https://svn.lrde.epita.fr/svn/oln/branches/cleanup-2008/milena/sandbox Index: ChangeLog from Ugo Jardonnet &lt;jardonnet(a)lrde.epita.fr&gt; INIM: Classif: Final Upgrade. * inim/classif/src/max_tree.hh: Fix comment. * inim/classif/src/proj.hh: Add specific projection. * inim/classif/src/v2.cc: Add efficient technique based histo value merging. max_tree.hh | 7 +++++-- proj.hh | 58 ++++++++++++++++++++++++++++++++++++++++++++++++++++++---- v2.cc | 50 ++++++++++++++++++++++++++++++++------------------ 3 files changed, 91 insertions(+), 24 deletions(-) Index: inim/classif/src/max_tree.hh --- inim/classif/src/max_tree.hh (revision 2838) +++ inim/classif/src/max_tree.hh (working copy) @@ -153,6 +153,7 @@ return mean_color; } + // Filter method template<typename X> void lumberjack(const X& ima, const mln_value(X)& lambda) { @@ -177,8 +178,9 @@ std::cout << std::endl; } + // Fusion method template<typename X> - void nuclear_fusion(const X& ima, const mln_value(X)& lambda) + void nuclear_fusion(const X& ima, double lambda) { unsigned progress = 0; unsigned step = s.nsites() / 100; @@ -188,7 +190,8 @@ mln_fwd_piter(S) p(s); for_all(p) { - if (fabs(1 - ima(new_parent(p)) / ima(p)) < lambda) + if (ima(p) != 0) + if (fabs(1. - ima(new_parent(p)) / (double) ima(p)) < lambda) is_active(p) = false; ++progress; Index: inim/classif/src/display.hh Index: inim/classif/src/proj.hh --- inim/classif/src/proj.hh (revision 2838) +++ inim/classif/src/proj.hh (working copy) @@ -35,6 +35,7 @@ #include <mln/accu/maj_h.hh> #include <mln/literal/white.hh> #include <mln/literal/colors.hh> +#include <mln/make/vec.hh> namespace mln { @@ -59,11 +60,11 @@ save_class(const image3d<T>& histo, const image3d<U>& ws, K mean, const char * fn) { - accu::maj_h<value::int_u8> max_1; - image2d<value::int_u8> hproj = proj(histo, max_1); + accu::maj_h<value::int_u8> maj_1; + image2d<value::int_u8> hproj = proj(histo, maj_1); - accu::maj_h<value::int_u8> max_2; - image2d<value::int_u8> proj_class = proj(ws, max_2); + accu::maj_h<value::int_u8> maj_2; + image2d<value::int_u8> proj_class = proj(ws, maj_2); //std::cout << histo; @@ -82,6 +83,55 @@ io::ppm::save(out, fn); } + template <typename T, typename I, typename A> + image2d<mln_result(A)> + proj_vec(const image3d<T>& input, const I& histo, A) + { + image2d<A> acc(geom::nslis(input), geom::nrows(input)); + mln_piter(image3d<T>) p(input.domain()); + for_all(p) // 3d + if (histo(p) != literal::zero) + acc.at(p.sli(), p.row()).take(input(p)); + + image2d<mln_result(A)> output(acc.domain()); + level::paste(acc, output); + return output; + } + + template <typename I, typename T, typename U, typename V> + void + save_class_v2(const I& ima, const T& histo, image3d<U>& mean, + const image3d<V>& parent, unsigned f, + const char * fn) + { + image3d<value::rgb8> out3d(histo.domain()); + + mln_piter(I) p(ima.domain()); + for_all(p) + { + point3d p3 = point3d(ima(p).red() / f, + ima(p).green() / f, + ima(p).blue() / f); + out3d(p3) = convert::to<value::rgb8>(mean(parent(p3))); + } + + //FIXME: maj_h implies set is finite, mx set is ordered + accu::mean<mln::algebra::vec<3u, float> > maj_2; + image2d<mln::algebra::vec<3u, float> > mproj = + proj_vec(out3d, histo, maj_2); + + image2d<value::rgb8> out(geom::nslis(histo), geom::nrows(histo)); + level::fill(out, literal::white); + + mln_piter(image2d<value::int_u8>) p1(out.domain()); + for_all(p1) + { + out(p1) = convert::to<value::rgb8>(mproj(p1)); + } + + io::ppm::save(out, fn); + } + } // end of namespace mln #endif /* MLN_PROJ_HH */ Index: inim/classif/src/v2.cc --- inim/classif/src/v2.cc (revision 2838) +++ inim/classif/src/v2.cc (working copy) @@ -30,7 +30,6 @@ const value::int_u8 v = 256 / f; // FIXME image3d<unsigned> histo(v,v,v); level::fill(histo, 0); - unsigned i = 0; mln_piter(I) p(ima.domain()); for_all(p) @@ -55,11 +54,11 @@ } template <typename I, typename J, typename N> -unsigned +void process_max_tree(const I& ima, const J& histo, const N& nbh, - double density_lambda, unsigned volume_lambda, - unsigned nb_represent_lambda, unsigned color_lambda, - unsigned div_factor) + double density_lambda, double value_lambda, + unsigned volume_lambda, unsigned nb_represent_lambda, + unsigned color_lambda, unsigned div_factor) { max_tree_<J,N> run(histo, nbh); @@ -70,13 +69,20 @@ image3d< algebra::vec<3, double> > mean_color = run.compute_mean_color(); image3d<double> density = compute_density(nb_represent, volume); - // Density closing + // Density fusion if (density_lambda > 0.00001) { - std::cout << "Density cutting" << std::endl; + std::cout << "Density fusion" << std::endl; run.nuclear_fusion(density, density_lambda); } + // value fusion + if (value_lambda > 0.00001) + { + std::cout << "Value fusion" << std::endl; + run.nuclear_fusion(histo, value_lambda); + } + // Volume cutting if (volume_lambda != 0) { @@ -115,7 +121,9 @@ for_all(p) if (run.is_active(p)) { - std::cerr << mean_color(p) << "\t\t" << nb_class << "\t\t" << density(p) << "\t\t" << volume(p) << "\t\t" << nb_represent(p) << std::endl; + std::cerr << mean_color(p) << "\t\t" << nb_class + << "\t\t" << density(p) << "\t\t" << volume(p) + << "\t\t" << nb_represent(p) << std::endl; ++nb_class; } @@ -125,13 +133,21 @@ // Write the image w.r.t. the max tree run.to_ppm(ima, "out.ppm", div_factor, mean_color); + + //proj + save_class_v2(ima, histo, mean_color, run.new_parent, + div_factor, "histo.ppm"); } bool usage(int argc, char ** argv) { - if (argc != 7) + if (argc != 8) { - std::cout << "usage: " << argv[0] << " image div_factor density_lambda volume_lambda nb_represent_lambda color_lambda" << std::endl; + std::cout << "usage: " << argv[0] << " image div_factor " + << "density_lambda value_lambda volume_lambda " + << "nb_represent_lambda color_lambda" << std::endl; + std::cout << "Help: A value of 0 for any lambda means " + << "the related action won't be performed" << std::endl; return false; } @@ -149,17 +165,15 @@ int div_factor = atoi(argv[2]); float density_lambda = atof(argv[3]); - unsigned volume_lambda = atoi(argv[4]); - unsigned nb_represent_lambda = atoi(argv[5]); - unsigned color_lambda = atoi(argv[6]); + float value_lambda = atof(argv[4]); + unsigned volume_lambda = atoi(argv[5]); + unsigned nb_represent_lambda = atoi(argv[6]); + unsigned color_lambda = atoi(argv[7]); //make histo image3d<unsigned> histo = fill_histo(ima, div_factor); - //proj - accu::mean<unsigned, unsigned, unsigned> mean; - image2d<unsigned> phisto = proj(histo, mean); - // Process max_tree - process_max_tree(ima, histo, c6(), density_lambda, volume_lambda, nb_represent_lambda, color_lambda, div_factor); + process_max_tree(ima, histo, c6(), density_lambda, value_lambda, + volume_lambda, nb_represent_lambda, color_lambda, div_factor); }