last-svn-commit-27-g92ed726 Delete BUG image file in milena/img.
by green
* milena/img/BUG_lean_ascii.pgm.gz: Delete this file.
---
milena/img/BUG_lean_ascii.pgm.gz | Bin 75726 -> 0 bytes
1 files changed, 0 insertions(+), 0 deletions(-)
delete mode 100644 milena/img/BUG_lean_ascii.pgm.gz
diff --git a/milena/img/BUG_lean_ascii.pgm.gz b/milena/img/BUG_lean_ascii.pgm.gz
deleted file mode 100644
index 7ba3e9d1b02e3a41704448faf72a6c7afe2e8259..0000000000000000000000000000000000000000
GIT binary patch
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--
1.5.6.5
14Â years, 2Â months
- 1
- 0
last-svn-commit-28-gea9c5e5 Turn around Millet 2008 hsv descriptors.
by Yann Jacquelet
* green/demo/annotating/hsv: New directory.
* green/demo/annotating/hsv/Makefile.am: New Makefile.
---
.../regional_maxima => annotating/hsv}/Makefile.am | 6 +-
milena/sandbox/green/demo/annotating/hsv/hsv.cc | 607 ++++++++++++++++++++
.../sandbox/green/ChangeLog | 0
3 files changed, 611 insertions(+), 2 deletions(-)
copy milena/sandbox/green/demo/{labeling/regional_maxima => annotating/hsv}/Makefile.am (94%)
create mode 100644 milena/sandbox/green/demo/annotating/hsv/hsv.cc
copy milena/doc/outputs/accu-right-instanciation.txt => scribo/sandbox/green/ChangeLog (100%)
diff --git a/milena/sandbox/green/demo/labeling/regional_maxima/Makefile.am b/milena/sandbox/green/demo/annotating/hsv/Makefile.am
similarity index 94%
copy from milena/sandbox/green/demo/labeling/regional_maxima/Makefile.am
copy to milena/sandbox/green/demo/annotating/hsv/Makefile.am
index 1dd1cfb..a5d4fff 100644
--- a/milena/sandbox/green/demo/labeling/regional_maxima/Makefile.am
+++ b/milena/sandbox/green/demo/annotating/hsv/Makefile.am
@@ -6,8 +6,10 @@
# TOOLS #
#########
-INCLUDES= -I$(HOME)/svn/oln/trunk/milena/sandbox/green
-CXXFLAGS= -ggdb -O0 -Wall -W -pedantic -ansi -pipe $(INCLUDES)
+INCLUDES1= -I$(HOME)/git/olena/milena/sandbox/green
+INCLUDES2= -I$(HOME)/git/olena/milena
+INCLUDES= $(INCLUDES1) $(INCLUDES2)
+CXXFLAGS= -DNDEBUG -ggdb -O0 -Wall -W -pedantic -ansi -pipe $(INCLUDES)
#CXXFLAGS= -DNDEBUG -O1 -Wall -W -pedantic -ansi -pipe $(INCLUDES)
#CXXFLAGS= -DNDEBUG -O3 -Wall -W -pedantic -ansi -pipe $(INCLUDES)
ECHO= echo
diff --git a/milena/sandbox/green/demo/annotating/hsv/hsv.cc b/milena/sandbox/green/demo/annotating/hsv/hsv.cc
new file mode 100644
index 0000000..a61a5de
--- /dev/null
+++ b/milena/sandbox/green/demo/annotating/hsv/hsv.cc
@@ -0,0 +1,607 @@
+// Test de l'opérateur de Millet TSVal (HSV)
+//
+// Val = max(R,G,B)
+// Sat = (max(R,G,B) - min(R,G,B))/max(R,G,B)
+// si R = max(R,G,B) alors Hue = 60 * [(V-B)/(max(R,G,B)-min(R,G,B))]
+// si G = max(R,G,B) alors Hue = 60 * [2 + (B-R)/(max(R,G,B)-min(R,G,B))]
+// si B = max(R,G,B) alors Hue = 60 * [4 + (R-G)/(max(R,G,B)-min(R,G,B))]
+
+
+#include <iostream>
+#include <fstream>
+
+#include <mln/accu/max_site.hh>
+#include <mln/accu/math/count.hh>
+#include <mln/accu/stat/histo1d.hh>
+
+#include <mln/binarization/threshold.hh>
+
+#include <mln/core/alias/point1d.hh>
+#include <mln/core/alias/box1d.hh>
+#include <mln/core/concept/image.hh>
+#include <mln/core/image/image2d.hh>
+#include <mln/core/image/dmorph/image_if.hh>
+
+#include <mln/data/transform.hh>
+#include <mln/data/compute.hh>
+#include <mln/data/stretch.hh>
+
+#include <mln/debug/println.hh>
+
+#include <mln/literal/colors.hh>
+#include <mln/literal/grays.hh>
+
+#include <mln/fun/v2v/rgb_to_hsv.hh>
+#include <mln/fun/v2v/rgb_to_achromatism_map.hh>
+#include <mln/fun/v2v/achromatism.hh>
+#include <mln/fun/v2v/hue_concentration.hh>
+#include <mln/fun/p2b/component_equals.hh>
+#include <mln/fun/p2b/achromatic.hh>
+#include <mln/fun/v2v/component.hh>
+
+#include <mln/geom/nsites.hh>
+
+#include <mln/img_path.hh>
+
+#include <mln/io/plot/save_image_sh.hh>
+#include <mln/io/ppm/load.hh>
+#include <mln/io/pgm/save.hh>
+#include <mln/io/pbm/save.hh>
+
+#include <mln/pw/cst.hh>
+#include <mln/pw/value.hh>
+//#include <mln/trace/quiet.hh>
+
+#include <mln/value/rgb8.hh>
+#include <mln/value/int_u8.hh>
+#include <mln/value/hsv.hh>
+
+
+mln::value::rgb8 label_color(const mln::value::rgb8 rgb)
+{
+ mln::value::hsv_f hsv = mln::fun::v2v::f_rgb_to_hsv_f(rgb);
+
+ mln::value::rgb8 result;
+
+ // Is it a gray level ?
+ if (0 == hsv.sat())
+ {
+ // which result one ?
+ if (82 > hsv.sat())
+ result = mln::literal::black;
+ else if (179 > hsv.sat())
+ result= mln::literal::medium_gray;
+ else
+ result = mln::literal::white;
+ }
+ // Is it a true result color ?
+ else if (14 > hsv.hue())
+ result = mln::literal::red;
+ else if (29 > hsv.hue())
+ {
+ // Is is brown or orange ?
+ unsigned dist_orange = mln::math::abs(hsv.sat() - 184)
+ + mln::math::abs(hsv.val() - 65);
+
+ unsigned dist_brown = mln::math::abs(hsv.sat() - 255)
+ + mln::math::abs(hsv.val() - 125);
+
+ if (dist_orange < dist_brown)
+ result = mln::literal::orange;
+ else
+ result = mln::literal::brown;
+ }
+ else if (45 > hsv.hue())
+ {
+ // Is it green or yellow ?
+ if (80 > hsv.val())
+ result = mln::literal::green;
+ else
+ result = mln::literal::yellow;
+ }
+ else if (113 > hsv.hue())
+ result = mln::literal::green;
+ else if (149 > hsv.hue())
+ result = mln::literal::cyan;
+ else if (205 > hsv.hue())
+ result = mln::literal::blue;
+ else if (235 > hsv.hue())
+ result = mln::literal::violet;
+ else if (242 > hsv.hue())
+ result = mln::literal::pink;
+ else
+ result = mln::literal::red;
+
+ return result;
+}
+
+//unsigned count_histo(const mln::image1d<unsigned>& img)
+template <typename I>
+unsigned count_histo(const mln::Image<I>& 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;
+}
+
+// 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>
+unsigned peak_histo(const mln::Image<I>& 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;
+}
+
+
+// unsigned stddev_color(mln::image2d<mln::value::int_u8> input_int_u8,
+// const char *name_histo,
+// const char *name_image)
+// {
+// typedef mln::point1d t_point1d;
+// typedef mln::value::rgb8 t_rgb8;
+// typedef mln::value::int_u8 t_int_u8;
+// typedef mln::image2d<t_rgb8> t_image2d_rgb8;
+// typedef mln::image2d<t_int_u8> t_image2d_int_u8;
+// typedef mln::image1d<unsigned> t_histo1d;
+// typedef mln::fun::v2v::rgb8_to_int_u8 t_rgb8_to_int_u8;
+// typedef mln::accu::meta::stat::histo1d t_histo1d_fun;
+// typedef mln::accu::max_site<t_histo1d> t_max_site_fun;
+
+// t_histo1d histo;
+
+// std::cout << "histo : " << name_histo << std::endl;
+// std::cout << "image : " << name_image << std::endl;
+
+// histo = mln::data::compute(t_histo1d_fun(), input_int_u8);
+
+// mln::io::pgm::save(input_int_u8, name_image);
+// mln::io::plot::save_image_sh(histo, name_histo);
+// mln::debug::println(histo);
+
+// // Find the peak of the histogram
+// unsigned v_max = mln::opt::at(histo, 0);
+// short p_max = 0;
+
+// mln_piter_(t_histo1d) p(histo.domain());
+
+// for_all(p)
+// {
+// if (v_max < histo(p))
+// {
+// v_max = histo(p);
+// p_max = p.ind();
+// }
+// }
+
+// // Compute the specific stddev
+
+// float stddev_low = 0.0;
+// float stddev_up = 0.0;
+// float stddev = 0.0;
+
+// if (250 > p_max)
+// for (short i = p_max+1; i < p_max+6; ++i)
+// stddev_up += r(p_max, mln::opt::at(histo,p_max),
+// i, mln::opt::at(histo,i));
+
+// if (5 < p_max)
+// for (short i = p_max-1; i > p_max-6; --i)
+// stddev_low += r(p_max, mln::opt::at(histo,p_max),
+// i, mln::opt::at(histo,i));
+
+// stddev = (250 < p_max)? stddev_low : (5 > p_max)? stddev_up :
+// (stddev_low + stddev_up)/2;
+
+// std::cout << "max_site : " << p_max << std::endl;
+// std::cout << "h(max_site) : " << v_max << std::endl;
+// std::cout << "stddev_up : " << stddev_up << std::endl;
+// std::cout << "stddev_low : " << stddev_low << std::endl;
+// std::cout << "stddev : " << stddev << std::endl;
+
+// return 0;
+// }
+
+
+// -------------------------------------
+// input image <name>.ppm
+// map <name>-<map>.pgm
+// thresholded map <name>-<map>.pbm
+// histogram <name>-<map>.sh
+// decision <name>-<map>.txt
+// -------------------------------------
+
+// Achromatism <name>-achromatism.pgm
+
+// call achromatism(input_rgb8, 7, 99.0)
+void achromatism(mln::image2d<mln::value::rgb8> input_rgb8,
+ mln::value::int_u8 threshold,
+ float percentage)
+{
+ typedef mln::fun::v2v::rgb_to_achromatism_map<8> t_rgb_to_achromatism_map;
+
+ mln::image2d<mln::value::int_u8> map;
+ mln::image2d<mln::value::int_u8> view;
+ mln::image2d<bool> mask;
+ mln::image1d<unsigned> histo;
+ unsigned cnt1;
+ unsigned cnt2;
+ float prop;
+ bool result;
+
+
+ map = mln::data::transform(input_rgb8, t_rgb_to_achromatism_map());
+ view = mln::data::stretch(mln::value::int_u8(), map);
+ mask = mln::binarization::threshold(map, threshold);
+ histo = mln::data::compute(mln::accu::meta::stat::histo1d(),
+ map | (mln::pw::value(mask) == true));
+ cnt1 = count_histo(histo);
+ cnt2 = mln::geom::nsites(input_rgb8);
+ prop = (100.0 * (cnt2 - cnt1) / cnt2);
+ result = (prop > percentage);
+
+
+ std::ofstream txt_stream("achromatism.txt");
+ txt_stream << "Achromatism" << std::endl;
+
+ txt_stream << "Nbre pixels : " << cnt2 << std::endl;
+ txt_stream << "Nbre pixels achromatiques : " << (cnt2-cnt1)<< std::endl;
+ txt_stream << "Percentage : " << prop << std::endl;
+ txt_stream << "Image achromatique : " << result << std::endl;
+ txt_stream << std::endl;
+
+ txt_stream.flush();
+ txt_stream.close();
+
+ mln::io::pgm::save(view, "achromatism.pgm");
+ mln::io::plot::save_image_sh(histo, "achromatism.sh");
+ mln::io::pbm::save(mask, "achromatism.pbm");
+}
+
+// call low_saturation(input_rgb8, achromatism_mask, 100, 95.0)
+void low_saturation(mln::image2d<mln::value::hsv_f> input_hsvf,
+ mln::image2d<bool> achromatism_mask,
+ mln::value::int_u8 threshold,
+ float percentage)
+{
+ typedef mln::value::hsv_f t_hsvf;
+ typedef mln::value::hsv_f::s_type t_sat;
+ typedef mln::fun::v2v::component<t_hsvf,1> t_component_s;
+
+ mln::image2d<t_sat> map;
+ mln::image2d<mln::value::int_u8> view;
+ mln::image2d<bool> mask;
+ mln::image1d<unsigned> histo;
+ unsigned cnt1;
+ unsigned cnt2;
+ float prop;
+ bool result;
+
+
+ map = mln::data::transform(input_hsvf, t_component_s());
+ view = mln::data::stretch(mln::value::int_u8(), map);
+// where is histo ??
+ prop = (100.0 * (cnt2 - cnt1) / cnt2);
+ result = (prop > percentage);
+
+ std::cout << "Saturation" << std::endl;
+
+ cnt1 = count_histo(histo_s | mln::box1d(mln::point1d(0),mln::point1d(100)));
+
+ cnt2= mln::geom::nsites(achromatic | (mln::pw::value(achromatic)==false));
+
+
+
+ std::ofstream txt_stream("achromatism.txt");
+ txt_stream << "Saturation" << std::endl;
+
+ txt_stream << "Nbre pixels : " << cnt2 << std::endl;
+ txt_stream << "Nbre p faiblement saturés : " << cnt1 << std::endl;
+ txt_stream << "Pourcentage : " << prop << std::endl;
+ txt_stream << "Image faiblement saturé : " << result << std::endl;
+ txt_stream << std::endl;
+
+ txt_stream.flush();
+ txt_stream.close();
+
+ mln::io::pgm::save(view, "achromatism.pgm");
+ mln::io::plot::save_image_sh(histo, "achromatism.sh");
+ mln::io::pbm::save(mask, "achromatism.pbm");
+}
+
+/*
+// COLOR
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/mp00032c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/mp00042c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/mp00076c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/mp00082c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/mp00142c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/mp00215c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/mp00228c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/mp00234c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/mp00248c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/mp00252c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/mp00253c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/mp00255c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/mp00259c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/mp00271c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/mp00290c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/mp00293c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/mp00304c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/mp00307c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/mp00376c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/mp00411c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/mp00419c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/mp00447c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/mp00498c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/mp00510c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/mp00550c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/mp00573c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/mp00589c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/mp00592c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/mp00597c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/mp00599c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/mp00600c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/ta00031c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/ta00034c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/ta00043c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/ta00063c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/ta00065c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/ta00072c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/ta00081c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/ta00083c_20p.ppm");
+
+// BLACK AND WHITE
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/mp00329c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/ta00036c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/ta00037c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/ta00039c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/ta00040c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/ta00049c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/ta00055c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/ta00057c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/ta00068c_20p.ppm");
+
+
+// A LITTLE BIT OF COLOR
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/mp00262c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/mp00263c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/mp00311c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/mp00319c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/mp00440c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/mp00608c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/mp00630c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/mp00631c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/ta00028c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/ta00046c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/ta00073c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/ta00089c_20p.ppm");
+ mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/ta00090c_20p.ppm");
+*/
+
+// To DO mettre le seuil d'achromaticité en paramètre
+// TO DO inverser les couleurs sur les masques
+int main()
+{
+ typedef mln::value::rgb8 t_rgb8;
+ typedef mln::value::int_u8 t_int_u8;
+ typedef mln::value::hsv_f t_hsvf;
+ typedef mln::value::hsv_f::h_type t_hue;
+ typedef mln::value::hsv_f::s_type t_sat;
+ typedef mln::value::hsv_f::v_type t_val;
+ typedef mln::image2d<t_hue> t_image2d_hue;
+ typedef mln::image2d<t_sat> t_image2d_sat;
+ typedef mln::image2d<t_val> t_image2d_val;
+ typedef mln::image2d<t_hsvf> t_image2d_hsvf;
+ typedef mln::image2d<t_rgb8> t_image2d_rgb8;
+ typedef mln::image2d<float> t_image2d_float;
+ typedef mln::image1d<unsigned> t_histo1d;
+ typedef mln::image2d<t_int_u8> t_image2d_int_u8;
+ typedef mln::image2d<bool> t_mask;
+ typedef mln::fun::v2v::f_rgb_to_hsv_f_t t_rgb8_to_hsv;
+ typedef mln::accu::math::count<t_hsvf> t_count;
+ typedef mln::fun::v2v::component<t_hsvf,0> t_component_h;
+ typedef mln::fun::v2v::component<t_hsvf,1> t_component_s;
+ typedef mln::fun::v2v::component<t_hsvf,2> t_component_v;
+ typedef mln::fun::p2b::component_equals<t_image2d_hsvf,0> t_component_eq0;
+ typedef mln::fun::p2b::component_equals<t_image2d_hsvf,1> t_component_eq1;
+ typedef mln::fun::p2b::component_equals<t_image2d_hsvf,2> t_component_eq2;
+ typedef mln::fun::p2b::achromatic<t_rgb8> t_achromatic;
+
+ t_image2d_rgb8 input_rgb8;
+ t_image2d_hsvf input_hsvf;
+
+ t_mask achromatic;
+ t_mask low_saturation;
+
+ t_image2d_float achromatism1;
+ t_image2d_int_u8 achromatism2;
+ t_image2d_float hue_concentration1;
+ t_image2d_int_u8 hue_concentration2;
+
+ t_image2d_hue input_h;
+ t_image2d_hue input_h2;
+ t_image2d_sat input_s;
+ t_image2d_val input_v;
+
+ t_image2d_int_u8 input_h8;
+ t_image2d_int_u8 input_s8;
+ t_image2d_int_u8 input_v8;
+
+ t_histo1d histo_h;
+ t_histo1d histo_s;
+ t_histo1d histo_v;
+
+ unsigned cnt1;
+ unsigned cnt2;
+ float percentage;
+ bool result;
+
+
+
+ // IMAGE LOADING PHASE
+ std::cout << "Image loading phase ..." << std::endl;
+// mln::io::ppm::load(input_rgb8, ANNOTATING_1_BILL_IMG_PATH"/bill03.ppm");
+// mln::io::ppm::load(input_rgb8, ICDAR_20P_PPM_IMG_PATH"/mp00082c_20p.ppm");
+
+
+ achromatism(input_rgb8,7,99.0);
+ exit(-1);
+ // REPERAGE DES PIXELS ACHROMATICS
+ std::cout << "Init achromatic mask ..." << std::endl;
+ initialize(achromatic, input_rgb8);
+ mln::data::fill(achromatic, false);
+ mln::data::fill((achromatic | t_achromatic(input_rgb8, 0.03)).rw(), true);
+
+ mln::io::pbm::save(achromatic, "achromatic.pbm");
+
+ std::cout << "Achieve canal forking ..." << std::endl;
+ input_hsvf = mln::data::transform(input_rgb8, t_rgb8_to_hsv());
+
+ input_h = mln::data::transform(input_hsvf, t_component_h());
+ input_s = mln::data::transform(input_hsvf, t_component_s());
+ input_v = mln::data::transform(input_hsvf, t_component_v());
+
+ // quid des achromatiques ???
+ input_h8 = mln::data::stretch(t_int_u8(), input_h);
+ input_s8 = mln::data::stretch(t_int_u8(), input_s);
+ input_v8 = mln::data::stretch(t_int_u8(), input_v);
+
+ // REPERAGE DES PIXELS ACHROMATICS
+ std::cout << "Init low saturation mask ..." << std::endl;
+ initialize(low_saturation, input_s8);
+ mln::data::fill(low_saturation, false);
+ mln::data::fill((low_saturation|(mln::pw::value(input_s8) <
+ mln::pw::cst(100u))).rw(), true);
+
+ mln::io::pbm::save(low_saturation, "low_saturation.pbm");
+
+ std::cout << "Compute histograms ..." << std::endl;
+ histo_h = mln::data::compute(mln::accu::meta::stat::histo1d(),
+ input_h8|(mln::pw::value(achromatic)==false));
+
+ histo_s = mln::data::compute(mln::accu::meta::stat::histo1d(),
+ input_s8|(mln::pw::value(achromatic)==false));
+
+ histo_v = mln::data::compute(mln::accu::meta::stat::histo1d(),
+ input_v8|(mln::pw::value(achromatic)==false));
+
+
+ // etude des cartes
+
+ hue_concentration1=mln::data::transform(input_h,
+ mln::fun::v2v::hue_concentration(histo_h));
+ achromatism1=mln::data::transform(input_rgb8,mln::fun::v2v::achromatism());
+
+ hue_concentration2= mln::data::stretch(t_int_u8(), hue_concentration1);
+ achromatism2= mln::data::stretch(t_int_u8(), achromatism1);
+
+ mln::io::pgm::save(achromatism2, "achromatism_map.pgm");
+ mln::io::pgm::save(hue_concentration2, "hue_concentration_map.pgm");
+ mln::io::pgm::save(input_s8, "saturation_map.pgm");
+
+// cnt1 = mln::data::compute(t_count(),
+// (input_hsvf|t_component_eq0(input_hsvf,-1)).rw());
+
+
+ // (I) ACHROMATISME
+ std::cout << "Achromatism" << std::endl;
+ cnt1 = count_histo(histo_h);
+ cnt2 = mln::geom::nsites(input_h);
+
+ percentage = (100.0 * (cnt2 - cnt1) / cnt2);
+ result = percentage > 99.0;
+
+ std::cout << "Nbre pixels : " << cnt2 << std::endl;
+ std::cout << "Nbre pixels achromatiques : " << (cnt2-cnt1)<< std::endl;
+ std::cout << "Percentage : " << percentage << std::endl;
+ std::cout << "Image achromatique : " << result << std::endl;
+ std::cout << std::endl;
+
+ // (II) FAIBLE SATURATION
+ std::cout << "Saturation" << std::endl;
+
+ cnt1 = count_histo(histo_s | mln::box1d(mln::point1d(0),mln::point1d(100)));
+
+ cnt2= mln::geom::nsites(achromatic | (mln::pw::value(achromatic)==false));
+
+ percentage = (100.0 * cnt1 / cnt2);
+ result = percentage > 95.0;
+
+ std::cout << "Nbre pixels : " << cnt2 << std::endl;
+ std::cout << "Nbre p faiblement saturés : " << cnt1 << std::endl;
+ std::cout << "Percentage : " << percentage << std::endl;
+ std::cout << "Image faiblement saturé : " << result << std::endl;
+ std::cout << std::endl;
+
+ // (III) DOMINANCE DE LA TEINTE
+ // et peut être 50% des pixels faiblement saturées
+
+ mln::debug::println(histo_h);
+ unsigned peak = peak_histo(histo_h);
+
+ cnt1 = count_histo(histo_h | mln::box1d(mln::point1d(peak-20),
+ mln::point1d(peak+20)));
+
+ cnt2= count_histo(histo_h);
+
+ percentage = (100.0 * cnt1 / cnt2);
+ result = percentage > 95.0;
+
+ std::cout << "Position du pic : " << peak << std::endl;
+ std::cout << "Nbre pixels : " << cnt2 << std::endl;
+ std::cout << "Nbre pixels proches pic : " << cnt1 << std::endl;
+ std::cout << "Percentage : " << percentage << std::endl;
+ std::cout << "Image fortement teintée : " << result << std::endl;
+ std::cout << std::endl;
+
+
+
+ // Autre possibilité
+ // calculer le maximum de la teinte et regarder si le pourcentage pixels dont
+ // la distance est inférieure à 20 > 95%
+ // alors
+}
+
+// 3 cartes
+// 1) carte d'achromaticité d = max(|r-g|,|r-b|,|g-b|)
+// 2) carte de saturation
+// 3) carte d'éloignement par rapport au pic de teinte
+
+
+// QUELS SONT LES CHARACTERISTIQUES HSV DE LA BASE ICDAR ?
+// FAIBLE SATURATION DES IMAGES ?
+// DOMINANCE DES TEINTES ?
+// ACHROMATISME ?
diff --git a/milena/doc/outputs/accu-right-instanciation.txt b/scribo/sandbox/green/ChangeLog
similarity index 100%
copy from milena/doc/outputs/accu-right-instanciation.txt
copy to scribo/sandbox/green/ChangeLog
--
1.5.6.5
14Â years, 2Â months
- 1
- 0
last-svn-commit-29-gd7c3738 Test on image database the achromatism descriptor.
by Yann Jacquelet
* 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.
* green/exp/annotating/achromatism/text-img.txt: New image class.
* green/exp/annotating/achromatism/text-only.txt: New image class.
---
milena/sandbox/ChangeLog | 18 +++
.../{nb_color => achromastism}/Makefile.am | 4 +-
.../exp/annotating/achromastism/achromastism.cc | 113 ++++++++++++++++++++
.../exp/annotating/achromastism/text-color.txt | 15 +++
.../green/exp/annotating/achromastism/text-img.txt | 40 +++++++
.../exp/annotating/achromastism/text-only.txt | 8 ++
6 files changed, 197 insertions(+), 1 deletions(-)
copy milena/sandbox/green/exp/annotating/{nb_color => achromastism}/Makefile.am (96%)
create mode 100644 milena/sandbox/green/exp/annotating/achromastism/achromastism.cc
create mode 100644 milena/sandbox/green/exp/annotating/achromastism/text-color.txt
create mode 100644 milena/sandbox/green/exp/annotating/achromastism/text-img.txt
create mode 100644 milena/sandbox/green/exp/annotating/achromastism/text-only.txt
diff --git a/milena/sandbox/ChangeLog b/milena/sandbox/ChangeLog
index 6f08caf..0086d22 100644
--- a/milena/sandbox/ChangeLog
+++ b/milena/sandbox/ChangeLog
@@ -1,3 +1,21 @@
+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.
+ * green/exp/annotating/achromatism/achromatism.am: New source.
+ * green/exp/annotating/achromatism/text-color.txt: New image class.
+ * green/exp/annotating/achromatism/text-img.txt: New image class.
+ * green/exp/annotating/achromatism/text-only.txt: New image class.
+
+2010-06-21 Yann Jacquelet <jacquelet(a)lrde.epita.fr>
+
+ Turn around Millet 2008 hsv descriptors.
+
+ * green/demo/annotating/hsv: New directory.
+ * green/demo/annotating/hsv/Makefile.am: New Makefile.
+
+
2010-02-10 Yann Jacquelet <jacquelet(a)lrde.epita.fr>
Fix bugs in the histogram visualization tools.
diff --git a/milena/sandbox/green/exp/annotating/nb_color/Makefile.am b/milena/sandbox/green/exp/annotating/achromastism/Makefile.am
similarity index 96%
copy from milena/sandbox/green/exp/annotating/nb_color/Makefile.am
copy to milena/sandbox/green/exp/annotating/achromastism/Makefile.am
index 8e204c6..d33b94d 100644
--- a/milena/sandbox/green/exp/annotating/nb_color/Makefile.am
+++ b/milena/sandbox/green/exp/annotating/achromastism/Makefile.am
@@ -7,7 +7,9 @@
#########
LOADLIBES= -lboost_filesystem
-INCLUDES= -I$(HOME)/svn/oln/trunk/milena/sandbox/green
+INCLUDES1= -I$(HOME)/git/olena/milena/sandbox/green
+INCLUDES2= -I$(HOME)/git/olena/milena
+INCLUDES= $(INCLUDES1) $(INCLUDES2)
#CXXFLAGS= -ggdb -O0 -Wall -W -pedantic -ansi -pipe $(INCLUDES)
#CXXFLAGS= -DNDEBUG -O1 -Wall -W -pedantic -ansi -pipe $(INCLUDES)
CXXFLAGS= -DNDEBUG -O3 -Wall -W -pedantic -ansi -pipe $(INCLUDES)
diff --git a/milena/sandbox/green/exp/annotating/achromastism/achromastism.cc b/milena/sandbox/green/exp/annotating/achromastism/achromastism.cc
new file mode 100644
index 0000000..fdb8e6d
--- /dev/null
+++ b/milena/sandbox/green/exp/annotating/achromastism/achromastism.cc
@@ -0,0 +1,113 @@
+// ACHROMATISM 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/math/max.hh>
+#include <mln/math/min.hh>
+
+#include <mln/geom/nsites.hh>
+
+#include <mln/fun/v2v/rgb_to_achromatism_map.hh>
+
+#include <mln/io/ppm/load.hh>
+#include <mln/io/plot/save_image_sh.hh>
+
+#include <mln/value/rgb8.hh>
+
+template <typename I>
+unsigned count_histo(const mln::Image<I>& 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;
+}
+
+float achromatism_test(const std::string input,
+ const std::string output,
+ const unsigned threshold)
+
+{
+ typedef mln::fun::v2v::rgb_to_achromatism_map<8> t_rgb_to_achromatism_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;
+
+ mln::io::ppm::load(input_rgb8, input.c_str());
+
+ map = mln::data::transform(input_rgb8, t_rgb_to_achromatism_map());
+ histo = mln::data::compute(mln::accu::meta::stat::histo1d(), map);
+ cnt1 = count_histo(histo | mln::box1d(mln::point1d(0),
+ mln::point1d(threshold)));
+ cnt2 = mln::geom::nsites(input_rgb8);
+ prop = ((100.0 * cnt1) / cnt2);
+
+ mln::io::plot::save_image_sh(histo, output.c_str());
+
+ 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_ACHROMATISM_RET_PATH);
+ t_path leaf = dir_iter->path().leaf();
+ t_path output = change_extension(directory / leaf, ".sh");
+
+ prop = achromatism_test(dir_iter->path().string(),
+ output.string(),
+ 11);
+
+ 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/achromastism/text-color.txt
new file mode 100644
index 0000000..4dfcbd3
--- /dev/null
+++ b/milena/sandbox/green/exp/annotating/achromastism/text-color.txt
@@ -0,0 +1,15 @@
+mp00262c_20p.ppm
+mp00263c_20p.ppm
+mp00319c_20p.ppm
+mp00440c_20p.ppm
+mp00608c_20p.ppm
+mp00630c_20p.ppm
+mp00631c_20p.ppm
+ta00028c_20p.ppm
+ta00037c_20p.ppm
+ta00043c_20p.ppm
+ta00046c_20p.ppm
+ta00073c_20p.ppm
+ta00081c_20p.ppm
+ta00089c_20p.ppm
+ta00090c_20p.ppm
diff --git a/milena/sandbox/green/exp/annotating/achromastism/text-img.txt b/milena/sandbox/green/exp/annotating/achromastism/text-img.txt
new file mode 100644
index 0000000..4ecb7ca
--- /dev/null
+++ b/milena/sandbox/green/exp/annotating/achromastism/text-img.txt
@@ -0,0 +1,40 @@
+mp00032c_20p.ppm
+mp00042c_20p.ppm
+mp00076c_20p.ppm
+mp00082c_20p.ppm
+mp00142c_20p.ppm
+mp00215c_20p.ppm
+mp00228c_20p.ppm
+mp00234c_20p.ppm
+mp00248c_20p.ppm
+mp00252c_20p.ppm
+mp00253c_20p.ppm
+mp00255c_20p.ppm
+mp00259c_20p.ppm
+mp00271c_20p.ppm
+mp00290c_20p.ppm
+mp00293c_20p.ppm
+mp00304c_20p.ppm
+mp00307c_20p.ppm
+mp00311c_20p.ppm
+mp00376c_20p.ppm
+mp00411c_20p.ppm
+mp00419c_20p.ppm
+mp00447c_20p.ppm
+mp00498c_20p.ppm
+mp00510c_20p.ppm
+mp00550c_20p.ppm
+mp00573c_20p.ppm
+mp00589c_20p.ppm
+mp00592c_20p.ppm
+mp00597c_20p.ppm
+mp00599c_20p.ppm
+mp00600c_20p.ppm
+ta00031c_20p.ppm
+ta00034c_20p.ppm
+ta00063c_20p.ppm
+ta00065c_20p.ppm
+ta00072c_20p.ppm
+ta00081c_20p.ppm
+ta00083c_20p.ppm
+
diff --git a/milena/sandbox/green/exp/annotating/achromastism/text-only.txt b/milena/sandbox/green/exp/annotating/achromastism/text-only.txt
new file mode 100644
index 0000000..0218a2a
--- /dev/null
+++ b/milena/sandbox/green/exp/annotating/achromastism/text-only.txt
@@ -0,0 +1,8 @@
+mp00329c_20p.ppm
+ta00036c_20p.ppm
+ta00039c_20p.ppm
+ta00040c_20p.ppm
+ta00049c_20p.ppm
+ta00055c_20p.ppm
+ta00057c_20p.ppm
+ta00068c_20p.ppm
--
1.5.6.5
14Â years, 2Â months
- 1
- 0
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<I>& 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<I>& 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<I>& 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<I>& 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<I>& 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<I>& 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<I>& 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<I>& 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<I>& 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<I>& 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<I>& 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<I>& 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<I>& 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<I>& 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[" << p << "] = " << err[p] << std::endl;
+
+ if (error > 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[" << p << "]= " << v_in[p] << std::endl;
+
+ if (min_var > 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
14Â years, 2Â months
- 1
- 0
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<I>& 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<I>& 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<I>& 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<I>& 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<I>& 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<I>& 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<I>& 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 = " << p
+ << ";c00 = " << c00[p]
+ << ";c10 = " << c10[p]
+ << ";c01 = " << c01[p]
+ << ";c11 = " << c11[p]
+ << std::endl;
+// std::cout << "err[" << p << "] = " << err[p] << std::endl;
+
+ if (error > 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[" << p << "]= " << v_in[p] << std::endl;
+
+ if (min_var > 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
14Â years, 2Â months
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-----------------------------------------------------------------------
6c094d01081e780f2f665042bb2b0786f926a117 Import annotating sources from milena green's sandbox.
-----------------------------------------------------------------------
hooks/post-receive
--
Olena, a generic and efficient image processing platform
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- Log -----------------------------------------------------------------
d652519 Import annotating sources from milena green's sandbox.
6ce521a Import regional maxima sources from milena green's sandbox.
c87f968 Add some futur materials on regional maxima.
0c912a2 Implement the kmean algorithh and start to optimize it.
02c36c2 Define documentation files.
7e1539b Define gnuplot shell export format.
c0859da Import files from milena/sandbox/green.
da5a388 Define accumulator which computes histogram view as image.
30dc3f0 Import files from milena/sandbox/green.
b050ed7 Simple integration test.
97cf182 Fix the way to convert unsigned to float.
a7832fe Add milena library components.
cf874ab Work on Millet value descriptor.
40d7890 Work on Millet saturation descriptor.
b17f057 Work on Millet saturation descriptor.
e0453aa Work on Millet hsv descriptors.
66ea248 Work on histograms view as density.
5144d5f Test error quantification as a color descriptor in our database.
de4f736 Benchmark few descriptors.
d7c3738 Test on image database the achromatism descriptor.
ea9c5e5 Turn around Millet 2008 hsv descriptors.
92ed726 Delete BUG image file in milena/img.
25ef511 Fix bugs in the histogram visualization tools.
a3fa356 Fix last details in the image processing chain.
17b0492 Extend the histogram visualization tools for new projection concept.
ccd6711 Build translation table between number of pixels and percentage of
e7dcb79 Split the regional maxima binary in small atomic binaries.
abdea30 Write the opening volume thresholds for the scribo image mp00082c.ppm.
cfe8986 Experiment variation on regional maxima labeling.
-----------------------------------------------------------------------
Summary of changes:
milena/sandbox/ChangeLog | 171 +---------------
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hooks/post-receive
--
Olena, a generic and efficient image processing platform
14Â years, 2Â months
- 1
- 0
last-svn-commit-47-g6ce521a Import regional maxima sources from milena green's sandbox.
by Guillaume Lazzara
* README.green: Update documentation.
Implement a primary demonstrator with watershed labeling.
* demo/labeling/watershed: New directory.
* demo/labeling/watershed/Makefile.am: New makefile.
* demo/labeling/watershed/watershed.cc: New demo source.
* demo/labeling/watershed/gaussian.sh: New calibrate tools.
Implement a secondary demonstrator with regional maxima labeling.
* demo/labeling/regional_maxima: New directory.
* demo/labeling/regional_maxima/Makefile.am: New makefile.
* demo/labeling/regional_maxima/regional_maxima.cc: New demo source.
* demo/labeling/regional_maxima/threshold.txt: New threshold map file.
Implement the same demonstrator with directory scanning.
* exp/labeling/regional_maxima: New directory.
* exp/labeling/regional_maxima/Makefile.am: New makefile.
* exp/labeling/regional_maxima/regional_maxima.cc: New demo source.
* exp/labeling/regional_maxima/threshold.txt: New threshold map file.
Implement r/g projection.
* mln/display: New directory.
* mln/display/display_histo.hh: New library file.
* mln/display/project_histo.hh: New library file.
Give minimal code for using r/w projection.
* use/display/display_histo: New directory.
* use/display/display_histo/Makefile.am: New Makefile.
* use/display/display_histo/display_histo.cc: New source.
Divide the secondary demonstrator in four binaries in order to test it.
Implement the quantified RGB histogram.
* tools/labeling/histo: New directory.
* tools/labeling/histo/Makefile.am: new makefile.
* tools/labeling/histo/histo.cc: New source.
Filter the quantified RGB histogram by morphological volume attribute.
* tools/labeling/opening: New directory.
* tools/labeling/opening/Makefile.am: New makfile.
* tools/labeling/opening/opening.cc: New source.
Labeling the resulting histogram.
* tools/labeling/regmax: New directory.
* tools/labeling/regmax/Makefile: New directory.
* tools/labeling/regmax/regmax.cc: New source.
Propagate labels in the labeling histogram.
* tools/labeling/iz: New directory.
* tools/labeling/iz/Makefile: New directory.
* tools/labeling/iz/iz.cc: New source.
Import documentation directory.
* doc: New directory.
Import annotating search notes.
* doc/annotating/class.txt: New documentation text file.
* doc/annotating/syntheseMillet.txt: New documentation text file.
* doc/annotating/testMillet2008: New documentation text file.
Import milena learning examples.
* doc/examples: New directory.
* doc/examples/hello_world: New directory.
* doc/examples/hello_world/Makefile.am: New makefile.
* doc/examples/hello_world/hellow_world.cc: New source file.
* doc/examples/hello_world/print.cc: New source file.
* doc/examples/hello_milena: New directory.
* doc/examples/hello_milena/Makefile.am: New makefile.
* doc/examples/hello_milena/hello_milena.cc: New source file.
* doc/examples/learn_milena: New directory.
* doc/examples/learn_milena/Makefile.am: New makefile.
* doc/examples/learn_milena/learn_milena.cc: New source file.
* doc/examples/otsu: New directory.
* doc/examples/otsu/Makefile.am: New makefile.
* doc/examples/otsu/otsu.cc: New source file.
* doc/examples/frac: New directory.
* doc/examples/frac/Makefile.am: New makefile.
* doc/examples/frac/frac.cc: New source file.
* doc/examples/frac/frac.hh: New source file.
* doc/examples/frac/sign_prod.hh: New source file.
* doc/examples/frac/gcd.hh: New source file.
* doc/examples/accu_color: New directory.
* doc/examples/accu_color/accu_color.cc: New source file.
* doc/examples/io: New directory.
* doc/examples/io/Makefile.am: New makefile.
* doc/examples/io/io.cc: New source file.
Write down the basis of the quick tour summary documentation.
* doc/quick_tour: New specific directory.
* doc/quick_tour/quick_tour.tex: New documentation work.
Write down 3d currently used formulaes.
* doc/formulae: New specific directory.
* doc/formulae/formulae.tex: New recipe of 3d formulae.
---
scribo/sandbox/green/ChangeLog | 1083 ++++++++++++++++++++
scribo/sandbox/green/README.green | 346 ++++++-
.../regional_maxima}/Makefile.am | 0
.../labeling/regional_maxima/regional_maxima.cc | 198 ++++
.../demo/labeling/regional_maxima/thresholds.txt | 0
.../kmean1d => labeling/watershed}/Makefile.am | 0
.../green/demo/labeling/watershed}/gaussian.sh | 0
.../green/demo/labeling/watershed/watershed.cc | 360 +++++++
.../sandbox/green/doc/annotating/class.txt | 0
.../green/doc/annotating/syntheseMillet2008.txt | 0
.../sandbox/green/doc/annotating/testMillet2008 | 0
.../green/doc/examples/accu_color/accu_color.cc | 0
.../sandbox/green/doc/examples/frac/Makefile.am | 0
.../sandbox/green/doc/examples/frac/frac.cc | 0
.../sandbox/green/doc/examples/frac/frac.hh | 0
.../sandbox/green/doc/examples/frac/gcd.hh | 0
.../sandbox/green/doc/examples/frac/sign_prod.hh | 0
.../green/doc/examples/hello_milena/Makefile.am | 0
.../doc/examples/hello_milena/hello_milena.cc | 0
.../green/doc/examples/hello_world}/Makefile.am | 0
.../green/doc/examples/hello_world/hello_world.cc | 0
.../green/doc/examples/hello_world/print.cc | 0
.../sandbox/green/doc/examples/io/Makefile.am | 0
.../sandbox/green/doc/examples/io/io.cc | 0
.../green/doc/examples/learn_milena}/Makefile.am | 0
.../doc/examples/learn_milena/learn_milena.cc | 0
.../sandbox/green/doc/examples/otsu}/Makefile.am | 0
.../sandbox/green/doc/examples/otsu/otsu.cc | 0
.../sandbox/green/doc/examples/stats}/Makefile.am | 0
.../sandbox/green/doc/examples/stats/stats.cc | 0
.../sandbox/green/doc/formulae/formulae.tex | 0
.../sandbox/green/doc/quick_tour/quick_tour.tex | 0
.../sandbox/green/exp/regional_maxima/Makefile.am | 153 +++
.../green/exp/regional_maxima/regional_maxima.cc | 196 ++++
.../green/exp}/regional_maxima/thresholds.txt | 0
scribo/sandbox/green/mln/display/display_histo.hh | 149 +++-
scribo/sandbox/green/mln/display/project_histo.hh | 178 +++-
.../sandbox/green/tools/labeling/histo/Makefile.am | 153 +++
scribo/sandbox/green/tools/labeling/histo/histo.cc | 204 ++++
scribo/sandbox/green/tools/labeling/iz/Makefile.am | 153 +++
scribo/sandbox/green/tools/labeling/iz/iz.cc | 495 +++++++++
.../green/tools/labeling/opening/Makefile.am | 153 +++
.../green/tools/labeling/opening/opening.cc | 174 ++++
.../green/tools/labeling/regmax/Makefile.am | 153 +++
.../sandbox/green/tools/labeling/regmax/regmax.cc | 428 ++++++++
.../histo1d => display/display_histo}/Makefile.am | 0
.../use/display/display_histo/display_histo.cc | 86 ++
47 files changed, 4614 insertions(+), 48 deletions(-)
copy scribo/sandbox/green/demo/{clustering/kmean1d => labeling/regional_maxima}/Makefile.am (100%)
create mode 100644 scribo/sandbox/green/demo/labeling/regional_maxima/regional_maxima.cc
copy {milena => scribo}/sandbox/green/demo/labeling/regional_maxima/thresholds.txt (100%)
copy scribo/sandbox/green/demo/{clustering/kmean1d => labeling/watershed}/Makefile.am (100%)
copy {milena/sandbox/green/tests/accu/stat/histo1d => scribo/sandbox/green/demo/labeling/watershed}/gaussian.sh (100%)
create mode 100644 scribo/sandbox/green/demo/labeling/watershed/watershed.cc
copy {milena => scribo}/sandbox/green/doc/annotating/class.txt (100%)
copy {milena => scribo}/sandbox/green/doc/annotating/syntheseMillet2008.txt (100%)
copy {milena => scribo}/sandbox/green/doc/annotating/testMillet2008 (100%)
copy {milena => scribo}/sandbox/green/doc/examples/accu_color/accu_color.cc (100%)
copy {milena => scribo}/sandbox/green/doc/examples/frac/Makefile.am (100%)
copy {milena => scribo}/sandbox/green/doc/examples/frac/frac.cc (100%)
copy {milena => scribo}/sandbox/green/doc/examples/frac/frac.hh (100%)
copy {milena => scribo}/sandbox/green/doc/examples/frac/gcd.hh (100%)
copy {milena => scribo}/sandbox/green/doc/examples/frac/sign_prod.hh (100%)
copy {milena => scribo}/sandbox/green/doc/examples/hello_milena/Makefile.am (100%)
copy {milena => scribo}/sandbox/green/doc/examples/hello_milena/hello_milena.cc (100%)
copy {milena/sandbox/green/doc/examples/hello_milena => scribo/sandbox/green/doc/examples/hello_world}/Makefile.am (100%)
copy {milena => scribo}/sandbox/green/doc/examples/hello_world/hello_world.cc (100%)
copy {milena => scribo}/sandbox/green/doc/examples/hello_world/print.cc (100%)
copy {milena => scribo}/sandbox/green/doc/examples/io/Makefile.am (100%)
copy {milena => scribo}/sandbox/green/doc/examples/io/io.cc (100%)
copy {milena/sandbox/green/doc/examples/hello_milena => scribo/sandbox/green/doc/examples/learn_milena}/Makefile.am (100%)
copy {milena => scribo}/sandbox/green/doc/examples/learn_milena/learn_milena.cc (100%)
copy {milena/sandbox/green/doc/examples/hello_milena => scribo/sandbox/green/doc/examples/otsu}/Makefile.am (100%)
copy {milena => scribo}/sandbox/green/doc/examples/otsu/otsu.cc (100%)
copy {milena/sandbox/green/doc/examples/hello_milena => scribo/sandbox/green/doc/examples/stats}/Makefile.am (100%)
copy {milena => scribo}/sandbox/green/doc/examples/stats/stats.cc (100%)
copy {milena => scribo}/sandbox/green/doc/formulae/formulae.tex (100%)
copy {milena => scribo}/sandbox/green/doc/quick_tour/quick_tour.tex (100%)
create mode 100644 scribo/sandbox/green/exp/regional_maxima/Makefile.am
create mode 100644 scribo/sandbox/green/exp/regional_maxima/regional_maxima.cc
copy {milena/sandbox/green/demo/labeling => scribo/sandbox/green/exp}/regional_maxima/thresholds.txt (100%)
create mode 100644 scribo/sandbox/green/tools/labeling/histo/Makefile.am
create mode 100644 scribo/sandbox/green/tools/labeling/histo/histo.cc
create mode 100644 scribo/sandbox/green/tools/labeling/iz/Makefile.am
create mode 100644 scribo/sandbox/green/tools/labeling/iz/iz.cc
create mode 100644 scribo/sandbox/green/tools/labeling/opening/Makefile.am
create mode 100644 scribo/sandbox/green/tools/labeling/opening/opening.cc
create mode 100644 scribo/sandbox/green/tools/labeling/regmax/Makefile.am
create mode 100644 scribo/sandbox/green/tools/labeling/regmax/regmax.cc
copy scribo/sandbox/green/use/{accu/stat/histo1d => display/display_histo}/Makefile.am (100%)
create mode 100644 scribo/sandbox/green/use/display/display_histo/display_histo.cc
diff --git a/scribo/sandbox/green/ChangeLog b/scribo/sandbox/green/ChangeLog
index 9e9b7d6..5e4cb27 100644
--- a/scribo/sandbox/green/ChangeLog
+++ b/scribo/sandbox/green/ChangeLog
@@ -1,3 +1,1086 @@
+2010-07-07 Yann Jacquelet <jacquelet(a)lrde.epita.fr>
+
+ Import regional maxima sources from milena green's sandbox.
+
+ * README.green: Update documentation.
+
+ Implement a primary demonstrator with watershed labeling.
+
+ * demo/labeling/watershed: New directory.
+ * demo/labeling/watershed/Makefile.am: New makefile.
+ * demo/labeling/watershed/watershed.cc: New demo source.
+ * demo/labeling/watershed/gaussian.sh: New calibrate tools.
+
+ Implement a secondary demonstrator with regional maxima labeling.
+
+ * demo/labeling/regional_maxima: New directory.
+ * demo/labeling/regional_maxima/Makefile.am: New makefile.
+ * demo/labeling/regional_maxima/regional_maxima.cc: New demo source.
+ * demo/labeling/regional_maxima/threshold.txt: New threshold map file.
+
+ Implement the same demonstrator with directory scanning.
+
+ * exp/labeling/regional_maxima: New directory.
+ * exp/labeling/regional_maxima/Makefile.am: New makefile.
+ * exp/labeling/regional_maxima/regional_maxima.cc: New demo source.
+ * exp/labeling/regional_maxima/threshold.txt: New threshold map file.
+
+ Implement r/g projection.
+
+ * mln/display: New directory.
+ * mln/display/display_histo.hh: New library file.
+ * mln/display/project_histo.hh: New library file.
+
+ Give minimal code for using r/w projection.
+
+ * use/display/display_histo: New directory.
+ * use/display/display_histo/Makefile.am: New Makefile.
+ * use/display/display_histo/display_histo.cc: New source.
+
+ Divide the secondary demonstrator in four binaries in order to test it.
+
+ Implement the quantified RGB histogram.
+
+ * tools/labeling/histo: New directory.
+ * tools/labeling/histo/Makefile.am: new makefile.
+ * tools/labeling/histo/histo.cc: New source.
+
+ Filter the quantified RGB histogram by morphological volume attribute.
+
+ * tools/labeling/opening: New directory.
+ * tools/labeling/opening/Makefile.am: New makfile.
+ * tools/labeling/opening/opening.cc: New source.
+
+ Labeling the resulting histogram.
+
+ * tools/labeling/regmax: New directory.
+ * tools/labeling/regmax/Makefile: New directory.
+ * tools/labeling/regmax/regmax.cc: New source.
+
+ Propagate labels in the labeling histogram.
+
+ * tools/labeling/iz: New directory.
+ * tools/labeling/iz/Makefile: New directory.
+ * tools/labeling/iz/iz.cc: New source.
+
+ Import documentation directory.
+
+ * doc: New directory.
+
+ Import experimentation backups.
+
+ * doc/labeling: New directory.
+
+ * doc/labeling/cmp_methode: New directory.
+ * doc/labeling/cmp_method/h0_input.pgm.gz: New img file.
+ * doc/labeling/cmp_method/h2_mean.pgm.gz: New img file.
+ * doc/labeling/cmp_method/h2_merge.pgm.gz: New img file.
+ * doc/labeling/cmp_method/h3_mean.pgm.gz: New img file.
+ * doc/labeling/cmp_method/h3_merge.pgm.gz: New img file.
+ * doc/labeling/cmp_method/h4_mean.pgm.gz: New img file.
+ * doc/labeling/cmp_method/h4_merge.pgm.gz: New img file
+ * doc/labeling/cmp_method/h5_mean.pgm.gz: New img file.
+ * doc/labeling/cmp_method/h5_merge.pgm.gz: New img file.
+ * doc/labeling/cmp_method/i2_mean.ppm.gz: New img file.
+ * doc/labeling/cmp_method/i2_merge.ppm.gz: New img file.
+ * doc/labeling/cmp_method/i3_mean.ppm.gz: New img file.
+ * doc/labeling/cmp_method/i3_merge.ppm.gz: New img file.
+ * doc/labeling/cmp_method/i4_mean.ppm.gz: New img file.
+ * doc/labeling/cmp_method/i4_merge.ppm.gz: New img file
+ * doc/labeling/cmp_method/i5_mean.ppm.gz: New img file.
+ * doc/labeling/cmp_method/i5_merge.ppm.gz: New img file.
+ * doc/labeling/cmp_method/l2_input.pgm.gz: New img file.
+ * doc/labeling/cmp_method/l3_input.pgm.gz: New img file.
+ * doc/labeling/cmp_method/l4_input.pgm.gz: New img file.
+ * doc/labeling/cmp_method/l5_input.pgm.gz: New img file.
+ * doc/labeling/cmp_method/s2_histo.txt.gz: New txt file.
+ * doc/labeling/cmp_method/s3_histo.txt.gz: New txt file.
+ * doc/labeling/cmp_method/s4_histo.txt.gz: New txt file.
+ * doc/labeling/cmp_method/s5_histo.txt.gz: New txt file.
+ * doc/labeling/cmp_method/reponse_theo.eml.gz: New email.
+ * doc/labeling/cmp_method/synthese.txt.gz: New experiment doc.
+
+ * doc/labeling/cmp_quant: New directory.
+ * doc/labeling/cmp_quant/h0_input.pgm.gz: New img file.
+ * doc/labeling/cmp_quant/h5_mean_q2.pgm.gz: New img file.
+ * doc/labeling/cmp_quant/h5_mean_q3.pgm.gz: New img file.
+ * doc/labeling/cmp_quant/h5_mean_q4.pgm.gz: New img file.
+ * doc/labeling/cmp_quant/h5_mean_q5.pgm.gz: New img file.
+ * doc/labeling/cmp_quant/h5_mean_q6.pgm.gz: New img file.
+ * doc/labeling/cmp_quant/h5_mean_q7.pgm.gz: New img file.
+ * doc/labeling/cmp_quant/h5_mean_q8.pgm.gz: New img file.
+ * doc/labeling/cmp_quant/h5_merge_q2.pgm.gz: New img file.
+ * doc/labeling/cmp_quant/h5_merge_q3.pgm.gz: New img file.
+ * doc/labeling/cmp_quant/h5_merge_q4.pgm.gz: New img file.
+ * doc/labeling/cmp_quant/h5_merge_q5.pgm.gz: New img file.
+ * doc/labeling/cmp_quant/h5_merge_q6.pgm.gz: New img file.
+ * doc/labeling/cmp_quant/h5_merge_q7.pgm.gz: New img file.
+ * doc/labeling/cmp_quant/h5_merge_q8.pgm.gz: New img file.
+ * doc/labeling/cmp_quant/i5_mean_q2.ppm.gz: New img file.
+ * doc/labeling/cmp_quant/i5_mean_q3.ppm.gz: New img file.
+ * doc/labeling/cmp_quant/i5_mean_q4.ppm.gz: New img file.
+ * doc/labeling/cmp_quant/i5_mean_q5.ppm.gz: New img file.
+ * doc/labeling/cmp_quant/i5_mean_q6.ppm.gz: New img file.
+ * doc/labeling/cmp_quant/i5_mean_q7.ppm.gz: New img file.
+ * doc/labeling/cmp_quant/i5_mean_q8.ppm.gz: New img file.
+ * doc/labeling/cmp_quant/i5_merge_q2.ppm.gz: New img file.
+ * doc/labeling/cmp_quant/i5_merge_q3.ppm.gz: New img file.
+ * doc/labeling/cmp_quant/i5_merge_q4.ppm.gz: New img file.
+ * doc/labeling/cmp_quant/i5_merge_q5.ppm.gz: New img file.
+ * doc/labeling/cmp_quant/i5_merge_q6.ppm.gz: New img file.
+ * doc/labeling/cmp_quant/i5_merge_q7.ppm.gz: New img file.
+ * doc/labeling/cmp_quant/i5_merge_q8.ppm.gz: New img file.
+ * doc/labeling/cmp_quant/l5_input_q2.pgm.gz: New img file.
+ * doc/labeling/cmp_quant/l5_input_q3.pgm.gz: New img file.
+ * doc/labeling/cmp_quant/l5_input_q4.pgm.gz: New img file.
+ * doc/labeling/cmp_quant/l5_input_q5.pgm.gz: New img file.
+ * doc/labeling/cmp_quant/l5_input_q6.pgm.gz: New img file.
+ * doc/labeling/cmp_quant/l5_input_q7.pgm.gz: New img file.
+ * doc/labeling/cmp_quant/l5_input_q8.pgm.gz: New img file.
+ * doc/labeling/cmp_quant/s5_histo_q2.txt.gz: New txt file.
+ * doc/labeling/cmp_quant/s5_histo_q3.txt.gz: New txt file.
+ * doc/labeling/cmp_quant/s5_histo_q4.txt.gz: New txt file.
+ * doc/labeling/cmp_quant/s5_histo_q5.txt.gz: New txt file.
+ * doc/labeling/cmp_quant/s5_histo_q6.txt.gz: New txt file.
+ * doc/labeling/cmp_quant/s5_histo_q7.txt.gz: New txt file.
+ * doc/labeling/cmp_quant/s5_histo_q8.txt.gz: New txt file.
+ * doc/labeling/cmp_quant/synthese.txt.gz: New experiment doc.
+
+ * doc/labeling/mp00411c: New directory.
+ * doc/labeling/mp00411c/colormap_all_q4.txt.gz: New txt file.
+ * doc/labeling/mp00411c/colormap_all_q5.txt.gz: New txt file.
+ * doc/labeling/mp00411c/colormap_thick_q4.txt.gz: New txt file.
+ * doc/labeling/mp00411c/colormap_thick_q5.txt.gz: New txt file.
+ * doc/labeling/mp00411c/colormap_thin_q4.txt.gz: New txt file.
+ * doc/labeling/mp00411c/colormap_thin_q5.txt.gz: New txt file.
+ * doc/labeling/mp00411c/histo_all_q4.dump.gz: New dump file.
+ * doc/labeling/mp00411c/histo_all_q5.dump.gz: New dump file.
+ * doc/labeling/mp00411c/histo_thick_q4.dump.gz: New dump file.
+ * doc/labeling/mp00411c/histo_thick_q5.dump.gz: New dump file.
+ * doc/labeling/mp00411c/histo_thin_q4.dump.gz: New dump file.
+ * doc/labeling/mp00411c/histo_thin_q5.dump.gz: New dump file.
+ * doc/labeling/mp00411c/iz_all_q4.dump.gz: New dump file.
+ * doc/labeling/mp00411c/iz_all_q5.dump.gz: New dump file.
+ * doc/labeling/mp00411c/iz_thick_q4.dump.gz: New dump file.
+ * doc/labeling/mp00411c/iz_thick_q5.dump.gz: New dump file.
+ * doc/labeling/mp00411c/iz_thin_q4.dump.gz: New dump file.
+ * doc/labeling/mp00411c/iz_thin_q5.dump.gz: New dump file.
+ * doc/labeling/mp00411c/labeled_all_q4.dump.gz: New dump file.
+ * doc/labeling/mp00411c/labeled_all_q5.dump.gz: New dump file.
+ * doc/labeling/mp00411c/labeled_thick_q4.dump.gz: New dump file.
+ * doc/labeling/mp00411c/labeled_thick_q5.dump.gz: New dump file.
+ * doc/labeling/mp00411c/labeled_thin_q4.dump.gz: New dump file.
+ * doc/labeling/mp00411c/labeled_thin_q5.dump.gz: New dump file.
+ * doc/labeling/mp00411c/mean3_all_q4.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/mean3_all_q5.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/mean3_thick_q4.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/mean3_thick_q5.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/mean3_thin_q4.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/mean3_thin_q5.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/mean4_all_q4.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/mean4_all_q5.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/mean4_thick_q4.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/mean4_thick_q5.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/mean4_thin_q4.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/mean4_thin_q5.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/mp00411c.ppm.gz: New input file.
+ * doc/labeling/mp00411c/mp00411c_thin.pbm.gz: New gradient mask.
+ * doc/labeling/mp00411c/mp00411c_thick.pbm.gz: New gradient mask.
+ * doc/labeling/mp00411c/mp00411c.sh.gz: New script shell.
+ * doc/labeling/mp00411c/opened_all_q4.dump.gz: New dump file.
+ * doc/labeling/mp00411c/opened_all_q5.dump.gz: New dump file.
+ * doc/labeling/mp00411c/opened_thick_q4.dump.gz: New dump file.
+ * doc/labeling/mp00411c/opened_thick_q5.dump.gz: New dump file.
+ * doc/labeling/mp00411c/opened_thin_q4.dump.gz: New dump file.
+ * doc/labeling/mp00411c/opened_thin_q5.dump.gz: New dump file.
+ * doc/labeling/mp00411c/proj1_all_q4.pgm.gz: New pgm file.
+ * doc/labeling/mp00411c/proj1_all_q5.pgm.gz: New pgm file.
+ * doc/labeling/mp00411c/proj1_thick_q4.pgm.gz: New pgm file.
+ * doc/labeling/mp00411c/proj1_thick_q5.pgm.gz: New pgm file.
+ * doc/labeling/mp00411c/proj1_thin_q4.pgm.gz: New pgm file.
+ * doc/labeling/mp00411c/proj1_thin_q5.pgm.gz: New pgm file.
+ * doc/labeling/mp00411c/proj2_all_q4.pgm.gz: New pgm file.
+ * doc/labeling/mp00411c/proj2_all_q5.pgm.gz: New pgm file.
+ * doc/labeling/mp00411c/proj2_thick_q4.pgm.gz: New pgm file.
+ * doc/labeling/mp00411c/proj2_thick_q5.pgm.gz: New pgm file.
+ * doc/labeling/mp00411c/proj2_thin_q4.pgm.gz: New pgm file.
+ * doc/labeling/mp00411c/proj2_thin_q5.pgm.gz: New pgm file.
+ * doc/labeling/mp00411c/proj3_all_q4.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/proj3_all_q5.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/proj3_thick_q4.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/proj3_thick_q5.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/proj3_thin_q4.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/proj3_thin_q5.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/proj4_all_q4.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/proj4_all_q5.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/proj4_thick_q4.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/proj4_thick_q5.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/proj4_thin_q4.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/proj4_thin_q5.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/quant_q4.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/quant_q5.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/stat3_all_q4.txt.gz: New txt file.
+ * doc/labeling/mp00411c/stat3_all_q5.txt.gz: New txt file.
+ * doc/labeling/mp00411c/stat3_thick_q4.txt.gz: New txt file.
+ * doc/labeling/mp00411c/stat3_thick_q5.txt.gz: New txt file.
+ * doc/labeling/mp00411c/stat3_thin_q4.txt.gz: New txt file.
+ * doc/labeling/mp00411c/stat3_thin_q5.txt.gz: New txt file.
+ * doc/labeling/mp00411c/stat4_all_q4.txt.gz: New txt file.
+ * doc/labeling/mp00411c/stat4_all_q5.txt.gz: New txt file.
+ * doc/labeling/mp00411c/stat4_thick_q4.txt.gz: New txt file.
+ * doc/labeling/mp00411c/stat4_thick_q5.txt.gz: New txt file.
+ * doc/labeling/mp00411c/stat4_thin_q4.txt.gz: New txt file.
+ * doc/labeling/mp00411c/stat4_thin_q5.txt.gz: New txt file.
+ * doc/labeling/mp00411c/synthese.txt.gz: New txt file.
+
+ * doc/labeling/mp00307c_bis: New directory.
+ * doc/labeling/mp00307c_bis/colormap_all_q4_r06f.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_all_q4_r06h.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_all_q4_r18f.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_all_q4_r18h.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_all_q4_r26f.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_all_q4_r26h.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_all_q5_r06f.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_all_q5_r06h.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_all_q5_r18f.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_all_q5_r18h.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_all_q5_r26f.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_all_q5_r26h.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thin_q4_r06f.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thin_q4_r06h.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thin_q4_r18f.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thin_q4_r18h.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thin_q4_r26f.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thin_q4_r26h.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thin_q5_r06f.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thin_q5_r06h.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thin_q5_r18f.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thin_q5_r18h.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thin_q5_r26f.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thin_q5_r26h.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thick_q4_r06f.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thick_q4_r06h.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thick_q4_r18f.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thick_q4_r18h.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thick_q4_r26f.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thick_q4_r26h.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thick_q5_r06f.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thick_q5_r06h.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thick_q5_r18f.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thick_q5_r18h.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thick_q5_r26f.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thick_q5_r26h.txt: New colormap.
+ * doc/labeling/mp00307c_bis/histo_all_q4.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/histo_all_q5.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/histo_all_q8.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/histo_thin_q4.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/histo_thin_q5.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/histo_thin_q8.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/histo_thick_q4.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/histo_thick_q5.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/histo_thick_q8.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/iz_all_q4_r06f_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q4_r06f_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q4_r06f_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q4_r06h_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q4_r06h_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q4_r06h_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q4_r18f_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q4_r18f_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q4_r18f_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q4_r18h_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q4_r18h_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q4_r18h_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q4_r26f_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q4_r26f_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q4_r26f_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q4_r26h_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q4_r26h_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q4_r26h_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q5_r06f_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q5_r06f_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q5_r06f_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q5_r06h_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q5_r06h_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q5_r06h_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q5_r18f_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q5_r18f_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q5_r18f_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q5_r18h_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q5_r18h_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q5_r18h_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q5_r26f_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q5_r26f_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q5_r26f_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q5_r26h_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q5_r26h_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q5_r26h_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q4_r06f_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q4_r06f_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q4_r06f_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q4_r06h_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q4_r06h_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q4_r06h_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q4_r18f_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q4_r18f_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q4_r18f_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q4_r18h_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q4_r18h_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q4_r18h_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q4_r26f_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q4_r26f_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q4_r26f_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q4_r26h_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q4_r26h_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q4_r26h_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q5_r06f_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q5_r06f_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q5_r06f_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q5_r06h_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q5_r06h_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q5_r06h_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q5_r18f_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q5_r18f_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q5_r18f_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q5_r18h_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q5_r18h_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q5_r18h_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q5_r26f_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q5_r26f_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q5_r26f_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q5_r26h_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q5_r26h_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q5_r26h_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thick_q4_r06f_i06.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q4_r06f_i18.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q4_r06f_i26.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q4_r06h_i06.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q4_r06h_i18.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q4_r06h_i26.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q4_r18f_i06.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q4_r18f_i18.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q4_r18f_i26.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q4_r18h_i06.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q4_r18h_i18.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q4_r18h_i26.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q4_r26f_i06.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q4_r26f_i18.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q4_r26f_i26.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q4_r26h_i06.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q4_r26h_i18.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q4_r26h_i26.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q5_r06f_i06.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q5_r06f_i18.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q5_r06f_i26.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q5_r06h_i06.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q5_r06h_i18.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q5_r06h_i26.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q5_r18f_i06.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q5_r18f_i18.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q5_r18f_i26.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q5_r18h_i06.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q5_r18h_i18.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q5_r18h_i26.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q5_r26f_i06.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q5_r26f_i18.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q5_r26f_i26.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q5_r26h_i06.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q5_r26h_i18.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q5_r26h_i26.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/labeled_all_q4_r06f.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_all_q4_r06h.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_all_q4_r18f.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_all_q4_r18h.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_all_q4_r28f.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_all_q4_r28h.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_all_q5_r06f.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_all_q5_r06h.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_all_q5_r18f.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_all_q5_r18h.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_all_q5_r28f.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_all_q5_r28h.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thin_q4_r06f.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thin_q4_r06h.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thin_q4_r18f.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thin_q4_r18h.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thin_q4_r28f.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thin_q4_r28h.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thin_q5_r06f.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thin_q5_r06h.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thin_q5_r18f.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thin_q5_r18h.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thin_q5_r28f.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thin_q5_r28h.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thick_q4_r06f.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thick_q4_r06h.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thick_q4_r18f.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thick_q4_r18h.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thick_q4_r28f.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thick_q4_r28h.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thick_q5_r06f.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thick_q5_r06h.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thick_q5_r18f.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thick_q5_r18h.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thick_q5_r28f.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thick_q5_r28h.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/mean3_all_q4_r06f.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_all_q4_r06h.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_all_q4_r18f.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_all_q4_r18h.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_all_q4_r26f.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_all_q4_r26h.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_all_q5_r06f.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_all_q5_r06h.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_all_q5_r18f.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_all_q5_r18h.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_all_q5_r26f.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_all_q5_r26h.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thin_q4_r06f.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thin_q4_r06h.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thin_q4_r18f.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thin_q4_r18h.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thin_q4_r26f.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thin_q4_r26h.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thin_q5_r06f.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thin_q5_r06h.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thin_q5_r18f.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thin_q5_r18h.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thin_q5_r26f.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thin_q5_r26h.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thick_q4_r06f.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thick_q4_r06h.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thick_q4_r18f.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thick_q4_r18h.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thick_q4_r26f.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thick_q4_r26h.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thick_q5_r06f.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thick_q5_r06h.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thick_q5_r18f.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thick_q5_r18h.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thick_q5_r26f.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thick_q5_r26h.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q4_r06f_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q4_r06f_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q4_r06f_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q4_r06h_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q4_r06h_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q4_r06h_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q4_r18f_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q4_r18f_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q4_r18f_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q4_r18h_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q4_r18h_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q4_r18h_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q4_r26f_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q4_r26f_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q4_r26f_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q4_r26h_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q4_r26h_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q4_r26h_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q5_r06f_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q5_r06f_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q5_r06f_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q5_r06h_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q5_r06h_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q5_r06h_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q5_r18f_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q5_r18f_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q5_r18f_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q5_r18h_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q5_r18h_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q5_r18h_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q5_r26f_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q5_r26f_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q5_r26f_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q5_r26h_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q5_r26h_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q5_r26h_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q4_r06f_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q4_r06f_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q4_r06f_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q4_r06h_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q4_r06h_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q4_r06h_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q4_r18f_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q4_r18f_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q4_r18f_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q4_r18h_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q4_r18h_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q4_r18h_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q4_r26f_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q4_r26f_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q4_r26f_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q4_r26h_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q4_r26h_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q4_r26h_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q5_r06f_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q5_r06f_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q5_r06f_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q5_r06h_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q5_r06h_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q5_r06h_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q5_r18f_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q5_r18f_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q5_r18f_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q5_r18h_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q5_r18h_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q5_r18h_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q5_r26f_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q5_r26f_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q5_r26f_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q5_r26h_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q5_r26h_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q5_r26h_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thick_q4_r06f_i06.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q4_r06f_i18.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q4_r06f_i26.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q4_r06h_i06.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q4_r06h_i18.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q4_r06h_i26.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q4_r18f_i06.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q4_r18f_i18.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q4_r18f_i26.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q4_r18h_i06.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q4_r18h_i18.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q4_r18h_i26.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q4_r26f_i06.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q4_r26f_i18.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q4_r26f_i26.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q4_r26h_i06.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q4_r26h_i18.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q4_r26h_i26.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q5_r06f_i06.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q5_r06f_i18.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q5_r06f_i26.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q5_r06h_i06.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q5_r06h_i18.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q5_r06h_i26.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q5_r18f_i06.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q5_r18f_i18.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q5_r18f_i26.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q5_r18h_i06.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q5_r18h_i18.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q5_r18h_i26.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q5_r26f_i06.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q5_r26f_i18.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q5_r26f_i26.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q5_r26h_i06.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q5_r26h_i18.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q5_r26h_i26.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mp00307c.ppm.gz: New input img.
+ * doc/labeling/mp00307c_bis/mp00307c.sh.gz: New script shell.
+ * doc/labeling/mp00307c_bis/mp00307c_thick.pgm.gz: New mask.
+ * doc/labeling/mp00307c_bis/mp00307c_thin.pgm.gz: New mask.
+ * doc/labeling/mp00307c_bis/opened_all_q4.dump.gz: New filtered histo.
+ * doc/labeling/mp00307c_bis/opened_all_q5.dump.gz: New filtered histo.
+ * doc/labeling/mp00307c_bis/opened_all_q8.dump.gz: New filtered histo.
+ * doc/labeling/mp00307c_bis/opened_thin_q4.dump.gz: New filtered histo.
+ * doc/labeling/mp00307c_bis/opened_thin_q5.dump.gz: New filtered histo.
+ * doc/labeling/mp00307c_bis/opened_thin_q8.dump.gz: New filtered histo.
+ * doc/labeling/mp00307c_bis/opened_thick_q4.dump.gz: New filtered histo.
+ * doc/labeling/mp00307c_bis/opened_thick_q5.dump.gz: New filtered histo.
+ * doc/labeling/mp00307c_bis/opened_thick_q8.dump.gz: New filtered histo.
+ * doc/labeling/mp00307c_bis/proj1_all_q4.pgm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj1_all_q4.ppm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj1_all_q5.pgm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj1_all_q5.ppm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj1_all_q8.pgm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj1_all_q8.ppm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj1_thin_q4.pgm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj1_thin_q4.ppm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj1_thin_q5.pgm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj1_thin_q5.ppm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj1_thin_q8.pgm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj1_thin_q8.ppm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj1_thick_q4.pgm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj1_thick_q4.ppm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj1_thick_q5.pgm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj1_thick_q5.ppm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj1_thick_q8.pgm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj1_thick_q8.ppm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj2_all_q4.pgm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj2_all_q4.ppm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj2_all_q5.pgm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj2_all_q5.ppm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj2_all_q8.pgm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj2_all_q8.ppm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj2_thin_q4.pgm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj2_thin_q4.ppm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj2_thin_q5.pgm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj2_thin_q5.ppm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj2_thin_q8.pgm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj2_thin_q8.ppm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj2_thick_q4.pgm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj2_thick_q4.ppm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj2_thick_q5.pgm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj2_thick_q5.ppm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj2_thick_q8.pgm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj2_thick_q8.ppm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj3_all_q4_r06f.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_all_q4_r06h.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_all_q4_r18f.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_all_q4_r18h.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_all_q4_r26f.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_all_q4_r26h.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_all_q5_r06f.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_all_q5_r06h.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_all_q5_r18f.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_all_q5_r18h.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_all_q5_r26f.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_all_q5_r26h.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thin_q4_r06f.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thin_q4_r06h.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thin_q4_r18f.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thin_q4_r18h.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thin_q4_r26f.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thin_q4_r26h.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thin_q5_r06f.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thin_q5_r06h.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thin_q5_r18f.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thin_q5_r18h.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thin_q5_r26f.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thin_q5_r26h.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thick_q4_r06f.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thick_q4_r06h.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thick_q4_r18f.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thick_q4_r18h.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thick_q4_r26f.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thick_q4_r26h.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thick_q5_r06f.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thick_q5_r06h.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thick_q5_r18f.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thick_q5_r18h.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thick_q5_r26f.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thick_q5_r26h.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj4_all_q4_r06f_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q4_r06f_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q4_r06f_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q4_r06h_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q4_r06h_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q4_r06h_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q4_r18f_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q4_r18f_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q4_r18f_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q4_r18h_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q4_r18h_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q4_r18h_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q4_r26f_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q4_r26f_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q4_r26f_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q4_r26h_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q4_r26h_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q4_r26h_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q5_r06f_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q5_r06f_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q5_r06f_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q5_r06h_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q5_r06h_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q5_r06h_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q5_r18f_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q5_r18f_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q5_r18f_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q5_r18h_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q5_r18h_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q5_r18h_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q5_r26f_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q5_r26f_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q5_r26f_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q5_r26h_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q5_r26h_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q5_r26h_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q4_r06f_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q4_r06f_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q4_r06f_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q4_r06h_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q4_r06h_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q4_r06h_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q4_r18f_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q4_r18f_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q4_r18f_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q4_r18h_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q4_r18h_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q4_r18h_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q4_r26f_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q4_r26f_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q4_r26f_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q4_r26h_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q4_r26h_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q4_r26h_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q5_r06f_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q5_r06f_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q5_r06f_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q5_r06h_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q5_r06h_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q5_r06h_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q5_r18f_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q5_r18f_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q5_r18f_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q5_r18h_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q5_r18h_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q5_r18h_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q5_r26f_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q5_r26f_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q5_r26f_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q5_r26h_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q5_r26h_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q5_r26h_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q4_r06f_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q4_r06f_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q4_r06f_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q4_r06h_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q4_r06h_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q4_r06h_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q4_r18f_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q4_r18f_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q4_r18f_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q4_r18h_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q4_r18h_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q4_r18h_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q4_r26f_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q4_r26f_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q4_r26f_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q4_r26h_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q4_r26h_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q4_r26h_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q5_r06f_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q5_r06f_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q5_r06f_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q5_r06h_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q5_r06h_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q5_r06h_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q5_r18f_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q5_r18f_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q5_r18f_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q5_r18h_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q5_r18h_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q5_r18h_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q5_r26f_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q5_r26f_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q5_r26f_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q5_r26h_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q5_r26h_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q5_r26h_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/quant_q4.ppm.gz: New quantified img.
+ * doc/labeling/mp00307c_bis/quant_q5.ppm.gz: New quantified img.
+ * doc/labeling/mp00307c_bis/quant_q8.ppm.gz: New quantified img.
+ * doc/labeling/mp00307c_bis/stats3_all_q4_r06f.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_all_q4_r06h.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_all_q4_r18f.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_all_q4_r18h.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_all_q4_r26f.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_all_q4_r26h.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_all_q5_r06f.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_all_q5_r06h.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_all_q5_r18f.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_all_q5_r18h.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_all_q5_r26f.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_all_q5_r26h.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thin_q4_r06f.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thin_q4_r06h.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thin_q4_r18f.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thin_q4_r18h.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thin_q4_r26f.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thin_q4_r26h.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thin_q5_r06f.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thin_q5_r06h.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thin_q5_r18f.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thin_q5_r18h.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thin_q5_r26f.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thin_q5_r26h.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thick_q4_r06f.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thick_q4_r06h.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thick_q4_r18f.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thick_q4_r18h.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thick_q4_r26f.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thick_q4_r26h.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thick_q5_r06f.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thick_q5_r06h.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thick_q5_r18f.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thick_q5_r18h.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thick_q5_r26f.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thick_q5_r26h.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q4_r06f_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q4_r06f_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q4_r06f_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q4_r06h_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q4_r06h_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q4_r06h_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q4_r18f_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q4_r18f_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q4_r18f_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q4_r18h_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q4_r18h_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q4_r18h_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q4_r26f_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q4_r26f_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q4_r26f_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q4_r26h_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q4_r26h_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q4_r26h_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q5_r06f_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q5_r06f_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q5_r06f_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q5_r06h_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q5_r06h_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q5_r06h_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q5_r18f_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q5_r18f_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q5_r18f_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q5_r18h_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q5_r18h_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q5_r18h_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q5_r26f_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q5_r26f_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q5_r26f_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q5_r26h_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q5_r26h_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q5_r26h_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q4_r06f_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q4_r06f_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q4_r06f_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q4_r06h_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q4_r06h_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q4_r06h_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q4_r18f_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q4_r18f_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q4_r18f_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q4_r18h_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q4_r18h_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q4_r18h_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q4_r26f_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q4_r26f_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q4_r26f_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q4_r26h_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q4_r26h_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q4_r26h_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q5_r06f_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q5_r06f_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q5_r06f_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q5_r06h_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q5_r06h_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q5_r06h_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q5_r18f_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q5_r18f_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q5_r18f_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q5_r18h_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q5_r18h_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q5_r18h_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q5_r26f_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q5_r26f_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q5_r26f_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q5_r26h_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q5_r26h_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q5_r26h_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q4_r06f_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q4_r06f_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q4_r06f_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q4_r06h_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q4_r06h_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q4_r06h_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q4_r18f_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q4_r18f_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q4_r18f_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q4_r18h_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q4_r18h_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q4_r18h_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q4_r26f_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q4_r26f_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q4_r26f_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q4_r26h_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q4_r26h_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q4_r26h_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q5_r06f_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q5_r06f_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q5_r06f_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q5_r06h_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q5_r06h_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q5_r06h_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q5_r18f_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q5_r18f_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q5_r18f_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q5_r18h_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q5_r18h_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q5_r18h_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q5_r26f_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q5_r26f_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q5_r26f_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q5_r26h_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q5_r26h_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q5_r26h_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/synthese.txt.gz: New synthesis file.
+
+
+ * doc/labeling/mp00042c: New directory.
+ * doc/labeling/mp00042c/histo_all.dump.gz: New histo.
+ * doc/labeling/mp00042c/histo_thick.dump.gz: New histo.
+ * doc/labeling/mp00042c/histo_thin.dump.gz: New histo.
+ * doc/labeling/mp00042c/labeled_all.dump.gz: New labeled histo.
+ * doc/labeling/mp00042c/labeled_thick.dump.gz: New labeled histo.
+ * doc/labeling/mp00042c/labeled_thin.dump.gz: New labeled histo.
+ * doc/labeling/mp00042c/mean_all.dump.gz: New mean img.
+ * doc/labeling/mp00042c/mean_thin.dump.gz: New mean img.
+ * doc/labeling/mp00042c/mean_thick.dump.gz: New mean img.
+ * doc/labeling/mp00042c/mp00042c.ppm.gz: New input img.
+ * doc/labeling/mp00042c/mp00042c.sh.gz: New script shell.
+ * doc/labeling/mp00042c/mp00042c_thick.gz: New mask.
+ * doc/labeling/mp00042c/mp00042c_thin.gz: New mask.
+ * doc/labeling/mp00042c/opened_all.gz: New filtered histo.
+ * doc/labeling/mp00042c/opened_thin.gz: New filtered histo.
+ * doc/labeling/mp00042c/opened_thick.gz: New filtered histo.
+ * doc/labeling/mp00042c/pal_all.gz: New colormap.
+ * doc/labeling/mp00042c/pal_thin.gz: New colormap.
+ * doc/labeling/mp00042c/pal_thick.gz: New colormap.
+ * doc/labeling/mp00042c/proj1.pgm.gz: New r/g projection.
+ * doc/labeling/mp00042c/proj2.pgm.gz: New r/g projection.
+ * doc/labeling/mp00042c/proj3.ppm.gz: New r/g projection.
+ * doc/labeling/mp00042c/proj2_all.pgm.gz: New r/g projection
+ * doc/labeling/mp00042c/proj2_thin.pgm.gz: New r/g projection.
+ * doc/labeling/mp00042c/proj2_thick.pgm.gz: New r/g projection.
+ * doc/labeling/mp00042c/proj3_all.pgm.gz: New r/g projection.
+ * doc/labeling/mp00042c/proj3_thin.pgm.gz: New r/g projection.
+ * doc/labeling/mp00042c/proj3_thick.pgm.gz: New r/g projection.
+ * doc/labeling/mp00042c/proj_all.pgm.gz: New r/g projection.
+ * doc/labeling/mp00042c/proj_thick.pgm.gz: New r/g projection.
+ * doc/labeling/mp00042c/proj_thin.pgm.gz: New r/g projection.
+ * doc/labeling/mp00042c/quant.ppm.gz: New quantified img.
+
+ * doc/labeling/mp00307c: New directory.
+ * doc/labeling/mp00307c/colormap_all.txt.tgz: New colormap.
+ * doc/labeling/mp00307c/colormap_thin.txt.tgz: New colormap.
+ * doc/labeling/mp00307c/colormap_thick.txt.tgz: New colormap.
+ * doc/labeling/mp00307c/histo_all.dump.tgz: New histo.
+ * doc/labeling/mp00307c/histo_thin.dump.tgz: New histo.
+ * doc/labeling/mp00307c/histo_thick.dump.tgz: New histo.
+ * doc/labeling/mp00307c/iz_all.dump.tgz: New label propagation..
+ * doc/labeling/mp00307c/iz_thick.dump.tgz: New label propagation..
+ * doc/labeling/mp00307c/labeled_all.dump.tgz: New label histo.
+ * doc/labeling/mp00307c/labeled_thin.dump.tgz: New label histo.
+ * doc/labeling/mp00307c/labeled_thick.dump.tgz: New label histo.
+ * doc/labeling/mp00307c/mean3_all.ppm.tgz: New mean img.
+ * doc/labeling/mp00307c/mean3_thin.ppm.tgz: New mean img.
+ * doc/labeling/mp00307c/mean3_thick.ppm.tgz: New mean img.
+ * doc/labeling/mp00307c/mean4_all.ppm.tgz: New mean img.
+ * doc/labeling/mp00307c/mean4_thin.ppm.tgz: New mean img.
+ * doc/labeling/mp00307c/mean4_thick.ppm.tgz: New mean img.
+ * doc/labeling/mp00307c/mp00307.ppm.tgz: New input img.
+ * doc/labeling/mp00307c/mp00307.sh.tgz: New script shell.
+ * doc/labeling/mp00307c/mp00307_thin.pbm.tgz: New mask.
+ * doc/labeling/mp00307c/mp00307_thick.pbm.tgz: New mask.
+ * doc/labeling/mp00307c/opened_all.dump.tgz: New filtered img.
+ * doc/labeling/mp00307c/opened_thin.dump.tgz: New filtered img.
+ * doc/labeling/mp00307c/opened_thick.dump.tgz: New filtered img.
+ * doc/labeling/mp00307c/proj1_all.pgm.tgz: New r/g projection.
+ * doc/labeling/mp00307c/proj1_all.ppm.tgz: New r/g projection.
+ * doc/labeling/mp00307c/proj1_thin.pgm.tgz: New r/g projection.
+ * doc/labeling/mp00307c/proj1_thin.ppm.tgz: New r/g projection.
+ * doc/labeling/mp00307c/proj1_thick.pgm.tgz: New r/g projection.
+ * doc/labeling/mp00307c/proj1_thick.ppm.tgz: New r/g projection.
+ * doc/labeling/mp00307c/proj2_all.pgm.tgz: New r/g projection.
+ * doc/labeling/mp00307c/proj2_all.ppm.tgz: New r/g projection.
+ * doc/labeling/mp00307c/proj2_thin.pgm.tgz: New r/g projection.
+ * doc/labeling/mp00307c/proj2_thin.ppm.tgz: New r/g projection.
+ * doc/labeling/mp00307c/proj2_thick.pgm.tgz: New r/g projection.
+ * doc/labeling/mp00307c/proj2_thick.ppm.tgz: New r/g projection.
+ * doc/labeling/mp00307c/proj3_all.pgm.tgz: New r/g projection.
+ * doc/labeling/mp00307c/proj3_all.ppm.tgz: New r/g projection.
+ * doc/labeling/mp00307c/proj3_thin.pgm.tgz: New r/g projection.
+ * doc/labeling/mp00307c/proj3_thin.ppm.tgz: New r/g projection.
+ * doc/labeling/mp00307c/proj3_thick.pgm.tgz: New r/g projection.
+ * doc/labeling/mp00307c/proj3_thick.ppm.tgz: New r/g projection.
+ * doc/labeling/mp00307c/proj4_all.pgm.tgz: New r/g projection.
+ * doc/labeling/mp00307c/proj4_all.ppm.tgz: New r/g projection.
+ * doc/labeling/mp00307c/proj4_thin.pgm.tgz: New r/g projection.
+ * doc/labeling/mp00307c/proj4_thin.ppm.tgz: New r/g projection.
+ * doc/labeling/mp00307c/proj4_thick.pgm.tgz: New r/g projection.
+ * doc/labeling/mp00307c/proj4_thick.ppm.tgz: New r/g projection
+ * doc/labeling/mp00307c/quant.ppm.tgz: New quantified img
+ * doc/labeling/mp00307c/stats3_all.txt.tgz: New stats file.
+ * doc/labeling/mp00307c/stats3_thin.txt.tgz: New stats file.
+ * doc/labeling/mp00307c/stats3_thick.txt.tgz: New stats file.
+ * doc/labeling/mp00307c/stats4_all.txt.tgz: New stats file.
+ * doc/labeling/mp00307c/stats4_thin.txt.tgz: New stats file.
+ * doc/labeling/mp00307c/stats4_thick.txt.tgz: New stats file.
+ * doc/labeling/mp00307c/synthese.txt.tgz: New synthesis file.
+
+ Import materials for next tests.
+
+ * doc/labeling/mp00215c: New directory.
+ * doc/labeling/mp00215c/mp00215c.ppm.gz: New color input img.
+ * doc/labeling/mp00215c/mp00215c_thick.pbm.gz: New thick mask.
+ * doc/labeling/mp00215c/mp00215c_thin.pbm.gz: New thin mask.
+
+ * doc/labeling/mp00234c: New directory.
+ * doc/labeling/mp00234c/mp00234c.ppm.gz: New color input img.
+ * doc/labeling/mp00234c/mp00234c_thick.pbm.gz: New thick mask.
+ * doc/labeling/mp00234c/mp00234c_thin.pbm.gz: New thin mask.
+
+ * doc/labeling/mp00248c: New directory.
+ * doc/labeling/mp00248c/mp00248c.ppm.gz: New color input img.
+ * doc/labeling/mp00248c/mp00248c_thick.pbm.gz: New thick mask.
+ * doc/labeling/mp00248c/mp00248c_thin.pbm.gz: New thin mask.
+
+ * doc/labeling/mp00031c: New directory.
+ * doc/labeling/mp00031c/mp00031c.ppm.gz: New color input img.
+ * doc/labeling/mp00031c/mp00031c_thick.pbm.gz: New thick mask.
+ * doc/labeling/mp00031c/mp00031c_thin.pbm.gz: New thin mask.
+
+ * doc/labeling/mp00083c: New directory.
+ * doc/labeling/mp00083c/mp00083c.ppm.gz: New color input img.
+ * doc/labeling/mp00083c/mp00083c_thick.pbm.gz: New thick mask.
+ * doc/labeling/mp00083c/mp00083c_thin.pbm.gz: New thin mask.
+
+ Import annotating search notes.
+
+ * doc/annotating/class.txt: New documentation text file.
+ * doc/annotating/syntheseMillet.txt: New documentation text file.
+ * doc/annotating/testMillet2008: New documentation text file.
+
+ Import milena learning examples.
+
+ * doc/examples: New directory.
+
+ * doc/examples/hello_world: New directory.
+ * doc/examples/hello_world/Makefile.am: New makefile.
+ * doc/examples/hello_world/hellow_world.cc: New source file.
+ * doc/examples/hello_world/print.cc: New source file.
+
+ * doc/examples/hello_milena: New directory.
+ * doc/examples/hello_milena/Makefile.am: New makefile.
+ * doc/examples/hello_milena/hello_milena.cc: New source file.
+
+ * doc/examples/learn_milena: New directory.
+ * doc/examples/learn_milena/Makefile.am: New makefile.
+ * doc/examples/learn_milena/learn_milena.cc: New source file.
+
+ * doc/examples/otsu: New directory.
+ * doc/examples/otsu/Makefile.am: New makefile.
+ * doc/examples/otsu/otsu.cc: New source file.
+
+ * doc/examples/frac: New directory.
+ * doc/examples/frac/Makefile.am: New makefile.
+ * doc/examples/frac/frac.cc: New source file.
+ * doc/examples/frac/frac.hh: New source file.
+ * doc/examples/frac/sign_prod.hh: New source file.
+ * doc/examples/frac/gcd.hh: New source file.
+
+ * doc/examples/accu_color: New directory.
+ * doc/examples/accu_color/accu_color.cc: New source file.
+
+ * doc/examples/io: New directory.
+ * doc/examples/io/Makefile.am: New makefile.
+ * doc/examples/io/io.cc: New source file.
+
+ Write down the basis of the quick tour summary documentation.
+
+ * doc/quick_tour: New specific directory.
+ * doc/quick_tour/quick_tour.tex: New documentation work.
+
+ Write down 3d currently used formulaes.
+
+ * doc/formulae: New specific directory.
+ * doc/formulae/formulae.tex: New recipe of 3d formulae.
+
+
2010-06-30 Yann Jacquelet <jacquelet(a)lrde.epita.fr>
Add some futur materials on regional maxima.
diff --git a/scribo/sandbox/green/README.green b/scribo/sandbox/green/README.green
index 02d8654..7886914 100644
--- a/scribo/sandbox/green/README.green
+++ b/scribo/sandbox/green/README.green
@@ -236,13 +236,94 @@ n'importe quel algorithme type huffman (tous les archiveurs en possède un).
VIII VISUALISATION HISTOGRAMMES 3D
----------------------------------
-==> to do
-
-
-* demo/accu/stat/histo2d
-
-* mln/display/dispay_histo.hh
-* mln/display/project_histo.hh
+Les histogrammes sur lesquels nous sommes amenés à travailler sont en
+3d. Nous étudions des images couleurs dans l'espace RGB, donc
+l'histogramme dans cet espace possède 3 dimensions (une par axe, R, G
+et B) et la cellule désignée par cette position RGB renfermera le nombre
+de pixels de l'image ayant exactement cette couleur. Il est très
+difficile de bien visualiser ces images, car elles sont en 3d. Gnuplot
+nous donne qu'une aide très limitée, car il faut afficher 3 axes et la
+force de la cellule, ce qui fait en fait quatre informations Ã
+afficher. Il est possible de jouer avec les couleurs, mais il n'y a
+pas de représentation très utile, on peut afficher le nuage des
+couleurs pour percevoir sa forme générale, mais l'interprétation ne
+peut pas vraiment aller plus loin. C'est pourquoi, nous proposons une
+représentation plus pertinente. C'est Théo qui a roulé sa bosse en
+classification qui a developpé ce genre de technique, je ne fais que
+réutilliser les mêmes analyses en beaucoup moins fins que ce qu'il a
+déjà pu développer par ailleurs.
+
+La première idée est de gommer une dimension, et c'est possible de le
+faire car dans une image RGB, souvent l'axe bleu est fortement
+correllé avec l'axe vert. Cela dépend beaucoup de la formation des
+images et pour des images synthétiques, il n'y a aucune raison que
+ce soit le cas. C'est juste une propriété qui s'applique pour les
+images naturelles. La forte corrélation obtenue ne veut pas dire qu'il
+y a exactement les mêmes informations, juste que dans l'ensemble on
+note une relative redondance (du point de vue statistique). Pour t'en
+convaincre, tu peux regarder sous gimp, les histogrammes sur les
+différents canaux et tu observeras qu'il y a deux canaux (le vert et
+bleu) pour lesquels les histogrammes sont presque identiques.
+
+La dernière étape est de réaliser un traitement sur la dimension qui a
+été supprimée. Par exemple, sommer toutes les valeurs rencontrées ou
+ne retenir que la valeur max ...
+
+Le fichier display_histo.hh joue le rôle de front hand pour les
+routines de visualisation. Il a pour rôle d'initialiser, d'instancier,
+de coordonner la chaine de visualisation. Le fichier project_histo.hh
+décrit les algorithmes au coeur de la visualisation, comment est
+construite concrêtement l'information que l'on visualise à la fin.
+
+Nous avons construit 3 sortes de projecteurs. Le premier va sommer le
+long de l'axe bleu les différentes informations
+rencontrées. Globalement, cela signifie, que plus il y a de pixels
+dans le sous espace (red=v1,green=v2) avec pour chaque pixel
+rencontrés des valeurs de bleu différentes, plus le nombre construit
+sera grand. Sur cette information, on fera passer un logarithme pour
+diminuer les pics et ne faire ressortir visuellement que les
+informations les plus saillantes. En dernier lieu, on rescalera les
+valeurs obtenues pour utiliser pleinement la dynamique d'une image de
+256 niveaux de gris. La visualisation obtenue nous donne un aperçu de
+la densité de l'espace des couleurs. On observera en très lumineux les
+endroits de forte population de couleurs et en presque noir l'absence
+de couleur dans l'image pour cette portion de l'espace RGB.
+
+Les autres techniques de visualisation sont des variantes du même
+traitement que nous allons decrire. La chaine de base consiste Ã
+parcourir la dimension bleu pour chaque point de l'espace rouge/vert
+(comme dans la première technique). Cette fois-ci, ce n'est plus la
+somme qui nous intéresse, mais la couleur la plus représentée. On va
+faire un max des valeurs obtenues en parcourant l'axe bleu. Une
+première version rapportera la position bleue qui rassemble le plus de
+pixels. Une seconde version remplacera cette position bleue par un
+label associé à une segmentation déjà effectuée dans cet espace.
+
+La dernière technique modifie la version précédente de la manière
+suivante: Nous sommes toujours interessé par le max, mais on va remplacer
+cette information directement par la couleur reconstituée (nous sommes
+sur un point particulier de l'espace red/green donc red et green sont
+connus, et on vient d'obtenir la valeur bleue la plus représentée, on
+utilisera cette valeur pour former une couleur RGB). A l'issu du
+processus, on obtient donc une image couleur. L'information obtenue
+ici, n'est plus la densité de l'histogramme, mais plutôt la couleur la
+plus représentée à cet endroit. La toute première technique et celle-ci
+sont complémentaires pour la bonne visualisation d'un histogramme
+3d. Si l'on dispose d'une segmentation de l'espace des couleurs, on
+peut trouver le label associé au bleu prédominant et récupérer dans
+une palette de couleur annexe la couleur associée au label.
+
+* mln/display/dispay_histo.hh: Front hand pour les routines de projection.
+* mln/display/project_histo.hh: Les algorithmes de visualisations.
+
+Le travail dans use ne représente que deux routines sur six de
+display_histo. Par manque de temps, je ne fais pas le reste de
+manière à insister sur d'autres points documentaires plus
+importants. Le cadre est en place et les autres routines plus
+sophistiquées faisant intervenir la segmentation de l'histogramme
+peuvent être tirées de tools/labeling/regmax par exemple.
+
+* use/display/display_histo: Visualisations des histogrammes.
IX KMEANS
@@ -388,29 +469,266 @@ tests effectués et montrent l'évolution du temps de calcul suivant la
progression du paramètre observé (taille de l'image ou nombre de
centres).
-==> to do : le changelog + commit + give it to scribo-z branch
-
X REGIONAL MAXIMA
-----------------
-==> to do
+Pour cette partie, le temps a commencé à s'accélérer, ce qui fait
+qu'il n'y a plus de tests unitaires. Par ailleurs, comme la
+fonctionnalité n'a pas été pensée comme un élément de la librairie, il
+n'y a donc pas non plus de répertoire "use" à cet effet.
+
+
+a) Segmentation basé sur le watershed
+
+Cet exemple essaye une première méthode de filtrage de
+l'histogramme. A noter elle ne compile pas. Elle eu compilé dans le
+temps, mais le source a été tellement remanié que sa reconstruction
+doit régler encore quelques détails. Sa compilation n'a pas vraiment
+d'intérêt en soi, seule la démarche compte ici. Le temps me manque et
+je ne persisterais pas à essayer de le faire compiler à tout prix. D'autres
+sources sont beaucoup plus intéressant. Nota, gaussian.sh est un gnuplot
+script shell qui sert à calibrer le filtrage de l'histogramme. Il permet
+de déterminer visuellement la taille de la fenêtre win utilisée lors de la
+convolution en fonction d'un écart type sigma donné.
+
+* demo/labeling/watershed: Demonstrator de la segmentation d'un histogramme.
+
+
+b) Second essai avec les regional_maxima
+
+Le programme actuel ne compile pas non plus. Il n'est pas d'une grande
+importance, alors du coup je le laisse tel quel. Il a servi a
+plusieurs choses, en premier à tester les regional_maxima mais en
+dernier lieu surtout à tester le filtrage par attribut (volume) qui
+semblait avoir quelques soucis. A l'heure d'aujourd'hui, je ne peux
+toujours pas dire s'il fonctionne convenablement ou non, il semble que
+parfois des anomalies se produisent à ce niveau, mais elles peuvent
+aussi bien être générées par un problème interne à mon programme.
+
+* demo/labeling/regional_maxima: Testeur du filtrage par attribut de volume.
+
+
+c) Déplacement du programme b) dans exp.
+
+Même programme que b) mais qui compile.
+
+* exp/labeling/regional_maxima: Testeur du filtrage par attribut de volume.
+
+
+d) Sources importantes ==> regional_maxima
+
+Il y avait une autre version des regional_maxima ou toute la chaine était
+présente, si j'avais davantage de temps, je l'aurais réecrite. Il semble
+qu'elle se soit perdue lors de la migration de SVN vers GIT. Aucune importance.
+Les outils "up to date" sont ceux dont les sources sont dans tools. La classe
+outil représente des binaires un peu plus travaillé au niveau de l'interface
+texte, en gros ils prennent plein de paramètres et génèrent des résultats
+intermédiaires. Chaque outil à son usage ...
+
+
+Ce qu'il faut savoir sur l'outil histo. Tout d'abord le programme
+prend 7 ou 8 arguments et c'est le dernier qui est optionnel. Les
+arguments sont l'image couleur à partir de laquelle on veut extraire
+l'histogramme couleur (3d), le degré de quantification que l'on veut
+utiliser (sous échantillonnnage de l'image), le chemin de l'image
+couleur quantifiée résultante après analyse, le chemin de
+l'histogramme produit (réutilisé par les autres outils), la
+visualisation rouge/verte de l'histogramme (brute) et la visualisation
+augmentée de ce même histogramme avec les maxima dessus. Se reporter Ã
+la documentation des histogrammes pour avoir plus d'information sur ce
+sujet. Le dernier paramètre optionnel est un masque à appliquer sur
+les pixels de l'image d'entrée. La chaine de traitement de l'outil,
+commence par sous échantillonner l'image en n bits, n < 8, puis
+construit l'histogramme 3d à partir des pixels présents dans le masque,
+si ce dernier existe et enfin sauvegarde des résultats et des images
+servant à la visualisation.
+
+* tools/labeling/histo: Construction de l'histogramme.
+
+
+Ce qu'il faut savoir sur l'outil de filtrage de l'histogramme. Tout
+d'abord, il prend en paramètre 6 arguments obligatoires. Les arguments
+sont la quantification utilisée par l'outil de création de
+l'histogramme, le chemin de l'histogramme à filtrer, le seuil utilisé
+pour le filtrage (c'est le volume minimal en dessous duquel
+l'information est jugée comme du bruit et donc ne doit pas passer), le
+chemin de l'histogramme filtré, le chemin de la projection en densité
+de l'histogramme et le chemin de la projection en couleurs
+majoritaires de l'histogramme. Se reporter au chapitre sur la
+visualisation pour comprendre les différentes projections. Le filtrage
+est un traitement très simple, il applique uniquement l'algorithme
+morphologique d'ouverture sur les attributs de volume. Imagine un
+histogramme en 1d, l'attribut de volume est alors la surface sous la
+courbe de l'histogramme. Une ouverture volumique consiste à supprimer
+tous les pics ayant un volume inférieur au seuil. Cela fonctionne très
+bien en général, toutefois, il y a des cas où les informations
+retournées ne sont pas celles attendues. Concrêtement, des composantes
+de volume inférieur au seuil sont retrouvées plus loin dans la chaine
+de traitement, ce qui contredit l'usage de l'ouverture
+morphologique. Il est difficile de définir ce qui se passe vraiment,
+il est possible qu'il y ait un bug ou simplement que le reste de ma
+chaine induise quelque fois ce résultat étrange. Honnêtement, je ne
+sais pas ce qui se passe. Le cas n'arrive pas fréquemment, donc il est
+très difficile d'isoler l'erreur.
+
+* tools/labeling/opening: Filtrage de l'histogramme.
+
+
+Ce qu'il faut savoir sur l'outil de labellisation. Tout d'abord, il
+prend 11 arguments dont le dernier est optionel. Les arguments sont
+l'image originale (nécessaire pour calculer la couleur moyenne des
+labels ==> réalité augmentée), la quantification utilisée
+précédemment, l'image préalablement quantifiée, l'histogramme
+original, l'histogramme filtré, le voisinage sur lequel effectué les
+opérations (c6, c18 ou c26), l'histogramme segmenté en 3d, la
+projection red/green associée, la colormap, l'image reconstruite des
+moyennes associé à chaque label et éventuellement un fichier décrivant
+les statistiques associés aux labels (couleur moyenne associé au
+label, plus nombre de pixels concernés dans l'image, plus pourcentage
+absolu et pourcentage sans tenir compte du fond). Le seul appel
+intéressant est la labellisation de l'histogramme filtré qui produit
+une image 3d de label. Tout le reste est de la tuyauterie pour faire
+de la rélatité augmentée. Par exemple pour formée l'image des moyennes
+associées à chaque label, il est nécessaire de construire l'image 2d
+des labels qui fait intervenir elle-même l'image d'entrée quantifiée
+et l'image originale. Idem pour la construction de la
+colormap. L'outil segmente l'histogramme filtré par la détermination
+des maxima régionnaux, autrement dit des zones de très fortes
+densités. Ces zones sont en général très petites, quelques pixels pas
+plus. C'est pourquoi l'outil suivant va nous servir à les étendre un
+peu.
+
+* tools/labeling/regmax: Segmentation de l'histogramme.
+
+
+Petite suprise désagréable, l'outil iz ne compile plus. La raison en
+est toute simple, il y a eu du mouvement dans les fonctions
+mln::transform::influence_zone_geodesic(). Un revamp un peu violent,
+avec une version
+mln::transform::influence_zone_geodesic_saturated(). J'ai corrigé le
+changement d'appel, mais cela ne suffit pas. Dans la méthode
+mln::transform::influence_zone_geodesic_fastest(), l.127, tu utilises
+la méthode at() pour une image 2d et là pas de chance, moi j'utilise
+cet algorithme pour une image de labels 3d (nous sommes dans un espace
+RGB quantifié en n bits, n < 8). Je ne veux surtout rien détruire dans
+scribo, donc je te laisse effectuer les changements qui s'imposent et
+je continue la documentation.
+
+Ce qu'il faut savoir sur iz. Tout d'abord cette routine prend 12
+arguments dont le dernier est optionel. Les arguments sont
+l'histogramme labelisé par l'outil précédent, la profondeur utilisée
+pour l'influence par zone géodésique (0 signifie l'infini), puis vient
+le voisinage 3d utilisé pour la propagation, puis l'image initiale,
+puis le degrée de quantification utilisé par tous les outils, puis le
+dump de l'histogramme, la colormap (utilisée pour la projection r/g
+avec segmentation, puis l'histogramme labelisé après propagation nommé
+iz et enfin la projection r/g, l'image reconstruite à l'aide des
+moyennes des classes et le fichier de statistiques intégrant la
+propagation des classes. La propagation a pour vocation d'agrandir les
+classes obtenues jusqu'Ã maintenant. C'est une information que l'on
+voit bien avec les changements dans les projections r/g.
+
+* tools/labeling/iz: Propagation des classes par zone d'influence.
+
+
+Comme le paramétrage est difficile, il est conseillé de relire les
+scripts des jeux de tests qui coordonnent l'appel de ces routines avec
+une sucession de paramètres cohérents. Je sais ce que tu vas me dire,
+c'est mal, il ne faut pas mettre d'images sur le dépot git. Dans
+l'absolu, je suis d'accord, mais aujourd'hui, le code iz est cassé et
+rejouer ces tests peut prendre énormément de temps, donc par facilité,
+je me contente des résultats que j'avais archivé et que tu seras
+content de trouver pour en inclure une partie dans ton rapport.
+
+Tout d'abord un jeu de répertoire de test en instance d'être lancé. Le
+répertoire porte le nom de l'image sur laquelle est effectué le
+test. On y trouvera l'image originale pleine résolution, et les deux
+masques de gradient fin et un peu plus épais. Pour faire le test, il
+suffit d'écrire le script comme dans doc/labeling/mp00307.
+
+* doc/labeling/mp00215c
+* doc/labeling/mp00234c
+* doc/labeling/mp00248c
+* doc/labeling/ta00031c
+* doc/labeling/ta00083c
+
+
+Puis, nous avons les tous premiers tests qui ont servi pour déterminer
+la quantification à utiliser et la méthode de propagation (infinie ou
+saturée). Il y a longtemps, pour ces tests, je disposais d'une chaine
+complète mais cette dernière c'est perdu dans la migration entre svn
+et git. Il n'y a donc pas de script shell qui lance les outils, par
+contre il existe un fichier de synthese qui explique exactement ce qui
+a avait été lancé et avec quels paramètres, histoire de pouvoir rejouer le test.
+
+* doc/labeling/cmp_method: Test sur le type de propagation à utiliser.
+* doc/labelling/cmp_quant: Test sur la quantification a utiliser.
+
+
+Puis, nous avons les tests effectués à l'aide d'un script. Lire les
+scripts pour situer correctement les binaires outils utilisés. Le
+premier jeu test avait pour but d'étudier la combinatoire des options
+et de choisir ensuite les paramètres qui vont bien. Il n'y a pas de
+certitude complète en la matière. Lire attentivement le fichier
+synthèse. Tout ces éléments ont été validés par théo. Je ne me rapelle
+plus du détail, mais j'ai rédigé tout ce que je pouvais. Le dernier
+répertoire n'a pas de fichier synthèse, je pense que l'étude était du
+même gabarit que le test précédent. J'en étais à tester la routine sur
+un maximum d'images pour voir si le jeu réduit de couleurs obtenues
+correspondait à nos attentes ou non. Les paramètres stables sont Ã
+rechercher dans les derniers répertoires mp00042c et mp00307c.
+
+* doc/labeling/mp00307c_bis: Test sur un grand nombre de combinaisons.
+* doc/labeling/mp00411c: Test sur l'altération des statistiques.
+* doc/labeling/mp00042c: Test sur la representativité des couleurs trouvées.
+* doc/labeling/mp00307c: Test sur la representativité des couleurs trouvées.
+
+
+Faire le changelog, il y a de l'aide dans git/doc/Changelog
+... et commiter
XI ANNOTATING
--------------
+--------------
==> to do
-a) La sauvegarde des images au format gnuplot shell
-* mln/io/plot/save_image_sh.hh: Librairie sauvegarde format gnuplot shell.
+* doc/annotating
+
+
-to do ...
+XI AUTRES ASPECTS DOCUMENTAIRES
+-------------------------------
+Ces exemples de codes sont livrés tels quels sans aucune documentation
+de ma part. Si tu as besoin de quelque chose, sert toi, tu les
+remanieras à ta sauce. Il n'y a pas de raison de les documenter, se
+serait disperser mes efforts vainement.
+* doc/examples/accu_color: Petit programme pour se bidouiller avec la couleur.
+* doc/examples/frac: Librairie pour manipuler des fractions sous milena.
+* doc/examples/hello_milena: Petit exemple allant avec la doc de milena.
+* doc/examples/hello_world: Test de la plateforme c++.
+* doc/examples/io: Rien de vraiment intéressant dans l'état actuel.
+* doc/examples/learn_milena: Autre exemple de base avec milena.
+* doc/examples/otsu: Petit programme Otsu.
+* doc/examples/stats: Exemple de manipulation d'accumulateurs.
+Voici deux exemples sous LaTex. Un jeu de test avec la confection de
+vecteur et de matrices pour relater les forrmules connues en espace
+3d. La version actuelle est dégradée par rapport à ce que j'avais pu
+écrire. J'étais arrivé à la mise au point d'un extracteur de valeurs
+propres mais je n'ai jamais pu retrouver cette version là , surement
+une erreur sous svn. Le second document devait présenter la
+documentation quick tour sous milena, mais j'avoue que c'est un
+lamentable échec, je n'ai pas pris le temps de le faire. Je pense que
+l'idée d'une documentation collaborative permettrait de répartir
+l'effort.
+* doc/formulae: LaTex directory.
+* doc/quick_tour: LaTex directory.
diff --git a/scribo/sandbox/green/demo/clustering/kmean1d/Makefile.am b/scribo/sandbox/green/demo/labeling/regional_maxima/Makefile.am
similarity index 100%
copy from scribo/sandbox/green/demo/clustering/kmean1d/Makefile.am
copy to scribo/sandbox/green/demo/labeling/regional_maxima/Makefile.am
diff --git a/scribo/sandbox/green/demo/labeling/regional_maxima/regional_maxima.cc b/scribo/sandbox/green/demo/labeling/regional_maxima/regional_maxima.cc
new file mode 100644
index 0000000..d0c524b
--- /dev/null
+++ b/scribo/sandbox/green/demo/labeling/regional_maxima/regional_maxima.cc
@@ -0,0 +1,198 @@
+// Copyright (C) 2007, 2008, 2009, 2010 EPITA 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.
+
+/// \file
+///
+/// This demonstrator is aimed to experiment the regional maxima
+/// method. regional_maxima.It first test the 3d histogram from an
+/// image and the number of colors which results. And in fact, doesn't
+/// use the regional_maxima routine. Too many parameters must be fixed
+/// and parts of the code has been commented. The last action of this
+/// program consists in counting the number of colors of each image in a
+/// directory. This source has been used to test the annotating image base.
+///
+/// \fixme At this time, the source is in a transitional step. It doesn't
+/// compile, something wrong with boost library. It doesn't matter, that's not
+/// an important file.
+
+
+#include <iostream>
+#include <sstream>
+#include <boost/filesystem.hpp>
+
+#include <mln/img_path.hh>
+
+#include <mln/accu/math/sum.hh>
+#include <mln/accu/math/count.hh>
+#include <mln/accu/stat/histo3d_rgb.hh>
+#include <mln/accu/stat/mean.hh>
+#include <mln/accu/stat/variance.hh>
+
+#include <mln/algebra/vec.hh>
+
+#include <mln/arith/diff_abs.hh>
+
+#include <mln/core/macros.hh>
+#include <mln/core/alias/neighb3d.hh>
+#include <mln/core/image/image2d.hh>
+#include <mln/core/image/image3d.hh>
+#include <mln/core/image/dmorph/image_if.hh>
+#include <mln/core/routine/initialize.hh>
+
+#include <mln/data/compute.hh>
+#include <mln/data/fill.hh>
+#include <mln/data/transform.hh>
+
+#include <mln/fun/v2v/rgb8_to_rgbn.hh>
+
+#include <mln/io/pgm/load.hh>
+#include <mln/io/pgm/save.hh>
+#include <mln/io/ppm/load.hh>
+#include <mln/io/ppm/save.hh>
+
+#include <mln/labeling/regional_maxima.hh>
+#include <mln/labeling/mean_values.hh>
+#include <mln/labeling/compute.hh>
+
+#include <mln/literal/colors.hh>
+
+#include <mln/morpho/opening/volume.hh>
+#include <mln/morpho/elementary/dilation.hh>
+
+#include <mln/opt/at.hh>
+
+#include <mln/pw/cst.hh>
+
+#include <mln/util/array.hh>
+#include <mln/util/timer.hh>
+
+#include <mln/value/label_8.hh>
+#include <mln/value/rgb8.hh>
+#include <mln/value/rgb.hh>
+#include <mln/value/int_u.hh>
+
+
+/// \brief This is the count method.
+///
+/// \param[in] image the colored image.
+///
+/// This function loads a color image (ppm) and count the colors after
+/// using the min volume processing on the 3d histogram. Percentage
+/// thresholding is in test. The file threshold.txt establishes the link
+/// between percentage and size in image.
+///
+// n < 8, n is the degree of quantification
+template <unsigned n>
+unsigned count_image_color(const std::string& image)
+{
+ typedef mln::value::label_8 t_lbl8;
+ typedef mln::value::int_u8 t_int_u8;
+ typedef mln::value::rgb8 t_rgb8;
+ typedef mln::value::rgb<n> t_rgbn;
+ typedef mln::image3d<t_lbl8> t_image3d_lbl8;
+ typedef mln::image2d<t_lbl8> t_image2d_lbl8;
+ typedef mln::image2d<t_rgb8> t_image2d_rgb8;
+ typedef mln::image2d<t_rgbn> t_image2d_rgbn;
+ typedef mln::image2d<t_int_u8> t_image2d_int_u8;
+ typedef mln::image3d<unsigned> t_histo3d;
+ typedef mln::image2d<unsigned> t_histo2d;
+ typedef mln::fun::v2v::rgb8_to_rgbn<n> t_rgb8_to_rgbn;
+ typedef mln::accu::meta::stat::histo3d_rgb t_histo3d_fun;
+ typedef mln::accu::meta::math::count t_count_fun;
+
+ t_image2d_rgb8 input_rgb8;
+ t_image2d_rgbn input_rgbn;
+ t_image2d_rgbn output_rgbn;
+ t_histo3d histo;
+ t_histo3d opened;
+ t_image3d_lbl8 label;
+ t_image2d_lbl8 label_img;
+ t_image3d_lbl8 dilated;
+ t_lbl8 n_labels;
+
+ mln::io::ppm::load(input_rgb8, image.c_str());
+
+ unsigned nb_pixel = input_rgb8.ncols() * input_rgb8.nrows();
+ unsigned min_volume = (unsigned)(nb_pixel * 0.054);
+
+ input_rgbn = mln::data::transform(input_rgb8, t_rgb8_to_rgbn());
+ histo = mln::data::compute(t_histo3d_fun(), input_rgbn);
+ return mln::data::compute(t_count_fun(), histo);
+
+ // return nb_pixel;
+ // opened = mln::morpho::opening::volume(histo, mln::c6(), min_volume);
+ // label = mln::labeling::regional_maxima(opened, mln::c6(), n_labels);
+ // return n_labels;
+}
+
+/// \brief The main function aimed at looping over the whole directory.
+///
+/// The main function is used to take care of file part in this
+/// sofware. It manages the directory scanning aspect while the last
+/// function does the image processing aspect. Statistics are
+/// generated (mean and variance) about the number of colors after using
+/// the min_volume routine. Some strange things happens with that routine
+/// sometimes.
+int main()
+{
+ typedef boost::filesystem::path t_path;
+ //typedef boost::filesystem::initial_path<t_path()> t_init_path;
+ typedef boost::filesystem::directory_iterator t_iter_path;
+
+ t_path full_path(ANNOTATING_1_TYPED_IMG_PATH);
+
+ std::cout << "entering " << full_path << std::endl;
+
+ if (//1 < argc &&
+ boost::filesystem::exists(full_path) &&
+ boost::filesystem::is_directory(full_path))
+ {
+ boost::filesystem::system_complete(full_path);
+ const t_iter_path end_iter;
+ unsigned count = 0;
+ unsigned sum1 = 0;
+ unsigned sum2 = 0;
+
+ for (t_iter_path dir_iter(full_path); end_iter != dir_iter; ++dir_iter)
+ {
+ unsigned val = count_image_color<5>(dir_iter->path().string());
+
+ ++count;
+ sum1 += val;
+ sum2 += val*val;
+
+ std::cout << dir_iter->path().string() << " => " << val << std::endl;
+ }
+
+ unsigned mean = sum1 / count;
+ unsigned var = sum2 / count - mean * mean;
+
+ std::cout << "mean : " << mean << std::endl;
+ std::cout << "var : " << var << std::endl;
+ }
+
+ return 0;
+}
+
diff --git a/milena/sandbox/green/demo/labeling/regional_maxima/thresholds.txt b/scribo/sandbox/green/demo/labeling/regional_maxima/thresholds.txt
similarity index 100%
copy from milena/sandbox/green/demo/labeling/regional_maxima/thresholds.txt
copy to scribo/sandbox/green/demo/labeling/regional_maxima/thresholds.txt
diff --git a/scribo/sandbox/green/demo/clustering/kmean1d/Makefile.am b/scribo/sandbox/green/demo/labeling/watershed/Makefile.am
similarity index 100%
copy from scribo/sandbox/green/demo/clustering/kmean1d/Makefile.am
copy to scribo/sandbox/green/demo/labeling/watershed/Makefile.am
diff --git a/milena/sandbox/green/tests/accu/stat/histo1d/gaussian.sh b/scribo/sandbox/green/demo/labeling/watershed/gaussian.sh
similarity index 100%
copy from milena/sandbox/green/tests/accu/stat/histo1d/gaussian.sh
copy to scribo/sandbox/green/demo/labeling/watershed/gaussian.sh
diff --git a/scribo/sandbox/green/demo/labeling/watershed/watershed.cc b/scribo/sandbox/green/demo/labeling/watershed/watershed.cc
new file mode 100644
index 0000000..a9289f7
--- /dev/null
+++ b/scribo/sandbox/green/demo/labeling/watershed/watershed.cc
@@ -0,0 +1,360 @@
+// Copyright (C) 2007, 2008, 2009, 2010 EPITA 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.
+
+/// \file
+///
+/// This demonstrator is the first step before using
+/// regional_maxima. Its purpose is to work on histogram filtering and
+/// on the whole image processing chain.
+///
+/// \fixme: this source doesn't compile. I've no time to fix it. It's not
+/// so important because it's just a basic sample, just keep in mind the
+/// method to reach the result, it will be reuse for regional_maxima.
+
+#include <iostream>
+#include <sstream>
+
+#include <mln/accu/stat/histo1d.hh>
+
+#include <mln/arith/revert.hh>
+
+#include <mln/core/alias/neighb1d.hh>
+#include <mln/core/alias/window1d.hh>
+#include <mln/core/macros.hh>
+#include <mln/core/image/image1d.hh>
+#include <mln/core/image/image2d.hh>
+#include <mln/core/routine/initialize.hh>
+
+#include <mln/data/compute.hh>
+#include <mln/data/transform.hh>
+
+#include <mln/io/pgm/load.hh>
+#include <mln/io/pgm/save.hh>
+#include <mln/io/ppm/save.hh>
+#include <mln/io/plot/save_image_sh.hh>
+
+#include <mln/labeling/colorize.hh>
+#include <mln/labeling/mean_values.hh>
+#include <mln/labeling/regional_maxima.hh>
+
+#include <mln/linear/convolve.hh>
+//#include <mln/linear/gaussian.hh>
+
+#include <mln/literal/colors.hh>
+
+#include <mln/morpho/elementary/closing.hh>
+#include <mln/morpho/elementary/dilation.hh>
+#include <mln/morpho/elementary/opening.hh>
+#include <mln/morpho/opening/structural.hh>
+#include <mln/morpho/watershed/flooding.hh>
+
+#include <mln/img_path.hh>
+
+#include <mln/value/int_u8.hh>
+#include <mln/value/rgb8.hh>
+#include <mln/value/label_8.hh>
+
+#include <mln/win/disk1d.hh>
+
+
+/// \brief Compute the gaussian probability to obtain a given value.
+///
+/// \param[in] x the value from which we want the probability.
+/// \param[in] mean the mean parameter of the gaussian distribution.
+/// \param[in] sigma the sqrt(variance) parameter of the gaussian.
+/// \return the probability to obtain the x value.
+///
+/// Implements the standard 1d equation of the gaussian.
+double gaussian_distribution(const double x,
+ const double mean,
+ const 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;
+}
+
+
+/// \brief Make a 1d gaussian filter.
+///
+/// \param[out] ws the window (filter) where to put the probability values.
+/// \param[in] size the size of the filter.
+/// \param[in] sigma the gaussian parameter for the standard deviation.
+/// \return the probability to obtain the x value.
+///
+/// Approach the gaussian distribution for a few discrete sites, and
+/// then normilize the results to be sure that the sum obtain 1.
+void gaussian_filter(double ws[], const unsigned size, const 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;
+}
+
+
+/// \brief Merge input image with label one.
+///
+/// \param[in] input the window (filter) where to put the probability values.
+/// \param[in] label the size of the filter.
+/// \return the merged image.
+///
+/// This function build a new image in which the input pixels are
+/// replaced by the label associated to their grey level.
+mln::image2d<mln::value::label_8>
+merge(const mln::image2d<mln::value::int_u8>& input,
+ const mln::image1d<mln::value::label_8>& label)
+{
+ 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;
+ }
+
+ return output;
+}
+
+/// \brief This is the wathersed method for segmenting the histogram.
+///
+/// \param[in] image the input image.
+///
+/// The function returns nothing but writes different images on the
+/// filesystem. The 3 outputs are the image label, the random coloring
+/// of the image label and the average tone of the label image
+/// (replace every label by the grey average of the group to which
+/// it's belong to) .
+void do_demo(const std::string& image)
+{
+ typedef mln::value::int_u8 t_int_u8;
+ typedef mln::value::label_8 t_lbl8;
+ typedef mln::value::rgb8 t_rgb8;
+ typedef mln::image1d<t_lbl8> t_image1d_lbl8;
+ typedef mln::image2d<t_rgb8> t_image2d_rgb8;
+ typedef mln::image2d<t_int_u8> t_image2d_int_u8;
+ typedef mln::image2d<t_lbl8> t_image2d_lbl8;
+ typedef mln::image1d<unsigned> t_image1d_unsigned;
+
+ t_image2d_int_u8 img;
+ t_image1d_unsigned histo;
+ t_image1d_unsigned filtered;
+ t_image1d_unsigned reverted;
+ t_image1d_lbl8 label;
+ t_image2d_lbl8 output;
+ t_image2d_int_u8 mean;
+ t_image2d_rgb8 colorized;
+ t_lbl8 n_labels;
+
+
+ //---------------------------------------------------------------------------
+ // LOADING PHASE
+ //---------------------------------------------------------------------------
+ mln::io::pgm::load(img, image.c_str());
+ mln::io::pgm::save(img, "img.pgm");
+
+
+ //---------------------------------------------------------------------------
+ // HISTO COMPUTING PHASE
+ //---------------------------------------------------------------------------
+ histo = mln::data::compute(mln::accu::meta::stat::histo1d(), img);
+ mln::io::plot::save_image_sh(histo, "histo.sh");
+
+
+ //---------------------------------------------------------------------------
+ // HISTO FILTERING PHASE
+ //---------------------------------------------------------------------------
+
+ // a) GAUSSIAN FILTERING
+ double ws[41];
+ gaussian_filter(ws, 41, 6.0);
+ filtered = mln::linear::convolve(histo, mln::make::w_window1d(ws));
+
+ // b) MORPHOLOGICAL ELEMENTARY OPENING
+ // filtered = mln::morpho::elementary::opening(histo, mln::c4());
+
+ // c) MORPHOLOGICAL STRUCTURAL OPENING (C4,C8 ??)
+ // filtered = mln::morpho::opening::structural(histo, mln::win_c8p());
+
+ // d) MORPHOLOGICAL STRUCTURAL DISK OPENING (SIZE = 11/21/31/41/51 ??)
+ // mln::win::disk1d disk1d(21);
+ // filtered = mln::morpho::opening::structural(histo, disk1d);
+
+ mln::io::plot::save_image_sh(filtered, "filtered.sh");
+
+
+ //---------------------------------------------------------------------------
+ // HISTO LABELING PHASE
+ //---------------------------------------------------------------------------
+ // a) watershed
+ reverted = mln::arith::revert(histo);
+ label = mln::morpho::watershed::flooding(reverted, mln::c4(), n_labels);
+ // b) regional maxima
+ // label = mln::labeling::regional_maxima(opened, mln::c8(), n_labels);
+ mln::io::pgm::save(label, "label.pgm");
+
+
+ //---------------------------------------------------------------------------
+ // FUZZY PHASE
+ //---------------------------------------------------------------------------
+ dilated = mln::morpho::elementary::dilation(label, mln::c8());
+ mln::io::pgm::save(dilated, "dilated.pgm");
+
+
+ //---------------------------------------------------------------------------
+ // OUTPUT PHASE
+ //---------------------------------------------------------------------------
+ output = merge(house_rg8, label);
+ mean = mln::labeling::mean_values(img, label, nlabels);
+ colorized = mln::labeling::colorize(rgb8(), label);
+
+ mln::io::pgm::save(output, "output.pgm");
+ mln::io::pgm::save(mean, "mean.pgm");
+ mln::io::ppm::save(colorized, "colorized.ppm");
+}
+
+
+/// \brief This is the launcher of the method.
+///
+/// \param[in] image the input image.
+///
+/// The launcher is the good place for debugging input arguments or
+/// setting defaults one.
+void demo(const std::string& image = SCRIBO_PGM_IMG_PATH"/mp00082c_50p.pgm")
+{
+ std::cout << "----------------------------------------" << std::endl;
+ std::cout << "Launching the demo with these parameters" << std::endl;
+ std::cout << "image : " << image << std::endl;
+ std::cout << "----------------------------------------" << std::endl;
+
+ do_demo(image);
+}
+
+
+/// \bief The usage function of the binary.
+///
+/// \param[in] argc the binary number of arguments.
+/// \param[in] args the binary array of arguments.
+///
+/// This binary requires one input image to work. It is a grey level
+/// image in pgm format.
+void usage(const int argc, const char *args[])
+{
+ std::cout << "----------------------------------------" << std::endl;
+ std::cout << "argc : " << argc << std::endl;
+
+ for (int i = 0; i < argc; ++i)
+ std::cout << "args[" << i << "] : " << args[i] << std::endl;
+
+ std::cout << "----------------------------------------" << std::endl;
+ std::cout << "usage: wateshed [image]" << std::endl;
+ std::cout << "pgm image (image to label)" << std::endl;
+ std::cout << "----------------------------------------" << std::endl;
+}
+
+
+/// \brief Convert a c string parameter to string object like.
+///
+/// \param[in] status the flag to prevent bad work.
+/// \param[in] arg the c string to convert in string object.
+/// \param[out] val the return string object.
+/// \return a flag to say if every thing goes well.
+///
+/// Convert a c string (char *) in string object (std::string) in order
+/// to simplify some string operations.
+bool char_to_string(const bool status, const char *arg, std::string& val)
+{
+ bool result = false;
+
+ if (status)
+ {
+ std::istringstream arg_stream(arg);
+
+ arg_stream >> val;
+
+ return !arg_stream.fail();
+ }
+
+ return result;
+}
+
+
+/// \brief Segment by the watershed method histogram space.
+///
+/// \param[in] img the input image.
+/// \return merge image.
+///
+/// This is the main entry of the program. It takes an image as input
+/// parameter and computes its histogram. The method segments the
+/// histogram in order to build color classes (even we stay in grey
+/// level). Merging image is returned where pixels have been replaced
+/// by some attribute of the class (like the average color).
+int main(const int argc, const char *args[])
+{
+ std::string image("top");
+ bool status = true;
+
+ switch (argc)
+ {
+ case 2: status = char_to_string(status, args[1], image); break;
+ case 1: status = true; break;
+ default: status = false;
+ }
+
+ if (status)
+ {
+ switch (argc)
+ {
+ case 1: demo(); break;
+ case 2: demo(image); break;
+ }
+ }
+ else
+ usage(argc, args);
+
+ return 0;
+}
diff --git a/milena/sandbox/green/doc/annotating/class.txt b/scribo/sandbox/green/doc/annotating/class.txt
similarity index 100%
copy from milena/sandbox/green/doc/annotating/class.txt
copy to scribo/sandbox/green/doc/annotating/class.txt
diff --git a/milena/sandbox/green/doc/annotating/syntheseMillet2008.txt b/scribo/sandbox/green/doc/annotating/syntheseMillet2008.txt
similarity index 100%
copy from milena/sandbox/green/doc/annotating/syntheseMillet2008.txt
copy to scribo/sandbox/green/doc/annotating/syntheseMillet2008.txt
diff --git a/milena/sandbox/green/doc/annotating/testMillet2008 b/scribo/sandbox/green/doc/annotating/testMillet2008
similarity index 100%
copy from milena/sandbox/green/doc/annotating/testMillet2008
copy to scribo/sandbox/green/doc/annotating/testMillet2008
diff --git a/milena/sandbox/green/doc/examples/accu_color/accu_color.cc b/scribo/sandbox/green/doc/examples/accu_color/accu_color.cc
similarity index 100%
copy from milena/sandbox/green/doc/examples/accu_color/accu_color.cc
copy to scribo/sandbox/green/doc/examples/accu_color/accu_color.cc
diff --git a/milena/sandbox/green/doc/examples/frac/Makefile.am b/scribo/sandbox/green/doc/examples/frac/Makefile.am
similarity index 100%
copy from milena/sandbox/green/doc/examples/frac/Makefile.am
copy to scribo/sandbox/green/doc/examples/frac/Makefile.am
diff --git a/milena/sandbox/green/doc/examples/frac/frac.cc b/scribo/sandbox/green/doc/examples/frac/frac.cc
similarity index 100%
copy from milena/sandbox/green/doc/examples/frac/frac.cc
copy to scribo/sandbox/green/doc/examples/frac/frac.cc
diff --git a/milena/sandbox/green/doc/examples/frac/frac.hh b/scribo/sandbox/green/doc/examples/frac/frac.hh
similarity index 100%
copy from milena/sandbox/green/doc/examples/frac/frac.hh
copy to scribo/sandbox/green/doc/examples/frac/frac.hh
diff --git a/milena/sandbox/green/doc/examples/frac/gcd.hh b/scribo/sandbox/green/doc/examples/frac/gcd.hh
similarity index 100%
copy from milena/sandbox/green/doc/examples/frac/gcd.hh
copy to scribo/sandbox/green/doc/examples/frac/gcd.hh
diff --git a/milena/sandbox/green/doc/examples/frac/sign_prod.hh b/scribo/sandbox/green/doc/examples/frac/sign_prod.hh
similarity index 100%
copy from milena/sandbox/green/doc/examples/frac/sign_prod.hh
copy to scribo/sandbox/green/doc/examples/frac/sign_prod.hh
diff --git a/milena/sandbox/green/doc/examples/hello_milena/Makefile.am b/scribo/sandbox/green/doc/examples/hello_milena/Makefile.am
similarity index 100%
copy from milena/sandbox/green/doc/examples/hello_milena/Makefile.am
copy to scribo/sandbox/green/doc/examples/hello_milena/Makefile.am
diff --git a/milena/sandbox/green/doc/examples/hello_milena/hello_milena.cc b/scribo/sandbox/green/doc/examples/hello_milena/hello_milena.cc
similarity index 100%
copy from milena/sandbox/green/doc/examples/hello_milena/hello_milena.cc
copy to scribo/sandbox/green/doc/examples/hello_milena/hello_milena.cc
diff --git a/milena/sandbox/green/doc/examples/hello_milena/Makefile.am b/scribo/sandbox/green/doc/examples/hello_world/Makefile.am
similarity index 100%
copy from milena/sandbox/green/doc/examples/hello_milena/Makefile.am
copy to scribo/sandbox/green/doc/examples/hello_world/Makefile.am
diff --git a/milena/sandbox/green/doc/examples/hello_world/hello_world.cc b/scribo/sandbox/green/doc/examples/hello_world/hello_world.cc
similarity index 100%
copy from milena/sandbox/green/doc/examples/hello_world/hello_world.cc
copy to scribo/sandbox/green/doc/examples/hello_world/hello_world.cc
diff --git a/milena/sandbox/green/doc/examples/hello_world/print.cc b/scribo/sandbox/green/doc/examples/hello_world/print.cc
similarity index 100%
copy from milena/sandbox/green/doc/examples/hello_world/print.cc
copy to scribo/sandbox/green/doc/examples/hello_world/print.cc
diff --git a/milena/sandbox/green/doc/examples/io/Makefile.am b/scribo/sandbox/green/doc/examples/io/Makefile.am
similarity index 100%
copy from milena/sandbox/green/doc/examples/io/Makefile.am
copy to scribo/sandbox/green/doc/examples/io/Makefile.am
diff --git a/milena/sandbox/green/doc/examples/io/io.cc b/scribo/sandbox/green/doc/examples/io/io.cc
similarity index 100%
copy from milena/sandbox/green/doc/examples/io/io.cc
copy to scribo/sandbox/green/doc/examples/io/io.cc
diff --git a/milena/sandbox/green/doc/examples/hello_milena/Makefile.am b/scribo/sandbox/green/doc/examples/learn_milena/Makefile.am
similarity index 100%
copy from milena/sandbox/green/doc/examples/hello_milena/Makefile.am
copy to scribo/sandbox/green/doc/examples/learn_milena/Makefile.am
diff --git a/milena/sandbox/green/doc/examples/learn_milena/learn_milena.cc b/scribo/sandbox/green/doc/examples/learn_milena/learn_milena.cc
similarity index 100%
copy from milena/sandbox/green/doc/examples/learn_milena/learn_milena.cc
copy to scribo/sandbox/green/doc/examples/learn_milena/learn_milena.cc
diff --git a/milena/sandbox/green/doc/examples/hello_milena/Makefile.am b/scribo/sandbox/green/doc/examples/otsu/Makefile.am
similarity index 100%
copy from milena/sandbox/green/doc/examples/hello_milena/Makefile.am
copy to scribo/sandbox/green/doc/examples/otsu/Makefile.am
diff --git a/milena/sandbox/green/doc/examples/otsu/otsu.cc b/scribo/sandbox/green/doc/examples/otsu/otsu.cc
similarity index 100%
copy from milena/sandbox/green/doc/examples/otsu/otsu.cc
copy to scribo/sandbox/green/doc/examples/otsu/otsu.cc
diff --git a/milena/sandbox/green/doc/examples/hello_milena/Makefile.am b/scribo/sandbox/green/doc/examples/stats/Makefile.am
similarity index 100%
copy from milena/sandbox/green/doc/examples/hello_milena/Makefile.am
copy to scribo/sandbox/green/doc/examples/stats/Makefile.am
diff --git a/milena/sandbox/green/doc/examples/stats/stats.cc b/scribo/sandbox/green/doc/examples/stats/stats.cc
similarity index 100%
copy from milena/sandbox/green/doc/examples/stats/stats.cc
copy to scribo/sandbox/green/doc/examples/stats/stats.cc
diff --git a/milena/sandbox/green/doc/formulae/formulae.tex b/scribo/sandbox/green/doc/formulae/formulae.tex
similarity index 100%
copy from milena/sandbox/green/doc/formulae/formulae.tex
copy to scribo/sandbox/green/doc/formulae/formulae.tex
diff --git a/milena/sandbox/green/doc/quick_tour/quick_tour.tex b/scribo/sandbox/green/doc/quick_tour/quick_tour.tex
similarity index 100%
copy from milena/sandbox/green/doc/quick_tour/quick_tour.tex
copy to scribo/sandbox/green/doc/quick_tour/quick_tour.tex
diff --git a/scribo/sandbox/green/exp/regional_maxima/Makefile.am b/scribo/sandbox/green/exp/regional_maxima/Makefile.am
new file mode 100644
index 0000000..68bb53e
--- /dev/null
+++ b/scribo/sandbox/green/exp/regional_maxima/Makefile.am
@@ -0,0 +1,153 @@
+#
+# Generic Makefile
+#
+
+#########
+# TOOLS #
+#########
+
+LOADLIBES= -lboost_filesystem
+INCLUDES1= -I$(HOME)/git/olena/scribo/sandbox/green
+INCLUDES2= -I$(HOME)/git/olena/milena
+INCLUDES= $(INCLUDES1) $(INCLUDES2)
+CXXFLAGS= -ggdb -O0 -Wall -W -pedantic -ansi -pipe $(INCLUDES)
+#CXXFLAGS= -DNDEBUG -O1 -Wall -W -pedantic -ansi -pipe $(INCLUDES)
+#CXXFLAGS= -DNDEBUG -O3 -Wall -W -pedantic -ansi -pipe $(INCLUDES)
+ECHO= echo
+RM= rm
+MKDIR= mkdir -p
+CP= cp
+
+SOURCE_PATTERN= green/exp
+BUILD__PATTERN= green/build/exp
+
+
+ifeq ($(findstring $(BUILD__PATTERN),$(PWD)), $(BUILD__PATTERN))
+# Case where make is done from build directory.
+SOURCE_DIR= $(subst $(BUILD__PATTERN),$(SOURCE_PATTERN),$(PWD))
+BUILD__DIR= $(PWD)/
+else
+# Case where make is done from source directory.
+SOURCE_DIR= $(PWD)/
+BUILD__DIR= $(subst $(SOURCE_PATTERN),$(BUILD__PATTERN),$(PWD))
+endif
+
+SRC= $(notdir $(wildcard $(SOURCE_DIR)/*.cc))
+OLD= $(notdir $(wildcard $(SOURCE_DIR)/*~))
+OBJ= $(patsubst %.cc,%.o,$(SRC))
+SOURCE_MAKEFILE=Makefile.am
+BUILD__MAKEFILE=Makefile
+TARGET_FILE= $(notdir $(PWD))
+SOURCE_FILES= $(notdir $(wildcard $(SOURCE_DIR)/*.*))
+BUILD__FILES= $(filter-out $(SRC) $(SOURCE_MAKEFILE), $(SOURCE_FILES))
+
+BUILD__F_PATH= $(addprefix $(BUILD__DIR)/,$(BUILD__FILES))
+SOURCE_F_PATH= $(addprefix $(SOURCE_DIR)/,$(SOURCE_FILES))
+
+BUILD__M_PATH= $(addprefix $(BUILD__DIR)/,$(BUILD__MAKEFILE))
+SOURCE_M_PATH= $(addprefix $(SOURCE_DIR)/,$(SOURCE_MAKEFILE))
+
+TARGET_F_PATH= $(addprefix $(BUILD__DIR)/,$(TARGET_FILE))
+OBJ_F_PATH= $(addprefix $(BUILD__DIR)/,$(OBJ))
+SRC_F_PATH= $(addprefix $(SOURCE_DIR)/,$(SRC))
+OLD_F_PATH= $(addprefix $(SOURCE_DIR)/,$(OLD))
+
+#############
+# BOOTSTRAP #
+#############
+
+
+bootstrap: $(BUILD__DIR) $(BUILD__F_PATH) $(BUILD__M_PATH)
+
+# Create, if nessary, the destination directory
+$(BUILD__DIR):
+ $(MKDIR) $(BUILD__DIR)
+
+# Copy, if nessary, all the files, except the Makefile.am
+$(BUILD__F_PATH): $(SOURCE_F_PATH)
+ $(CP) $(addprefix $(SOURCE_DIR),$(@F)) $@
+
+# Copy if nessary, the Makefile.am into Makefile
+$(BUILD__M_PATH): $(SOURCE_M_PATH)
+ $(CP) $(SOURCE_M_PATH) $(BUILD__M_PATH)
+
+
+#######
+# ALL #
+#######
+
+# We assume that the call is done from the build directory.
+# With the directive vpath, hidden files are found in the source directory.
+
+all: $(TARGET_F_PATH)
+
+
+$(TARGET_F_PATH): $(OBJ_F_PATH)
+ $(LINK.cc) $< $(LOADLIBES) $(LDLIBS) -o $@
+
+$(OBJ_F_PATH):$(SRC_F_PATH)
+ $(COMPILE.cc) $(OUTPUT_OPTION) $<
+
+
+#########
+# CLEAN #
+#########
+
+# Force every time the deletion
+clean: clean_target clean_obj clean_dst clean_old #clean_make
+
+
+clean_target:
+ -@$(RM) $(TARGET_F_PATH) &> /dev/null
+
+clean_obj:
+ -@$(RM) $(OBJ_F_PATH) &> /dev/null
+
+clean_dst:
+ -@$(RM) $(BUILD_F_PATH) &> /dev/null
+
+clean_make:
+ -@$(RM) $(BUILD_M_PATH) &> /dev/null
+
+clean_old:
+ -@$(RM) $(OLD_F_PATH) &> /dev/null
+
+
+#########
+# PRINT #
+#########
+
+print: print_tools print_bootstrap
+
+print_tools:
+ @$(ECHO) "HOME = $(HOME)"
+ @$(ECHO) "INCLUDES = $(INCLUDES)"
+ @$(ECHO) "CXXFLAGS = $(CXXFLAGS)"
+ @$(ECHO) "ECHO = $(ECHO)"
+ @$(ECHO) "RM = $(RM)"
+ @$(ECHO) "MKDIR = $(MKDIR)"
+ @$(ECHO) "CP = $(CP)"
+ @$(ECHO)
+
+print_bootstrap:
+ @$(ECHO) "PWD = $(PWD)"
+ @$(ECHO) "SOURCE_PATTERN = $(SOURCE_PATTERN)"
+ @$(ECHO) "BUILD__PATTERN = $(BUILD__PATTERN)"
+ @$(ECHO) "SOURCE_DIR = $(SOURCE_DIR)"
+ @$(ECHO) "BUILD__DIR = $(BUILD__DIR)"
+ @$(ECHO) "SOURCE_MAKEFILE = $(SOURCE_MAKEFILE)"
+ @$(ECHO) "BUILD__MAKEFILE = $(BUILD__MAKEFILE)"
+ @$(ECHO) "TARGET_FILE = $(TARGET_FILE)"
+ @$(ECHO) "SOURCE_FILES = $(SOURCE_FILES)"
+ @$(ECHO) "SOURCE_F_PATH = $(SOURCE_F_PATH)"
+ @$(ECHO) "BUILD__FILES = $(BUILD__FILES)"
+ @$(ECHO) "BUILD__F_PATH = $(BUILD__F_PATH)"
+ @$(ECHO) "BUILD__M_PATH = $(BUILD__M_PATH)"
+ @$(ECHO) "SOURCE_M_PATH = $(SOURCE_M_PATH)"
+ @$(ECHO) "SRC = $(SRC)"
+ @$(ECHO) "OBJ = $(OBJ)"
+ @$(ECHO) "OLD = $(OLD)"
+ @$(ECHO) "SRC_F_PATH = $(SRC_F_PATH)"
+ @$(ECHO) "OBJ_F_PATH = $(OBJ_F_PATH)"
+ @$(ECHO) "OLD_F_PATH = $(OLD_F_PATH)"
+ @$(ECHO)
diff --git a/scribo/sandbox/green/exp/regional_maxima/regional_maxima.cc b/scribo/sandbox/green/exp/regional_maxima/regional_maxima.cc
new file mode 100644
index 0000000..0cd8389
--- /dev/null
+++ b/scribo/sandbox/green/exp/regional_maxima/regional_maxima.cc
@@ -0,0 +1,196 @@
+// Copyright (C) 2007, 2008, 2009, 2010 EPITA 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.
+
+/// \file
+///
+/// This demonstrator is aimed to experiment the regional maxima
+/// method. regional_maxima.It first test the 3d histogram from an
+/// image and the number of colors which results. And in fact, doesn't
+/// use the regional_maxima routine. Too many parameters must be fixed
+/// and parts of the code has been commented. The last action of this
+/// program consists in counting the number of colors of each image in a
+/// directory. This source has been used to test the annotating image base.
+
+#include <iostream>
+#include <sstream>
+#include <boost/filesystem.hpp>
+
+#include <mln/img_path.hh>
+
+#include <mln/accu/math/sum.hh>
+#include <mln/accu/math/count.hh>
+#include <mln/accu/stat/histo3d_rgb.hh>
+#include <mln/accu/stat/mean.hh>
+#include <mln/accu/stat/variance.hh>
+
+#include <mln/algebra/vec.hh>
+
+#include <mln/arith/diff_abs.hh>
+
+#include <mln/core/macros.hh>
+#include <mln/core/alias/neighb3d.hh>
+#include <mln/core/image/image2d.hh>
+#include <mln/core/image/image3d.hh>
+#include <mln/core/image/dmorph/image_if.hh>
+#include <mln/core/routine/initialize.hh>
+
+#include <mln/data/compute.hh>
+#include <mln/data/fill.hh>
+#include <mln/data/transform.hh>
+
+#include <mln/fun/v2v/rgb8_to_rgbn.hh>
+
+#include <mln/io/pgm/load.hh>
+#include <mln/io/pgm/save.hh>
+#include <mln/io/ppm/load.hh>
+#include <mln/io/ppm/save.hh>
+
+#include <mln/labeling/regional_maxima.hh>
+#include <mln/labeling/mean_values.hh>
+#include <mln/labeling/compute.hh>
+
+#include <mln/literal/colors.hh>
+
+#include <mln/morpho/opening/volume.hh>
+#include <mln/morpho/elementary/dilation.hh>
+
+#include <mln/opt/at.hh>
+
+#include <mln/pw/cst.hh>
+
+#include <mln/util/array.hh>
+#include <mln/util/timer.hh>
+
+#include <mln/value/label_8.hh>
+#include <mln/value/rgb8.hh>
+#include <mln/value/rgb.hh>
+#include <mln/value/int_u.hh>
+
+/// \brief This is the count method.
+///
+/// \param[in] image the colored image.
+///
+/// This function loads a color image (ppm) and count the colors after
+/// using the min volume processing on the 3d histogram. Percentage
+/// thresholding is in test. The file threshold.txt establishes the link
+/// between percentage and size in image.
+///
+// n < 8, n is the degree of quantification
+template <unsigned n>
+unsigned count_image_color(const std::string& image)
+{
+ typedef mln::value::label_8 t_lbl8;
+ typedef mln::value::int_u8 t_int_u8;
+ typedef mln::value::rgb8 t_rgb8;
+ typedef mln::value::rgb<n> t_rgbn;
+ typedef mln::image3d<t_lbl8> t_image3d_lbl8;
+ typedef mln::image2d<t_lbl8> t_image2d_lbl8;
+ typedef mln::image2d<t_rgb8> t_image2d_rgb8;
+ typedef mln::image2d<t_rgbn> t_image2d_rgbn;
+ typedef mln::image2d<t_int_u8> t_image2d_int_u8;
+ typedef mln::image3d<unsigned> t_histo3d;
+ typedef mln::image2d<unsigned> t_histo2d;
+ typedef mln::fun::v2v::rgb8_to_rgbn<n> t_rgb8_to_rgbn;
+ typedef mln::accu::meta::stat::histo3d_rgb t_histo3d_fun;
+ typedef mln::accu::meta::math::count t_count_fun;
+
+ t_image2d_rgb8 input_rgb8;
+ t_image2d_rgbn input_rgbn;
+ t_image2d_rgbn output_rgbn;
+ t_histo3d histo;
+ t_histo3d opened;
+ t_image3d_lbl8 label;
+ t_image2d_lbl8 label_img;
+ t_image3d_lbl8 dilated;
+ t_lbl8 n_labels;
+
+ mln::io::ppm::load(input_rgb8, image.c_str());
+
+ unsigned nb_pixel = input_rgb8.ncols() * input_rgb8.nrows();
+ unsigned min_volume = (unsigned)(nb_pixel * 0.054);
+
+ input_rgbn = mln::data::transform(input_rgb8, t_rgb8_to_rgbn());
+ histo = mln::data::compute(t_histo3d_fun(), input_rgbn);
+ return mln::data::compute(t_count_fun(), histo);
+ // return nb_pixel;
+ // opened = mln::morpho::opening::volume(histo, mln::c6(), min_volume);
+ // label = mln::labeling::regional_maxima(opened, mln::c6(), n_labels);
+ // return n_labels;
+}
+
+
+/// \brief The main function aimed at looping over the whole directory.
+///
+/// The main function is used to take care of file part in this
+/// sofware. It manages the directory scanning aspect while the last
+/// function does the image processing aspect. Statistics are
+/// generated (mean and variance) about the number of colors after using
+/// the min_volume routine. Some strange things happens with that routine
+/// sometimes.
+int main()
+{
+ typedef boost::filesystem::path t_path;
+ //typedef boost::filesystem::initial_path<t_path()> t_init_path;
+ typedef boost::filesystem::directory_iterator t_iter_path;
+
+ t_path full_path(ANNOTATING_1_TYPED_IMG_PATH);
+
+ std::cout << "entering " << full_path << std::endl;
+
+ if (//1 < argc &&
+ boost::filesystem::exists(full_path) &&
+ boost::filesystem::is_directory(full_path))
+ {
+ boost::filesystem::system_complete(full_path);
+ const t_iter_path end_iter;
+ unsigned count = 0;
+ unsigned sum1 = 0;
+ unsigned sum2 = 0;
+
+ for (t_iter_path dir_iter(full_path); end_iter != dir_iter; ++dir_iter)
+ {
+ unsigned val = count_image_color<5>(dir_iter->path().string());
+
+ ++count;
+ sum1 += val;
+ sum2 += val*val;
+
+ std::cout << dir_iter->path().string() << " => " << val << std::endl;
+ // FIXME NB COULEURS BRUTES
+ // FIXME NB DE COULEURS
+ // FIXME LISTE DES COULEURS
+ // IMPORTANCES
+ }
+
+ unsigned mean = sum1 / count;
+ unsigned var = sum2 / count - mean * mean;
+
+ std::cout << "mean : " << mean << std::endl;
+ std::cout << "var : " << var << std::endl;
+ }
+
+ return 0;
+}
+
diff --git a/milena/sandbox/green/demo/labeling/regional_maxima/thresholds.txt b/scribo/sandbox/green/exp/regional_maxima/thresholds.txt
similarity index 100%
copy from milena/sandbox/green/demo/labeling/regional_maxima/thresholds.txt
copy to scribo/sandbox/green/exp/regional_maxima/thresholds.txt
diff --git a/scribo/sandbox/green/mln/display/display_histo.hh b/scribo/sandbox/green/mln/display/display_histo.hh
index ef47182..d48f47f 100644
--- a/scribo/sandbox/green/mln/display/display_histo.hh
+++ b/scribo/sandbox/green/mln/display/display_histo.hh
@@ -47,6 +47,64 @@
/// the blue dimension (green and blue composantes are being correlated). In
/// fact, we sum in along the blue direction. Then, we stretch value to feet
/// pgm format.
+///
+/// This is the sample code to use the red/green visualization.
+///
+/// \fixme There is a lot of routines in display_histo.hh, but only
+/// two of them have been call here. Stuff to complete.
+///
+/// #include <iostream>
+/// #include <mln/accu/stat/histo3d_rgb.hh>
+/// #include <mln/core/macros.hh>
+/// #include <mln/core/image/image2d.hh>
+/// #include <mln/core/image/image3d.hh>
+/// #include <mln/data/compute.hh>
+/// #include <mln/data/transform.hh>
+/// #include <mln/display/display_histo.hh>
+/// #include <mln/fun/v2v/rgb8_to_rgbn.hh>
+/// #include <mln/img_path.hh>
+/// #include <mln/io/ppm/load.hh>
+/// #include <mln/io/pgm/save.hh>
+/// #include <mln/io/ppm/save.hh>
+/// #include <mln/literal/colors.hh>
+/// #include <mln/value/rgb8.hh>
+/// #include <mln/value/rgb.hh>
+///
+/// int main()
+/// {
+/// typedef mln::value::int_u8 t_int_u8;
+/// typedef mln::value::int_u<4> t_int_u4;
+/// typedef mln::value::rgb8 t_rgb8;
+/// typedef mln::value::rgb<4> t_rgb4;
+/// typedef mln::image2d<t_int_u8> t_image2d_int_u8;
+/// typedef mln::image2d<t_int_u4> t_image2d_int_u4;
+/// typedef mln::image2d<t_rgb8> t_image2d_rgb8;
+/// typedef mln::image2d<t_rgb4> t_image2d_rgb4;
+/// typedef mln::image2d<bool> t_image2d_bool;
+/// typedef mln::image3d<unsigned> t_histo3d;
+/// typedef mln::fun::v2v::rgb8_to_rgbn<4> t_rgb8_to_rgb4;
+/// typedef mln::accu::meta::stat::histo3d_rgb t_histo3d_fun;
+///
+/// t_image2d_rgb8 i0_input; // input rgb8
+/// t_image2d_rgb4 i1_input; // input rgbn
+/// t_histo3d h1_input; // histo input
+/// t_image2d_int_u8 p1_histo1;// histo proj1
+/// t_image2d_rgb4 p1_histo2;// histo proj2
+/// t_rgb4 red(mln::literal::red);
+///
+/// mln::io::ppm::load(i0_input, OLENA_IMG_PATH"/lena.ppm");
+///
+/// i1_input = mln::data::transform(i0_input, t_rgb8_to_rgb4());
+/// h1_input = mln::data::compute(t_histo3d_fun(), i1_input);
+/// p1_histo1 = mln::display::display_histo3d_unsigned(h1_input);
+/// p1_histo2 = mln::display::display3_histo3d_unsigned(h1_input, red);
+///
+/// mln::io::pgm::save(p1_histo1, "proj1.pgm");
+/// mln::io::ppm::save(p1_histo2, "proj2.ppm");
+///
+/// return 0;
+/// }
+
namespace mln
@@ -55,26 +113,100 @@ namespace mln
namespace display
{
- // Forward declaration.
+ /// \brief Allow the visualization of the density of the 3d histogram.
+ ///
+ /// Direction r = 1
+ /// Direction g = 2
+ /// Direction b = 0
+ ///
+ /// \parameter[in] histo the histogram in 3d.
+ /// \result return the projection of the histogram in 2d.
+ ///
+ /// The 3d histogram is projected in red/green space by
+ /// accumulating around the the blue dimension (green and blue
+ /// composantes are being correlated). In fact, we sum along the
+ /// blue direction and take the log of value. Then, we stretch
+ /// value to feet pgm format.
image2d<value::int_u8>
display_histo3d_unsigned(const image3d<unsigned>& histo);
+
+ /// \brief Allow the visualization of the important color of the 3d histo.
+ ///
+ /// Direction r = 1
+ /// Direction g = 2
+ /// Direction b = 0
+ ///
+ /// \parameter[in] histo the histogram in 3d.
+ /// \parameter[in] ambiguous_color the color when no max is found.
+ /// \result return the projection of the histogram in 2d.
+ ///
+ /// The 3d histogram is projected in red/green space. In the blue
+ /// direction we check the max blue component. The position in
+ /// this blue axis is returned in the projection image.
template <unsigned n>
image2d< value::int_u<n> >
display2_histo3d_unsigned(const image3d<unsigned>& histo,
const value::int_u<n> ambiguous_color);
+
+ /// \brief Allow the visualization of the color of the 3d segmented histo.
+ ///
+ /// Direction r = 1
+ /// Direction g = 2
+ /// Direction b = 0
+ ///
+ /// \parameter[in] histo the histogram in 3d.
+ /// \parameter[in] label the label image to associate the result with.
+ /// \parameter[in] ambiguous_color the color when no max is found.
+ /// \result return the projection of the histogram in 2d.
+ ///
+ /// The 3d histogram is projected in red/green space. In the blue
+ /// direction we check the max blue component. The position in
+ /// this blue axis is associated to a segmented label and this label
+ /// is returned in the projection image.
template <unsigned n>
image2d<value::label_8>
display2_histo3d_unsigned(const image3d<unsigned>& histo,
const image3d<value::label_8>& label,
const value::label_8 ambiguous_label);
+
+ /// \brief Allow the visualization with color of the 3d histo.
+ ///
+ /// Direction r = 1
+ /// Direction g = 2
+ /// Direction b = 0
+ ///
+ /// \parameter[in] histo the histogram in 3d.
+ /// \parameter[in] ambiguous_color the color when no max is found.
+ /// \result return the projection of the histogram in 2d.
+ ///
+ /// The 3d histogram is projected in red/green space. In the blue
+ /// direction we check the max blue component. The position is used
+ /// to build a rgb color and put it as a returned value in projection image.
template <unsigned n>
image2d< value::rgb<n> >
display3_histo3d_unsigned(const image3d<unsigned>& histo,
const value::rgb<n> ambiguous_color);
+
+ /// \brief Allow the visualization with color of the 3d segmented histo.
+ ///
+ /// Direction r = 1
+ /// Direction g = 2
+ /// Direction b = 0
+ ///
+ /// \parameter[in] histo the histogram in 3d.
+ /// \parameter[in] label the label image to associte the result with.
+ /// \parameter[in] pal the color indexed list to associate to the label.
+ /// \parameter[in] ambiguous_color the color when no max is found.
+ /// \result return the projection of the histogram in 2d.
+ ///
+ /// The 3d histogram is projected in red/green space. In the blue
+ /// direction we check the max blue component. The position is used
+ /// to find the label associate to it and then the color associated to
+ /// this label. That's the information we return in the projection image.
template <unsigned n>
image2d< value::rgb8 >
display3_histo3d_unsigned(const image3d<unsigned>& histo,
@@ -84,21 +216,6 @@ namespace mln
#ifndef MLN_INCLUDE_ONLY
- /// \brief Allow the visualization of a 3d histogram by projection.
- ///
- /// The 3d histogram is projected in red/green space by
- /// accumulating around the the blue dimension (green and blue
- /// composantes are being correlated). In fact, we sum along
- /// the blue direction. Then, we stretch value to feet pgm
- /// format.
- /// Direction r = 1
- /// Direction g = 2
- /// Direction b = 0
- ///
- /// \parameter[in] histo the histogram in 3d.
- /// \result return a equivalent 2d image.
-
- // FIXME : display_shape [in int_u8]
image2d<value::int_u8>
display_histo3d_unsigned(const image3d<unsigned>& histo)
{
diff --git a/scribo/sandbox/green/mln/display/project_histo.hh b/scribo/sandbox/green/mln/display/project_histo.hh
index 30bcd6d..36a5542 100644
--- a/scribo/sandbox/green/mln/display/project_histo.hh
+++ b/scribo/sandbox/green/mln/display/project_histo.hh
@@ -49,9 +49,71 @@
/// \file
///
-/// \brief Allow the visualization of 3d histogram.
-/// The 3d histogram is projected in 2d such as the data in that direction
-/// are accumulated to the two others.
+/// \brief Allow the complete visualization of a 3d histogram by projection.
+///
+/// The 3d histogram is projected in red/green space by accumulating around the
+/// the blue dimension (green and blue composantes are being correlated). In
+/// fact, we sum in along the blue direction. Then, we stretch value to feet
+/// pgm format. This is the same preambule documentation as in display_histo
+/// because display_histo is use as a front hand for this file.
+///
+/// This is the sample code to use the red/green visualization.
+///
+/// \fixme There is a lot of routines in display_histo.hh, but only
+/// two of them have been call here. Stuff to complete.
+///
+/// #include <iostream>
+/// #include <mln/accu/stat/histo3d_rgb.hh>
+/// #include <mln/core/macros.hh>
+/// #include <mln/core/image/image2d.hh>
+/// #include <mln/core/image/image3d.hh>
+/// #include <mln/data/compute.hh>
+/// #include <mln/data/transform.hh>
+/// #include <mln/display/display_histo.hh>
+/// #include <mln/fun/v2v/rgb8_to_rgbn.hh>
+/// #include <mln/img_path.hh>
+/// #include <mln/io/ppm/load.hh>
+/// #include <mln/io/pgm/save.hh>
+/// #include <mln/io/ppm/save.hh>
+/// #include <mln/literal/colors.hh>
+/// #include <mln/value/rgb8.hh>
+/// #include <mln/value/rgb.hh>
+///
+/// int main()
+/// {
+/// typedef mln::value::int_u8 t_int_u8;
+/// typedef mln::value::int_u<4> t_int_u4;
+/// typedef mln::value::rgb8 t_rgb8;
+/// typedef mln::value::rgb<4> t_rgb4;
+/// typedef mln::image2d<t_int_u8> t_image2d_int_u8;
+/// typedef mln::image2d<t_int_u4> t_image2d_int_u4;
+/// typedef mln::image2d<t_rgb8> t_image2d_rgb8;
+/// typedef mln::image2d<t_rgb4> t_image2d_rgb4;
+/// typedef mln::image2d<bool> t_image2d_bool;
+/// typedef mln::image3d<unsigned> t_histo3d;
+/// typedef mln::fun::v2v::rgb8_to_rgbn<4> t_rgb8_to_rgb4;
+/// typedef mln::accu::meta::stat::histo3d_rgb t_histo3d_fun;
+///
+/// t_image2d_rgb8 i0_input; // input rgb8
+/// t_image2d_rgb4 i1_input; // input rgbn
+/// t_histo3d h1_input; // histo input
+/// t_image2d_int_u8 p1_histo1;// histo proj1
+/// t_image2d_rgb4 p1_histo2;// histo proj2
+/// t_rgb4 red(mln::literal::red);
+///
+/// mln::io::ppm::load(i0_input, OLENA_IMG_PATH"/lena.ppm");
+///
+/// i1_input = mln::data::transform(i0_input, t_rgb8_to_rgb4());
+/// h1_input = mln::data::compute(t_histo3d_fun(), i1_input);
+/// p1_histo1 = mln::display::display_histo3d_unsigned(h1_input);
+/// p1_histo2 = mln::display::display3_histo3d_unsigned(h1_input, red);
+///
+/// mln::io::pgm::save(p1_histo1, "proj1.pgm");
+/// mln::io::ppm::save(p1_histo2, "proj2.ppm");
+///
+/// return 0;
+/// }
+
namespace mln
{
@@ -59,50 +121,130 @@ namespace mln
namespace display
{
- // Forward declaration.
+ /// \brief Allow the visualization of the density of the 3d histogram.
+ ///
+ /// Parameter A is the type of accumulator, for instance, accu::math::sum.
+ /// Parameter direction is the way of the projection, for instance blue one.
+ /// Parameter V is the value we use to accumulate information.
+ ///
+ /// Direction r = 1
+ /// Direction g = 2
+ /// Direction b = 0
+ ///
+ /// \parameter[in] histo the histogram in 3d.
+ /// \result return the projection of the histogram in 2d.
+ ///
+ /// The 3d histogram is projected in red/green space by
+ /// accumulating around the the blue dimension (green and blue
+ /// composantes are being correlated). In fact, we sum along the
+ /// blue direction and take the log of value. Then, we stretch
+ /// value to feet pgm format. Not limited to red/green space.
template <typename A, unsigned direction, typename V>
image2d<mln_result(A)>
project_histo(const image3d<V>& histo);
+
+ /// \brief Allow the visualization of the important color of the 3d histo.
+ ///
+ /// Parameter A is the type of accumulator, for instance, accu::math::sum.
+ /// Parameter direction is the way of the projection, for instance blue one.
+ /// Parameter V is the value we use to accumulate information.
+ ///
+ /// Direction r = 1
+ /// Direction g = 2
+ /// Direction b = 0
+ ///
+ /// \parameter[in] histo the histogram in 3d.
+ /// \parameter[in] ambiguous_color the color when no max is found.
+ /// \result return the projection of the histogram in 2d.
+ ///
+ /// The 3d histogram is projected in red/green space. In the blue
+ /// direction we check the max blue component. The position in
+ /// this blue axis is returned in the projection image. Not
+ /// limited to red/green space.
template <typename A, unsigned n, unsigned direction, typename V>
image2d<mln_result(A)>
project2_histo(const image3d<V>& histo,
const value::int_u<n>& ambiguous_color);
+
+ /// \brief Allow the visualization of the color of the 3d segmented histo.
+ ///
+ /// Parameter A is the type of accumulator, for instance, accu::math::sum.
+ /// Parameter direction is the way of the projection, for instance blue one.
+ /// Parameter V is the value we use to accumulate information.
+ ///
+ /// Direction r = 1
+ /// Direction g = 2
+ /// Direction b = 0
+ ///
+ /// \parameter[in] histo the histogram in 3d.
+ /// \parameter[in] label the label image to associate the result with.
+ /// \result return the projection of the histogram in 2d.
+ ///
+ /// The 3d histogram is projected in red/green space. In the blue
+ /// direction we check the max blue component. The position in
+ /// this blue axis is associated to a segmented label and this label
+ /// is returned in the projection image. Not limited to red/green space.
template <unsigned n, unsigned direction, typename V>
image2d<V>
project2_histo(const image3d<unsigned>& histo,
const image3d<V>& label);
+ /// \brief Allow the visualization with color of the 3d histo.
+ ///
+ /// Parameter A is the type of accumulator, for instance, accu::math::sum.
+ /// Parameter direction is the way of the projection, for instance blue one.
+ /// Parameter V is the value we use to accumulate information.
+ ///
+ /// Direction r = 1
+ /// Direction g = 2
+ /// Direction b = 0
+ ///
+ /// \parameter[in] histo the histogram in 3d.
+ /// \parameter[in] ambiguous_color the color when no max is found.
+ /// \result return the projection of the histogram in 2d.
+ ///
+ /// The 3d histogram is projected in red/green space. In the blue
+ /// direction we check the max blue component. The position is
+ /// used to build a rgb color and put it as a returned value in
+ /// projection image. Not limited to red/green space.
template <unsigned n, unsigned direction>
image2d< value::rgb<n> >
project3_histo(const image3d<unsigned>& histo,
const value::rgb<n> ambiguous_color);
+ /// \brief Allow the visualization with color of the 3d segmented histo.
+ ///
+ /// Parameter A is the type of accumulator, for instance, accu::math::sum.
+ /// Parameter direction is the way of the projection, for instance blue one.
+ /// Parameter V is the value we use to accumulate information.
+ ///
+ /// Direction r = 1
+ /// Direction g = 2
+ /// Direction b = 0
+ ///
+ /// \parameter[in] histo the histogram in 3d.
+ /// \parameter[in] label the label image to associte the result with.
+ /// \parameter[in] pal the color indexed list to associate to the label.
+ /// \parameter[in] ambiguous_color the color when no max is found.
+ /// \result return the projection of the histogram in 2d.
+ ///
+ /// The 3d histogram is projected in red/green space. In the blue
+ /// direction we check the max blue component. The position is used
+ /// to find the label associate to it and then the color associated to
+ /// this label. That's the information we return in the projection image.
+ /// Not limited to red/green space.
template <unsigned n, unsigned direction>
image2d< value::rgb8 >
project3_histo(const image3d<unsigned>& histo,
const image3d<value::label_8>& label,
const util::array<algebra::vec<3, float> >& pal,
const value::rgb8 ambiguous_color);
- // FIXME ==> palette must be 1d-image not an array !!
-
# ifndef MLN_INCLUDE_ONLY
- /// \brief Allow the visualization of 3d histogram.
- ///
- /// The 3d histogram is projected in 2d such as the data in that direction
- /// are accumulated to the two others.
- ///
- /// Parameter A is the type of accumulator, for instance, accu::math::sum.
- /// Parameter direction is the way of the projection, for instance blue one.
- /// Parameter V is the value we use to accumulate information.
- ///
- /// \prameter[in] the histogram 3d.
- /// \result the 2d projection of the 3d histogram.
-
template <typename A, unsigned direction, typename V>
image2d<mln_result(A)>
project_histo(const image3d<V>& histo)
diff --git a/scribo/sandbox/green/tools/labeling/histo/Makefile.am b/scribo/sandbox/green/tools/labeling/histo/Makefile.am
new file mode 100644
index 0000000..f03a836
--- /dev/null
+++ b/scribo/sandbox/green/tools/labeling/histo/Makefile.am
@@ -0,0 +1,153 @@
+#
+# Generic Makefile
+#
+
+#########
+# TOOLS #
+#########
+
+#LOADLIBES= -lboost_filesystem
+INCLUDES1= -I$(HOME)/git/olena/scribo/sandbox/green
+INCLUDES2= -I$(HOME)/git/olena/milena
+INCLUDES= $(INCLUDES1) $(INCLUDES2)
+CXXFLAGS= -ggdb -O0 -Wall -W -pedantic -ansi -pipe $(INCLUDES)
+#CXXFLAGS= -DNDEBUG -O1 -Wall -W -pedantic -ansi -pipe $(INCLUDES)
+#CXXFLAGS= -DNDEBUG -O3 -Wall -W -pedantic -ansi -pipe $(INCLUDES)
+ECHO= echo
+RM= rm
+MKDIR= mkdir -p
+CP= cp
+
+SOURCE_PATTERN= green/tools
+BUILD__PATTERN= green/build/tools
+
+
+ifeq ($(findstring $(BUILD__PATTERN),$(PWD)), $(BUILD__PATTERN))
+# Case where make is done from build directory.
+SOURCE_DIR= $(subst $(BUILD__PATTERN),$(SOURCE_PATTERN),$(PWD))
+BUILD__DIR= $(PWD)/
+else
+# Case where make is done from source directory.
+SOURCE_DIR= $(PWD)/
+BUILD__DIR= $(subst $(SOURCE_PATTERN),$(BUILD__PATTERN),$(PWD))
+endif
+
+SRC= $(notdir $(wildcard $(SOURCE_DIR)/*.cc))
+OLD= $(notdir $(wildcard $(SOURCE_DIR)/*~))
+OBJ= $(patsubst %.cc,%.o,$(SRC))
+SOURCE_MAKEFILE=Makefile.am
+BUILD__MAKEFILE=Makefile
+TARGET_FILE= $(notdir $(PWD))
+SOURCE_FILES= $(notdir $(wildcard $(SOURCE_DIR)/*.*))
+BUILD__FILES= $(filter-out $(SRC) $(SOURCE_MAKEFILE), $(SOURCE_FILES))
+
+BUILD__F_PATH= $(addprefix $(BUILD__DIR)/,$(BUILD__FILES))
+SOURCE_F_PATH= $(addprefix $(SOURCE_DIR)/,$(SOURCE_FILES))
+
+BUILD__M_PATH= $(addprefix $(BUILD__DIR)/,$(BUILD__MAKEFILE))
+SOURCE_M_PATH= $(addprefix $(SOURCE_DIR)/,$(SOURCE_MAKEFILE))
+
+TARGET_F_PATH= $(addprefix $(BUILD__DIR)/,$(TARGET_FILE))
+OBJ_F_PATH= $(addprefix $(BUILD__DIR)/,$(OBJ))
+SRC_F_PATH= $(addprefix $(SOURCE_DIR)/,$(SRC))
+OLD_F_PATH= $(addprefix $(SOURCE_DIR)/,$(OLD))
+
+#############
+# BOOTSTRAP #
+#############
+
+
+bootstrap: $(BUILD__DIR) $(BUILD__F_PATH) $(BUILD__M_PATH)
+
+# Create, if nessary, the destination directory
+$(BUILD__DIR):
+ $(MKDIR) $(BUILD__DIR)
+
+# Copy, if nessary, all the files, except the Makefile.am
+$(BUILD__F_PATH): $(SOURCE_F_PATH)
+ $(CP) $(addprefix $(SOURCE_DIR),$(@F)) $@
+
+# Copy if nessary, the Makefile.am into Makefile
+$(BUILD__M_PATH): $(SOURCE_M_PATH)
+ $(CP) $(SOURCE_M_PATH) $(BUILD__M_PATH)
+
+
+#######
+# ALL #
+#######
+
+# We assume that the call is done from the build directory.
+# With the directive vpath, hidden files are found in the source directory.
+
+all: $(TARGET_F_PATH)
+
+
+$(TARGET_F_PATH): $(OBJ_F_PATH)
+ $(LINK.cc) $< $(LOADLIBES) $(LDLIBS) -o $@
+
+$(OBJ_F_PATH):$(SRC_F_PATH)
+ $(COMPILE.cc) $(OUTPUT_OPTION) $<
+
+
+#########
+# CLEAN #
+#########
+
+# Force every time the deletion
+clean: clean_target clean_obj clean_dst clean_old #clean_make
+
+
+clean_target:
+ -@$(RM) $(TARGET_F_PATH) &> /dev/null
+
+clean_obj:
+ -@$(RM) $(OBJ_F_PATH) &> /dev/null
+
+clean_dst:
+ -@$(RM) $(BUILD_F_PATH) &> /dev/null
+
+clean_make:
+ -@$(RM) $(BUILD_M_PATH) &> /dev/null
+
+clean_old:
+ -@$(RM) $(OLD_F_PATH) &> /dev/null
+
+
+#########
+# PRINT #
+#########
+
+print: print_tools print_bootstrap
+
+print_tools:
+ @$(ECHO) "HOME = $(HOME)"
+ @$(ECHO) "INCLUDES = $(INCLUDES)"
+ @$(ECHO) "CXXFLAGS = $(CXXFLAGS)"
+ @$(ECHO) "ECHO = $(ECHO)"
+ @$(ECHO) "RM = $(RM)"
+ @$(ECHO) "MKDIR = $(MKDIR)"
+ @$(ECHO) "CP = $(CP)"
+ @$(ECHO)
+
+print_bootstrap:
+ @$(ECHO) "PWD = $(PWD)"
+ @$(ECHO) "SOURCE_PATTERN = $(SOURCE_PATTERN)"
+ @$(ECHO) "BUILD__PATTERN = $(BUILD__PATTERN)"
+ @$(ECHO) "SOURCE_DIR = $(SOURCE_DIR)"
+ @$(ECHO) "BUILD__DIR = $(BUILD__DIR)"
+ @$(ECHO) "SOURCE_MAKEFILE = $(SOURCE_MAKEFILE)"
+ @$(ECHO) "BUILD__MAKEFILE = $(BUILD__MAKEFILE)"
+ @$(ECHO) "TARGET_FILE = $(TARGET_FILE)"
+ @$(ECHO) "SOURCE_FILES = $(SOURCE_FILES)"
+ @$(ECHO) "SOURCE_F_PATH = $(SOURCE_F_PATH)"
+ @$(ECHO) "BUILD__FILES = $(BUILD__FILES)"
+ @$(ECHO) "BUILD__F_PATH = $(BUILD__F_PATH)"
+ @$(ECHO) "BUILD__M_PATH = $(BUILD__M_PATH)"
+ @$(ECHO) "SOURCE_M_PATH = $(SOURCE_M_PATH)"
+ @$(ECHO) "SRC = $(SRC)"
+ @$(ECHO) "OBJ = $(OBJ)"
+ @$(ECHO) "OLD = $(OLD)"
+ @$(ECHO) "SRC_F_PATH = $(SRC_F_PATH)"
+ @$(ECHO) "OBJ_F_PATH = $(OBJ_F_PATH)"
+ @$(ECHO) "OLD_F_PATH = $(OLD_F_PATH)"
+ @$(ECHO)
diff --git a/scribo/sandbox/green/tools/labeling/histo/histo.cc b/scribo/sandbox/green/tools/labeling/histo/histo.cc
new file mode 100644
index 0000000..1fee9df
--- /dev/null
+++ b/scribo/sandbox/green/tools/labeling/histo/histo.cc
@@ -0,0 +1,204 @@
+// Copyright (C) 2007, 2008, 2009, 2010 EPITA 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.
+
+/// \file
+///
+/// \brief This tool aimed at building 3d RGB histogram.
+///
+/// Building histogram means quantifying the input and then image computing
+/// the 3d histogram in RGB space.
+
+#include <iostream>
+
+#include <mln/accu/stat/histo3d_rgb.hh>
+
+#include <mln/core/macros.hh>
+#include <mln/core/image/image2d.hh>
+#include <mln/core/image/image3d.hh>
+#include <mln/core/image/dmorph/image_if.hh>
+
+#include <mln/data/compute.hh>
+#include <mln/data/transform.hh>
+
+#include <mln/display/display_histo.hh>
+
+#include <mln/fun/v2v/rgb8_to_rgbn.hh>
+
+#include <mln/io/pbm/load.hh>
+#include <mln/io/ppm/load.hh>
+#include <mln/io/dump/save.hh>
+#include <mln/io/pgm/save.hh>
+#include <mln/io/ppm/save.hh>
+
+#include <mln/literal/colors.hh>
+
+#include <mln/opt/at.hh>
+
+#include <mln/pw/value.hh>
+
+#include <mln/value/rgb8.hh>
+#include <mln/value/rgb.hh>
+
+
+/// \brief The histogram image processing chain.
+///
+/// \param[in] input the input image.
+/// \param[out] quant the name of the resulting quantified image.
+/// \param[out] histo the name of the resulting 3d histogram.
+/// \param[out] proj1 the red/green projection of the histogram.
+/// \param[out] proj2 the red/green projection with maxima plot on.
+/// \param[in] mask the mask with selects the pixels of the input image.
+///
+/// This chain aimed at computing 3d RGB histogram of 2d RGB color
+/// quantified image. As the 3d histogram induces lots and lots of
+/// data, quantifiying the input image reduces the size of the
+/// resulting histogram. Then, dumping and projections are done.
+template <unsigned n>
+void mk_histo(const std::string& input, // in
+ const std::string& quant, // in
+ const std::string& histo, // out
+ const std::string& proj1, // out
+ const std::string& proj2, // out
+ const std::string& mask) // [in]
+{
+ typedef mln::value::int_u8 t_int_u8;
+ typedef mln::value::int_u<n> t_int_un;
+ typedef mln::value::rgb8 t_rgb8;
+ typedef mln::value::rgb<n> t_rgbn;
+ typedef mln::image2d<t_int_u8> t_image2d_int_u8;
+ typedef mln::image2d<t_int_un> t_image2d_int_un;
+ typedef mln::image2d<t_rgb8> t_image2d_rgb8;
+ typedef mln::image2d<t_rgbn> t_image2d_rgbn;
+ typedef mln::image2d<bool> t_image2d_bool;
+ typedef mln::image3d<unsigned> t_histo3d;
+ typedef mln::fun::v2v::rgb8_to_rgbn<n> t_rgb8_to_rgbn;
+ typedef mln::accu::meta::stat::histo3d_rgb t_histo3d_fun;
+
+ // START OF IMAGE PROCESSING CHAIN
+ t_image2d_rgb8 i0_input; // input rgb8
+ t_image2d_rgbn i1_input; // input rgbn
+ t_image2d_bool m0_input; // mask input
+ t_histo3d h1_input; // histo input
+ t_image2d_int_u8 p1_histo1;// histo proj1
+ t_image2d_rgbn p1_histo2;// histo proj2
+ t_rgbn red(mln::literal::red);
+
+ mln::io::ppm::load(i0_input, input.c_str());
+ i1_input = mln::data::transform(i0_input, t_rgb8_to_rgbn());
+
+ if (0 < mask.size())
+ {
+ mln::io::pbm::load(m0_input, mask.c_str());
+ h1_input = mln::data::compute(t_histo3d_fun(),
+ (i1_input | mln::pw::value(m0_input)).rw());
+ }
+ else
+ {
+ h1_input = mln::data::compute(t_histo3d_fun(), i1_input);
+ }
+ // END OF IMAGE PROCESSING CHAIN
+
+ // BEGIN DUMPING
+ p1_histo1 = mln::display::display_histo3d_unsigned(h1_input);
+ p1_histo2 = mln::display::display3_histo3d_unsigned(h1_input, red);
+
+ mln::io::ppm::save(i1_input, quant.c_str());
+ mln::io::dump::save(h1_input, histo.c_str());
+ mln::io::pgm::save(p1_histo1, proj1.c_str());
+ mln::io::ppm::save(p1_histo2, proj2.c_str());
+ // END DUMPING
+}
+
+
+/// \brief The online documentation of the tool.
+///
+/// Print the documentation of the tool with the meaning of the
+/// different parameters.
+void usage()
+{
+ std::cout << std::endl;
+ std::cout << "histo input.ppm q quant.ppm histo.dump proj.pgm"
+ << " proj.ppm [msk.pbm]" << std::endl;
+ std::cout << std::endl;
+ std::cout << "where :" << std::endl;
+ std::cout << "* [ in] input.ppm is the 8 bits color ppm image" << std::endl;
+ std::cout << "* [ in] q is the degree of quantification"
+ << " {2,3,4,5,6,7,8}" << std::endl;
+ std::cout << "* [out] quant.ppm is the q bits quantified input"
+ << " image" << std::endl;
+ std::cout << "* [out] histo.dump is the quantified color"
+ << " histogram" << std::endl;
+ std::cout << "* [out] proj.pgm is the r/g projection of the"
+ << " histogram (summing along the blue axe)" << std::endl;
+ std::cout << "* [out] proj.ppm is the r/g projection of the"
+ << " histogram with maxima plot on" << std::endl;
+ std::cout << "* [ in] msk.pbm is the mask which selects the"
+ << " pixels" << std::endl;
+ std::cout << std::endl;
+}
+
+
+/// \brief The main entry of the software.
+///
+/// \param[in] input the input image.
+/// \param[in] q the quantification.
+/// \param[out] quant.ppm the name of the resulting quantified image.
+/// \param[out] histo.dump the name of the resulting 3d histogram.
+/// \param[out] proj.pgm the red/green projection of the histogram.
+/// \param[out] proj.ppm the red/green projection with maxima plot on.
+/// \param[in] msk.pbm the mask with selects the pixels of the input image.
+///
+/// This is the front hand for the image processing routine. The goal of this
+/// chain is to provide 3d histogram for further analysis and to give a way to
+/// see it.
+int main(int argc, char* args[])
+{
+ if (7 == argc || 8 == argc)
+ {
+ const std::string input(args[1]); // in
+ const char q = args[2][0]; // in
+ const std::string quant(args[3]); // out
+ const std::string histo(args[4]); // out
+ const std::string proj1(args[5]); // out
+ const std::string proj2(args[6]); // out
+ const std::string mask(8 == argc? args[7] : ""); // [in]
+
+ switch(q)
+ {
+ case '2': mk_histo<2>(input, quant, histo, proj1, proj2, mask); break;
+ case '3': mk_histo<3>(input, quant, histo, proj1, proj2, mask); break;
+ case '4': mk_histo<4>(input, quant, histo, proj1, proj2, mask); break;
+ case '5': mk_histo<5>(input, quant, histo, proj1, proj2, mask); break;
+ case '6': mk_histo<6>(input, quant, histo, proj1, proj2, mask); break;
+ case '7': mk_histo<7>(input, quant, histo, proj1, proj2, mask); break;
+ case '8': mk_histo<8>(input, quant, histo, proj1, proj2, mask); break;
+ default: usage(); break;
+ }
+ }
+ else
+ usage();
+
+ return 0;
+}
diff --git a/scribo/sandbox/green/tools/labeling/iz/Makefile.am b/scribo/sandbox/green/tools/labeling/iz/Makefile.am
new file mode 100644
index 0000000..57e7ec9
--- /dev/null
+++ b/scribo/sandbox/green/tools/labeling/iz/Makefile.am
@@ -0,0 +1,153 @@
+#
+# Generic Makefile
+#
+
+#########
+# TOOLS #
+#########
+
+LOADLIBES= -lboost_filesystem
+INCLUDES1= -I$(HOME)/git/olena/scribo/sandbox/green
+INCLUDES2= -I$(HOME)/git/olena/milena
+INCLUDES= $(INCLUDES1) $(INCLUDES2)
+CXXFLAGS= -ggdb -O0 -Wall -W -pedantic -ansi -pipe $(INCLUDES)
+#CXXFLAGS= -DNDEBUG -O1 -Wall -W -pedantic -ansi -pipe $(INCLUDES)
+#CXXFLAGS= -DNDEBUG -O3 -Wall -W -pedantic -ansi -pipe $(INCLUDES)
+ECHO= echo
+RM= rm
+MKDIR= mkdir -p
+CP= cp
+
+SOURCE_PATTERN= green/tools
+BUILD__PATTERN= green/build/tools
+
+
+ifeq ($(findstring $(BUILD__PATTERN),$(PWD)), $(BUILD__PATTERN))
+# Case where make is done from build directory.
+SOURCE_DIR= $(subst $(BUILD__PATTERN),$(SOURCE_PATTERN),$(PWD))
+BUILD__DIR= $(PWD)/
+else
+# Case where make is done from source directory.
+SOURCE_DIR= $(PWD)/
+BUILD__DIR= $(subst $(SOURCE_PATTERN),$(BUILD__PATTERN),$(PWD))
+endif
+
+SRC= $(notdir $(wildcard $(SOURCE_DIR)/*.cc))
+OLD= $(notdir $(wildcard $(SOURCE_DIR)/*~))
+OBJ= $(patsubst %.cc,%.o,$(SRC))
+SOURCE_MAKEFILE=Makefile.am
+BUILD__MAKEFILE=Makefile
+TARGET_FILE= $(notdir $(PWD))
+SOURCE_FILES= $(notdir $(wildcard $(SOURCE_DIR)/*.*))
+BUILD__FILES= $(filter-out $(SRC) $(SOURCE_MAKEFILE), $(SOURCE_FILES))
+
+BUILD__F_PATH= $(addprefix $(BUILD__DIR)/,$(BUILD__FILES))
+SOURCE_F_PATH= $(addprefix $(SOURCE_DIR)/,$(SOURCE_FILES))
+
+BUILD__M_PATH= $(addprefix $(BUILD__DIR)/,$(BUILD__MAKEFILE))
+SOURCE_M_PATH= $(addprefix $(SOURCE_DIR)/,$(SOURCE_MAKEFILE))
+
+TARGET_F_PATH= $(addprefix $(BUILD__DIR)/,$(TARGET_FILE))
+OBJ_F_PATH= $(addprefix $(BUILD__DIR)/,$(OBJ))
+SRC_F_PATH= $(addprefix $(SOURCE_DIR)/,$(SRC))
+OLD_F_PATH= $(addprefix $(SOURCE_DIR)/,$(OLD))
+
+#############
+# BOOTSTRAP #
+#############
+
+
+bootstrap: $(BUILD__DIR) $(BUILD__F_PATH) $(BUILD__M_PATH)
+
+# Create, if nessary, the destination directory
+$(BUILD__DIR):
+ $(MKDIR) $(BUILD__DIR)
+
+# Copy, if nessary, all the files, except the Makefile.am
+$(BUILD__F_PATH): $(SOURCE_F_PATH)
+ $(CP) $(addprefix $(SOURCE_DIR),$(@F)) $@
+
+# Copy if nessary, the Makefile.am into Makefile
+$(BUILD__M_PATH): $(SOURCE_M_PATH)
+ $(CP) $(SOURCE_M_PATH) $(BUILD__M_PATH)
+
+
+#######
+# ALL #
+#######
+
+# We assume that the call is done from the build directory.
+# With the directive vpath, hidden files are found in the source directory.
+
+all: $(TARGET_F_PATH)
+
+
+$(TARGET_F_PATH): $(OBJ_F_PATH)
+ $(LINK.cc) $< $(LOADLIBES) $(LDLIBS) -o $@
+
+$(OBJ_F_PATH):$(SRC_F_PATH)
+ $(COMPILE.cc) $(OUTPUT_OPTION) $<
+
+
+#########
+# CLEAN #
+#########
+
+# Force every time the deletion
+clean: clean_target clean_obj clean_dst clean_old #clean_make
+
+
+clean_target:
+ -@$(RM) $(TARGET_F_PATH) &> /dev/null
+
+clean_obj:
+ -@$(RM) $(OBJ_F_PATH) &> /dev/null
+
+clean_dst:
+ -@$(RM) $(BUILD_F_PATH) &> /dev/null
+
+clean_make:
+ -@$(RM) $(BUILD_M_PATH) &> /dev/null
+
+clean_old:
+ -@$(RM) $(OLD_F_PATH) &> /dev/null
+
+
+#########
+# PRINT #
+#########
+
+print: print_tools print_bootstrap
+
+print_tools:
+ @$(ECHO) "HOME = $(HOME)"
+ @$(ECHO) "INCLUDES = $(INCLUDES)"
+ @$(ECHO) "CXXFLAGS = $(CXXFLAGS)"
+ @$(ECHO) "ECHO = $(ECHO)"
+ @$(ECHO) "RM = $(RM)"
+ @$(ECHO) "MKDIR = $(MKDIR)"
+ @$(ECHO) "CP = $(CP)"
+ @$(ECHO)
+
+print_bootstrap:
+ @$(ECHO) "PWD = $(PWD)"
+ @$(ECHO) "SOURCE_PATTERN = $(SOURCE_PATTERN)"
+ @$(ECHO) "BUILD__PATTERN = $(BUILD__PATTERN)"
+ @$(ECHO) "SOURCE_DIR = $(SOURCE_DIR)"
+ @$(ECHO) "BUILD__DIR = $(BUILD__DIR)"
+ @$(ECHO) "SOURCE_MAKEFILE = $(SOURCE_MAKEFILE)"
+ @$(ECHO) "BUILD__MAKEFILE = $(BUILD__MAKEFILE)"
+ @$(ECHO) "TARGET_FILE = $(TARGET_FILE)"
+ @$(ECHO) "SOURCE_FILES = $(SOURCE_FILES)"
+ @$(ECHO) "SOURCE_F_PATH = $(SOURCE_F_PATH)"
+ @$(ECHO) "BUILD__FILES = $(BUILD__FILES)"
+ @$(ECHO) "BUILD__F_PATH = $(BUILD__F_PATH)"
+ @$(ECHO) "BUILD__M_PATH = $(BUILD__M_PATH)"
+ @$(ECHO) "SOURCE_M_PATH = $(SOURCE_M_PATH)"
+ @$(ECHO) "SRC = $(SRC)"
+ @$(ECHO) "OBJ = $(OBJ)"
+ @$(ECHO) "OLD = $(OLD)"
+ @$(ECHO) "SRC_F_PATH = $(SRC_F_PATH)"
+ @$(ECHO) "OBJ_F_PATH = $(OBJ_F_PATH)"
+ @$(ECHO) "OLD_F_PATH = $(OLD_F_PATH)"
+ @$(ECHO)
diff --git a/scribo/sandbox/green/tools/labeling/iz/iz.cc b/scribo/sandbox/green/tools/labeling/iz/iz.cc
new file mode 100644
index 0000000..f977898
--- /dev/null
+++ b/scribo/sandbox/green/tools/labeling/iz/iz.cc
@@ -0,0 +1,495 @@
+// Copyright (C) 2007, 2008, 2009, 2010 EPITA 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.
+
+/// \file
+///
+/// \brief This tool aimed at propagating segmented labels over the background.
+///
+/// Because regional maxima are very small regions, we need to make
+/// them growing to be representative in the color space.
+///
+/// \fixme Sorry, this source doesn't compile. The fact is the
+/// influence_zone_geodesic has changed and fastest version is more
+/// attentive to 2d image than 3d. That's why l.127 it call a 2d version of the
+/// method at() and it's make trouble with my code that uses a 3d image.
+
+#include <iostream>
+#include <fstream>
+#include <boost/format.hpp>
+
+#include <mln/accu/stat/histo3d_rgb.hh>
+
+#include <mln/core/macros.hh>
+#include <mln/core/alias/neighb3d.hh>
+#include <mln/core/image/image2d.hh>
+#include <mln/core/image/image3d.hh>
+
+#include <mln/data/compute.hh>
+
+#include <mln/display/display_histo.hh>
+
+#include <mln/io/dump/load.hh>
+#include <mln/io/dump/save.hh>
+#include <mln/io/ppm/load.hh>
+#include <mln/io/ppm/save.hh>
+#include <mln/io/pgm/load.hh>
+#include <mln/io/pgm/save.hh>
+
+#include <mln/literal/colors.hh>
+
+#include <mln/labeling/compute.hh>
+#include <mln/labeling/mean_values.hh>
+
+#include <mln/transform/influence_zone_geodesic.hh>
+#include <mln/transform/influence_zone_geodesic_saturated.hh>
+
+#include <mln/value/int_u8.hh>
+
+/// \ brief Compute the 2d labeled image.
+///
+/// Compute the 2d labeled image with the 2d labeled histogram and
+/// the input image.
+///
+/// \fixme Need to put it in mln library. Nothing to do here.
+template <unsigned n>
+struct t_labeling_rgbn : mln::Function_v2v< t_labeling_rgbn<n> >
+{
+ typedef mln::value::rgb<n> t_rgbn;
+ typedef mln::value::label_8 t_lbl8;
+ typedef t_rgbn argument;
+ typedef t_lbl8 result;
+ typedef mln::image3d<t_lbl8> t_label;
+
+ const t_label& _label;
+
+ t_labeling_rgbn(const t_label& label) : _label(label) {}
+
+ result operator()(const argument& c) const
+ {
+ t_lbl8 tmp = mln::opt::at(_label, c.blue(), c.red(), c.green());
+
+ return tmp;
+ }
+};
+
+/// \brief Compute and dump stats.
+///
+/// \param[in] i_input_rgb8 the 2d rgb input image.
+/// \param[in] l_input_lbl8 the 2d labeled image.
+/// \param[in] h_histo_rgbn the quantified histogram.
+/// \param[in] l_histo_lbl8 the labeled quantified histogram.
+/// \param[in] n_labels the number of labels (number of regions).
+/// \param[in] the name of the logging file for the stats.
+///
+/// Every segmented color has got it's own label. For each label, we
+/// compute the mean in the r/g/b channels, the total of pixels, the
+/// percentage of pixels in the image and the percentage without counting
+/// the background (label 0).
+void compute_stats(const mln::image2d<mln::value::rgb8>& i_input_rgb8,
+ const mln::image2d<mln::value::label_8>& l_input_lbl8,
+ const mln::image3d<unsigned>& h_histo_rgbn,
+ const mln::image3d<mln::value::label_8>& l_histo_lbl8,
+ const mln::value::label_8& n_labels,
+ const std::string& log)
+{
+ typedef mln::algebra::vec<3,float> t_vec3f;
+ typedef mln::accu::math::sum<unsigned,unsigned> t_sum;
+ typedef mln::accu::stat::mean<t_vec3f,t_vec3f,t_vec3f> t_mean;
+ typedef mln::util::array<unsigned> t_count_array;
+ typedef mln::util::array<t_vec3f> t_mean_array;
+
+ mln::util::array<float> abs((unsigned)(n_labels)+1);
+ mln::util::array<float> rel((unsigned)(n_labels)+1);
+ unsigned nb = 0;
+
+ for (unsigned i = 0; i <= n_labels; ++i)
+ {
+ abs[i] = 0.0;
+ rel[i] = 0.0;
+ }
+
+ // COMPUTE THE SUM
+ t_count_array count = mln::labeling::compute(t_sum(),
+ h_histo_rgbn,
+ l_histo_lbl8,
+ n_labels);
+
+ // COMPUTE THE TOTAL
+ for (unsigned i = 0; i <= n_labels; ++i)
+ {
+ unsigned c = count[i];
+ nb += c;
+ }
+
+ // COMPUTE THE PERCENTAGES
+ for (unsigned i = 0; i <= n_labels; ++i)
+ if (0 < count[i])
+ {
+ abs[i] = ((float)count[i] / nb)*100.0;
+ rel[i] = ((float)count[i] / (nb - count[0]))*100.0;
+ }
+
+ // COMPUTE THE MEAN
+
+ t_mean_array mean = mln::labeling::compute(t_mean(),
+ i_input_rgb8,
+ l_input_lbl8,
+ n_labels);
+
+ // CORRECT 0 LABEL STATS
+ rel[0] = 0;
+ mean[0][0] = 255.0;
+ mean[0][1] = 255.0;
+ mean[0][2] = 0.0;
+
+ // PRINT STATS
+ std::ofstream log_stream(log.c_str());
+
+ for (unsigned i = 0; i <= n_labels; ++i)
+ {
+ const t_vec3f& mean_v = mean[i];
+
+ log_stream << boost::format("%2i|"
+ "r = %6.2f, g = %6.2f, b = %6.2f |"
+ "c = %7i, %%i = %5.2f, %%c = %5.2f")
+ % i
+ % mean_v[0]
+ % mean_v[1]
+ % mean_v[2]
+ % count[i]
+ % abs[i]
+ % rel[i]
+ << std::endl;
+ }
+
+ log_stream << std::endl << std::endl;
+ log_stream.flush();
+ log_stream.close();
+}
+
+
+/// \brief Verify that a marker is present on the stream.
+///
+/// \param[in] stream the input stream.
+/// \param[in] expected the expected character to be on the stream.
+///
+/// \return true if the expected character was on the stream, else false.
+///
+/// This routine enables to read structured colormap file and to
+/// follow the structure while reading colors.
+bool expect(std::istream& stream, const std::string expected)
+{
+ bool result;
+ std::string got;
+
+ stream >> got;
+
+ result = (got == expected);
+
+ return result;
+}
+
+/// \brief Read a line of the colormap.
+///
+/// \param[in] stream the input stream.
+/// \param[out] color the output color read in the current line.
+///
+/// \return the modified streams.
+///
+/// This routine splits a line in differents marks in order to read
+/// the R/G/B channels of the output color.
+std::istream& operator>>(std::istream& stream,
+ mln::algebra::vec<3,float>& color)
+{
+ unsigned lbl;
+
+ stream >> lbl;
+ if (expect(stream, std::string("|")) &&
+ expect(stream, std::string("r")) &&
+ expect(stream, std::string("=")))
+ {
+ stream >> color[0];
+
+ if (expect(stream, std::string(",")) &&
+ expect(stream, std::string("g")) &&
+ expect(stream, std::string("=")))
+ {
+ stream >> color[1];
+
+ if (expect(stream, std::string(",")) &&
+ expect(stream, std::string("b")) &&
+ expect(stream, std::string("=")))
+ {
+ stream >> color[2];
+ }
+ }
+ }
+
+ return stream;
+}
+
+
+/// \brief Load the colormap.
+///
+/// \param[out] m2_label the memory representation of the colormap.
+/// \param[in] colormap the name of the file where the colormap is stocked.
+///
+/// This routine coordonates parsing actions in the colormap file.
+void load(mln::util::array< mln::algebra::vec<3,float> >& m2_label,
+ const char *colormap)
+{
+ typedef mln::algebra::vec<3,float> t_vec3f;
+ typedef mln::util::array<t_vec3f> t_mean_array;
+
+ std::ifstream stream(colormap);
+ std::string buffer;
+
+ getline(stream, buffer);
+
+ while (0 < buffer.size())
+ {
+ std::stringstream line(buffer);
+ t_vec3f mean_v;
+
+ line >> mean_v;
+
+ m2_label.append(mean_v);
+
+ getline(stream, buffer);
+ }
+
+ stream.close();
+}
+
+/// \brief The image processing routine.
+///
+/// \param[in] labeled the name of the 3d labeled histogram.
+/// \param[in] d the depth for the zone influence transformation, 0 eq infinite.
+/// \param[in] nbh the neighbouring (c6|c18|c26).
+/// \param[in] input the 8 bit color ppm input image.
+/// \param[in] quant the name of quantified RGB input image.
+/// \param[in] histo the name of the 3d RGB quantified histogram.
+/// \param[in] colormap the name of the colormap for labels.
+/// \param[out] iz is the iz labeled 3d histogram.
+/// \param[out] proj the red/green projection of the segmented histogram.
+/// \param[out] mean the name of the mean rebuilded image.
+/// \param[out] stats the name of the statistics file (optional).
+///
+/// The core routine starts with image loading, then calls the rigth
+/// iz version and then dumps the results, computes the stats and
+/// makes r/g projection. The role of the iz routine is to propagated
+/// labels around the regional maxima to enlarge the small previous
+/// obtained regions.
+template<unsigned n>
+void mk_iz(const std::string& labeled, // in
+ const unsigned d, // in
+ const mln::neighb3d& nbh, // in
+ const std::string& input, // in
+ const std::string& quant, // in
+ const std::string& histo, // in
+ const std::string& colormap,// in
+ const std::string& iz, // out
+ const std::string& proj, // out
+ const std::string& mean, // out
+ const std::string& stats) // [out]
+{
+ typedef mln::value::int_u8 t_int_u8;
+ typedef mln::value::label_8 t_lbl8;
+ typedef mln::value::rgb8 t_rgb8;
+ typedef mln::value::rgb<n> t_rgbn;
+ typedef mln::algebra::vec<3,float> t_v3f;
+ typedef mln::image2d<t_int_u8> t_image2d_int_u8;
+ typedef mln::image2d<t_rgb8> t_image2d_rgb8;
+ typedef mln::image2d<t_rgbn> t_image2d_rgbn;
+ typedef mln::image2d<t_lbl8> t_image2d_lbl8;
+ typedef mln::image3d<unsigned> t_histo3d;
+ typedef mln::image3d<t_lbl8> t_image3d_lbl8;
+ typedef mln::accu::meta::stat::histo3d_rgb t_histo3d_fun;
+ typedef mln::accu::stat::mean<t_v3f,t_v3f,t_v3f> t_mean;
+ typedef mln::util::array<t_v3f> t_mean_array;
+
+ // START OF IMAGE PROCESSING CHAIN
+ t_image2d_rgb8 i0_input; // input img
+ t_image2d_rgbn i1_input; // quant img
+ t_histo3d h1_input; // histo input
+ t_histo3d h2_input; // histo input
+ t_image2d_int_u8 p1_histo; // histo proj
+ t_image2d_rgb8 p3_histo; // histo proj
+ t_image3d_lbl8 l2_histo; // label histo
+ t_image3d_lbl8 l3_histo; // iz label hist
+ t_mean_array m2_label; // colormap
+ t_mean_array m3_label; // colormap
+ t_image2d_lbl8 l3_input; // label input
+ t_image2d_rgb8 i3_mean; // reconstructed
+
+ t_lbl8 n_lbl; // nb labels
+ t_rgb8 red(mln::literal::red);
+
+ mln::io::dump::load(l2_histo, labeled.c_str());
+ mln::io::ppm::load(i0_input, input.c_str());
+ mln::io::ppm::load(i1_input, quant.c_str());
+ mln::io::dump::load(h1_input, histo.c_str());
+ load(m2_label, colormap.c_str());
+
+ if (0 == d)
+ {
+ l3_histo = mln::transform::influence_zone_geodesic(l2_histo, nbh);
+ }
+ else
+ {
+ l3_histo =mln::transform::influence_zone_geodesic_saturated(l2_histo,nbh,d);
+ }
+ // END OF IMAGE PROCESSING CHAIN
+
+ // BEGIN DUMPING
+
+ n_lbl = (t_lbl8)(m2_label.size()-1);
+
+ l3_input = mln::data::transform(i1_input, t_labeling_rgbn<n>(l3_histo));
+ i3_mean = mln::labeling::mean_values(i0_input, l3_input, n_lbl);
+ m3_label = mln::labeling::compute(t_mean(), i0_input, l3_input, n_lbl);
+
+ // CORRECT 0 LABEL STATS
+ m3_label[0][0] = 255.0;
+ m3_label[0][1] = 255.0;
+ m3_label[0][2] = 0.0;
+
+ p3_histo = mln::display::display3_histo3d_unsigned<n>(h1_input,
+ l3_histo,
+ m3_label,
+ red);
+ mln::io::dump::save(l3_input, iz.c_str());
+ mln::io::ppm::save(p3_histo, proj.c_str());
+ mln::io::ppm::save(i3_mean, mean.c_str());
+
+ if (0 < stats.size())
+ compute_stats(i0_input, l3_input, h1_input, l3_histo, n_lbl, stats);
+
+ // END DUMPING
+}
+
+
+/// \brief The online documentation of the tool.
+///
+/// Print the documentation of the tool with the meaning of the
+/// different parameters.
+void usage()
+{
+ std::cout << std::endl;
+ std::cout << "iz labeled.dump d nbh input.ppm q quant.ppm"
+ << " histo.dump colormap.txt iz.dump proj.ppm"
+ << " mean.ppm [stats.txt]" << std::endl;
+ std::cout << std::endl;
+ std::cout << "where :" << std::endl;
+ std::cout << "* [ in] labeled.dump is the labeled 3d histogram" << std::endl;
+ std::cout << "* [ in] d is the depth for the zone influence"
+ << " transformation (0 means infinite)" << std::endl;
+ std::cout << "* [ in] nbh is the 3d neighbourhood {6,18,26}" << std::endl;
+ std::cout << "* [ in] input.ppm is the 8 bits color ppm image" << std::endl;
+ std::cout << "* [ in] q is the degree of quantification"
+ << " {2,3,4,5,6,7,8}" << std::endl;
+ std::cout << "* [ in] quant.ppm is the q bits quantified input"
+ << " image" << std::endl;
+ std::cout << "* [ in] histo.dump is the quantified color"
+ << " histogram" << std::endl;
+ std::cout << "* [ in] colormap.txt is the colormap for labels" << std::endl;
+ std::cout << "* [out] iz.dump is the iz labeled 3d histogram" << std::endl;
+ std::cout << "* [out] proj.ppm is the r/g projection of the"
+ << " histogram with maxima label plot on" << std::endl;
+ std::cout << "* [out] mean.ppm is the mean reconstructed image" << std::endl;
+ std::cout << "* [out] stats.txt is the statistical label report"<< std::endl;
+ std::cout << std::endl;
+}
+
+/// \brief The main entry of the software.
+///
+/// \param[in] labeled.dump the name of the 3d labeled histogram.
+/// \param[in] d the depth for the zone influence transformation, 0 eq infinite.
+/// \param[in] nbh the code for the neighbouring (6|18|26).
+/// \param[in] input.ppm the 8 bit color ppm input image.
+/// \param[in] q is the degree of quantification {2,3,4,5,6,7,8}.
+/// \param[in] quant.ppm the name of quantified RGB input image.
+/// \param[in] histo.dump the name of the 3d RGB quantified histogram.
+/// \param[in] colormap.txt the name of the colormap for labels.
+/// \param[out] iz.dump is the iz labeled 3d histogram.
+/// \param[out] proj.ppm the red/green projection of the segmented histogram.
+/// \param[out] mean.ppm the name of the mean rebuilded image.
+/// \param[out] stats.txt the name of the statistics file (optional).
+///
+/// This is the front hand for the image processing routine. The goal of this
+/// chain is to provide 3d histogram for further analysis and to give a way to
+/// see it.
+int main(int argc, char* args[])
+{
+ if (12 == argc || 13 == argc)
+ {
+ const std::string labeled(args[1]); // in
+ const unsigned d = atoi(args[2]); // in
+ const char nbh = args[3][0]; // in
+ const std::string input(args[4]); // in
+ const char q = args[5][0]; // in
+ const std::string quant(args[6]); // in
+ const std::string histo(args[7]); // in
+ const std::string colormap(args[8]); // in
+ const std::string iz(args[9]); // out
+ const std::string proj(args[10]); // out
+ const std::string mean(args[11]); // out
+ const std::string stats(13 == argc? args[12] : ""); // [out]
+
+
+ mln::neighb3d neighbourhood;
+
+ switch (nbh)
+ {
+ case '6': neighbourhood = mln::c6(); break;
+ case '1': neighbourhood = mln::c18(); break;
+ case '2': neighbourhood = mln::c26(); break;
+ default: usage(); return 0; // force usage and quit
+ }
+
+ switch (q)
+ {
+ case '2' : mk_iz<2>(labeled,d,neighbourhood,input,quant,
+ histo,colormap,iz,proj,mean,stats);break;
+ case '3' : mk_iz<3>(labeled,d,neighbourhood,input,quant,
+ histo,colormap,iz,proj,mean,stats);break;
+ case '4' : mk_iz<4>(labeled,d,neighbourhood,input,quant,
+ histo,colormap,iz,proj,mean,stats);break;
+ case '5' : mk_iz<5>(labeled,d,neighbourhood,input,quant,
+ histo,colormap,iz,proj,mean,stats);break;
+ case '6' : mk_iz<6>(labeled,d,neighbourhood,input,quant,
+ histo,colormap,iz,proj,mean,stats);break;
+ case '7' : mk_iz<7>(labeled,d,neighbourhood,input,quant,
+ histo,colormap,iz,proj,mean,stats);break;
+ case '8' : mk_iz<8>(labeled,d,neighbourhood,input,quant,
+ histo,colormap,iz,proj,mean,stats);break;
+ default: usage(); break;
+ }
+ }
+ else
+ usage();
+
+ return 0;
+}
diff --git a/scribo/sandbox/green/tools/labeling/opening/Makefile.am b/scribo/sandbox/green/tools/labeling/opening/Makefile.am
new file mode 100644
index 0000000..f03a836
--- /dev/null
+++ b/scribo/sandbox/green/tools/labeling/opening/Makefile.am
@@ -0,0 +1,153 @@
+#
+# Generic Makefile
+#
+
+#########
+# TOOLS #
+#########
+
+#LOADLIBES= -lboost_filesystem
+INCLUDES1= -I$(HOME)/git/olena/scribo/sandbox/green
+INCLUDES2= -I$(HOME)/git/olena/milena
+INCLUDES= $(INCLUDES1) $(INCLUDES2)
+CXXFLAGS= -ggdb -O0 -Wall -W -pedantic -ansi -pipe $(INCLUDES)
+#CXXFLAGS= -DNDEBUG -O1 -Wall -W -pedantic -ansi -pipe $(INCLUDES)
+#CXXFLAGS= -DNDEBUG -O3 -Wall -W -pedantic -ansi -pipe $(INCLUDES)
+ECHO= echo
+RM= rm
+MKDIR= mkdir -p
+CP= cp
+
+SOURCE_PATTERN= green/tools
+BUILD__PATTERN= green/build/tools
+
+
+ifeq ($(findstring $(BUILD__PATTERN),$(PWD)), $(BUILD__PATTERN))
+# Case where make is done from build directory.
+SOURCE_DIR= $(subst $(BUILD__PATTERN),$(SOURCE_PATTERN),$(PWD))
+BUILD__DIR= $(PWD)/
+else
+# Case where make is done from source directory.
+SOURCE_DIR= $(PWD)/
+BUILD__DIR= $(subst $(SOURCE_PATTERN),$(BUILD__PATTERN),$(PWD))
+endif
+
+SRC= $(notdir $(wildcard $(SOURCE_DIR)/*.cc))
+OLD= $(notdir $(wildcard $(SOURCE_DIR)/*~))
+OBJ= $(patsubst %.cc,%.o,$(SRC))
+SOURCE_MAKEFILE=Makefile.am
+BUILD__MAKEFILE=Makefile
+TARGET_FILE= $(notdir $(PWD))
+SOURCE_FILES= $(notdir $(wildcard $(SOURCE_DIR)/*.*))
+BUILD__FILES= $(filter-out $(SRC) $(SOURCE_MAKEFILE), $(SOURCE_FILES))
+
+BUILD__F_PATH= $(addprefix $(BUILD__DIR)/,$(BUILD__FILES))
+SOURCE_F_PATH= $(addprefix $(SOURCE_DIR)/,$(SOURCE_FILES))
+
+BUILD__M_PATH= $(addprefix $(BUILD__DIR)/,$(BUILD__MAKEFILE))
+SOURCE_M_PATH= $(addprefix $(SOURCE_DIR)/,$(SOURCE_MAKEFILE))
+
+TARGET_F_PATH= $(addprefix $(BUILD__DIR)/,$(TARGET_FILE))
+OBJ_F_PATH= $(addprefix $(BUILD__DIR)/,$(OBJ))
+SRC_F_PATH= $(addprefix $(SOURCE_DIR)/,$(SRC))
+OLD_F_PATH= $(addprefix $(SOURCE_DIR)/,$(OLD))
+
+#############
+# BOOTSTRAP #
+#############
+
+
+bootstrap: $(BUILD__DIR) $(BUILD__F_PATH) $(BUILD__M_PATH)
+
+# Create, if nessary, the destination directory
+$(BUILD__DIR):
+ $(MKDIR) $(BUILD__DIR)
+
+# Copy, if nessary, all the files, except the Makefile.am
+$(BUILD__F_PATH): $(SOURCE_F_PATH)
+ $(CP) $(addprefix $(SOURCE_DIR),$(@F)) $@
+
+# Copy if nessary, the Makefile.am into Makefile
+$(BUILD__M_PATH): $(SOURCE_M_PATH)
+ $(CP) $(SOURCE_M_PATH) $(BUILD__M_PATH)
+
+
+#######
+# ALL #
+#######
+
+# We assume that the call is done from the build directory.
+# With the directive vpath, hidden files are found in the source directory.
+
+all: $(TARGET_F_PATH)
+
+
+$(TARGET_F_PATH): $(OBJ_F_PATH)
+ $(LINK.cc) $< $(LOADLIBES) $(LDLIBS) -o $@
+
+$(OBJ_F_PATH):$(SRC_F_PATH)
+ $(COMPILE.cc) $(OUTPUT_OPTION) $<
+
+
+#########
+# CLEAN #
+#########
+
+# Force every time the deletion
+clean: clean_target clean_obj clean_dst clean_old #clean_make
+
+
+clean_target:
+ -@$(RM) $(TARGET_F_PATH) &> /dev/null
+
+clean_obj:
+ -@$(RM) $(OBJ_F_PATH) &> /dev/null
+
+clean_dst:
+ -@$(RM) $(BUILD_F_PATH) &> /dev/null
+
+clean_make:
+ -@$(RM) $(BUILD_M_PATH) &> /dev/null
+
+clean_old:
+ -@$(RM) $(OLD_F_PATH) &> /dev/null
+
+
+#########
+# PRINT #
+#########
+
+print: print_tools print_bootstrap
+
+print_tools:
+ @$(ECHO) "HOME = $(HOME)"
+ @$(ECHO) "INCLUDES = $(INCLUDES)"
+ @$(ECHO) "CXXFLAGS = $(CXXFLAGS)"
+ @$(ECHO) "ECHO = $(ECHO)"
+ @$(ECHO) "RM = $(RM)"
+ @$(ECHO) "MKDIR = $(MKDIR)"
+ @$(ECHO) "CP = $(CP)"
+ @$(ECHO)
+
+print_bootstrap:
+ @$(ECHO) "PWD = $(PWD)"
+ @$(ECHO) "SOURCE_PATTERN = $(SOURCE_PATTERN)"
+ @$(ECHO) "BUILD__PATTERN = $(BUILD__PATTERN)"
+ @$(ECHO) "SOURCE_DIR = $(SOURCE_DIR)"
+ @$(ECHO) "BUILD__DIR = $(BUILD__DIR)"
+ @$(ECHO) "SOURCE_MAKEFILE = $(SOURCE_MAKEFILE)"
+ @$(ECHO) "BUILD__MAKEFILE = $(BUILD__MAKEFILE)"
+ @$(ECHO) "TARGET_FILE = $(TARGET_FILE)"
+ @$(ECHO) "SOURCE_FILES = $(SOURCE_FILES)"
+ @$(ECHO) "SOURCE_F_PATH = $(SOURCE_F_PATH)"
+ @$(ECHO) "BUILD__FILES = $(BUILD__FILES)"
+ @$(ECHO) "BUILD__F_PATH = $(BUILD__F_PATH)"
+ @$(ECHO) "BUILD__M_PATH = $(BUILD__M_PATH)"
+ @$(ECHO) "SOURCE_M_PATH = $(SOURCE_M_PATH)"
+ @$(ECHO) "SRC = $(SRC)"
+ @$(ECHO) "OBJ = $(OBJ)"
+ @$(ECHO) "OLD = $(OLD)"
+ @$(ECHO) "SRC_F_PATH = $(SRC_F_PATH)"
+ @$(ECHO) "OBJ_F_PATH = $(OBJ_F_PATH)"
+ @$(ECHO) "OLD_F_PATH = $(OLD_F_PATH)"
+ @$(ECHO)
diff --git a/scribo/sandbox/green/tools/labeling/opening/opening.cc b/scribo/sandbox/green/tools/labeling/opening/opening.cc
new file mode 100644
index 0000000..c4f1cb9
--- /dev/null
+++ b/scribo/sandbox/green/tools/labeling/opening/opening.cc
@@ -0,0 +1,174 @@
+// Copyright (C) 2007, 2008, 2009, 2010 EPITA 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.
+
+/// \file
+///
+/// \brief This tool aimed at filtering the previous 3d RGB histogram.
+///
+/// The current filtering is managed with morphological volume attribute.
+///
+/// \fixme I don't know if the volume attribute do well it's
+/// job. Sometimes, there is something strange happened. I know it's
+/// related to that part of processing but i can't tell where it is wrong.
+
+#include <iostream>
+
+#include <mln/accu/stat/histo3d_rgb.hh>
+
+#include <mln/core/macros.hh>
+#include <mln/core/alias/neighb3d.hh>
+#include <mln/core/image/image2d.hh>
+#include <mln/core/image/image3d.hh>
+
+#include <mln/data/compute.hh>
+
+#include <mln/display/display_histo.hh>
+
+#include <mln/io/dump/load.hh>
+#include <mln/io/dump/save.hh>
+#include <mln/io/ppm/save.hh>
+#include <mln/io/pgm/save.hh>
+
+#include <mln/literal/colors.hh>
+
+#include <mln/morpho/opening/volume.hh>
+
+#include <mln/value/rgb.hh>
+#include <mln/value/int_u8.hh>
+
+/// \brief The histogram image processing chain.
+///
+/// \param[in] histo the name of the input histogram to filter.
+/// \param[in] min_vol the minimum volume threshold to leave in the image.
+/// \param[out] opened the name of the filtered histogram.
+/// \param[out] proj1 the red/green projection of the histogram.
+/// \param[out] proj2 the red/green projection with maxima plot on.
+///
+/// This chain aimed at filtering 3d RGB histogram by volume
+/// morphological attribute. The threshold indicates the minimum
+/// volume information to leave, otherwhise information with less
+/// volume attribute is discarded. Then, dumping and
+/// projections are done.
+template <unsigned n>
+void mk_opening(const std::string& histo, // in
+ const unsigned min_vol, // in
+ const std::string& opened, // out
+ const std::string& proj1, // out
+ const std::string& proj2) // out
+{
+ typedef mln::value::int_u8 t_int_u8;
+ typedef mln::value::rgb<n> t_rgbn;
+ typedef mln::image2d<t_int_u8> t_image2d_int_u8;
+ typedef mln::image2d<t_rgbn> t_image2d_rgbn;
+ typedef mln::image3d<unsigned> t_histo3d;
+ typedef mln::accu::meta::stat::histo3d_rgb t_histo3d_fun;
+
+ // START OF IMAGE PROCESSING CHAIN
+ t_histo3d h1_input; // histo input
+ t_histo3d h2_input; // histo input
+ t_image2d_int_u8 p1_histo1;// histo proj1
+ t_image2d_rgbn p1_histo2;// histo proj2
+ t_rgbn red(mln::literal::red);
+
+ mln::io::dump::load(h1_input, histo.c_str());
+ h2_input = mln::morpho::opening::volume(h1_input, mln::c6(), min_vol);
+ // END OF IMAGE PROCESSING CHAIN
+
+ // BEGIN DUMPING
+ p1_histo1 = mln::display::display_histo3d_unsigned(h2_input);
+ p1_histo2 = mln::display::display3_histo3d_unsigned(h2_input, red);
+ mln::io::dump::save(h2_input, opened.c_str());
+ mln::io::pgm::save(p1_histo1, proj1.c_str());
+ mln::io::ppm::save(p1_histo2, proj2.c_str());
+ // END DUMPING
+}
+
+
+/// \brief The online documentation of the tool.
+///
+/// Print the documentation of the tool with the meaning of the
+/// different parameters.
+void usage()
+{
+ std::cout << std::endl;
+ std::cout << "opening q histo.dump v opened.dump proj.pgm"
+ << " proj.ppm" << std::endl;
+ std::cout << std::endl;
+ std::cout << "where :" << std::endl;
+ std::cout << "* [ in] q is the degree of quantification"
+ << " {2,3,4,5,6,7,8}" << std::endl;
+ std::cout << "* [ in] histo.dump is the quantified color"
+ << " histogram" << std::endl;
+ std::cout << "* [ in] v is the minimum size (in pixels) of"
+ << " each composant" << std::endl;
+ std::cout << "* [out] opened.dump is the filtered histogram" << std::endl;
+ std::cout << "* [out] proj.pgm is the r/g projection of the"
+ << " histogram (summing along the blue axe)" << std::endl;
+ std::cout << "* [out] proj.ppm is the r/g projection of the"
+ << " histogram with maxima plot on" << std::endl;
+ std::cout << std::endl;
+}
+
+
+/// \brief The main entry of the software.
+///
+/// \param[in] q the quantification previously used.
+/// \param[in] histo the name of the 3d RGB histogram to filter.
+/// \param[in] min_vol the threshold of the morphological filtering.
+/// \param[out] opened.dump the name of the resulting 3d histogram.
+/// \param[out] proj.pgm the red/green projection of the histogram.
+/// \param[out] proj2.ppm the red/green projection with maxima plot on.
+///
+/// This is the front hand for the image processing routine. The goal of this
+/// chain is to filter 3d histogram for further analysis and to give a way to
+/// see it.
+int main(int argc, char* args[])
+{
+ if (7 == argc)
+ {
+ const char q = args[1][0]; // in
+ const std::string histo(args[2]); // in
+ const unsigned min_vol = atoi(args[3]); // in
+ const std::string opened(args[4]); // out
+ const std::string proj1(args[5]); // out
+ const std::string proj2(args[6]); // out
+
+ switch(q)
+ {
+ case '2': mk_opening<2>(histo, min_vol, opened, proj1, proj2); break;
+ case '3': mk_opening<3>(histo, min_vol, opened, proj1, proj2); break;
+ case '4': mk_opening<4>(histo, min_vol, opened, proj1, proj2); break;
+ case '5': mk_opening<5>(histo, min_vol, opened, proj1, proj2); break;
+ case '6': mk_opening<6>(histo, min_vol, opened, proj1, proj2); break;
+ case '7': mk_opening<7>(histo, min_vol, opened, proj1, proj2); break;
+ case '8': mk_opening<8>(histo, min_vol, opened, proj1, proj2); break;
+ default: usage(); break;
+ }
+ }
+ else
+ usage();
+
+ return 0;
+}
diff --git a/scribo/sandbox/green/tools/labeling/regmax/Makefile.am b/scribo/sandbox/green/tools/labeling/regmax/Makefile.am
new file mode 100644
index 0000000..f03a836
--- /dev/null
+++ b/scribo/sandbox/green/tools/labeling/regmax/Makefile.am
@@ -0,0 +1,153 @@
+#
+# Generic Makefile
+#
+
+#########
+# TOOLS #
+#########
+
+#LOADLIBES= -lboost_filesystem
+INCLUDES1= -I$(HOME)/git/olena/scribo/sandbox/green
+INCLUDES2= -I$(HOME)/git/olena/milena
+INCLUDES= $(INCLUDES1) $(INCLUDES2)
+CXXFLAGS= -ggdb -O0 -Wall -W -pedantic -ansi -pipe $(INCLUDES)
+#CXXFLAGS= -DNDEBUG -O1 -Wall -W -pedantic -ansi -pipe $(INCLUDES)
+#CXXFLAGS= -DNDEBUG -O3 -Wall -W -pedantic -ansi -pipe $(INCLUDES)
+ECHO= echo
+RM= rm
+MKDIR= mkdir -p
+CP= cp
+
+SOURCE_PATTERN= green/tools
+BUILD__PATTERN= green/build/tools
+
+
+ifeq ($(findstring $(BUILD__PATTERN),$(PWD)), $(BUILD__PATTERN))
+# Case where make is done from build directory.
+SOURCE_DIR= $(subst $(BUILD__PATTERN),$(SOURCE_PATTERN),$(PWD))
+BUILD__DIR= $(PWD)/
+else
+# Case where make is done from source directory.
+SOURCE_DIR= $(PWD)/
+BUILD__DIR= $(subst $(SOURCE_PATTERN),$(BUILD__PATTERN),$(PWD))
+endif
+
+SRC= $(notdir $(wildcard $(SOURCE_DIR)/*.cc))
+OLD= $(notdir $(wildcard $(SOURCE_DIR)/*~))
+OBJ= $(patsubst %.cc,%.o,$(SRC))
+SOURCE_MAKEFILE=Makefile.am
+BUILD__MAKEFILE=Makefile
+TARGET_FILE= $(notdir $(PWD))
+SOURCE_FILES= $(notdir $(wildcard $(SOURCE_DIR)/*.*))
+BUILD__FILES= $(filter-out $(SRC) $(SOURCE_MAKEFILE), $(SOURCE_FILES))
+
+BUILD__F_PATH= $(addprefix $(BUILD__DIR)/,$(BUILD__FILES))
+SOURCE_F_PATH= $(addprefix $(SOURCE_DIR)/,$(SOURCE_FILES))
+
+BUILD__M_PATH= $(addprefix $(BUILD__DIR)/,$(BUILD__MAKEFILE))
+SOURCE_M_PATH= $(addprefix $(SOURCE_DIR)/,$(SOURCE_MAKEFILE))
+
+TARGET_F_PATH= $(addprefix $(BUILD__DIR)/,$(TARGET_FILE))
+OBJ_F_PATH= $(addprefix $(BUILD__DIR)/,$(OBJ))
+SRC_F_PATH= $(addprefix $(SOURCE_DIR)/,$(SRC))
+OLD_F_PATH= $(addprefix $(SOURCE_DIR)/,$(OLD))
+
+#############
+# BOOTSTRAP #
+#############
+
+
+bootstrap: $(BUILD__DIR) $(BUILD__F_PATH) $(BUILD__M_PATH)
+
+# Create, if nessary, the destination directory
+$(BUILD__DIR):
+ $(MKDIR) $(BUILD__DIR)
+
+# Copy, if nessary, all the files, except the Makefile.am
+$(BUILD__F_PATH): $(SOURCE_F_PATH)
+ $(CP) $(addprefix $(SOURCE_DIR),$(@F)) $@
+
+# Copy if nessary, the Makefile.am into Makefile
+$(BUILD__M_PATH): $(SOURCE_M_PATH)
+ $(CP) $(SOURCE_M_PATH) $(BUILD__M_PATH)
+
+
+#######
+# ALL #
+#######
+
+# We assume that the call is done from the build directory.
+# With the directive vpath, hidden files are found in the source directory.
+
+all: $(TARGET_F_PATH)
+
+
+$(TARGET_F_PATH): $(OBJ_F_PATH)
+ $(LINK.cc) $< $(LOADLIBES) $(LDLIBS) -o $@
+
+$(OBJ_F_PATH):$(SRC_F_PATH)
+ $(COMPILE.cc) $(OUTPUT_OPTION) $<
+
+
+#########
+# CLEAN #
+#########
+
+# Force every time the deletion
+clean: clean_target clean_obj clean_dst clean_old #clean_make
+
+
+clean_target:
+ -@$(RM) $(TARGET_F_PATH) &> /dev/null
+
+clean_obj:
+ -@$(RM) $(OBJ_F_PATH) &> /dev/null
+
+clean_dst:
+ -@$(RM) $(BUILD_F_PATH) &> /dev/null
+
+clean_make:
+ -@$(RM) $(BUILD_M_PATH) &> /dev/null
+
+clean_old:
+ -@$(RM) $(OLD_F_PATH) &> /dev/null
+
+
+#########
+# PRINT #
+#########
+
+print: print_tools print_bootstrap
+
+print_tools:
+ @$(ECHO) "HOME = $(HOME)"
+ @$(ECHO) "INCLUDES = $(INCLUDES)"
+ @$(ECHO) "CXXFLAGS = $(CXXFLAGS)"
+ @$(ECHO) "ECHO = $(ECHO)"
+ @$(ECHO) "RM = $(RM)"
+ @$(ECHO) "MKDIR = $(MKDIR)"
+ @$(ECHO) "CP = $(CP)"
+ @$(ECHO)
+
+print_bootstrap:
+ @$(ECHO) "PWD = $(PWD)"
+ @$(ECHO) "SOURCE_PATTERN = $(SOURCE_PATTERN)"
+ @$(ECHO) "BUILD__PATTERN = $(BUILD__PATTERN)"
+ @$(ECHO) "SOURCE_DIR = $(SOURCE_DIR)"
+ @$(ECHO) "BUILD__DIR = $(BUILD__DIR)"
+ @$(ECHO) "SOURCE_MAKEFILE = $(SOURCE_MAKEFILE)"
+ @$(ECHO) "BUILD__MAKEFILE = $(BUILD__MAKEFILE)"
+ @$(ECHO) "TARGET_FILE = $(TARGET_FILE)"
+ @$(ECHO) "SOURCE_FILES = $(SOURCE_FILES)"
+ @$(ECHO) "SOURCE_F_PATH = $(SOURCE_F_PATH)"
+ @$(ECHO) "BUILD__FILES = $(BUILD__FILES)"
+ @$(ECHO) "BUILD__F_PATH = $(BUILD__F_PATH)"
+ @$(ECHO) "BUILD__M_PATH = $(BUILD__M_PATH)"
+ @$(ECHO) "SOURCE_M_PATH = $(SOURCE_M_PATH)"
+ @$(ECHO) "SRC = $(SRC)"
+ @$(ECHO) "OBJ = $(OBJ)"
+ @$(ECHO) "OLD = $(OLD)"
+ @$(ECHO) "SRC_F_PATH = $(SRC_F_PATH)"
+ @$(ECHO) "OBJ_F_PATH = $(OBJ_F_PATH)"
+ @$(ECHO) "OLD_F_PATH = $(OLD_F_PATH)"
+ @$(ECHO)
diff --git a/scribo/sandbox/green/tools/labeling/regmax/regmax.cc b/scribo/sandbox/green/tools/labeling/regmax/regmax.cc
new file mode 100644
index 0000000..1fc9976
--- /dev/null
+++ b/scribo/sandbox/green/tools/labeling/regmax/regmax.cc
@@ -0,0 +1,428 @@
+// Copyright (C) 2007, 2008, 2009, 2010 EPITA 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.
+
+/// \file
+///
+/// \brief This tool aimed at segmenting the histogram.
+///
+/// The current segmentation of the histogram is done by finding the
+/// regional maxima. Regional maxima are isolated small regions inside
+/// the background (label 0).
+
+#include <iostream>
+#include <fstream>
+#include <boost/format.hpp>
+
+#include <mln/accu/stat/histo3d_rgb.hh>
+#include <mln/accu/stat/mean.hh>
+
+#include <mln/algebra/vec.hh>
+
+#include <mln/core/macros.hh>
+#include <mln/core/alias/neighb3d.hh>
+#include <mln/core/image/image2d.hh>
+#include <mln/core/image/image3d.hh>
+
+#include <mln/data/compute.hh>
+
+#include <mln/debug/println.hh>
+#include <mln/display/display_histo.hh>
+
+#include <mln/io/dump/load.hh>
+#include <mln/io/dump/save.hh>
+#include <mln/io/pgm/load.hh>
+#include <mln/io/pgm/save.hh>
+#include <mln/io/ppm/load.hh>
+#include <mln/io/ppm/save.hh>
+
+#include <mln/labeling/regional_maxima.hh>
+#include <mln/labeling/compute.hh>
+#include <mln/labeling/mean_values.hh>
+
+#include <mln/literal/colors.hh>
+
+#include <mln/morpho/opening/volume.hh>
+
+#include <mln/value/label_8.hh>
+#include <mln/value/int_u8.hh>
+#include <mln/value/rgb8.hh>
+
+#include <mln/util/array.hh>
+
+/// \ brief Compute the 2d labeled image.
+///
+/// Compute the 2d labeled image with the 2d labeled histogram and
+/// the input image.
+///
+/// \fixme Need to put it in mln library. Nothing to do here.
+template <unsigned n>
+struct t_labeling_rgbn : mln::Function_v2v< t_labeling_rgbn<n> >
+{
+ typedef mln::value::rgb<n> t_rgbn;
+ typedef mln::value::label_8 t_lbl8;
+ typedef t_rgbn argument;
+ typedef t_lbl8 result;
+ typedef mln::image3d<t_lbl8> t_label;
+
+ const t_label& _label;
+
+ t_labeling_rgbn(const t_label& label) : _label(label) {}
+
+ result operator()(const argument& c) const
+ {
+ t_lbl8 tmp = mln::opt::at(_label, c.blue(), c.red(), c.green());
+
+ return tmp;
+ }
+};
+
+
+/// \brief Compute and dump stats.
+///
+/// \param[in] i_input_rgb8 the 2d rgb input image.
+/// \param[in] l_input_lbl8 the 2d labeled image.
+/// \param[in] h_histo_rgbn the quantified histogram.
+/// \param[in] l_histo_lbl8 the labeled quantified histogram.
+/// \param[in] n_labels the number of labels (number of regions).
+/// \param[in] the name of the logging file for the stats.
+///
+/// Every segmented color has got it's own label. For each label, we
+/// compute the mean in the r/g/b channels, the total of pixels, the
+/// percentage of pixels in the image and the percentage without counting
+/// the background (label 0).
+void compute_stats(const mln::image2d<mln::value::rgb8>& i_input_rgb8,
+ const mln::image2d<mln::value::label_8>& l_input_lbl8,
+ const mln::image3d<unsigned>& h_histo_rgbn,
+ const mln::image3d<mln::value::label_8>& l_histo_lbl8,
+ const mln::value::label_8& n_labels,
+ const std::string& log)
+{
+ typedef mln::algebra::vec<3,float> t_vec3f;
+ typedef mln::accu::math::sum<unsigned,unsigned> t_sum;
+ typedef mln::accu::stat::mean<t_vec3f,t_vec3f,t_vec3f> t_mean;
+ typedef mln::util::array<unsigned> t_count_array;
+ typedef mln::util::array<t_vec3f> t_mean_array;
+
+ mln::util::array<float> abs((unsigned)(n_labels)+1);
+ mln::util::array<float> rel((unsigned)(n_labels)+1);
+ unsigned nb = 0;
+
+ for (unsigned i = 0; i <= n_labels; ++i)
+ {
+ abs[i] = 0.0;
+ rel[i] = 0.0;
+ }
+
+ // COMPUTE THE SUM
+ t_count_array count = mln::labeling::compute(t_sum(),
+ h_histo_rgbn,
+ l_histo_lbl8,
+ n_labels);
+
+ // COMPUTE THE TOTAL
+ for (unsigned i = 0; i <= n_labels; ++i)
+ {
+ unsigned c = count[i];
+ nb += c;
+ }
+
+ // COMPUTE THE PERCENTAGES
+ for (unsigned i = 0; i <= n_labels; ++i)
+ if (0 < count[i])
+ {
+ abs[i] = ((float)count[i] / nb)*100.0;
+ rel[i] = ((float)count[i] / (nb - count[0]))*100.0;
+ }
+
+ // COMPUTE THE MEAN
+
+ t_mean_array mean = mln::labeling::compute(t_mean(),
+ i_input_rgb8,
+ l_input_lbl8,
+ n_labels);
+
+ // CORRECT 0 LABEL STATS
+ rel[0] = 0;
+ mean[0][0] = 255.0;
+ mean[0][1] = 255.0;
+ mean[0][2] = 0.0;
+
+ // PRINT STATS
+ std::ofstream log_stream(log.c_str());
+
+ for (unsigned i = 0; i <= n_labels; ++i)
+ {
+ const t_vec3f& mean_v = mean[i];
+
+ log_stream << boost::format("%2i|"
+ "r = %6.2f, g = %6.2f, b = %6.2f |"
+ "c = %7i, %%i = %5.2f, %%c = %5.2f")
+ % i
+ % mean_v[0]
+ % mean_v[1]
+ % mean_v[2]
+ % count[i]
+ % abs[i]
+ % rel[i]
+ << std::endl;
+ }
+
+ log_stream << std::endl << std::endl;
+ log_stream.flush();
+ log_stream.close();
+}
+
+
+
+/// \brief Dump the colormap.
+///
+/// \param[in] m2_label the internal representation of the colormap.
+/// \param[in] colormap the name of the colormap in the filesystem.
+///
+/// Take an dynamic array of 3d vector which represents the colormap.
+/// Use boost formatting to dump it properly.
+void save(mln::util::array< mln::algebra::vec<3,float> >& m2_label,
+ const char *colormap)
+{
+ typedef mln::algebra::vec<3,float> t_vec3f;
+ typedef mln::util::array<t_vec3f> t_mean_array;
+
+ std::ofstream stream(colormap);
+
+ for (unsigned i = 0; i < m2_label.size(); ++i)
+ {
+ const t_vec3f& mean_v = m2_label[i];
+
+ stream << boost::format("%2i | r = %6.2f, g = %6.2f, b = %6.2f")
+ % i
+ % mean_v[0]
+ % mean_v[1]
+ % mean_v[2]
+ << std::endl;
+ }
+
+ stream.flush();
+ stream.close();
+}
+
+
+/// \brief The regmax image processing chain.
+///
+/// \param[in] input the name of the RGB input image.
+/// \param[in] quant the name of quantified RGB input image.
+/// \param[in] histo the name of the 3d RGB histogram to filter.
+/// \param[in] opened the name of 3d histogram.
+/// \param[in] nbh the neighbouring (c6|c18|c26).
+/// \param[out] labeled the 3d labeled histogram.
+/// \param[out] proj the red/green projection of the segmented histogram.
+/// \param[out] colormap the name of the colormap produced.
+/// \param[out] mean the name of the mean rebuilded image.
+/// \param[out] stats the name of the statistics (optional).
+///
+/// This is the core routine of this file. First every input file
+/// (images or histograms) are loaded. Then regional labeling is
+/// done. And finally, every colormap dumping, stats saving,
+/// projection is done.
+template <unsigned n>
+void mk_regmax(const std::string& input, // in
+ const std::string& quant, // in
+ const std::string& histo, // in
+ const std::string& opened, // in
+ const mln::neighb3d& nbh, // in
+ const std::string& labeled, // out
+ const std::string& proj, // out
+ const std::string& colormap,// out
+ const std::string& mean, // out
+ const std::string& stats) // [out]
+{
+ typedef mln::value::label_8 t_lbl8;
+ typedef mln::value::rgb8 t_rgb8;
+ typedef mln::value::rgb<n> t_rgbn;
+ typedef mln::value::int_u8 t_int_u8;
+ typedef mln::value::int_u<n> t_int_un;
+ typedef mln::algebra::vec<3,float> t_v3f;
+ typedef mln::image2d<t_int_u8> t_image2d_int_u8;
+ typedef mln::image2d<t_int_un> t_image2d_int_un;
+ typedef mln::image2d<t_rgb8> t_image2d_rgb8;
+ typedef mln::image2d<t_rgbn> t_image2d_rgbn;
+ typedef mln::image3d<t_lbl8> t_image3d_lbl8;
+ typedef mln::image2d<t_lbl8> t_image2d_lbl8;
+ typedef mln::image3d<unsigned> t_histo3d;
+ typedef mln::accu::meta::stat::histo3d_rgb t_histo3d_fun;
+ typedef mln::accu::stat::mean<t_v3f,t_v3f,t_v3f> t_mean;
+ typedef mln::util::array<t_v3f> t_mean_array;
+
+ t_image2d_rgb8 i0_input; // input img
+ t_image2d_rgbn i1_input; // quant img
+ t_histo3d h1_input; // input histo
+ t_histo3d h2_input; // opened histo
+ t_image2d_rgb8 p2_label; // histo proj
+ t_image3d_lbl8 l2_histo; // label histo
+ t_image2d_lbl8 l2_input; // label input
+ t_mean_array m2_label; // colormap
+ t_image2d_rgb8 i2_mean; // reconstructed
+
+ t_lbl8 n_lbl; // nb class
+ t_rgb8 red(mln::literal::red);
+
+
+ // BEGIN LOADING
+ mln::io::ppm::load(i0_input, input.c_str());
+ mln::io::ppm::load(i1_input, quant.c_str());
+ mln::io::dump::load(h1_input, histo.c_str());
+ mln::io::dump::load(h2_input, opened.c_str());
+ // END LOADING
+
+ // BEGIN IMAGE PROCESSING
+ l2_histo = mln::labeling::regional_maxima(h2_input, nbh, n_lbl);
+ // END IMAGE PROCESSING
+
+ // BEGIN SAVING
+ mln::io::dump::save(l2_histo, labeled.c_str());
+
+ l2_input = mln::data::transform(i1_input, t_labeling_rgbn<n>(l2_histo));
+ i2_mean = mln::labeling::mean_values(i0_input, l2_input, n_lbl);
+ m2_label = mln::labeling::compute(t_mean(), i0_input, l2_input, n_lbl);
+
+ // CORRECT 0 LABEL STATS
+ m2_label[0][0] = 255.0;
+ m2_label[0][1] = 255.0;
+ m2_label[0][2] = 0.0;
+
+ p2_label =mln::display::display3_histo3d_unsigned<n>(h1_input,
+ l2_histo,
+ m2_label,
+ red);
+
+ mln::io::ppm::save(p2_label, proj.c_str());
+ save(m2_label, colormap.c_str());
+ mln::io::ppm::save(i2_mean, mean.c_str());
+
+ if (0 < stats.size())
+ compute_stats(i0_input, l2_input, h1_input, l2_histo, n_lbl, stats);
+
+ // END SAVING
+}
+
+
+/// \brief The online documentation of the tool.
+///
+/// Print the documentation of the tool with the meaning of the
+/// different parameters.
+void usage()
+{
+ std::cout << std::endl;
+ std::cout << "regmax input.ppm q quant.ppm histo.dump"
+ << " opened.dump nbh labeled.dump proj.ppm"
+ << " colormap.txt mean.ppm [stats.txt]" << std::endl;
+ std::cout << std::endl;
+ std::cout << "where :" << std::endl;
+ std::cout << "* [ in] input.ppm is the 8 bits color ppm image" << std::endl;
+ std::cout << "* [ in] q is the degree of quantification"
+ << " {2,3,4,5,6,7,8}" << std::endl;
+ std::cout << "* [ in] quant.ppm is the q bits quantified input"
+ << " image" << std::endl;
+ std::cout << "* [ in] histo.dump is the quantified color"
+ << " histogram" << std::endl;
+ std::cout << "* [ in] opened.dump is the filtered histogram" << std::endl;
+ std::cout << "* [ in] nbh is the 3d neighbourhood {6,18,26}" << std::endl;
+ std::cout << "* [out] labeled.dump is the labeled 3d histogram" << std::endl;
+ std::cout << "* [out] proj.ppm is the r/g projection of the"
+ << " histogram with maxima label plot on" << std::endl;
+ std::cout << "* [out] colormap.txt is the colormap for labels" << std::endl;
+ std::cout << "* [out] mean.ppm is the mean reconstructed image" << std::endl;
+ std::cout << "* [out] stats.txt is the statistical label report"<< std::endl;
+ std::cout << std::endl;
+}
+
+
+/// \brief The main entry of the software.
+///
+/// \param[in] input.ppm the name of the RGB input image.
+/// \param[in] q the quantification previously used.
+/// \param[in] quant.ppm the name of quantified RGB input image.
+/// \param[in] histo.dump the name of the 3d RGB histogram to filter.
+/// \param[in] opened.dump the name of 3d histogram.
+/// \param[in] nbh the code for the neighbouring (6|18|26).
+/// \param[out] labeled.dump the 3d labeled histogram.
+/// \param[out] proj.ppm the red/green projection of the segmented histogram.
+/// \param[out] colormap.txt the name of the colormap produced.
+/// \param[out] mean.ppm the name of the mean rebuilded image.
+/// \param[out] stats.txt the name of the statistics file (optional).
+///
+/// This is the front hand for the image processing routine. The goal of this
+/// chain is to segment the 3d histogram.
+int main(int argc, char* args[])
+{
+ if (11 == argc || 12 == argc)
+ {
+ const std::string input(args[1]); // in
+ const char q = args[2][0]; // in
+ const std::string quant(args[3]); // in
+ const std::string histo(args[4]); // in
+ const std::string opened(args[5]); // in
+ const char nbh = args[6][0]; // in
+ const std::string labeled(args[7]); // out
+ const std::string proj(args[8]); // out
+ const std::string colormap(args[9]);// out
+ const std::string mean(args[10]); // out
+ const std::string stats(12 == argc? args[11] : ""); // [out]
+
+
+ mln::neighb3d neighbourhood;
+
+ switch (nbh)
+ {
+ case '6': neighbourhood = mln::c6(); break;
+ case '1': neighbourhood = mln::c18(); break;
+ case '2': neighbourhood = mln::c26(); break;
+ default: usage(); return 0; // force usage and quit
+ }
+
+ switch (q)
+ {
+
+ case '2': mk_regmax<2>(input,quant,histo,opened,neighbourhood,
+ labeled,proj,colormap,mean,stats); break;
+ case '3': mk_regmax<3>(input,quant,histo,opened,neighbourhood,
+ labeled,proj,colormap,mean,stats); break;
+ case '4': mk_regmax<4>(input,quant,histo,opened,neighbourhood,
+ labeled,proj,colormap,mean,stats); break;
+ case '5': mk_regmax<5>(input,quant,histo,opened,neighbourhood,
+ labeled,proj,colormap,mean,stats); break;
+ case '6': mk_regmax<6>(input,quant,histo,opened,neighbourhood,
+ labeled,proj,colormap,mean,stats); break;
+ case '7': mk_regmax<7>(input,quant,histo,opened,neighbourhood,
+ labeled,proj,colormap,mean,stats); break;
+ case '8': mk_regmax<8>(input,quant,histo,opened,neighbourhood,
+ labeled,proj,colormap,mean,stats); break;
+ default: usage(); break;
+ }
+ }
+ else
+ usage();
+
+ return 0;
+}
diff --git a/scribo/sandbox/green/use/accu/stat/histo1d/Makefile.am b/scribo/sandbox/green/use/display/display_histo/Makefile.am
similarity index 100%
copy from scribo/sandbox/green/use/accu/stat/histo1d/Makefile.am
copy to scribo/sandbox/green/use/display/display_histo/Makefile.am
diff --git a/scribo/sandbox/green/use/display/display_histo/display_histo.cc b/scribo/sandbox/green/use/display/display_histo/display_histo.cc
new file mode 100644
index 0000000..090b609
--- /dev/null
+++ b/scribo/sandbox/green/use/display/display_histo/display_histo.cc
@@ -0,0 +1,86 @@
+// 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.
+
+/// \file
+///
+/// \brief Sample code to use the red/green visualization.
+///
+/// \fixme There is a lot of routines in display_histo.hh, but only
+/// two of them have been call here. It's a poor job from me, but i've
+/// the time to do it know.
+
+#include <iostream>
+#include <mln/accu/stat/histo3d_rgb.hh>
+#include <mln/core/macros.hh>
+#include <mln/core/image/image2d.hh>
+#include <mln/core/image/image3d.hh>
+#include <mln/data/compute.hh>
+#include <mln/data/transform.hh>
+#include <mln/display/display_histo.hh>
+#include <mln/fun/v2v/rgb8_to_rgbn.hh>
+#include <mln/img_path.hh>
+#include <mln/io/ppm/load.hh>
+#include <mln/io/pgm/save.hh>
+#include <mln/io/ppm/save.hh>
+#include <mln/literal/colors.hh>
+#include <mln/value/rgb8.hh>
+#include <mln/value/rgb.hh>
+
+int main()
+{
+ typedef mln::value::int_u8 t_int_u8;
+ typedef mln::value::int_u<4> t_int_u4;
+ typedef mln::value::rgb8 t_rgb8;
+ typedef mln::value::rgb<4> t_rgb4;
+ typedef mln::image2d<t_int_u8> t_image2d_int_u8;
+ typedef mln::image2d<t_int_u4> t_image2d_int_u4;
+ typedef mln::image2d<t_rgb8> t_image2d_rgb8;
+ typedef mln::image2d<t_rgb4> t_image2d_rgb4;
+ typedef mln::image2d<bool> t_image2d_bool;
+ typedef mln::image3d<unsigned> t_histo3d;
+ typedef mln::fun::v2v::rgb8_to_rgbn<4> t_rgb8_to_rgb4;
+ typedef mln::accu::meta::stat::histo3d_rgb t_histo3d_fun;
+
+ t_image2d_rgb8 i0_input; // input rgb8
+ t_image2d_rgb4 i1_input; // input rgbn
+ t_histo3d h1_input; // histo input
+ t_image2d_int_u8 p1_histo1;// histo proj1
+ t_image2d_rgb4 p1_histo2;// histo proj2
+ t_rgb4 red(mln::literal::red);
+
+ mln::io::ppm::load(i0_input, OLENA_IMG_PATH"/lena.ppm");
+
+ i1_input = mln::data::transform(i0_input, t_rgb8_to_rgb4());
+ h1_input = mln::data::compute(t_histo3d_fun(), i1_input);
+ p1_histo1 = mln::display::display_histo3d_unsigned(h1_input);
+ p1_histo2 = mln::display::display3_histo3d_unsigned(h1_input, red);
+
+ mln::io::pgm::save(p1_histo1, "proj1.pgm");
+ mln::io::ppm::save(p1_histo2, "proj2.ppm");
+
+ return 0;
+}
--
1.5.6.5
14Â years, 2Â months
- 1
- 0
last-svn-commit-47-g175ec2f Import regional maxima sources from milena green's sandbox.
by Guillaume Lazzara
* README.green: Update documentation.
Implement a primary demonstrator with watershed labeling.
* demo/labeling/watershed: New directory.
* demo/labeling/watershed/Makefile.am: New makefile.
* demo/labeling/watershed/watershed.cc: New demo source.
* demo/labeling/watershed/gaussian.sh: New calibrate tools.
Implement a secondary demonstrator with regional maxima labeling.
* demo/labeling/regional_maxima: New directory.
* demo/labeling/regional_maxima/Makefile.am: New makefile.
* demo/labeling/regional_maxima/regional_maxima.cc: New demo source.
* demo/labeling/regional_maxima/threshold.txt: New threshold map file.
Implement the same demonstrator with directory scanning.
* exp/labeling/regional_maxima: New directory.
* exp/labeling/regional_maxima/Makefile.am: New makefile.
* exp/labeling/regional_maxima/regional_maxima.cc: New demo source.
* exp/labeling/regional_maxima/threshold.txt: New threshold map file.
Implement r/g projection.
* mln/display: New directory.
* mln/display/display_histo.hh: New library file.
* mln/display/project_histo.hh: New library file.
Give minimal code for using r/w projection.
* use/display/display_histo: New directory.
* use/display/display_histo/Makefile.am: New Makefile.
* use/display/display_histo/display_histo.cc: New source.
Divide the secondary demonstrator in four binaries in order to test it.
Implement the quantified RGB histogram.
* tools/labeling/histo: New directory.
* tools/labeling/histo/Makefile.am: new makefile.
* tools/labeling/histo/histo.cc: New source.
Filter the quantified RGB histogram by morphological volume attribute.
* tools/labeling/opening: New directory.
* tools/labeling/opening/Makefile.am: New makfile.
* tools/labeling/opening/opening.cc: New source.
Labeling the resulting histogram.
* tools/labeling/regmax: New directory.
* tools/labeling/regmax/Makefile: New directory.
* tools/labeling/regmax/regmax.cc: New source.
Propagate labels in the labeling histogram.
* tools/labeling/iz: New directory.
* tools/labeling/iz/Makefile: New directory.
* tools/labeling/iz/iz.cc: New source.
Import documentation directory.
* doc: New directory.
Import annotating search notes.
* doc/annotating/class.txt: New documentation text file.
* doc/annotating/syntheseMillet.txt: New documentation text file.
* doc/annotating/testMillet2008: New documentation text file.
Import milena learning examples.
* doc/examples: New directory.
* doc/examples/hello_world: New directory.
* doc/examples/hello_world/Makefile.am: New makefile.
* doc/examples/hello_world/hellow_world.cc: New source file.
* doc/examples/hello_world/print.cc: New source file.
* doc/examples/hello_milena: New directory.
* doc/examples/hello_milena/Makefile.am: New makefile.
* doc/examples/hello_milena/hello_milena.cc: New source file.
* doc/examples/learn_milena: New directory.
* doc/examples/learn_milena/Makefile.am: New makefile.
* doc/examples/learn_milena/learn_milena.cc: New source file.
* doc/examples/otsu: New directory.
* doc/examples/otsu/Makefile.am: New makefile.
* doc/examples/otsu/otsu.cc: New source file.
* doc/examples/frac: New directory.
* doc/examples/frac/Makefile.am: New makefile.
* doc/examples/frac/frac.cc: New source file.
* doc/examples/frac/frac.hh: New source file.
* doc/examples/frac/sign_prod.hh: New source file.
* doc/examples/frac/gcd.hh: New source file.
* doc/examples/accu_color: New directory.
* doc/examples/accu_color/accu_color.cc: New source file.
* doc/examples/io: New directory.
* doc/examples/io/Makefile.am: New makefile.
* doc/examples/io/io.cc: New source file.
Write down the basis of the quick tour summary documentation.
* doc/quick_tour: New specific directory.
* doc/quick_tour/quick_tour.tex: New documentation work.
Write down 3d currently used formulaes.
* doc/formulae: New specific directory.
* doc/formulae/formulae.tex: New recipe of 3d formulae.
---
scribo/sandbox/green/ChangeLog | 1083 ++++++++++++++++++++
scribo/sandbox/green/README.green | 346 ++++++-
.../regional_maxima}/Makefile.am | 0
.../labeling/regional_maxima/regional_maxima.cc | 198 ++++
.../demo/labeling/regional_maxima/thresholds.txt | 0
.../kmean1d => labeling/watershed}/Makefile.am | 0
.../green/demo/labeling/watershed}/gaussian.sh | 0
.../green/demo/labeling/watershed/watershed.cc | 360 +++++++
.../sandbox/green/doc/annotating/class.txt | 0
.../green/doc/annotating/syntheseMillet2008.txt | 0
.../sandbox/green/doc/annotating/testMillet2008 | 0
.../green/doc/examples/accu_color/accu_color.cc | 0
.../sandbox/green/doc/examples/frac/Makefile.am | 0
.../sandbox/green/doc/examples/frac/frac.cc | 0
.../sandbox/green/doc/examples/frac/frac.hh | 0
.../sandbox/green/doc/examples/frac/gcd.hh | 0
.../sandbox/green/doc/examples/frac/sign_prod.hh | 0
.../green/doc/examples/hello_milena/Makefile.am | 0
.../doc/examples/hello_milena/hello_milena.cc | 0
.../green/doc/examples/hello_world}/Makefile.am | 0
.../green/doc/examples/hello_world/hello_world.cc | 0
.../green/doc/examples/hello_world/print.cc | 0
.../sandbox/green/doc/examples/io/Makefile.am | 0
.../sandbox/green/doc/examples/io/io.cc | 0
.../green/doc/examples/learn_milena}/Makefile.am | 0
.../doc/examples/learn_milena/learn_milena.cc | 0
.../sandbox/green/doc/examples/otsu}/Makefile.am | 0
.../sandbox/green/doc/examples/otsu/otsu.cc | 0
.../sandbox/green/doc/examples/stats}/Makefile.am | 0
.../sandbox/green/doc/examples/stats/stats.cc | 0
.../sandbox/green/doc/formulae/formulae.tex | 0
.../sandbox/green/doc/quick_tour/quick_tour.tex | 0
.../sandbox/green/exp/regional_maxima/Makefile.am | 153 +++
.../green/exp/regional_maxima/regional_maxima.cc | 196 ++++
.../green/exp}/regional_maxima/thresholds.txt | 0
scribo/sandbox/green/mln/display/display_histo.hh | 149 +++-
scribo/sandbox/green/mln/display/project_histo.hh | 178 +++-
.../sandbox/green/tools/labeling/histo/Makefile.am | 153 +++
scribo/sandbox/green/tools/labeling/histo/histo.cc | 204 ++++
scribo/sandbox/green/tools/labeling/iz/Makefile.am | 153 +++
scribo/sandbox/green/tools/labeling/iz/iz.cc | 495 +++++++++
.../green/tools/labeling/opening/Makefile.am | 153 +++
.../green/tools/labeling/opening/opening.cc | 174 ++++
.../green/tools/labeling/regmax/Makefile.am | 153 +++
.../sandbox/green/tools/labeling/regmax/regmax.cc | 428 ++++++++
.../histo1d => display/display_histo}/Makefile.am | 0
.../use/display/display_histo/display_histo.cc | 86 ++
47 files changed, 4614 insertions(+), 48 deletions(-)
copy scribo/sandbox/green/demo/{clustering/kmean1d => labeling/regional_maxima}/Makefile.am (100%)
create mode 100644 scribo/sandbox/green/demo/labeling/regional_maxima/regional_maxima.cc
copy {milena => scribo}/sandbox/green/demo/labeling/regional_maxima/thresholds.txt (100%)
copy scribo/sandbox/green/demo/{clustering/kmean1d => labeling/watershed}/Makefile.am (100%)
copy {milena/sandbox/green/tests/accu/stat/histo1d => scribo/sandbox/green/demo/labeling/watershed}/gaussian.sh (100%)
create mode 100644 scribo/sandbox/green/demo/labeling/watershed/watershed.cc
copy {milena => scribo}/sandbox/green/doc/annotating/class.txt (100%)
copy {milena => scribo}/sandbox/green/doc/annotating/syntheseMillet2008.txt (100%)
copy {milena => scribo}/sandbox/green/doc/annotating/testMillet2008 (100%)
copy {milena => scribo}/sandbox/green/doc/examples/accu_color/accu_color.cc (100%)
copy {milena => scribo}/sandbox/green/doc/examples/frac/Makefile.am (100%)
copy {milena => scribo}/sandbox/green/doc/examples/frac/frac.cc (100%)
copy {milena => scribo}/sandbox/green/doc/examples/frac/frac.hh (100%)
copy {milena => scribo}/sandbox/green/doc/examples/frac/gcd.hh (100%)
copy {milena => scribo}/sandbox/green/doc/examples/frac/sign_prod.hh (100%)
copy {milena => scribo}/sandbox/green/doc/examples/hello_milena/Makefile.am (100%)
copy {milena => scribo}/sandbox/green/doc/examples/hello_milena/hello_milena.cc (100%)
copy {milena/sandbox/green/doc/examples/hello_milena => scribo/sandbox/green/doc/examples/hello_world}/Makefile.am (100%)
copy {milena => scribo}/sandbox/green/doc/examples/hello_world/hello_world.cc (100%)
copy {milena => scribo}/sandbox/green/doc/examples/hello_world/print.cc (100%)
copy {milena => scribo}/sandbox/green/doc/examples/io/Makefile.am (100%)
copy {milena => scribo}/sandbox/green/doc/examples/io/io.cc (100%)
copy {milena/sandbox/green/doc/examples/hello_milena => scribo/sandbox/green/doc/examples/learn_milena}/Makefile.am (100%)
copy {milena => scribo}/sandbox/green/doc/examples/learn_milena/learn_milena.cc (100%)
copy {milena/sandbox/green/doc/examples/hello_milena => scribo/sandbox/green/doc/examples/otsu}/Makefile.am (100%)
copy {milena => scribo}/sandbox/green/doc/examples/otsu/otsu.cc (100%)
copy {milena/sandbox/green/doc/examples/hello_milena => scribo/sandbox/green/doc/examples/stats}/Makefile.am (100%)
copy {milena => scribo}/sandbox/green/doc/examples/stats/stats.cc (100%)
copy {milena => scribo}/sandbox/green/doc/formulae/formulae.tex (100%)
copy {milena => scribo}/sandbox/green/doc/quick_tour/quick_tour.tex (100%)
create mode 100644 scribo/sandbox/green/exp/regional_maxima/Makefile.am
create mode 100644 scribo/sandbox/green/exp/regional_maxima/regional_maxima.cc
copy {milena/sandbox/green/demo/labeling => scribo/sandbox/green/exp}/regional_maxima/thresholds.txt (100%)
create mode 100644 scribo/sandbox/green/tools/labeling/histo/Makefile.am
create mode 100644 scribo/sandbox/green/tools/labeling/histo/histo.cc
create mode 100644 scribo/sandbox/green/tools/labeling/iz/Makefile.am
create mode 100644 scribo/sandbox/green/tools/labeling/iz/iz.cc
create mode 100644 scribo/sandbox/green/tools/labeling/opening/Makefile.am
create mode 100644 scribo/sandbox/green/tools/labeling/opening/opening.cc
create mode 100644 scribo/sandbox/green/tools/labeling/regmax/Makefile.am
create mode 100644 scribo/sandbox/green/tools/labeling/regmax/regmax.cc
copy scribo/sandbox/green/use/{accu/stat/histo1d => display/display_histo}/Makefile.am (100%)
create mode 100644 scribo/sandbox/green/use/display/display_histo/display_histo.cc
diff --git a/scribo/sandbox/green/ChangeLog b/scribo/sandbox/green/ChangeLog
index 9e9b7d6..5e4cb27 100644
--- a/scribo/sandbox/green/ChangeLog
+++ b/scribo/sandbox/green/ChangeLog
@@ -1,3 +1,1086 @@
+2010-07-07 Yann Jacquelet <jacquelet(a)lrde.epita.fr>
+
+ Import regional maxima sources from milena green's sandbox.
+
+ * README.green: Update documentation.
+
+ Implement a primary demonstrator with watershed labeling.
+
+ * demo/labeling/watershed: New directory.
+ * demo/labeling/watershed/Makefile.am: New makefile.
+ * demo/labeling/watershed/watershed.cc: New demo source.
+ * demo/labeling/watershed/gaussian.sh: New calibrate tools.
+
+ Implement a secondary demonstrator with regional maxima labeling.
+
+ * demo/labeling/regional_maxima: New directory.
+ * demo/labeling/regional_maxima/Makefile.am: New makefile.
+ * demo/labeling/regional_maxima/regional_maxima.cc: New demo source.
+ * demo/labeling/regional_maxima/threshold.txt: New threshold map file.
+
+ Implement the same demonstrator with directory scanning.
+
+ * exp/labeling/regional_maxima: New directory.
+ * exp/labeling/regional_maxima/Makefile.am: New makefile.
+ * exp/labeling/regional_maxima/regional_maxima.cc: New demo source.
+ * exp/labeling/regional_maxima/threshold.txt: New threshold map file.
+
+ Implement r/g projection.
+
+ * mln/display: New directory.
+ * mln/display/display_histo.hh: New library file.
+ * mln/display/project_histo.hh: New library file.
+
+ Give minimal code for using r/w projection.
+
+ * use/display/display_histo: New directory.
+ * use/display/display_histo/Makefile.am: New Makefile.
+ * use/display/display_histo/display_histo.cc: New source.
+
+ Divide the secondary demonstrator in four binaries in order to test it.
+
+ Implement the quantified RGB histogram.
+
+ * tools/labeling/histo: New directory.
+ * tools/labeling/histo/Makefile.am: new makefile.
+ * tools/labeling/histo/histo.cc: New source.
+
+ Filter the quantified RGB histogram by morphological volume attribute.
+
+ * tools/labeling/opening: New directory.
+ * tools/labeling/opening/Makefile.am: New makfile.
+ * tools/labeling/opening/opening.cc: New source.
+
+ Labeling the resulting histogram.
+
+ * tools/labeling/regmax: New directory.
+ * tools/labeling/regmax/Makefile: New directory.
+ * tools/labeling/regmax/regmax.cc: New source.
+
+ Propagate labels in the labeling histogram.
+
+ * tools/labeling/iz: New directory.
+ * tools/labeling/iz/Makefile: New directory.
+ * tools/labeling/iz/iz.cc: New source.
+
+ Import documentation directory.
+
+ * doc: New directory.
+
+ Import experimentation backups.
+
+ * doc/labeling: New directory.
+
+ * doc/labeling/cmp_methode: New directory.
+ * doc/labeling/cmp_method/h0_input.pgm.gz: New img file.
+ * doc/labeling/cmp_method/h2_mean.pgm.gz: New img file.
+ * doc/labeling/cmp_method/h2_merge.pgm.gz: New img file.
+ * doc/labeling/cmp_method/h3_mean.pgm.gz: New img file.
+ * doc/labeling/cmp_method/h3_merge.pgm.gz: New img file.
+ * doc/labeling/cmp_method/h4_mean.pgm.gz: New img file.
+ * doc/labeling/cmp_method/h4_merge.pgm.gz: New img file
+ * doc/labeling/cmp_method/h5_mean.pgm.gz: New img file.
+ * doc/labeling/cmp_method/h5_merge.pgm.gz: New img file.
+ * doc/labeling/cmp_method/i2_mean.ppm.gz: New img file.
+ * doc/labeling/cmp_method/i2_merge.ppm.gz: New img file.
+ * doc/labeling/cmp_method/i3_mean.ppm.gz: New img file.
+ * doc/labeling/cmp_method/i3_merge.ppm.gz: New img file.
+ * doc/labeling/cmp_method/i4_mean.ppm.gz: New img file.
+ * doc/labeling/cmp_method/i4_merge.ppm.gz: New img file
+ * doc/labeling/cmp_method/i5_mean.ppm.gz: New img file.
+ * doc/labeling/cmp_method/i5_merge.ppm.gz: New img file.
+ * doc/labeling/cmp_method/l2_input.pgm.gz: New img file.
+ * doc/labeling/cmp_method/l3_input.pgm.gz: New img file.
+ * doc/labeling/cmp_method/l4_input.pgm.gz: New img file.
+ * doc/labeling/cmp_method/l5_input.pgm.gz: New img file.
+ * doc/labeling/cmp_method/s2_histo.txt.gz: New txt file.
+ * doc/labeling/cmp_method/s3_histo.txt.gz: New txt file.
+ * doc/labeling/cmp_method/s4_histo.txt.gz: New txt file.
+ * doc/labeling/cmp_method/s5_histo.txt.gz: New txt file.
+ * doc/labeling/cmp_method/reponse_theo.eml.gz: New email.
+ * doc/labeling/cmp_method/synthese.txt.gz: New experiment doc.
+
+ * doc/labeling/cmp_quant: New directory.
+ * doc/labeling/cmp_quant/h0_input.pgm.gz: New img file.
+ * doc/labeling/cmp_quant/h5_mean_q2.pgm.gz: New img file.
+ * doc/labeling/cmp_quant/h5_mean_q3.pgm.gz: New img file.
+ * doc/labeling/cmp_quant/h5_mean_q4.pgm.gz: New img file.
+ * doc/labeling/cmp_quant/h5_mean_q5.pgm.gz: New img file.
+ * doc/labeling/cmp_quant/h5_mean_q6.pgm.gz: New img file.
+ * doc/labeling/cmp_quant/h5_mean_q7.pgm.gz: New img file.
+ * doc/labeling/cmp_quant/h5_mean_q8.pgm.gz: New img file.
+ * doc/labeling/cmp_quant/h5_merge_q2.pgm.gz: New img file.
+ * doc/labeling/cmp_quant/h5_merge_q3.pgm.gz: New img file.
+ * doc/labeling/cmp_quant/h5_merge_q4.pgm.gz: New img file.
+ * doc/labeling/cmp_quant/h5_merge_q5.pgm.gz: New img file.
+ * doc/labeling/cmp_quant/h5_merge_q6.pgm.gz: New img file.
+ * doc/labeling/cmp_quant/h5_merge_q7.pgm.gz: New img file.
+ * doc/labeling/cmp_quant/h5_merge_q8.pgm.gz: New img file.
+ * doc/labeling/cmp_quant/i5_mean_q2.ppm.gz: New img file.
+ * doc/labeling/cmp_quant/i5_mean_q3.ppm.gz: New img file.
+ * doc/labeling/cmp_quant/i5_mean_q4.ppm.gz: New img file.
+ * doc/labeling/cmp_quant/i5_mean_q5.ppm.gz: New img file.
+ * doc/labeling/cmp_quant/i5_mean_q6.ppm.gz: New img file.
+ * doc/labeling/cmp_quant/i5_mean_q7.ppm.gz: New img file.
+ * doc/labeling/cmp_quant/i5_mean_q8.ppm.gz: New img file.
+ * doc/labeling/cmp_quant/i5_merge_q2.ppm.gz: New img file.
+ * doc/labeling/cmp_quant/i5_merge_q3.ppm.gz: New img file.
+ * doc/labeling/cmp_quant/i5_merge_q4.ppm.gz: New img file.
+ * doc/labeling/cmp_quant/i5_merge_q5.ppm.gz: New img file.
+ * doc/labeling/cmp_quant/i5_merge_q6.ppm.gz: New img file.
+ * doc/labeling/cmp_quant/i5_merge_q7.ppm.gz: New img file.
+ * doc/labeling/cmp_quant/i5_merge_q8.ppm.gz: New img file.
+ * doc/labeling/cmp_quant/l5_input_q2.pgm.gz: New img file.
+ * doc/labeling/cmp_quant/l5_input_q3.pgm.gz: New img file.
+ * doc/labeling/cmp_quant/l5_input_q4.pgm.gz: New img file.
+ * doc/labeling/cmp_quant/l5_input_q5.pgm.gz: New img file.
+ * doc/labeling/cmp_quant/l5_input_q6.pgm.gz: New img file.
+ * doc/labeling/cmp_quant/l5_input_q7.pgm.gz: New img file.
+ * doc/labeling/cmp_quant/l5_input_q8.pgm.gz: New img file.
+ * doc/labeling/cmp_quant/s5_histo_q2.txt.gz: New txt file.
+ * doc/labeling/cmp_quant/s5_histo_q3.txt.gz: New txt file.
+ * doc/labeling/cmp_quant/s5_histo_q4.txt.gz: New txt file.
+ * doc/labeling/cmp_quant/s5_histo_q5.txt.gz: New txt file.
+ * doc/labeling/cmp_quant/s5_histo_q6.txt.gz: New txt file.
+ * doc/labeling/cmp_quant/s5_histo_q7.txt.gz: New txt file.
+ * doc/labeling/cmp_quant/s5_histo_q8.txt.gz: New txt file.
+ * doc/labeling/cmp_quant/synthese.txt.gz: New experiment doc.
+
+ * doc/labeling/mp00411c: New directory.
+ * doc/labeling/mp00411c/colormap_all_q4.txt.gz: New txt file.
+ * doc/labeling/mp00411c/colormap_all_q5.txt.gz: New txt file.
+ * doc/labeling/mp00411c/colormap_thick_q4.txt.gz: New txt file.
+ * doc/labeling/mp00411c/colormap_thick_q5.txt.gz: New txt file.
+ * doc/labeling/mp00411c/colormap_thin_q4.txt.gz: New txt file.
+ * doc/labeling/mp00411c/colormap_thin_q5.txt.gz: New txt file.
+ * doc/labeling/mp00411c/histo_all_q4.dump.gz: New dump file.
+ * doc/labeling/mp00411c/histo_all_q5.dump.gz: New dump file.
+ * doc/labeling/mp00411c/histo_thick_q4.dump.gz: New dump file.
+ * doc/labeling/mp00411c/histo_thick_q5.dump.gz: New dump file.
+ * doc/labeling/mp00411c/histo_thin_q4.dump.gz: New dump file.
+ * doc/labeling/mp00411c/histo_thin_q5.dump.gz: New dump file.
+ * doc/labeling/mp00411c/iz_all_q4.dump.gz: New dump file.
+ * doc/labeling/mp00411c/iz_all_q5.dump.gz: New dump file.
+ * doc/labeling/mp00411c/iz_thick_q4.dump.gz: New dump file.
+ * doc/labeling/mp00411c/iz_thick_q5.dump.gz: New dump file.
+ * doc/labeling/mp00411c/iz_thin_q4.dump.gz: New dump file.
+ * doc/labeling/mp00411c/iz_thin_q5.dump.gz: New dump file.
+ * doc/labeling/mp00411c/labeled_all_q4.dump.gz: New dump file.
+ * doc/labeling/mp00411c/labeled_all_q5.dump.gz: New dump file.
+ * doc/labeling/mp00411c/labeled_thick_q4.dump.gz: New dump file.
+ * doc/labeling/mp00411c/labeled_thick_q5.dump.gz: New dump file.
+ * doc/labeling/mp00411c/labeled_thin_q4.dump.gz: New dump file.
+ * doc/labeling/mp00411c/labeled_thin_q5.dump.gz: New dump file.
+ * doc/labeling/mp00411c/mean3_all_q4.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/mean3_all_q5.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/mean3_thick_q4.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/mean3_thick_q5.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/mean3_thin_q4.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/mean3_thin_q5.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/mean4_all_q4.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/mean4_all_q5.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/mean4_thick_q4.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/mean4_thick_q5.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/mean4_thin_q4.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/mean4_thin_q5.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/mp00411c.ppm.gz: New input file.
+ * doc/labeling/mp00411c/mp00411c_thin.pbm.gz: New gradient mask.
+ * doc/labeling/mp00411c/mp00411c_thick.pbm.gz: New gradient mask.
+ * doc/labeling/mp00411c/mp00411c.sh.gz: New script shell.
+ * doc/labeling/mp00411c/opened_all_q4.dump.gz: New dump file.
+ * doc/labeling/mp00411c/opened_all_q5.dump.gz: New dump file.
+ * doc/labeling/mp00411c/opened_thick_q4.dump.gz: New dump file.
+ * doc/labeling/mp00411c/opened_thick_q5.dump.gz: New dump file.
+ * doc/labeling/mp00411c/opened_thin_q4.dump.gz: New dump file.
+ * doc/labeling/mp00411c/opened_thin_q5.dump.gz: New dump file.
+ * doc/labeling/mp00411c/proj1_all_q4.pgm.gz: New pgm file.
+ * doc/labeling/mp00411c/proj1_all_q5.pgm.gz: New pgm file.
+ * doc/labeling/mp00411c/proj1_thick_q4.pgm.gz: New pgm file.
+ * doc/labeling/mp00411c/proj1_thick_q5.pgm.gz: New pgm file.
+ * doc/labeling/mp00411c/proj1_thin_q4.pgm.gz: New pgm file.
+ * doc/labeling/mp00411c/proj1_thin_q5.pgm.gz: New pgm file.
+ * doc/labeling/mp00411c/proj2_all_q4.pgm.gz: New pgm file.
+ * doc/labeling/mp00411c/proj2_all_q5.pgm.gz: New pgm file.
+ * doc/labeling/mp00411c/proj2_thick_q4.pgm.gz: New pgm file.
+ * doc/labeling/mp00411c/proj2_thick_q5.pgm.gz: New pgm file.
+ * doc/labeling/mp00411c/proj2_thin_q4.pgm.gz: New pgm file.
+ * doc/labeling/mp00411c/proj2_thin_q5.pgm.gz: New pgm file.
+ * doc/labeling/mp00411c/proj3_all_q4.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/proj3_all_q5.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/proj3_thick_q4.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/proj3_thick_q5.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/proj3_thin_q4.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/proj3_thin_q5.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/proj4_all_q4.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/proj4_all_q5.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/proj4_thick_q4.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/proj4_thick_q5.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/proj4_thin_q4.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/proj4_thin_q5.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/quant_q4.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/quant_q5.ppm.gz: New ppm file.
+ * doc/labeling/mp00411c/stat3_all_q4.txt.gz: New txt file.
+ * doc/labeling/mp00411c/stat3_all_q5.txt.gz: New txt file.
+ * doc/labeling/mp00411c/stat3_thick_q4.txt.gz: New txt file.
+ * doc/labeling/mp00411c/stat3_thick_q5.txt.gz: New txt file.
+ * doc/labeling/mp00411c/stat3_thin_q4.txt.gz: New txt file.
+ * doc/labeling/mp00411c/stat3_thin_q5.txt.gz: New txt file.
+ * doc/labeling/mp00411c/stat4_all_q4.txt.gz: New txt file.
+ * doc/labeling/mp00411c/stat4_all_q5.txt.gz: New txt file.
+ * doc/labeling/mp00411c/stat4_thick_q4.txt.gz: New txt file.
+ * doc/labeling/mp00411c/stat4_thick_q5.txt.gz: New txt file.
+ * doc/labeling/mp00411c/stat4_thin_q4.txt.gz: New txt file.
+ * doc/labeling/mp00411c/stat4_thin_q5.txt.gz: New txt file.
+ * doc/labeling/mp00411c/synthese.txt.gz: New txt file.
+
+ * doc/labeling/mp00307c_bis: New directory.
+ * doc/labeling/mp00307c_bis/colormap_all_q4_r06f.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_all_q4_r06h.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_all_q4_r18f.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_all_q4_r18h.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_all_q4_r26f.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_all_q4_r26h.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_all_q5_r06f.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_all_q5_r06h.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_all_q5_r18f.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_all_q5_r18h.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_all_q5_r26f.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_all_q5_r26h.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thin_q4_r06f.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thin_q4_r06h.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thin_q4_r18f.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thin_q4_r18h.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thin_q4_r26f.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thin_q4_r26h.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thin_q5_r06f.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thin_q5_r06h.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thin_q5_r18f.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thin_q5_r18h.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thin_q5_r26f.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thin_q5_r26h.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thick_q4_r06f.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thick_q4_r06h.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thick_q4_r18f.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thick_q4_r18h.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thick_q4_r26f.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thick_q4_r26h.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thick_q5_r06f.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thick_q5_r06h.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thick_q5_r18f.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thick_q5_r18h.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thick_q5_r26f.txt: New colormap.
+ * doc/labeling/mp00307c_bis/colormap_thick_q5_r26h.txt: New colormap.
+ * doc/labeling/mp00307c_bis/histo_all_q4.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/histo_all_q5.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/histo_all_q8.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/histo_thin_q4.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/histo_thin_q5.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/histo_thin_q8.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/histo_thick_q4.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/histo_thick_q5.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/histo_thick_q8.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/iz_all_q4_r06f_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q4_r06f_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q4_r06f_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q4_r06h_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q4_r06h_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q4_r06h_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q4_r18f_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q4_r18f_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q4_r18f_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q4_r18h_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q4_r18h_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q4_r18h_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q4_r26f_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q4_r26f_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q4_r26f_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q4_r26h_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q4_r26h_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q4_r26h_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q5_r06f_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q5_r06f_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q5_r06f_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q5_r06h_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q5_r06h_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q5_r06h_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q5_r18f_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q5_r18f_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q5_r18f_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q5_r18h_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q5_r18h_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q5_r18h_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q5_r26f_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q5_r26f_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q5_r26f_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q5_r26h_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q5_r26h_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_all_q5_r26h_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q4_r06f_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q4_r06f_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q4_r06f_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q4_r06h_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q4_r06h_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q4_r06h_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q4_r18f_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q4_r18f_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q4_r18f_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q4_r18h_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q4_r18h_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q4_r18h_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q4_r26f_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q4_r26f_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q4_r26f_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q4_r26h_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q4_r26h_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q4_r26h_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q5_r06f_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q5_r06f_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q5_r06f_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q5_r06h_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q5_r06h_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q5_r06h_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q5_r18f_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q5_r18f_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q5_r18f_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q5_r18h_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q5_r18h_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q5_r18h_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q5_r26f_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q5_r26f_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q5_r26f_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q5_r26h_i06.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q5_r26h_i18.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thin_q5_r26h_i26.dump.gz: New lbl propag.
+ * doc/labeling/mp00307c_bis/iz_thick_q4_r06f_i06.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q4_r06f_i18.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q4_r06f_i26.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q4_r06h_i06.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q4_r06h_i18.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q4_r06h_i26.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q4_r18f_i06.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q4_r18f_i18.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q4_r18f_i26.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q4_r18h_i06.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q4_r18h_i18.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q4_r18h_i26.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q4_r26f_i06.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q4_r26f_i18.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q4_r26f_i26.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q4_r26h_i06.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q4_r26h_i18.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q4_r26h_i26.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q5_r06f_i06.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q5_r06f_i18.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q5_r06f_i26.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q5_r06h_i06.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q5_r06h_i18.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q5_r06h_i26.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q5_r18f_i06.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q5_r18f_i18.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q5_r18f_i26.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q5_r18h_i06.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q5_r18h_i18.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q5_r18h_i26.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q5_r26f_i06.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q5_r26f_i18.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q5_r26f_i26.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q5_r26h_i06.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q5_r26h_i18.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/iz_thick_q5_r26h_i26.dump.gz: New lbl prop.
+ * doc/labeling/mp00307c_bis/labeled_all_q4_r06f.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_all_q4_r06h.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_all_q4_r18f.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_all_q4_r18h.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_all_q4_r28f.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_all_q4_r28h.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_all_q5_r06f.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_all_q5_r06h.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_all_q5_r18f.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_all_q5_r18h.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_all_q5_r28f.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_all_q5_r28h.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thin_q4_r06f.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thin_q4_r06h.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thin_q4_r18f.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thin_q4_r18h.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thin_q4_r28f.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thin_q4_r28h.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thin_q5_r06f.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thin_q5_r06h.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thin_q5_r18f.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thin_q5_r18h.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thin_q5_r28f.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thin_q5_r28h.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thick_q4_r06f.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thick_q4_r06h.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thick_q4_r18f.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thick_q4_r18h.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thick_q4_r28f.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thick_q4_r28h.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thick_q5_r06f.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thick_q5_r06h.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thick_q5_r18f.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thick_q5_r18h.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thick_q5_r28f.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/labeled_thick_q5_r28h.dump.gz: New histo.
+ * doc/labeling/mp00307c_bis/mean3_all_q4_r06f.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_all_q4_r06h.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_all_q4_r18f.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_all_q4_r18h.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_all_q4_r26f.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_all_q4_r26h.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_all_q5_r06f.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_all_q5_r06h.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_all_q5_r18f.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_all_q5_r18h.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_all_q5_r26f.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_all_q5_r26h.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thin_q4_r06f.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thin_q4_r06h.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thin_q4_r18f.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thin_q4_r18h.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thin_q4_r26f.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thin_q4_r26h.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thin_q5_r06f.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thin_q5_r06h.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thin_q5_r18f.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thin_q5_r18h.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thin_q5_r26f.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thin_q5_r26h.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thick_q4_r06f.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thick_q4_r06h.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thick_q4_r18f.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thick_q4_r18h.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thick_q4_r26f.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thick_q4_r26h.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thick_q5_r06f.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thick_q5_r06h.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thick_q5_r18f.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thick_q5_r18h.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thick_q5_r26f.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean3_thick_q5_r26h.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q4_r06f_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q4_r06f_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q4_r06f_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q4_r06h_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q4_r06h_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q4_r06h_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q4_r18f_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q4_r18f_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q4_r18f_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q4_r18h_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q4_r18h_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q4_r18h_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q4_r26f_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q4_r26f_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q4_r26f_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q4_r26h_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q4_r26h_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q4_r26h_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q5_r06f_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q5_r06f_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q5_r06f_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q5_r06h_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q5_r06h_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q5_r06h_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q5_r18f_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q5_r18f_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q5_r18f_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q5_r18h_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q5_r18h_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q5_r18h_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q5_r26f_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q5_r26f_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q5_r26f_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q5_r26h_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q5_r26h_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_all_q5_r26h_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q4_r06f_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q4_r06f_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q4_r06f_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q4_r06h_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q4_r06h_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q4_r06h_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q4_r18f_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q4_r18f_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q4_r18f_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q4_r18h_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q4_r18h_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q4_r18h_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q4_r26f_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q4_r26f_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q4_r26f_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q4_r26h_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q4_r26h_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q4_r26h_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q5_r06f_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q5_r06f_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q5_r06f_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q5_r06h_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q5_r06h_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q5_r06h_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q5_r18f_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q5_r18f_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q5_r18f_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q5_r18h_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q5_r18h_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q5_r18h_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q5_r26f_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q5_r26f_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q5_r26f_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q5_r26h_i06.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q5_r26h_i18.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thin_q5_r26h_i26.ppm.gz: New mean img.
+ * doc/labeling/mp00307c_bis/mean4_thick_q4_r06f_i06.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q4_r06f_i18.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q4_r06f_i26.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q4_r06h_i06.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q4_r06h_i18.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q4_r06h_i26.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q4_r18f_i06.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q4_r18f_i18.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q4_r18f_i26.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q4_r18h_i06.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q4_r18h_i18.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q4_r18h_i26.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q4_r26f_i06.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q4_r26f_i18.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q4_r26f_i26.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q4_r26h_i06.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q4_r26h_i18.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q4_r26h_i26.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q5_r06f_i06.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q5_r06f_i18.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q5_r06f_i26.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q5_r06h_i06.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q5_r06h_i18.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q5_r06h_i26.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q5_r18f_i06.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q5_r18f_i18.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q5_r18f_i26.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q5_r18h_i06.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q5_r18h_i18.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q5_r18h_i26.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q5_r26f_i06.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q5_r26f_i18.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q5_r26f_i26.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q5_r26h_i06.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q5_r26h_i18.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mean4_thick_q5_r26h_i26.ppm.gz: New mean .
+ * doc/labeling/mp00307c_bis/mp00307c.ppm.gz: New input img.
+ * doc/labeling/mp00307c_bis/mp00307c.sh.gz: New script shell.
+ * doc/labeling/mp00307c_bis/mp00307c_thick.pgm.gz: New mask.
+ * doc/labeling/mp00307c_bis/mp00307c_thin.pgm.gz: New mask.
+ * doc/labeling/mp00307c_bis/opened_all_q4.dump.gz: New filtered histo.
+ * doc/labeling/mp00307c_bis/opened_all_q5.dump.gz: New filtered histo.
+ * doc/labeling/mp00307c_bis/opened_all_q8.dump.gz: New filtered histo.
+ * doc/labeling/mp00307c_bis/opened_thin_q4.dump.gz: New filtered histo.
+ * doc/labeling/mp00307c_bis/opened_thin_q5.dump.gz: New filtered histo.
+ * doc/labeling/mp00307c_bis/opened_thin_q8.dump.gz: New filtered histo.
+ * doc/labeling/mp00307c_bis/opened_thick_q4.dump.gz: New filtered histo.
+ * doc/labeling/mp00307c_bis/opened_thick_q5.dump.gz: New filtered histo.
+ * doc/labeling/mp00307c_bis/opened_thick_q8.dump.gz: New filtered histo.
+ * doc/labeling/mp00307c_bis/proj1_all_q4.pgm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj1_all_q4.ppm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj1_all_q5.pgm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj1_all_q5.ppm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj1_all_q8.pgm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj1_all_q8.ppm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj1_thin_q4.pgm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj1_thin_q4.ppm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj1_thin_q5.pgm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj1_thin_q5.ppm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj1_thin_q8.pgm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj1_thin_q8.ppm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj1_thick_q4.pgm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj1_thick_q4.ppm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj1_thick_q5.pgm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj1_thick_q5.ppm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj1_thick_q8.pgm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj1_thick_q8.ppm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj2_all_q4.pgm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj2_all_q4.ppm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj2_all_q5.pgm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj2_all_q5.ppm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj2_all_q8.pgm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj2_all_q8.ppm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj2_thin_q4.pgm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj2_thin_q4.ppm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj2_thin_q5.pgm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj2_thin_q5.ppm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj2_thin_q8.pgm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj2_thin_q8.ppm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj2_thick_q4.pgm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj2_thick_q4.ppm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj2_thick_q5.pgm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj2_thick_q5.ppm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj2_thick_q8.pgm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj2_thick_q8.ppm.gz: New r/g projection.
+ * doc/labeling/mp00307c_bis/proj3_all_q4_r06f.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_all_q4_r06h.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_all_q4_r18f.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_all_q4_r18h.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_all_q4_r26f.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_all_q4_r26h.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_all_q5_r06f.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_all_q5_r06h.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_all_q5_r18f.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_all_q5_r18h.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_all_q5_r26f.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_all_q5_r26h.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thin_q4_r06f.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thin_q4_r06h.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thin_q4_r18f.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thin_q4_r18h.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thin_q4_r26f.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thin_q4_r26h.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thin_q5_r06f.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thin_q5_r06h.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thin_q5_r18f.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thin_q5_r18h.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thin_q5_r26f.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thin_q5_r26h.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thick_q4_r06f.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thick_q4_r06h.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thick_q4_r18f.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thick_q4_r18h.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thick_q4_r26f.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thick_q4_r26h.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thick_q5_r06f.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thick_q5_r06h.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thick_q5_r18f.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thick_q5_r18h.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thick_q5_r26f.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj3_thick_q5_r26h.ppm.gz: New r/g proj.
+ * doc/labeling/mp00307c_bis/proj4_all_q4_r06f_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q4_r06f_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q4_r06f_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q4_r06h_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q4_r06h_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q4_r06h_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q4_r18f_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q4_r18f_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q4_r18f_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q4_r18h_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q4_r18h_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q4_r18h_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q4_r26f_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q4_r26f_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q4_r26f_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q4_r26h_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q4_r26h_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q4_r26h_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q5_r06f_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q5_r06f_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q5_r06f_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q5_r06h_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q5_r06h_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q5_r06h_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q5_r18f_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q5_r18f_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q5_r18f_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q5_r18h_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q5_r18h_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q5_r18h_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q5_r26f_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q5_r26f_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q5_r26f_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q5_r26h_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q5_r26h_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_all_q5_r26h_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q4_r06f_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q4_r06f_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q4_r06f_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q4_r06h_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q4_r06h_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q4_r06h_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q4_r18f_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q4_r18f_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q4_r18f_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q4_r18h_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q4_r18h_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q4_r18h_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q4_r26f_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q4_r26f_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q4_r26f_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q4_r26h_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q4_r26h_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q4_r26h_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q5_r06f_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q5_r06f_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q5_r06f_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q5_r06h_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q5_r06h_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q5_r06h_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q5_r18f_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q5_r18f_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q5_r18f_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q5_r18h_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q5_r18h_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q5_r18h_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q5_r26f_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q5_r26f_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q5_r26f_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q5_r26h_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q5_r26h_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thin_q5_r26h_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q4_r06f_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q4_r06f_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q4_r06f_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q4_r06h_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q4_r06h_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q4_r06h_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q4_r18f_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q4_r18f_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q4_r18f_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q4_r18h_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q4_r18h_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q4_r18h_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q4_r26f_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q4_r26f_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q4_r26f_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q4_r26h_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q4_r26h_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q4_r26h_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q5_r06f_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q5_r06f_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q5_r06f_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q5_r06h_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q5_r06h_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q5_r06h_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q5_r18f_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q5_r18f_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q5_r18f_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q5_r18h_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q5_r18h_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q5_r18h_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q5_r26f_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q5_r26f_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q5_r26f_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q5_r26h_i06.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q5_r26h_i18.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/proj4_thick_q5_r26h_i26.ppm.gz: New rg prj.
+ * doc/labeling/mp00307c_bis/quant_q4.ppm.gz: New quantified img.
+ * doc/labeling/mp00307c_bis/quant_q5.ppm.gz: New quantified img.
+ * doc/labeling/mp00307c_bis/quant_q8.ppm.gz: New quantified img.
+ * doc/labeling/mp00307c_bis/stats3_all_q4_r06f.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_all_q4_r06h.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_all_q4_r18f.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_all_q4_r18h.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_all_q4_r26f.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_all_q4_r26h.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_all_q5_r06f.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_all_q5_r06h.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_all_q5_r18f.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_all_q5_r18h.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_all_q5_r26f.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_all_q5_r26h.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thin_q4_r06f.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thin_q4_r06h.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thin_q4_r18f.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thin_q4_r18h.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thin_q4_r26f.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thin_q4_r26h.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thin_q5_r06f.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thin_q5_r06h.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thin_q5_r18f.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thin_q5_r18h.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thin_q5_r26f.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thin_q5_r26h.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thick_q4_r06f.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thick_q4_r06h.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thick_q4_r18f.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thick_q4_r18h.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thick_q4_r26f.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thick_q4_r26h.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thick_q5_r06f.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thick_q5_r06h.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thick_q5_r18f.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thick_q5_r18h.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thick_q5_r26f.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats3_thick_q5_r26h.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q4_r06f_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q4_r06f_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q4_r06f_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q4_r06h_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q4_r06h_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q4_r06h_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q4_r18f_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q4_r18f_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q4_r18f_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q4_r18h_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q4_r18h_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q4_r18h_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q4_r26f_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q4_r26f_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q4_r26f_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q4_r26h_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q4_r26h_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q4_r26h_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q5_r06f_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q5_r06f_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q5_r06f_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q5_r06h_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q5_r06h_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q5_r06h_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q5_r18f_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q5_r18f_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q5_r18f_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q5_r18h_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q5_r18h_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q5_r18h_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q5_r26f_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q5_r26f_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q5_r26f_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q5_r26h_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q5_r26h_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_all_q5_r26h_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q4_r06f_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q4_r06f_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q4_r06f_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q4_r06h_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q4_r06h_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q4_r06h_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q4_r18f_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q4_r18f_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q4_r18f_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q4_r18h_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q4_r18h_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q4_r18h_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q4_r26f_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q4_r26f_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q4_r26f_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q4_r26h_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q4_r26h_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q4_r26h_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q5_r06f_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q5_r06f_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q5_r06f_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q5_r06h_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q5_r06h_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q5_r06h_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q5_r18f_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q5_r18f_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q5_r18f_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q5_r18h_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q5_r18h_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q5_r18h_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q5_r26f_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q5_r26f_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q5_r26f_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q5_r26h_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q5_r26h_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thin_q5_r26h_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q4_r06f_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q4_r06f_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q4_r06f_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q4_r06h_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q4_r06h_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q4_r06h_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q4_r18f_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q4_r18f_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q4_r18f_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q4_r18h_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q4_r18h_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q4_r18h_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q4_r26f_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q4_r26f_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q4_r26f_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q4_r26h_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q4_r26h_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q4_r26h_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q5_r06f_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q5_r06f_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q5_r06f_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q5_r06h_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q5_r06h_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q5_r06h_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q5_r18f_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q5_r18f_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q5_r18f_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q5_r18h_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q5_r18h_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q5_r18h_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q5_r26f_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q5_r26f_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q5_r26f_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q5_r26h_i06.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q5_r26h_i18.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/stats4_thick_q5_r26h_i26.ppm.gz: New stats.
+ * doc/labeling/mp00307c_bis/synthese.txt.gz: New synthesis file.
+
+
+ * doc/labeling/mp00042c: New directory.
+ * doc/labeling/mp00042c/histo_all.dump.gz: New histo.
+ * doc/labeling/mp00042c/histo_thick.dump.gz: New histo.
+ * doc/labeling/mp00042c/histo_thin.dump.gz: New histo.
+ * doc/labeling/mp00042c/labeled_all.dump.gz: New labeled histo.
+ * doc/labeling/mp00042c/labeled_thick.dump.gz: New labeled histo.
+ * doc/labeling/mp00042c/labeled_thin.dump.gz: New labeled histo.
+ * doc/labeling/mp00042c/mean_all.dump.gz: New mean img.
+ * doc/labeling/mp00042c/mean_thin.dump.gz: New mean img.
+ * doc/labeling/mp00042c/mean_thick.dump.gz: New mean img.
+ * doc/labeling/mp00042c/mp00042c.ppm.gz: New input img.
+ * doc/labeling/mp00042c/mp00042c.sh.gz: New script shell.
+ * doc/labeling/mp00042c/mp00042c_thick.gz: New mask.
+ * doc/labeling/mp00042c/mp00042c_thin.gz: New mask.
+ * doc/labeling/mp00042c/opened_all.gz: New filtered histo.
+ * doc/labeling/mp00042c/opened_thin.gz: New filtered histo.
+ * doc/labeling/mp00042c/opened_thick.gz: New filtered histo.
+ * doc/labeling/mp00042c/pal_all.gz: New colormap.
+ * doc/labeling/mp00042c/pal_thin.gz: New colormap.
+ * doc/labeling/mp00042c/pal_thick.gz: New colormap.
+ * doc/labeling/mp00042c/proj1.pgm.gz: New r/g projection.
+ * doc/labeling/mp00042c/proj2.pgm.gz: New r/g projection.
+ * doc/labeling/mp00042c/proj3.ppm.gz: New r/g projection.
+ * doc/labeling/mp00042c/proj2_all.pgm.gz: New r/g projection
+ * doc/labeling/mp00042c/proj2_thin.pgm.gz: New r/g projection.
+ * doc/labeling/mp00042c/proj2_thick.pgm.gz: New r/g projection.
+ * doc/labeling/mp00042c/proj3_all.pgm.gz: New r/g projection.
+ * doc/labeling/mp00042c/proj3_thin.pgm.gz: New r/g projection.
+ * doc/labeling/mp00042c/proj3_thick.pgm.gz: New r/g projection.
+ * doc/labeling/mp00042c/proj_all.pgm.gz: New r/g projection.
+ * doc/labeling/mp00042c/proj_thick.pgm.gz: New r/g projection.
+ * doc/labeling/mp00042c/proj_thin.pgm.gz: New r/g projection.
+ * doc/labeling/mp00042c/quant.ppm.gz: New quantified img.
+
+ * doc/labeling/mp00307c: New directory.
+ * doc/labeling/mp00307c/colormap_all.txt.tgz: New colormap.
+ * doc/labeling/mp00307c/colormap_thin.txt.tgz: New colormap.
+ * doc/labeling/mp00307c/colormap_thick.txt.tgz: New colormap.
+ * doc/labeling/mp00307c/histo_all.dump.tgz: New histo.
+ * doc/labeling/mp00307c/histo_thin.dump.tgz: New histo.
+ * doc/labeling/mp00307c/histo_thick.dump.tgz: New histo.
+ * doc/labeling/mp00307c/iz_all.dump.tgz: New label propagation..
+ * doc/labeling/mp00307c/iz_thick.dump.tgz: New label propagation..
+ * doc/labeling/mp00307c/labeled_all.dump.tgz: New label histo.
+ * doc/labeling/mp00307c/labeled_thin.dump.tgz: New label histo.
+ * doc/labeling/mp00307c/labeled_thick.dump.tgz: New label histo.
+ * doc/labeling/mp00307c/mean3_all.ppm.tgz: New mean img.
+ * doc/labeling/mp00307c/mean3_thin.ppm.tgz: New mean img.
+ * doc/labeling/mp00307c/mean3_thick.ppm.tgz: New mean img.
+ * doc/labeling/mp00307c/mean4_all.ppm.tgz: New mean img.
+ * doc/labeling/mp00307c/mean4_thin.ppm.tgz: New mean img.
+ * doc/labeling/mp00307c/mean4_thick.ppm.tgz: New mean img.
+ * doc/labeling/mp00307c/mp00307.ppm.tgz: New input img.
+ * doc/labeling/mp00307c/mp00307.sh.tgz: New script shell.
+ * doc/labeling/mp00307c/mp00307_thin.pbm.tgz: New mask.
+ * doc/labeling/mp00307c/mp00307_thick.pbm.tgz: New mask.
+ * doc/labeling/mp00307c/opened_all.dump.tgz: New filtered img.
+ * doc/labeling/mp00307c/opened_thin.dump.tgz: New filtered img.
+ * doc/labeling/mp00307c/opened_thick.dump.tgz: New filtered img.
+ * doc/labeling/mp00307c/proj1_all.pgm.tgz: New r/g projection.
+ * doc/labeling/mp00307c/proj1_all.ppm.tgz: New r/g projection.
+ * doc/labeling/mp00307c/proj1_thin.pgm.tgz: New r/g projection.
+ * doc/labeling/mp00307c/proj1_thin.ppm.tgz: New r/g projection.
+ * doc/labeling/mp00307c/proj1_thick.pgm.tgz: New r/g projection.
+ * doc/labeling/mp00307c/proj1_thick.ppm.tgz: New r/g projection.
+ * doc/labeling/mp00307c/proj2_all.pgm.tgz: New r/g projection.
+ * doc/labeling/mp00307c/proj2_all.ppm.tgz: New r/g projection.
+ * doc/labeling/mp00307c/proj2_thin.pgm.tgz: New r/g projection.
+ * doc/labeling/mp00307c/proj2_thin.ppm.tgz: New r/g projection.
+ * doc/labeling/mp00307c/proj2_thick.pgm.tgz: New r/g projection.
+ * doc/labeling/mp00307c/proj2_thick.ppm.tgz: New r/g projection.
+ * doc/labeling/mp00307c/proj3_all.pgm.tgz: New r/g projection.
+ * doc/labeling/mp00307c/proj3_all.ppm.tgz: New r/g projection.
+ * doc/labeling/mp00307c/proj3_thin.pgm.tgz: New r/g projection.
+ * doc/labeling/mp00307c/proj3_thin.ppm.tgz: New r/g projection.
+ * doc/labeling/mp00307c/proj3_thick.pgm.tgz: New r/g projection.
+ * doc/labeling/mp00307c/proj3_thick.ppm.tgz: New r/g projection.
+ * doc/labeling/mp00307c/proj4_all.pgm.tgz: New r/g projection.
+ * doc/labeling/mp00307c/proj4_all.ppm.tgz: New r/g projection.
+ * doc/labeling/mp00307c/proj4_thin.pgm.tgz: New r/g projection.
+ * doc/labeling/mp00307c/proj4_thin.ppm.tgz: New r/g projection.
+ * doc/labeling/mp00307c/proj4_thick.pgm.tgz: New r/g projection.
+ * doc/labeling/mp00307c/proj4_thick.ppm.tgz: New r/g projection
+ * doc/labeling/mp00307c/quant.ppm.tgz: New quantified img
+ * doc/labeling/mp00307c/stats3_all.txt.tgz: New stats file.
+ * doc/labeling/mp00307c/stats3_thin.txt.tgz: New stats file.
+ * doc/labeling/mp00307c/stats3_thick.txt.tgz: New stats file.
+ * doc/labeling/mp00307c/stats4_all.txt.tgz: New stats file.
+ * doc/labeling/mp00307c/stats4_thin.txt.tgz: New stats file.
+ * doc/labeling/mp00307c/stats4_thick.txt.tgz: New stats file.
+ * doc/labeling/mp00307c/synthese.txt.tgz: New synthesis file.
+
+ Import materials for next tests.
+
+ * doc/labeling/mp00215c: New directory.
+ * doc/labeling/mp00215c/mp00215c.ppm.gz: New color input img.
+ * doc/labeling/mp00215c/mp00215c_thick.pbm.gz: New thick mask.
+ * doc/labeling/mp00215c/mp00215c_thin.pbm.gz: New thin mask.
+
+ * doc/labeling/mp00234c: New directory.
+ * doc/labeling/mp00234c/mp00234c.ppm.gz: New color input img.
+ * doc/labeling/mp00234c/mp00234c_thick.pbm.gz: New thick mask.
+ * doc/labeling/mp00234c/mp00234c_thin.pbm.gz: New thin mask.
+
+ * doc/labeling/mp00248c: New directory.
+ * doc/labeling/mp00248c/mp00248c.ppm.gz: New color input img.
+ * doc/labeling/mp00248c/mp00248c_thick.pbm.gz: New thick mask.
+ * doc/labeling/mp00248c/mp00248c_thin.pbm.gz: New thin mask.
+
+ * doc/labeling/mp00031c: New directory.
+ * doc/labeling/mp00031c/mp00031c.ppm.gz: New color input img.
+ * doc/labeling/mp00031c/mp00031c_thick.pbm.gz: New thick mask.
+ * doc/labeling/mp00031c/mp00031c_thin.pbm.gz: New thin mask.
+
+ * doc/labeling/mp00083c: New directory.
+ * doc/labeling/mp00083c/mp00083c.ppm.gz: New color input img.
+ * doc/labeling/mp00083c/mp00083c_thick.pbm.gz: New thick mask.
+ * doc/labeling/mp00083c/mp00083c_thin.pbm.gz: New thin mask.
+
+ Import annotating search notes.
+
+ * doc/annotating/class.txt: New documentation text file.
+ * doc/annotating/syntheseMillet.txt: New documentation text file.
+ * doc/annotating/testMillet2008: New documentation text file.
+
+ Import milena learning examples.
+
+ * doc/examples: New directory.
+
+ * doc/examples/hello_world: New directory.
+ * doc/examples/hello_world/Makefile.am: New makefile.
+ * doc/examples/hello_world/hellow_world.cc: New source file.
+ * doc/examples/hello_world/print.cc: New source file.
+
+ * doc/examples/hello_milena: New directory.
+ * doc/examples/hello_milena/Makefile.am: New makefile.
+ * doc/examples/hello_milena/hello_milena.cc: New source file.
+
+ * doc/examples/learn_milena: New directory.
+ * doc/examples/learn_milena/Makefile.am: New makefile.
+ * doc/examples/learn_milena/learn_milena.cc: New source file.
+
+ * doc/examples/otsu: New directory.
+ * doc/examples/otsu/Makefile.am: New makefile.
+ * doc/examples/otsu/otsu.cc: New source file.
+
+ * doc/examples/frac: New directory.
+ * doc/examples/frac/Makefile.am: New makefile.
+ * doc/examples/frac/frac.cc: New source file.
+ * doc/examples/frac/frac.hh: New source file.
+ * doc/examples/frac/sign_prod.hh: New source file.
+ * doc/examples/frac/gcd.hh: New source file.
+
+ * doc/examples/accu_color: New directory.
+ * doc/examples/accu_color/accu_color.cc: New source file.
+
+ * doc/examples/io: New directory.
+ * doc/examples/io/Makefile.am: New makefile.
+ * doc/examples/io/io.cc: New source file.
+
+ Write down the basis of the quick tour summary documentation.
+
+ * doc/quick_tour: New specific directory.
+ * doc/quick_tour/quick_tour.tex: New documentation work.
+
+ Write down 3d currently used formulaes.
+
+ * doc/formulae: New specific directory.
+ * doc/formulae/formulae.tex: New recipe of 3d formulae.
+
+
2010-06-30 Yann Jacquelet <jacquelet(a)lrde.epita.fr>
Add some futur materials on regional maxima.
diff --git a/scribo/sandbox/green/README.green b/scribo/sandbox/green/README.green
index 02d8654..7886914 100644
--- a/scribo/sandbox/green/README.green
+++ b/scribo/sandbox/green/README.green
@@ -236,13 +236,94 @@ n'importe quel algorithme type huffman (tous les archiveurs en possède un).
VIII VISUALISATION HISTOGRAMMES 3D
----------------------------------
-==> to do
-
-
-* demo/accu/stat/histo2d
-
-* mln/display/dispay_histo.hh
-* mln/display/project_histo.hh
+Les histogrammes sur lesquels nous sommes amenés à travailler sont en
+3d. Nous étudions des images couleurs dans l'espace RGB, donc
+l'histogramme dans cet espace possède 3 dimensions (une par axe, R, G
+et B) et la cellule désignée par cette position RGB renfermera le nombre
+de pixels de l'image ayant exactement cette couleur. Il est très
+difficile de bien visualiser ces images, car elles sont en 3d. Gnuplot
+nous donne qu'une aide très limitée, car il faut afficher 3 axes et la
+force de la cellule, ce qui fait en fait quatre informations Ã
+afficher. Il est possible de jouer avec les couleurs, mais il n'y a
+pas de représentation très utile, on peut afficher le nuage des
+couleurs pour percevoir sa forme générale, mais l'interprétation ne
+peut pas vraiment aller plus loin. C'est pourquoi, nous proposons une
+représentation plus pertinente. C'est Théo qui a roulé sa bosse en
+classification qui a developpé ce genre de technique, je ne fais que
+réutilliser les mêmes analyses en beaucoup moins fins que ce qu'il a
+déjà pu développer par ailleurs.
+
+La première idée est de gommer une dimension, et c'est possible de le
+faire car dans une image RGB, souvent l'axe bleu est fortement
+correllé avec l'axe vert. Cela dépend beaucoup de la formation des
+images et pour des images synthétiques, il n'y a aucune raison que
+ce soit le cas. C'est juste une propriété qui s'applique pour les
+images naturelles. La forte corrélation obtenue ne veut pas dire qu'il
+y a exactement les mêmes informations, juste que dans l'ensemble on
+note une relative redondance (du point de vue statistique). Pour t'en
+convaincre, tu peux regarder sous gimp, les histogrammes sur les
+différents canaux et tu observeras qu'il y a deux canaux (le vert et
+bleu) pour lesquels les histogrammes sont presque identiques.
+
+La dernière étape est de réaliser un traitement sur la dimension qui a
+été supprimée. Par exemple, sommer toutes les valeurs rencontrées ou
+ne retenir que la valeur max ...
+
+Le fichier display_histo.hh joue le rôle de front hand pour les
+routines de visualisation. Il a pour rôle d'initialiser, d'instancier,
+de coordonner la chaine de visualisation. Le fichier project_histo.hh
+décrit les algorithmes au coeur de la visualisation, comment est
+construite concrêtement l'information que l'on visualise à la fin.
+
+Nous avons construit 3 sortes de projecteurs. Le premier va sommer le
+long de l'axe bleu les différentes informations
+rencontrées. Globalement, cela signifie, que plus il y a de pixels
+dans le sous espace (red=v1,green=v2) avec pour chaque pixel
+rencontrés des valeurs de bleu différentes, plus le nombre construit
+sera grand. Sur cette information, on fera passer un logarithme pour
+diminuer les pics et ne faire ressortir visuellement que les
+informations les plus saillantes. En dernier lieu, on rescalera les
+valeurs obtenues pour utiliser pleinement la dynamique d'une image de
+256 niveaux de gris. La visualisation obtenue nous donne un aperçu de
+la densité de l'espace des couleurs. On observera en très lumineux les
+endroits de forte population de couleurs et en presque noir l'absence
+de couleur dans l'image pour cette portion de l'espace RGB.
+
+Les autres techniques de visualisation sont des variantes du même
+traitement que nous allons decrire. La chaine de base consiste Ã
+parcourir la dimension bleu pour chaque point de l'espace rouge/vert
+(comme dans la première technique). Cette fois-ci, ce n'est plus la
+somme qui nous intéresse, mais la couleur la plus représentée. On va
+faire un max des valeurs obtenues en parcourant l'axe bleu. Une
+première version rapportera la position bleue qui rassemble le plus de
+pixels. Une seconde version remplacera cette position bleue par un
+label associé à une segmentation déjà effectuée dans cet espace.
+
+La dernière technique modifie la version précédente de la manière
+suivante: Nous sommes toujours interessé par le max, mais on va remplacer
+cette information directement par la couleur reconstituée (nous sommes
+sur un point particulier de l'espace red/green donc red et green sont
+connus, et on vient d'obtenir la valeur bleue la plus représentée, on
+utilisera cette valeur pour former une couleur RGB). A l'issu du
+processus, on obtient donc une image couleur. L'information obtenue
+ici, n'est plus la densité de l'histogramme, mais plutôt la couleur la
+plus représentée à cet endroit. La toute première technique et celle-ci
+sont complémentaires pour la bonne visualisation d'un histogramme
+3d. Si l'on dispose d'une segmentation de l'espace des couleurs, on
+peut trouver le label associé au bleu prédominant et récupérer dans
+une palette de couleur annexe la couleur associée au label.
+
+* mln/display/dispay_histo.hh: Front hand pour les routines de projection.
+* mln/display/project_histo.hh: Les algorithmes de visualisations.
+
+Le travail dans use ne représente que deux routines sur six de
+display_histo. Par manque de temps, je ne fais pas le reste de
+manière à insister sur d'autres points documentaires plus
+importants. Le cadre est en place et les autres routines plus
+sophistiquées faisant intervenir la segmentation de l'histogramme
+peuvent être tirées de tools/labeling/regmax par exemple.
+
+* use/display/display_histo: Visualisations des histogrammes.
IX KMEANS
@@ -388,29 +469,266 @@ tests effectués et montrent l'évolution du temps de calcul suivant la
progression du paramètre observé (taille de l'image ou nombre de
centres).
-==> to do : le changelog + commit + give it to scribo-z branch
-
X REGIONAL MAXIMA
-----------------
-==> to do
+Pour cette partie, le temps a commencé à s'accélérer, ce qui fait
+qu'il n'y a plus de tests unitaires. Par ailleurs, comme la
+fonctionnalité n'a pas été pensée comme un élément de la librairie, il
+n'y a donc pas non plus de répertoire "use" à cet effet.
+
+
+a) Segmentation basé sur le watershed
+
+Cet exemple essaye une première méthode de filtrage de
+l'histogramme. A noter elle ne compile pas. Elle eu compilé dans le
+temps, mais le source a été tellement remanié que sa reconstruction
+doit régler encore quelques détails. Sa compilation n'a pas vraiment
+d'intérêt en soi, seule la démarche compte ici. Le temps me manque et
+je ne persisterais pas à essayer de le faire compiler à tout prix. D'autres
+sources sont beaucoup plus intéressant. Nota, gaussian.sh est un gnuplot
+script shell qui sert à calibrer le filtrage de l'histogramme. Il permet
+de déterminer visuellement la taille de la fenêtre win utilisée lors de la
+convolution en fonction d'un écart type sigma donné.
+
+* demo/labeling/watershed: Demonstrator de la segmentation d'un histogramme.
+
+
+b) Second essai avec les regional_maxima
+
+Le programme actuel ne compile pas non plus. Il n'est pas d'une grande
+importance, alors du coup je le laisse tel quel. Il a servi a
+plusieurs choses, en premier à tester les regional_maxima mais en
+dernier lieu surtout à tester le filtrage par attribut (volume) qui
+semblait avoir quelques soucis. A l'heure d'aujourd'hui, je ne peux
+toujours pas dire s'il fonctionne convenablement ou non, il semble que
+parfois des anomalies se produisent à ce niveau, mais elles peuvent
+aussi bien être générées par un problème interne à mon programme.
+
+* demo/labeling/regional_maxima: Testeur du filtrage par attribut de volume.
+
+
+c) Déplacement du programme b) dans exp.
+
+Même programme que b) mais qui compile.
+
+* exp/labeling/regional_maxima: Testeur du filtrage par attribut de volume.
+
+
+d) Sources importantes ==> regional_maxima
+
+Il y avait une autre version des regional_maxima ou toute la chaine était
+présente, si j'avais davantage de temps, je l'aurais réecrite. Il semble
+qu'elle se soit perdue lors de la migration de SVN vers GIT. Aucune importance.
+Les outils "up to date" sont ceux dont les sources sont dans tools. La classe
+outil représente des binaires un peu plus travaillé au niveau de l'interface
+texte, en gros ils prennent plein de paramètres et génèrent des résultats
+intermédiaires. Chaque outil à son usage ...
+
+
+Ce qu'il faut savoir sur l'outil histo. Tout d'abord le programme
+prend 7 ou 8 arguments et c'est le dernier qui est optionnel. Les
+arguments sont l'image couleur à partir de laquelle on veut extraire
+l'histogramme couleur (3d), le degré de quantification que l'on veut
+utiliser (sous échantillonnnage de l'image), le chemin de l'image
+couleur quantifiée résultante après analyse, le chemin de
+l'histogramme produit (réutilisé par les autres outils), la
+visualisation rouge/verte de l'histogramme (brute) et la visualisation
+augmentée de ce même histogramme avec les maxima dessus. Se reporter Ã
+la documentation des histogrammes pour avoir plus d'information sur ce
+sujet. Le dernier paramètre optionnel est un masque à appliquer sur
+les pixels de l'image d'entrée. La chaine de traitement de l'outil,
+commence par sous échantillonner l'image en n bits, n < 8, puis
+construit l'histogramme 3d à partir des pixels présents dans le masque,
+si ce dernier existe et enfin sauvegarde des résultats et des images
+servant à la visualisation.
+
+* tools/labeling/histo: Construction de l'histogramme.
+
+
+Ce qu'il faut savoir sur l'outil de filtrage de l'histogramme. Tout
+d'abord, il prend en paramètre 6 arguments obligatoires. Les arguments
+sont la quantification utilisée par l'outil de création de
+l'histogramme, le chemin de l'histogramme à filtrer, le seuil utilisé
+pour le filtrage (c'est le volume minimal en dessous duquel
+l'information est jugée comme du bruit et donc ne doit pas passer), le
+chemin de l'histogramme filtré, le chemin de la projection en densité
+de l'histogramme et le chemin de la projection en couleurs
+majoritaires de l'histogramme. Se reporter au chapitre sur la
+visualisation pour comprendre les différentes projections. Le filtrage
+est un traitement très simple, il applique uniquement l'algorithme
+morphologique d'ouverture sur les attributs de volume. Imagine un
+histogramme en 1d, l'attribut de volume est alors la surface sous la
+courbe de l'histogramme. Une ouverture volumique consiste à supprimer
+tous les pics ayant un volume inférieur au seuil. Cela fonctionne très
+bien en général, toutefois, il y a des cas où les informations
+retournées ne sont pas celles attendues. Concrêtement, des composantes
+de volume inférieur au seuil sont retrouvées plus loin dans la chaine
+de traitement, ce qui contredit l'usage de l'ouverture
+morphologique. Il est difficile de définir ce qui se passe vraiment,
+il est possible qu'il y ait un bug ou simplement que le reste de ma
+chaine induise quelque fois ce résultat étrange. Honnêtement, je ne
+sais pas ce qui se passe. Le cas n'arrive pas fréquemment, donc il est
+très difficile d'isoler l'erreur.
+
+* tools/labeling/opening: Filtrage de l'histogramme.
+
+
+Ce qu'il faut savoir sur l'outil de labellisation. Tout d'abord, il
+prend 11 arguments dont le dernier est optionel. Les arguments sont
+l'image originale (nécessaire pour calculer la couleur moyenne des
+labels ==> réalité augmentée), la quantification utilisée
+précédemment, l'image préalablement quantifiée, l'histogramme
+original, l'histogramme filtré, le voisinage sur lequel effectué les
+opérations (c6, c18 ou c26), l'histogramme segmenté en 3d, la
+projection red/green associée, la colormap, l'image reconstruite des
+moyennes associé à chaque label et éventuellement un fichier décrivant
+les statistiques associés aux labels (couleur moyenne associé au
+label, plus nombre de pixels concernés dans l'image, plus pourcentage
+absolu et pourcentage sans tenir compte du fond). Le seul appel
+intéressant est la labellisation de l'histogramme filtré qui produit
+une image 3d de label. Tout le reste est de la tuyauterie pour faire
+de la rélatité augmentée. Par exemple pour formée l'image des moyennes
+associées à chaque label, il est nécessaire de construire l'image 2d
+des labels qui fait intervenir elle-même l'image d'entrée quantifiée
+et l'image originale. Idem pour la construction de la
+colormap. L'outil segmente l'histogramme filtré par la détermination
+des maxima régionnaux, autrement dit des zones de très fortes
+densités. Ces zones sont en général très petites, quelques pixels pas
+plus. C'est pourquoi l'outil suivant va nous servir à les étendre un
+peu.
+
+* tools/labeling/regmax: Segmentation de l'histogramme.
+
+
+Petite suprise désagréable, l'outil iz ne compile plus. La raison en
+est toute simple, il y a eu du mouvement dans les fonctions
+mln::transform::influence_zone_geodesic(). Un revamp un peu violent,
+avec une version
+mln::transform::influence_zone_geodesic_saturated(). J'ai corrigé le
+changement d'appel, mais cela ne suffit pas. Dans la méthode
+mln::transform::influence_zone_geodesic_fastest(), l.127, tu utilises
+la méthode at() pour une image 2d et là pas de chance, moi j'utilise
+cet algorithme pour une image de labels 3d (nous sommes dans un espace
+RGB quantifié en n bits, n < 8). Je ne veux surtout rien détruire dans
+scribo, donc je te laisse effectuer les changements qui s'imposent et
+je continue la documentation.
+
+Ce qu'il faut savoir sur iz. Tout d'abord cette routine prend 12
+arguments dont le dernier est optionel. Les arguments sont
+l'histogramme labelisé par l'outil précédent, la profondeur utilisée
+pour l'influence par zone géodésique (0 signifie l'infini), puis vient
+le voisinage 3d utilisé pour la propagation, puis l'image initiale,
+puis le degrée de quantification utilisé par tous les outils, puis le
+dump de l'histogramme, la colormap (utilisée pour la projection r/g
+avec segmentation, puis l'histogramme labelisé après propagation nommé
+iz et enfin la projection r/g, l'image reconstruite à l'aide des
+moyennes des classes et le fichier de statistiques intégrant la
+propagation des classes. La propagation a pour vocation d'agrandir les
+classes obtenues jusqu'Ã maintenant. C'est une information que l'on
+voit bien avec les changements dans les projections r/g.
+
+* tools/labeling/iz: Propagation des classes par zone d'influence.
+
+
+Comme le paramétrage est difficile, il est conseillé de relire les
+scripts des jeux de tests qui coordonnent l'appel de ces routines avec
+une sucession de paramètres cohérents. Je sais ce que tu vas me dire,
+c'est mal, il ne faut pas mettre d'images sur le dépot git. Dans
+l'absolu, je suis d'accord, mais aujourd'hui, le code iz est cassé et
+rejouer ces tests peut prendre énormément de temps, donc par facilité,
+je me contente des résultats que j'avais archivé et que tu seras
+content de trouver pour en inclure une partie dans ton rapport.
+
+Tout d'abord un jeu de répertoire de test en instance d'être lancé. Le
+répertoire porte le nom de l'image sur laquelle est effectué le
+test. On y trouvera l'image originale pleine résolution, et les deux
+masques de gradient fin et un peu plus épais. Pour faire le test, il
+suffit d'écrire le script comme dans doc/labeling/mp00307.
+
+* doc/labeling/mp00215c
+* doc/labeling/mp00234c
+* doc/labeling/mp00248c
+* doc/labeling/ta00031c
+* doc/labeling/ta00083c
+
+
+Puis, nous avons les tous premiers tests qui ont servi pour déterminer
+la quantification à utiliser et la méthode de propagation (infinie ou
+saturée). Il y a longtemps, pour ces tests, je disposais d'une chaine
+complète mais cette dernière c'est perdu dans la migration entre svn
+et git. Il n'y a donc pas de script shell qui lance les outils, par
+contre il existe un fichier de synthese qui explique exactement ce qui
+a avait été lancé et avec quels paramètres, histoire de pouvoir rejouer le test.
+
+* doc/labeling/cmp_method: Test sur le type de propagation à utiliser.
+* doc/labelling/cmp_quant: Test sur la quantification a utiliser.
+
+
+Puis, nous avons les tests effectués à l'aide d'un script. Lire les
+scripts pour situer correctement les binaires outils utilisés. Le
+premier jeu test avait pour but d'étudier la combinatoire des options
+et de choisir ensuite les paramètres qui vont bien. Il n'y a pas de
+certitude complète en la matière. Lire attentivement le fichier
+synthèse. Tout ces éléments ont été validés par théo. Je ne me rapelle
+plus du détail, mais j'ai rédigé tout ce que je pouvais. Le dernier
+répertoire n'a pas de fichier synthèse, je pense que l'étude était du
+même gabarit que le test précédent. J'en étais à tester la routine sur
+un maximum d'images pour voir si le jeu réduit de couleurs obtenues
+correspondait à nos attentes ou non. Les paramètres stables sont Ã
+rechercher dans les derniers répertoires mp00042c et mp00307c.
+
+* doc/labeling/mp00307c_bis: Test sur un grand nombre de combinaisons.
+* doc/labeling/mp00411c: Test sur l'altération des statistiques.
+* doc/labeling/mp00042c: Test sur la representativité des couleurs trouvées.
+* doc/labeling/mp00307c: Test sur la representativité des couleurs trouvées.
+
+
+Faire le changelog, il y a de l'aide dans git/doc/Changelog
+... et commiter
XI ANNOTATING
--------------
+--------------
==> to do
-a) La sauvegarde des images au format gnuplot shell
-* mln/io/plot/save_image_sh.hh: Librairie sauvegarde format gnuplot shell.
+* doc/annotating
+
+
-to do ...
+XI AUTRES ASPECTS DOCUMENTAIRES
+-------------------------------
+Ces exemples de codes sont livrés tels quels sans aucune documentation
+de ma part. Si tu as besoin de quelque chose, sert toi, tu les
+remanieras à ta sauce. Il n'y a pas de raison de les documenter, se
+serait disperser mes efforts vainement.
+* doc/examples/accu_color: Petit programme pour se bidouiller avec la couleur.
+* doc/examples/frac: Librairie pour manipuler des fractions sous milena.
+* doc/examples/hello_milena: Petit exemple allant avec la doc de milena.
+* doc/examples/hello_world: Test de la plateforme c++.
+* doc/examples/io: Rien de vraiment intéressant dans l'état actuel.
+* doc/examples/learn_milena: Autre exemple de base avec milena.
+* doc/examples/otsu: Petit programme Otsu.
+* doc/examples/stats: Exemple de manipulation d'accumulateurs.
+Voici deux exemples sous LaTex. Un jeu de test avec la confection de
+vecteur et de matrices pour relater les forrmules connues en espace
+3d. La version actuelle est dégradée par rapport à ce que j'avais pu
+écrire. J'étais arrivé à la mise au point d'un extracteur de valeurs
+propres mais je n'ai jamais pu retrouver cette version là , surement
+une erreur sous svn. Le second document devait présenter la
+documentation quick tour sous milena, mais j'avoue que c'est un
+lamentable échec, je n'ai pas pris le temps de le faire. Je pense que
+l'idée d'une documentation collaborative permettrait de répartir
+l'effort.
+* doc/formulae: LaTex directory.
+* doc/quick_tour: LaTex directory.
diff --git a/scribo/sandbox/green/demo/clustering/kmean1d/Makefile.am b/scribo/sandbox/green/demo/labeling/regional_maxima/Makefile.am
similarity index 100%
copy from scribo/sandbox/green/demo/clustering/kmean1d/Makefile.am
copy to scribo/sandbox/green/demo/labeling/regional_maxima/Makefile.am
diff --git a/scribo/sandbox/green/demo/labeling/regional_maxima/regional_maxima.cc b/scribo/sandbox/green/demo/labeling/regional_maxima/regional_maxima.cc
new file mode 100644
index 0000000..d0c524b
--- /dev/null
+++ b/scribo/sandbox/green/demo/labeling/regional_maxima/regional_maxima.cc
@@ -0,0 +1,198 @@
+// Copyright (C) 2007, 2008, 2009, 2010 EPITA 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.
+
+/// \file
+///
+/// This demonstrator is aimed to experiment the regional maxima
+/// method. regional_maxima.It first test the 3d histogram from an
+/// image and the number of colors which results. And in fact, doesn't
+/// use the regional_maxima routine. Too many parameters must be fixed
+/// and parts of the code has been commented. The last action of this
+/// program consists in counting the number of colors of each image in a
+/// directory. This source has been used to test the annotating image base.
+///
+/// \fixme At this time, the source is in a transitional step. It doesn't
+/// compile, something wrong with boost library. It doesn't matter, that's not
+/// an important file.
+
+
+#include <iostream>
+#include <sstream>
+#include <boost/filesystem.hpp>
+
+#include <mln/img_path.hh>
+
+#include <mln/accu/math/sum.hh>
+#include <mln/accu/math/count.hh>
+#include <mln/accu/stat/histo3d_rgb.hh>
+#include <mln/accu/stat/mean.hh>
+#include <mln/accu/stat/variance.hh>
+
+#include <mln/algebra/vec.hh>
+
+#include <mln/arith/diff_abs.hh>
+
+#include <mln/core/macros.hh>
+#include <mln/core/alias/neighb3d.hh>
+#include <mln/core/image/image2d.hh>
+#include <mln/core/image/image3d.hh>
+#include <mln/core/image/dmorph/image_if.hh>
+#include <mln/core/routine/initialize.hh>
+
+#include <mln/data/compute.hh>
+#include <mln/data/fill.hh>
+#include <mln/data/transform.hh>
+
+#include <mln/fun/v2v/rgb8_to_rgbn.hh>
+
+#include <mln/io/pgm/load.hh>
+#include <mln/io/pgm/save.hh>
+#include <mln/io/ppm/load.hh>
+#include <mln/io/ppm/save.hh>
+
+#include <mln/labeling/regional_maxima.hh>
+#include <mln/labeling/mean_values.hh>
+#include <mln/labeling/compute.hh>
+
+#include <mln/literal/colors.hh>
+
+#include <mln/morpho/opening/volume.hh>
+#include <mln/morpho/elementary/dilation.hh>
+
+#include <mln/opt/at.hh>
+
+#include <mln/pw/cst.hh>
+
+#include <mln/util/array.hh>
+#include <mln/util/timer.hh>
+
+#include <mln/value/label_8.hh>
+#include <mln/value/rgb8.hh>
+#include <mln/value/rgb.hh>
+#include <mln/value/int_u.hh>
+
+
+/// \brief This is the count method.
+///
+/// \param[in] image the colored image.
+///
+/// This function loads a color image (ppm) and count the colors after
+/// using the min volume processing on the 3d histogram. Percentage
+/// thresholding is in test. The file threshold.txt establishes the link
+/// between percentage and size in image.
+///
+// n < 8, n is the degree of quantification
+template <unsigned n>
+unsigned count_image_color(const std::string& image)
+{
+ typedef mln::value::label_8 t_lbl8;
+ typedef mln::value::int_u8 t_int_u8;
+ typedef mln::value::rgb8 t_rgb8;
+ typedef mln::value::rgb<n> t_rgbn;
+ typedef mln::image3d<t_lbl8> t_image3d_lbl8;
+ typedef mln::image2d<t_lbl8> t_image2d_lbl8;
+ typedef mln::image2d<t_rgb8> t_image2d_rgb8;
+ typedef mln::image2d<t_rgbn> t_image2d_rgbn;
+ typedef mln::image2d<t_int_u8> t_image2d_int_u8;
+ typedef mln::image3d<unsigned> t_histo3d;
+ typedef mln::image2d<unsigned> t_histo2d;
+ typedef mln::fun::v2v::rgb8_to_rgbn<n> t_rgb8_to_rgbn;
+ typedef mln::accu::meta::stat::histo3d_rgb t_histo3d_fun;
+ typedef mln::accu::meta::math::count t_count_fun;
+
+ t_image2d_rgb8 input_rgb8;
+ t_image2d_rgbn input_rgbn;
+ t_image2d_rgbn output_rgbn;
+ t_histo3d histo;
+ t_histo3d opened;
+ t_image3d_lbl8 label;
+ t_image2d_lbl8 label_img;
+ t_image3d_lbl8 dilated;
+ t_lbl8 n_labels;
+
+ mln::io::ppm::load(input_rgb8, image.c_str());
+
+ unsigned nb_pixel = input_rgb8.ncols() * input_rgb8.nrows();
+ unsigned min_volume = (unsigned)(nb_pixel * 0.054);
+
+ input_rgbn = mln::data::transform(input_rgb8, t_rgb8_to_rgbn());
+ histo = mln::data::compute(t_histo3d_fun(), input_rgbn);
+ return mln::data::compute(t_count_fun(), histo);
+
+ // return nb_pixel;
+ // opened = mln::morpho::opening::volume(histo, mln::c6(), min_volume);
+ // label = mln::labeling::regional_maxima(opened, mln::c6(), n_labels);
+ // return n_labels;
+}
+
+/// \brief The main function aimed at looping over the whole directory.
+///
+/// The main function is used to take care of file part in this
+/// sofware. It manages the directory scanning aspect while the last
+/// function does the image processing aspect. Statistics are
+/// generated (mean and variance) about the number of colors after using
+/// the min_volume routine. Some strange things happens with that routine
+/// sometimes.
+int main()
+{
+ typedef boost::filesystem::path t_path;
+ //typedef boost::filesystem::initial_path<t_path()> t_init_path;
+ typedef boost::filesystem::directory_iterator t_iter_path;
+
+ t_path full_path(ANNOTATING_1_TYPED_IMG_PATH);
+
+ std::cout << "entering " << full_path << std::endl;
+
+ if (//1 < argc &&
+ boost::filesystem::exists(full_path) &&
+ boost::filesystem::is_directory(full_path))
+ {
+ boost::filesystem::system_complete(full_path);
+ const t_iter_path end_iter;
+ unsigned count = 0;
+ unsigned sum1 = 0;
+ unsigned sum2 = 0;
+
+ for (t_iter_path dir_iter(full_path); end_iter != dir_iter; ++dir_iter)
+ {
+ unsigned val = count_image_color<5>(dir_iter->path().string());
+
+ ++count;
+ sum1 += val;
+ sum2 += val*val;
+
+ std::cout << dir_iter->path().string() << " => " << val << std::endl;
+ }
+
+ unsigned mean = sum1 / count;
+ unsigned var = sum2 / count - mean * mean;
+
+ std::cout << "mean : " << mean << std::endl;
+ std::cout << "var : " << var << std::endl;
+ }
+
+ return 0;
+}
+
diff --git a/milena/sandbox/green/demo/labeling/regional_maxima/thresholds.txt b/scribo/sandbox/green/demo/labeling/regional_maxima/thresholds.txt
similarity index 100%
copy from milena/sandbox/green/demo/labeling/regional_maxima/thresholds.txt
copy to scribo/sandbox/green/demo/labeling/regional_maxima/thresholds.txt
diff --git a/scribo/sandbox/green/demo/clustering/kmean1d/Makefile.am b/scribo/sandbox/green/demo/labeling/watershed/Makefile.am
similarity index 100%
copy from scribo/sandbox/green/demo/clustering/kmean1d/Makefile.am
copy to scribo/sandbox/green/demo/labeling/watershed/Makefile.am
diff --git a/milena/sandbox/green/tests/accu/stat/histo1d/gaussian.sh b/scribo/sandbox/green/demo/labeling/watershed/gaussian.sh
similarity index 100%
copy from milena/sandbox/green/tests/accu/stat/histo1d/gaussian.sh
copy to scribo/sandbox/green/demo/labeling/watershed/gaussian.sh
diff --git a/scribo/sandbox/green/demo/labeling/watershed/watershed.cc b/scribo/sandbox/green/demo/labeling/watershed/watershed.cc
new file mode 100644
index 0000000..a9289f7
--- /dev/null
+++ b/scribo/sandbox/green/demo/labeling/watershed/watershed.cc
@@ -0,0 +1,360 @@
+// Copyright (C) 2007, 2008, 2009, 2010 EPITA 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.
+
+/// \file
+///
+/// This demonstrator is the first step before using
+/// regional_maxima. Its purpose is to work on histogram filtering and
+/// on the whole image processing chain.
+///
+/// \fixme: this source doesn't compile. I've no time to fix it. It's not
+/// so important because it's just a basic sample, just keep in mind the
+/// method to reach the result, it will be reuse for regional_maxima.
+
+#include <iostream>
+#include <sstream>
+
+#include <mln/accu/stat/histo1d.hh>
+
+#include <mln/arith/revert.hh>
+
+#include <mln/core/alias/neighb1d.hh>
+#include <mln/core/alias/window1d.hh>
+#include <mln/core/macros.hh>
+#include <mln/core/image/image1d.hh>
+#include <mln/core/image/image2d.hh>
+#include <mln/core/routine/initialize.hh>
+
+#include <mln/data/compute.hh>
+#include <mln/data/transform.hh>
+
+#include <mln/io/pgm/load.hh>
+#include <mln/io/pgm/save.hh>
+#include <mln/io/ppm/save.hh>
+#include <mln/io/plot/save_image_sh.hh>
+
+#include <mln/labeling/colorize.hh>
+#include <mln/labeling/mean_values.hh>
+#include <mln/labeling/regional_maxima.hh>
+
+#include <mln/linear/convolve.hh>
+//#include <mln/linear/gaussian.hh>
+
+#include <mln/literal/colors.hh>
+
+#include <mln/morpho/elementary/closing.hh>
+#include <mln/morpho/elementary/dilation.hh>
+#include <mln/morpho/elementary/opening.hh>
+#include <mln/morpho/opening/structural.hh>
+#include <mln/morpho/watershed/flooding.hh>
+
+#include <mln/img_path.hh>
+
+#include <mln/value/int_u8.hh>
+#include <mln/value/rgb8.hh>
+#include <mln/value/label_8.hh>
+
+#include <mln/win/disk1d.hh>
+
+
+/// \brief Compute the gaussian probability to obtain a given value.
+///
+/// \param[in] x the value from which we want the probability.
+/// \param[in] mean the mean parameter of the gaussian distribution.
+/// \param[in] sigma the sqrt(variance) parameter of the gaussian.
+/// \return the probability to obtain the x value.
+///
+/// Implements the standard 1d equation of the gaussian.
+double gaussian_distribution(const double x,
+ const double mean,
+ const 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;
+}
+
+
+/// \brief Make a 1d gaussian filter.
+///
+/// \param[out] ws the window (filter) where to put the probability values.
+/// \param[in] size the size of the filter.
+/// \param[in] sigma the gaussian parameter for the standard deviation.
+/// \return the probability to obtain the x value.
+///
+/// Approach the gaussian distribution for a few discrete sites, and
+/// then normilize the results to be sure that the sum obtain 1.
+void gaussian_filter(double ws[], const unsigned size, const 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;
+}
+
+
+/// \brief Merge input image with label one.
+///
+/// \param[in] input the window (filter) where to put the probability values.
+/// \param[in] label the size of the filter.
+/// \return the merged image.
+///
+/// This function build a new image in which the input pixels are
+/// replaced by the label associated to their grey level.
+mln::image2d<mln::value::label_8>
+merge(const mln::image2d<mln::value::int_u8>& input,
+ const mln::image1d<mln::value::label_8>& label)
+{
+ 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;
+ }
+
+ return output;
+}
+
+/// \brief This is the wathersed method for segmenting the histogram.
+///
+/// \param[in] image the input image.
+///
+/// The function returns nothing but writes different images on the
+/// filesystem. The 3 outputs are the image label, the random coloring
+/// of the image label and the average tone of the label image
+/// (replace every label by the grey average of the group to which
+/// it's belong to) .
+void do_demo(const std::string& image)
+{
+ typedef mln::value::int_u8 t_int_u8;
+ typedef mln::value::label_8 t_lbl8;
+ typedef mln::value::rgb8 t_rgb8;
+ typedef mln::image1d<t_lbl8> t_image1d_lbl8;
+ typedef mln::image2d<t_rgb8> t_image2d_rgb8;
+ typedef mln::image2d<t_int_u8> t_image2d_int_u8;
+ typedef mln::image2d<t_lbl8> t_image2d_lbl8;
+ typedef mln::image1d<unsigned> t_image1d_unsigned;
+
+ t_image2d_int_u8 img;
+ t_image1d_unsigned histo;
+ t_image1d_unsigned filtered;
+ t_image1d_unsigned reverted;
+ t_image1d_lbl8 label;
+ t_image2d_lbl8 output;
+ t_image2d_int_u8 mean;
+ t_image2d_rgb8 colorized;
+ t_lbl8 n_labels;
+
+
+ //---------------------------------------------------------------------------
+ // LOADING PHASE
+ //---------------------------------------------------------------------------
+ mln::io::pgm::load(img, image.c_str());
+ mln::io::pgm::save(img, "img.pgm");
+
+
+ //---------------------------------------------------------------------------
+ // HISTO COMPUTING PHASE
+ //---------------------------------------------------------------------------
+ histo = mln::data::compute(mln::accu::meta::stat::histo1d(), img);
+ mln::io::plot::save_image_sh(histo, "histo.sh");
+
+
+ //---------------------------------------------------------------------------
+ // HISTO FILTERING PHASE
+ //---------------------------------------------------------------------------
+
+ // a) GAUSSIAN FILTERING
+ double ws[41];
+ gaussian_filter(ws, 41, 6.0);
+ filtered = mln::linear::convolve(histo, mln::make::w_window1d(ws));
+
+ // b) MORPHOLOGICAL ELEMENTARY OPENING
+ // filtered = mln::morpho::elementary::opening(histo, mln::c4());
+
+ // c) MORPHOLOGICAL STRUCTURAL OPENING (C4,C8 ??)
+ // filtered = mln::morpho::opening::structural(histo, mln::win_c8p());
+
+ // d) MORPHOLOGICAL STRUCTURAL DISK OPENING (SIZE = 11/21/31/41/51 ??)
+ // mln::win::disk1d disk1d(21);
+ // filtered = mln::morpho::opening::structural(histo, disk1d);
+
+ mln::io::plot::save_image_sh(filtered, "filtered.sh");
+
+
+ //---------------------------------------------------------------------------
+ // HISTO LABELING PHASE
+ //---------------------------------------------------------------------------
+ // a) watershed
+ reverted = mln::arith::revert(histo);
+ label = mln::morpho::watershed::flooding(reverted, mln::c4(), n_labels);
+ // b) regional maxima
+ // label = mln::labeling::regional_maxima(opened, mln::c8(), n_labels);
+ mln::io::pgm::save(label, "label.pgm");
+
+
+ //---------------------------------------------------------------------------
+ // FUZZY PHASE
+ //---------------------------------------------------------------------------
+ dilated = mln::morpho::elementary::dilation(label, mln::c8());
+ mln::io::pgm::save(dilated, "dilated.pgm");
+
+
+ //---------------------------------------------------------------------------
+ // OUTPUT PHASE
+ //---------------------------------------------------------------------------
+ output = merge(house_rg8, label);
+ mean = mln::labeling::mean_values(img, label, nlabels);
+ colorized = mln::labeling::colorize(rgb8(), label);
+
+ mln::io::pgm::save(output, "output.pgm");
+ mln::io::pgm::save(mean, "mean.pgm");
+ mln::io::ppm::save(colorized, "colorized.ppm");
+}
+
+
+/// \brief This is the launcher of the method.
+///
+/// \param[in] image the input image.
+///
+/// The launcher is the good place for debugging input arguments or
+/// setting defaults one.
+void demo(const std::string& image = SCRIBO_PGM_IMG_PATH"/mp00082c_50p.pgm")
+{
+ std::cout << "----------------------------------------" << std::endl;
+ std::cout << "Launching the demo with these parameters" << std::endl;
+ std::cout << "image : " << image << std::endl;
+ std::cout << "----------------------------------------" << std::endl;
+
+ do_demo(image);
+}
+
+
+/// \bief The usage function of the binary.
+///
+/// \param[in] argc the binary number of arguments.
+/// \param[in] args the binary array of arguments.
+///
+/// This binary requires one input image to work. It is a grey level
+/// image in pgm format.
+void usage(const int argc, const char *args[])
+{
+ std::cout << "----------------------------------------" << std::endl;
+ std::cout << "argc : " << argc << std::endl;
+
+ for (int i = 0; i < argc; ++i)
+ std::cout << "args[" << i << "] : " << args[i] << std::endl;
+
+ std::cout << "----------------------------------------" << std::endl;
+ std::cout << "usage: wateshed [image]" << std::endl;
+ std::cout << "pgm image (image to label)" << std::endl;
+ std::cout << "----------------------------------------" << std::endl;
+}
+
+
+/// \brief Convert a c string parameter to string object like.
+///
+/// \param[in] status the flag to prevent bad work.
+/// \param[in] arg the c string to convert in string object.
+/// \param[out] val the return string object.
+/// \return a flag to say if every thing goes well.
+///
+/// Convert a c string (char *) in string object (std::string) in order
+/// to simplify some string operations.
+bool char_to_string(const bool status, const char *arg, std::string& val)
+{
+ bool result = false;
+
+ if (status)
+ {
+ std::istringstream arg_stream(arg);
+
+ arg_stream >> val;
+
+ return !arg_stream.fail();
+ }
+
+ return result;
+}
+
+
+/// \brief Segment by the watershed method histogram space.
+///
+/// \param[in] img the input image.
+/// \return merge image.
+///
+/// This is the main entry of the program. It takes an image as input
+/// parameter and computes its histogram. The method segments the
+/// histogram in order to build color classes (even we stay in grey
+/// level). Merging image is returned where pixels have been replaced
+/// by some attribute of the class (like the average color).
+int main(const int argc, const char *args[])
+{
+ std::string image("top");
+ bool status = true;
+
+ switch (argc)
+ {
+ case 2: status = char_to_string(status, args[1], image); break;
+ case 1: status = true; break;
+ default: status = false;
+ }
+
+ if (status)
+ {
+ switch (argc)
+ {
+ case 1: demo(); break;
+ case 2: demo(image); break;
+ }
+ }
+ else
+ usage(argc, args);
+
+ return 0;
+}
diff --git a/milena/sandbox/green/doc/annotating/class.txt b/scribo/sandbox/green/doc/annotating/class.txt
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diff --git a/milena/sandbox/green/doc/examples/frac/gcd.hh b/scribo/sandbox/green/doc/examples/frac/gcd.hh
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diff --git a/milena/sandbox/green/doc/examples/hello_milena/Makefile.am b/scribo/sandbox/green/doc/examples/hello_milena/Makefile.am
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diff --git a/milena/sandbox/green/doc/examples/hello_world/print.cc b/scribo/sandbox/green/doc/examples/hello_world/print.cc
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diff --git a/milena/sandbox/green/doc/examples/io/Makefile.am b/scribo/sandbox/green/doc/examples/io/Makefile.am
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diff --git a/milena/sandbox/green/doc/examples/hello_milena/Makefile.am b/scribo/sandbox/green/doc/examples/learn_milena/Makefile.am
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diff --git a/milena/sandbox/green/doc/examples/hello_milena/Makefile.am b/scribo/sandbox/green/doc/examples/otsu/Makefile.am
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diff --git a/milena/sandbox/green/doc/formulae/formulae.tex b/scribo/sandbox/green/doc/formulae/formulae.tex
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diff --git a/scribo/sandbox/green/exp/regional_maxima/Makefile.am b/scribo/sandbox/green/exp/regional_maxima/Makefile.am
new file mode 100644
index 0000000..68bb53e
--- /dev/null
+++ b/scribo/sandbox/green/exp/regional_maxima/Makefile.am
@@ -0,0 +1,153 @@
+#
+# Generic Makefile
+#
+
+#########
+# TOOLS #
+#########
+
+LOADLIBES= -lboost_filesystem
+INCLUDES1= -I$(HOME)/git/olena/scribo/sandbox/green
+INCLUDES2= -I$(HOME)/git/olena/milena
+INCLUDES= $(INCLUDES1) $(INCLUDES2)
+CXXFLAGS= -ggdb -O0 -Wall -W -pedantic -ansi -pipe $(INCLUDES)
+#CXXFLAGS= -DNDEBUG -O1 -Wall -W -pedantic -ansi -pipe $(INCLUDES)
+#CXXFLAGS= -DNDEBUG -O3 -Wall -W -pedantic -ansi -pipe $(INCLUDES)
+ECHO= echo
+RM= rm
+MKDIR= mkdir -p
+CP= cp
+
+SOURCE_PATTERN= green/exp
+BUILD__PATTERN= green/build/exp
+
+
+ifeq ($(findstring $(BUILD__PATTERN),$(PWD)), $(BUILD__PATTERN))
+# Case where make is done from build directory.
+SOURCE_DIR= $(subst $(BUILD__PATTERN),$(SOURCE_PATTERN),$(PWD))
+BUILD__DIR= $(PWD)/
+else
+# Case where make is done from source directory.
+SOURCE_DIR= $(PWD)/
+BUILD__DIR= $(subst $(SOURCE_PATTERN),$(BUILD__PATTERN),$(PWD))
+endif
+
+SRC= $(notdir $(wildcard $(SOURCE_DIR)/*.cc))
+OLD= $(notdir $(wildcard $(SOURCE_DIR)/*~))
+OBJ= $(patsubst %.cc,%.o,$(SRC))
+SOURCE_MAKEFILE=Makefile.am
+BUILD__MAKEFILE=Makefile
+TARGET_FILE= $(notdir $(PWD))
+SOURCE_FILES= $(notdir $(wildcard $(SOURCE_DIR)/*.*))
+BUILD__FILES= $(filter-out $(SRC) $(SOURCE_MAKEFILE), $(SOURCE_FILES))
+
+BUILD__F_PATH= $(addprefix $(BUILD__DIR)/,$(BUILD__FILES))
+SOURCE_F_PATH= $(addprefix $(SOURCE_DIR)/,$(SOURCE_FILES))
+
+BUILD__M_PATH= $(addprefix $(BUILD__DIR)/,$(BUILD__MAKEFILE))
+SOURCE_M_PATH= $(addprefix $(SOURCE_DIR)/,$(SOURCE_MAKEFILE))
+
+TARGET_F_PATH= $(addprefix $(BUILD__DIR)/,$(TARGET_FILE))
+OBJ_F_PATH= $(addprefix $(BUILD__DIR)/,$(OBJ))
+SRC_F_PATH= $(addprefix $(SOURCE_DIR)/,$(SRC))
+OLD_F_PATH= $(addprefix $(SOURCE_DIR)/,$(OLD))
+
+#############
+# BOOTSTRAP #
+#############
+
+
+bootstrap: $(BUILD__DIR) $(BUILD__F_PATH) $(BUILD__M_PATH)
+
+# Create, if nessary, the destination directory
+$(BUILD__DIR):
+ $(MKDIR) $(BUILD__DIR)
+
+# Copy, if nessary, all the files, except the Makefile.am
+$(BUILD__F_PATH): $(SOURCE_F_PATH)
+ $(CP) $(addprefix $(SOURCE_DIR),$(@F)) $@
+
+# Copy if nessary, the Makefile.am into Makefile
+$(BUILD__M_PATH): $(SOURCE_M_PATH)
+ $(CP) $(SOURCE_M_PATH) $(BUILD__M_PATH)
+
+
+#######
+# ALL #
+#######
+
+# We assume that the call is done from the build directory.
+# With the directive vpath, hidden files are found in the source directory.
+
+all: $(TARGET_F_PATH)
+
+
+$(TARGET_F_PATH): $(OBJ_F_PATH)
+ $(LINK.cc) $< $(LOADLIBES) $(LDLIBS) -o $@
+
+$(OBJ_F_PATH):$(SRC_F_PATH)
+ $(COMPILE.cc) $(OUTPUT_OPTION) $<
+
+
+#########
+# CLEAN #
+#########
+
+# Force every time the deletion
+clean: clean_target clean_obj clean_dst clean_old #clean_make
+
+
+clean_target:
+ -@$(RM) $(TARGET_F_PATH) &> /dev/null
+
+clean_obj:
+ -@$(RM) $(OBJ_F_PATH) &> /dev/null
+
+clean_dst:
+ -@$(RM) $(BUILD_F_PATH) &> /dev/null
+
+clean_make:
+ -@$(RM) $(BUILD_M_PATH) &> /dev/null
+
+clean_old:
+ -@$(RM) $(OLD_F_PATH) &> /dev/null
+
+
+#########
+# PRINT #
+#########
+
+print: print_tools print_bootstrap
+
+print_tools:
+ @$(ECHO) "HOME = $(HOME)"
+ @$(ECHO) "INCLUDES = $(INCLUDES)"
+ @$(ECHO) "CXXFLAGS = $(CXXFLAGS)"
+ @$(ECHO) "ECHO = $(ECHO)"
+ @$(ECHO) "RM = $(RM)"
+ @$(ECHO) "MKDIR = $(MKDIR)"
+ @$(ECHO) "CP = $(CP)"
+ @$(ECHO)
+
+print_bootstrap:
+ @$(ECHO) "PWD = $(PWD)"
+ @$(ECHO) "SOURCE_PATTERN = $(SOURCE_PATTERN)"
+ @$(ECHO) "BUILD__PATTERN = $(BUILD__PATTERN)"
+ @$(ECHO) "SOURCE_DIR = $(SOURCE_DIR)"
+ @$(ECHO) "BUILD__DIR = $(BUILD__DIR)"
+ @$(ECHO) "SOURCE_MAKEFILE = $(SOURCE_MAKEFILE)"
+ @$(ECHO) "BUILD__MAKEFILE = $(BUILD__MAKEFILE)"
+ @$(ECHO) "TARGET_FILE = $(TARGET_FILE)"
+ @$(ECHO) "SOURCE_FILES = $(SOURCE_FILES)"
+ @$(ECHO) "SOURCE_F_PATH = $(SOURCE_F_PATH)"
+ @$(ECHO) "BUILD__FILES = $(BUILD__FILES)"
+ @$(ECHO) "BUILD__F_PATH = $(BUILD__F_PATH)"
+ @$(ECHO) "BUILD__M_PATH = $(BUILD__M_PATH)"
+ @$(ECHO) "SOURCE_M_PATH = $(SOURCE_M_PATH)"
+ @$(ECHO) "SRC = $(SRC)"
+ @$(ECHO) "OBJ = $(OBJ)"
+ @$(ECHO) "OLD = $(OLD)"
+ @$(ECHO) "SRC_F_PATH = $(SRC_F_PATH)"
+ @$(ECHO) "OBJ_F_PATH = $(OBJ_F_PATH)"
+ @$(ECHO) "OLD_F_PATH = $(OLD_F_PATH)"
+ @$(ECHO)
diff --git a/scribo/sandbox/green/exp/regional_maxima/regional_maxima.cc b/scribo/sandbox/green/exp/regional_maxima/regional_maxima.cc
new file mode 100644
index 0000000..0cd8389
--- /dev/null
+++ b/scribo/sandbox/green/exp/regional_maxima/regional_maxima.cc
@@ -0,0 +1,196 @@
+// Copyright (C) 2007, 2008, 2009, 2010 EPITA 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.
+
+/// \file
+///
+/// This demonstrator is aimed to experiment the regional maxima
+/// method. regional_maxima.It first test the 3d histogram from an
+/// image and the number of colors which results. And in fact, doesn't
+/// use the regional_maxima routine. Too many parameters must be fixed
+/// and parts of the code has been commented. The last action of this
+/// program consists in counting the number of colors of each image in a
+/// directory. This source has been used to test the annotating image base.
+
+#include <iostream>
+#include <sstream>
+#include <boost/filesystem.hpp>
+
+#include <mln/img_path.hh>
+
+#include <mln/accu/math/sum.hh>
+#include <mln/accu/math/count.hh>
+#include <mln/accu/stat/histo3d_rgb.hh>
+#include <mln/accu/stat/mean.hh>
+#include <mln/accu/stat/variance.hh>
+
+#include <mln/algebra/vec.hh>
+
+#include <mln/arith/diff_abs.hh>
+
+#include <mln/core/macros.hh>
+#include <mln/core/alias/neighb3d.hh>
+#include <mln/core/image/image2d.hh>
+#include <mln/core/image/image3d.hh>
+#include <mln/core/image/dmorph/image_if.hh>
+#include <mln/core/routine/initialize.hh>
+
+#include <mln/data/compute.hh>
+#include <mln/data/fill.hh>
+#include <mln/data/transform.hh>
+
+#include <mln/fun/v2v/rgb8_to_rgbn.hh>
+
+#include <mln/io/pgm/load.hh>
+#include <mln/io/pgm/save.hh>
+#include <mln/io/ppm/load.hh>
+#include <mln/io/ppm/save.hh>
+
+#include <mln/labeling/regional_maxima.hh>
+#include <mln/labeling/mean_values.hh>
+#include <mln/labeling/compute.hh>
+
+#include <mln/literal/colors.hh>
+
+#include <mln/morpho/opening/volume.hh>
+#include <mln/morpho/elementary/dilation.hh>
+
+#include <mln/opt/at.hh>
+
+#include <mln/pw/cst.hh>
+
+#include <mln/util/array.hh>
+#include <mln/util/timer.hh>
+
+#include <mln/value/label_8.hh>
+#include <mln/value/rgb8.hh>
+#include <mln/value/rgb.hh>
+#include <mln/value/int_u.hh>
+
+/// \brief This is the count method.
+///
+/// \param[in] image the colored image.
+///
+/// This function loads a color image (ppm) and count the colors after
+/// using the min volume processing on the 3d histogram. Percentage
+/// thresholding is in test. The file threshold.txt establishes the link
+/// between percentage and size in image.
+///
+// n < 8, n is the degree of quantification
+template <unsigned n>
+unsigned count_image_color(const std::string& image)
+{
+ typedef mln::value::label_8 t_lbl8;
+ typedef mln::value::int_u8 t_int_u8;
+ typedef mln::value::rgb8 t_rgb8;
+ typedef mln::value::rgb<n> t_rgbn;
+ typedef mln::image3d<t_lbl8> t_image3d_lbl8;
+ typedef mln::image2d<t_lbl8> t_image2d_lbl8;
+ typedef mln::image2d<t_rgb8> t_image2d_rgb8;
+ typedef mln::image2d<t_rgbn> t_image2d_rgbn;
+ typedef mln::image2d<t_int_u8> t_image2d_int_u8;
+ typedef mln::image3d<unsigned> t_histo3d;
+ typedef mln::image2d<unsigned> t_histo2d;
+ typedef mln::fun::v2v::rgb8_to_rgbn<n> t_rgb8_to_rgbn;
+ typedef mln::accu::meta::stat::histo3d_rgb t_histo3d_fun;
+ typedef mln::accu::meta::math::count t_count_fun;
+
+ t_image2d_rgb8 input_rgb8;
+ t_image2d_rgbn input_rgbn;
+ t_image2d_rgbn output_rgbn;
+ t_histo3d histo;
+ t_histo3d opened;
+ t_image3d_lbl8 label;
+ t_image2d_lbl8 label_img;
+ t_image3d_lbl8 dilated;
+ t_lbl8 n_labels;
+
+ mln::io::ppm::load(input_rgb8, image.c_str());
+
+ unsigned nb_pixel = input_rgb8.ncols() * input_rgb8.nrows();
+ unsigned min_volume = (unsigned)(nb_pixel * 0.054);
+
+ input_rgbn = mln::data::transform(input_rgb8, t_rgb8_to_rgbn());
+ histo = mln::data::compute(t_histo3d_fun(), input_rgbn);
+ return mln::data::compute(t_count_fun(), histo);
+ // return nb_pixel;
+ // opened = mln::morpho::opening::volume(histo, mln::c6(), min_volume);
+ // label = mln::labeling::regional_maxima(opened, mln::c6(), n_labels);
+ // return n_labels;
+}
+
+
+/// \brief The main function aimed at looping over the whole directory.
+///
+/// The main function is used to take care of file part in this
+/// sofware. It manages the directory scanning aspect while the last
+/// function does the image processing aspect. Statistics are
+/// generated (mean and variance) about the number of colors after using
+/// the min_volume routine. Some strange things happens with that routine
+/// sometimes.
+int main()
+{
+ typedef boost::filesystem::path t_path;
+ //typedef boost::filesystem::initial_path<t_path()> t_init_path;
+ typedef boost::filesystem::directory_iterator t_iter_path;
+
+ t_path full_path(ANNOTATING_1_TYPED_IMG_PATH);
+
+ std::cout << "entering " << full_path << std::endl;
+
+ if (//1 < argc &&
+ boost::filesystem::exists(full_path) &&
+ boost::filesystem::is_directory(full_path))
+ {
+ boost::filesystem::system_complete(full_path);
+ const t_iter_path end_iter;
+ unsigned count = 0;
+ unsigned sum1 = 0;
+ unsigned sum2 = 0;
+
+ for (t_iter_path dir_iter(full_path); end_iter != dir_iter; ++dir_iter)
+ {
+ unsigned val = count_image_color<5>(dir_iter->path().string());
+
+ ++count;
+ sum1 += val;
+ sum2 += val*val;
+
+ std::cout << dir_iter->path().string() << " => " << val << std::endl;
+ // FIXME NB COULEURS BRUTES
+ // FIXME NB DE COULEURS
+ // FIXME LISTE DES COULEURS
+ // IMPORTANCES
+ }
+
+ unsigned mean = sum1 / count;
+ unsigned var = sum2 / count - mean * mean;
+
+ std::cout << "mean : " << mean << std::endl;
+ std::cout << "var : " << var << std::endl;
+ }
+
+ return 0;
+}
+
diff --git a/milena/sandbox/green/demo/labeling/regional_maxima/thresholds.txt b/scribo/sandbox/green/exp/regional_maxima/thresholds.txt
similarity index 100%
copy from milena/sandbox/green/demo/labeling/regional_maxima/thresholds.txt
copy to scribo/sandbox/green/exp/regional_maxima/thresholds.txt
diff --git a/scribo/sandbox/green/mln/display/display_histo.hh b/scribo/sandbox/green/mln/display/display_histo.hh
index ef47182..d48f47f 100644
--- a/scribo/sandbox/green/mln/display/display_histo.hh
+++ b/scribo/sandbox/green/mln/display/display_histo.hh
@@ -47,6 +47,64 @@
/// the blue dimension (green and blue composantes are being correlated). In
/// fact, we sum in along the blue direction. Then, we stretch value to feet
/// pgm format.
+///
+/// This is the sample code to use the red/green visualization.
+///
+/// \fixme There is a lot of routines in display_histo.hh, but only
+/// two of them have been call here. Stuff to complete.
+///
+/// #include <iostream>
+/// #include <mln/accu/stat/histo3d_rgb.hh>
+/// #include <mln/core/macros.hh>
+/// #include <mln/core/image/image2d.hh>
+/// #include <mln/core/image/image3d.hh>
+/// #include <mln/data/compute.hh>
+/// #include <mln/data/transform.hh>
+/// #include <mln/display/display_histo.hh>
+/// #include <mln/fun/v2v/rgb8_to_rgbn.hh>
+/// #include <mln/img_path.hh>
+/// #include <mln/io/ppm/load.hh>
+/// #include <mln/io/pgm/save.hh>
+/// #include <mln/io/ppm/save.hh>
+/// #include <mln/literal/colors.hh>
+/// #include <mln/value/rgb8.hh>
+/// #include <mln/value/rgb.hh>
+///
+/// int main()
+/// {
+/// typedef mln::value::int_u8 t_int_u8;
+/// typedef mln::value::int_u<4> t_int_u4;
+/// typedef mln::value::rgb8 t_rgb8;
+/// typedef mln::value::rgb<4> t_rgb4;
+/// typedef mln::image2d<t_int_u8> t_image2d_int_u8;
+/// typedef mln::image2d<t_int_u4> t_image2d_int_u4;
+/// typedef mln::image2d<t_rgb8> t_image2d_rgb8;
+/// typedef mln::image2d<t_rgb4> t_image2d_rgb4;
+/// typedef mln::image2d<bool> t_image2d_bool;
+/// typedef mln::image3d<unsigned> t_histo3d;
+/// typedef mln::fun::v2v::rgb8_to_rgbn<4> t_rgb8_to_rgb4;
+/// typedef mln::accu::meta::stat::histo3d_rgb t_histo3d_fun;
+///
+/// t_image2d_rgb8 i0_input; // input rgb8
+/// t_image2d_rgb4 i1_input; // input rgbn
+/// t_histo3d h1_input; // histo input
+/// t_image2d_int_u8 p1_histo1;// histo proj1
+/// t_image2d_rgb4 p1_histo2;// histo proj2
+/// t_rgb4 red(mln::literal::red);
+///
+/// mln::io::ppm::load(i0_input, OLENA_IMG_PATH"/lena.ppm");
+///
+/// i1_input = mln::data::transform(i0_input, t_rgb8_to_rgb4());
+/// h1_input = mln::data::compute(t_histo3d_fun(), i1_input);
+/// p1_histo1 = mln::display::display_histo3d_unsigned(h1_input);
+/// p1_histo2 = mln::display::display3_histo3d_unsigned(h1_input, red);
+///
+/// mln::io::pgm::save(p1_histo1, "proj1.pgm");
+/// mln::io::ppm::save(p1_histo2, "proj2.ppm");
+///
+/// return 0;
+/// }
+
namespace mln
@@ -55,26 +113,100 @@ namespace mln
namespace display
{
- // Forward declaration.
+ /// \brief Allow the visualization of the density of the 3d histogram.
+ ///
+ /// Direction r = 1
+ /// Direction g = 2
+ /// Direction b = 0
+ ///
+ /// \parameter[in] histo the histogram in 3d.
+ /// \result return the projection of the histogram in 2d.
+ ///
+ /// The 3d histogram is projected in red/green space by
+ /// accumulating around the the blue dimension (green and blue
+ /// composantes are being correlated). In fact, we sum along the
+ /// blue direction and take the log of value. Then, we stretch
+ /// value to feet pgm format.
image2d<value::int_u8>
display_histo3d_unsigned(const image3d<unsigned>& histo);
+
+ /// \brief Allow the visualization of the important color of the 3d histo.
+ ///
+ /// Direction r = 1
+ /// Direction g = 2
+ /// Direction b = 0
+ ///
+ /// \parameter[in] histo the histogram in 3d.
+ /// \parameter[in] ambiguous_color the color when no max is found.
+ /// \result return the projection of the histogram in 2d.
+ ///
+ /// The 3d histogram is projected in red/green space. In the blue
+ /// direction we check the max blue component. The position in
+ /// this blue axis is returned in the projection image.
template <unsigned n>
image2d< value::int_u<n> >
display2_histo3d_unsigned(const image3d<unsigned>& histo,
const value::int_u<n> ambiguous_color);
+
+ /// \brief Allow the visualization of the color of the 3d segmented histo.
+ ///
+ /// Direction r = 1
+ /// Direction g = 2
+ /// Direction b = 0
+ ///
+ /// \parameter[in] histo the histogram in 3d.
+ /// \parameter[in] label the label image to associate the result with.
+ /// \parameter[in] ambiguous_color the color when no max is found.
+ /// \result return the projection of the histogram in 2d.
+ ///
+ /// The 3d histogram is projected in red/green space. In the blue
+ /// direction we check the max blue component. The position in
+ /// this blue axis is associated to a segmented label and this label
+ /// is returned in the projection image.
template <unsigned n>
image2d<value::label_8>
display2_histo3d_unsigned(const image3d<unsigned>& histo,
const image3d<value::label_8>& label,
const value::label_8 ambiguous_label);
+
+ /// \brief Allow the visualization with color of the 3d histo.
+ ///
+ /// Direction r = 1
+ /// Direction g = 2
+ /// Direction b = 0
+ ///
+ /// \parameter[in] histo the histogram in 3d.
+ /// \parameter[in] ambiguous_color the color when no max is found.
+ /// \result return the projection of the histogram in 2d.
+ ///
+ /// The 3d histogram is projected in red/green space. In the blue
+ /// direction we check the max blue component. The position is used
+ /// to build a rgb color and put it as a returned value in projection image.
template <unsigned n>
image2d< value::rgb<n> >
display3_histo3d_unsigned(const image3d<unsigned>& histo,
const value::rgb<n> ambiguous_color);
+
+ /// \brief Allow the visualization with color of the 3d segmented histo.
+ ///
+ /// Direction r = 1
+ /// Direction g = 2
+ /// Direction b = 0
+ ///
+ /// \parameter[in] histo the histogram in 3d.
+ /// \parameter[in] label the label image to associte the result with.
+ /// \parameter[in] pal the color indexed list to associate to the label.
+ /// \parameter[in] ambiguous_color the color when no max is found.
+ /// \result return the projection of the histogram in 2d.
+ ///
+ /// The 3d histogram is projected in red/green space. In the blue
+ /// direction we check the max blue component. The position is used
+ /// to find the label associate to it and then the color associated to
+ /// this label. That's the information we return in the projection image.
template <unsigned n>
image2d< value::rgb8 >
display3_histo3d_unsigned(const image3d<unsigned>& histo,
@@ -84,21 +216,6 @@ namespace mln
#ifndef MLN_INCLUDE_ONLY
- /// \brief Allow the visualization of a 3d histogram by projection.
- ///
- /// The 3d histogram is projected in red/green space by
- /// accumulating around the the blue dimension (green and blue
- /// composantes are being correlated). In fact, we sum along
- /// the blue direction. Then, we stretch value to feet pgm
- /// format.
- /// Direction r = 1
- /// Direction g = 2
- /// Direction b = 0
- ///
- /// \parameter[in] histo the histogram in 3d.
- /// \result return a equivalent 2d image.
-
- // FIXME : display_shape [in int_u8]
image2d<value::int_u8>
display_histo3d_unsigned(const image3d<unsigned>& histo)
{
diff --git a/scribo/sandbox/green/mln/display/project_histo.hh b/scribo/sandbox/green/mln/display/project_histo.hh
index 30bcd6d..36a5542 100644
--- a/scribo/sandbox/green/mln/display/project_histo.hh
+++ b/scribo/sandbox/green/mln/display/project_histo.hh
@@ -49,9 +49,71 @@
/// \file
///
-/// \brief Allow the visualization of 3d histogram.
-/// The 3d histogram is projected in 2d such as the data in that direction
-/// are accumulated to the two others.
+/// \brief Allow the complete visualization of a 3d histogram by projection.
+///
+/// The 3d histogram is projected in red/green space by accumulating around the
+/// the blue dimension (green and blue composantes are being correlated). In
+/// fact, we sum in along the blue direction. Then, we stretch value to feet
+/// pgm format. This is the same preambule documentation as in display_histo
+/// because display_histo is use as a front hand for this file.
+///
+/// This is the sample code to use the red/green visualization.
+///
+/// \fixme There is a lot of routines in display_histo.hh, but only
+/// two of them have been call here. Stuff to complete.
+///
+/// #include <iostream>
+/// #include <mln/accu/stat/histo3d_rgb.hh>
+/// #include <mln/core/macros.hh>
+/// #include <mln/core/image/image2d.hh>
+/// #include <mln/core/image/image3d.hh>
+/// #include <mln/data/compute.hh>
+/// #include <mln/data/transform.hh>
+/// #include <mln/display/display_histo.hh>
+/// #include <mln/fun/v2v/rgb8_to_rgbn.hh>
+/// #include <mln/img_path.hh>
+/// #include <mln/io/ppm/load.hh>
+/// #include <mln/io/pgm/save.hh>
+/// #include <mln/io/ppm/save.hh>
+/// #include <mln/literal/colors.hh>
+/// #include <mln/value/rgb8.hh>
+/// #include <mln/value/rgb.hh>
+///
+/// int main()
+/// {
+/// typedef mln::value::int_u8 t_int_u8;
+/// typedef mln::value::int_u<4> t_int_u4;
+/// typedef mln::value::rgb8 t_rgb8;
+/// typedef mln::value::rgb<4> t_rgb4;
+/// typedef mln::image2d<t_int_u8> t_image2d_int_u8;
+/// typedef mln::image2d<t_int_u4> t_image2d_int_u4;
+/// typedef mln::image2d<t_rgb8> t_image2d_rgb8;
+/// typedef mln::image2d<t_rgb4> t_image2d_rgb4;
+/// typedef mln::image2d<bool> t_image2d_bool;
+/// typedef mln::image3d<unsigned> t_histo3d;
+/// typedef mln::fun::v2v::rgb8_to_rgbn<4> t_rgb8_to_rgb4;
+/// typedef mln::accu::meta::stat::histo3d_rgb t_histo3d_fun;
+///
+/// t_image2d_rgb8 i0_input; // input rgb8
+/// t_image2d_rgb4 i1_input; // input rgbn
+/// t_histo3d h1_input; // histo input
+/// t_image2d_int_u8 p1_histo1;// histo proj1
+/// t_image2d_rgb4 p1_histo2;// histo proj2
+/// t_rgb4 red(mln::literal::red);
+///
+/// mln::io::ppm::load(i0_input, OLENA_IMG_PATH"/lena.ppm");
+///
+/// i1_input = mln::data::transform(i0_input, t_rgb8_to_rgb4());
+/// h1_input = mln::data::compute(t_histo3d_fun(), i1_input);
+/// p1_histo1 = mln::display::display_histo3d_unsigned(h1_input);
+/// p1_histo2 = mln::display::display3_histo3d_unsigned(h1_input, red);
+///
+/// mln::io::pgm::save(p1_histo1, "proj1.pgm");
+/// mln::io::ppm::save(p1_histo2, "proj2.ppm");
+///
+/// return 0;
+/// }
+
namespace mln
{
@@ -59,50 +121,130 @@ namespace mln
namespace display
{
- // Forward declaration.
+ /// \brief Allow the visualization of the density of the 3d histogram.
+ ///
+ /// Parameter A is the type of accumulator, for instance, accu::math::sum.
+ /// Parameter direction is the way of the projection, for instance blue one.
+ /// Parameter V is the value we use to accumulate information.
+ ///
+ /// Direction r = 1
+ /// Direction g = 2
+ /// Direction b = 0
+ ///
+ /// \parameter[in] histo the histogram in 3d.
+ /// \result return the projection of the histogram in 2d.
+ ///
+ /// The 3d histogram is projected in red/green space by
+ /// accumulating around the the blue dimension (green and blue
+ /// composantes are being correlated). In fact, we sum along the
+ /// blue direction and take the log of value. Then, we stretch
+ /// value to feet pgm format. Not limited to red/green space.
template <typename A, unsigned direction, typename V>
image2d<mln_result(A)>
project_histo(const image3d<V>& histo);
+
+ /// \brief Allow the visualization of the important color of the 3d histo.
+ ///
+ /// Parameter A is the type of accumulator, for instance, accu::math::sum.
+ /// Parameter direction is the way of the projection, for instance blue one.
+ /// Parameter V is the value we use to accumulate information.
+ ///
+ /// Direction r = 1
+ /// Direction g = 2
+ /// Direction b = 0
+ ///
+ /// \parameter[in] histo the histogram in 3d.
+ /// \parameter[in] ambiguous_color the color when no max is found.
+ /// \result return the projection of the histogram in 2d.
+ ///
+ /// The 3d histogram is projected in red/green space. In the blue
+ /// direction we check the max blue component. The position in
+ /// this blue axis is returned in the projection image. Not
+ /// limited to red/green space.
template <typename A, unsigned n, unsigned direction, typename V>
image2d<mln_result(A)>
project2_histo(const image3d<V>& histo,
const value::int_u<n>& ambiguous_color);
+
+ /// \brief Allow the visualization of the color of the 3d segmented histo.
+ ///
+ /// Parameter A is the type of accumulator, for instance, accu::math::sum.
+ /// Parameter direction is the way of the projection, for instance blue one.
+ /// Parameter V is the value we use to accumulate information.
+ ///
+ /// Direction r = 1
+ /// Direction g = 2
+ /// Direction b = 0
+ ///
+ /// \parameter[in] histo the histogram in 3d.
+ /// \parameter[in] label the label image to associate the result with.
+ /// \result return the projection of the histogram in 2d.
+ ///
+ /// The 3d histogram is projected in red/green space. In the blue
+ /// direction we check the max blue component. The position in
+ /// this blue axis is associated to a segmented label and this label
+ /// is returned in the projection image. Not limited to red/green space.
template <unsigned n, unsigned direction, typename V>
image2d<V>
project2_histo(const image3d<unsigned>& histo,
const image3d<V>& label);
+ /// \brief Allow the visualization with color of the 3d histo.
+ ///
+ /// Parameter A is the type of accumulator, for instance, accu::math::sum.
+ /// Parameter direction is the way of the projection, for instance blue one.
+ /// Parameter V is the value we use to accumulate information.
+ ///
+ /// Direction r = 1
+ /// Direction g = 2
+ /// Direction b = 0
+ ///
+ /// \parameter[in] histo the histogram in 3d.
+ /// \parameter[in] ambiguous_color the color when no max is found.
+ /// \result return the projection of the histogram in 2d.
+ ///
+ /// The 3d histogram is projected in red/green space. In the blue
+ /// direction we check the max blue component. The position is
+ /// used to build a rgb color and put it as a returned value in
+ /// projection image. Not limited to red/green space.
template <unsigned n, unsigned direction>
image2d< value::rgb<n> >
project3_histo(const image3d<unsigned>& histo,
const value::rgb<n> ambiguous_color);
+ /// \brief Allow the visualization with color of the 3d segmented histo.
+ ///
+ /// Parameter A is the type of accumulator, for instance, accu::math::sum.
+ /// Parameter direction is the way of the projection, for instance blue one.
+ /// Parameter V is the value we use to accumulate information.
+ ///
+ /// Direction r = 1
+ /// Direction g = 2
+ /// Direction b = 0
+ ///
+ /// \parameter[in] histo the histogram in 3d.
+ /// \parameter[in] label the label image to associte the result with.
+ /// \parameter[in] pal the color indexed list to associate to the label.
+ /// \parameter[in] ambiguous_color the color when no max is found.
+ /// \result return the projection of the histogram in 2d.
+ ///
+ /// The 3d histogram is projected in red/green space. In the blue
+ /// direction we check the max blue component. The position is used
+ /// to find the label associate to it and then the color associated to
+ /// this label. That's the information we return in the projection image.
+ /// Not limited to red/green space.
template <unsigned n, unsigned direction>
image2d< value::rgb8 >
project3_histo(const image3d<unsigned>& histo,
const image3d<value::label_8>& label,
const util::array<algebra::vec<3, float> >& pal,
const value::rgb8 ambiguous_color);
- // FIXME ==> palette must be 1d-image not an array !!
-
# ifndef MLN_INCLUDE_ONLY
- /// \brief Allow the visualization of 3d histogram.
- ///
- /// The 3d histogram is projected in 2d such as the data in that direction
- /// are accumulated to the two others.
- ///
- /// Parameter A is the type of accumulator, for instance, accu::math::sum.
- /// Parameter direction is the way of the projection, for instance blue one.
- /// Parameter V is the value we use to accumulate information.
- ///
- /// \prameter[in] the histogram 3d.
- /// \result the 2d projection of the 3d histogram.
-
template <typename A, unsigned direction, typename V>
image2d<mln_result(A)>
project_histo(const image3d<V>& histo)
diff --git a/scribo/sandbox/green/tools/labeling/histo/Makefile.am b/scribo/sandbox/green/tools/labeling/histo/Makefile.am
new file mode 100644
index 0000000..f03a836
--- /dev/null
+++ b/scribo/sandbox/green/tools/labeling/histo/Makefile.am
@@ -0,0 +1,153 @@
+#
+# Generic Makefile
+#
+
+#########
+# TOOLS #
+#########
+
+#LOADLIBES= -lboost_filesystem
+INCLUDES1= -I$(HOME)/git/olena/scribo/sandbox/green
+INCLUDES2= -I$(HOME)/git/olena/milena
+INCLUDES= $(INCLUDES1) $(INCLUDES2)
+CXXFLAGS= -ggdb -O0 -Wall -W -pedantic -ansi -pipe $(INCLUDES)
+#CXXFLAGS= -DNDEBUG -O1 -Wall -W -pedantic -ansi -pipe $(INCLUDES)
+#CXXFLAGS= -DNDEBUG -O3 -Wall -W -pedantic -ansi -pipe $(INCLUDES)
+ECHO= echo
+RM= rm
+MKDIR= mkdir -p
+CP= cp
+
+SOURCE_PATTERN= green/tools
+BUILD__PATTERN= green/build/tools
+
+
+ifeq ($(findstring $(BUILD__PATTERN),$(PWD)), $(BUILD__PATTERN))
+# Case where make is done from build directory.
+SOURCE_DIR= $(subst $(BUILD__PATTERN),$(SOURCE_PATTERN),$(PWD))
+BUILD__DIR= $(PWD)/
+else
+# Case where make is done from source directory.
+SOURCE_DIR= $(PWD)/
+BUILD__DIR= $(subst $(SOURCE_PATTERN),$(BUILD__PATTERN),$(PWD))
+endif
+
+SRC= $(notdir $(wildcard $(SOURCE_DIR)/*.cc))
+OLD= $(notdir $(wildcard $(SOURCE_DIR)/*~))
+OBJ= $(patsubst %.cc,%.o,$(SRC))
+SOURCE_MAKEFILE=Makefile.am
+BUILD__MAKEFILE=Makefile
+TARGET_FILE= $(notdir $(PWD))
+SOURCE_FILES= $(notdir $(wildcard $(SOURCE_DIR)/*.*))
+BUILD__FILES= $(filter-out $(SRC) $(SOURCE_MAKEFILE), $(SOURCE_FILES))
+
+BUILD__F_PATH= $(addprefix $(BUILD__DIR)/,$(BUILD__FILES))
+SOURCE_F_PATH= $(addprefix $(SOURCE_DIR)/,$(SOURCE_FILES))
+
+BUILD__M_PATH= $(addprefix $(BUILD__DIR)/,$(BUILD__MAKEFILE))
+SOURCE_M_PATH= $(addprefix $(SOURCE_DIR)/,$(SOURCE_MAKEFILE))
+
+TARGET_F_PATH= $(addprefix $(BUILD__DIR)/,$(TARGET_FILE))
+OBJ_F_PATH= $(addprefix $(BUILD__DIR)/,$(OBJ))
+SRC_F_PATH= $(addprefix $(SOURCE_DIR)/,$(SRC))
+OLD_F_PATH= $(addprefix $(SOURCE_DIR)/,$(OLD))
+
+#############
+# BOOTSTRAP #
+#############
+
+
+bootstrap: $(BUILD__DIR) $(BUILD__F_PATH) $(BUILD__M_PATH)
+
+# Create, if nessary, the destination directory
+$(BUILD__DIR):
+ $(MKDIR) $(BUILD__DIR)
+
+# Copy, if nessary, all the files, except the Makefile.am
+$(BUILD__F_PATH): $(SOURCE_F_PATH)
+ $(CP) $(addprefix $(SOURCE_DIR),$(@F)) $@
+
+# Copy if nessary, the Makefile.am into Makefile
+$(BUILD__M_PATH): $(SOURCE_M_PATH)
+ $(CP) $(SOURCE_M_PATH) $(BUILD__M_PATH)
+
+
+#######
+# ALL #
+#######
+
+# We assume that the call is done from the build directory.
+# With the directive vpath, hidden files are found in the source directory.
+
+all: $(TARGET_F_PATH)
+
+
+$(TARGET_F_PATH): $(OBJ_F_PATH)
+ $(LINK.cc) $< $(LOADLIBES) $(LDLIBS) -o $@
+
+$(OBJ_F_PATH):$(SRC_F_PATH)
+ $(COMPILE.cc) $(OUTPUT_OPTION) $<
+
+
+#########
+# CLEAN #
+#########
+
+# Force every time the deletion
+clean: clean_target clean_obj clean_dst clean_old #clean_make
+
+
+clean_target:
+ -@$(RM) $(TARGET_F_PATH) &> /dev/null
+
+clean_obj:
+ -@$(RM) $(OBJ_F_PATH) &> /dev/null
+
+clean_dst:
+ -@$(RM) $(BUILD_F_PATH) &> /dev/null
+
+clean_make:
+ -@$(RM) $(BUILD_M_PATH) &> /dev/null
+
+clean_old:
+ -@$(RM) $(OLD_F_PATH) &> /dev/null
+
+
+#########
+# PRINT #
+#########
+
+print: print_tools print_bootstrap
+
+print_tools:
+ @$(ECHO) "HOME = $(HOME)"
+ @$(ECHO) "INCLUDES = $(INCLUDES)"
+ @$(ECHO) "CXXFLAGS = $(CXXFLAGS)"
+ @$(ECHO) "ECHO = $(ECHO)"
+ @$(ECHO) "RM = $(RM)"
+ @$(ECHO) "MKDIR = $(MKDIR)"
+ @$(ECHO) "CP = $(CP)"
+ @$(ECHO)
+
+print_bootstrap:
+ @$(ECHO) "PWD = $(PWD)"
+ @$(ECHO) "SOURCE_PATTERN = $(SOURCE_PATTERN)"
+ @$(ECHO) "BUILD__PATTERN = $(BUILD__PATTERN)"
+ @$(ECHO) "SOURCE_DIR = $(SOURCE_DIR)"
+ @$(ECHO) "BUILD__DIR = $(BUILD__DIR)"
+ @$(ECHO) "SOURCE_MAKEFILE = $(SOURCE_MAKEFILE)"
+ @$(ECHO) "BUILD__MAKEFILE = $(BUILD__MAKEFILE)"
+ @$(ECHO) "TARGET_FILE = $(TARGET_FILE)"
+ @$(ECHO) "SOURCE_FILES = $(SOURCE_FILES)"
+ @$(ECHO) "SOURCE_F_PATH = $(SOURCE_F_PATH)"
+ @$(ECHO) "BUILD__FILES = $(BUILD__FILES)"
+ @$(ECHO) "BUILD__F_PATH = $(BUILD__F_PATH)"
+ @$(ECHO) "BUILD__M_PATH = $(BUILD__M_PATH)"
+ @$(ECHO) "SOURCE_M_PATH = $(SOURCE_M_PATH)"
+ @$(ECHO) "SRC = $(SRC)"
+ @$(ECHO) "OBJ = $(OBJ)"
+ @$(ECHO) "OLD = $(OLD)"
+ @$(ECHO) "SRC_F_PATH = $(SRC_F_PATH)"
+ @$(ECHO) "OBJ_F_PATH = $(OBJ_F_PATH)"
+ @$(ECHO) "OLD_F_PATH = $(OLD_F_PATH)"
+ @$(ECHO)
diff --git a/scribo/sandbox/green/tools/labeling/histo/histo.cc b/scribo/sandbox/green/tools/labeling/histo/histo.cc
new file mode 100644
index 0000000..1fee9df
--- /dev/null
+++ b/scribo/sandbox/green/tools/labeling/histo/histo.cc
@@ -0,0 +1,204 @@
+// Copyright (C) 2007, 2008, 2009, 2010 EPITA 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.
+
+/// \file
+///
+/// \brief This tool aimed at building 3d RGB histogram.
+///
+/// Building histogram means quantifying the input and then image computing
+/// the 3d histogram in RGB space.
+
+#include <iostream>
+
+#include <mln/accu/stat/histo3d_rgb.hh>
+
+#include <mln/core/macros.hh>
+#include <mln/core/image/image2d.hh>
+#include <mln/core/image/image3d.hh>
+#include <mln/core/image/dmorph/image_if.hh>
+
+#include <mln/data/compute.hh>
+#include <mln/data/transform.hh>
+
+#include <mln/display/display_histo.hh>
+
+#include <mln/fun/v2v/rgb8_to_rgbn.hh>
+
+#include <mln/io/pbm/load.hh>
+#include <mln/io/ppm/load.hh>
+#include <mln/io/dump/save.hh>
+#include <mln/io/pgm/save.hh>
+#include <mln/io/ppm/save.hh>
+
+#include <mln/literal/colors.hh>
+
+#include <mln/opt/at.hh>
+
+#include <mln/pw/value.hh>
+
+#include <mln/value/rgb8.hh>
+#include <mln/value/rgb.hh>
+
+
+/// \brief The histogram image processing chain.
+///
+/// \param[in] input the input image.
+/// \param[out] quant the name of the resulting quantified image.
+/// \param[out] histo the name of the resulting 3d histogram.
+/// \param[out] proj1 the red/green projection of the histogram.
+/// \param[out] proj2 the red/green projection with maxima plot on.
+/// \param[in] mask the mask with selects the pixels of the input image.
+///
+/// This chain aimed at computing 3d RGB histogram of 2d RGB color
+/// quantified image. As the 3d histogram induces lots and lots of
+/// data, quantifiying the input image reduces the size of the
+/// resulting histogram. Then, dumping and projections are done.
+template <unsigned n>
+void mk_histo(const std::string& input, // in
+ const std::string& quant, // in
+ const std::string& histo, // out
+ const std::string& proj1, // out
+ const std::string& proj2, // out
+ const std::string& mask) // [in]
+{
+ typedef mln::value::int_u8 t_int_u8;
+ typedef mln::value::int_u<n> t_int_un;
+ typedef mln::value::rgb8 t_rgb8;
+ typedef mln::value::rgb<n> t_rgbn;
+ typedef mln::image2d<t_int_u8> t_image2d_int_u8;
+ typedef mln::image2d<t_int_un> t_image2d_int_un;
+ typedef mln::image2d<t_rgb8> t_image2d_rgb8;
+ typedef mln::image2d<t_rgbn> t_image2d_rgbn;
+ typedef mln::image2d<bool> t_image2d_bool;
+ typedef mln::image3d<unsigned> t_histo3d;
+ typedef mln::fun::v2v::rgb8_to_rgbn<n> t_rgb8_to_rgbn;
+ typedef mln::accu::meta::stat::histo3d_rgb t_histo3d_fun;
+
+ // START OF IMAGE PROCESSING CHAIN
+ t_image2d_rgb8 i0_input; // input rgb8
+ t_image2d_rgbn i1_input; // input rgbn
+ t_image2d_bool m0_input; // mask input
+ t_histo3d h1_input; // histo input
+ t_image2d_int_u8 p1_histo1;// histo proj1
+ t_image2d_rgbn p1_histo2;// histo proj2
+ t_rgbn red(mln::literal::red);
+
+ mln::io::ppm::load(i0_input, input.c_str());
+ i1_input = mln::data::transform(i0_input, t_rgb8_to_rgbn());
+
+ if (0 < mask.size())
+ {
+ mln::io::pbm::load(m0_input, mask.c_str());
+ h1_input = mln::data::compute(t_histo3d_fun(),
+ (i1_input | mln::pw::value(m0_input)).rw());
+ }
+ else
+ {
+ h1_input = mln::data::compute(t_histo3d_fun(), i1_input);
+ }
+ // END OF IMAGE PROCESSING CHAIN
+
+ // BEGIN DUMPING
+ p1_histo1 = mln::display::display_histo3d_unsigned(h1_input);
+ p1_histo2 = mln::display::display3_histo3d_unsigned(h1_input, red);
+
+ mln::io::ppm::save(i1_input, quant.c_str());
+ mln::io::dump::save(h1_input, histo.c_str());
+ mln::io::pgm::save(p1_histo1, proj1.c_str());
+ mln::io::ppm::save(p1_histo2, proj2.c_str());
+ // END DUMPING
+}
+
+
+/// \brief The online documentation of the tool.
+///
+/// Print the documentation of the tool with the meaning of the
+/// different parameters.
+void usage()
+{
+ std::cout << std::endl;
+ std::cout << "histo input.ppm q quant.ppm histo.dump proj.pgm"
+ << " proj.ppm [msk.pbm]" << std::endl;
+ std::cout << std::endl;
+ std::cout << "where :" << std::endl;
+ std::cout << "* [ in] input.ppm is the 8 bits color ppm image" << std::endl;
+ std::cout << "* [ in] q is the degree of quantification"
+ << " {2,3,4,5,6,7,8}" << std::endl;
+ std::cout << "* [out] quant.ppm is the q bits quantified input"
+ << " image" << std::endl;
+ std::cout << "* [out] histo.dump is the quantified color"
+ << " histogram" << std::endl;
+ std::cout << "* [out] proj.pgm is the r/g projection of the"
+ << " histogram (summing along the blue axe)" << std::endl;
+ std::cout << "* [out] proj.ppm is the r/g projection of the"
+ << " histogram with maxima plot on" << std::endl;
+ std::cout << "* [ in] msk.pbm is the mask which selects the"
+ << " pixels" << std::endl;
+ std::cout << std::endl;
+}
+
+
+/// \brief The main entry of the software.
+///
+/// \param[in] input the input image.
+/// \param[in] q the quantification.
+/// \param[out] quant.ppm the name of the resulting quantified image.
+/// \param[out] histo.dump the name of the resulting 3d histogram.
+/// \param[out] proj.pgm the red/green projection of the histogram.
+/// \param[out] proj.ppm the red/green projection with maxima plot on.
+/// \param[in] msk.pbm the mask with selects the pixels of the input image.
+///
+/// This is the front hand for the image processing routine. The goal of this
+/// chain is to provide 3d histogram for further analysis and to give a way to
+/// see it.
+int main(int argc, char* args[])
+{
+ if (7 == argc || 8 == argc)
+ {
+ const std::string input(args[1]); // in
+ const char q = args[2][0]; // in
+ const std::string quant(args[3]); // out
+ const std::string histo(args[4]); // out
+ const std::string proj1(args[5]); // out
+ const std::string proj2(args[6]); // out
+ const std::string mask(8 == argc? args[7] : ""); // [in]
+
+ switch(q)
+ {
+ case '2': mk_histo<2>(input, quant, histo, proj1, proj2, mask); break;
+ case '3': mk_histo<3>(input, quant, histo, proj1, proj2, mask); break;
+ case '4': mk_histo<4>(input, quant, histo, proj1, proj2, mask); break;
+ case '5': mk_histo<5>(input, quant, histo, proj1, proj2, mask); break;
+ case '6': mk_histo<6>(input, quant, histo, proj1, proj2, mask); break;
+ case '7': mk_histo<7>(input, quant, histo, proj1, proj2, mask); break;
+ case '8': mk_histo<8>(input, quant, histo, proj1, proj2, mask); break;
+ default: usage(); break;
+ }
+ }
+ else
+ usage();
+
+ return 0;
+}
diff --git a/scribo/sandbox/green/tools/labeling/iz/Makefile.am b/scribo/sandbox/green/tools/labeling/iz/Makefile.am
new file mode 100644
index 0000000..57e7ec9
--- /dev/null
+++ b/scribo/sandbox/green/tools/labeling/iz/Makefile.am
@@ -0,0 +1,153 @@
+#
+# Generic Makefile
+#
+
+#########
+# TOOLS #
+#########
+
+LOADLIBES= -lboost_filesystem
+INCLUDES1= -I$(HOME)/git/olena/scribo/sandbox/green
+INCLUDES2= -I$(HOME)/git/olena/milena
+INCLUDES= $(INCLUDES1) $(INCLUDES2)
+CXXFLAGS= -ggdb -O0 -Wall -W -pedantic -ansi -pipe $(INCLUDES)
+#CXXFLAGS= -DNDEBUG -O1 -Wall -W -pedantic -ansi -pipe $(INCLUDES)
+#CXXFLAGS= -DNDEBUG -O3 -Wall -W -pedantic -ansi -pipe $(INCLUDES)
+ECHO= echo
+RM= rm
+MKDIR= mkdir -p
+CP= cp
+
+SOURCE_PATTERN= green/tools
+BUILD__PATTERN= green/build/tools
+
+
+ifeq ($(findstring $(BUILD__PATTERN),$(PWD)), $(BUILD__PATTERN))
+# Case where make is done from build directory.
+SOURCE_DIR= $(subst $(BUILD__PATTERN),$(SOURCE_PATTERN),$(PWD))
+BUILD__DIR= $(PWD)/
+else
+# Case where make is done from source directory.
+SOURCE_DIR= $(PWD)/
+BUILD__DIR= $(subst $(SOURCE_PATTERN),$(BUILD__PATTERN),$(PWD))
+endif
+
+SRC= $(notdir $(wildcard $(SOURCE_DIR)/*.cc))
+OLD= $(notdir $(wildcard $(SOURCE_DIR)/*~))
+OBJ= $(patsubst %.cc,%.o,$(SRC))
+SOURCE_MAKEFILE=Makefile.am
+BUILD__MAKEFILE=Makefile
+TARGET_FILE= $(notdir $(PWD))
+SOURCE_FILES= $(notdir $(wildcard $(SOURCE_DIR)/*.*))
+BUILD__FILES= $(filter-out $(SRC) $(SOURCE_MAKEFILE), $(SOURCE_FILES))
+
+BUILD__F_PATH= $(addprefix $(BUILD__DIR)/,$(BUILD__FILES))
+SOURCE_F_PATH= $(addprefix $(SOURCE_DIR)/,$(SOURCE_FILES))
+
+BUILD__M_PATH= $(addprefix $(BUILD__DIR)/,$(BUILD__MAKEFILE))
+SOURCE_M_PATH= $(addprefix $(SOURCE_DIR)/,$(SOURCE_MAKEFILE))
+
+TARGET_F_PATH= $(addprefix $(BUILD__DIR)/,$(TARGET_FILE))
+OBJ_F_PATH= $(addprefix $(BUILD__DIR)/,$(OBJ))
+SRC_F_PATH= $(addprefix $(SOURCE_DIR)/,$(SRC))
+OLD_F_PATH= $(addprefix $(SOURCE_DIR)/,$(OLD))
+
+#############
+# BOOTSTRAP #
+#############
+
+
+bootstrap: $(BUILD__DIR) $(BUILD__F_PATH) $(BUILD__M_PATH)
+
+# Create, if nessary, the destination directory
+$(BUILD__DIR):
+ $(MKDIR) $(BUILD__DIR)
+
+# Copy, if nessary, all the files, except the Makefile.am
+$(BUILD__F_PATH): $(SOURCE_F_PATH)
+ $(CP) $(addprefix $(SOURCE_DIR),$(@F)) $@
+
+# Copy if nessary, the Makefile.am into Makefile
+$(BUILD__M_PATH): $(SOURCE_M_PATH)
+ $(CP) $(SOURCE_M_PATH) $(BUILD__M_PATH)
+
+
+#######
+# ALL #
+#######
+
+# We assume that the call is done from the build directory.
+# With the directive vpath, hidden files are found in the source directory.
+
+all: $(TARGET_F_PATH)
+
+
+$(TARGET_F_PATH): $(OBJ_F_PATH)
+ $(LINK.cc) $< $(LOADLIBES) $(LDLIBS) -o $@
+
+$(OBJ_F_PATH):$(SRC_F_PATH)
+ $(COMPILE.cc) $(OUTPUT_OPTION) $<
+
+
+#########
+# CLEAN #
+#########
+
+# Force every time the deletion
+clean: clean_target clean_obj clean_dst clean_old #clean_make
+
+
+clean_target:
+ -@$(RM) $(TARGET_F_PATH) &> /dev/null
+
+clean_obj:
+ -@$(RM) $(OBJ_F_PATH) &> /dev/null
+
+clean_dst:
+ -@$(RM) $(BUILD_F_PATH) &> /dev/null
+
+clean_make:
+ -@$(RM) $(BUILD_M_PATH) &> /dev/null
+
+clean_old:
+ -@$(RM) $(OLD_F_PATH) &> /dev/null
+
+
+#########
+# PRINT #
+#########
+
+print: print_tools print_bootstrap
+
+print_tools:
+ @$(ECHO) "HOME = $(HOME)"
+ @$(ECHO) "INCLUDES = $(INCLUDES)"
+ @$(ECHO) "CXXFLAGS = $(CXXFLAGS)"
+ @$(ECHO) "ECHO = $(ECHO)"
+ @$(ECHO) "RM = $(RM)"
+ @$(ECHO) "MKDIR = $(MKDIR)"
+ @$(ECHO) "CP = $(CP)"
+ @$(ECHO)
+
+print_bootstrap:
+ @$(ECHO) "PWD = $(PWD)"
+ @$(ECHO) "SOURCE_PATTERN = $(SOURCE_PATTERN)"
+ @$(ECHO) "BUILD__PATTERN = $(BUILD__PATTERN)"
+ @$(ECHO) "SOURCE_DIR = $(SOURCE_DIR)"
+ @$(ECHO) "BUILD__DIR = $(BUILD__DIR)"
+ @$(ECHO) "SOURCE_MAKEFILE = $(SOURCE_MAKEFILE)"
+ @$(ECHO) "BUILD__MAKEFILE = $(BUILD__MAKEFILE)"
+ @$(ECHO) "TARGET_FILE = $(TARGET_FILE)"
+ @$(ECHO) "SOURCE_FILES = $(SOURCE_FILES)"
+ @$(ECHO) "SOURCE_F_PATH = $(SOURCE_F_PATH)"
+ @$(ECHO) "BUILD__FILES = $(BUILD__FILES)"
+ @$(ECHO) "BUILD__F_PATH = $(BUILD__F_PATH)"
+ @$(ECHO) "BUILD__M_PATH = $(BUILD__M_PATH)"
+ @$(ECHO) "SOURCE_M_PATH = $(SOURCE_M_PATH)"
+ @$(ECHO) "SRC = $(SRC)"
+ @$(ECHO) "OBJ = $(OBJ)"
+ @$(ECHO) "OLD = $(OLD)"
+ @$(ECHO) "SRC_F_PATH = $(SRC_F_PATH)"
+ @$(ECHO) "OBJ_F_PATH = $(OBJ_F_PATH)"
+ @$(ECHO) "OLD_F_PATH = $(OLD_F_PATH)"
+ @$(ECHO)
diff --git a/scribo/sandbox/green/tools/labeling/iz/iz.cc b/scribo/sandbox/green/tools/labeling/iz/iz.cc
new file mode 100644
index 0000000..f977898
--- /dev/null
+++ b/scribo/sandbox/green/tools/labeling/iz/iz.cc
@@ -0,0 +1,495 @@
+// Copyright (C) 2007, 2008, 2009, 2010 EPITA 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.
+
+/// \file
+///
+/// \brief This tool aimed at propagating segmented labels over the background.
+///
+/// Because regional maxima are very small regions, we need to make
+/// them growing to be representative in the color space.
+///
+/// \fixme Sorry, this source doesn't compile. The fact is the
+/// influence_zone_geodesic has changed and fastest version is more
+/// attentive to 2d image than 3d. That's why l.127 it call a 2d version of the
+/// method at() and it's make trouble with my code that uses a 3d image.
+
+#include <iostream>
+#include <fstream>
+#include <boost/format.hpp>
+
+#include <mln/accu/stat/histo3d_rgb.hh>
+
+#include <mln/core/macros.hh>
+#include <mln/core/alias/neighb3d.hh>
+#include <mln/core/image/image2d.hh>
+#include <mln/core/image/image3d.hh>
+
+#include <mln/data/compute.hh>
+
+#include <mln/display/display_histo.hh>
+
+#include <mln/io/dump/load.hh>
+#include <mln/io/dump/save.hh>
+#include <mln/io/ppm/load.hh>
+#include <mln/io/ppm/save.hh>
+#include <mln/io/pgm/load.hh>
+#include <mln/io/pgm/save.hh>
+
+#include <mln/literal/colors.hh>
+
+#include <mln/labeling/compute.hh>
+#include <mln/labeling/mean_values.hh>
+
+#include <mln/transform/influence_zone_geodesic.hh>
+#include <mln/transform/influence_zone_geodesic_saturated.hh>
+
+#include <mln/value/int_u8.hh>
+
+/// \ brief Compute the 2d labeled image.
+///
+/// Compute the 2d labeled image with the 2d labeled histogram and
+/// the input image.
+///
+/// \fixme Need to put it in mln library. Nothing to do here.
+template <unsigned n>
+struct t_labeling_rgbn : mln::Function_v2v< t_labeling_rgbn<n> >
+{
+ typedef mln::value::rgb<n> t_rgbn;
+ typedef mln::value::label_8 t_lbl8;
+ typedef t_rgbn argument;
+ typedef t_lbl8 result;
+ typedef mln::image3d<t_lbl8> t_label;
+
+ const t_label& _label;
+
+ t_labeling_rgbn(const t_label& label) : _label(label) {}
+
+ result operator()(const argument& c) const
+ {
+ t_lbl8 tmp = mln::opt::at(_label, c.blue(), c.red(), c.green());
+
+ return tmp;
+ }
+};
+
+/// \brief Compute and dump stats.
+///
+/// \param[in] i_input_rgb8 the 2d rgb input image.
+/// \param[in] l_input_lbl8 the 2d labeled image.
+/// \param[in] h_histo_rgbn the quantified histogram.
+/// \param[in] l_histo_lbl8 the labeled quantified histogram.
+/// \param[in] n_labels the number of labels (number of regions).
+/// \param[in] the name of the logging file for the stats.
+///
+/// Every segmented color has got it's own label. For each label, we
+/// compute the mean in the r/g/b channels, the total of pixels, the
+/// percentage of pixels in the image and the percentage without counting
+/// the background (label 0).
+void compute_stats(const mln::image2d<mln::value::rgb8>& i_input_rgb8,
+ const mln::image2d<mln::value::label_8>& l_input_lbl8,
+ const mln::image3d<unsigned>& h_histo_rgbn,
+ const mln::image3d<mln::value::label_8>& l_histo_lbl8,
+ const mln::value::label_8& n_labels,
+ const std::string& log)
+{
+ typedef mln::algebra::vec<3,float> t_vec3f;
+ typedef mln::accu::math::sum<unsigned,unsigned> t_sum;
+ typedef mln::accu::stat::mean<t_vec3f,t_vec3f,t_vec3f> t_mean;
+ typedef mln::util::array<unsigned> t_count_array;
+ typedef mln::util::array<t_vec3f> t_mean_array;
+
+ mln::util::array<float> abs((unsigned)(n_labels)+1);
+ mln::util::array<float> rel((unsigned)(n_labels)+1);
+ unsigned nb = 0;
+
+ for (unsigned i = 0; i <= n_labels; ++i)
+ {
+ abs[i] = 0.0;
+ rel[i] = 0.0;
+ }
+
+ // COMPUTE THE SUM
+ t_count_array count = mln::labeling::compute(t_sum(),
+ h_histo_rgbn,
+ l_histo_lbl8,
+ n_labels);
+
+ // COMPUTE THE TOTAL
+ for (unsigned i = 0; i <= n_labels; ++i)
+ {
+ unsigned c = count[i];
+ nb += c;
+ }
+
+ // COMPUTE THE PERCENTAGES
+ for (unsigned i = 0; i <= n_labels; ++i)
+ if (0 < count[i])
+ {
+ abs[i] = ((float)count[i] / nb)*100.0;
+ rel[i] = ((float)count[i] / (nb - count[0]))*100.0;
+ }
+
+ // COMPUTE THE MEAN
+
+ t_mean_array mean = mln::labeling::compute(t_mean(),
+ i_input_rgb8,
+ l_input_lbl8,
+ n_labels);
+
+ // CORRECT 0 LABEL STATS
+ rel[0] = 0;
+ mean[0][0] = 255.0;
+ mean[0][1] = 255.0;
+ mean[0][2] = 0.0;
+
+ // PRINT STATS
+ std::ofstream log_stream(log.c_str());
+
+ for (unsigned i = 0; i <= n_labels; ++i)
+ {
+ const t_vec3f& mean_v = mean[i];
+
+ log_stream << boost::format("%2i|"
+ "r = %6.2f, g = %6.2f, b = %6.2f |"
+ "c = %7i, %%i = %5.2f, %%c = %5.2f")
+ % i
+ % mean_v[0]
+ % mean_v[1]
+ % mean_v[2]
+ % count[i]
+ % abs[i]
+ % rel[i]
+ << std::endl;
+ }
+
+ log_stream << std::endl << std::endl;
+ log_stream.flush();
+ log_stream.close();
+}
+
+
+/// \brief Verify that a marker is present on the stream.
+///
+/// \param[in] stream the input stream.
+/// \param[in] expected the expected character to be on the stream.
+///
+/// \return true if the expected character was on the stream, else false.
+///
+/// This routine enables to read structured colormap file and to
+/// follow the structure while reading colors.
+bool expect(std::istream& stream, const std::string expected)
+{
+ bool result;
+ std::string got;
+
+ stream >> got;
+
+ result = (got == expected);
+
+ return result;
+}
+
+/// \brief Read a line of the colormap.
+///
+/// \param[in] stream the input stream.
+/// \param[out] color the output color read in the current line.
+///
+/// \return the modified streams.
+///
+/// This routine splits a line in differents marks in order to read
+/// the R/G/B channels of the output color.
+std::istream& operator>>(std::istream& stream,
+ mln::algebra::vec<3,float>& color)
+{
+ unsigned lbl;
+
+ stream >> lbl;
+ if (expect(stream, std::string("|")) &&
+ expect(stream, std::string("r")) &&
+ expect(stream, std::string("=")))
+ {
+ stream >> color[0];
+
+ if (expect(stream, std::string(",")) &&
+ expect(stream, std::string("g")) &&
+ expect(stream, std::string("=")))
+ {
+ stream >> color[1];
+
+ if (expect(stream, std::string(",")) &&
+ expect(stream, std::string("b")) &&
+ expect(stream, std::string("=")))
+ {
+ stream >> color[2];
+ }
+ }
+ }
+
+ return stream;
+}
+
+
+/// \brief Load the colormap.
+///
+/// \param[out] m2_label the memory representation of the colormap.
+/// \param[in] colormap the name of the file where the colormap is stocked.
+///
+/// This routine coordonates parsing actions in the colormap file.
+void load(mln::util::array< mln::algebra::vec<3,float> >& m2_label,
+ const char *colormap)
+{
+ typedef mln::algebra::vec<3,float> t_vec3f;
+ typedef mln::util::array<t_vec3f> t_mean_array;
+
+ std::ifstream stream(colormap);
+ std::string buffer;
+
+ getline(stream, buffer);
+
+ while (0 < buffer.size())
+ {
+ std::stringstream line(buffer);
+ t_vec3f mean_v;
+
+ line >> mean_v;
+
+ m2_label.append(mean_v);
+
+ getline(stream, buffer);
+ }
+
+ stream.close();
+}
+
+/// \brief The image processing routine.
+///
+/// \param[in] labeled the name of the 3d labeled histogram.
+/// \param[in] d the depth for the zone influence transformation, 0 eq infinite.
+/// \param[in] nbh the neighbouring (c6|c18|c26).
+/// \param[in] input the 8 bit color ppm input image.
+/// \param[in] quant the name of quantified RGB input image.
+/// \param[in] histo the name of the 3d RGB quantified histogram.
+/// \param[in] colormap the name of the colormap for labels.
+/// \param[out] iz is the iz labeled 3d histogram.
+/// \param[out] proj the red/green projection of the segmented histogram.
+/// \param[out] mean the name of the mean rebuilded image.
+/// \param[out] stats the name of the statistics file (optional).
+///
+/// The core routine starts with image loading, then calls the rigth
+/// iz version and then dumps the results, computes the stats and
+/// makes r/g projection. The role of the iz routine is to propagated
+/// labels around the regional maxima to enlarge the small previous
+/// obtained regions.
+template<unsigned n>
+void mk_iz(const std::string& labeled, // in
+ const unsigned d, // in
+ const mln::neighb3d& nbh, // in
+ const std::string& input, // in
+ const std::string& quant, // in
+ const std::string& histo, // in
+ const std::string& colormap,// in
+ const std::string& iz, // out
+ const std::string& proj, // out
+ const std::string& mean, // out
+ const std::string& stats) // [out]
+{
+ typedef mln::value::int_u8 t_int_u8;
+ typedef mln::value::label_8 t_lbl8;
+ typedef mln::value::rgb8 t_rgb8;
+ typedef mln::value::rgb<n> t_rgbn;
+ typedef mln::algebra::vec<3,float> t_v3f;
+ typedef mln::image2d<t_int_u8> t_image2d_int_u8;
+ typedef mln::image2d<t_rgb8> t_image2d_rgb8;
+ typedef mln::image2d<t_rgbn> t_image2d_rgbn;
+ typedef mln::image2d<t_lbl8> t_image2d_lbl8;
+ typedef mln::image3d<unsigned> t_histo3d;
+ typedef mln::image3d<t_lbl8> t_image3d_lbl8;
+ typedef mln::accu::meta::stat::histo3d_rgb t_histo3d_fun;
+ typedef mln::accu::stat::mean<t_v3f,t_v3f,t_v3f> t_mean;
+ typedef mln::util::array<t_v3f> t_mean_array;
+
+ // START OF IMAGE PROCESSING CHAIN
+ t_image2d_rgb8 i0_input; // input img
+ t_image2d_rgbn i1_input; // quant img
+ t_histo3d h1_input; // histo input
+ t_histo3d h2_input; // histo input
+ t_image2d_int_u8 p1_histo; // histo proj
+ t_image2d_rgb8 p3_histo; // histo proj
+ t_image3d_lbl8 l2_histo; // label histo
+ t_image3d_lbl8 l3_histo; // iz label hist
+ t_mean_array m2_label; // colormap
+ t_mean_array m3_label; // colormap
+ t_image2d_lbl8 l3_input; // label input
+ t_image2d_rgb8 i3_mean; // reconstructed
+
+ t_lbl8 n_lbl; // nb labels
+ t_rgb8 red(mln::literal::red);
+
+ mln::io::dump::load(l2_histo, labeled.c_str());
+ mln::io::ppm::load(i0_input, input.c_str());
+ mln::io::ppm::load(i1_input, quant.c_str());
+ mln::io::dump::load(h1_input, histo.c_str());
+ load(m2_label, colormap.c_str());
+
+ if (0 == d)
+ {
+ l3_histo = mln::transform::influence_zone_geodesic(l2_histo, nbh);
+ }
+ else
+ {
+ l3_histo =mln::transform::influence_zone_geodesic_saturated(l2_histo,nbh,d);
+ }
+ // END OF IMAGE PROCESSING CHAIN
+
+ // BEGIN DUMPING
+
+ n_lbl = (t_lbl8)(m2_label.size()-1);
+
+ l3_input = mln::data::transform(i1_input, t_labeling_rgbn<n>(l3_histo));
+ i3_mean = mln::labeling::mean_values(i0_input, l3_input, n_lbl);
+ m3_label = mln::labeling::compute(t_mean(), i0_input, l3_input, n_lbl);
+
+ // CORRECT 0 LABEL STATS
+ m3_label[0][0] = 255.0;
+ m3_label[0][1] = 255.0;
+ m3_label[0][2] = 0.0;
+
+ p3_histo = mln::display::display3_histo3d_unsigned<n>(h1_input,
+ l3_histo,
+ m3_label,
+ red);
+ mln::io::dump::save(l3_input, iz.c_str());
+ mln::io::ppm::save(p3_histo, proj.c_str());
+ mln::io::ppm::save(i3_mean, mean.c_str());
+
+ if (0 < stats.size())
+ compute_stats(i0_input, l3_input, h1_input, l3_histo, n_lbl, stats);
+
+ // END DUMPING
+}
+
+
+/// \brief The online documentation of the tool.
+///
+/// Print the documentation of the tool with the meaning of the
+/// different parameters.
+void usage()
+{
+ std::cout << std::endl;
+ std::cout << "iz labeled.dump d nbh input.ppm q quant.ppm"
+ << " histo.dump colormap.txt iz.dump proj.ppm"
+ << " mean.ppm [stats.txt]" << std::endl;
+ std::cout << std::endl;
+ std::cout << "where :" << std::endl;
+ std::cout << "* [ in] labeled.dump is the labeled 3d histogram" << std::endl;
+ std::cout << "* [ in] d is the depth for the zone influence"
+ << " transformation (0 means infinite)" << std::endl;
+ std::cout << "* [ in] nbh is the 3d neighbourhood {6,18,26}" << std::endl;
+ std::cout << "* [ in] input.ppm is the 8 bits color ppm image" << std::endl;
+ std::cout << "* [ in] q is the degree of quantification"
+ << " {2,3,4,5,6,7,8}" << std::endl;
+ std::cout << "* [ in] quant.ppm is the q bits quantified input"
+ << " image" << std::endl;
+ std::cout << "* [ in] histo.dump is the quantified color"
+ << " histogram" << std::endl;
+ std::cout << "* [ in] colormap.txt is the colormap for labels" << std::endl;
+ std::cout << "* [out] iz.dump is the iz labeled 3d histogram" << std::endl;
+ std::cout << "* [out] proj.ppm is the r/g projection of the"
+ << " histogram with maxima label plot on" << std::endl;
+ std::cout << "* [out] mean.ppm is the mean reconstructed image" << std::endl;
+ std::cout << "* [out] stats.txt is the statistical label report"<< std::endl;
+ std::cout << std::endl;
+}
+
+/// \brief The main entry of the software.
+///
+/// \param[in] labeled.dump the name of the 3d labeled histogram.
+/// \param[in] d the depth for the zone influence transformation, 0 eq infinite.
+/// \param[in] nbh the code for the neighbouring (6|18|26).
+/// \param[in] input.ppm the 8 bit color ppm input image.
+/// \param[in] q is the degree of quantification {2,3,4,5,6,7,8}.
+/// \param[in] quant.ppm the name of quantified RGB input image.
+/// \param[in] histo.dump the name of the 3d RGB quantified histogram.
+/// \param[in] colormap.txt the name of the colormap for labels.
+/// \param[out] iz.dump is the iz labeled 3d histogram.
+/// \param[out] proj.ppm the red/green projection of the segmented histogram.
+/// \param[out] mean.ppm the name of the mean rebuilded image.
+/// \param[out] stats.txt the name of the statistics file (optional).
+///
+/// This is the front hand for the image processing routine. The goal of this
+/// chain is to provide 3d histogram for further analysis and to give a way to
+/// see it.
+int main(int argc, char* args[])
+{
+ if (12 == argc || 13 == argc)
+ {
+ const std::string labeled(args[1]); // in
+ const unsigned d = atoi(args[2]); // in
+ const char nbh = args[3][0]; // in
+ const std::string input(args[4]); // in
+ const char q = args[5][0]; // in
+ const std::string quant(args[6]); // in
+ const std::string histo(args[7]); // in
+ const std::string colormap(args[8]); // in
+ const std::string iz(args[9]); // out
+ const std::string proj(args[10]); // out
+ const std::string mean(args[11]); // out
+ const std::string stats(13 == argc? args[12] : ""); // [out]
+
+
+ mln::neighb3d neighbourhood;
+
+ switch (nbh)
+ {
+ case '6': neighbourhood = mln::c6(); break;
+ case '1': neighbourhood = mln::c18(); break;
+ case '2': neighbourhood = mln::c26(); break;
+ default: usage(); return 0; // force usage and quit
+ }
+
+ switch (q)
+ {
+ case '2' : mk_iz<2>(labeled,d,neighbourhood,input,quant,
+ histo,colormap,iz,proj,mean,stats);break;
+ case '3' : mk_iz<3>(labeled,d,neighbourhood,input,quant,
+ histo,colormap,iz,proj,mean,stats);break;
+ case '4' : mk_iz<4>(labeled,d,neighbourhood,input,quant,
+ histo,colormap,iz,proj,mean,stats);break;
+ case '5' : mk_iz<5>(labeled,d,neighbourhood,input,quant,
+ histo,colormap,iz,proj,mean,stats);break;
+ case '6' : mk_iz<6>(labeled,d,neighbourhood,input,quant,
+ histo,colormap,iz,proj,mean,stats);break;
+ case '7' : mk_iz<7>(labeled,d,neighbourhood,input,quant,
+ histo,colormap,iz,proj,mean,stats);break;
+ case '8' : mk_iz<8>(labeled,d,neighbourhood,input,quant,
+ histo,colormap,iz,proj,mean,stats);break;
+ default: usage(); break;
+ }
+ }
+ else
+ usage();
+
+ return 0;
+}
diff --git a/scribo/sandbox/green/tools/labeling/opening/Makefile.am b/scribo/sandbox/green/tools/labeling/opening/Makefile.am
new file mode 100644
index 0000000..f03a836
--- /dev/null
+++ b/scribo/sandbox/green/tools/labeling/opening/Makefile.am
@@ -0,0 +1,153 @@
+#
+# Generic Makefile
+#
+
+#########
+# TOOLS #
+#########
+
+#LOADLIBES= -lboost_filesystem
+INCLUDES1= -I$(HOME)/git/olena/scribo/sandbox/green
+INCLUDES2= -I$(HOME)/git/olena/milena
+INCLUDES= $(INCLUDES1) $(INCLUDES2)
+CXXFLAGS= -ggdb -O0 -Wall -W -pedantic -ansi -pipe $(INCLUDES)
+#CXXFLAGS= -DNDEBUG -O1 -Wall -W -pedantic -ansi -pipe $(INCLUDES)
+#CXXFLAGS= -DNDEBUG -O3 -Wall -W -pedantic -ansi -pipe $(INCLUDES)
+ECHO= echo
+RM= rm
+MKDIR= mkdir -p
+CP= cp
+
+SOURCE_PATTERN= green/tools
+BUILD__PATTERN= green/build/tools
+
+
+ifeq ($(findstring $(BUILD__PATTERN),$(PWD)), $(BUILD__PATTERN))
+# Case where make is done from build directory.
+SOURCE_DIR= $(subst $(BUILD__PATTERN),$(SOURCE_PATTERN),$(PWD))
+BUILD__DIR= $(PWD)/
+else
+# Case where make is done from source directory.
+SOURCE_DIR= $(PWD)/
+BUILD__DIR= $(subst $(SOURCE_PATTERN),$(BUILD__PATTERN),$(PWD))
+endif
+
+SRC= $(notdir $(wildcard $(SOURCE_DIR)/*.cc))
+OLD= $(notdir $(wildcard $(SOURCE_DIR)/*~))
+OBJ= $(patsubst %.cc,%.o,$(SRC))
+SOURCE_MAKEFILE=Makefile.am
+BUILD__MAKEFILE=Makefile
+TARGET_FILE= $(notdir $(PWD))
+SOURCE_FILES= $(notdir $(wildcard $(SOURCE_DIR)/*.*))
+BUILD__FILES= $(filter-out $(SRC) $(SOURCE_MAKEFILE), $(SOURCE_FILES))
+
+BUILD__F_PATH= $(addprefix $(BUILD__DIR)/,$(BUILD__FILES))
+SOURCE_F_PATH= $(addprefix $(SOURCE_DIR)/,$(SOURCE_FILES))
+
+BUILD__M_PATH= $(addprefix $(BUILD__DIR)/,$(BUILD__MAKEFILE))
+SOURCE_M_PATH= $(addprefix $(SOURCE_DIR)/,$(SOURCE_MAKEFILE))
+
+TARGET_F_PATH= $(addprefix $(BUILD__DIR)/,$(TARGET_FILE))
+OBJ_F_PATH= $(addprefix $(BUILD__DIR)/,$(OBJ))
+SRC_F_PATH= $(addprefix $(SOURCE_DIR)/,$(SRC))
+OLD_F_PATH= $(addprefix $(SOURCE_DIR)/,$(OLD))
+
+#############
+# BOOTSTRAP #
+#############
+
+
+bootstrap: $(BUILD__DIR) $(BUILD__F_PATH) $(BUILD__M_PATH)
+
+# Create, if nessary, the destination directory
+$(BUILD__DIR):
+ $(MKDIR) $(BUILD__DIR)
+
+# Copy, if nessary, all the files, except the Makefile.am
+$(BUILD__F_PATH): $(SOURCE_F_PATH)
+ $(CP) $(addprefix $(SOURCE_DIR),$(@F)) $@
+
+# Copy if nessary, the Makefile.am into Makefile
+$(BUILD__M_PATH): $(SOURCE_M_PATH)
+ $(CP) $(SOURCE_M_PATH) $(BUILD__M_PATH)
+
+
+#######
+# ALL #
+#######
+
+# We assume that the call is done from the build directory.
+# With the directive vpath, hidden files are found in the source directory.
+
+all: $(TARGET_F_PATH)
+
+
+$(TARGET_F_PATH): $(OBJ_F_PATH)
+ $(LINK.cc) $< $(LOADLIBES) $(LDLIBS) -o $@
+
+$(OBJ_F_PATH):$(SRC_F_PATH)
+ $(COMPILE.cc) $(OUTPUT_OPTION) $<
+
+
+#########
+# CLEAN #
+#########
+
+# Force every time the deletion
+clean: clean_target clean_obj clean_dst clean_old #clean_make
+
+
+clean_target:
+ -@$(RM) $(TARGET_F_PATH) &> /dev/null
+
+clean_obj:
+ -@$(RM) $(OBJ_F_PATH) &> /dev/null
+
+clean_dst:
+ -@$(RM) $(BUILD_F_PATH) &> /dev/null
+
+clean_make:
+ -@$(RM) $(BUILD_M_PATH) &> /dev/null
+
+clean_old:
+ -@$(RM) $(OLD_F_PATH) &> /dev/null
+
+
+#########
+# PRINT #
+#########
+
+print: print_tools print_bootstrap
+
+print_tools:
+ @$(ECHO) "HOME = $(HOME)"
+ @$(ECHO) "INCLUDES = $(INCLUDES)"
+ @$(ECHO) "CXXFLAGS = $(CXXFLAGS)"
+ @$(ECHO) "ECHO = $(ECHO)"
+ @$(ECHO) "RM = $(RM)"
+ @$(ECHO) "MKDIR = $(MKDIR)"
+ @$(ECHO) "CP = $(CP)"
+ @$(ECHO)
+
+print_bootstrap:
+ @$(ECHO) "PWD = $(PWD)"
+ @$(ECHO) "SOURCE_PATTERN = $(SOURCE_PATTERN)"
+ @$(ECHO) "BUILD__PATTERN = $(BUILD__PATTERN)"
+ @$(ECHO) "SOURCE_DIR = $(SOURCE_DIR)"
+ @$(ECHO) "BUILD__DIR = $(BUILD__DIR)"
+ @$(ECHO) "SOURCE_MAKEFILE = $(SOURCE_MAKEFILE)"
+ @$(ECHO) "BUILD__MAKEFILE = $(BUILD__MAKEFILE)"
+ @$(ECHO) "TARGET_FILE = $(TARGET_FILE)"
+ @$(ECHO) "SOURCE_FILES = $(SOURCE_FILES)"
+ @$(ECHO) "SOURCE_F_PATH = $(SOURCE_F_PATH)"
+ @$(ECHO) "BUILD__FILES = $(BUILD__FILES)"
+ @$(ECHO) "BUILD__F_PATH = $(BUILD__F_PATH)"
+ @$(ECHO) "BUILD__M_PATH = $(BUILD__M_PATH)"
+ @$(ECHO) "SOURCE_M_PATH = $(SOURCE_M_PATH)"
+ @$(ECHO) "SRC = $(SRC)"
+ @$(ECHO) "OBJ = $(OBJ)"
+ @$(ECHO) "OLD = $(OLD)"
+ @$(ECHO) "SRC_F_PATH = $(SRC_F_PATH)"
+ @$(ECHO) "OBJ_F_PATH = $(OBJ_F_PATH)"
+ @$(ECHO) "OLD_F_PATH = $(OLD_F_PATH)"
+ @$(ECHO)
diff --git a/scribo/sandbox/green/tools/labeling/opening/opening.cc b/scribo/sandbox/green/tools/labeling/opening/opening.cc
new file mode 100644
index 0000000..c4f1cb9
--- /dev/null
+++ b/scribo/sandbox/green/tools/labeling/opening/opening.cc
@@ -0,0 +1,174 @@
+// Copyright (C) 2007, 2008, 2009, 2010 EPITA 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.
+
+/// \file
+///
+/// \brief This tool aimed at filtering the previous 3d RGB histogram.
+///
+/// The current filtering is managed with morphological volume attribute.
+///
+/// \fixme I don't know if the volume attribute do well it's
+/// job. Sometimes, there is something strange happened. I know it's
+/// related to that part of processing but i can't tell where it is wrong.
+
+#include <iostream>
+
+#include <mln/accu/stat/histo3d_rgb.hh>
+
+#include <mln/core/macros.hh>
+#include <mln/core/alias/neighb3d.hh>
+#include <mln/core/image/image2d.hh>
+#include <mln/core/image/image3d.hh>
+
+#include <mln/data/compute.hh>
+
+#include <mln/display/display_histo.hh>
+
+#include <mln/io/dump/load.hh>
+#include <mln/io/dump/save.hh>
+#include <mln/io/ppm/save.hh>
+#include <mln/io/pgm/save.hh>
+
+#include <mln/literal/colors.hh>
+
+#include <mln/morpho/opening/volume.hh>
+
+#include <mln/value/rgb.hh>
+#include <mln/value/int_u8.hh>
+
+/// \brief The histogram image processing chain.
+///
+/// \param[in] histo the name of the input histogram to filter.
+/// \param[in] min_vol the minimum volume threshold to leave in the image.
+/// \param[out] opened the name of the filtered histogram.
+/// \param[out] proj1 the red/green projection of the histogram.
+/// \param[out] proj2 the red/green projection with maxima plot on.
+///
+/// This chain aimed at filtering 3d RGB histogram by volume
+/// morphological attribute. The threshold indicates the minimum
+/// volume information to leave, otherwhise information with less
+/// volume attribute is discarded. Then, dumping and
+/// projections are done.
+template <unsigned n>
+void mk_opening(const std::string& histo, // in
+ const unsigned min_vol, // in
+ const std::string& opened, // out
+ const std::string& proj1, // out
+ const std::string& proj2) // out
+{
+ typedef mln::value::int_u8 t_int_u8;
+ typedef mln::value::rgb<n> t_rgbn;
+ typedef mln::image2d<t_int_u8> t_image2d_int_u8;
+ typedef mln::image2d<t_rgbn> t_image2d_rgbn;
+ typedef mln::image3d<unsigned> t_histo3d;
+ typedef mln::accu::meta::stat::histo3d_rgb t_histo3d_fun;
+
+ // START OF IMAGE PROCESSING CHAIN
+ t_histo3d h1_input; // histo input
+ t_histo3d h2_input; // histo input
+ t_image2d_int_u8 p1_histo1;// histo proj1
+ t_image2d_rgbn p1_histo2;// histo proj2
+ t_rgbn red(mln::literal::red);
+
+ mln::io::dump::load(h1_input, histo.c_str());
+ h2_input = mln::morpho::opening::volume(h1_input, mln::c6(), min_vol);
+ // END OF IMAGE PROCESSING CHAIN
+
+ // BEGIN DUMPING
+ p1_histo1 = mln::display::display_histo3d_unsigned(h2_input);
+ p1_histo2 = mln::display::display3_histo3d_unsigned(h2_input, red);
+ mln::io::dump::save(h2_input, opened.c_str());
+ mln::io::pgm::save(p1_histo1, proj1.c_str());
+ mln::io::ppm::save(p1_histo2, proj2.c_str());
+ // END DUMPING
+}
+
+
+/// \brief The online documentation of the tool.
+///
+/// Print the documentation of the tool with the meaning of the
+/// different parameters.
+void usage()
+{
+ std::cout << std::endl;
+ std::cout << "opening q histo.dump v opened.dump proj.pgm"
+ << " proj.ppm" << std::endl;
+ std::cout << std::endl;
+ std::cout << "where :" << std::endl;
+ std::cout << "* [ in] q is the degree of quantification"
+ << " {2,3,4,5,6,7,8}" << std::endl;
+ std::cout << "* [ in] histo.dump is the quantified color"
+ << " histogram" << std::endl;
+ std::cout << "* [ in] v is the minimum size (in pixels) of"
+ << " each composant" << std::endl;
+ std::cout << "* [out] opened.dump is the filtered histogram" << std::endl;
+ std::cout << "* [out] proj.pgm is the r/g projection of the"
+ << " histogram (summing along the blue axe)" << std::endl;
+ std::cout << "* [out] proj.ppm is the r/g projection of the"
+ << " histogram with maxima plot on" << std::endl;
+ std::cout << std::endl;
+}
+
+
+/// \brief The main entry of the software.
+///
+/// \param[in] q the quantification previously used.
+/// \param[in] histo the name of the 3d RGB histogram to filter.
+/// \param[in] min_vol the threshold of the morphological filtering.
+/// \param[out] opened.dump the name of the resulting 3d histogram.
+/// \param[out] proj.pgm the red/green projection of the histogram.
+/// \param[out] proj2.ppm the red/green projection with maxima plot on.
+///
+/// This is the front hand for the image processing routine. The goal of this
+/// chain is to filter 3d histogram for further analysis and to give a way to
+/// see it.
+int main(int argc, char* args[])
+{
+ if (7 == argc)
+ {
+ const char q = args[1][0]; // in
+ const std::string histo(args[2]); // in
+ const unsigned min_vol = atoi(args[3]); // in
+ const std::string opened(args[4]); // out
+ const std::string proj1(args[5]); // out
+ const std::string proj2(args[6]); // out
+
+ switch(q)
+ {
+ case '2': mk_opening<2>(histo, min_vol, opened, proj1, proj2); break;
+ case '3': mk_opening<3>(histo, min_vol, opened, proj1, proj2); break;
+ case '4': mk_opening<4>(histo, min_vol, opened, proj1, proj2); break;
+ case '5': mk_opening<5>(histo, min_vol, opened, proj1, proj2); break;
+ case '6': mk_opening<6>(histo, min_vol, opened, proj1, proj2); break;
+ case '7': mk_opening<7>(histo, min_vol, opened, proj1, proj2); break;
+ case '8': mk_opening<8>(histo, min_vol, opened, proj1, proj2); break;
+ default: usage(); break;
+ }
+ }
+ else
+ usage();
+
+ return 0;
+}
diff --git a/scribo/sandbox/green/tools/labeling/regmax/Makefile.am b/scribo/sandbox/green/tools/labeling/regmax/Makefile.am
new file mode 100644
index 0000000..f03a836
--- /dev/null
+++ b/scribo/sandbox/green/tools/labeling/regmax/Makefile.am
@@ -0,0 +1,153 @@
+#
+# Generic Makefile
+#
+
+#########
+# TOOLS #
+#########
+
+#LOADLIBES= -lboost_filesystem
+INCLUDES1= -I$(HOME)/git/olena/scribo/sandbox/green
+INCLUDES2= -I$(HOME)/git/olena/milena
+INCLUDES= $(INCLUDES1) $(INCLUDES2)
+CXXFLAGS= -ggdb -O0 -Wall -W -pedantic -ansi -pipe $(INCLUDES)
+#CXXFLAGS= -DNDEBUG -O1 -Wall -W -pedantic -ansi -pipe $(INCLUDES)
+#CXXFLAGS= -DNDEBUG -O3 -Wall -W -pedantic -ansi -pipe $(INCLUDES)
+ECHO= echo
+RM= rm
+MKDIR= mkdir -p
+CP= cp
+
+SOURCE_PATTERN= green/tools
+BUILD__PATTERN= green/build/tools
+
+
+ifeq ($(findstring $(BUILD__PATTERN),$(PWD)), $(BUILD__PATTERN))
+# Case where make is done from build directory.
+SOURCE_DIR= $(subst $(BUILD__PATTERN),$(SOURCE_PATTERN),$(PWD))
+BUILD__DIR= $(PWD)/
+else
+# Case where make is done from source directory.
+SOURCE_DIR= $(PWD)/
+BUILD__DIR= $(subst $(SOURCE_PATTERN),$(BUILD__PATTERN),$(PWD))
+endif
+
+SRC= $(notdir $(wildcard $(SOURCE_DIR)/*.cc))
+OLD= $(notdir $(wildcard $(SOURCE_DIR)/*~))
+OBJ= $(patsubst %.cc,%.o,$(SRC))
+SOURCE_MAKEFILE=Makefile.am
+BUILD__MAKEFILE=Makefile
+TARGET_FILE= $(notdir $(PWD))
+SOURCE_FILES= $(notdir $(wildcard $(SOURCE_DIR)/*.*))
+BUILD__FILES= $(filter-out $(SRC) $(SOURCE_MAKEFILE), $(SOURCE_FILES))
+
+BUILD__F_PATH= $(addprefix $(BUILD__DIR)/,$(BUILD__FILES))
+SOURCE_F_PATH= $(addprefix $(SOURCE_DIR)/,$(SOURCE_FILES))
+
+BUILD__M_PATH= $(addprefix $(BUILD__DIR)/,$(BUILD__MAKEFILE))
+SOURCE_M_PATH= $(addprefix $(SOURCE_DIR)/,$(SOURCE_MAKEFILE))
+
+TARGET_F_PATH= $(addprefix $(BUILD__DIR)/,$(TARGET_FILE))
+OBJ_F_PATH= $(addprefix $(BUILD__DIR)/,$(OBJ))
+SRC_F_PATH= $(addprefix $(SOURCE_DIR)/,$(SRC))
+OLD_F_PATH= $(addprefix $(SOURCE_DIR)/,$(OLD))
+
+#############
+# BOOTSTRAP #
+#############
+
+
+bootstrap: $(BUILD__DIR) $(BUILD__F_PATH) $(BUILD__M_PATH)
+
+# Create, if nessary, the destination directory
+$(BUILD__DIR):
+ $(MKDIR) $(BUILD__DIR)
+
+# Copy, if nessary, all the files, except the Makefile.am
+$(BUILD__F_PATH): $(SOURCE_F_PATH)
+ $(CP) $(addprefix $(SOURCE_DIR),$(@F)) $@
+
+# Copy if nessary, the Makefile.am into Makefile
+$(BUILD__M_PATH): $(SOURCE_M_PATH)
+ $(CP) $(SOURCE_M_PATH) $(BUILD__M_PATH)
+
+
+#######
+# ALL #
+#######
+
+# We assume that the call is done from the build directory.
+# With the directive vpath, hidden files are found in the source directory.
+
+all: $(TARGET_F_PATH)
+
+
+$(TARGET_F_PATH): $(OBJ_F_PATH)
+ $(LINK.cc) $< $(LOADLIBES) $(LDLIBS) -o $@
+
+$(OBJ_F_PATH):$(SRC_F_PATH)
+ $(COMPILE.cc) $(OUTPUT_OPTION) $<
+
+
+#########
+# CLEAN #
+#########
+
+# Force every time the deletion
+clean: clean_target clean_obj clean_dst clean_old #clean_make
+
+
+clean_target:
+ -@$(RM) $(TARGET_F_PATH) &> /dev/null
+
+clean_obj:
+ -@$(RM) $(OBJ_F_PATH) &> /dev/null
+
+clean_dst:
+ -@$(RM) $(BUILD_F_PATH) &> /dev/null
+
+clean_make:
+ -@$(RM) $(BUILD_M_PATH) &> /dev/null
+
+clean_old:
+ -@$(RM) $(OLD_F_PATH) &> /dev/null
+
+
+#########
+# PRINT #
+#########
+
+print: print_tools print_bootstrap
+
+print_tools:
+ @$(ECHO) "HOME = $(HOME)"
+ @$(ECHO) "INCLUDES = $(INCLUDES)"
+ @$(ECHO) "CXXFLAGS = $(CXXFLAGS)"
+ @$(ECHO) "ECHO = $(ECHO)"
+ @$(ECHO) "RM = $(RM)"
+ @$(ECHO) "MKDIR = $(MKDIR)"
+ @$(ECHO) "CP = $(CP)"
+ @$(ECHO)
+
+print_bootstrap:
+ @$(ECHO) "PWD = $(PWD)"
+ @$(ECHO) "SOURCE_PATTERN = $(SOURCE_PATTERN)"
+ @$(ECHO) "BUILD__PATTERN = $(BUILD__PATTERN)"
+ @$(ECHO) "SOURCE_DIR = $(SOURCE_DIR)"
+ @$(ECHO) "BUILD__DIR = $(BUILD__DIR)"
+ @$(ECHO) "SOURCE_MAKEFILE = $(SOURCE_MAKEFILE)"
+ @$(ECHO) "BUILD__MAKEFILE = $(BUILD__MAKEFILE)"
+ @$(ECHO) "TARGET_FILE = $(TARGET_FILE)"
+ @$(ECHO) "SOURCE_FILES = $(SOURCE_FILES)"
+ @$(ECHO) "SOURCE_F_PATH = $(SOURCE_F_PATH)"
+ @$(ECHO) "BUILD__FILES = $(BUILD__FILES)"
+ @$(ECHO) "BUILD__F_PATH = $(BUILD__F_PATH)"
+ @$(ECHO) "BUILD__M_PATH = $(BUILD__M_PATH)"
+ @$(ECHO) "SOURCE_M_PATH = $(SOURCE_M_PATH)"
+ @$(ECHO) "SRC = $(SRC)"
+ @$(ECHO) "OBJ = $(OBJ)"
+ @$(ECHO) "OLD = $(OLD)"
+ @$(ECHO) "SRC_F_PATH = $(SRC_F_PATH)"
+ @$(ECHO) "OBJ_F_PATH = $(OBJ_F_PATH)"
+ @$(ECHO) "OLD_F_PATH = $(OLD_F_PATH)"
+ @$(ECHO)
diff --git a/scribo/sandbox/green/tools/labeling/regmax/regmax.cc b/scribo/sandbox/green/tools/labeling/regmax/regmax.cc
new file mode 100644
index 0000000..1fc9976
--- /dev/null
+++ b/scribo/sandbox/green/tools/labeling/regmax/regmax.cc
@@ -0,0 +1,428 @@
+// Copyright (C) 2007, 2008, 2009, 2010 EPITA 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.
+
+/// \file
+///
+/// \brief This tool aimed at segmenting the histogram.
+///
+/// The current segmentation of the histogram is done by finding the
+/// regional maxima. Regional maxima are isolated small regions inside
+/// the background (label 0).
+
+#include <iostream>
+#include <fstream>
+#include <boost/format.hpp>
+
+#include <mln/accu/stat/histo3d_rgb.hh>
+#include <mln/accu/stat/mean.hh>
+
+#include <mln/algebra/vec.hh>
+
+#include <mln/core/macros.hh>
+#include <mln/core/alias/neighb3d.hh>
+#include <mln/core/image/image2d.hh>
+#include <mln/core/image/image3d.hh>
+
+#include <mln/data/compute.hh>
+
+#include <mln/debug/println.hh>
+#include <mln/display/display_histo.hh>
+
+#include <mln/io/dump/load.hh>
+#include <mln/io/dump/save.hh>
+#include <mln/io/pgm/load.hh>
+#include <mln/io/pgm/save.hh>
+#include <mln/io/ppm/load.hh>
+#include <mln/io/ppm/save.hh>
+
+#include <mln/labeling/regional_maxima.hh>
+#include <mln/labeling/compute.hh>
+#include <mln/labeling/mean_values.hh>
+
+#include <mln/literal/colors.hh>
+
+#include <mln/morpho/opening/volume.hh>
+
+#include <mln/value/label_8.hh>
+#include <mln/value/int_u8.hh>
+#include <mln/value/rgb8.hh>
+
+#include <mln/util/array.hh>
+
+/// \ brief Compute the 2d labeled image.
+///
+/// Compute the 2d labeled image with the 2d labeled histogram and
+/// the input image.
+///
+/// \fixme Need to put it in mln library. Nothing to do here.
+template <unsigned n>
+struct t_labeling_rgbn : mln::Function_v2v< t_labeling_rgbn<n> >
+{
+ typedef mln::value::rgb<n> t_rgbn;
+ typedef mln::value::label_8 t_lbl8;
+ typedef t_rgbn argument;
+ typedef t_lbl8 result;
+ typedef mln::image3d<t_lbl8> t_label;
+
+ const t_label& _label;
+
+ t_labeling_rgbn(const t_label& label) : _label(label) {}
+
+ result operator()(const argument& c) const
+ {
+ t_lbl8 tmp = mln::opt::at(_label, c.blue(), c.red(), c.green());
+
+ return tmp;
+ }
+};
+
+
+/// \brief Compute and dump stats.
+///
+/// \param[in] i_input_rgb8 the 2d rgb input image.
+/// \param[in] l_input_lbl8 the 2d labeled image.
+/// \param[in] h_histo_rgbn the quantified histogram.
+/// \param[in] l_histo_lbl8 the labeled quantified histogram.
+/// \param[in] n_labels the number of labels (number of regions).
+/// \param[in] the name of the logging file for the stats.
+///
+/// Every segmented color has got it's own label. For each label, we
+/// compute the mean in the r/g/b channels, the total of pixels, the
+/// percentage of pixels in the image and the percentage without counting
+/// the background (label 0).
+void compute_stats(const mln::image2d<mln::value::rgb8>& i_input_rgb8,
+ const mln::image2d<mln::value::label_8>& l_input_lbl8,
+ const mln::image3d<unsigned>& h_histo_rgbn,
+ const mln::image3d<mln::value::label_8>& l_histo_lbl8,
+ const mln::value::label_8& n_labels,
+ const std::string& log)
+{
+ typedef mln::algebra::vec<3,float> t_vec3f;
+ typedef mln::accu::math::sum<unsigned,unsigned> t_sum;
+ typedef mln::accu::stat::mean<t_vec3f,t_vec3f,t_vec3f> t_mean;
+ typedef mln::util::array<unsigned> t_count_array;
+ typedef mln::util::array<t_vec3f> t_mean_array;
+
+ mln::util::array<float> abs((unsigned)(n_labels)+1);
+ mln::util::array<float> rel((unsigned)(n_labels)+1);
+ unsigned nb = 0;
+
+ for (unsigned i = 0; i <= n_labels; ++i)
+ {
+ abs[i] = 0.0;
+ rel[i] = 0.0;
+ }
+
+ // COMPUTE THE SUM
+ t_count_array count = mln::labeling::compute(t_sum(),
+ h_histo_rgbn,
+ l_histo_lbl8,
+ n_labels);
+
+ // COMPUTE THE TOTAL
+ for (unsigned i = 0; i <= n_labels; ++i)
+ {
+ unsigned c = count[i];
+ nb += c;
+ }
+
+ // COMPUTE THE PERCENTAGES
+ for (unsigned i = 0; i <= n_labels; ++i)
+ if (0 < count[i])
+ {
+ abs[i] = ((float)count[i] / nb)*100.0;
+ rel[i] = ((float)count[i] / (nb - count[0]))*100.0;
+ }
+
+ // COMPUTE THE MEAN
+
+ t_mean_array mean = mln::labeling::compute(t_mean(),
+ i_input_rgb8,
+ l_input_lbl8,
+ n_labels);
+
+ // CORRECT 0 LABEL STATS
+ rel[0] = 0;
+ mean[0][0] = 255.0;
+ mean[0][1] = 255.0;
+ mean[0][2] = 0.0;
+
+ // PRINT STATS
+ std::ofstream log_stream(log.c_str());
+
+ for (unsigned i = 0; i <= n_labels; ++i)
+ {
+ const t_vec3f& mean_v = mean[i];
+
+ log_stream << boost::format("%2i|"
+ "r = %6.2f, g = %6.2f, b = %6.2f |"
+ "c = %7i, %%i = %5.2f, %%c = %5.2f")
+ % i
+ % mean_v[0]
+ % mean_v[1]
+ % mean_v[2]
+ % count[i]
+ % abs[i]
+ % rel[i]
+ << std::endl;
+ }
+
+ log_stream << std::endl << std::endl;
+ log_stream.flush();
+ log_stream.close();
+}
+
+
+
+/// \brief Dump the colormap.
+///
+/// \param[in] m2_label the internal representation of the colormap.
+/// \param[in] colormap the name of the colormap in the filesystem.
+///
+/// Take an dynamic array of 3d vector which represents the colormap.
+/// Use boost formatting to dump it properly.
+void save(mln::util::array< mln::algebra::vec<3,float> >& m2_label,
+ const char *colormap)
+{
+ typedef mln::algebra::vec<3,float> t_vec3f;
+ typedef mln::util::array<t_vec3f> t_mean_array;
+
+ std::ofstream stream(colormap);
+
+ for (unsigned i = 0; i < m2_label.size(); ++i)
+ {
+ const t_vec3f& mean_v = m2_label[i];
+
+ stream << boost::format("%2i | r = %6.2f, g = %6.2f, b = %6.2f")
+ % i
+ % mean_v[0]
+ % mean_v[1]
+ % mean_v[2]
+ << std::endl;
+ }
+
+ stream.flush();
+ stream.close();
+}
+
+
+/// \brief The regmax image processing chain.
+///
+/// \param[in] input the name of the RGB input image.
+/// \param[in] quant the name of quantified RGB input image.
+/// \param[in] histo the name of the 3d RGB histogram to filter.
+/// \param[in] opened the name of 3d histogram.
+/// \param[in] nbh the neighbouring (c6|c18|c26).
+/// \param[out] labeled the 3d labeled histogram.
+/// \param[out] proj the red/green projection of the segmented histogram.
+/// \param[out] colormap the name of the colormap produced.
+/// \param[out] mean the name of the mean rebuilded image.
+/// \param[out] stats the name of the statistics (optional).
+///
+/// This is the core routine of this file. First every input file
+/// (images or histograms) are loaded. Then regional labeling is
+/// done. And finally, every colormap dumping, stats saving,
+/// projection is done.
+template <unsigned n>
+void mk_regmax(const std::string& input, // in
+ const std::string& quant, // in
+ const std::string& histo, // in
+ const std::string& opened, // in
+ const mln::neighb3d& nbh, // in
+ const std::string& labeled, // out
+ const std::string& proj, // out
+ const std::string& colormap,// out
+ const std::string& mean, // out
+ const std::string& stats) // [out]
+{
+ typedef mln::value::label_8 t_lbl8;
+ typedef mln::value::rgb8 t_rgb8;
+ typedef mln::value::rgb<n> t_rgbn;
+ typedef mln::value::int_u8 t_int_u8;
+ typedef mln::value::int_u<n> t_int_un;
+ typedef mln::algebra::vec<3,float> t_v3f;
+ typedef mln::image2d<t_int_u8> t_image2d_int_u8;
+ typedef mln::image2d<t_int_un> t_image2d_int_un;
+ typedef mln::image2d<t_rgb8> t_image2d_rgb8;
+ typedef mln::image2d<t_rgbn> t_image2d_rgbn;
+ typedef mln::image3d<t_lbl8> t_image3d_lbl8;
+ typedef mln::image2d<t_lbl8> t_image2d_lbl8;
+ typedef mln::image3d<unsigned> t_histo3d;
+ typedef mln::accu::meta::stat::histo3d_rgb t_histo3d_fun;
+ typedef mln::accu::stat::mean<t_v3f,t_v3f,t_v3f> t_mean;
+ typedef mln::util::array<t_v3f> t_mean_array;
+
+ t_image2d_rgb8 i0_input; // input img
+ t_image2d_rgbn i1_input; // quant img
+ t_histo3d h1_input; // input histo
+ t_histo3d h2_input; // opened histo
+ t_image2d_rgb8 p2_label; // histo proj
+ t_image3d_lbl8 l2_histo; // label histo
+ t_image2d_lbl8 l2_input; // label input
+ t_mean_array m2_label; // colormap
+ t_image2d_rgb8 i2_mean; // reconstructed
+
+ t_lbl8 n_lbl; // nb class
+ t_rgb8 red(mln::literal::red);
+
+
+ // BEGIN LOADING
+ mln::io::ppm::load(i0_input, input.c_str());
+ mln::io::ppm::load(i1_input, quant.c_str());
+ mln::io::dump::load(h1_input, histo.c_str());
+ mln::io::dump::load(h2_input, opened.c_str());
+ // END LOADING
+
+ // BEGIN IMAGE PROCESSING
+ l2_histo = mln::labeling::regional_maxima(h2_input, nbh, n_lbl);
+ // END IMAGE PROCESSING
+
+ // BEGIN SAVING
+ mln::io::dump::save(l2_histo, labeled.c_str());
+
+ l2_input = mln::data::transform(i1_input, t_labeling_rgbn<n>(l2_histo));
+ i2_mean = mln::labeling::mean_values(i0_input, l2_input, n_lbl);
+ m2_label = mln::labeling::compute(t_mean(), i0_input, l2_input, n_lbl);
+
+ // CORRECT 0 LABEL STATS
+ m2_label[0][0] = 255.0;
+ m2_label[0][1] = 255.0;
+ m2_label[0][2] = 0.0;
+
+ p2_label =mln::display::display3_histo3d_unsigned<n>(h1_input,
+ l2_histo,
+ m2_label,
+ red);
+
+ mln::io::ppm::save(p2_label, proj.c_str());
+ save(m2_label, colormap.c_str());
+ mln::io::ppm::save(i2_mean, mean.c_str());
+
+ if (0 < stats.size())
+ compute_stats(i0_input, l2_input, h1_input, l2_histo, n_lbl, stats);
+
+ // END SAVING
+}
+
+
+/// \brief The online documentation of the tool.
+///
+/// Print the documentation of the tool with the meaning of the
+/// different parameters.
+void usage()
+{
+ std::cout << std::endl;
+ std::cout << "regmax input.ppm q quant.ppm histo.dump"
+ << " opened.dump nbh labeled.dump proj.ppm"
+ << " colormap.txt mean.ppm [stats.txt]" << std::endl;
+ std::cout << std::endl;
+ std::cout << "where :" << std::endl;
+ std::cout << "* [ in] input.ppm is the 8 bits color ppm image" << std::endl;
+ std::cout << "* [ in] q is the degree of quantification"
+ << " {2,3,4,5,6,7,8}" << std::endl;
+ std::cout << "* [ in] quant.ppm is the q bits quantified input"
+ << " image" << std::endl;
+ std::cout << "* [ in] histo.dump is the quantified color"
+ << " histogram" << std::endl;
+ std::cout << "* [ in] opened.dump is the filtered histogram" << std::endl;
+ std::cout << "* [ in] nbh is the 3d neighbourhood {6,18,26}" << std::endl;
+ std::cout << "* [out] labeled.dump is the labeled 3d histogram" << std::endl;
+ std::cout << "* [out] proj.ppm is the r/g projection of the"
+ << " histogram with maxima label plot on" << std::endl;
+ std::cout << "* [out] colormap.txt is the colormap for labels" << std::endl;
+ std::cout << "* [out] mean.ppm is the mean reconstructed image" << std::endl;
+ std::cout << "* [out] stats.txt is the statistical label report"<< std::endl;
+ std::cout << std::endl;
+}
+
+
+/// \brief The main entry of the software.
+///
+/// \param[in] input.ppm the name of the RGB input image.
+/// \param[in] q the quantification previously used.
+/// \param[in] quant.ppm the name of quantified RGB input image.
+/// \param[in] histo.dump the name of the 3d RGB histogram to filter.
+/// \param[in] opened.dump the name of 3d histogram.
+/// \param[in] nbh the code for the neighbouring (6|18|26).
+/// \param[out] labeled.dump the 3d labeled histogram.
+/// \param[out] proj.ppm the red/green projection of the segmented histogram.
+/// \param[out] colormap.txt the name of the colormap produced.
+/// \param[out] mean.ppm the name of the mean rebuilded image.
+/// \param[out] stats.txt the name of the statistics file (optional).
+///
+/// This is the front hand for the image processing routine. The goal of this
+/// chain is to segment the 3d histogram.
+int main(int argc, char* args[])
+{
+ if (11 == argc || 12 == argc)
+ {
+ const std::string input(args[1]); // in
+ const char q = args[2][0]; // in
+ const std::string quant(args[3]); // in
+ const std::string histo(args[4]); // in
+ const std::string opened(args[5]); // in
+ const char nbh = args[6][0]; // in
+ const std::string labeled(args[7]); // out
+ const std::string proj(args[8]); // out
+ const std::string colormap(args[9]);// out
+ const std::string mean(args[10]); // out
+ const std::string stats(12 == argc? args[11] : ""); // [out]
+
+
+ mln::neighb3d neighbourhood;
+
+ switch (nbh)
+ {
+ case '6': neighbourhood = mln::c6(); break;
+ case '1': neighbourhood = mln::c18(); break;
+ case '2': neighbourhood = mln::c26(); break;
+ default: usage(); return 0; // force usage and quit
+ }
+
+ switch (q)
+ {
+
+ case '2': mk_regmax<2>(input,quant,histo,opened,neighbourhood,
+ labeled,proj,colormap,mean,stats); break;
+ case '3': mk_regmax<3>(input,quant,histo,opened,neighbourhood,
+ labeled,proj,colormap,mean,stats); break;
+ case '4': mk_regmax<4>(input,quant,histo,opened,neighbourhood,
+ labeled,proj,colormap,mean,stats); break;
+ case '5': mk_regmax<5>(input,quant,histo,opened,neighbourhood,
+ labeled,proj,colormap,mean,stats); break;
+ case '6': mk_regmax<6>(input,quant,histo,opened,neighbourhood,
+ labeled,proj,colormap,mean,stats); break;
+ case '7': mk_regmax<7>(input,quant,histo,opened,neighbourhood,
+ labeled,proj,colormap,mean,stats); break;
+ case '8': mk_regmax<8>(input,quant,histo,opened,neighbourhood,
+ labeled,proj,colormap,mean,stats); break;
+ default: usage(); break;
+ }
+ }
+ else
+ usage();
+
+ return 0;
+}
diff --git a/scribo/sandbox/green/use/accu/stat/histo1d/Makefile.am b/scribo/sandbox/green/use/display/display_histo/Makefile.am
similarity index 100%
copy from scribo/sandbox/green/use/accu/stat/histo1d/Makefile.am
copy to scribo/sandbox/green/use/display/display_histo/Makefile.am
diff --git a/scribo/sandbox/green/use/display/display_histo/display_histo.cc b/scribo/sandbox/green/use/display/display_histo/display_histo.cc
new file mode 100644
index 0000000..090b609
--- /dev/null
+++ b/scribo/sandbox/green/use/display/display_histo/display_histo.cc
@@ -0,0 +1,86 @@
+// 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.
+
+/// \file
+///
+/// \brief Sample code to use the red/green visualization.
+///
+/// \fixme There is a lot of routines in display_histo.hh, but only
+/// two of them have been call here. It's a poor job from me, but i've
+/// the time to do it know.
+
+#include <iostream>
+#include <mln/accu/stat/histo3d_rgb.hh>
+#include <mln/core/macros.hh>
+#include <mln/core/image/image2d.hh>
+#include <mln/core/image/image3d.hh>
+#include <mln/data/compute.hh>
+#include <mln/data/transform.hh>
+#include <mln/display/display_histo.hh>
+#include <mln/fun/v2v/rgb8_to_rgbn.hh>
+#include <mln/img_path.hh>
+#include <mln/io/ppm/load.hh>
+#include <mln/io/pgm/save.hh>
+#include <mln/io/ppm/save.hh>
+#include <mln/literal/colors.hh>
+#include <mln/value/rgb8.hh>
+#include <mln/value/rgb.hh>
+
+int main()
+{
+ typedef mln::value::int_u8 t_int_u8;
+ typedef mln::value::int_u<4> t_int_u4;
+ typedef mln::value::rgb8 t_rgb8;
+ typedef mln::value::rgb<4> t_rgb4;
+ typedef mln::image2d<t_int_u8> t_image2d_int_u8;
+ typedef mln::image2d<t_int_u4> t_image2d_int_u4;
+ typedef mln::image2d<t_rgb8> t_image2d_rgb8;
+ typedef mln::image2d<t_rgb4> t_image2d_rgb4;
+ typedef mln::image2d<bool> t_image2d_bool;
+ typedef mln::image3d<unsigned> t_histo3d;
+ typedef mln::fun::v2v::rgb8_to_rgbn<4> t_rgb8_to_rgb4;
+ typedef mln::accu::meta::stat::histo3d_rgb t_histo3d_fun;
+
+ t_image2d_rgb8 i0_input; // input rgb8
+ t_image2d_rgb4 i1_input; // input rgbn
+ t_histo3d h1_input; // histo input
+ t_image2d_int_u8 p1_histo1;// histo proj1
+ t_image2d_rgb4 p1_histo2;// histo proj2
+ t_rgb4 red(mln::literal::red);
+
+ mln::io::ppm::load(i0_input, OLENA_IMG_PATH"/lena.ppm");
+
+ i1_input = mln::data::transform(i0_input, t_rgb8_to_rgb4());
+ h1_input = mln::data::compute(t_histo3d_fun(), i1_input);
+ p1_histo1 = mln::display::display_histo3d_unsigned(h1_input);
+ p1_histo2 = mln::display::display3_histo3d_unsigned(h1_input, red);
+
+ mln::io::pgm::save(p1_histo1, "proj1.pgm");
+ mln::io::ppm::save(p1_histo2, "proj2.ppm");
+
+ return 0;
+}
--
1.5.6.5
14Â years, 2Â months
- 1
- 0
last-svn-commit-20-gcfe8986 Experiment variation on regional maxima labeling.
by Guillaume Lazzara
* green/demo/labeling/regional_maxima/regional_maxima.cc
(demo_17_12_2009): New function that describes the experimentation.
---
milena/sandbox/ChangeLog | 7 +
.../labeling/regional_maxima/regional_maxima.cc | 702 ++++++++++----------
2 files changed, 367 insertions(+), 342 deletions(-)
diff --git a/milena/sandbox/ChangeLog b/milena/sandbox/ChangeLog
index 3a7ffb7..8a92218 100644
--- a/milena/sandbox/ChangeLog
+++ b/milena/sandbox/ChangeLog
@@ -1,3 +1,10 @@
+2009-12-23 Yann Jacquelet <jacquelet(a)lrde.epita.fr>
+
+ Experiment variation on regional maxima labeling.
+
+ * green/demo/labeling/regional_maxima/regional_maxima.cc
+ (demo_17_12_2009): New function that describes the experimentation.
+
2009-12-18 Yann Jacquelet<jacquelet(a)lrde.epita.fr>
Fix the right behaviour of the regmax software.
diff --git a/milena/sandbox/green/demo/labeling/regional_maxima/regional_maxima.cc b/milena/sandbox/green/demo/labeling/regional_maxima/regional_maxima.cc
index 65b6608..566c698 100644
--- a/milena/sandbox/green/demo/labeling/regional_maxima/regional_maxima.cc
+++ b/milena/sandbox/green/demo/labeling/regional_maxima/regional_maxima.cc
@@ -2,6 +2,7 @@
#include <iostream>
#include <sstream>
+#include <fstream>
#include <boost/format.hpp>
#include <mln/img_path.hh>
@@ -144,182 +145,6 @@ unsigned unquant(const float& value)
return result;
}
-template <unsigned n>
-void print_count2(const mln::image2d<mln::value::rgb<n> >& input_rgbn,
- const mln::image3d<unsigned>& histo,
- const mln::image3d<mln::value::label_8>& label,
- const unsigned n_labels)
-{
- typedef mln::value::label_8 t_lbl8;
- typedef mln::value::rgb<n> t_rgbn;
- typedef mln::value::int_u<n> t_int_un;
- typedef mln::algebra::vec<3,float> t_vec3f;
- typedef mln::accu::math::sum<unsigned,unsigned> t_sum;
- typedef mln::accu::stat::mean<t_vec3f,t_vec3f,t_vec3f> t_mean;
- typedef mln::accu::math::sum<t_vec3f,t_vec3f> t_diff;
- typedef mln::accu::stat::variance<float,float,float> t_var;
- typedef mln::image2d<t_lbl8> t_image2d_lbl8;
- typedef mln::image2d<t_rgbn> t_image2d_rgbn;
- typedef mln::image2d<t_int_un> t_image2d_int_un;
-
- mln::util::array<t_mean> mean((unsigned)(n_labels)+1);
-// mln::util::array<t_diff> diff((unsigned)(n_labels)+1);
- mln::util::array<t_var> var_red((unsigned)(n_labels)+1);
- mln::util::array<t_var> var_green((unsigned)(n_labels)+1);
- mln::util::array<t_var> var_blue((unsigned)(n_labels)+1);
- mln::util::array<t_sum> count((unsigned)(n_labels)+1);
- mln::util::array<float> abs((unsigned)(n_labels)+1);
- mln::util::array<float> rel((unsigned)(n_labels)+1);
- unsigned nb = 0;
-
- for (unsigned i = 0; i <= n_labels; ++i)
- {
- count(i).init();
- mean(i).init();
-// diff(i).init();
- var_red(i).init();
- var_green(i).init();
- var_blue(i).init();
- abs[i] = 0.0;
- rel[i] = 0.0;
- }
-
- mln::labeling::compute(count, histo, label, n_labels);
-
- for (unsigned i = 0; i <= n_labels; ++i)
- {
- unsigned c = count[i];
- nb += c;
- }
-
- for (unsigned i = 0; i <= n_labels; ++i)
- if (0 < count[i])
- {
- abs[i] = ((float)count[i] / nb)*100.0;
- rel[i] = ((float)count[i] / (nb - count[0]))*100.0;
- }
-
- t_image2d_lbl8 label_img = mln::data::transform(input_rgbn,
- t_labeling_rgbn<n>(label));
-
- mln::labeling::compute(mean, input_rgbn, label_img, n_labels);
-
-
-// t_image2d_rgbn mean_rgbn = mln::labeling::mean_values(input_rgbn,
-// label_img,
-// n_labels);
-
-// t_image2d_int_un mean_red =mln::data::transform(mean_rgbn,t_channel<n>());
-// t_image2d_int_un mean_green=mln::data::transform(mean_rgbn,t_channel<n>());
-// t_image2d_int_un mean_blue =mln::data::transform(mean_rgbn,t_channel<n>());
-
- t_image2d_int_un input_red =mln::data::transform(input_rgbn,
- t_channel<n,0>());
- t_image2d_int_un input_green=mln::data::transform(input_rgbn,
- t_channel<n,1>());
- t_image2d_int_un input_blue =mln::data::transform(input_rgbn,
- t_channel<n,2>());
-
-// FIXME VARIANCE NEGATIVE DANS LES RESULTATS !!
-
-// mln::labeling::compute(var_red, input_rgbn, label_img, n_labels);
-// mln::labeling::compute(var_green, input_rgbn, label_img, n_labels);
-// mln::labeling::compute(var_blue, input_rgbn, label_img, n_labels);
-
-// t_image2d_rgbn diff_rgbn = mln::arith::diff_abs(input_rgbn, mean_rgbn);
-
- std::cout << mln::labeling::compute(var_red, input_red, label_img, n_labels)(29) << std::endl;
-// mln::labeling::compute(t_var(), input_red, label_img, n_labels);
- mln::labeling::compute(var_green, input_green, label_img, n_labels);
- mln::labeling::compute(var_blue, input_blue, label_img, n_labels);
-
- for (unsigned i = 0; i <= n_labels; ++i)
- {
- if (5.0 < abs[i] && 10.0 < rel[i])
- {
- const t_vec3f& mean_v = mean[i];
-// const t_vec3f& diff_v = diff[i];
-
- std::cout << i << " :[" << unquant<n>(mean_v[0])
-// << "(" << diff_v[0]
- << "(" << var_red[i]
- << ")," << unquant<n>(mean_v[1])
-// << "(" << diff_v[1]
- << "(" << var_green[i]
- << ")," << unquant<n>(mean_v[2])
-// << "(" << diff_v[2]
- << "(" << var_blue[i]
- << ")]- " << count[i]
- << " - " << abs[i]
- << " - " << rel[i]
- << std::endl;
- }
- }
-}
-
-
-void print_count(const mln::image3d<unsigned>& histo,
- const mln::image3d<mln::value::label_8>& label,
- const unsigned n_labels)
-{
- unsigned count[255];
- unsigned red[255];
- unsigned green[255];
- unsigned blue[255];
- unsigned nb = 0;
- unsigned tmp = 0;
-
- for (unsigned i = 0; i <= n_labels; ++i)
- {
- count[i] = 0;
- red[i] = 0;
- green[i] = 0;
- blue[i] = 0;
- }
-
- mln_piter_(mln::image3d<unsigned>) p(histo.domain());
-
- for_all(p)
- {
- count[label(p)] += histo(p);
- red[label(p)] += histo(p) * p.row();
- green[label(p)] += histo(p) * p.col();
- blue[label(p)] += histo(p) * p.sli();
- nb += histo(p);
- ++tmp;
- }
-
- std::cout << std::endl;
-
- std::cout << "nb : " << nb << std::endl;
- std::cout << "tmp : " << tmp << std::endl;
-
- std::cout << std::endl;
-
- for (unsigned i = 0; i <= n_labels; ++i)
- if (0 < count[i])
- {
- float percentage_abs = ((float)count[i] / nb)*100.0;
- float percentage_rel = ((float)count[i] / (nb - count[0]))*100.0;
-
- red[i] = red[i] / count[i];
- green[i] = green[i] / count[i];
- blue[i] = blue[i] / count[i];
-
- std::cout << "count[" << i << "]("
- << red[i] << ", " << green[i] << ", "
- << blue[i] << ") = " << count[i] << "("
- << percentage_abs << "%)";
-
- if (0 < i)
- std::cout << "[" << percentage_rel << "%]";
-
- std::cout << std::endl;
- }
-
- std::cout << std::endl;
-}
-
// Version optimisée de merge
template <unsigned n>
@@ -354,111 +179,98 @@ struct t_merge_lbl8_with_rgbn : mln::Function_v2v< t_merge_lbl8_with_rgbn<n> >
}
};
-// version non optimisée de merge
-template <unsigned n>
-mln::image2d< mln::value::rgb<n> >
-merge(const mln::image2d< mln::value::rgb<n> >& input,
- const mln::image3d< mln::value::label_8 >& label)
-{
- mln::image2d<mln::value::rgb<n> > output;
- mln::initialize(output, input);
- // mln::data::fill(output, mln::literal::green);
+void compute_stats(const mln::image2d<mln::value::rgb8>& i_input_rgb8,
+ const mln::image2d<mln::value::label_8>& l_input_lbl8,
+ const mln::image3d<unsigned>& h_histo_rgbn,
+ const mln::image3d<mln::value::label_8>& l_histo_lbl8,
+ const mln::value::label_8& n_labels,
+ const std::string& log)
+{
+ typedef mln::algebra::vec<3,float> t_vec3f;
+ typedef mln::accu::math::sum<unsigned,unsigned> t_sum;
+ typedef mln::accu::stat::mean<t_vec3f,t_vec3f,t_vec3f> t_mean;
+ typedef mln::util::array<unsigned> t_count_array;
+ typedef mln::util::array<t_vec3f> t_mean_array;
- mln_piter(mln::image2d< mln::value::rgb<n> >) pi(input.domain());
- mln_piter(mln::image2d< mln::value::rgb<n> >) po(output.domain());
+ mln::util::array<float> abs((unsigned)(n_labels)+1);
+ mln::util::array<float> rel((unsigned)(n_labels)+1);
+ unsigned nb = 0;
- for_all_2(pi, po)
+ for (unsigned i = 0; i <= n_labels; ++i)
{
- const mln::value::rgb<n>& vi = input(pi);
- mln::value::rgb<n>& vo = output(po);
-
- if (0 < mln::opt::at(label,vi.blue(),vi.red(),vi.green()))
- {
- vo.red() = vi.red();
- vo.green() = vi.green();
- vo.blue() = vi.blue();
- }
- else
- vo = mln::literal::black;
+ abs[i] = 0.0;
+ rel[i] = 0.0;
}
- return output;
-}
-
-
-//
-// Theo regional maxima image processing chain.
-//
-
-// FIXME C'est la dilatation qui fait apparaître des classes < min_volume.
-// Une couleur se dilate au détriment du fond et des autres couleurs.
-
-int main2()
-{
- const unsigned min_volume = 1000;
- //const std::string& image = OLENA_IMG_PATH"/fly.ppm";
- const std::string& image = SCRIBO_PPM_IMG_PATH"/mp00082c_50p.ppm";
- //const std::string& image = OLENA_IMG_PATH"/tiny.ppm";
-
- typedef mln::value::label_8 t_lbl8;
- typedef mln::value::rgb8 t_rgb8;
- typedef mln::value::rgb<5> t_rgb5;
- typedef mln::image2d<t_rgb8> t_image2d_rgb8;
- typedef mln::image2d<t_rgb5> t_image2d_rgb5;
- typedef mln::image3d<t_lbl8> t_image3d_lbl8;
- typedef mln::image3d<unsigned> t_image3d_unsigned;
- typedef mln::fun::v2v::rgb8_to_rgbn<5> t_rgb8_to_rgb5;
- typedef mln::accu::meta::stat::histo3d_rgb t_histo3d_fun;
- typedef mln::accu::math::sum<unsigned,unsigned> t_sum;
-
- mln::util::timer timer;
-
- // START IMAGE PROCESSING CHAIN
- timer.start();
-
- t_image2d_rgb8 input_rgb8;
- t_image2d_rgb5 input_rgb5;
- t_image3d_unsigned histo;
- t_image3d_unsigned opened;
- t_image3d_lbl8 label;
- t_image3d_lbl8 dilated;
- t_lbl8 n_labels;
-
-
- mln::io::ppm::load(input_rgb8, image.c_str());
- input_rgb5 = mln::data::transform(input_rgb8, t_rgb8_to_rgb5());
- histo = mln::data::compute(t_histo3d_fun(), input_rgb5);
- opened = mln::morpho::opening::volume(histo, mln::c6(), min_volume);
- label = mln::labeling::regional_maxima(opened, mln::c6(), n_labels);
- dilated = mln::morpho::elementary::dilation(label, mln::c26());
+ // COMPUTE THE SUM
+ t_count_array count = mln::labeling::compute(t_sum(),
+ h_histo_rgbn,
+ l_histo_lbl8,
+ n_labels);
- mln::util::array<t_sum> length((unsigned)(n_labels)+1);
+ // COMPUTE THE TOTAL
+ for (unsigned i = 0; i <= n_labels; ++i)
+ {
+ unsigned c = count[i];
+ nb += c;
+ }
+ // COMPUTE THE PERCENTAGES
for (unsigned i = 0; i <= n_labels; ++i)
- length(i).init();
+ if (0 < count[i])
+ {
+ abs[i] = ((float)count[i] / nb)*100.0;
+ rel[i] = ((float)count[i] / (nb - count[0]))*100.0;
+ }
- mln::labeling::compute(length, histo, dilated, n_labels);
+ // COMPUTE THE MEAN
+
+ t_mean_array mean = mln::labeling::compute(t_mean(),
+ i_input_rgb8,
+ l_input_lbl8,
+ n_labels);
- timer.stop();
- // STOP IMAGE PROCESSING CHAIN
+ // CORRECT 0 LABEL STATS
+ rel[0] = 0;
+ mean[0][0] = 255.0;
+ mean[0][1] = 255.0;
+ mean[0][2] = 0.0;
- std::cout << "Done in " << timer.read() << " ms" << std::endl;
- std::cout << "n_labels : " << n_labels << std::endl;
+ // PRINT STATS
+ std::ofstream log_stream(log.c_str());
for (unsigned i = 0; i <= n_labels; ++i)
{
- std::cout << "count[" << i << "] = " << length[i] << std::endl;
- }
-
- print_count(histo,label,n_labels);
+ const t_vec3f& mean_v = mean[i];
- //mln::io::plot::save_image_sh(histo, "histo.sh");
- //mln::io::plot::save_image_sh(histo, "opened.sh");
- //mln::io::plot::save_image_sh(label, "label.sh");
+ log_stream << boost::format("%2i|"
+ "r = %6.2f, g = %6.2f, b = %6.2f |"
+ "c = %7i, %%i = %5.2f, %%c = %5.2f")
+ % i
+ % mean_v[0]
+ % mean_v[1]
+ % mean_v[2]
+ % count[i]
+ % abs[i]
+ % rel[i]
+ << std::endl;
+ /*
+ std::cout << i << "|("
+ << "r = " << unquant<n>(mean_v[0]) << ", "
+ << "g = " << unquant<n>(mean_v[1]) << ", "
+ << "b = " << unquant<n>(mean_v[2]) << ")|("
+ << "c = " << count[i] << ", "
+ << "%i= " << abs[i] << "%, "
+ << "%c= " << rel[i] << "%)"
+ << std::endl;
+ */
+ }
- return 0;
+ log_stream << std::endl << std::endl;
+ log_stream.flush();
+ log_stream.close();
}
void compute_stats(const mln::image2d<mln::value::rgb8>& i_input_rgb8,
@@ -546,7 +358,6 @@ void compute_stats(const mln::image2d<mln::value::rgb8>& i_input_rgb8,
}
std::cout << std::endl << std::endl;
-
}
void save_histo(const mln::image2d<mln::value::rgb8>& input_rgb8,
@@ -565,7 +376,7 @@ void save_histo(const mln::image2d<mln::value::rgb8>& input_rgb8,
// n < 8, n is the degree of quantification
template <unsigned n>
-void demo(const std::string& image, const unsigned min_vol)
+void demo_17_12_2009(const std::string& image, const unsigned min_vol)
{
typedef mln::value::label_8 t_lbl8;
typedef mln::value::int_u8 t_int_u8;
@@ -622,8 +433,6 @@ void demo(const std::string& image, const unsigned min_vol)
// END OF IMAGE PROCESSING CHAIN
-// i2_mean = mln::data::transform(l0_input,t_mean_lbl8_with_rgb8(mean_array));
-
// BEGIN DUMPING
save_histo(i0_input, "h0_input.pgm");
@@ -683,69 +492,235 @@ void demo(const std::string& image, const unsigned min_vol)
save_histo(i5_mean, "h5_mean.pgm");
save_histo(i5_merge, "h5_merge.pgm");
// END DUMPING
+}
-/*
- std::ostringstream name;
- std::ostringstream name2;
- std::ostringstream name3;
-
- name << "input_rgb" << n << ".ppm";
- name2 << "output_rgb" << n << ".ppm";
- name3 << "label_img" << n << ".pgm";
-
- std::cout << "Labels : " << n_labels << std::endl;
- std::cout << "Name : " << name.str() << std::endl;
-
-// mln::io::ppm::save(input_rgbn, name.str());
-
- std::cout << "timer2 : " << timer2.read() << std::endl;
- output_rgbn = mln::data::transform(input_rgbn,
- t_merge_lbl8_with_rgbn<n>(label));
- // output_rgbn = merge<n>(input_rgbn, dilated);
- mln::io::ppm::save(output_rgbn, name2.str());
-
- label_img = mln::data::transform(input_rgbn,
- t_labeling_rgbn<n>(label));
- // label_img = label_image<n>(input_rgbn, dilated);
- mln::io::pgm::save(label_img, name3.str());
-*/
-
- // localiser les couleurs sur l'image (fond en black, le reste)
-
- // La dilatation englobe beaucoup plus de couleur, mais celles-ci ne
- // sont pas forcément présentes dans l'image. Du coup, les classes ne
- // bougent pas démeusurément.
-
-// mln::io::ppm::save(input_rgb5, "input_rgb5.ppm");
-// mln::io::plot::save_image_sh(input_rgb8, "input_rgb8.sh");
-// mln::io::plot::save_image_sh(input_rgb5, "input_rgb5.sh");
-// projected = mln::display::display_histo3d_unsigned(histo);
-// mln::io::pgm::save(projected, "histo.pgm");
-// mln::io::plot::save_image_sh(histo, "histo.sh");
-// mln::io::plot::save_image_sh(opened, "opened.sh");
-// filtered = mln::display::display_histo3d_unsigned(opened);
-// mln::io::pgm::save(filtered, "filtered.pgm");
-// mln::io::plot::save_image_sh(label, "label.sh");
- // mln::io::plot::save_image_sh(dilated, "dilated.sh");
-
- /*
- // OUTPUT PHASE
- std::cout << "Output phase ..." << std::endl;
- output_rgb5 = merge(input_rgb5, dilated);
- //mln::io::ppm::save(output_rgb5, "output_rgb5.ppm");
- mln::io::plot::save_image_sh(output_rgb5, "output_rgb5.sh");
-
-
- // LABELING IMG OUTPUT
- std::cout << "Labeling img output phase ..." << std::endl;
- label_img = label_image(input_rgb5, dilated);
- mln::io::pgm::save(label_img, "label_img.pgm");
-
- // BUILDING MEAN VALUES
- std::cout << "Building mean values phase ..." << std::endl;
- mean_rgb5 = mln::labeling::mean_values(input_rgb5, label_img, n_labels);
- mln::io::ppm::save(mean_rgb5, "mean.ppm");
- */
+// n < 8, n is the degree of quantification
+template <unsigned n>
+void demo_21_12_2009(const std::string& image, const unsigned min_vol)
+{
+ typedef mln::value::label_8 t_lbl8;
+ typedef mln::value::int_u8 t_int_u8;
+ typedef mln::value::rgb8 t_rgb8;
+ typedef mln::value::rgb<n> t_rgbn;
+ typedef mln::image3d<t_lbl8> t_image3d_lbl8;
+ typedef mln::image2d<t_lbl8> t_image2d_lbl8;
+ typedef mln::image2d<t_rgb8> t_image2d_rgb8;
+ typedef mln::image2d<t_rgbn> t_image2d_rgbn;
+ typedef mln::image2d<t_int_u8> t_image2d_int_u8;
+ typedef mln::image3d<unsigned> t_histo3d;
+ typedef mln::image2d<unsigned> t_histo2d;
+ typedef mln::fun::v2v::rgb8_to_rgbn<n> t_rgb8_to_rgbn;
+ typedef mln::accu::meta::stat::histo3d_rgb t_histo3d_fun;
+
+ // START OF IMAGE PROCESSING CHAIN
+ t_image2d_rgb8 i0_input; // input rgb8
+ t_histo3d h0_input; // histo input
+
+ t_image2d_rgbn i1_input; // input rgbn
+ t_histo3d h1_input; // histo input
+
+ t_histo3d h2_input; // histo opened
+ t_image3d_lbl8 l2_histo; // label histo
+ t_image2d_lbl8 l2_input; // label image
+ t_image2d_rgb8 i2_merge; // merge label
+ t_image2d_rgb8 i2_mean; // mean label
+
+ t_image3d_lbl8 l5_histo; // label iz 2
+ t_image2d_lbl8 l5_input; // label image
+ t_image2d_rgb8 i5_merge; // merge label
+ t_image2d_rgb8 i5_mean; // mean label
+
+ t_lbl8 n_lbl; // nb class
+
+ mln::io::ppm::load(i0_input, image.c_str());
+ i1_input = mln::data::transform(i0_input, t_rgb8_to_rgbn());
+ h1_input = mln::data::compute(t_histo3d_fun(), i1_input);
+ h2_input = mln::morpho::opening::volume(h1_input, mln::c6(), min_vol);
+ l2_histo = mln::labeling::regional_maxima(h2_input, mln::c6(), n_lbl);
+ l5_histo = mln::transform::influence_zone_geodesic(l2_histo, mln::c26(), 2);
+ // END OF IMAGE PROCESSING CHAIN
+
+ // BEGIN DUMPING
+ save_histo(i0_input, "h0_input.pgm");
+
+ // without nothing
+ l2_input = mln::data::transform(i1_input, t_labeling_rgbn<n>(l2_histo));
+ i2_mean = mln::labeling::mean_values(i0_input, l2_input, n_lbl);
+ i2_merge = mln::data::transform(i0_input,t_merge_lbl8_with_rgbn<n>(l2_histo));
+
+ compute_stats(i0_input, l2_input, h1_input, l2_histo, n_lbl);
+
+ mln::io::pgm::save(l2_input, "l2_input.pgm");
+ mln::io::ppm::save(i2_mean, "i2_mean.ppm");
+ mln::io::ppm::save(i2_merge, "i2_merge.ppm");
+
+ save_histo(i2_mean, "h2_mean.pgm");
+ save_histo(i2_merge, "h2_merge.pgm");
+
+ // with restricted geodesic influence
+ l5_input = mln::data::transform(i1_input, t_labeling_rgbn<n>(l5_histo));
+ i5_mean = mln::labeling::mean_values(i0_input, l5_input, n_lbl);
+ i5_merge = mln::data::transform(i0_input,t_merge_lbl8_with_rgbn<n>(l5_histo));
+
+ compute_stats(i0_input, l5_input, h1_input, l5_histo, n_lbl);
+
+ mln::io::pgm::save(l5_input, "l5_input.pgm");
+ mln::io::ppm::save(i5_mean, "i5_mean.ppm");
+ mln::io::ppm::save(i5_merge, "i5_merge.ppm");
+
+ save_histo(i5_mean, "h5_mean.pgm");
+ save_histo(i5_merge, "h5_merge.pgm");
+ // END DUMPING
+}
+
+
+// EXE THEO
+// a.out input.ppm q v output.ppm [log.txt]
+// input.ppm ==> l'image 8 bits couleur format ppm
+// q ==> la quantification [2,3,4,5,6,7,8]
+// v ==> l'effectif minimal de chaque classe [0 = pas de filtrage]
+// output.ppm ==> l'image où l'étiquette est remplacée par la couleur moyenne
+// log.txt ==> le fichier de statistiques [optionnel]
+
+// n < 8, n is the degree of quantification
+template <unsigned n>
+void exe_theo_22_12_2009(const std::string& input,
+ const unsigned min_vol,
+ const std::string& output,
+ const std::string& log)
+{
+ typedef mln::value::label_8 t_lbl8;
+ typedef mln::value::int_u8 t_int_u8;
+ typedef mln::value::rgb8 t_rgb8;
+ typedef mln::value::rgb<n> t_rgbn;
+ typedef mln::image3d<t_lbl8> t_image3d_lbl8;
+ typedef mln::image2d<t_lbl8> t_image2d_lbl8;
+ typedef mln::image2d<t_rgb8> t_image2d_rgb8;
+ typedef mln::image2d<t_rgbn> t_image2d_rgbn;
+ typedef mln::image2d<t_int_u8> t_image2d_int_u8;
+ typedef mln::image3d<unsigned> t_histo3d;
+ typedef mln::image2d<unsigned> t_histo2d;
+ typedef mln::fun::v2v::rgb8_to_rgbn<n> t_rgb8_to_rgbn;
+ typedef mln::accu::meta::stat::histo3d_rgb t_histo3d_fun;
+
+ // START OF IMAGE PROCESSING CHAIN
+ t_image2d_rgb8 i0_input; // input rgb8
+ t_histo3d h0_input; // histo input
+
+ t_image2d_rgbn i1_input; // input rgbn
+ t_histo3d h1_input; // histo input
+
+ t_histo3d h2_input; // histo opened
+ t_image3d_lbl8 l2_histo; // label histo
+
+ t_image3d_lbl8 l4_histo; // label iz
+ t_image2d_lbl8 l4_input; // label image
+ t_image2d_rgb8 i4_merge; // merge label
+ t_image2d_rgb8 i4_mean; // mean label
+
+ t_lbl8 n_lbl; // nb class
+
+ mln::io::ppm::load(i0_input, input.c_str());
+ i1_input = mln::data::transform(i0_input, t_rgb8_to_rgbn());
+ h1_input = mln::data::compute(t_histo3d_fun(), i1_input);
+
+ if (0 < min_vol)
+ h2_input = mln::morpho::opening::volume(h1_input, mln::c6(), min_vol);
+ else
+ h2_input = h1_input; // no filtering
+
+ l2_histo = mln::labeling::regional_maxima(h2_input, mln::c6(), n_lbl);
+ l4_histo = mln::transform::influence_zone_geodesic(l2_histo, mln::c26());
+ // END OF IMAGE PROCESSING CHAIN
+
+ // BEGIN DUMPING
+ l4_input = mln::data::transform(i1_input, t_labeling_rgbn<n>(l4_histo));
+ i4_mean = mln::labeling::mean_values(i0_input, l4_input, n_lbl);
+
+ if (0 < log.size())
+ compute_stats(i0_input, l4_input, h1_input, l4_histo, n_lbl, log);
+
+ mln::io::ppm::save(i4_mean, output.c_str());
+ // END DUMPING
+}
+
+// n < 8, n is the degree of quantification
+template <unsigned n>
+void demo_22_12_2009(const std::string& image, const unsigned min_vol)
+{
+ typedef mln::value::label_8 t_lbl8;
+ typedef mln::value::int_u8 t_int_u8;
+ typedef mln::value::rgb8 t_rgb8;
+ typedef mln::value::rgb<n> t_rgbn;
+ typedef mln::image3d<t_lbl8> t_image3d_lbl8;
+ typedef mln::image2d<t_lbl8> t_image2d_lbl8;
+ typedef mln::image2d<t_rgb8> t_image2d_rgb8;
+ typedef mln::image2d<t_rgbn> t_image2d_rgbn;
+ typedef mln::image2d<t_int_u8> t_image2d_int_u8;
+ typedef mln::image3d<unsigned> t_histo3d;
+ typedef mln::image2d<unsigned> t_histo2d;
+ typedef mln::fun::v2v::rgb8_to_rgbn<n> t_rgb8_to_rgbn;
+ typedef mln::accu::meta::stat::histo3d_rgb t_histo3d_fun;
+
+ // START OF IMAGE PROCESSING CHAIN
+ t_image2d_rgb8 i0_input; // input rgb8
+ t_histo3d h0_input; // histo input
+
+ t_image2d_rgbn i1_input; // input rgbn
+ t_histo3d h1_input; // histo input
+
+ t_histo3d h2_input; // histo opened
+ t_image3d_lbl8 l2_histo; // label histo
+ t_image2d_lbl8 l2_input; // label image
+ t_image2d_rgb8 i2_merge; // merge label
+ t_image2d_rgb8 i2_mean; // mean label
+
+ t_image3d_lbl8 l5_histo; // label iz 2
+ t_image2d_lbl8 l5_input; // label image
+ t_image2d_rgb8 i5_merge; // merge label
+ t_image2d_rgb8 i5_mean; // mean label
+
+ t_lbl8 n_lbl; // nb class
+
+ mln::io::ppm::load(i0_input, image.c_str());
+ i1_input = mln::data::transform(i0_input, t_rgb8_to_rgbn());
+ h1_input = mln::data::compute(t_histo3d_fun(), i1_input);
+ h2_input = mln::morpho::opening::volume(h1_input, mln::c6(), min_vol);
+ l2_histo = mln::labeling::regional_maxima(h2_input, mln::c6(), n_lbl);
+ l5_histo = mln::transform::influence_zone_geodesic(l2_histo, mln::c26(), 2);
+ // END OF IMAGE PROCESSING CHAIN
+
+ // BEGIN DUMPING
+ save_histo(i0_input, "h0_input.pgm");
+
+ // without nothing
+ l2_input = mln::data::transform(i1_input, t_labeling_rgbn<n>(l2_histo));
+ i2_mean = mln::labeling::mean_values(i0_input, l2_input, n_lbl);
+ i2_merge = mln::data::transform(i0_input,t_merge_lbl8_with_rgbn<n>(l2_histo));
+
+ compute_stats(i0_input, l2_input, h1_input, l2_histo, n_lbl);
+
+ mln::io::pgm::save(l2_input, "l2_input.pgm");
+ mln::io::ppm::save(i2_mean, "i2_mean.ppm");
+ mln::io::ppm::save(i2_merge, "i2_merge.ppm");
+
+ save_histo(i2_mean, "h2_mean.pgm");
+ save_histo(i2_merge, "h2_merge.pgm");
+
+ // with restricted geodesic influence
+ l5_input = mln::data::transform(i1_input, t_labeling_rgbn<n>(l5_histo));
+ i5_mean = mln::labeling::mean_values(i0_input, l5_input, n_lbl);
+ i5_merge = mln::data::transform(i0_input,t_merge_lbl8_with_rgbn<n>(l5_histo));
+
+ compute_stats(i0_input, l5_input, h1_input, l5_histo, n_lbl);
+
+ mln::io::pgm::save(l5_input, "l5_input.pgm");
+ mln::io::ppm::save(i5_mean, "i5_mean.ppm");
+ mln::io::ppm::save(i5_merge, "i5_merge.ppm");
+
+ save_histo(i5_mean, "h5_mean.pgm");
+ save_histo(i5_merge, "h5_merge.pgm");
+ // END DUMPING
}
@@ -774,30 +749,73 @@ void usage()
// *
}
-int main(int argc, char* args[])
+void usage_exe_theo_22_12_2009()
{
- if (argc != 3)
+ std::cout << std::endl;
+ std::cout << "a.out input.ppm q v [log.txt]" << std::endl;
+ std::cout << "where" << std::endl;
+ std::cout << "input.ppm is the 8 bits color ppm image" << std::endl;
+ std::cout << "q is the degree of quanification {2,3,4,5,6,7,8}" << std::endl;
+ std::cout << "v is the minimal size for the histogram classes" << std::endl;
+ std::cout << "log.txt is the statistical file for classes" << std::endl;
+ std::cout << std::endl;
+}
+
+int main_21_12_2009(int argc, char* args[])
+{
+ if (argc == 2)
{
// const std::string& image = OLENA_IMG_PATH"/fly.ppm";
const std::string& image = SCRIBO_PPM_IMG_PATH"/mp00082c_50p.ppm";
// const std::string& image = OLENA_IMG_PATH"/tiny.ppm";
// const std::string image = OLENA_IMG_PATH"/tiny.ppm";
- const unsigned min_volume = 1000;
- // const unsigned min_volume = atoi(args[2]);
+ // const unsigned min_volume = 1000;
+ const unsigned min_volume = atoi(args[1]);
- switch(args[2][0])
+// switch(args[1][0])
+ switch(5)
{
- case '2': demo<2>(image, min_volume); break;
- case '3': demo<3>(image, min_volume); break;
- case '4': demo<4>(image, min_volume); break;
- case '5': demo<5>(image, min_volume); break;
- case '6': demo<6>(image, min_volume); break;
- case '7': demo<7>(image, min_volume); break;
- case '8': demo<8>(image, min_volume); break;
- default: demo<5>(image, min_volume); break;
+ case '2': demo_21_12_2009<2>(image, min_volume); break;
+ case '3': demo_21_12_2009<3>(image, min_volume); break;
+ case '4': demo_21_12_2009<4>(image, min_volume); break;
+ case '5': demo_21_12_2009<5>(image, min_volume); break;
+ case '6': demo_21_12_2009<6>(image, min_volume); break;
+ case '7': demo_21_12_2009<7>(image, min_volume); break;
+ case '8': demo_21_12_2009<8>(image, min_volume); break;
+ default: demo_21_12_2009<5>(image, min_volume); break;
// default: usage(); break;
}
}
else
usage();
+
+ return 0;
+}
+
+int main(int argc, char* args[])
+{
+ if (5 == argc || 6 == argc)
+ {
+ const std::string input(args[1]);
+ const char q = args[2][0];
+ const unsigned v = atoi(args[3]);
+ const std::string output(args[4]);
+ const std::string log(6 == argc? args[5] : "");
+
+ switch(q)
+ {
+ case '2': exe_theo_22_12_2009<2>(input, v, output, log); break;
+ case '3': exe_theo_22_12_2009<3>(input, v, output, log); break;
+ case '4': exe_theo_22_12_2009<4>(input, v, output, log); break;
+ case '5': exe_theo_22_12_2009<5>(input, v, output, log); break;
+ case '6': exe_theo_22_12_2009<6>(input, v, output, log); break;
+ case '7': exe_theo_22_12_2009<7>(input, v, output, log); break;
+ case '8': exe_theo_22_12_2009<8>(input, v, output, log); break;
+ default: usage_exe_theo_22_12_2009(); break;
+ }
+ }
+ else
+ usage_exe_theo_22_12_2009();
+
+ return 0;
}
--
1.5.6.5
14Â years, 2Â months
- 1
- 0