---
trunk/milena/sandbox/ChangeLog | 14 ++
trunk/milena/sandbox/green/histo1d/Makefile.am | 5 +-
trunk/milena/sandbox/green/histo1d/gaussian.sh | 12 ++
trunk/milena/sandbox/green/histo1d/histo1d.cc | 169 +++++++++++++++++--
.../milena/sandbox/green/histo1d/mp00082c_50p.pgm | Bin 0 -> 3663665 bytes
trunk/milena/sandbox/green/histo1d/save_sh.hh | 10 +-
6 files changed, 186 insertions(+), 24 deletions(-)
create mode 100755 trunk/milena/sandbox/green/histo1d/gaussian.sh
create mode 100644 trunk/milena/sandbox/green/histo1d/mp00082c_50p.pgm
diff --git a/trunk/milena/sandbox/ChangeLog b/trunk/milena/sandbox/ChangeLog
index f48342e..55ec807 100644
--- a/trunk/milena/sandbox/ChangeLog
+++ b/trunk/milena/sandbox/ChangeLog
@@ -1,3 +1,17 @@
+2009-08-14 Yann Jacquelet <jacquelet(a)lrde.epita.fr>
+
+ Test more accurately the histo1d class in image processing chain.
+ Try to isolate the background color of mp000082c_50p.pgm.
+
+ * green/histo1d/histo1d.hh : New C++ type.
+ * green/histo1d/gaussian.sh : New GNUPLOT script to calibrate
+ gaussian filter.
+ * green/histo1d/save_sh.hh
+ (save_sh) : Update some GNUPLOT style.
+ * green/histo1d/histo1d.cc
+ (test_classify) : New function.
+ * green/histo1d/mp00082c_50p.pgm : New test scribo image.
+
2009-08-12 Yann Jacquelet <jacquelet(a)lrde.epita.fr>
Write an histogram accumulator which the result is an image1d.
diff --git a/trunk/milena/sandbox/green/histo1d/Makefile.am
b/trunk/milena/sandbox/green/histo1d/Makefile.am
index 36a83e3..1834984 100644
--- a/trunk/milena/sandbox/green/histo1d/Makefile.am
+++ b/trunk/milena/sandbox/green/histo1d/Makefile.am
@@ -5,7 +5,8 @@
BIN_PATTERN= trunk/build/milena
SRC_PATTERN= trunk/milena
-CXXFLAGS= -ggdb -O0 -Wall -W -pedantic -ansi -pipe
+INCLUDES= -I/home/green/svn/oln/trunk/milena
+CXXFLAGS= -ggdb -O0 -Wall -W -pedantic -ansi -pipe $(INCLUDES)
ECHO= echo
RM= rm
MKDIR= mkdir
@@ -30,7 +31,7 @@ OBJ_FILES= $(addprefix $(BIN_DIR), $(notdir $(SRC_FILES:%.cc=%.o)))
all: $(BIN_DIR) $(TARGET)
- @$(ECHO) "Compilation terminée"
+ @$(ECHO) "Compilation terminée"
$(BIN_DIR):
$(MKDIR) $(BIN_DIR)
diff --git a/trunk/milena/sandbox/green/histo1d/gaussian.sh
b/trunk/milena/sandbox/green/histo1d/gaussian.sh
new file mode 100755
index 0000000..4d2164a
--- /dev/null
+++ b/trunk/milena/sandbox/green/histo1d/gaussian.sh
@@ -0,0 +1,12 @@
+#!/bin/sh
+
+############
+# gaussian #
+############
+
+gnuplot <<EOF
+set terminal x11 persist 1
+square(x)=x*x
+gaussian(x,mean,sigma)=exp(-0.5*square((x-mean)/sigma))/(sigma*sqrt(2*pi))
+plot [-20:20] gaussian(x,0,6)
+EOF
diff --git a/trunk/milena/sandbox/green/histo1d/histo1d.cc
b/trunk/milena/sandbox/green/histo1d/histo1d.cc
index c39a412..7ceba16 100644
--- a/trunk/milena/sandbox/green/histo1d/histo1d.cc
+++ b/trunk/milena/sandbox/green/histo1d/histo1d.cc
@@ -4,12 +4,16 @@
#include "histo1d.hh"
#include <mln/io/pgm/load.hh>
+#include <mln/io/pgm/save.hh>
+#include <mln/io/ppm/save.hh>
#include <mln/io/plot/save.hh>
#include <mln/data/compute.hh>
+#include <mln/data/fill.hh>
#include <mln/value/int_u8.hh>
#include <mln/value/label_8.hh>
+#include <mln/value/rgb8.hh>
#include <mln/core/alias/neighb1d.hh>
#include <mln/core/alias/box1d.hh>
@@ -27,6 +31,24 @@
#include <mln/morpho/elementary/dilation.hh>
#include <mln/morpho/elementary/closing.hh>
+#include <mln/linear/convolve.hh>
+#include <mln/linear/gaussian.hh>
+#include <mln/labeling/regional_maxima.hh>
+#include <mln/labeling/colorize.hh>
+#include <mln/labeling/mean_values.hh>
+
+#include <mln/make/w_window1d.hh>
+
+#include <mln/math/sqr.hh>
+#include <mln/math/pi.hh>
+#include <mln/math/abs.hh>
+
+#include <mln/core/image/dmorph/image_if.hh>
+#include <mln/pw/value.hh>
+
+
+
+
void test_operator_equal()
{
using namespace mln::accu::stat;
@@ -43,6 +65,7 @@ void test_operator_equal()
histo1.take(val);
+ /// FIXME mln_assertion(histo1 != histo2); doesn't work!!
mln_assertion(!(histo1 == histo2));
histo2.take(val);
@@ -209,51 +232,159 @@ void test_integration()
const double var_ref = mln::data::compute(variance(), img_ref);
img_res = mln::data::compute(mln::accu::stat::histo1d<int_u8>(), img_ref);
-
+
const double count_res = count_histo(img_res);
const double mean_res = mean_histo(img_res);
const double var_res = var_histo(img_res);
mln_assertion(count_ref == count_res);
mln_assertion( mean_ref == mean_res );
- mln_assertion( var_ref == var_res );
+ mln_assertion(0.0001 > abs(var_ref - var_res));
std::cout << "test integration : ok" << std::endl;
}
+double gaussian_distribution(double x, double mean, double sigma)
+{
+ double num = exp(-0.5*mln::math::sqr((x - mean)/sigma));
+ double denom = sigma*mln::math::sqrt(2*mln::math::pi);
+ double result = num/denom;
+
+ return result;
+}
+
+/// To calibrate with gnuplot (see gaussian.sh)
+/// square(x) = x*x
+/// gaussian(x,mean,sigma)=exp(-0.5*square((x-mean)/sigma))/(sigma*sqrt(2*pi))
+/// plot [-20:20] gaussian(x,0,6.0)
+
+void gaussian_filter(double ws[], unsigned size, double sigma)
+{
+ int h = size/2;
+
+ for (int i = -h; i <= h; ++i)
+ {
+ ws[i+h] = gaussian_distribution(i, 0.0, sigma);
+ }
+
+ double sum = 0.0;
+
+ for (unsigned i = 0; i < size; ++i)
+ sum += ws[i];
+
+ for (unsigned i = 0; i < size; ++i)
+ ws[i] /= sum;
+}
+
+/// The aim of this function is to rebuild an label image2d from the segmenting
+/// image of the histogram (label) and the original image (input).
+/// label_image2d / for each grey tone, associate its label.
+
+mln::image2d<mln::value::label_8>
+build(const mln::image2d<mln::value::int_u8>& input,
+ const mln::image1d<mln::value::label_8>& label)
+{
+ mln::trace::entering("build");
+ mln_precondition(label.is_valid());
+ mln_precondition(input.is_valid());
+
+ mln::image2d<mln::value::label_8> output;
+
+ mln::initialize(output, input);
+
+ mln_piter_(mln::image2d<mln::value::int_u8>) pi(input.domain());
+ mln_piter_(mln::image2d<mln::value::label_8>) po(output.domain());
+
+ for_all_2(pi, po)
+ {
+ mln::value::int_u8 val = input(pi);
+ unsigned grp = label(mln::point1d(val));
+
+ output(po) = grp;
+ }
+
+ mln::trace::exiting("build");
+ return output;
+}
+
+
void test_classifying()
{
- typedef mln::value::int_u8 int_u8;
- typedef mln::value::label_8 label_8;
+ typedef mln::value::int_u8 int_u8;
+ typedef mln::value::label_8 label_8;
+ typedef mln::value::rgb8 rgb8;
+ typedef mln::accu::stat::mean<double> mean;
mln::image2d<int_u8> img_ref;
+ mln::image2d<int_u8> img_out;
+ mln::image2d<rgb8> img_rgb;
mln::image1d<unsigned> img_res;
+ mln::image1d<double> img_smooth;
mln::image1d<label_8> labels;
- label_8 n_shape;
+ label_8 nlabels;
- mln::io::pgm::load(img_ref, "/usr/local/share/olena/images/lena.pgm");
-
+ //-----------------------------------------------------
+ // Loading the scribo image and computing its histogram
+ //-----------------------------------------------------
+
+ std::cout << "LOADING HISTOGRAM" << std::endl;
+
+ // mln::io::pgm::load(img_ref, "/usr/local/share/olena/images/lena.pgm");
+ mln::io::pgm::load(img_ref, "mp00082c_50p.pgm");
img_res = mln::data::compute(mln::accu::stat::histo1d<int_u8>(), img_ref);
+ mln::io::plot::save_sh(img_res, "histo0.sh");
- mln::io::plot::save_sh(img_res, "histo.sh");
- img_res = mln::morpho::elementary::closing(img_res, mln::c2());
- img_res = mln::morpho::elementary::closing(img_res, mln::c2());
- img_res = mln::morpho::elementary::closing(img_res, mln::c2());
+ //-----------------------------------------------------
+ // Smoothing the histogram with a gaussian filter
+ //-----------------------------------------------------
+
+ std::cout << "SMOOTHING HISTOGRAM" << std::endl;
+
+ double ws[41];
+ gaussian_filter(ws, 41, 6.0);
+ img_smooth = mln::linear::convolve(img_res, mln::make::w_window1d(ws));
+ mln::io::plot::save_sh(img_smooth, "histo1.sh");
- mln::io::plot::save_sh(img_res, "histo1.sh");
- /*
- labels = mln::morpho::watershed::flooding(img_res, mln::c2(), n_shape);
+ //-----------------------------------------------------
+ // Segmenting the histogram with the watershed method
+ //-----------------------------------------------------
+
+ std::cout << "SEGMENTING HISTOGRAM" << std::endl;
+
+ /*
+ labels = mln::labeling::regional_maxima(img_smooth, mln::c2(), nlabels);
+ std::cout << "N labels : " << nlabels << std::endl;
mln::io::plot::save_sh(labels, "histo2.sh");
+ */
- labels = mln::morpho::elementary::dilation(labels, mln::c2());
- mln::io::plot::save_sh(labels, "histo3.sh");
+ labels = mln::morpho::watershed::flooding(img_smooth, mln::c2(), nlabels);
+ std::cout << "N labels : " << nlabels << std::endl;
+ mln::io::plot::save_sh(labels, "histo2.sh");
+
+
+ //-----------------------------------------------------
+ // Rebuilding the image with the mean of each region
+ //-----------------------------------------------------
+
+ std::cout << "BUILDING OUTPUT" << std::endl;
+ mln::image2d<label_8>img_label = build(img_ref, labels);
+
+ std::cout << "COLORING OUTPUT" << std::endl;
+
+ img_out = mln::labeling::mean_values(img_ref, img_label, nlabels);
+ img_rgb = mln::labeling::colorize(rgb8(), img_label);
+
+ mln::io::pgm::save(img_out, "out.pgm");
+ mln::io::ppm::save(img_rgb, "color.pgm");
+
+ //labels = mln::morpho::elementary::dilation(labels, mln::c2());
+ //mln::io::plot::save_sh(labels, "histo3.sh");
//mln::io::plot::save(labels, "labelized.data");
- */
}
int main()
@@ -261,14 +392,16 @@ int main()
using namespace mln;
using namespace std;
+ /*
test_instantiation_without_argument();
test_initialization();
test_take_argument();
test_take_other();
test_operator_equal();
test_integration();
+ */
- //test_classifying();
+ test_classifying();
return 0;
}
diff --git a/trunk/milena/sandbox/green/histo1d/mp00082c_50p.pgm
b/trunk/milena/sandbox/green/histo1d/mp00082c_50p.pgm
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HcmV?d00001
diff --git a/trunk/milena/sandbox/green/histo1d/save_sh.hh
b/trunk/milena/sandbox/green/histo1d/save_sh.hh
index ece30f4..21321e3 100644
--- a/trunk/milena/sandbox/green/histo1d/save_sh.hh
+++ b/trunk/milena/sandbox/green/histo1d/save_sh.hh
@@ -91,8 +91,8 @@ namespace mln
trace::entering("mln::io::plot::save_sh<1d>");
mln_precondition(img.is_valid());
- std::ofstream out(filename.c_str());
- mln_piter(image1d<I>) p(img.domain());
+ std::ofstream out(filename.c_str());
+ mln_piter(image1d<I>) p(img.domain());
out << "#!/bin/sh" << std::endl;
out << "##########################" << std::endl;
@@ -101,13 +101,15 @@ namespace mln
out << std::endl;
out << "gnuplot <<EOF" <<
std::endl;
out << "set terminal x11 persist 1" << std::endl;
+ out << "plot '-' with points pointtype 20" << std::endl;
//out << "plot '-' with points pointtype 0" <<
std::endl;
- out << "plot '-' with histograms" << std::endl;
+ //out << "plot '-' with histograms" << std::endl;
+ //out << "plot '-' smooth unique" << std::endl;
for_all(p)
{
// for (unsigned i = 0; i < mln_dim(I); ++i)
- // out << p[0] << " ";
+ out << p[0] << " ";
out << img(p) << std::endl;
}
--
1.5.6.5