatism > + { + typedef float result; + + float operator()(const value::rgb8 rgb) const; + }; + +# ifndef MLN_INCLUDE_ONLY + + float achromatism::operator()(const value::rgb8 rgb) const + { + return (math::abs(rgb.red() - rgb.green()) + + math::abs(rgb.red() - rgb.blue()) + + math::abs(rgb.green() - rgb.blue()))/3.0; + } + +# endif // !MLN_INCLUDE_ONLY + + } // end of namespace fun::v2v + + } // end of namespace fun + +} // end of namespace mln + +#endif // ! MLN_FUN_V2V_ACHROMATISM_HH diff --git a/milena/sandbox/green/mln/fun/v2v/hue_concentration.hh b/milena/sandbox/green/mln/fun/v2v/hue_concentration.hh new file mode 100644 index 0000000..84d26c8 --- /dev/null +++ b/milena/sandbox/green/mln/fun/v2v/hue_concentration.hh @@ -0,0 +1,100 @@ +// Copyright (C) 2008, 2009 EPITA Research and Development Laboratory (LRDE) +// +// This file is part of Olena. +// +// Olena is free software: you can redistribute it and/or modify it under +// the terms of the GNU General Public License as published by the Free +// Software Foundation, version 2 of the License. +// +// Olena is distributed in the hope that it will be useful, +// but WITHOUT ANY WARRANTY; without even the implied warranty of +// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU +// General Public License for more details. +// +// You should have received a copy of the GNU General Public License +// along with Olena. If not, see <http://www.gnu.org/licenses/>. +// +// As a special exception, you may use this file as part of a free +// software project without restriction. Specifically, if other files +// instantiate templates or use macros or inline functions from this +// file, or you compile this file and link it with other files to produce +// an executable, this file does not by itself cause the resulting +// executable to be covered by the GNU General Public License. This +// exception does not however invalidate any other reasons why the +// executable file might be covered by the GNU General Public License. + +#ifndef MLN_FUN_V2V_HUE_CONCENTRATION_HH +# define MLN_FUN_V2V_HUE_CONCENTRATION_HH + +# include <mln/core/image/image1d.hh> +# include <mln/math/abs.hh> +# include <mln/opt/at.hh> +# include <mln/value/hsv.hh> +# include <mln/value/rgb8.hh> + +namespace mln +{ + + namespace fun + { + + namespace v2v + { + + unsigned peak_histo(const mln::image1d<unsigned>& hue_histo); + + struct hue_concentration : public Function_v2v< hue_concentration > + { + typedef float result; + + float operator()(const float hue) const; + + hue_concentration(const mln::image1d<unsigned>& hue_histo) + { + peak = peak_histo(hue_histo); + } + + unsigned peak; + }; + + +# ifndef MLN_INCLUDE_ONLY + + + unsigned peak_histo(const mln::image1d<unsigned>& hue_histo) + { + mln_precondition(hue_histo.is_valid()); + + // Find the peak of the histogram + unsigned v_max = mln::opt::at(hue_histo, 0); + short p_max = 0; + + mln_piter_(mln::image1d<unsigned>) p(hue_histo.domain()); + + for_all(p) + { + if (v_max < hue_histo(p)) + { + v_max = hue_histo(p); + p_max = p.ind(); + } + } + + return p_max; + } + + + float hue_concentration::operator()(float hue) const + { + return mln::math::abs(peak - hue); + } + +# endif // !MLN_INCLUDE_ONLY + + } // end of namespace fun::v2v + + } // end of namespace fun + +} // end of namespace mln + +#endif // ! MLN_FUN_V2V_HUE_CONCENTRATION_HH diff --git a/milena/sandbox/green/mln/fun/v2v/rgb_to_achromatism_map.hh b/milena/sandbox/green/mln/fun/v2v/rgb_to_achromatism_map.hh new file mode 100644 index 0000000..6de63ec --- /dev/null +++ b/milena/sandbox/green/mln/fun/v2v/rgb_to_achromatism_map.hh @@ -0,0 +1,77 @@ +// Copyright (C) 2007 EPITA Research and Development Laboratory (LRDE) +// Copyright (C) 2008 EPITA Research and Development Laboratory (LRDE) +// Copyright (C) 2009 EPITA Research and Development Laboratory (LRDE) +// +// This file is part of Olena. +// +// Olena is free software: you can redistribute it and/or modify it under +// the terms of the GNU General Public License as published by the Free +// Software Foundation, version 2 of the License. +// +// Olena is distributed in the hope that it will be useful, +// but WITHOUT ANY WARRANTY; without even the implied warranty of +// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU +// General Public License for more details. +// +// You should have received a copy of the GNU General Public License +// along with Olena. If not, see <http://www.gnu.org/licenses/>. +// +// As a special exception, you may use this file as part of a free +// software project without restriction. Specifically, if other files +// instantiate templates or use macros or inline functions from this +// file, or you compile this file and link it with other files to produce +// an executable, this file does not by itself cause the resulting +// executable to be covered by the GNU General Public License. This +// exception does not however invalidate any other reasons why the +// executable file might be covered by the GNU General Public License. + +#ifndef MLN_FUN_V2V_RGB_TO_ACHROMATISM_MAP_HH +# define MLN_FUN_V2V_RGB_TO_ACHROMATISM_MAP_HH + +# include <mln/math/abs.hh> +# include <mln/math/max.hh> + +# include <mln/value/rgb.hh> + + +/// \file +/// +/// \brief Convert rgb value to achromatism map. + +namespace mln +{ + + namespace fun + { + + namespace v2v + { + + /// \brief Convert rgb value to achromatism map. + /// + /// \ingroup modfunv2v + + template <unsigned n> + struct rgb_to_achromatism_map : + Function_v2v< rgb_to_achromatism_map<n> > + { + typedef value::rgb<n> argument; + typedef value::int_u<n> result; + + result operator()(const argument& v) const + { + result max = math::max(math::max(v.red(),v.green()),v.blue()); + result min = math::min(math::min(v.red(),v.green()),v.blue()); + result ret = max - min; + + return ret; + } + }; + + } // end of namespace mln::fun::v2v + + } // end of namespace mln::fun + +} // end of namespace mln + +#endif // ! MLN_FUN_V2V_RGB_TO_ACHROMATISM_MAP_HH diff --git a/milena/sandbox/green/mln/fun/v2v/rgb_to_hsv.hh b/milena/sandbox/green/mln/fun/v2v/rgb_to_hsv.hh new file mode 100644 index 0000000..3dd8eb0 --- /dev/null +++ b/milena/sandbox/green/mln/fun/v2v/rgb_to_hsv.hh @@ -0,0 +1,149 @@ +// Copyright (C) 2008, 2009 EPITA Research and Development Laboratory (LRDE) +// +// This file is part of Olena. +// +// Olena is free software: you can redistribute it and/or modify it under +// the terms of the GNU General Public License as published by the Free +// Software Foundation, version 2 of the License. +// +// Olena is distributed in the hope that it will be useful, +// but WITHOUT ANY WARRANTY; without even the implied warranty of +// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU +// General Public License for more details. +// +// You should have received a copy of the GNU General Public License +// along with Olena. If not, see <http://www.gnu.org/licenses/>. +// +// As a special exception, you may use this file as part of a free +// software project without restriction. Specifically, if other files +// instantiate templates or use macros or inline functions from this +// file, or you compile this file and link it with other files to produce +// an executable, this file does not by itself cause the resulting +// executable to be covered by the GNU General Public License. This +// exception does not however invalidate any other reasons why the +// executable file might be covered by the GNU General Public License. + +#ifndef MLN_FUN_V2V_RGB_TO_HSV_HH +# define MLN_FUN_V2V_RGB_TO_HSV_HH + +#include <mln/math/max.hh> +#include <mln/math/min.hh> + +#include <mln/trait/promote.hh> + +#include <mln/value/hsv.hh> +#include <mln/value/rgb.hh> + +namespace mln +{ + + namespace value + { + template <typename H, typename S, typename V> class hsv_; + typedef hsv_<float, float, float> hsv_f; + typedef hsv_<double, double, double> hsv_d; + template <unsigned n> struct rgb; + } + + namespace fun + { + + namespace v2v + { + + template <typename T_hsv> + struct f_rgb_to_hsv_ : public Function_v2v< f_rgb_to_hsv_<T_hsv> > + { + typedef T_hsv result; + + + /// HSV implementation from millet.2008.phd.pdf p67 + template <typename T_rgb> + T_hsv operator()(const T_rgb& rgb) const; + + }; + + typedef f_rgb_to_hsv_<value::hsv_f> f_rgb_to_hsv_f_t; + + extern f_rgb_to_hsv_f_t f_rgb_to_hsv_f; + + +# ifndef MLN_INCLUDE_ONLY + + /// Global variables. + /// \{ + f_rgb_to_hsv_f_t f_rgb_to_hsv_f; + /// \} + + + template <typename T_hsv> + template <typename T_rgb> + inline + T_hsv + f_rgb_to_hsv_<T_hsv>::operator()(const T_rgb& rgb) const + { + typedef typename T_rgb::red_t t_red; + typedef typename T_rgb::green_t t_green; + typedef typename T_rgb::blue_t t_blue; + typedef typename T_hsv::h_type t_hue; + typedef typename T_hsv::s_type t_sat; + typedef typename T_hsv::v_type t_val; + typedef mln_trait_promote(t_hue, t_sat) t_max_hue_sat; + typedef mln_trait_promote(t_max_hue_sat, t_val) t_max_hsv; + + // To obtain red between 0 and 1 + const t_max_hsv max_red = mln_max(t_red); + const t_max_hsv min_red = mln_min(t_red); + const t_max_hsv red = (rgb.red() - min_red)/(max_red - min_red); + + // To obtain green between 0 and 1 + const t_max_hsv max_green = mln_max(t_green); + const t_max_hsv min_green = mln_min(t_green); + const t_max_hsv green =(rgb.green()-min_green)/(max_green-min_green); + + // To obtain blue between 0 and 1 + const t_max_hsv max_blue = mln_max(t_blue); + const t_max_hsv min_blue = mln_min(t_blue); + const t_max_hsv blue = (rgb.blue()-min_blue)/(max_blue-min_blue); + + const t_max_hsv max = math::max(red, math::max(green, blue)); + const t_max_hsv min = math::min(red, math::min(green, blue)); + const t_max_hsv max_minus_min = max-min; + const t_max_hsv s = 0.03; + + // Locals. + T_hsv hsv; + + // SPECIFIC CASE WHEN PIXEL IS ACHROMATIC + if (s > math::abs(red - blue) && + s > math::abs(blue - red) && + s > math::abs(red - green)) + { + hsv.val() = (red + green + blue)/3.0; + hsv.sat() = 0.0; + hsv.hue() = -1.0; + } + else + { + hsv.val() = max; + hsv.sat() = max_minus_min / max; + if (max == red) + hsv.hue() = 60 * ((green - blue) / max_minus_min); + else if (max == green) + hsv.hue() = 60 * (2 + (blue - red) / max_minus_min); + else // (max == blue) + hsv.hue() = 60 * (4 + (red - green) / max_minus_min); + } + return hsv; + } + + +# endif // !MLN_INCLUDE_ONLY + + } // end of namespace fun::v2v + + } // end of namespace fun + +} // end of namespace mln + +#endif // ! MLN_FUN_V2V_RGB_TO_HSV_HH diff --git a/milena/sandbox/green/mln/fun/v2v/rgb_to_hue_map.hh b/milena/sandbox/green/mln/fun/v2v/rgb_to_hue_map.hh new file mode 100644 index 0000000..8b228e0 --- /dev/null +++ b/milena/sandbox/green/mln/fun/v2v/rgb_to_hue_map.hh @@ -0,0 +1,96 @@ +// Copyright (C) 2007 EPITA Research and Development Laboratory (LRDE) +// Copyright (C) 2008 EPITA Research and Development Laboratory (LRDE) +// Copyright (C) 2009 EPITA Research and Development Laboratory (LRDE) +// +// This file is part of Olena. +// +// Olena is free software: you can redistribute it and/or modify it under +// the terms of the GNU General Public License as published by the Free +// Software Foundation, version 2 of the License. +// +// Olena is distributed in the hope that it will be useful, +// but WITHOUT ANY WARRANTY; without even the implied warranty of +// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU +// General Public License for more details. +// +// You should have received a copy of the GNU General Public License +// along with Olena. If not, see <http://www.gnu.org/licenses/>. +// +// As a special exception, you may use this file as part of a free +// software project without restriction. Specifically, if other files +// instantiate templates or use macros or inline functions from this +// file, or you compile this file and link it with other files to produce +// an executable, this file does not by itself cause the resulting +// executable to be covered by the GNU General Public License. This +// exception does not however invalidate any other reasons why the +// executable file might be covered by the GNU General Public License. + +#ifndef MLN_FUN_V2V_RGB_TO_HUE_MAP_HH +# define MLN_FUN_V2V_RGB_TO_HUE_MAP_HH + +# include <mln/math/abs.hh> +# include <mln/math/max.hh> + +# include <mln/value/rgb.hh> + + +/// \file +/// +/// \brief Convert rgb value to hue map. + +namespace mln +{ + + namespace fun + { + + namespace v2v + { + + /// \brief Convert rgb value to hue map. + /// + /// \ingroup modfunv2v + + template <unsigned n> + struct rgb_to_hue_map : + Function_v2v< rgb_to_hue_map<n> > + { + typedef value::rgb<n> argument; + typedef value::int_u<n> result; + + result operator()(const argument& v) const + { + const float max = math::max(math::max(v.red(), v.green()), v.blue()); + const float min = math::min(math::min(v.red(), v.green()), v.blue()); + const float diff = max - min; + float hue = 0; + + if (0 != diff) + { + if (v.red() == max) + { + hue = 60 * ((v.green() - v.blue()) / diff); + + if (0 < hue) + hue = 360.0 + hue; + } + else if (v.green() == max) + hue = 60 * (2 + (v.blue() - v.red()) / diff); + else // (v.blue() == max) + hue = 60 * (4 + (v.red() - v.green()) / diff); + } + + const result ret = (hue/360.0) * (mln_max(result) - mln_min(result)) + + mln_min(result); + + return ret; + } + }; + + } // end of namespace mln::fun::v2v + + } // end of namespace mln::fun + +} // end of namespace mln + +#endif // ! MLN_FUN_V2V_RGB_TO_HUE_MAP_HH diff --git a/milena/sandbox/green/mln/fun/v2v/rgb_to_saturation_map.hh b/milena/sandbox/green/mln/fun/v2v/rgb_to_saturation_map.hh new file mode 100644 index 0000000..a8847a0 --- /dev/null +++ b/milena/sandbox/green/mln/fun/v2v/rgb_to_saturation_map.hh @@ -0,0 +1,83 @@ +// Copyright (C) 2007 EPITA Research and Development Laboratory (LRDE) +// Copyright (C) 2008 EPITA Research and Development Laboratory (LRDE) +// Copyright (C) 2009 EPITA Research and Development Laboratory (LRDE) +// +// This file is part of Olena. +// +// Olena is free software: you can redistribute it and/or modify it under +// the terms of the GNU General Public License as published by the Free +// Software Foundation, version 2 of the License. +// +// Olena is distributed in the hope that it will be useful, +// but WITHOUT ANY WARRANTY; without even the implied warranty of +// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU +// General Public License for more details. +// +// You should have received a copy of the GNU General Public License +// along with Olena. If not, see <http://www.gnu.org/licenses/>. +// +// As a special exception, you may use this file as part of a free +// software project without restriction. Specifically, if other files +// instantiate templates or use macros or inline functions from this +// file, or you compile this file and link it with other files to produce +// an executable, this file does not by itself cause the resulting +// executable to be covered by the GNU General Public License. This +// exception does not however invalidate any other reasons why the +// executable file might be covered by the GNU General Public License. + +#ifndef MLN_FUN_V2V_RGB_TO_SATURATION_MAP_HH +# define MLN_FUN_V2V_RGB_TO_SATURATION_MAP_HH + +# include <mln/math/abs.hh> +# include <mln/math/max.hh> + +# include <mln/value/rgb.hh> + + +/// \file +/// +/// \brief Convert rgb value to saturation map. + +namespace mln +{ + + namespace fun + { + + namespace v2v + { + + /// \brief Convert rgb value to saturation map. + /// + /// \ingroup modfunv2v + + template <unsigned n> + struct rgb_to_saturation_map : + Function_v2v< rgb_to_saturation_map<n> > + { + typedef value::rgb<n> argument; + typedef value::int_u<n> result; + + result operator()(const argument& v) const + { + const float max = math::max(math::max(v.red(), v.green()), v.blue()); + const float min = math::min(math::min(v.red(), v.green()), v.blue()); + float sat = 0.0; + + if (0 != max) + sat = (1 - (float)min/max); + + const result ret = sat * (mln_max(result) - mln_min(result)) + + mln_min(result); + + return ret; + } + }; + + } // end of namespace mln::fun::v2v + + } // end of namespace mln::fun + +} // end of namespace mln + +#endif // ! MLN_FUN_V2V_RGB_TO_SATURATION_MAP_HH diff --git a/milena/sandbox/green/mln/fun/v2v/rgb_to_value_map.hh b/milena/sandbox/green/mln/fun/v2v/rgb_to_value_map.hh new file mode 100644 index 0000000..12ac1db --- /dev/null +++ b/milena/sandbox/green/mln/fun/v2v/rgb_to_value_map.hh @@ -0,0 +1,75 @@ +// Copyright (C) 2007 EPITA Research and Development Laboratory (LRDE) +// Copyright (C) 2008 EPITA Research and Development Laboratory (LRDE) +// Copyright (C) 2009 EPITA Research and Development Laboratory (LRDE) +// +// This file is part of Olena. +// +// Olena is free software: you can redistribute it and/or modify it under +// the terms of the GNU General Public License as published by the Free +// Software Foundation, version 2 of the License. +// +// Olena is distributed in the hope that it will be useful, +// but WITHOUT ANY WARRANTY; without even the implied warranty of +// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU +// General Public License for more details. +// +// You should have received a copy of the GNU General Public License +// along with Olena. If not, see <http://www.gnu.org/licenses/>. +// +// As a special exception, you may use this file as part of a free +// software project without restriction. Specifically, if other files +// instantiate templates or use macros or inline functions from this +// file, or you compile this file and link it with other files to produce +// an executable, this file does not by itself cause the resulting +// executable to be covered by the GNU General Public License. This +// exception does not however invalidate any other reasons why the +// executable file might be covered by the GNU General Public License. + +#ifndef MLN_FUN_V2V_RGB_TO_VALUE_MAP_HH +# define MLN_FUN_V2V_RGB_TO_VALUE_MAP_HH + +# include <mln/math/abs.hh> +# include <mln/math/max.hh> + +# include <mln/value/rgb.hh> + + +/// \file +/// +/// \brief Convert rgb value to value map. + +namespace mln +{ + + namespace fun + { + + namespace v2v + { + + /// \brief Convert rgb value to value map. + /// + /// \ingroup modfunv2v + + template <unsigned n> + struct rgb_to_value_map : + Function_v2v< rgb_to_value_map<n> > + { + typedef value::rgb<n> argument; + typedef value::int_u<n> result; + + result operator()(const argument& v) const + { + const result ret = math::max(math::max(v.red(), v.green()), v.blue()); + + return ret; + } + }; + + } // end of namespace mln::fun::v2v + + } // end of namespace mln::fun + +} // end of namespace mln + +#endif // ! MLN_FUN_V2V_RGB_TO_VALUE_MAP_HH diff --git a/milena/sandbox/green/mln/img_path.hh b/milena/sandbox/green/mln/img_path.hh index 7368c22..d205e1f 100644 --- a/milena/sandbox/green/mln/img_path.hh +++ b/milena/sandbox/green/mln/img_path.hh @@ -28,41 +28,212 @@ #ifndef MLN_IMG_PATH_HH # define MLN_IMG_PATH_HH -# define IMG_PATH "/home/green/svn/oln/trunk/milena/sandbox/green/img" -# define RESULT_PATH "/home/green/svn/oln/trunk/milena/sandbox/green/result" +# define IMG_PATH "/home/green/git/img" +# define RET_PATH "/home/green/git/result" # define INIM_IMG_PATH IMG_PATH"/inim" -# define INIM_FG_BG_IMG_PATH INIM_IMG_PATH"/fg_bg" +# define INIM_BG_IMG_PATH INIM_IMG_PATH"/bg" +# define INIM_FG_IMG_PATH INIM_IMG_PATH"/fg" # define INIM_IN_IMG_PATH INIM_IMG_PATH"/in" # define OLENA_IMG_PATH IMG_PATH"/olena" -# define SCRIBO_IMG_PATH IMG_PATH"/scribo" -# define SCRIBO_JPG_IMG_PATH SCRIBO_IMG_PATH"/jpg_50p" -# define SCRIBO_PGM_IMG_PATH SCRIBO_IMG_PATH"/pgm_50p" -# define SCRIBO_PPM_IMG_PATH SCRIBO_IMG_PATH"/ppm_50p" - -# define ANNOTATING_IMG_PATH IMG_PATH"/annotating" -# define ANNOTATING_BILL_IMG_PATH ANNOTATING_IMG_PATH"/bill" -# define ANNOTATING_FAX_IMG_PATH ANNOTATING_IMG_PATH"/fax" -# define ANNOTATING_HANDWRITTEN_IMG_PATH ANNOTATING_IMG_PATH"/handwritten" -# define ANNOTATING_LOGO_IMG_PATH ANNOTATING_IMG_PATH"/logo" -# define ANNOTATING_MAP_IMG_PATH ANNOTATING_IMG_PATH"/map" -# define ANNOTATING_SCREENSHOT_IMG_PATH ANNOTATING_IMG_PATH"/screenshot" -# define ANNOTATING_SLIDE_IMG_PATH ANNOTATING_IMG_PATH"/slide" -# define ANNOTATING_TYPED_IMG_PATH ANNOTATING_IMG_PATH"/typed" -# define ANNOTATING_PHOTO_IMG_PATH ANNOTATING_IMG_PATH"/photo" +# define ICDAR_IMG_PATH IMG_PATH"/icdar" +# define ICDAR_100P_IMG_PATH ICDAR_IMG_PATH"/100p" +# define ICDAR_100P_PPM_IMG_PATH ICDAR_100P_IMG_PATH"/ppm" +# define ICDAR_100P_PGM_IMG_PATH ICDAR_100P_IMG_PATH"/pgm" +# define ICDAR_100P_PBM_IMG_PATH ICDAR_100P_IMG_PATH"/pbm" +# define ICDAR_100P_THICK_IMG_PATH ICDAR_100P_IMG_PATH"/gradient_thick" +# define ICDAR_100P_THIN_IMG_PATH ICDAR_100P_IMG_PATH"/gradient_thin" + +# define ICDAR_50P_IMG_PATH ICDAR_IMG_PATH"/50p" +# define ICDAR_50P_PPM_IMG_PATH ICDAR_50P_IMG_PATH"/ppm" +# define ICDAR_50P_PGM_IMG_PATH ICDAR_50P_IMG_PATH"/pgm" +# define ICDAR_50P_PBM_IMG_PATH ICDAR_50P_IMG_PATH"/pbm" + +# define ICDAR_20P_IMG_PATH ICDAR_IMG_PATH"/20p" +# define ICDAR_20P_TEXT_ONLY_IMG_PATH ICDAR_20P_IMG_PATH"/text-only" +# define ICDAR_20P_TEXT_COLOR_IMG_PATH ICDAR_20P_IMG_PATH"/text-color" +# define ICDAR_20P_TEXT_PHOTO_IMG_PATH ICDAR_20P_IMG_PATH"/text-photo" +# define ICDAR_20P_GMP30_IMG_PATH ICDAR_20P_IMG_PATH"/gimp-pal-30" +# define ICDAR_20P_MGK30_IMG_PATH ICDAR_20P_IMG_PATH"/magick-pal-30" +# define ICDAR_20P_GMP20_IMG_PATH ICDAR_20P_IMG_PATH"/gimp-pal-20" +# define ICDAR_20P_MGK20_IMG_PATH ICDAR_20P_IMG_PATH"/magick-pal-20" +# define ICDAR_20P_GMP10_IMG_PATH ICDAR_20P_IMG_PATH"/gimp-pal-10" +# define ICDAR_20P_MGK10_IMG_PATH ICDAR_20P_IMG_PATH"/magick-pal-10" +# define ICDAR_20P_INPUT_IMG_PATH ICDAR_20P_IMG_PATH"/ppm" +# define ICDAR_20P_CROP_IMG_PATH ICDAR_20P_IMG_PATH"/crop" +# define ICDAR_20P_PGM_IMG_PATH ICDAR_20P_IMG_PATH"/pgm" +# define ICDAR_20P_PPM_IMG_PATH ICDAR_20P_IMG_PATH"/ppm" +# define ICDAR_20P_PBM_IMG_PATH ICDAR_20P_IMG_PATH"/pbm" + +# define AFP_IMG_PATH IMG_PATH"/afp" +# define AFP_GMP30_IMG_PATH AFP_IMG_PATH"/gimp-pal-30" +# define AFP_GMP20_IMG_PATH AFP_IMG_PATH"/gimp-pal-20" +# define AFP_GMP10_IMG_PATH AFP_IMG_PATH"/gimp-pal-10" +# define AFP_MGK30_IMG_PATH AFP_IMG_PATH"/magick-pal-30" +# define AFP_MGK20_IMG_PATH AFP_IMG_PATH"/magick-pal-20" +# define AFP_MGK10_IMG_PATH AFP_IMG_PATH"/magick-pal-10" +# define AFP_INPUT_IMG_PATH AFP_IMG_PATH"/ppm" +# define AFP_PPM_IMG_PATH AFP_IMG_PATH"/ppm" +# define AFP_JPG_IMG_PATH AFP_IMG_PATH"/jpg" + +# define ANNOTATING_1_IMG_PATH IMG_PATH"/annotating-1" +# define ANNOTATING_1_BILL_IMG_PATH ANNOTATING_1_IMG_PATH"/bill" +# define ANNOTATING_1_FAX_IMG_PATH ANNOTATING_1_IMG_PATH"/fax" +# define ANNOTATING_1_HANDWRITTEN_IMG_PATH ANNOTATING_1_IMG_PATH"/handwritten" +# define ANNOTATING_1_LOGO_IMG_PATH ANNOTATING_1_IMG_PATH"/logo" +# define ANNOTATING_1_MAP_IMG_PATH ANNOTATING_1_IMG_PATH"/map" +# define ANNOTATING_1_SCREENSHOT_IMG_PATH ANNOTATING_1_IMG_PATH"/screenshot" +# define ANNOTATING_1_SLIDE_IMG_PATH ANNOTATING_1_IMG_PATH"/slide" +# define ANNOTATING_1_TYPED_IMG_PATH ANNOTATING_1_IMG_PATH"/typed" +# define ANNOTATING_1_PHOTO_IMG_PATH ANNOTATING_1_IMG_PATH"/photo" + +# define ANNOTATING_2_IMG_PATH IMG_PATH"/annotating-2" +# define ANNOTATING_2_BILL_IMG_PATH ANNOTATING_2_IMG_PATH"/bill" +# define ANNOTATING_2_FAX_IMG_PATH ANNOTATING_2_IMG_PATH"/fax" +# define ANNOTATING_2_HANDWRITTEN_IMG_PATH ANNOTATING_2_IMG_PATH"/handwritten" +# define ANNOTATING_2_LOGO_IMG_PATH ANNOTATING_2_IMG_PATH"/logo" +# define ANNOTATING_2_MAP_IMG_PATH ANNOTATING_2_IMG_PATH"/map" +# define ANNOTATING_2_SCREENSHOT_IMG_PATH ANNOTATING_2_IMG_PATH"/screenshot" +# define ANNOTATING_2_SLIDE_IMG_PATH ANNOTATING_2_IMG_PATH"/slide" +# define ANNOTATING_2_TYPED_IMG_PATH ANNOTATING_2_IMG_PATH"/typed" +# define ANNOTATING_2_PHOTO_IMG_PATH ANNOTATING_2_IMG_PATH"/photo" // result directories -# define RESULT_ANNOTATING_PATH RESULT_PATH"/annotating" -# define RESULT_ANNOTATING_BILL_PATH RESULT_ANNOTATING_PATH"/bill" -# define RESULT_ANNOTATING_FAX_PATH RESULT_ANNOTATING_PATH"/fax" -# define RESULT_ANNOTATING_HANDWRITTEN_PATH RESULT_ANNOTATING_PATH"/handwritten" -# define RESULT_ANNOTATING_LOGO_PATH RESULT_ANNOTATING_PATH"/logo" -# define RESULT_ANNOTATING_MAP_PATH RESULT_ANNOTATING_PATH"/map" -# define RESULT_ANNOTATING_SCREENSHOT_PATH RESULT_ANNOTATING_PATH"/screenshot" -# define RESULT_ANNOTATING_SLIDE_PATH RESULT_ANNOTATING_PATH"/slide" -# define RESULT_ANNOTATING_TYPED_PATH RESULT_ANNOTATING_PATH"/typed" -# define RESULT_ANNOTATING_PHOTO_PATH RESULT_ANNOTATING_PATH"/photo" +# define ANNOTATING_RET_PATH RET_PATH"/annotating" + +# define ANNOTATING_ICDAR_RET_PATH ANNOTATING_RET_PATH"/icdar" + +# define ANNOTATING_ICDAR_INPUT_RET_PATH ANNOTATING_ICDAR_RET_PATH"/input" +# define ANNOTATING_ICDAR_H_INPUT_RET_PATH ANNOTATING_ICDAR_INPUT_RET_PATH"/h" +# define ANNOTATING_ICDAR_S_INPUT_RET_PATH ANNOTATING_ICDAR_INPUT_RET_PATH"/s" +# define ANNOTATING_ICDAR_V_INPUT_RET_PATH ANNOTATING_ICDAR_INPUT_RET_PATH"/v" +# define ANNOTATING_ICDAR_R_INPUT_RET_PATH ANNOTATING_ICDAR_INPUT_RET_PATH"/r" +# define ANNOTATING_ICDAR_G_INPUT_RET_PATH ANNOTATING_ICDAR_INPUT_RET_PATH"/g" +# define ANNOTATING_ICDAR_B_INPUT_RET_PATH ANNOTATING_ICDAR_INPUT_RET_PATH"/b" + +# define ANNOTATING_ICDAR_GMP30_RET_PATH ANNOTATING_ICDAR_RET_PATH"/gimp-pal-30" +# define ANNOTATING_ICDAR_H_GMP30_RET_PATH ANNOTATING_ICDAR_GMP30_RET_PATH"/h" +# define ANNOTATING_ICDAR_S_GMP30_RET_PATH ANNOTATING_ICDAR_GMP30_RET_PATH"/s" +# define ANNOTATING_ICDAR_V_GMP30_RET_PATH ANNOTATING_ICDAR_GMP30_RET_PATH"/v" +# define ANNOTATING_ICDAR_R_GMP30_RET_PATH ANNOTATING_ICDAR_GMP30_RET_PATH"/r" +# define ANNOTATING_ICDAR_G_GMP30_RET_PATH ANNOTATING_ICDAR_GMP30_RET_PATH"/g" +# define ANNOTATING_ICDAR_B_GMP30_RET_PATH ANNOTATING_ICDAR_GMP30_RET_PATH"/b" + +# define ANNOTATING_ICDAR_GMP20_RET_PATH ANNOTATING_ICDAR_RET_PATH"/gimp-pal-20" +# define ANNOTATING_ICDAR_H_GMP20_RET_PATH ANNOTATING_ICDAR_GMP20_RET_PATH"/h" +# define ANNOTATING_ICDAR_S_GMP20_RET_PATH ANNOTATING_ICDAR_GMP20_RET_PATH"/s" +# define ANNOTATING_ICDAR_V_GMP20_RET_PATH ANNOTATING_ICDAR_GMP20_RET_PATH"/v" +# define ANNOTATING_ICDAR_R_GMP20_RET_PATH ANNOTATING_ICDAR_GMP20_RET_PATH"/r" +# define ANNOTATING_ICDAR_G_GMP20_RET_PATH ANNOTATING_ICDAR_GMP20_RET_PATH"/g" +# define ANNOTATING_ICDAR_B_GMP20_RET_PATH ANNOTATING_ICDAR_GMP20_RET_PATH"/b" + +# define ANNOTATING_ICDAR_GMP10_RET_PATH ANNOTATING_ICDAR_RET_PATH"/gimp-pal-10" +# define ANNOTATING_ICDAR_H_GMP10_RET_PATH ANNOTATING_ICDAR_GMP10_RET_PATH"/h" +# define ANNOTATING_ICDAR_S_GMP10_RET_PATH ANNOTATING_ICDAR_GMP10_RET_PATH"/s" +# define ANNOTATING_ICDAR_V_GMP10_RET_PATH ANNOTATING_ICDAR_GMP10_RET_PATH"/v" +# define ANNOTATING_ICDAR_R_GMP10_RET_PATH ANNOTATING_ICDAR_GMP10_RET_PATH"/r" +# define ANNOTATING_ICDAR_G_GMP10_RET_PATH ANNOTATING_ICDAR_GMP10_RET_PATH"/g" +# define ANNOTATING_ICDAR_B_GMP10_RET_PATH ANNOTATING_ICDAR_GMP10_RET_PATH"/b" + +# define ANNOTATING_ICDAR_MGK30_RET_PATH ANNOTATING_ICDAR_RET_PATH"/magick-pal-30" +# define ANNOTATING_ICDAR_H_MGK30_RET_PATH ANNOTATING_ICDAR_MGK30_RET_PATH"/h" +# define ANNOTATING_ICDAR_S_MGK30_RET_PATH ANNOTATING_ICDAR_MGK30_RET_PATH"/s" +# define ANNOTATING_ICDAR_V_MGK30_RET_PATH ANNOTATING_ICDAR_MGK30_RET_PATH"/v" +# define ANNOTATING_ICDAR_R_MGK30_RET_PATH ANNOTATING_ICDAR_MGK30_RET_PATH"/r" +# define ANNOTATING_ICDAR_G_MGK30_RET_PATH ANNOTATING_ICDAR_MGK30_RET_PATH"/g" +# define ANNOTATING_ICDAR_B_MGK30_RET_PATH ANNOTATING_ICDAR_MGK30_RET_PATH"/b" + +# define ANNOTATING_ICDAR_MGK20_RET_PATH ANNOTATING_ICDAR_RET_PATH"/magick-pal-20" +# define ANNOTATING_ICDAR_H_MGK20_RET_PATH ANNOTATING_ICDAR_MGK20_RET_PATH"/h" +# define ANNOTATING_ICDAR_S_MGK20_RET_PATH ANNOTATING_ICDAR_MGK20_RET_PATH"/s" +# define ANNOTATING_ICDAR_V_MGK20_RET_PATH ANNOTATING_ICDAR_MGK20_RET_PATH"/v" +# define ANNOTATING_ICDAR_R_MGK20_RET_PATH ANNOTATING_ICDAR_MGK20_RET_PATH"/r" +# define ANNOTATING_ICDAR_G_MGK20_RET_PATH ANNOTATING_ICDAR_MGK20_RET_PATH"/g" +# define ANNOTATING_ICDAR_B_MGK20_RET_PATH ANNOTATING_ICDAR_MGK20_RET_PATH"/b" + +# define ANNOTATING_ICDAR_MGK10_RET_PATH ANNOTATING_ICDAR_RET_PATH"/magick-pal-10" +# define ANNOTATING_ICDAR_H_MGK10_RET_PATH ANNOTATING_ICDAR_MGK10_RET_PATH"/h" +# define ANNOTATING_ICDAR_S_MGK10_RET_PATH ANNOTATING_ICDAR_MGK10_RET_PATH"/s" +# define ANNOTATING_ICDAR_V_MGK10_RET_PATH ANNOTATING_ICDAR_MGK10_RET_PATH"/v" +# define ANNOTATING_ICDAR_R_MGK10_RET_PATH ANNOTATING_ICDAR_MGK10_RET_PATH"/r" +# define ANNOTATING_ICDAR_G_MGK10_RET_PATH ANNOTATING_ICDAR_MGK10_RET_PATH"/g" +# define ANNOTATING_ICDAR_B_MGK10_RET_PATH ANNOTATING_ICDAR_MGK10_RET_PATH"/b" + + + + +# define ANNOTATING_AFP_RET_PATH ANNOTATING_RET_PATH"/afp" + +# define ANNOTATING_AFP_INPUT_RET_PATH ANNOTATING_AFP_RET_PATH"/input" +# define ANNOTATING_AFP_H_INPUT_RET_PATH ANNOTATING_AFP_INPUT_RET_PATH"/h" +# define ANNOTATING_AFP_S_INPUT_RET_PATH ANNOTATING_AFP_INPUT_RET_PATH"/s" +# define ANNOTATING_AFP_V_INPUT_RET_PATH ANNOTATING_AFP_INPUT_RET_PATH"/v" +# define ANNOTATING_AFP_R_INPUT_RET_PATH ANNOTATING_AFP_INPUT_RET_PATH"/r" +# define ANNOTATING_AFP_G_INPUT_RET_PATH ANNOTATING_AFP_INPUT_RET_PATH"/g" +# define ANNOTATING_AFP_B_INPUT_RET_PATH ANNOTATING_AFP_INPUT_RET_PATH"/b" + +# define ANNOTATING_AFP_GMP30_RET_PATH ANNOTATING_AFP_RET_PATH"/gimp-pal-30" +# define ANNOTATING_AFP_H_GMP30_RET_PATH ANNOTATING_AFP_GMP30_RET_PATH"/h" +# define ANNOTATING_AFP_S_GMP30_RET_PATH ANNOTATING_AFP_GMP30_RET_PATH"/s" +# define ANNOTATING_AFP_V_GMP30_RET_PATH ANNOTATING_AFP_GMP30_RET_PATH"/v" +# define ANNOTATING_AFP_R_GMP30_RET_PATH ANNOTATING_AFP_GMP30_RET_PATH"/r" +# define ANNOTATING_AFP_G_GMP30_RET_PATH ANNOTATING_AFP_GMP30_RET_PATH"/g" +# define ANNOTATING_AFP_B_GMP30_RET_PATH ANNOTATING_AFP_GMP30_RET_PATH"/b" + +# define ANNOTATING_AFP_GMP20_RET_PATH ANNOTATING_AFP_RET_PATH"/gimp-pal-20" +# define ANNOTATING_AFP_H_GMP20_RET_PATH ANNOTATING_AFP_GMP20_RET_PATH"/h" +# define ANNOTATING_AFP_S_GMP20_RET_PATH ANNOTATING_AFP_GMP20_RET_PATH"/s" +# define ANNOTATING_AFP_V_GMP20_RET_PATH ANNOTATING_AFP_GMP20_RET_PATH"/v" +# define ANNOTATING_AFP_R_GMP20_RET_PATH ANNOTATING_AFP_GMP20_RET_PATH"/r" +# define ANNOTATING_AFP_G_GMP20_RET_PATH ANNOTATING_AFP_GMP20_RET_PATH"/g" +# define ANNOTATING_AFP_B_GMP20_RET_PATH ANNOTATING_AFP_GMP20_RET_PATH"/b" + +# define ANNOTATING_AFP_GMP10_RET_PATH ANNOTATING_AFP_RET_PATH"/gimp-pal-10" +# define ANNOTATING_AFP_H_GMP10_RET_PATH ANNOTATING_AFP_GMP10_RET_PATH"/h" +# define ANNOTATING_AFP_S_GMP10_RET_PATH ANNOTATING_AFP_GMP10_RET_PATH"/s" +# define ANNOTATING_AFP_V_GMP10_RET_PATH ANNOTATING_AFP_GMP10_RET_PATH"/v" +# define ANNOTATING_AFP_R_GMP10_RET_PATH ANNOTATING_AFP_GMP10_RET_PATH"/r" +# define ANNOTATING_AFP_G_GMP10_RET_PATH ANNOTATING_AFP_GMP10_RET_PATH"/g" +# define ANNOTATING_AFP_B_GMP10_RET_PATH ANNOTATING_AFP_GMP10_RET_PATH"/b" + +# define ANNOTATING_AFP_MGK30_RET_PATH ANNOTATING_AFP_RET_PATH"/magick-pal-30" +# define ANNOTATING_AFP_H_MGK30_RET_PATH ANNOTATING_AFP_MGK30_RET_PATH"/h" +# define ANNOTATING_AFP_S_MGK30_RET_PATH ANNOTATING_AFP_MGK30_RET_PATH"/s" +# define ANNOTATING_AFP_V_MGK30_RET_PATH ANNOTATING_AFP_MGK30_RET_PATH"/v" +# define ANNOTATING_AFP_R_MGK30_RET_PATH ANNOTATING_AFP_MGK30_RET_PATH"/r" +# define ANNOTATING_AFP_G_MGK30_RET_PATH ANNOTATING_AFP_MGK30_RET_PATH"/g" +# define ANNOTATING_AFP_B_MGK30_RET_PATH ANNOTATING_AFP_MGK30_RET_PATH"/b" + +# define ANNOTATING_AFP_MGK20_RET_PATH ANNOTATING_AFP_RET_PATH"/magick-pal-20" +# define ANNOTATING_AFP_H_MGK20_RET_PATH ANNOTATING_AFP_MGK20_RET_PATH"/h" +# define ANNOTATING_AFP_S_MGK20_RET_PATH ANNOTATING_AFP_MGK20_RET_PATH"/s" +# define ANNOTATING_AFP_V_MGK20_RET_PATH ANNOTATING_AFP_MGK20_RET_PATH"/v" +# define ANNOTATING_AFP_R_MGK20_RET_PATH ANNOTATING_AFP_MGK20_RET_PATH"/r" +# define ANNOTATING_AFP_G_MGK20_RET_PATH ANNOTATING_AFP_MGK20_RET_PATH"/g" +# define ANNOTATING_AFP_B_MGK20_RET_PATH ANNOTATING_AFP_MGK20_RET_PATH"/b" + +# define ANNOTATING_AFP_MGK10_RET_PATH ANNOTATING_AFP_RET_PATH"/magick-pal-10" +# define ANNOTATING_AFP_H_MGK10_RET_PATH ANNOTATING_AFP_MGK10_RET_PATH"/h" +# define ANNOTATING_AFP_S_MGK10_RET_PATH ANNOTATING_AFP_MGK10_RET_PATH"/s" +# define ANNOTATING_AFP_V_MGK10_RET_PATH ANNOTATING_AFP_MGK10_RET_PATH"/v" +# define ANNOTATING_AFP_R_MGK10_RET_PATH ANNOTATING_AFP_MGK10_RET_PATH"/r" +# define ANNOTATING_AFP_G_MGK10_RET_PATH ANNOTATING_AFP_MGK10_RET_PATH"/g" +# define ANNOTATING_AFP_B_MGK10_RET_PATH ANNOTATING_AFP_MGK10_RET_PATH"/b" + + +# define ANNOTATING_BILL_RET_PATH ANNOTATING_RET_PATH"/bill" +# define ANNOTATING_FAX_RET_PATH ANNOTATING_RET_PATH"/fax" +# define ANNOTATING_HANDWRITTEN_RET_PATH ANNOTATING_RET_PATH"/handwritten" +# define ANNOTATING_LOGO_RET_PATH ANNOTATING_RET_PATH"/logo" +# define ANNOTATING_MAP_RET_PATH ANNOTATING_RET_PATH"/map" +# define ANNOTATING_SCREENSHOT_RET_PATH ANNOTATING_RET_PATH"/screenshot" +# define ANNOTATING_SLIDE_RET_PATH ANNOTATING_RET_PATH"/slide" +# define ANNOTATING_TYPED_RET_PATH ANNOTATING_RET_PATH"/typed" +# define ANNOTATING_PHOTO_RET_PATH ANNOTATING_RET_PATH"/photo" + +# define ANNOTATING_ICDAR_ACHROMATISM_RET_PATH ANNOTATING_ICDAR_RET_PATH"/achromatism" + #endif // ! MLN_IMG_PATH_HH diff --git a/milena/sandbox/green/mln/math/ceil.hh b/milena/sandbox/green/mln/math/ceil.hh new file mode 100644 index 0000000..6fc08c8 --- /dev/null +++ b/milena/sandbox/green/mln/math/ceil.hh @@ -0,0 +1,64 @@ +// Copyright (C) 2007, 2008, 2009, 2010 +// EPITA Research and Development Laboratory (LRDE) +// +// This file is part of Olena. +// +// Olena is free software: you can redistribute it and/or modify it under +// the terms of the GNU General Public License as published by the Free +// Software Foundation, version 2 of the License. +// +// Olena is distributed in the hope that it will be useful, +// but WITHOUT ANY WARRANTY; without even the implied warranty of +// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU +// General Public License for more details. +// +// You should have received a copy of the GNU General Public License +// along with Olena. If not, see <http://www.gnu.org/licenses/>. +// +// As a special exception, you may use this file as part of a free +// software project without restriction. Specifically, if other files +// instantiate templates or use macros or inline functions from this +// file, or you compile this file and link it with other files to produce +// an executable, this file does not by itself cause the resulting +// executable to be covered by the GNU General Public License. This +// exception does not however invalidate any other reasons why the +// executable file might be covered by the GNU General Public License. + +#ifndef MLN_MATH_CEIL_HH +# define MLN_MATH_CEIL_HH + +/*! \file + * + * \brief Define the ceil (ceil) routine. + */ + +# include <cmath> + + +namespace mln +{ + + namespace math + { + + template <typename T> + T ceil(const T& v); + + +# ifndef MLN_INCLUDE_ONLY + + template <typename T> + inline + T ceil(const T& v) + { + return std::ceil(v); + } + +# endif // ! MLN_INCLUDE_ONLY + + } // end of namespace mln::math + +} // end of namespace mln + + +#endif // ! MLN_MATH_FLOOR_HH diff --git a/milena/sandbox/green/mln/math/floor.hh b/milena/sandbox/green/mln/math/floor.hh new file mode 100644 index 0000000..97e63bd --- /dev/null +++ b/milena/sandbox/green/mln/math/floor.hh @@ -0,0 +1,64 @@ +// Copyright (C) 2007, 2008, 2009, 2010 +// EPITA Research and Development Laboratory (LRDE) +// +// This file is part of Olena. +// +// Olena is free software: you can redistribute it and/or modify it under +// the terms of the GNU General Public License as published by the Free +// Software Foundation, version 2 of the License. +// +// Olena is distributed in the hope that it will be useful, +// but WITHOUT ANY WARRANTY; without even the implied warranty of +// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU +// General Public License for more details. +// +// You should have received a copy of the GNU General Public License +// along with Olena. If not, see <http://www.gnu.org/licenses/>. +// +// As a special exception, you may use this file as part of a free +// software project without restriction. Specifically, if other files +// instantiate templates or use macros or inline functions from this +// file, or you compile this file and link it with other files to produce +// an executable, this file does not by itself cause the resulting +// executable to be covered by the GNU General Public License. This +// exception does not however invalidate any other reasons why the +// executable file might be covered by the GNU General Public License. + +#ifndef MLN_MATH_FLOOR_HH +# define MLN_MATH_FLOOR_HH + +/*! \file + * + * \brief Define the floor (floor) routine. + */ + +# include <cmath> + + +namespace mln +{ + + namespace math + { + + template <typename T> + T floor(const T& v); + + +# ifndef MLN_INCLUDE_ONLY + + template <typename T> + inline + T floor(const T& v) + { + return std::floor(v); + } + +# endif // ! MLN_INCLUDE_ONLY + + } // end of namespace mln::math + +} // end of namespace mln + + +#endif // ! MLN_MATH_FLOOR_HH diff --git a/milena/sandbox/green/mln/value/hsv.hh b/milena/sandbox/green/mln/value/hsv.hh new file mode 100644 index 0000000..69948d9 --- /dev/null +++ b/milena/sandbox/green/mln/value/hsv.hh @@ -0,0 +1,424 @@ +// Copyright (C) 2008, 2009 EPITA Research and Development Laboratory (LRDE) +// +// This file is part of Olena. +// +// Olena is free software: you can redistribute it and/or modify it under +// the terms of the GNU General Public License as published by the Free +// Software Foundation, version 2 of the License. +// +// Olena is distributed in the hope that it will be useful, +// but WITHOUT ANY WARRANTY; without even the implied warranty of +// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU +// General Public License for more details. +// +// You should have received a copy of the GNU General Public License +// along with Olena. If not, see <http://www.gnu.org/licenses/>. +// +// As a special exception, you may use this file as part of a free +// software project without restriction. Specifically, if other files +// instantiate templates or use macros or inline functions from this +// file, or you compile this file and link it with other files to produce +// an executable, this file does not by itself cause the resulting +// executable to be covered by the GNU General Public License. This +// exception does not however invalidate any other reasons why the +// executable file might be covered by the GNU General Public License. + +#ifndef MLN_VALUE_HSV_HH +# define MLN_VALUE_HSV_HH + +#include <mln/value/ops.hh> + +#include <mln/value/concept/vectorial.hh> +#include <mln/value/int_u.hh> +// #include <mln/algebra/vec.hh> + +// Used in from_to +// #include <mln/fun/v2v/rgb_to_hsv.hh> + + +namespace mln +{ + + // Forward declarations. + namespace value + { + + template <typename H, typename S, typename V> + class hsv_; + + } + + +/* + namespace convert + { + + namespace over_load + { + + // rgb to hsv_ + void + from_to_(const value::rgb<16>& from, value::hsv_<float,float,float>& to); + + // rgb to hsv_ + void + from_to_(const value::rgb<8>& from, value::hsv_<float,float,float>& to); + + } // end of namespace mln::convert::over_load + + } // end of namespace mln::convert +*/ + + + namespace trait + { + + template <typename H, typename S, typename V> + struct set_precise_binary_< op::plus, mln::value::hsv_<H,S,V>, + mln::value::hsv_<H,S,V> > + { + typedef mln::value::hsv_<H,S,V> ret; + }; + + template <typename H, typename S, typename V> + struct set_precise_binary_< op::minus, mln::value::hsv_<H,S,V>, + mln::value::hsv_<H,S,V> > + { + typedef mln::value::hsv_<H,S,V> ret; + }; + + template <typename H, typename S, typename V, typename S2> + struct set_precise_binary_< op::times, mln::value::hsv_<H,S,V>, + mln::value::scalar_<S2> > + { + typedef mln::value::hsv_<H,S,V> ret; + }; + + template <typename H, typename S, typename V, typename S2> + struct set_precise_binary_< op::div, mln::value::hsv_<H,S,V>, + mln::value::scalar_<S2> > + { + typedef mln::value::hsv_<H,S,V> ret; + }; + + + // FIXME : Is there any way more generic? a way to factor + // set_precise_binary_< op::div, mln::value::hsv_<H,S,V>, mln::value::scalar_<S> > + // and + // set_precise_binary_< op::div, mln::value::hsv_<H,S,V>, mln::value::int_u<m> > + // as for op::times. + + template <typename H, typename S, typename V, unsigned m> + struct set_precise_binary_< op::times, mln::value::hsv_<H,S,V>, + mln::value::int_u<m> > + { + typedef mln::value::hsv_<H,S,V> ret; + }; + + template <typename H, typename S, typename V, unsigned m> + struct set_precise_binary_< op::div, mln::value::hsv_<H,S,V>, + mln::value::int_u<m> > + { + typedef mln::value::hsv_<H,S,V> ret; + }; + + template <typename H, typename S, typename V> + struct value_< mln::value::hsv_<H,S,V> > + { + enum { + dim = 3, + nbits = (sizeof (H) + sizeof (S) + sizeof (V)) * 8, + card = mln_value_card_from_(nbits) + }; + + typedef trait::value::nature::vectorial nature; + typedef trait::value::kind::color kind; + typedef mln_value_quant_from_(card) quant; + + typedef void comp; + typedef H comp_0; + typedef S comp_1; + typedef V comp_2; + + template <typename VAL> + static comp_0 get_comp_0(const VAL& v) { return v.hue(); } + + template <typename VAL> + static comp_1 get_comp_1(const VAL& v) { return v.sat(); } + + template <typename VAL> + static comp_2 get_comp_2(const VAL& v) { return v.val(); } + + typedef mln::value::hsv_<H,S,V> sum; + }; + + } // end of namespace trait + + + namespace value + { + + template <typename E> + struct HSV : Object<E> + { + }; + + template <typename H, typename S, typename V> + class hsv_ : public HSV< hsv_<H,S,V> > + { + public: + + typedef H h_type; + typedef S s_type; + typedef V v_type; + + /// Constructor without argument. + hsv_() + { + } + + hsv_(const literal::zero_t&) + : hue_(0), + sat_(0), + val_(0) + { + } + + /// Constructor from component values. + hsv_(const H& hue, const S& sat, const V& val) + : hue_(hue), + sat_(sat), + val_(val) + { + } + + /// Read-only access to the hue component. + const H& hue() const; + const S& sat() const; + const V& val() const; + + /// Read-write access to the hue component. + H& hue(); + S& sat(); + V& val(); + + private: + //FIXME: Don't we want to store these values in a vector? + H hue_; + S sat_; + V val_; + }; + + + typedef hsv_<float, float, float> hsv_f; + typedef hsv_<double, double, double> hsv_d; + + + /// Print an hsv \p c into the output stream \p ostr. + /// + /// \param[in,out] ostr An output stream. + /// \param[in] c An rgb. + /// + /// \return The modified output stream \p ostr. + template <typename H, typename S, typename V> + std::ostream& operator<<(std::ostream& ostr, const hsv_<H,S,V>& c); + + + /// Addition. + /// { + template <typename H, typename S, typename V> + hsv_<H,S,V> + operator+(const hsv_<H,S,V>& lhs, const hsv_<H,S,V>& rhs); + /// \} + + /// Subtraction. + /// \{ + template <typename H, typename S, typename V> + hsv_<H,S,V> + operator-(const hsv_<H,S,V>& lhs, const hsv_<H,S,V>& rhs); + /// \} + + /// Product. + /// \{ + template <typename H, typename S, typename V, typename S2> + hsv_<H,S,V> + operator*(const hsv_<H,S,V>& lhs, const mln::value::scalar_<S2>& s); + /// \} + + /// Division. + /// \{ + template <typename H, typename S, typename V, typename S2> + hsv_<H,S,V> + operator/(const hsv_<H,S,V>& lhs, const mln::value::scalar_<S2>& s); + /// \} + + /// Comparison. + /// \{ + template <typename H, typename S, typename V> + bool + operator==(const hsv_<H,S,V>& lhs, const hsv_<H,S,V>& rhs); + /// \} + + } // end of namespace mln::value + + + + // More forward declarations + namespace fun + { + namespace v2v + { + + template <typename T_hsv> + struct f_rgb_to_hsv_; + + typedef f_rgb_to_hsv_<value::hsv_f> f_rgb_to_hsv_f_t; + + extern f_rgb_to_hsv_f_t f_rgb_to_hsv_f; + + } + + } + +# ifndef MLN_INCLUDE_ONLY + + + namespace value + { + + template <typename H, typename S, typename V> + const H& + hsv_<H,S,V>::hue() const + { + return this->hue_; + } + + template <typename H, typename S, typename V> + const S& + hsv_<H,S,V>::sat() const + { + return this->sat_; + } + + template <typename H, typename S, typename V> + const V& + hsv_<H,S,V>::val() const + { + return this->val_; + } + + template <typename H, typename S, typename V> + H& + hsv_<H,S,V>::hue() + { + return this->hue_; + } + + template <typename H, typename S, typename V> + S& + hsv_<H,S,V>::sat() + { + return this->sat_; + } + + template <typename H, typename S, typename V> + V& + hsv_<H,S,V>::val() + { + return this->val_; + } + + + template <typename H, typename S, typename V> + inline + std::ostream& operator<<(std::ostream& ostr, const hsv_<H,S,V>& v) + { + return ostr << '(' << debug::format(v.hue()) + << ',' << debug::format(v.sat()) + << ',' << debug::format(v.val()) + << ')'; + } + + + template <typename H, typename S, typename V> + hsv_<H,S,V> + operator+(const hsv_<H,S,V>& lhs, const hsv_<H,S,V>& rhs) + { + return hsv_<H,S,V>(lhs.hue() + rhs.hue(), + lhs.sat() + rhs.sat(), + lhs.val() + rhs.val()); + } + + + template <typename H, typename S, typename V> + hsv_<H,S,V> + operator-(const hsv_<H,S,V>& lhs, const hsv_<H,S,V>& rhs) + { + return hsv_<H,S,V>(lhs.hue() - rhs.hue(), + lhs.sat() - rhs.sat(), + lhs.val() - rhs.val()); + } + + + template <typename H, typename S, typename V, typename S2> + hsv_<H,S,V> + operator*(const hsv_<H,S,V>& lhs, const mln::value::scalar_<S2>& s) + { + return hsv_<H,S,V>(lhs.hue() * s, + lhs.sat() * s, + lhs.val() * s); + } + + + template <typename H, typename S, typename V, typename S2> + hsv_<H,S,V> + operator/(const hsv_<H,S,V>& lhs, const mln::value::scalar_<S2>& s) + { + return hsv_<H,S,V>(lhs.hue() / s, + lhs.sat() / s, + lhs.val() / s); + } + + template <typename H, typename S, typename V> + bool + operator==(const hsv_<H,S,V>& lhs, const hsv_<H,S,V>& rhs) + { + return lhs.hue() == rhs.hue() + && lhs.sat() == rhs.sat() + && lhs.val() == rhs.val(); + } + + } // end of namespace mln::value + +/* + namespace convert + { + + namespace over_load + { + + inline + void + from_to_(const value::rgb<16>& from, value::hsv_<float,float,float>& to) + { + to = fun::v2v::f_rgb_to_hsv_f(from); + } + + inline + void + from_to_(const value::rgb<8>& from, value::hsv_<float,float,float>& to) + { + to = fun::v2v::f_rgb_to_hsv_f(from); + } + + } // end of namespace mln::convert::over_load + + } // end of namespace mln::convert +*/ + +# endif // ! MLN_INCLUDE_ONLY + + +} // end of namespace mln + +#endif // ! MLN_VALUE_HSV_HH -- 1.5.6.5

14 years, 1 month

last-svn-commit-36-gcf874ab Work on Millet value descriptor.

by Yann Jacquelet

* green/exp/annotating/value: New directory. * green/exp/annotating/value/Makefile.am: New Makefile. * green/exp/annotating/value/value.cc: New source file. * green/exp/annotating/value/text-color.txt: New image class. * green/exp/annotating/value/text-img.txt: New image class. * green/exp/annotating/value/text-only.txt: New image class. --- .../annotating/{achromastism => value}/Makefile.am | 0 .../{achromastism => value}/text-color.txt | 0 .../{achromastism => value}/text-img.txt | 0 .../{achromastism => value}/text-only.txt | 0 .../exp/annotating/{hue/hue.cc => value/value.cc} | 143 ++++++++++++-------- 5 files changed, 84 insertions(+), 59 deletions(-) copy milena/sandbox/green/exp/annotating/{achromastism => value}/Makefile.am (100%) copy milena/sandbox/green/exp/annotating/{achromastism => value}/text-color.txt (100%) copy milena/sandbox/green/exp/annotating/{achromastism => value}/text-img.txt (100%) copy milena/sandbox/green/exp/annotating/{achromastism => value}/text-only.txt (100%) copy milena/sandbox/green/exp/annotating/{hue/hue.cc => value/value.cc} (68%) diff --git a/milena/sandbox/green/exp/annotating/achromastism/Makefile.am b/milena/sandbox/green/exp/annotating/value/Makefile.am similarity index 100% copy from milena/sandbox/green/exp/annotating/achromastism/Makefile.am copy to milena/sandbox/green/exp/annotating/value/Makefile.am diff --git a/milena/sandbox/green/exp/annotating/achromastism/text-color.txt b/milena/sandbox/green/exp/annotating/value/text-color.txt similarity index 100% copy from milena/sandbox/green/exp/annotating/achromastism/text-color.txt copy to milena/sandbox/green/exp/annotating/value/text-color.txt diff --git a/milena/sandbox/green/exp/annotating/achromastism/text-img.txt b/milena/sandbox/green/exp/annotating/value/text-img.txt similarity index 100% copy from milena/sandbox/green/exp/annotating/achromastism/text-img.txt copy to milena/sandbox/green/exp/annotating/value/text-img.txt diff --git a/milena/sandbox/green/exp/annotating/achromastism/text-only.txt b/milena/sandbox/green/exp/annotating/value/text-only.txt similarity index 100% copy from milena/sandbox/green/exp/annotating/achromastism/text-only.txt copy to milena/sandbox/green/exp/annotating/value/text-only.txt diff --git a/milena/sandbox/green/exp/annotating/hue/hue.cc b/milena/sandbox/green/exp/annotating/value/value.cc similarity index 68% copy from milena/sandbox/green/exp/annotating/hue/hue.cc copy to milena/sandbox/green/exp/annotating/value/value.cc index 883e1c6..9209d47 100644 --- a/milena/sandbox/green/exp/annotating/hue/hue.cc +++ b/milena/sandbox/green/exp/annotating/value/value.cc @@ -1,4 +1,4 @@ -// SATURATION TEST CF MILLET 2008 +// VALUE TEST CF MILLET 2008 #include <iostream> #include <sstream> @@ -26,7 +26,7 @@ #include <mln/geom/nsites.hh> -#include <mln/fun/v2v/rgb_to_hue_map.hh> +#include <mln/fun/v2v/rgb_to_value_map.hh> #include <mln/io/ppm/load.hh> #include <mln/io/pgm/save.hh> @@ -97,52 +97,25 @@ mln::value::rgb8 label_hue(const mln::value::int_u8 hue) { mln::value::rgb8 result; - - if (10 > hue) + if (14 > hue) result = mln::literal::red; - else if (32 > hue) + else if (29 > hue) result = mln::literal::orange; - else if (53 > hue) + else if (45 > hue) result = mln::literal::yellow; - else if (74 > hue) - result = mln::literal::green; // chartreuse - else if (96 > hue) + else if (113 > hue) result = mln::literal::green; - else if (116 > hue) - result = mln::literal::green;// turquoise, aigue-marine - else if (138 > hue) - result = mln::literal::green; // cyan - else if (159 > hue) - result = mln::literal::blue; // azur - else if (181 > hue) + else if (149 > hue) + result = mln::literal::cyan; + else if (205 > hue) result = mln::literal::blue; - else if (202 > hue) + else if (235 > hue) result = mln::literal::violet; - else if (223 > hue) + else if (242 > hue) result = mln::literal::pink; - else // if (244 > hue) + else result = mln::literal::red; - -// if (14 > hue) -// result = mln::literal::red; -// else if (29 > hue) -// result = mln::literal::orange; -// else if (45 > hue) -// result = mln::literal::yellow; -// else if (113 > hue) -// result = mln::literal::green; -// else if (149 > hue) -// result = mln::literal::cyan; -// else if (205 > hue) -// result = mln::literal::blue; -// else if (235 > hue) -// result = mln::literal::violet; -// else if (242 > hue) -// result = mln::literal::pink; -// else -// result = mln::literal::red; - return result; } @@ -212,14 +185,69 @@ unsigned mean_histo(const mln::Image& histo_) return mean; } +// calcul de contribution +float r(short p, unsigned histo_p, short x, unsigned histo_x) +{ + float result = mln::math::sqr(((float)histo_x / histo_p) * (x-p)); + + return result; +} + +template <typename I> +float stddev3(const mln::Image& histo_, unsigned peak) +{ + const I& histo = exact(histo_); + + mln_precondition(histo.is_valid()); + + // Compute stddev + + float stddev = 0.0; + + mln_piter(I) p(histo.domain()); + + for_all(p) + { + stddev += r((short)peak, mln::opt::at(histo,peak), p.ind(), histo(p)); + } + + return stddev; +} + +template <typename I> +float stddev2(const mln::Image& histo_, unsigned peak, unsigned limit) +{ + const I& histo = exact(histo_); + + mln_precondition(histo.is_valid()); + + float stddev_low = 0.0; + float stddev_up = 0.0; + float ret = 0.0; + + // A transformer avec des iterators + + if (250 > peak) + stddev_up = stddev3(histo |mln::box1d(mln::point1d(peak+1), + mln::point1d(peak+limit)), peak); + + if (5 < peak) + stddev_low = stddev3(histo |mln::box1d(mln::point1d(peak-limit), + mln::point1d(peak-1)), peak); + + ret = (250 < peak)? stddev_low : (5 > peak)? stddev_up : + (stddev_low + stddev_up)/2; + + return ret; +} -float hue_test(const std::string input, - const std::string output, - const std::string tmp, - const unsigned threshold) +float value_test(const std::string input, + const std::string output, + const std::string tmp, + const unsigned threshold) { - typedef mln::fun::v2v::rgb_to_hue_map<8> t_rgb_to_hue_map; + typedef mln::fun::v2v::rgb_to_value_map<8> t_rgb_to_value_map; mln::image2d<mln::value::rgb8> input_rgb8; mln::image2d<mln::value::int_u8> map; @@ -228,23 +256,20 @@ float hue_test(const std::string input, unsigned cnt2; float prop; unsigned peak; - mln::value::rgb8 color; mln::io::ppm::load(input_rgb8, input.c_str()); - map = mln::data::transform(input_rgb8, t_rgb_to_hue_map()); + map = mln::data::transform(input_rgb8, t_rgb_to_value_map()); histo = mln::data::compute(mln::accu::meta::stat::histo1d(), map); - peak = mean_histo(histo); //peak_histo(histo); - color = label_hue(peak); - cnt1 = count_histo(histo | mln::box1d(mln::point1d(peak-threshold), - mln::point1d(peak+threshold))); - cnt2 = mln::geom::nsites(input_rgb8); - prop = ((100.0 * cnt1) / cnt2); + peak = peak_histo(histo); // mean_histo(histo); + prop = stddev2(histo, peak, limit); +// cnt1 = count_histo(histo | mln::box1d(mln::point1d(peak-threshold), +// mln::point1d(peak+threshold))); +// cnt2 = mln::geom::nsites(input_rgb8); +// prop = ((100.0 * cnt1) / cnt2); mln::io::plot::save_image_sh(histo, output.c_str()); mln::io::pgm::save(map, tmp.c_str()); - std::cout << "peak = " << peak << std::endl; - std::cout << "color = " << color << std::endl; return prop; } @@ -271,15 +296,15 @@ int main() for (t_iter_path dir_iter(full_path[i]); end_iter != dir_iter; ++dir_iter) { // concatenation de chaine - t_path directory(ANNOTATING_HUE_RET_PATH); + t_path directory(ANNOTATING_VALUE_RET_PATH); t_path leaf = dir_iter->path().leaf(); t_path output = change_extension(directory / leaf, ".sh"); t_path tmp = change_extension(directory / leaf, ".pgm"); - prop = hue_test(dir_iter->path().string(), - output.string(), - tmp.string(), - 20); + prop = value_test(dir_iter->path().string(), + output.string(), + tmp.string(), + 15); std::cout << output << " : " << prop << std::endl; std::cerr << output << " : " << prop << std::endl; -- 1.5.6.5

14 years, 1 month

last-svn-commit-35-g40d7890 Work on Millet saturation descriptor.

by Yann Jacquelet

* green/exp/annotating/hue: New directory. * green/exp/annotating/hue/Makefile.am: New Makefile. * green/exp/annotating/hue/hue.cc: New source file. * green/exp/annotating/hue/text-color.txt: New image class. * green/exp/annotating/hue/text-img.txt: New image class. * green/exp/annotating/hue/text-only.txt: New image class. --- milena/sandbox/ChangeLog | 11 + .../annotating/{achromastism => hue}/Makefile.am | 0 milena/sandbox/green/exp/annotating/hue/hue.cc | 291 ++++++++++++++++++++ .../{achromastism => hue}/text-color.txt | 0 .../annotating/{achromastism => hue}/text-img.txt | 0 .../annotating/{achromastism => hue}/text-only.txt | 0 6 files changed, 302 insertions(+), 0 deletions(-) copy milena/sandbox/green/exp/annotating/{achromastism => hue}/Makefile.am (100%) create mode 100644 milena/sandbox/green/exp/annotating/hue/hue.cc copy milena/sandbox/green/exp/annotating/{achromastism => hue}/text-color.txt (100%) copy milena/sandbox/green/exp/annotating/{achromastism => hue}/text-img.txt (100%) copy milena/sandbox/green/exp/annotating/{achromastism => hue}/text-only.txt (100%) diff --git a/milena/sandbox/ChangeLog b/milena/sandbox/ChangeLog index 15c6c4b..c41ef7c 100644 --- a/milena/sandbox/ChangeLog +++ b/milena/sandbox/ChangeLog @@ -2,6 +2,17 @@ Work on Millet saturation descriptor. + * green/exp/annotating/hue: New directory. + * green/exp/annotating/hue/Makefile.am: New Makefile. + * green/exp/annotating/hue/hue.cc: New source file. + * green/exp/annotating/hue/text-color.txt: New image class. + * green/exp/annotating/hue/text-img.txt: New image class. + * green/exp/annotating/hue/text-only.txt: New image class. + +2010-06-21 Yann Jacquelet <jacquelet(a)lrde.epita.fr> + + Work on Millet saturation descriptor. + * green/exp/annotating/saturation: New directory. * green/exp/annotating/saturation/Makefile.am: New Makefile. * green/exp/annotating/saturation/saturation.cc: New source file. diff --git a/milena/sandbox/green/exp/annotating/achromastism/Makefile.am b/milena/sandbox/green/exp/annotating/hue/Makefile.am similarity index 100% copy from milena/sandbox/green/exp/annotating/achromastism/Makefile.am copy to milena/sandbox/green/exp/annotating/hue/Makefile.am diff --git a/milena/sandbox/green/exp/annotating/hue/hue.cc b/milena/sandbox/green/exp/annotating/hue/hue.cc new file mode 100644 index 0000000..883e1c6 --- /dev/null +++ b/milena/sandbox/green/exp/annotating/hue/hue.cc @@ -0,0 +1,291 @@ +// SATURATION TEST CF MILLET 2008 + +#include <iostream> +#include <sstream> +#include <boost/filesystem.hpp> + +#include <mln/img_path.hh> + +#include <mln/accu/stat/histo1d.hh> + +#include <mln/core/image/image1d.hh> +#include <mln/core/image/image2d.hh> +#include <mln/core/image/dmorph/image_if.hh> + +#include <mln/data/compute.hh> +#include <mln/data/stretch.hh> +#include <mln/data/transform.hh> + +#include <mln/literal/colors.hh> +#include <mln/literal/grays.hh> + +#include <mln/math/max.hh> +#include <mln/math/min.hh> + +#include <mln/opt/at.hh> + +#include <mln/geom/nsites.hh> + +#include <mln/fun/v2v/rgb_to_hue_map.hh> + +#include <mln/io/ppm/load.hh> +#include <mln/io/pgm/save.hh> +#include <mln/io/plot/save_image_sh.hh> + +#include <mln/value/rgb8.hh> + +mln::value::rgb8 label_val(const mln::value::int_u8 val) +{ + mln::value::rgb8 result; + + if (82 > val) + result = mln::literal::black; + else if (179 > val) + result= mln::literal::medium_gray; + else + result = mln::literal::white; + + return result; +} + + +mln::value::rgb8 label_orange_or_brown(const mln::value::rgb8 color, + const mln::value::int_u8 sat, + const mln::value::int_u8 val) +{ + mln::value::rgb8 result; + + if (mln::literal::orange == color) + { + unsigned dist_orange = mln::math::abs(sat - 184) + + mln::math::abs(val - 65); + + unsigned dist_brown = mln::math::abs(sat - 255) + + mln::math::abs(val - 125); + + if (dist_orange < dist_brown) + result = mln::literal::orange; + else + result = mln::literal::brown; + } + else + result = color; + + return result; +} + +mln::value::rgb8 label_yellow_or_green(const mln::value::rgb8 color, + const mln::value::int_u8 val) +{ + mln::value::rgb8 result; + + if (mln::literal::yellow == color) + { + // Is it green or yellow ? + if (80 > val) + result = mln::literal::green; + else + result = mln::literal::yellow; + } + else + return color; + + return result; +} + +mln::value::rgb8 label_hue(const mln::value::int_u8 hue) +{ + mln::value::rgb8 result; + + + if (10 > hue) + result = mln::literal::red; + else if (32 > hue) + result = mln::literal::orange; + else if (53 > hue) + result = mln::literal::yellow; + else if (74 > hue) + result = mln::literal::green; // chartreuse + else if (96 > hue) + result = mln::literal::green; + else if (116 > hue) + result = mln::literal::green;// turquoise, aigue-marine + else if (138 > hue) + result = mln::literal::green; // cyan + else if (159 > hue) + result = mln::literal::blue; // azur + else if (181 > hue) + result = mln::literal::blue; + else if (202 > hue) + result = mln::literal::violet; + else if (223 > hue) + result = mln::literal::pink; + else // if (244 > hue) + result = mln::literal::red; + + +// if (14 > hue) +// result = mln::literal::red; +// else if (29 > hue) +// result = mln::literal::orange; +// else if (45 > hue) +// result = mln::literal::yellow; +// else if (113 > hue) +// result = mln::literal::green; +// else if (149 > hue) +// result = mln::literal::cyan; +// else if (205 > hue) +// result = mln::literal::blue; +// else if (235 > hue) +// result = mln::literal::violet; +// else if (242 > hue) +// result = mln::literal::pink; +// else +// result = mln::literal::red; + + return result; +} + +template <typename I> +unsigned count_histo(const mln::Image& img_) +{ + const I& img = exact(img_); + + mln_precondition(img.is_valid()); + + unsigned result = 0; + + mln_piter(I) p(img.domain()); + + for_all(p) + result += img(p); + + return result; +} + +template <typename I> +unsigned peak_histo(const mln::Image& histo_) +{ + const I& histo = exact(histo_); + + mln_precondition(histo.is_valid()); + + // Find the peak of the histogram + unsigned v_max = mln::opt::at(histo, 0); + short p_max = 0; + + mln_piter(I) p(histo.domain()); + + for_all(p) + { + if (v_max < histo(p)) + { + v_max = histo(p); + p_max = p.ind(); + } + } + + return p_max; +} + +template <typename I> +unsigned mean_histo(const mln::Image& histo_) +{ + const I& histo = exact(histo_); + + mln_precondition(histo.is_valid()); + + // Find the mean of the histogram + float sum = 0; + float mean = 0; + + mln_piter(I) p(histo.domain()); + + for_all(p) + { + sum += histo(p); + mean += p.ind()*histo(p); + } + + mean = mean / sum; + + return mean; +} + + +float hue_test(const std::string input, + const std::string output, + const std::string tmp, + const unsigned threshold) + +{ + typedef mln::fun::v2v::rgb_to_hue_map<8> t_rgb_to_hue_map; + + mln::image2d<mln::value::rgb8> input_rgb8; + mln::image2d<mln::value::int_u8> map; + mln::image1d<unsigned> histo; + unsigned cnt1; + unsigned cnt2; + float prop; + unsigned peak; + mln::value::rgb8 color; + + mln::io::ppm::load(input_rgb8, input.c_str()); + + map = mln::data::transform(input_rgb8, t_rgb_to_hue_map()); + histo = mln::data::compute(mln::accu::meta::stat::histo1d(), map); + peak = mean_histo(histo); //peak_histo(histo); + color = label_hue(peak); + cnt1 = count_histo(histo | mln::box1d(mln::point1d(peak-threshold), + mln::point1d(peak+threshold))); + cnt2 = mln::geom::nsites(input_rgb8); + prop = ((100.0 * cnt1) / cnt2); + + mln::io::plot::save_image_sh(histo, output.c_str()); + mln::io::pgm::save(map, tmp.c_str()); + std::cout << "peak = " << peak << std::endl; + std::cout << "color = " << color << std::endl; + + return prop; +} + + +int main() +{ + typedef boost::filesystem::path t_path; + typedef boost::filesystem::directory_iterator t_iter_path; + + t_path full_path[] = {t_path(ICDAR_20P_PPM_IMG_PATH)}; + + for (int i = 0; i < 1; ++i) + { + std::cout << "entering " << full_path[i] << std::endl; + + if (boost::filesystem::exists(full_path[i]) && + boost::filesystem::is_directory(full_path[i])) + { + boost::filesystem::system_complete(full_path[i]); + const t_iter_path end_iter; + float prop = 0.0; + + for (t_iter_path dir_iter(full_path[i]); end_iter != dir_iter; ++dir_iter) + { + // concatenation de chaine + t_path directory(ANNOTATING_HUE_RET_PATH); + t_path leaf = dir_iter->path().leaf(); + t_path output = change_extension(directory / leaf, ".sh"); + t_path tmp = change_extension(directory / leaf, ".pgm"); + + prop = hue_test(dir_iter->path().string(), + output.string(), + tmp.string(), + 20); + + std::cout << output << " : " << prop << std::endl; + std::cerr << output << " : " << prop << std::endl; + } + } + } + + return 0; +} diff --git a/milena/sandbox/green/exp/annotating/achromastism/text-color.txt b/milena/sandbox/green/exp/annotating/hue/text-color.txt similarity index 100% copy from milena/sandbox/green/exp/annotating/achromastism/text-color.txt copy to milena/sandbox/green/exp/annotating/hue/text-color.txt diff --git a/milena/sandbox/green/exp/annotating/achromastism/text-img.txt b/milena/sandbox/green/exp/annotating/hue/text-img.txt similarity index 100% copy from milena/sandbox/green/exp/annotating/achromastism/text-img.txt copy to milena/sandbox/green/exp/annotating/hue/text-img.txt diff --git a/milena/sandbox/green/exp/annotating/achromastism/text-only.txt b/milena/sandbox/green/exp/annotating/hue/text-only.txt similarity index 100% copy from milena/sandbox/green/exp/annotating/achromastism/text-only.txt copy to milena/sandbox/green/exp/annotating/hue/text-only.txt -- 1.5.6.5

14 years, 1 month

last-svn-commit-34-gb17f057 Work on Millet saturation descriptor.

by Yann Jacquelet

* green/exp/annotating/saturation: New directory. * green/exp/annotating/saturation/Makefile.am: New Makefile. * green/exp/annotating/saturation/saturation.cc: New source file. --- milena/sandbox/ChangeLog | 14 ++++++++- .../{achromastism => saturation}/Makefile.am | 0 .../achromastism.cc => saturation/saturation.cc} | 30 ++++++++++++-------- .../{achromastism => saturation}/text-color.txt | 0 .../{achromastism => saturation}/text-img.txt | 0 .../{achromastism => saturation}/text-only.txt | 0 6 files changed, 31 insertions(+), 13 deletions(-) copy milena/sandbox/green/exp/annotating/{achromastism => saturation}/Makefile.am (100%) copy milena/sandbox/green/exp/annotating/{achromastism/achromastism.cc => saturation/saturation.cc} (75%) copy milena/sandbox/green/exp/annotating/{achromastism => saturation}/text-color.txt (100%) copy milena/sandbox/green/exp/annotating/{achromastism => saturation}/text-img.txt (100%) copy milena/sandbox/green/exp/annotating/{achromastism => saturation}/text-only.txt (100%) diff --git a/milena/sandbox/ChangeLog b/milena/sandbox/ChangeLog index 0e7ac9c..15c6c4b 100644 --- a/milena/sandbox/ChangeLog +++ b/milena/sandbox/ChangeLog @@ -1,9 +1,21 @@ 2010-06-21 Yann Jacquelet <jacquelet(a)lrde.epita.fr> + Work on Millet saturation descriptor. + + * green/exp/annotating/saturation: New directory. + * green/exp/annotating/saturation/Makefile.am: New Makefile. + * green/exp/annotating/saturation/saturation.cc: New source file. + * green/exp/annotating/saturation/text-color.txt: New image class. + * green/exp/annotating/saturation/text-img.txt: New image class. + * green/exp/annotating/saturation/text-only.txt: New image class. + + +2010-06-21 Yann Jacquelet <jacquelet(a)lrde.epita.fr> + Work on Millet hsv descriptors. * green/exp/annotating/hsv: New directory. - * green/Exp/annotating/hsv/hsv.cc: New source file. + * green/exp/annotating/hsv/hsv.cc: New source file. 2010-06-21 Yann Jacquelet <jacquelet(a)lrde.epita.fr> diff --git a/milena/sandbox/green/exp/annotating/achromastism/Makefile.am b/milena/sandbox/green/exp/annotating/saturation/Makefile.am similarity index 100% copy from milena/sandbox/green/exp/annotating/achromastism/Makefile.am copy to milena/sandbox/green/exp/annotating/saturation/Makefile.am diff --git a/milena/sandbox/green/exp/annotating/achromastism/achromastism.cc b/milena/sandbox/green/exp/annotating/saturation/saturation.cc similarity index 75% copy from milena/sandbox/green/exp/annotating/achromastism/achromastism.cc copy to milena/sandbox/green/exp/annotating/saturation/saturation.cc index fdb8e6d..3eb27a4 100644 --- a/milena/sandbox/green/exp/annotating/achromastism/achromastism.cc +++ b/milena/sandbox/green/exp/annotating/saturation/saturation.cc @@ -1,4 +1,4 @@ -// ACHROMATISM TEST CF MILLET 2008 +// SATURATION TEST CF MILLET 2008 #include <iostream> #include <sstream> @@ -21,9 +21,10 @@ #include <mln/geom/nsites.hh> -#include <mln/fun/v2v/rgb_to_achromatism_map.hh> +#include <mln/fun/v2v/rgb_to_saturation_map.hh> #include <mln/io/ppm/load.hh> +//#include <mln/io/pgm/save.hh> #include <mln/io/plot/save_image_sh.hh> #include <mln/value/rgb8.hh> @@ -45,12 +46,14 @@ unsigned count_histo(const mln::Image& img_) return result; } -float achromatism_test(const std::string input, - const std::string output, - const unsigned threshold) + +float saturation_test(const std::string input, + const std::string output, +// const std::string tmp, + const unsigned threshold) { - typedef mln::fun::v2v::rgb_to_achromatism_map<8> t_rgb_to_achromatism_map; + typedef mln::fun::v2v::rgb_to_saturation_map<8> t_rgb_to_saturation_map; mln::image2d<mln::value::rgb8> input_rgb8; mln::image2d<mln::value::int_u8> map; @@ -61,7 +64,7 @@ float achromatism_test(const std::string input, mln::io::ppm::load(input_rgb8, input.c_str()); - map = mln::data::transform(input_rgb8, t_rgb_to_achromatism_map()); + map = mln::data::transform(input_rgb8, t_rgb_to_saturation_map()); histo = mln::data::compute(mln::accu::meta::stat::histo1d(), map); cnt1 = count_histo(histo | mln::box1d(mln::point1d(0), mln::point1d(threshold))); @@ -69,6 +72,7 @@ float achromatism_test(const std::string input, prop = ((100.0 * cnt1) / cnt2); mln::io::plot::save_image_sh(histo, output.c_str()); +// mln::io::pgm::save(map, tmp.c_str()); return prop; } @@ -95,13 +99,15 @@ int main() for (t_iter_path dir_iter(full_path[i]); end_iter != dir_iter; ++dir_iter) { // concatenation de chaine - t_path directory(ANNOTATING_ACHROMATISM_RET_PATH); - t_path leaf = dir_iter->path().leaf(); + t_path directory(ANNOTATING_SATURATION_RET_PATH); + t_path leaf = dir_iter->path().leaf(); t_path output = change_extension(directory / leaf, ".sh"); + t_path tmp = change_extension(directory / leaf, ".pgm"); - prop = achromatism_test(dir_iter->path().string(), - output.string(), - 11); + prop = saturation_test(dir_iter->path().string(), + output.string(), +// tmp.string(), + 25); std::cout << output << " : " << prop << std::endl; std::cerr << output << " : " << prop << std::endl; diff --git a/milena/sandbox/green/exp/annotating/achromastism/text-color.txt b/milena/sandbox/green/exp/annotating/saturation/text-color.txt similarity index 100% copy from milena/sandbox/green/exp/annotating/achromastism/text-color.txt copy to milena/sandbox/green/exp/annotating/saturation/text-color.txt diff --git a/milena/sandbox/green/exp/annotating/achromastism/text-img.txt b/milena/sandbox/green/exp/annotating/saturation/text-img.txt similarity index 100% copy from milena/sandbox/green/exp/annotating/achromastism/text-img.txt copy to milena/sandbox/green/exp/annotating/saturation/text-img.txt diff --git a/milena/sandbox/green/exp/annotating/achromastism/text-only.txt b/milena/sandbox/green/exp/annotating/saturation/text-only.txt similarity index 100% copy from milena/sandbox/green/exp/annotating/achromastism/text-only.txt copy to milena/sandbox/green/exp/annotating/saturation/text-only.txt -- 1.5.6.5

14 years, 1 month

last-svn-commit-33-ge0453aa Work on Millet hsv descriptors.

by Yann Jacquelet

* green/exp/annotating/hsv: New directory. * green/Exp/annotating/hsv/hsv.cc: New source file. --- milena/sandbox/ChangeLog | 24 + .../annotating/{achromastism => hsv}/Makefile.am | 0 milena/sandbox/green/exp/annotating/hsv/hsv.cc | 652 ++++++++++++++++++++ 3 files changed, 676 insertions(+), 0 deletions(-) copy milena/sandbox/green/exp/annotating/{achromastism => hsv}/Makefile.am (100%) create mode 100644 milena/sandbox/green/exp/annotating/hsv/hsv.cc diff --git a/milena/sandbox/ChangeLog b/milena/sandbox/ChangeLog index 7489f70..0e7ac9c 100644 --- a/milena/sandbox/ChangeLog +++ b/milena/sandbox/ChangeLog @@ -1,5 +1,28 @@ 2010-06-21 Yann Jacquelet <jacquelet(a)lrde.epita.fr> + Work on Millet hsv descriptors. + + * green/exp/annotating/hsv: New directory. + * green/Exp/annotating/hsv/hsv.cc: New source file. + +2010-06-21 Yann Jacquelet <jacquelet(a)lrde.epita.fr> + + Work on histograms view as density. + + * green/exp/annotating/histo: New directory. + * green/exp/annotating/histo/histo.cc: New Makefile.am. + * green/exp/annotating/histo/histo.cc: New source. + +2010-06-21 Yann Jacquelet <jacquelet(a)lrde.epita.fr> + + Test error quantification as a color descriptor in our database. + + * green/exp/annotating/error: New directory. + * green/exp/annotating/error/Makefile.am: New Makefile. + * green/exp/annotating/error/error.cc: New source. + +2010-06-21 Yann Jacquelet <jacquelet(a)lrde.epita.fr> + Benchmark few descriptors. * green/exp/annotating/bench: New directory. @@ -10,6 +33,7 @@ Test on image database the achromatism descriptor. + * green/exp/annotating/achromatism: New directory. * green/exp/annotating/achromatism/Makefile.am: New Makefile. * green/exp/annotating/achromatism/achromatism.am: New source. * green/exp/annotating/achromatism/text-color.txt: New image class. diff --git a/milena/sandbox/green/exp/annotating/achromastism/Makefile.am b/milena/sandbox/green/exp/annotating/hsv/Makefile.am similarity index 100% copy from milena/sandbox/green/exp/annotating/achromastism/Makefile.am copy to milena/sandbox/green/exp/annotating/hsv/Makefile.am diff --git a/milena/sandbox/green/exp/annotating/hsv/hsv.cc b/milena/sandbox/green/exp/annotating/hsv/hsv.cc new file mode 100644 index 0000000..2aa9113 --- /dev/null +++ b/milena/sandbox/green/exp/annotating/hsv/hsv.cc @@ -0,0 +1,652 @@ +// HSV TEST CF MILLET 2008 + +#include <iostream> +#include <sstream> +#include <boost/filesystem.hpp> + +#include <mln/img_path.hh> + +#include <mln/accu/stat/histo1d.hh> + +#include <mln/arith/minus.hh> +#include <mln/arith/div.hh> + +#include <mln/core/image/image1d.hh> +#include <mln/core/image/image2d.hh> +#include <mln/core/image/dmorph/image_if.hh> + +#include <mln/data/convert.hh> +#include <mln/data/compute.hh> +#include <mln/data/stretch.hh> +#include <mln/data/transform.hh> + +#include <mln/literal/zero.hh> +#include <mln/literal/colors.hh> +#include <mln/literal/grays.hh> + +#include <mln/math/max.hh> +#include <mln/math/min.hh> +#include <mln/math/sqr.hh> +#include <mln/math/sqrt.hh> + +#include <mln/opt/at.hh> + +#include <mln/geom/nsites.hh> + +#include <mln/fun/v2v/rgb_to_hue_map.hh> +#include <mln/fun/v2v/rgb_to_saturation_map.hh> +#include <mln/fun/v2v/rgb_to_value_map.hh> + +#include <mln/io/ppm/load.hh> +#include <mln/io/pgm/save.hh> +#include <mln/io/plot/save_image_sh.hh> + +#include <mln/value/rgb8.hh> + +//============================================================================// +// HISTOGRAM +//============================================================================// + +template <typename I> +mln_value(I) count_histo(const mln::Image& histo_) +{ + const I& histo = exact(histo_); + + mln_precondition(histo.is_valid()); + + mln_value(I) result = mln::literal::zero; + mln_piter(I) p(histo.domain()); + + for_all(p) + result += histo(p); + + return result; +} + +template <typename I> +mln_value(I) sum_frequency_histo(const mln::Image& histo_) +{ + const I& histo = exact(histo_); + + mln_precondition(histo.is_valid()); + + mln_value(I) sum = mln::literal::zero; + mln_piter(I) p(histo.domain()); + + for_all(p) + sum += histo(p); + + return sum; +} + +template <typename I> +mln_value(I) count_null_frequency_histo(const mln::Image& histo_) +{ + const I& histo = exact(histo_); + + mln_precondition(histo.is_valid()); + + mln_value(I) count = mln::literal::zero; + mln_piter(I) p(histo.domain()); + + for_all(p) + if (0 == histo(p)) + count++; + + return count; +} + +template <typename I> +mln_coord(mln_site_(I)) peak_histo(const mln::Image& histo_) +{ + const I& histo = exact(histo_); + + mln_precondition(histo.is_valid()); + + // Find the peak of the histogram + mln_value(I) v_max = mln::opt::at(histo, mln::literal::zero); + mln_coord(mln_site_(I)) p_max = mln::literal::zero; + mln_piter(I) p(histo.domain()); + + for_all(p) + { + if (v_max < histo(p)) + { + v_max = histo(p); + p_max = p.ind(); + } + } + + return p_max; +} + +template <typename I> +mln_value(I) max_frequency_histo(const mln::Image& histo_) +{ + const I& histo = exact(histo_); + + mln_precondition(histo.is_valid()); + + // Find the value of the peak from the histogram + mln_value(I) max = mln::opt::at(histo, mln::literal::zero); + mln_piter(I) p(histo.domain()); + + for_all(p) + { + max = mln::math::max(histo(p),max); + } + + return max; +} + +template <typename I> +float mean_histo(const mln::Image& histo_) +{ + const I& histo = exact(histo_); + + mln_precondition(histo.is_valid()); + + // Find the mean of the histogram + float sum = 0; + float mean = 0; + + mln_piter(I) p(histo.domain()); + + for_all(p) + { + sum += histo(p); + mean += p.ind()*histo(p); + } + + mean = mean / sum; + + return mean; +} + +template <typename I> +float cmp_equi_frequency_histo(const mln::Image& histo_) +{ + const I& histo = exact(histo_); + + mln_precondition(histo.is_valid()); + + // Find the mean of the histogram + float sum = 0; + float var = 0; + + mln_piter(I) p(histo.domain()); + + for_all(p) + { + sum += histo(p); + var += mln::math::sqr(histo(p) - (1/256.0)); + } + + var = var / sum; + + return var; +} + +template <typename I> +float var_histo(const mln::Image& histo_, float mean) +{ + const I& histo = exact(histo_); + + mln_precondition(histo.is_valid()); + + // Find the mean of the histogram + float sum = 0; + float var = 0; + + mln_piter(I) p(histo.domain()); + + for_all(p) + { + sum += histo(p); + var += mln::math::sqr(p.ind() - mean) * histo(p); + } + + var = var / sum; + + return var; +} + +template <typename I> +float mean_frequency_histo(const mln::Image& histo_) +{ + const I& histo = exact(histo_); + + mln_precondition(histo.is_valid()); + + // Find the mean of the histogram + float sum = 0; + float mean = 0; + + mln_piter(I) p(histo.domain()); + + for_all(p) + { + sum++; + mean += histo(p); + } + + mean = mean / sum; + + return mean; +} + +template <typename I> +float stddev_frequency_histo(const mln::Image& histo_, float mean) +{ + const I& histo = exact(histo_); + + mln_precondition(histo.is_valid()); + + // Find the var of the histogram + float sum = 0; + float var = 0; + + mln_piter(I) p(histo.domain()); + + for_all(p) + { + sum++; + var += mln::math::sqr(histo(p)-mean); + } + + var = mln::math::sqrt(var / sum); + + return var; +} + + +//============================================================================// +// HUE TEST +//============================================================================// + +mln::value::rgb8 label_val(const mln::value::int_u8 val) +{ + mln::value::rgb8 result; + + if (82 > val) + result = mln::literal::black; + else if (179 > val) + result= mln::literal::medium_gray; + else + result = mln::literal::white; + + return result; +} + + +mln::value::rgb8 label_orange_or_brown(const mln::value::rgb8 color, + const mln::value::int_u8 sat, + const mln::value::int_u8 val) +{ + mln::value::rgb8 result; + + if (mln::literal::orange == color) + { + unsigned dist_orange = mln::math::abs(sat - 184) + + mln::math::abs(val - 65); + + unsigned dist_brown = mln::math::abs(sat - 255) + + mln::math::abs(val - 125); + + if (dist_orange < dist_brown) + result = mln::literal::orange; + else + result = mln::literal::brown; + } + else + result = color; + + return result; +} + +mln::value::rgb8 label_yellow_or_green(const mln::value::rgb8 color, + const mln::value::int_u8 val) +{ + mln::value::rgb8 result; + + if (mln::literal::yellow == color) + { + // Is it green or yellow ? + if (80 > val) + result = mln::literal::green; + else + result = mln::literal::yellow; + } + else + return color; + + return result; +} + +mln::value::rgb8 label_hue(const mln::value::int_u8 hue) +{ + mln::value::rgb8 result; + + + if (10 > hue) + result = mln::literal::red; + else if (32 > hue) + result = mln::literal::orange; + else if (53 > hue) + result = mln::literal::yellow; + else if (74 > hue) + result = mln::literal::green; // chartreuse + else if (96 > hue) + result = mln::literal::green; + else if (116 > hue) + result = mln::literal::green;// turquoise, aigue-marine + else if (138 > hue) + result = mln::literal::green; // cyan + else if (159 > hue) + result = mln::literal::blue; // azur + else if (181 > hue) + result = mln::literal::blue; + else if (202 > hue) + result = mln::literal::violet; + else if (223 > hue) + result = mln::literal::pink; + else // if (244 > hue) + result = mln::literal::red; + + return result; +} + +float hue_test(const std::string input, + const std::string output, + const std::string tmp, + const short threshold) + +{ + typedef mln::fun::v2v::rgb_to_hue_map<8> t_rgb_to_hue_map; + + mln::image2d<mln::value::rgb8> input_rgb8; + mln::image2d<mln::value::int_u8> map; + mln::image1d<unsigned> histo; + mln::image1d<float> histo_float; + float cnt1; + float cnt2; + float prop; + short peak; + mln::value::rgb8 color; + float sum; + mln::point1d inf; + mln::point1d sup; + + mln::io::ppm::load(input_rgb8, input.c_str()); + + map = mln::data::transform(input_rgb8, t_rgb_to_hue_map()); + histo = mln::data::compute(mln::accu::meta::stat::histo1d(), map); + sum = sum_frequency_histo(histo); + histo_float = mln::data::convert(float(), histo) / sum; + peak = mean_histo(histo); //peak_histo(histo); + color = label_hue(peak); + inf = mln::point1d(mln::math::max(0, peak-threshold)); + sup = mln::point1d(mln::math::min(255, peak+threshold)); + cnt1 = count_histo(histo_float|mln::box1d(inf,sup)); + cnt2 = count_histo(histo_float); + prop = ((100.0 * cnt1) / cnt2); + + mln::io::plot::save_image_sh(histo_float, output.c_str()); + mln::io::pgm::save(map, tmp.c_str()); +// std::cout << "peak = " << peak << std::endl; +// std::cout << "color = " << color << std::endl; + + return prop; +} + +//============================================================================// +// SATURATION TEST +//============================================================================// + +float saturation_test(const std::string input, + const std::string output, + const std::string tmp, + const short threshold) + +{ + typedef mln::fun::v2v::rgb_to_saturation_map<8> t_rgb_to_saturation_map; + + mln::image2d<mln::value::rgb8> input_rgb8; + mln::image2d<mln::value::int_u8> map; + mln::image1d<unsigned> histo; + mln::image1d<float> histo_float; + float cnt1; + float cnt2; + float sum; + float prop; + + mln::io::ppm::load(input_rgb8, input.c_str()); + + map = mln::data::transform(input_rgb8, t_rgb_to_saturation_map()); + histo = mln::data::compute(mln::accu::meta::stat::histo1d(), map); + sum = sum_frequency_histo(histo); + histo_float = mln::data::convert(float(), histo) / sum; + cnt1 = count_histo(histo_float | mln::box1d(mln::point1d(0), + mln::point1d(threshold))); + cnt2 = count_histo(histo_float); + prop = ((100.0 * cnt1) / cnt2); + + mln::io::plot::save_image_sh(histo_float, output.c_str()); + mln::io::pgm::save(map, tmp.c_str()); + + return prop; +} + +//============================================================================// +// VALUE TEST +//============================================================================// + +// calcul de contribution +float r(short p, unsigned histo_p, short x, unsigned histo_x) +{ + float result = mln::math::sqr(((float)histo_x / histo_p) * (x-p)); + + return result; +} + +template <typename I> +float stddev3(const mln::Image& histo_, unsigned peak) +{ + const I& histo = exact(histo_); + + mln_precondition(histo.is_valid()); + + // Compute stddev + + float stddev = 0.0; + + mln_piter(I) p(histo.domain()); + + for_all(p) + { + stddev += r((short)peak, mln::opt::at(histo,peak), p.ind(), histo(p)); + } + + return stddev; +} + +template <typename I> +float stddev2(const mln::Image& histo_, unsigned peak, unsigned limit) +{ + const I& histo = exact(histo_); + + mln_precondition(histo.is_valid()); + + float stddev_low = 0.0; + float stddev_up = 0.0; + float ret = 0.0; + + // A transformer avec des iterators + + if (250 > peak) + stddev_up = stddev3(histo |mln::box1d(mln::point1d(peak+1), + mln::point1d(peak+limit)), peak); + + if (5 < peak) + stddev_low = stddev3(histo |mln::box1d(mln::point1d(peak-limit), + mln::point1d(peak-1)), peak); + + ret = (250 < peak)? stddev_low : (5 > peak)? stddev_up : + (stddev_low + stddev_up)/2; + + return ret; +} + +// DOC: +// la discrimination entre la base AFP et la base ICDAR peut se faire en +// étudiant la forme des densités des niveaux de gris. +// Les images naturelles semblent avoir un spectre recouvrant +// en général les 256 niveaux de gris alors que les images de documents ont +// une présence importante du fond. Dans le cadre d'une densité, ce qui est +// alloué sur le fond ne peut se retrouver ailleurs. Une comparaison avec la +// densité équiprobable nous renseigne donc sur la nature des images. +// Il semble néanmoins qu'un certain nombre d'images défient ce dispositif. +// Par exemple des gros plans sur des zones mono-teintée (ski, voile,site web). + + + + +float value_test(const std::string input, + const std::string output, + const std::string tmp, + const short threshold) + +{ + typedef mln::fun::v2v::rgb_to_value_map<8> t_rgb_to_value_map; + + mln::image2d<mln::value::rgb8> input_rgb8; + mln::image2d<mln::value::int_u8> map; + mln::image1d<unsigned> histo; + mln::image1d<float> histo_float; + float cnt1; + float cnt2; + float prop; + float sum; + float prop4; + short peak; + mln::point1d inf; + mln::point1d sup; + + + mln::io::ppm::load(input_rgb8, input.c_str()); + + map = mln::data::transform(input_rgb8, t_rgb_to_value_map()); + histo = mln::data::compute(mln::accu::meta::stat::histo1d(), map); + sum = sum_frequency_histo(histo); + histo_float = mln::data::convert(float(), histo) / sum; + prop4 = cmp_equi_frequency_histo(histo_float); + peak = peak_histo(histo); // mean_histo(histo); + //prop = stddev2(histo, peak, threshold); + inf = mln::point1d(mln::math::max(0, peak-threshold)); + sup = mln::point1d(mln::math::min(255, peak+threshold)); + cnt1 = count_histo(histo_float|mln::box1d(inf,sup)); + cnt2 = count_histo(histo_float); + prop = ((100.0 * cnt1) / cnt2); + + std::cerr << "peak = " << peak << std::endl; + std::cerr << "inf = " << inf << std::endl; + std::cerr << "sup = " << sup << std::endl; + std::cerr << "cnt1 = " << cnt1 << std::endl; + std::cerr << "cnt2 = " << cnt2 << std::endl; + std::cerr << "prop = " << prop << std::endl; + std::cerr << "prop4= " << prop4 << std::endl; + + mln::io::plot::save_image_sh(histo_float, output.c_str()); + mln::io::pgm::save(map, tmp.c_str()); + + return prop; +} + +//============================================================================// +// MAIN +//============================================================================// + + +int main() +{ + typedef boost::filesystem::path t_path; + typedef boost::filesystem::directory_iterator t_iter_path; + +// t_path full_path[] = {t_path(ICDAR_20P_TEXT_ONLY_IMG_PATH), +// t_path(ICDAR_20P_TEXT_COLOR_IMG_PATH), +// t_path(ICDAR_20P_TEXT_PHOTO_IMG_PATH)}; + + t_path full_path[] = {t_path(AFP_PPM_IMG_PATH)}; + + std::cout << "#!/usr/bin/gnuplot" << std::endl; + std::cout << "set terminal x11 persist 1" << std::endl; + std::cout << "#HUE - SATURATION - VALUE" << std::endl; + std::cout << "plot '-' using 1:2 with point notitle,\\" << std::endl; + std::cout << " '-' using 1:2 with point notitle,\\" << std::endl; + std::cout << " '-' using 1:2 with point notitle" << std::endl; + + for (int i = 0; i < 1; ++i) + { + if (boost::filesystem::exists(full_path[i]) && + boost::filesystem::is_directory(full_path[i])) + { + boost::filesystem::system_complete(full_path[i]); + const t_iter_path end_iter; + float prop = 0.0; + t_path directory; + t_path leaf; + t_path output; + t_path tmp; + + std::cerr << "entering " << full_path[i] << std::endl; + + for (t_iter_path dir_iter(full_path[i]); end_iter != dir_iter; ++dir_iter) + { + std::cerr << dir_iter->path() << std::endl; + // concatenation de chaine +// directory = (ANNOTATING_ICDAR_HUE_RET_PATH); + directory = (ANNOTATING_AFP_HUE_RET_PATH); + leaf = dir_iter->path().leaf(); + output = change_extension(directory / leaf, ".sh"); + tmp = change_extension(directory / leaf, ".pgm"); + + prop = hue_test(dir_iter->path().string(), + output.string(), + tmp.string(), + 20); + + std::cout << prop << " "; + +// directory = (ANNOTATING_ICDAR_SAT_RET_PATH); + directory = (ANNOTATING_AFP_SAT_RET_PATH); + leaf = dir_iter->path().leaf(); + output = change_extension(directory / leaf, ".sh"); + tmp = change_extension(directory / leaf, ".pgm"); + + prop = saturation_test(dir_iter->path().string(), + output.string(), + tmp.string(), + 25); + + std::cout << prop << " "; + +// directory = (ANNOTATING_ICDAR_VAL_RET_PATH); + directory = (ANNOTATING_AFP_VAL_RET_PATH); + leaf = dir_iter->path().leaf(); + output = change_extension(directory / leaf, ".sh"); + tmp = change_extension(directory / leaf, ".pgm"); + + prop = value_test(dir_iter->path().string(), + output.string(), + tmp.string(), + 15); + + std::cout << prop << " "; + std::cout << "# " << dir_iter->path().leaf() << std::endl; + } + std::cout << "e" << std::endl; + } + } + + return 0; +} -- 1.5.6.5

14 years, 1 month

last-svn-commit-32-g66ea248 Work on histograms view as density.

by Yann Jacquelet

* green/exp/annotating/histo: New directory. * green/exp/annotating/histo/histo.cc: New Makefile.am. * green/exp/annotating/histo/histo.cc: New source. --- .../annotating/{achromastism => histo}/Makefile.am | 0 milena/sandbox/green/exp/annotating/histo/histo.cc | 306 ++++++++++++++++++++ 2 files changed, 306 insertions(+), 0 deletions(-) copy milena/sandbox/green/exp/annotating/{achromastism => histo}/Makefile.am (100%) create mode 100644 milena/sandbox/green/exp/annotating/histo/histo.cc diff --git a/milena/sandbox/green/exp/annotating/achromastism/Makefile.am b/milena/sandbox/green/exp/annotating/histo/Makefile.am similarity index 100% copy from milena/sandbox/green/exp/annotating/achromastism/Makefile.am copy to milena/sandbox/green/exp/annotating/histo/Makefile.am diff --git a/milena/sandbox/green/exp/annotating/histo/histo.cc b/milena/sandbox/green/exp/annotating/histo/histo.cc new file mode 100644 index 0000000..2fb0131 --- /dev/null +++ b/milena/sandbox/green/exp/annotating/histo/histo.cc @@ -0,0 +1,306 @@ +// Build normalized histogram as density + +#include <iostream> +#include <sstream> +#include <boost/filesystem.hpp> + +#include <mln/img_path.hh> + +#include <mln/accu/stat/histo1d.hh> + +#include <mln/arith/minus.hh> +#include <mln/arith/div.hh> + +#include <mln/core/image/image1d.hh> +#include <mln/core/image/image2d.hh> +#include <mln/core/image/dmorph/image_if.hh> + +#include <mln/data/convert.hh> +#include <mln/data/compute.hh> +#include <mln/data/stretch.hh> +#include <mln/data/transform.hh> + +#include <mln/literal/zero.hh> +#include <mln/literal/colors.hh> +#include <mln/literal/grays.hh> + +#include <mln/math/max.hh> +#include <mln/math/min.hh> +#include <mln/math/sqr.hh> +#include <mln/math/sqrt.hh> + +#include <mln/opt/at.hh> + +#include <mln/geom/nsites.hh> + +#include <mln/fun/v2v/rgb_to_hue_map.hh> +#include <mln/fun/v2v/rgb_to_saturation_map.hh> +#include <mln/fun/v2v/rgb_to_value_map.hh> +#include <mln/fun/v2v/component.hh> + +#include <mln/io/ppm/load.hh> +#include <mln/io/pgm/save.hh> +#include <mln/io/plot/save_image_sh.hh> + +#include <mln/value/rgb8.hh> + +//============================================================================// +// HISTOGRAM +//============================================================================// + +template <typename I> +mln_value(I) cnt_histo(const mln::Image& histo_) +{ + const I& histo = exact(histo_); + + mln_precondition(histo.is_valid()); + + mln_value(I) cnt = mln::literal::zero; + mln_piter(I) p(histo.domain()); + + for_all(p) + { + cnt += histo(p); + } + + return cnt; +} + +void histo(const std::string input, + const std::string output_map, + const std::string output_histo, + const char space) + +{ + typedef mln::value::rgb8 t_rgb8; + typedef mln::fun::v2v::rgb_to_hue_map<8> t_rgb_to_hue_map; + typedef mln::fun::v2v::rgb_to_saturation_map<8> t_rgb_to_sat_map; + typedef mln::fun::v2v::rgb_to_value_map<8> t_rgb_to_val_map; + typedef mln::fun::v2v::component<t_rgb8,0> t_component_r; + typedef mln::fun::v2v::component<t_rgb8,1> t_component_g; + typedef mln::fun::v2v::component<t_rgb8,2> t_component_b; + + mln::image2d<mln::value::rgb8> input_rgb8; + mln::image2d<mln::value::int_u8> map; + mln::image1d<unsigned> histo; + mln::image1d<float> histo_float; + float sum; + + mln::io::ppm::load(input_rgb8, input.c_str()); + + switch(space) + { + case 'h': map = mln::data::transform(input_rgb8, t_rgb_to_hue_map()); break; + case 's': map = mln::data::transform(input_rgb8, t_rgb_to_sat_map()); break; + case 'v': map = mln::data::transform(input_rgb8, t_rgb_to_val_map()); break; + case 'r': map = mln::data::transform(input_rgb8, t_component_r()); break; + case 'g': map = mln::data::transform(input_rgb8, t_component_g()); break; + case 'b': map = mln::data::transform(input_rgb8, t_component_b()); break; + default: break;// crash + } + + histo = mln::data::compute(mln::accu::meta::stat::histo1d(), map); + sum = cnt_histo(histo); + histo_float = mln::data::convert(float(), histo) / sum; + + mln::io::pgm::save(map, output_map.c_str()); + mln::io::plot::save_image_sh(histo_float, output_histo.c_str()); +} + +//============================================================================// +// MAIN +//============================================================================// + + +// in the directory of the images +// out the density directory +// 2 use-cases afp and icdar + +int main() +{ + typedef boost::filesystem::path t_path; + typedef boost::filesystem::directory_iterator t_iter_path; + +// t_path full_path[] = {t_path(ICDAR_20P_TEXT_ONLY_IMG_PATH), +// t_path(ICDAR_20P_TEXT_COLOR_IMG_PATH), +// t_path(ICDAR_20P_TEXT_PHOTO_IMG_PATH)}; + +// t_path full_path[] = {t_path(AFP_INPUT_IMG_PATH)}; +// t_path full_path[] = {t_path(AFP_GMP30_IMG_PATH)}; +// t_path full_path[] = {t_path(AFP_GMP20_IMG_PATH)}; +// t_path full_path[] = {t_path(AFP_GMP10_IMG_PATH)}; +// t_path full_path[] = {t_path(AFP_MGK30_IMG_PATH)}; +// t_path full_path[] = {t_path(AFP_MGK20_IMG_PATH)}; +// t_path full_path[] = {t_path(AFP_MGK10_IMG_PATH)}; + +// t_path full_path[] = {t_path(ICDAR_20P_INPUT_IMG_PATH)}; +// t_path full_path[] = {t_path(ICDAR_20P_GMP30_IMG_PATH)}; + t_path full_path[] = {t_path(ICDAR_20P_GMP20_IMG_PATH)}; +// t_path full_path[] = {t_path(ICDAR_20P_GMP10_IMG_PATH)}; +// t_path full_path[] = {t_path(ICDAR_20P_MGK30_IMG_PATH)}; +// t_path full_path[] = {t_path(ICDAR_20P_MGK20_IMG_PATH)}; +// t_path full_path[] = {t_path(ICDAR_20P_MGK10_IMG_PATH)}; + + for (int i = 0; i < 1; ++i) + { + if (boost::filesystem::exists(full_path[i]) && + boost::filesystem::is_directory(full_path[i])) + { + boost::filesystem::system_complete(full_path[i]); + const t_iter_path end_iter; + t_path directory; + t_path leaf; + t_path output_map; + t_path output_histo; + + std::cerr << "entering " << full_path[i] << std::endl; + + for (t_iter_path dir_iter(full_path[i]); end_iter != dir_iter; ++dir_iter) + { + std::cerr << dir_iter->path() << std::endl; + + leaf = dir_iter->path().leaf(); + +// directory = ANNOTATING_AFP_R_INPUT_RET_PATH; +// directory = ANNOTATING_AFP_R_GMP30_RET_PATH; +// directory = ANNOTATING_AFP_R_GMP20_RET_PATH; +// directory = ANNOTATING_AFP_R_GMP10_RET_PATH; +// directory = ANNOTATING_AFP_R_MGK30_RET_PATH; +// directory = ANNOTATING_AFP_R_MGK20_RET_PATH; +// directory = ANNOTATING_AFP_R_MGK10_RET_PATH; + +// directory = ANNOTATING_ICDAR_R_INPUT_RET_PATH; +// directory = ANNOTATING_ICDAR_R_GMP30_RET_PATH; + directory = ANNOTATING_ICDAR_R_GMP20_RET_PATH; +// directory = ANNOTATING_ICDAR_R_GMP10_RET_PATH; +// directory = ANNOTATING_ICDAR_R_MGK30_RET_PATH; +// directory = ANNOTATING_ICDAR_R_MGK20_RET_PATH; +// directory = ANNOTATING_ICDAR_R_MGK10_RET_PATH; + output_histo = change_extension(directory / leaf, ".sh"); + output_map = change_extension(directory / leaf, ".pgm"); + + histo(dir_iter->path().string(), + output_map.string(), + output_histo.string(), + 'r'); + +// directory = ANNOTATING_AFP_G_INPUT_RET_PATH; +// directory = ANNOTATING_AFP_G_GMP30_RET_PATH; +// directory = ANNOTATING_AFP_G_GMP20_RET_PATH; +// directory = ANNOTATING_AFP_G_GMP10_RET_PATH; +// directory = ANNOTATING_AFP_G_MGK30_RET_PATH; +// directory = ANNOTATING_AFP_G_MGK20_RET_PATH; +// directory = ANNOTATING_AFP_G_MGK10_RET_PATH; + +// directory = ANNOTATING_ICDAR_G_INPUT_RET_PATH; +// directory = ANNOTATING_ICDAR_G_GMP30_RET_PATH; + directory = ANNOTATING_ICDAR_G_GMP20_RET_PATH; +// directory = ANNOTATING_ICDAR_G_GMP10_RET_PATH; +// directory = ANNOTATING_ICDAR_G_MGK30_RET_PATH; +// directory = ANNOTATING_ICDAR_G_MGK20_RET_PATH; +// directory = ANNOTATING_ICDAR_G_MGK10_RET_PATH; + output_histo = change_extension(directory / leaf, ".sh"); + output_map = change_extension(directory / leaf, ".pgm"); + + histo(dir_iter->path().string(), + output_map.string(), + output_histo.string(), + 'g'); + +// directory = ANNOTATING_AFP_B_INPUT_RET_PATH; +// directory = ANNOTATING_AFP_B_GMP30_RET_PATH; +// directory = ANNOTATING_AFP_B_GMP20_RET_PATH; +// directory = ANNOTATING_AFP_B_GMP10_RET_PATH; +// directory = ANNOTATING_AFP_B_MGK30_RET_PATH; +// directory = ANNOTATING_AFP_B_MGK20_RET_PATH; +// directory = ANNOTATING_AFP_B_MGK10_RET_PATH; + +// directory = ANNOTATING_ICDAR_B_INPUT_RET_PATH; +// directory = ANNOTATING_ICDAR_B_GMP30_RET_PATH; + directory = ANNOTATING_ICDAR_B_GMP20_RET_PATH; +// directory = ANNOTATING_ICDAR_B_GMP10_RET_PATH; +// directory = ANNOTATING_ICDAR_B_MGK30_RET_PATH; +// directory = ANNOTATING_ICDAR_B_MGK20_RET_PATH; +// directory = ANNOTATING_ICDAR_B_MGK10_RET_PATH; + output_histo = change_extension(directory / leaf, ".sh"); + output_map = change_extension(directory / leaf, ".pgm"); + + histo(dir_iter->path().string(), + output_map.string(), + output_histo.string(), + 'b'); + +// directory = ANNOTATING_AFP_H_INPUT_RET_PATH; +// directory = ANNOTATING_AFP_H_GMP30_RET_PATH; +// directory = ANNOTATING_AFP_H_GMP20_RET_PATH; +// directory = ANNOTATING_AFP_H_GMP10_RET_PATH; +// directory = ANNOTATING_AFP_H_MGK30_RET_PATH; +// directory = ANNOTATING_AFP_H_MGK20_RET_PATH; +// directory = ANNOTATING_AFP_H_MGK10_RET_PATH; + +// directory = ANNOTATING_ICDAR_H_INPUT_RET_PATH; +// directory = ANNOTATING_ICDAR_H_GMP30_RET_PATH; + directory = ANNOTATING_ICDAR_H_GMP20_RET_PATH; +// directory = ANNOTATING_ICDAR_H_GMP10_RET_PATH; +// directory = ANNOTATING_ICDAR_H_MGK30_RET_PATH; +// directory = ANNOTATING_ICDAR_H_MGK20_RET_PATH; +// directory = ANNOTATING_ICDAR_H_MGK10_RET_PATH; + output_histo = change_extension(directory / leaf, ".sh"); + output_map = change_extension(directory / leaf, ".pgm"); + + histo(dir_iter->path().string(), + output_map.string(), + output_histo.string(), + 'h'); + +// directory = ANNOTATING_AFP_S_INPUT_RET_PATH; +// directory = ANNOTATING_AFP_S_GMP30_RET_PATH; +// directory = ANNOTATING_AFP_S_GMP20_RET_PATH; +// directory = ANNOTATING_AFP_S_GMP10_RET_PATH; +// directory = ANNOTATING_AFP_S_MGK30_RET_PATH; +// directory = ANNOTATING_AFP_S_MGK20_RET_PATH; +// directory = ANNOTATING_AFP_S_MGK10_RET_PATH; + +// directory = ANNOTATING_ICDAR_S_INPUT_RET_PATH; +// directory = ANNOTATING_ICDAR_S_GMP30_RET_PATH; + directory = ANNOTATING_ICDAR_S_GMP20_RET_PATH; +// directory = ANNOTATING_ICDAR_S_GMP10_RET_PATH; +// directory = ANNOTATING_ICDAR_S_MGK30_RET_PATH; +// directory = ANNOTATING_ICDAR_S_MGK20_RET_PATH; +// directory = ANNOTATING_ICDAR_S_MGK10_RET_PATH; + output_histo = change_extension(directory / leaf, ".sh"); + output_map = change_extension(directory / leaf, ".pgm"); + + histo(dir_iter->path().string(), + output_map.string(), + output_histo.string(), + 's'); + +// directory = ANNOTATING_AFP_V_INPUT_RET_PATH; +// directory = ANNOTATING_AFP_V_GMP30_RET_PATH; +// directory = ANNOTATING_AFP_V_GMP20_RET_PATH; +// directory = ANNOTATING_AFP_V_GMP10_RET_PATH; +// directory = ANNOTATING_AFP_V_MGK30_RET_PATH; +// directory = ANNOTATING_AFP_V_MGK20_RET_PATH; +// directory = ANNOTATING_AFP_V_MGK10_RET_PATH; + +// directory = ANNOTATING_ICDAR_V_INPUT_RET_PATH; +// directory = ANNOTATING_ICDAR_V_GMP30_RET_PATH; + directory = ANNOTATING_ICDAR_V_GMP20_RET_PATH; +// directory = ANNOTATING_ICDAR_V_GMP10_RET_PATH; +// directory = ANNOTATING_ICDAR_V_MGK30_RET_PATH; +// directory = ANNOTATING_ICDAR_V_MGK20_RET_PATH; +// directory = ANNOTATING_ICDAR_V_MGK10_RET_PATH; + output_histo = change_extension(directory / leaf, ".sh"); + output_map = change_extension(directory / leaf, ".pgm"); + + histo(dir_iter->path().string(), + output_map.string(), + output_histo.string(), + 'v'); + } + } + } + + return 0; +} -- 1.5.6.5

14 years, 1 month

last-svn-commit-31-g5144d5f Test error quantification as a color descriptor in our database.

by Yann Jacquelet

* green/exp/annotating/error: New directory. * green/exp/annotating/error/Makefile.am: New Makefile. * green/exp/annotating/error/error.cc: New source. --- .../annotating/{achromastism => error}/Makefile.am | 0 milena/sandbox/green/exp/annotating/error/error.cc | 700 ++++++++++++++++++++ 2 files changed, 700 insertions(+), 0 deletions(-) copy milena/sandbox/green/exp/annotating/{achromastism => error}/Makefile.am (100%) create mode 100644 milena/sandbox/green/exp/annotating/error/error.cc diff --git a/milena/sandbox/green/exp/annotating/achromastism/Makefile.am b/milena/sandbox/green/exp/annotating/error/Makefile.am similarity index 100% copy from milena/sandbox/green/exp/annotating/achromastism/Makefile.am copy to milena/sandbox/green/exp/annotating/error/Makefile.am diff --git a/milena/sandbox/green/exp/annotating/error/error.cc b/milena/sandbox/green/exp/annotating/error/error.cc new file mode 100644 index 0000000..5bc67ba --- /dev/null +++ b/milena/sandbox/green/exp/annotating/error/error.cc @@ -0,0 +1,700 @@ +// HSV TEST CF MILLET 2008 + +#include <iostream> +#include <sstream> +#include <boost/filesystem.hpp> + +#include <mln/algebra/vec.hh> + +#include <mln/img_path.hh> + +#include <mln/accu/stat/mean.hh> +#include <mln/accu/stat/histo1d.hh> + +#include <mln/arith/minus.hh> +#include <mln/arith/times.hh> +#include <mln/arith/diff_abs.hh> + +#include <mln/core/image/image1d.hh> +#include <mln/core/image/image2d.hh> +#include <mln/core/image/dmorph/image_if.hh> +#include <mln/core/alias/point1d.hh> +#include <mln/core/alias/box1d.hh> + +#include <mln/data/transform.hh> +#include <mln/data/compute.hh> +#include <mln/data/stretch.hh> +#include <mln/data/fill.hh> + +#include <mln/fun/v2v/component.hh> + +#include <mln/io/ppm/load.hh> +#include <mln/io/pgm/save.hh> +#include <mln/io/plot/save_image_sh.hh> + +#include <mln/literal/zero.hh> + +#include <mln/math/ceil.hh> +#include <mln/math/floor.hh> + +#include <mln/opt/at.hh> + +#include <mln/trait/value_.hh> + +#include <mln/value/rgb8.hh> +#include <mln/value/int_u8.hh> + +//============================================================================// +// CLASSIFICATION DE FISHER EN 2 CLASSES SUR UN HISTO 1D +//============================================================================// + +template <typename I> +mln_value(I) cnt_histo(const mln::Image& histo_) +{ + const I& histo = exact(histo_); + + mln_precondition(histo.is_valid()); + + mln_value(I) sum = mln::literal::zero; + mln_piter(I) p(histo.domain()); + + for_all(p) + { + sum += histo(p); + } + + return sum; +} + +template <typename I> +mln_value(I) sum_histo(const mln::Image& histo_) +{ + const I& histo = exact(histo_); + + mln_precondition(histo.is_valid()); + + mln_value(I) pos = mln::literal::zero; + mln_value(I) sum = mln::literal::zero; + mln_piter(I) p(histo.domain()); + + for_all(p) + { + pos = p.ind(); + sum += pos*histo(p); + } + + return sum; +} + +template <typename I> +mln_value(I) avg_histo(const mln::Image& histo_) +{ + const I& histo = exact(histo_); + + mln_precondition(histo.is_valid()); + + mln_value(I) pos = mln::literal::zero; + mln_value(I) sum = mln::literal::zero; + mln_value(I) cnt = mln::literal::zero; + mln_piter(I) p(histo.domain()); + + for_all(p) + { + pos = p.ind(); + cnt += histo(p); + sum += pos*histo(p); + } + + return (0 == cnt)? 0 : sum/cnt; +} + +template <typename I> +mln_value(I) var3_histo(const mln::Image& histo_, float mean) +{ + const I& histo = exact(histo_); + + mln_precondition(histo.is_valid()); + + mln_value(I) pos = mln::literal::zero; + mln_value(I) sum = mln::literal::zero; + mln_value(I) cnt = mln::literal::zero; + mln_piter(I) p(histo.domain()); + + for_all(p) + { + cnt += histo(p); + sum += (mln::math::sqr(p.ind()-mean)*histo(p)); + } + + return (0 == cnt)? 0 : sum/cnt; +} + +template <typename I> +mln_value(I) var2_histo(const mln::Image& histo_, float mean) +{ + const I& histo = exact(histo_); + + mln_precondition(histo.is_valid()); + + mln_value(I) pos = mln::literal::zero; + mln_value(I) sum = mln::literal::zero; + mln_value(I) sqr = mln::literal::zero; + mln_value(I) cnt = mln::literal::zero; + mln_value(I) dlt = mln::literal::zero; + mln_value(I) mxt = mln::literal::zero; + mln_piter(I) p(histo.domain()); + + for_all(p) + { + pos = p.ind(); + cnt += (histo(p)); + sum += (histo(p)*pos); + mxt += (histo(p)*pos*mean); + sqr += (histo(p)*mln::math::sqr(pos)); + dlt += (histo(p)*mln::math::sqr(pos - mean)); + + std::cout << "p = " << pos << std::endl; + std::cout << "p² = " << mln::math::sqr(pos) << std::endl; + std::cout << "p*mean = " << (pos*mean) << std::endl; + std::cout << "p-mean = " << (pos-mean) << std::endl; + std::cout << "(p-mean)² = " << mln::math::sqr(pos-mean) << std::endl; + std::cout << "histo(p) = " << histo(p) << std::endl; + std::cout << "histo(p)*p = " << (pos*histo(p)) << std::endl; + std::cout << "histo(p)*p²= " << (mln::math::sqr(pos)*histo(p)) + << std::endl; + std::cout << "cnt = " << cnt << std::endl; + std::cout << "sum = " << sum << std::endl; + std::cout << "sqr = " << sqr << std::endl; + std::cout << "dlt = " << dlt << std::endl; + std::cout << "mxt = " << mxt << std::endl; + std::cout << std::endl; + } + + std::cout << "sqr/cnt = " << (sqr/cnt) << std::endl; + std::cout << "sum/cnt = " << (sum/cnt) << std::endl; + std::cout << "(sum/cnt)² = " << mln::math::sqr(sum/cnt) << std::endl; + std::cout << "dlt/cnt = " << dlt/cnt << std::endl; + std::cout << "mxt/cnt = " << mxt/cnt << std::endl; + std::cout << std::endl; + + std::cout << "sqr = " + << (sqr) << std::endl; + std::cout << "dlt = " + << (dlt) << std::endl; + std::cout << "cnt*avg² = " + << (mln::math::sqr(sum/cnt)*cnt) << std::endl; + std::cout << "2*mxt = " + << (2*mxt) << std::endl; + std::cout << "sqr - cnt*avg² = " + << (sqr/cnt - mln::math::sqr(sum/cnt)) << std::endl; + std::cout << "(sqr -2*mxt + cnt*avg²) = " + << ((sqr - 2*mxt + mln::math::sqr(sum/cnt))/cnt) << std::endl; + std::cout << std::endl; + return (0 == cnt)? 0 : sqr/cnt - mln::math::sqr(sum/cnt); +} + +template <typename I> +mln_value(I) var_histo(const mln::Image& histo_) +{ + const I& histo = exact(histo_); + + mln_precondition(histo.is_valid()); + + mln_value(I) pos = mln::literal::zero; + mln_value(I) sum = mln::literal::zero; + mln_value(I) sqr = mln::literal::zero; + mln_value(I) cnt = mln::literal::zero; + mln_piter(I) p(histo.domain()); + + for_all(p) + { + pos = p.ind(); + cnt += (histo(p)); + sum += (histo(p)*pos); + sqr += (histo(p)*mln::math::sqr(pos)); + } + + return (0 == cnt)? 0 : sqr/cnt - mln::math::sqr(sum/cnt); +} + +//============================================================================// +// CLASSIFIEUR +//============================================================================// + + +// Linear discriminant analysis in 1d +// With same variance, threshold = (m1+m2)/2 +// With different variance, (m1*sqrt(v1)+m2*sqrt(v2))/(sqrt(v1)+sqrt(v2)) +float threshold_histo(float avg1, float var1, float avg2, float var2) +{ + float sigma1 = mln::math::sqrt(var1); + float sigma2 = mln::math::sqrt(var2); + float threshold = (avg1*sigma1+avg2*sigma2)/(sigma1+sigma2); + + return threshold; +} + +float threshold3_histo(float avg1, float var1, float avg2, float var2) +{ + float threshold = (avg1*var1+avg2*var2)/(var1+var2); + + return threshold; +} + + +// if gaussian without the same variance +float threshold2_histo(float avg1, float var1, float avg2, float var2) +{ + float a = var2 - var1; + float b = -2 * (avg1 * var2 - avg2 * var1); + float c = var2 * mln::math::sqr(avg1) - var1 * mln::math::sqr(avg2); + float d = mln::math::sqr(b) - 4 * a * c; + + if (d < 0) + std::cout << "delta negatif" << std::endl; + + float x1 = (-b+mln::math::sqrt(d))/(2*a); + float x2 = (-b-mln::math::sqrt(d))/(2*a); + + std::cout << "a = " << a << std::endl; + std::cout << "b = " << b << std::endl; + std::cout << "c = " << c << std::endl; + std::cout << "d = " << d << std::endl; + std::cout << "x1 = " << x1 << std::endl; + std::cout << "x2 = " << x2 << std::endl; + + return x2; +} + +template <typename I> +mln_value(I) sqr_histo(const mln::Image& histo_) +{ + const I& histo = exact(histo_); + + mln_precondition(histo.is_valid()); + + mln_value(I) sum = mln::literal::zero; + mln_piter(I) p(histo.domain()); + + for_all(p) + sum += (mln::math::sqr(p.ind())*histo(p)); + + return sum; +} + + +short min_error(const mln::image1d<float> histo_grp1, + const mln::image1d<float> histo_grp2) +{ + float c00[256]; + float c10[256]; + float c01[256]; + float c11[256]; + float err[256]; + + for (short p = 0; p < 256; p++) + { + c00[p] = cnt_histo(histo_grp1|mln::box1d(mln::point1d(0), + mln::point1d(p))); + + c10[p] = cnt_histo(histo_grp1|mln::box1d(mln::point1d(p+1), + mln::point1d(255))); + + c01[p] = cnt_histo(histo_grp2|mln::box1d(mln::point1d(0), + mln::point1d(p))); + + c11[p] = cnt_histo(histo_grp2|mln::box1d(mln::point1d(p+1), + mln::point1d(255))); + } + + short threshold = 0; + float error = c01[0] + c01[0] + c00[0] + c11[0]; + + for(short p = 0; p < 256; p++) + { + err[p] = c10[p] + c01[p]; + + std::cout << " p = " < err[p]) + { + error = err[p]; + threshold = p; + } + } + + return threshold; +} + +// return the threshold +short fisher_analysis(const mln::image1d<float> histo) +{ + typedef mln::value::int_u8 t_int_u8; + + // FIXE ME SIZE const short a = mln_min(t_int_u8); + // float cnt1[a]; + + float cnt1[256]; + float sum1[256]; + float sqr1[256]; + float avg1[256]; + float var1[256]; + + float cnt2[256]; + float sum2[256]; + float sqr2[256]; + float avg2[256]; + float var2[256]; + + float cnt0[256]; // count of points + float sum0[256]; // sum of population + float sqr0[256]; // sqr of population + float avg0[256]; // average of the population + float v_in[256]; // variance with-in class + float v_bw[256]; // variance between class + float var0[256]; // variance of the population + short threshold; + float pos; + float min_var; + + // Assign the first elements + cnt1[0] = 0; + sum1[0] = 0; + sqr1[0] = 0; + avg1[0] = 0; + var1[0] = 0; + + // Compute the stats of the wall histogram + cnt2[0] = 0; + sum2[0] = 0; + sqr2[0] = 0; + + for(short p = 0; p < 256; p++) + { + pos = p; + cnt2[0] += mln::opt::at(histo,p); + sum2[0] += (pos * mln::opt::at(histo,p)); + sqr2[0] += (mln::math::sqr(pos) * mln::opt::at(histo,p)); + } + + avg2[0] = (0 == cnt2[0])? 0 : sum2[0] / cnt2[0]; + var2[0] = (0 == cnt2[0])? 0 : sqr2[0] / cnt2[0] - mln::math::sqr(avg2[0]); + + // watch the array limits + for (short p = 1; p < 256; p++) + { + pos = p; + + // Assign the statistics to the primary class + cnt1[p] = cnt1[p-1] + mln::opt::at(histo, p); + sum1[p] = sum1[p-1] + pos * mln::opt::at(histo, p); + sqr1[p] = sqr1[p-1] + mln::math::sqr(pos) * mln::opt::at(histo, p); + avg1[p] = (0 == cnt1[p])? 0 : (sum1[p] / cnt1[p]); + var1[p] = (0 == cnt1[p])? 0 : ((sqr1[p] / cnt1[p])-mln::math::sqr(avg1[p])); + + // Assign the statistics to the second class + cnt2[p] = cnt2[p-1] - mln::opt::at(histo, p);; + sum2[p] = sum2[p-1] - p * mln::opt::at(histo, p);; + sqr2[p] = sqr2[p-1] - mln::math::sqr(p) * mln::opt::at(histo, p);; + avg2[p] = (0 == cnt2[p])? 0 : (sum2[p] / cnt2[p]); + var2[p] = (0 == cnt2[p])? 0 : ((sqr2[p] / cnt2[p])-mln::math::sqr(avg2[p])); + + // Lets compute the invariants + cnt0[p] = cnt1[p] + cnt2[p]; + sum0[p] = sum1[p] + sum2[p]; + sqr0[p] = sqr1[p] + sqr2[p]; + avg0[p] = (cnt1[p] * avg1[p] + cnt2[p] * avg2[p])/cnt0[p]; + v_in[p] = (cnt1[p] * var1[p] + cnt2[p] * var2[p])/cnt0[p]; + v_bw[p] = (cnt1[p] * mln::math::sqr(avg1[p]-avg0[p]) + + cnt2[p] * mln::math::sqr(avg2[p]-avg0[p]))/cnt0[p]; + var0[p] = v_in[p] + v_bw[p]; + } + + // Find the threshold that minimizes the intra-class variance + min_var = cnt2[0]*var2[0]; + threshold = 0; + + for(short p = 0; p < 256; p++) + { + // Compute the intra-class variance + v_in[p] = cnt1[p]*var1[p] + cnt2[p]*var2[p]; +// std::cout << "var intra[" < v_in[p]) + { + min_var = v_in[p]; + threshold = p; + } + } + + return threshold; +} + + +//============================================================================// +// ERROR (MSE, PNSNR) compression p278 Handbook Color +//============================================================================// + +float error_test(const std::string original, + const std::string reduced) + +{ + + typedef mln::value::rgb8 t_rgb8; + typedef mln::value::int_u8 t_int_u8; + typedef mln::fun::v2v::component<t_rgb8,0> t_component_red; + typedef mln::fun::v2v::component<t_rgb8,1> t_component_green; + typedef mln::fun::v2v::component<t_rgb8,2> t_component_blue; + typedef mln::accu::meta::stat::mean t_mean; + typedef mln::accu::meta::stat::histo1d t_histo; + typedef mln::image2d<t_int_u8> t_img; + typedef mln_trait_op_minus_(t_img,t_img) t_minus; + typedef mln_trait_op_times_(t_minus,t_minus) t_times; + + mln::image2d<mln::value::rgb8> original_rgb8; + mln::image2d<mln::value::rgb8> reduced_rgb8; + + mln::image2d<mln::value::int_u8> original_red; + mln::image2d<mln::value::int_u8> original_green; + mln::image2d<mln::value::int_u8> original_blue; + + mln::image2d<mln::value::int_u8> reduced_red; + mln::image2d<mln::value::int_u8> reduced_green; + mln::image2d<mln::value::int_u8> reduced_blue; + +// mln::image2d<mln::value::int_u8> map_red; +// mln::image2d<mln::value::int_u8> map_green; +// mln::image2d<mln::value::int_u8> map_blue; + +// mln::image1d<unsigned> histo_red; +// mln::image1d<unsigned> histo_green; +// mln::image1d<unsigned> histo_blue; + + t_minus minus_red; + t_minus minus_green; + t_minus minus_blue; + + t_times times_red; + t_times times_green; + t_times times_blue; + + float error_red; + float error_green; + float error_blue; + + float error; + + + mln::io::ppm::load(original_rgb8, original.c_str()); + mln::io::ppm::load(reduced_rgb8, reduced.c_str()); + + original_red = mln::data::transform(original_rgb8, t_component_red()); + original_green = mln::data::transform(original_rgb8, t_component_green()); + original_blue = mln::data::transform(original_rgb8, t_component_blue()); + + reduced_red = mln::data::transform(reduced_rgb8, t_component_red()); + reduced_green = mln::data::transform(reduced_rgb8, t_component_green()); + reduced_blue = mln::data::transform(reduced_rgb8, t_component_blue()); + + minus_red = (original_red - reduced_red); + times_red = minus_red * minus_red; + + minus_green = (original_green - reduced_green); + times_green = minus_green * minus_green; + + minus_blue = (original_blue - reduced_blue); + times_blue = minus_blue * minus_blue; + + error_red = mln::data::compute(t_mean(), times_red); + error_green = mln::data::compute(t_mean(), times_green); + error_blue = mln::data::compute(t_mean(), times_blue); + +// map_red = mln::data::stretch(t_int_u8(), times_red); +// map_green = mln::data::stretch(t_int_u8(), times_blue); +// map_blue = mln::data::stretch(t_int_u8(), times_green); + +// histo_red = mln::data::compute(t_histo(), map_red); +// histo_green = mln::data::compute(t_histo(), map_green); +// histo_blue = mln::data::compute(t_histo(), map_blue); + +// mln::io::plot::save_image_sh(histo_red, "histo_red.sh"); +// mln::io::plot::save_image_sh(histo_green,"histo_green.sh"); +// mln::io::plot::save_image_sh(histo_blue, "histo_blue.sh"); + +// mln::io::pgm::save(map_red, "red.pgm"); +// mln::io::pgm::save(map_green,"green.pgm"); +// mln::io::pgm::save(map_blue, "blue.pgm"); + + error = (error_red + error_green + error_blue)/3.0; + error = mln::math::sqrt(error); + error = 20 * log(255/error); + +// Le PNSNR semble offrir plus d'espace pour la discrimination +// Si les images sont identiques ==> PNSNR = +inf +// Si les images sont très différentes ==> PNSNR = 0 + + return error; +} + + +//============================================================================// +// MAIN +//============================================================================// + + +int main2() +{ + float val = error_test(AFP_PPM_IMG_PATH"/000_APP2003011515775.ppm", + AFP_GMP10_IMG_PATH"/000_APP2003011515775.ppm"); + + std::cout << val << std::endl; + + return 0; +} + +int main() +{ + typedef boost::filesystem::path t_path; + typedef boost::filesystem::directory_iterator t_iter_path; + + mln::image1d<float> histo(256); + mln::image1d<float> histo_grp[2]; // histo by group + + histo_grp[0].init_(mln::box1d(mln::point1d(0),mln::point1d(255))); + histo_grp[1].init_(mln::box1d(mln::point1d(0),mln::point1d(255))); + + mln::data::fill(histo, mln::literal::zero); + mln::data::fill(histo_grp[0], mln::literal::zero); + mln::data::fill(histo_grp[1], mln::literal::zero); + + t_path original_path[] = {ICDAR_20P_INPUT_IMG_PATH, + AFP_PPM_IMG_PATH}; + +// t_path reduced1_path[] = {ICDAR_20P_MGK30_IMG_PATH, +// AFP_MGK30_IMG_PATH}; + +// t_path reduced1_path[] = {ICDAR_20P_MGK20_IMG_PATH, +// AFP_MGK20_IMG_PATH}; + + t_path reduced1_path[] = {ICDAR_20P_MGK10_IMG_PATH, + AFP_MGK10_IMG_PATH}; + +// t_path reduced2_path[] = {ICDAR_20P_GMP30_IMG_PATH, +// AFP_GMP30_IMG_PATH}; + +// t_path reduced2_path[] = {ICDAR_20P_GMP20_IMG_PATH, +// AFP_GMP20_IMG_PATH}; + + t_path reduced2_path[] = {ICDAR_20P_GMP10_IMG_PATH, + AFP_GMP10_IMG_PATH}; + + + std::cout << "#!/usr/bin/gnuplot" << std::endl; + std::cout << "set terminal x11 persist 1" << std::endl; + std::cout << "ERROR" << std::endl; + std::cout << "plot '-' using 1 with point notitle,\\" << std::endl; + std::cout << " '-' using 1 with point notitle" << std::endl; + + for (int i = 0; i < 2; i++) + { + if (boost::filesystem::exists(original_path[i]) && + boost::filesystem::exists(reduced1_path[i]) && + boost::filesystem::exists(reduced2_path[i]) && + boost::filesystem::is_directory(original_path[i]) && + boost::filesystem::is_directory(reduced1_path[i]) && + boost::filesystem::is_directory(reduced2_path[i])) + { + boost::filesystem::system_complete(original_path[i]); + const t_iter_path end_iter; + float error1 = 0.0; + float error2 = 0.0; + t_path leaf; + t_path reduced1_file; + t_path reduced2_file; + + for (t_iter_path dir_iter(original_path[i]);end_iter!=dir_iter;++dir_iter) + { + leaf = dir_iter->path().leaf(); + reduced1_file = reduced1_path[i] / leaf; + reduced2_file = reduced2_path[i] / leaf; + + error1 = error_test(dir_iter->path().string(), reduced1_file.string()); + error2 = error_test(dir_iter->path().string(), reduced2_file.string()); + + float a1 = 1; + short v1 = (short)mln::math::floor(error2+0.4999); + mln::opt::at(histo,v1) += a1; + mln::opt::at(histo_grp[i],v1) += a1; + +// float a1 = error2 - mln::math::floor(error2); +// float a2 = mln::math::ceil(error2) - error2; +// short v1 = (short)mln::math::floor(error2); +// short v2 = (short)mln::math::ceil(error2); +// mln::opt::at(histo,v1) += a1; +// mln::opt::at(histo,v2) += a2; +// mln::opt::at(histo_grp[i],v1) += a1; +// mln::opt::at(histo_grp[i],v2) += a2; + + std::cout << error1 << " "; + std::cout << error2 << " "; + std::cout << "# " << dir_iter->path().leaf() << std::endl; + } + std::cout << "e" << std::endl; + } + } + + mln::io::plot::save_image_sh(histo, "histo.sh"); + mln::io::plot::save_image_sh(histo_grp[1], "histo_grp1.sh"); + mln::io::plot::save_image_sh(histo_grp[0], "histo_grp2.sh"); + + float threshold = fisher_analysis(histo); + float threshold2 = threshold_histo(avg_histo(histo_grp[1]), + var_histo(histo_grp[1]), + avg_histo(histo_grp[0]), + var_histo(histo_grp[0])); + float threshold3 = threshold2_histo(avg_histo(histo_grp[1]), + var_histo(histo_grp[1]), + avg_histo(histo_grp[0]), + var_histo(histo_grp[0])); + float threshold4 = min_error(histo_grp[1],histo_grp[0]); + + std::cout << "threshold = " << threshold << std::endl; + std::cout << "threshold2 = " << threshold2 << std::endl; + std::cout << "threshold3 = " << threshold3 << std::endl; + std::cout << "threshold4 = " << threshold4 << std::endl; + std::cout << "avg_grp1 = " << avg_histo(histo_grp[1]) << std::endl; + std::cout << "avg_grp2 = " << avg_histo(histo_grp[0]) << std::endl; + + // compute the classification matrix + // for each sub population + + float c00 = cnt_histo(histo_grp[1] | mln::box1d(mln::point1d(0), + mln::point1d(threshold))); + + float c10 = cnt_histo(histo_grp[1] | mln::box1d(mln::point1d(threshold+1), + mln::point1d(255))); + + float c01 = cnt_histo(histo_grp[0] | mln::box1d(mln::point1d(0), + mln::point1d(threshold))); + + float c11 = cnt_histo(histo_grp[0] | mln::box1d(mln::point1d(threshold+1), + mln::point1d(255))); + + + std::cout << "pop0 = " << cnt_histo(histo_grp[1]) << std::endl; + std::cout << "pop1 = " << cnt_histo(histo_grp[0]) << std::endl; + std::cout << std::endl; + + std::cout << "c00 = " << c00 << std::endl; + std::cout << "c10 = " << c10 << std::endl; + std::cout << "c01 = " << c01 << std::endl; + std::cout << "c11 = " << c11 << std::endl; + + return 0; +} -- 1.5.6.5

14 years, 1 month

last-svn-commit-30-gde4f736 Benchmark few descriptors.

by Yann Jacquelet

* green/exp/annotating/bench: New directory. * green/exp/annotating/bench/Makefile.am: New Makefile. * green/exp/annotating/bench/bench.cc: New source. --- milena/sandbox/ChangeLog | 8 + .../annotating/{achromastism => bench}/Makefile.am | 0 milena/sandbox/green/exp/annotating/bench/bench.cc | 1213 ++++++++++++++++++++ 3 files changed, 1221 insertions(+), 0 deletions(-) copy milena/sandbox/green/exp/annotating/{achromastism => bench}/Makefile.am (100%) create mode 100644 milena/sandbox/green/exp/annotating/bench/bench.cc diff --git a/milena/sandbox/ChangeLog b/milena/sandbox/ChangeLog index 0086d22..7489f70 100644 --- a/milena/sandbox/ChangeLog +++ b/milena/sandbox/ChangeLog @@ -1,5 +1,13 @@ 2010-06-21 Yann Jacquelet <jacquelet(a)lrde.epita.fr> + Benchmark few descriptors. + + * green/exp/annotating/bench: New directory. + * green/exp/annotating/bench/Makefile.am: New Makefile. + * green/exp/annotating/bench/bench.cc: New source. + +2010-06-21 Yann Jacquelet <jacquelet(a)lrde.epita.fr> + Test on image database the achromatism descriptor. * green/exp/annotating/achromatism/Makefile.am: New Makefile. diff --git a/milena/sandbox/green/exp/annotating/achromastism/Makefile.am b/milena/sandbox/green/exp/annotating/bench/Makefile.am similarity index 100% copy from milena/sandbox/green/exp/annotating/achromastism/Makefile.am copy to milena/sandbox/green/exp/annotating/bench/Makefile.am diff --git a/milena/sandbox/green/exp/annotating/bench/bench.cc b/milena/sandbox/green/exp/annotating/bench/bench.cc new file mode 100644 index 0000000..8e4525f --- /dev/null +++ b/milena/sandbox/green/exp/annotating/bench/bench.cc @@ -0,0 +1,1213 @@ +// BENCH TEST CF MILLET 2008 + +#include <iostream> +#include <sstream> +#include <boost/filesystem.hpp> + +#include <mln/algebra/vec.hh> + +#include <mln/img_path.hh> + +#include <mln/accu/stat/mean.hh> +#include <mln/accu/stat/histo1d.hh> + +#include <mln/arith/minus.hh> +#include <mln/arith/times.hh> +#include <mln/arith/diff_abs.hh> +#include <mln/arith/div.hh> + +#include <mln/core/image/image1d.hh> +#include <mln/core/image/image2d.hh> +#include <mln/core/image/dmorph/image_if.hh> +#include <mln/core/alias/point1d.hh> +#include <mln/core/alias/box1d.hh> + +#include <mln/data/transform.hh> +#include <mln/data/compute.hh> +#include <mln/data/convert.hh> +#include <mln/data/stretch.hh> +#include <mln/data/fill.hh> + +#include <mln/fun/v2v/component.hh> +#include <mln/fun/v2v/rgb_to_hue_map.hh> +#include <mln/fun/v2v/rgb_to_saturation_map.hh> +#include <mln/fun/v2v/rgb_to_value_map.hh> + +#include <mln/io/ppm/load.hh> +#include <mln/io/pgm/save.hh> +#include <mln/io/plot/save_image_sh.hh> + +#include <mln/literal/zero.hh> + +#include <mln/math/ceil.hh> +#include <mln/math/floor.hh> + +#include <mln/opt/at.hh> + +#include <mln/trait/value_.hh> + +#include <mln/value/rgb8.hh> + + +#include <mln/value/int_u8.hh> + +template <typename I> +mln_value(I) count_histo(const mln::Image& histo_) +{ + const I& histo = exact(histo_); + + mln_precondition(histo.is_valid()); + + mln_value(I) result = mln::literal::zero; + mln_piter(I) p(histo.domain()); + + for_all(p) + result += histo(p); + + return result; +} + + +template <typename I> +mln_value(I) sum_frequency_histo(const mln::Image& histo_) +{ + const I& histo = exact(histo_); + + mln_precondition(histo.is_valid()); + + mln_value(I) sum = mln::literal::zero; + mln_piter(I) p(histo.domain()); + + for_all(p) + sum += histo(p); + + return sum; +} + + +template <typename I> +mln_coord(mln_site_(I)) peak_histo(const mln::Image& histo_) +{ + const I& histo = exact(histo_); + + mln_precondition(histo.is_valid()); + + // Find the peak of the histogram + mln_value(I) v_max = mln::opt::at(histo, mln::literal::zero); + mln_coord(mln_site_(I)) p_max = mln::literal::zero; + mln_piter(I) p(histo.domain()); + + for_all(p) + { + if (v_max < histo(p)) + { + v_max = histo(p); + p_max = p.ind(); + } + } + + return p_max; +} + + +//============================================================================// +// MILLET HUE DESCRIPTOR +// +// This test is used for discrimination between black and white pictures and +// color ones. Some colored Black and white pictures have their energy near +// the peak. +//============================================================================// + +float hue1_descriptor(mln::image1d<unsigned> histo, const short threshold) +{ + float cnt1; + float cnt2; + float prop; + short peak; + mln::point1d inf; + mln::point1d sup; + + peak = peak_histo(histo); + inf = mln::point1d(mln::math::max(0, peak-threshold)); + sup = mln::point1d(mln::math::min(255, peak+threshold)); + cnt1 = count_histo(histo|mln::box1d(inf,sup)); + cnt2 = count_histo(histo); + prop = ((255.0 * cnt1) / cnt2); + + return prop; +} + + +//============================================================================// +// MILLET SATURATION DESCRIPTOR +// +// This test is used for discrimination between black and white pictures and +// color ones. Black and white pictures have their energy in the low saturation +// band. +//============================================================================// + +float sat1_descriptor(mln::image1d<unsigned> histo, const short threshold) +{ + float cnt1; + float cnt2; + float result; + + cnt1 = count_histo(histo | mln::box1d(mln::point1d(0), + mln::point1d(threshold))); + cnt2 = count_histo(histo); + result = ((255.0 * cnt1) / cnt2); + + return result; + color = label_hue(peak);} + + +//============================================================================// +// MILLET DESCRIPTOR +// +// This test aims at compute the number of grey levels. Photographies tends to +// use all the levels or many of them. +//============================================================================// + +template <typename I> +mln_value(I) count_null_frequency_histo(const mln::Image& histo_) +{ + const I& histo = exact(histo_); + + mln_precondition(histo.is_valid()); + + mln_value(I) count = mln::literal::zero; + mln_piter(I) p(histo.domain()); + + for_all(p) + if (0 == histo(p)) + count++; + + return count; +} + + +float lvl0_descriptor(mln::image1d<unsigned> histo) +{ + float result; + + // FIXME 255 + result = 255-count_null_frequency_histo(histo); + + return result; +} + +//============================================================================// +// DENSITY DESCRIPTOR +// +// +//============================================================================// + +template <typename I> +float cmp_equi_frequency_histo(const mln::Image& histo_) +{ + const I& histo = exact(histo_); + + mln_precondition(histo.is_valid()); + + float sum = 0; + float var = 0; + + mln_piter(I) p(histo.domain()); + + for_all(p) + { + sum ++; + var += mln::math::sqr(histo(p) - (1/256.0)); + } + + var = var / sum; + + return var; +} + +float hue0_descriptor(mln::image1d<unsigned> histo) +{ + mln::image1d<float> histo_float; + float sum; + float result; + + sum = sum_frequency_histo(histo); + histo_float = mln::data::convert(float(), histo) / sum; + result = cmp_equi_frequency_histo(histo_float); + + return result*255; +} + + +float sat0_descriptor(mln::image1d<unsigned> histo) +{ + mln::image1d<float> histo_float; + float sum; + float result; + + sum = sum_frequency_histo(histo); + histo_float = mln::data::convert(float(), histo) / sum; + result = cmp_equi_frequency_histo(histo_float); + + return result*255; +} + +float val0_descriptor(mln::image1d<unsigned> histo) +{ + mln::image1d<float> histo_float; + float sum; + float result; + + sum = sum_frequency_histo(histo); + histo_float = mln::data::convert(float(), histo) / sum; + result = cmp_equi_frequency_histo(histo_float); + + return result*255; +} + +//============================================================================// +// MILLET DESCRIPTOR +// +// This test aims at compute some deviation on the peak of the histogram of +// the image. Large deviations mean lots of graduation in colors (such as +// photos) and small ones mean something like cartoon. +//============================================================================// + + +// calcul de contribution +float r(short p, unsigned histo_p, short x, unsigned histo_x) +{ + float result = mln::math::sqr(((float)histo_x / histo_p) * (x-p)); + + return result; +} + +template <typename I> +float stddev3(const mln::Image& histo_, unsigned peak) +{ + const I& histo = exact(histo_); + + mln_precondition(histo.is_valid()); + + // Compute stddev + + float stddev = 0.0; + + mln_piter(I) p(histo.domain()); + + for_all(p) + { + stddev += r((short)peak, mln::opt::at(histo,peak), p.ind(), histo(p)); + } + + return stddev; +} + +template <typename I> +float stddev2(const mln::Image& histo_, unsigned peak, unsigned limit) +{ + const I& histo = exact(histo_); + + mln_precondition(histo.is_valid()); + + float stddev_low = 0.0; + float stddev_up = 0.0; + float ret = 0.0; + + // A transformer avec des iterators + + if (250 > peak) + stddev_up = stddev3(histo |mln::box1d(mln::point1d(peak+1), + mln::point1d(peak+limit)), peak); + + if (5 < peak) + stddev_low = stddev3(histo |mln::box1d(mln::point1d(peak-limit), + mln::point1d(peak-1)), peak); + + ret = (250 < peak)? stddev_low : (5 > peak)? stddev_up : + (stddev_low + stddev_up)/2; + + return ret; +} + +float var0_descriptor(mln::image1d<unsigned> histo, const short threshold) +{ + typedef mln::fun::v2v::rgb_to_value_map<8> t_rgb_to_value_map; + + float result; + short peak; + + peak = peak_histo(histo); + result = stddev2(histo, peak, threshold); + + return result; +} + + +//============================================================================// +// ERROR DESCRIPTOR +//============================================================================// + + +float err_descriptor(mln::image2d<mln::value::int_u8> r_img_map, + mln::image2d<mln::value::int_u8> g_img_map, + mln::image2d<mln::value::int_u8> b_img_map, + mln::image2d<mln::value::int_u8> r_rdc_map, + mln::image2d<mln::value::int_u8> g_rdc_map, + mln::image2d<mln::value::int_u8> b_rdc_map) + + +{ + typedef mln::accu::meta::stat::mean t_mean; + typedef mln::image2d<mln::value::int_u8> t_map; + typedef mln_trait_op_minus_(t_map,t_map) t_minus; + typedef mln_trait_op_times_(t_minus,t_minus) t_times; + + + t_minus minus_red; + t_minus minus_green; + t_minus minus_blue; + + t_times times_red; + t_times times_green; + t_times times_blue; + + float error_red; + float error_green; + float error_blue; + + float error; + + minus_red = (r_img_map - r_rdc_map); + times_red = minus_red * minus_red; + + minus_green = (g_img_map - g_rdc_map); + times_green = minus_green * minus_green; + + minus_blue = (b_img_map - b_rdc_map); + times_blue = minus_blue * minus_blue; + + error_red = mln::data::compute(t_mean(), times_red); + error_green = mln::data::compute(t_mean(), times_green); + error_blue = mln::data::compute(t_mean(), times_blue); + + error = (error_red + error_green + error_blue)/3.0; + error = mln::math::sqrt(error); + error = 20 * log(255/error); + +// Le PNSNR semble offrir plus d'espace pour la discrimination +// Si les images sont identiques ==> PNSNR = +inf +// Si les images sont très différentes ==> PNSNR = 0 + // FIXME METTRE UN MAX A 255 + + return error; +} + + + +//============================================================================// +// CLASSIFICATION DE FISHER EN 2 CLASSES SUR UN HISTO 1D +//============================================================================// + +template <typename I> +mln_value(I) cnt_histo(const mln::Image& histo_) +{ + const I& histo = exact(histo_); + + mln_precondition(histo.is_valid()); + + mln_value(I) sum = mln::literal::zero; + mln_piter(I) p(histo.domain()); + + for_all(p) + { + sum += histo(p); + } + + return sum; +} + +template <typename I> +mln_value(I) sum_histo(const mln::Image& histo_) +{ + const I& histo = exact(histo_); + + mln_precondition(histo.is_valid()); + + mln_value(I) pos = mln::literal::zero; + mln_value(I) sum = mln::literal::zero; + mln_piter(I) p(histo.domain()); + + for_all(p) + { + pos = p.ind(); + sum += pos*histo(p); + } + + return sum; +} + +template <typename I> +mln_value(I) avg_histo(const mln::Image& histo_) +{ + const I& histo = exact(histo_); + + mln_precondition(histo.is_valid()); + + mln_value(I) pos = mln::literal::zero; + mln_value(I) sum = mln::literal::zero; + mln_value(I) cnt = mln::literal::zero; + mln_piter(I) p(histo.domain()); + + for_all(p) + { + pos = p.ind(); + cnt += histo(p); + sum += pos*histo(p); + } + + return (0 == cnt)? 0 : sum/cnt; +} + +template <typename I> +mln_value(I) var3_histo(const mln::Image& histo_, float mean) +{ + const I& histo = exact(histo_); + + mln_precondition(histo.is_valid()); + + mln_value(I) pos = mln::literal::zero; + mln_value(I) sum = mln::literal::zero; + mln_value(I) cnt = mln::literal::zero; + mln_piter(I) p(histo.domain()); + + for_all(p) + { + cnt += histo(p); + sum += (mln::math::sqr(p.ind()-mean)*histo(p)); + } + + return (0 == cnt)? 0 : sum/cnt; +} + +template <typename I> +mln_value(I) var2_histo(const mln::Image& histo_, float mean) +{ + const I& histo = exact(histo_); + + mln_precondition(histo.is_valid()); + + mln_value(I) pos = mln::literal::zero; + mln_value(I) sum = mln::literal::zero; + mln_value(I) sqr = mln::literal::zero; + mln_value(I) cnt = mln::literal::zero; + mln_value(I) dlt = mln::literal::zero; + mln_value(I) mxt = mln::literal::zero; + mln_piter(I) p(histo.domain()); + + for_all(p) + { + pos = p.ind(); + cnt += (histo(p)); + sum += (histo(p)*pos); + mxt += (histo(p)*pos*mean); + sqr += (histo(p)*mln::math::sqr(pos)); + dlt += (histo(p)*mln::math::sqr(pos - mean)); + + std::cout << "p = " << pos << std::endl; + std::cout << "p² = " << mln::math::sqr(pos) << std::endl; + std::cout << "p*mean = " << (pos*mean) << std::endl; + std::cout << "p-mean = " << (pos-mean) << std::endl; + std::cout << "(p-mean)² = " << mln::math::sqr(pos-mean) << std::endl; + std::cout << "histo(p) = " << histo(p) << std::endl; + std::cout << "histo(p)*p = " << (pos*histo(p)) << std::endl; + std::cout << "histo(p)*p²= " << (mln::math::sqr(pos)*histo(p)) + << std::endl; + std::cout << "cnt = " << cnt << std::endl; + std::cout << "sum = " << sum << std::endl; + std::cout << "sqr = " << sqr << std::endl; + std::cout << "dlt = " << dlt << std::endl; + std::cout << "mxt = " << mxt << std::endl; + std::cout << std::endl; + } + + std::cout << "sqr/cnt = " << (sqr/cnt) << std::endl; + std::cout << "sum/cnt = " << (sum/cnt) << std::endl; + std::cout << "(sum/cnt)² = " << mln::math::sqr(sum/cnt) << std::endl; + std::cout << "dlt/cnt = " << dlt/cnt << std::endl; + std::cout << "mxt/cnt = " << mxt/cnt << std::endl; + std::cout << std::endl; + + std::cout << "sqr = " + << (sqr) << std::endl; + std::cout << "dlt = " + << (dlt) << std::endl; + std::cout << "cnt*avg² = " + << (mln::math::sqr(sum/cnt)*cnt) << std::endl; + std::cout << "2*mxt = " + << (2*mxt) << std::endl; + std::cout << "sqr - cnt*avg² = " + << (sqr/cnt - mln::math::sqr(sum/cnt)) << std::endl; + std::cout << "(sqr -2*mxt + cnt*avg²) = " + << ((sqr - 2*mxt + mln::math::sqr(sum/cnt))/cnt) << std::endl; + std::cout << std::endl; + return (0 == cnt)? 0 : sqr/cnt - mln::math::sqr(sum/cnt); +} + +template <typename I> +mln_value(I) var_histo(const mln::Image& histo_) +{ + const I& histo = exact(histo_); + + mln_precondition(histo.is_valid()); + + mln_value(I) pos = mln::literal::zero; + mln_value(I) sum = mln::literal::zero; + mln_value(I) sqr = mln::literal::zero; + mln_value(I) cnt = mln::literal::zero; + mln_piter(I) p(histo.domain()); + + for_all(p) + { + pos = p.ind(); + cnt += (histo(p)); + sum += (histo(p)*pos); + sqr += (histo(p)*mln::math::sqr(pos)); + } + + return (0 == cnt)? 0 : sqr/cnt - mln::math::sqr(sum/cnt); +} + +//============================================================================// +// CLASSIFIEUR +//============================================================================// + + +// Linear discriminant analysis in 1d +// With same variance, threshold = (m1+m2)/2 +// With different variance, (m1*sqrt(v1)+m2*sqrt(v2))/(sqrt(v1)+sqrt(v2)) +float threshold_histo(float avg1, float var1, float avg2, float var2) +{ + float sigma1 = mln::math::sqrt(var1); + float sigma2 = mln::math::sqrt(var2); + float threshold = (avg1*sigma1+avg2*sigma2)/(sigma1+sigma2); + + return threshold; +} + +float threshold3_histo(float avg1, float var1, float avg2, float var2) +{ + float threshold = (avg1*var1+avg2*var2)/(var1+var2); + + return threshold; +} + + +// if gaussian without the same variance +float threshold2_histo(float avg1, float var1, float avg2, float var2) +{ + float a = var2 - var1; + float b = -2 * (avg1 * var2 - avg2 * var1); + float c = var2 * mln::math::sqr(avg1) - var1 * mln::math::sqr(avg2); + float d = mln::math::sqr(b) - 4 * a * c; + + if (d < 0) + std::cout << "delta negatif" << std::endl; + + float x1 = (-b+mln::math::sqrt(d))/(2*a); + float x2 = (-b-mln::math::sqrt(d))/(2*a); + + std::cout << "a = " << a << std::endl; + std::cout << "b = " << b << std::endl; + std::cout << "c = " << c << std::endl; + std::cout << "d = " << d << std::endl; + std::cout << "x1 = " << x1 << std::endl; + std::cout << "x2 = " << x2 << std::endl; + + return x2; +} + +template <typename I> +mln_value(I) sqr_histo(const mln::Image& histo_) +{ + const I& histo = exact(histo_); + + mln_precondition(histo.is_valid()); + + mln_value(I) sum = mln::literal::zero; + mln_piter(I) p(histo.domain()); + + for_all(p) + sum += (mln::math::sqr(p.ind())*histo(p)); + + return sum; +} + + +short min_error(const mln::image1d<float> histo_grp1, + const mln::image1d<float> histo_grp2, + float *_c00, float *_c10, float *_c01, float *_c11) +{ + float c00[256]; + float c10[256]; + float c01[256]; + float c11[256]; + float err[256]; + + for (short p = 0; p < 256; p++) + { + c00[p] = cnt_histo(histo_grp1|mln::box1d(mln::point1d(0), + mln::point1d(p))); + + c10[p] = cnt_histo(histo_grp1|mln::box1d(mln::point1d(p+1), + mln::point1d(255))); + + c01[p] = cnt_histo(histo_grp2|mln::box1d(mln::point1d(0), + mln::point1d(p))); + + c11[p] = cnt_histo(histo_grp2|mln::box1d(mln::point1d(p+1), + mln::point1d(255))); + } + + short threshold = 0; + float error = c01[0] + c01[0] + c00[0] + c11[0]; + + for(short p = 0; p < 256; p++) + { + err[p] = c10[p] + c01[p]; + +// std::cout << " p = " << p +// << ";c00 = " << c00[p] +// << ";c10 = " << c10[p] +// << ";c01 = " << c01[p] +// << ";c11 = " << c11[p] +// << std::endl; +// std::cout << "err[" < err[p]) + { + error = err[p]; + threshold = p; + } + } + + *_c00 = c00[threshold]; + *_c10 = c10[threshold]; + *_c01 = c01[threshold]; + *_c11 = c11[threshold]; + + return threshold; +} + +// return the threshold +short fisher_analysis(const mln::image1d<float> histo) +{ + typedef mln::value::int_u8 t_int_u8; + + // FIXE ME SIZE const short a = mln_min(t_int_u8); + // float cnt1[a]; + + float cnt1[256]; + float sum1[256]; + float sqr1[256]; + float avg1[256]; + float var1[256]; + + float cnt2[256]; + float sum2[256]; + float sqr2[256]; + float avg2[256]; + float var2[256]; + + float cnt0[256]; // count of points + float sum0[256]; // sum of population + float sqr0[256]; // sqr of population + float avg0[256]; // average of the population + float v_in[256]; // variance with-in class + float v_bw[256]; // variance between class + float var0[256]; // variance of the population + short threshold; + float pos; + float min_var; + + // Assign the first elements + cnt1[0] = 0; + sum1[0] = 0; + sqr1[0] = 0; + avg1[0] = 0; + var1[0] = 0; + + // Compute the stats of the wall histogram + cnt2[0] = 0; + sum2[0] = 0; + sqr2[0] = 0; + + for(short p = 0; p < 256; p++) + { + pos = p; + cnt2[0] += mln::opt::at(histo,p); + sum2[0] += (pos * mln::opt::at(histo,p)); + sqr2[0] += (mln::math::sqr(pos) * mln::opt::at(histo,p)); + } + + avg2[0] = (0 == cnt2[0])? 0 : sum2[0] / cnt2[0]; + var2[0] = (0 == cnt2[0])? 0 : sqr2[0] / cnt2[0] - mln::math::sqr(avg2[0]); + + // watch the array limits + for (short p = 1; p < 256; p++) + { + pos = p; + + // Assign the statistics to the primary class + cnt1[p] = cnt1[p-1] + mln::opt::at(histo, p); + sum1[p] = sum1[p-1] + pos * mln::opt::at(histo, p); + sqr1[p] = sqr1[p-1] + mln::math::sqr(pos) * mln::opt::at(histo, p); + avg1[p] = (0 == cnt1[p])? 0 : (sum1[p] / cnt1[p]); + var1[p] = (0 == cnt1[p])? 0 : ((sqr1[p] / cnt1[p])-mln::math::sqr(avg1[p])); + + // Assign the statistics to the second class + cnt2[p] = cnt2[p-1] - mln::opt::at(histo, p);; + sum2[p] = sum2[p-1] - p * mln::opt::at(histo, p);; + sqr2[p] = sqr2[p-1] - mln::math::sqr(p) * mln::opt::at(histo, p);; + avg2[p] = (0 == cnt2[p])? 0 : (sum2[p] / cnt2[p]); + var2[p] = (0 == cnt2[p])? 0 : ((sqr2[p] / cnt2[p])-mln::math::sqr(avg2[p])); + + // Lets compute the invariants + cnt0[p] = cnt1[p] + cnt2[p]; + sum0[p] = sum1[p] + sum2[p]; + sqr0[p] = sqr1[p] + sqr2[p]; + avg0[p] = (cnt1[p] * avg1[p] + cnt2[p] * avg2[p])/cnt0[p]; + v_in[p] = (cnt1[p] * var1[p] + cnt2[p] * var2[p])/cnt0[p]; + v_bw[p] = (cnt1[p] * mln::math::sqr(avg1[p]-avg0[p]) + + cnt2[p] * mln::math::sqr(avg2[p]-avg0[p]))/cnt0[p]; + var0[p] = v_in[p] + v_bw[p]; + } + + // Find the threshold that minimizes the intra-class variance + min_var = cnt2[0]*var2[0]; + threshold = 0; + + for(short p = 0; p < 256; p++) + { + // Compute the intra-class variance + v_in[p] = cnt1[p]*var1[p] + cnt2[p]*var2[p]; +// std::cout << "var intra[" < v_in[p]) + { + min_var = v_in[p]; + threshold = p; + } + } + + return threshold; +} + + + + +//============================================================================// +// MAIN +//============================================================================// + + + + + +#define LVL0_DESCR 0 +#define HUE0_DESCR 1 +#define HUE1_DESCR 2 +#define SAT0_DESCR 3 +#define SAT1_DESCR 4 +#define VAL0_DESCR 5 +#define VAL1_DESCR 6 +#define GMP0_DESCR 7 +#define GMP1_DESCR 8 +#define GMP2_DESCR 9 +#define MGK0_DESCR 9 +#define MGK1_DESCR 10 +#define MGK2_DESCR 11 + +#define MGK_DESCR(version) (MGK0_DESCR + version) +#define GMP_DESCR(version) (GMP0_DESCR + version) + +#define NB_DESCR 12 +#define NB_DATABASE 2 +#define NB_IMAGE 110 +#define NB_VERSION 3 + + +void init_descriptors(std::string file_name[], + float result[][NB_DESCR], + int size[]) +{ + for (int i = 0; i < NB_IMAGE; i++) + { + file_name[i] = std::string("PGM"); + + for (int d = 0; d < NB_DESCR; d++) + result[i][d] = (i*d) % 256; + } + + size[0] = 62; + size[1] = 48; +} + + +void dump_descriptors(const std::string file_name[], + const float result[][NB_DESCR], + const int size[]) +{ + std::cout << "#!/usr/bin/gnuplot" << std::endl; + std::cout << "set terminal x11 persist 1" << std::endl; + std::cout << "plot '-' using 2 with point title 'ICDAR',\\" << std::endl; + std::cout << " '-' using 2 with point title 'AFP'" << std::endl; + + int num = 0; + + for (int db = 0; db < NB_DATABASE; db++) + { + for (int i = 0; i < size[db]; i++) + { + std::cout << result[num][LVL0_DESCR] << " "; + std::cout << result[num][HUE0_DESCR] << " "; + std::cout << result[num][HUE1_DESCR] << " "; + std::cout << result[num][SAT0_DESCR] << " "; + std::cout << result[num][SAT1_DESCR] << " "; + std::cout << result[num][VAL0_DESCR] << " "; + std::cout << result[num][VAL1_DESCR] << " "; + std::cout << result[num][GMP0_DESCR] << " "; + std::cout << result[num][GMP1_DESCR] << " "; + std::cout << result[num][GMP2_DESCR] << " "; + std::cout << result[num][MGK0_DESCR] << " "; + std::cout << result[num][MGK1_DESCR] << " "; + std::cout << result[num][MGK2_DESCR] << " "; + std::cout << " # " << file_name[num] << std::endl; + num++; + } + + std::cout << "e" << std::endl; + } +} + +void compute_histo(const float result[][NB_DESCR], + const int size[], + mln::image1d<float> histo[][NB_DATABASE]) +{ + for (int i = 0; i < NB_DESCR; i++) + for (int db = 0; db < NB_DATABASE; db++) + { + histo[i][db].init_(mln::box1d(mln::point1d(0),mln::point1d(255))); + + mln::data::fill(histo[i][db], mln::literal::zero); + } + + short v; + int num = 0; + + for (int db = 0; db < NB_DATABASE; db++) + { + for (int i = 0; i < size[db]; i++) + { + v = (short)mln::math::floor(result[num][VAR0_DESCR]+0.4999); + mln::opt::at(histo[VAR0_DESCR][db],v)++; + + v = (short)mln::math::floor(result[num][LVL0_DESCR]+0.4999); + mln::opt::at(histo[LVL0_DESCR][db],v)++; + + v = (short)mln::math::floor(result[num][HUE0_DESCR]+0.4999); + mln::opt::at(histo[HUE0_DESCR][db],v)++; + + v = (short)mln::math::floor(result[num][HUE1_DESCR]+0.4999); + mln::opt::at(histo[HUE1_DESCR][db],v)++; + + v = (short)mln::math::floor(result[num][SAT0_DESCR]+0.4999); + mln::opt::at(histo[SAT0_DESCR][db],v)++; + + v = (short)mln::math::floor(result[num][SAT1_DESCR]+0.4999); + mln::opt::at(histo[SAT1_DESCR][db],v)++; + + v = (short)mln::math::floor(result[num][VAL0_DESCR]+0.4999); + mln::opt::at(histo[VAL0_DESCR][db],v)++; + + v = (short)mln::math::floor(result[num][GMP0_DESCR]+0.4999); + mln::opt::at(histo[GMP0_DESCR][db],v)++; + + v = (short)mln::math::floor(result[num][GMP1_DESCR]+0.4999); + mln::opt::at(histo[GMP1_DESCR][db],v)++; + + v = (short)mln::math::floor(result[num][GMP2_DESCR]+0.4999); + mln::opt::at(histo[GMP2_DESCR][db],v)++; + + v = (short)mln::math::floor(result[num][MGK0_DESCR]+0.4999); + mln::opt::at(histo[MGK0_DESCR][db],v)++; + + v = (short)mln::math::floor(result[num][MGK1_DESCR]+0.4999); + mln::opt::at(histo[MGK1_DESCR][db],v)++; + + v = (short)mln::math::floor(result[num][MGK2_DESCR]+0.4999); + mln::opt::at(histo[MGK2_DESCR][db],v)++; + + num++; + } + } +} + +void compute_thresholds(const mln::image1d<float> histo[][NB_DATABASE], + short threshold[], + float c00[], + float c10[], + float c01[], + float c11[]) +{ + for (int i = 0; i < NB_DESCR; i++) + { + float avg0 = avg_histo(histo[i][0]); + float avg1 = avg_histo(histo[i][1]); + + if (avg0 < avg1) + { + threshold[i] = min_error(histo[i][0], histo[i][1], + &c00[i], &c10[i], &c01[i], &c11[i]); + } + else + { + threshold[i] = min_error(histo[i][1], histo[i][0], + &c00[i], &c10[i], &c01[i], &c11[i]); + } + + std::cerr << " i = " << i + << "; c00 = " << c00[i] + << "; c10 = " << c10[i] + << "; c01 = " << c01[i] + << "; c11 = " << c11[i] + << "; threshold " << threshold[i] + << std::endl; + + } +} + + +void compute_descriptors(std::string file_name[], + float result[][NB_DESCR], + int size[]) +{ + typedef boost::filesystem::path t_path; + typedef boost::filesystem::directory_iterator t_iter_path; + typedef mln::image1d<unsigned> t_histo; + typedef mln::value::rgb8 t_rgb8; + typedef mln::value::int_u8 t_int_u8; + typedef mln::image2d<t_int_u8> t_map; + typedef mln::image2d<t_rgb8> t_input; + typedef mln::fun::v2v::rgb_to_hue_map<8> t_rgb_2_hue; + typedef mln::fun::v2v::rgb_to_saturation_map<8> t_rgb_2_sat; + typedef mln::fun::v2v::rgb_to_value_map<8> t_rgb_2_val; + typedef mln::fun::v2v::component<t_rgb8,0> t_rgb_2_red; + typedef mln::fun::v2v::component<t_rgb8,1> t_rgb_2_green; + typedef mln::fun::v2v::component<t_rgb8,2> t_rgb_2_blue; + typedef mln::accu::meta::stat::histo1d t_accu_histo; + + + t_path img_path[2] = { ICDAR_20P_INPUT_IMG_PATH, AFP_PPM_IMG_PATH}; + t_path mgk_path[3][2] = {{ICDAR_20P_MGK30_IMG_PATH, AFP_MGK30_IMG_PATH}, + {ICDAR_20P_MGK20_IMG_PATH, AFP_MGK20_IMG_PATH}, + {ICDAR_20P_MGK10_IMG_PATH, AFP_MGK10_IMG_PATH}}; + t_path gmp_path[3][2] = {{ICDAR_20P_GMP30_IMG_PATH, AFP_GMP30_IMG_PATH}, + {ICDAR_20P_GMP20_IMG_PATH, AFP_GMP20_IMG_PATH}, + {ICDAR_20P_GMP10_IMG_PATH, AFP_GMP10_IMG_PATH}}; + + int num = 0; + int cnt = 0; + + for (int db = 0; db < NB_DATABASE; db++) + { + if (boost::filesystem::exists(img_path[db]) && + boost::filesystem::is_directory(img_path[db])) + { + boost::filesystem::system_complete(img_path[db]); + + const t_iter_path end_iter; + + cnt = 0; + + for (t_iter_path dir_iter(img_path[db]); end_iter != dir_iter; ++dir_iter) + { + t_path img_file = dir_iter->path().leaf(); + t_path dir_file = dir_iter->path(); + t_input img_input; + + mln::io::ppm::load(img_input, dir_file.string().c_str()); + + t_map h_img_map = mln::data::transform(img_input, t_rgb_2_hue()); + t_map s_img_map = mln::data::transform(img_input, t_rgb_2_sat()); + t_map v_img_map = mln::data::transform(img_input, t_rgb_2_val()); + t_map r_img_map = mln::data::transform(img_input, t_rgb_2_red()); + t_map g_img_map = mln::data::transform(img_input, t_rgb_2_green()); + t_map b_img_map = mln::data::transform(img_input, t_rgb_2_blue()); + t_histo h_img_hst = mln::data::compute(t_accu_histo(), h_img_map); + t_histo s_img_hst = mln::data::compute(t_accu_histo(), s_img_map); + t_histo v_img_hst = mln::data::compute(t_accu_histo(), v_img_map); + t_histo r_img_hst = mln::data::compute(t_accu_histo(), r_img_map); + t_histo g_img_hst = mln::data::compute(t_accu_histo(), g_img_map); + t_histo b_img_hst = mln::data::compute(t_accu_histo(), b_img_map); + + std::cerr << dir_iter->path() << std::endl; + + file_name[num] = img_file.string(); + + // descriptors + result[num][LVL0_DESCR] = lvl0_descriptor(v_img_hst); + result[num][HUE0_DESCR] = hue0_descriptor(h_img_hst); + result[num][HUE1_DESCR] = hue1_descriptor(h_img_hst,20); + result[num][SAT0_DESCR] = sat0_descriptor(s_img_hst); + result[num][SAT1_DESCR] = sat1_descriptor(s_img_hst,50); + result[num][VAL0_DESCR] = val0_descriptor(v_img_hst); + //result[num][VAL1_DESCR] = var0_descriptor(v_img_hst, 15); + result[num][VAL1_DESCR] = 0; + + // for gimp and magick + for (int v = 0; v < NB_VERSION; v++) + { + if (boost::filesystem::exists(mgk_path[v][db]) && + boost::filesystem::exists(gmp_path[v][db]) && + boost::filesystem::is_directory(mgk_path[v][db]) && + boost::filesystem::is_directory(gmp_path[v][db])) + { + t_path mgk_file = mgk_path[v][db] / img_file; + t_path gmp_file = gmp_path[v][db] / img_file; + t_input gmp_input; + + mln::io::ppm::load(gmp_input, gmp_file.string().c_str()); + + t_map r_gmp_map = mln::data::transform(gmp_input,t_rgb_2_red()); + t_map g_gmp_map = mln::data::transform(gmp_input,t_rgb_2_green()); + t_map b_gmp_map = mln::data::transform(gmp_input,t_rgb_2_blue()); + + result[num][GMP_DESCR(v)]= err_descriptor(r_img_map, + g_img_map, + b_img_map, + r_gmp_map, + g_gmp_map, + b_gmp_map); + + t_input mgk_input; + + mln::io::ppm::load(mgk_input, mgk_file.string().c_str()); + + t_map r_mgk_map = mln::data::transform(mgk_input,t_rgb_2_red()); + t_map g_mgk_map = mln::data::transform(mgk_input,t_rgb_2_green()); + t_map b_mgk_map = mln::data::transform(mgk_input,t_rgb_2_blue()); + + result[num][MGK_DESCR(v)]= err_descriptor(r_img_map, + g_img_map, + b_img_map, + r_mgk_map, + g_mgk_map, + b_mgk_map); + } + } + + num++; + cnt++; + } + } + + size[db] = cnt; + } +} + + +int main2() +{ + typedef mln::image1d<unsigned> t_histo; + typedef mln::value::rgb8 t_rgb8; + typedef mln::value::int_u8 t_int_u8; + typedef mln::image2d<t_int_u8> t_map; + typedef mln::image2d<t_rgb8> t_input; + typedef mln::fun::v2v::rgb_to_hue_map<8> t_rgb_2_hue; + typedef mln::fun::v2v::rgb_to_saturation_map<8> t_rgb_2_sat; + typedef mln::fun::v2v::rgb_to_value_map<8> t_rgb_2_val; + typedef mln::fun::v2v::component<t_rgb8,0> t_rgb_2_red; + typedef mln::fun::v2v::component<t_rgb8,1> t_rgb_2_green; + typedef mln::fun::v2v::component<t_rgb8,2> t_rgb_2_blue; + typedef mln::accu::meta::stat::histo1d t_accu_histo; + + t_input img_input; + + mln::io::ppm::load(img_input, ICDAR_20P_INPUT_IMG_PATH"/mp00032c_20p.ppm"); + //mln::io::ppm::load(img_input, AFP_PPM_IMG_PATH"/000_Del218430.ppm"); + + + + t_map h_img_map = mln::data::transform(img_input, t_rgb_2_hue()); + t_map s_img_map = mln::data::transform(img_input, t_rgb_2_sat()); + t_map v_img_map = mln::data::transform(img_input, t_rgb_2_val()); + t_map r_img_map = mln::data::transform(img_input, t_rgb_2_red()); + t_map g_img_map = mln::data::transform(img_input, t_rgb_2_green()); + t_map b_img_map = mln::data::transform(img_input, t_rgb_2_blue()); + t_histo h_img_hst = mln::data::compute(t_accu_histo(), h_img_map); + t_histo s_img_hst = mln::data::compute(t_accu_histo(), s_img_map); + t_histo v_img_hst = mln::data::compute(t_accu_histo(), v_img_map); + t_histo r_img_hst = mln::data::compute(t_accu_histo(), r_img_map); + t_histo g_img_hst = mln::data::compute(t_accu_histo(), g_img_map); + t_histo b_img_hst = mln::data::compute(t_accu_histo(), b_img_map); + + + std::cout << "sat2 : " << sat0_descriptor(s_img_hst) << std::endl; + + return 0; +} + +int main() +{ + std::string file_name[NB_IMAGE]; + float result[NB_IMAGE][NB_DESCR]; + int size[NB_DATABASE]; + mln::image1d<float> histo[NB_DESCR][NB_DATABASE]; + short threshold[NB_DESCR]; + float c00[NB_DESCR]; + float c10[NB_DESCR]; + float c01[NB_DESCR]; + float c11[NB_DESCR]; + + std::cerr << "DESCRIPTORS" << std::endl; + compute_descriptors(file_name,result,size); +// std::cout << "DUMPING" << std::endl; +// init_descriptors(file_name,result,size); + dump_descriptors(file_name,result,size); + std::cerr << "HISTO" << std::endl; + compute_histo(result,size,histo); + std::cerr << "THRESHOLD" << std::endl; + compute_thresholds(histo,threshold,c00,c10,c01,c11); + + mln::io::plot::save_image_sh(histo[LVL0_DESCR][0], "lvl0_histo1.sh"); + mln::io::plot::save_image_sh(histo[HUE0_DESCR][0], "hue0_histo1.sh"); + mln::io::plot::save_image_sh(histo[HUE1_DESCR][0], "hue1_histo1.sh"); + mln::io::plot::save_image_sh(histo[SAT0_DESCR][0], "sat0_histo1.sh"); + mln::io::plot::save_image_sh(histo[SAT1_DESCR][0], "sat1_histo1.sh"); + mln::io::plot::save_image_sh(histo[VAL0_DESCR][0], "val0_histo1.sh"); + mln::io::plot::save_image_sh(histo[VAL1_DESCR][0], "val1_histo1.sh"); + mln::io::plot::save_image_sh(histo[GMP0_DESCR][0], "gmp0_histo1.sh"); + mln::io::plot::save_image_sh(histo[GMP1_DESCR][0], "gmp1_histo1.sh"); + mln::io::plot::save_image_sh(histo[GMP2_DESCR][0], "gmp2_histo1.sh"); + mln::io::plot::save_image_sh(histo[MGK0_DESCR][0], "mgk0_histo1.sh"); + mln::io::plot::save_image_sh(histo[MGK1_DESCR][0], "mgk1_histo1.sh"); + mln::io::plot::save_image_sh(histo[MGK2_DESCR][0], "mgk2_histo1.sh"); + + mln::io::plot::save_image_sh(histo[LVL0_DESCR][1], "lvl0_histo2.sh"); + mln::io::plot::save_image_sh(histo[HUE0_DESCR][1], "hue0_histo2.sh"); + mln::io::plot::save_image_sh(histo[HUE1_DESCR][1], "hue1_histo2.sh"); + mln::io::plot::save_image_sh(histo[SAT0_DESCR][1], "sat0_histo2.sh"); + mln::io::plot::save_image_sh(histo[SAT1_DESCR][1], "sat1_histo2.sh"); + mln::io::plot::save_image_sh(histo[VAL0_DESCR][1], "val0_histo2.sh"); + mln::io::plot::save_image_sh(histo[VAL1_DESCR][1], "val1_histo2.sh"); + mln::io::plot::save_image_sh(histo[GMP0_DESCR][1], "gmp0_histo2.sh"); + mln::io::plot::save_image_sh(histo[GMP1_DESCR][1], "gmp1_histo2.sh"); + mln::io::plot::save_image_sh(histo[GMP2_DESCR][1], "gmp2_histo2.sh"); + mln::io::plot::save_image_sh(histo[MGK0_DESCR][1], "mgk0_histo2.sh"); + mln::io::plot::save_image_sh(histo[MGK1_DESCR][1], "mgk1_histo2.sh"); + mln::io::plot::save_image_sh(histo[MGK2_DESCR][1], "mgk2_histo2.sh"); + + return 0; +} + -- 1.5.6.5

14 years, 1 month

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Olena-patches November 2010