[Olena-patches] olena: olena-2.0-592-ge6c9b24 Add Keypoint class and start extremum elimination

--- milena/sandbox/anthony/Makefile | 2 +- milena/sandbox/anthony/src/keypoint.cc | 18 + milena/sandbox/anthony/src/keypoint.hh | 27 ++ milena/sandbox/anthony/src/scale_space.cc | 517 ----------------------------- 4 files changed, 46 insertions(+), 518 deletions(-) create mode 100644 milena/sandbox/anthony/src/keypoint.cc create mode 100644 milena/sandbox/anthony/src/keypoint.hh delete mode 100644 milena/sandbox/anthony/src/scale_space.cc diff --git a/milena/sandbox/anthony/Makefile b/milena/sandbox/anthony/Makefile index e43db7f..ff62f9e 100644 --- a/milena/sandbox/anthony/Makefile +++ b/milena/sandbox/anthony/Makefile @@ -4,7 +4,7 @@ CFLAGS=-Wall -Werror CLIBS=-I../../ CLEAN=*.o output/* log -SRC=src/scale_space.cc +SRC=src/main.cc src/keypoint.cc OUTPUT=a.out all: scale diff --git a/milena/sandbox/anthony/src/keypoint.cc b/milena/sandbox/anthony/src/keypoint.cc new file mode 100644 index 0000000..bf0a5f5 --- /dev/null +++ b/milena/sandbox/anthony/src/keypoint.cc @@ -0,0 +1,18 @@ +#include "keypoint.hh" + +// Constructor +Keypoint::Keypoint(unsigned i, unsigned j, + unsigned scale, unsigned size, bool maximum) +{ + this->i = i; + this->j = j; + this->scale = scale; + this->size = size; + this->maximum = maximum; +} + +// Getters +unsigned Keypoint::getI() { return i; } +unsigned Keypoint::getJ() { return j; } +unsigned Keypoint::getScale() { return scale; } +unsigned Keypoint::getSize() { return size; } diff --git a/milena/sandbox/anthony/src/keypoint.hh b/milena/sandbox/anthony/src/keypoint.hh new file mode 100644 index 0000000..798a980 --- /dev/null +++ b/milena/sandbox/anthony/src/keypoint.hh @@ -0,0 +1,27 @@ +#ifndef KEYPOINT_HH +# define KEYPOINT_HH + +# include <ostream> + +class Keypoint +{ + public: + // Constructor + Keypoint(unsigned i, unsigned j, + unsigned scale, unsigned size, bool maximum); + + // Getters + unsigned getI(); + unsigned getJ(); + unsigned getScale(); + unsigned getSize(); + + private: + unsigned i; + unsigned j; + unsigned scale; + unsigned size; + bool maximum; +}; + +#endif /* ! KEYPOINT_HH */ diff --git a/milena/sandbox/anthony/src/scale_space.cc b/milena/sandbox/anthony/src/scale_space.cc deleted file mode 100644 index 87853ef..0000000 --- a/milena/sandbox/anthony/src/scale_space.cc +++ /dev/null @@ -1,517 +0,0 @@ -#include <mln/core/image/image2d.hh> -#include <mln/data/all.hh> -#include <mln/io/pgm/all.hh> -#include <mln/io/ppm/save.hh> -#include <mln/core/alias/neighb2d.hh> -#include <mln/literal/all.hh> -#include <mln/value/int_s8.hh> - -#include <cmath> - -using namespace mln; - -// Set the gaussian kernel -float *gaussian_kernel() -{ - float variance = sqrt(2.0); - unsigned index = 0; - float *kernel = new float[49]; - static const float pi = 4.0 * atan(1.0); - float div = (2.0 * pi * variance); - - for (int i = -3; i < 4; ++i) - { - for (int j = -3; j < 4; ++j) - { - float e = exp(- (i*i + j*j) / (2.0 * variance) ); - kernel[index++] = e / div; - } - } - - return kernel; -} - -// Apply the convolution of the image by the kernel -template<typename I> -void convolve(const I& original, I& filtered, float *kernel) -{ - mln_piter(I) p(filtered.domain()); - window2d win; - - for (int i = -3; i < 4; ++i) - for (int j = -3; j < 4; ++j) - win.insert(i, j); - - // Iterate through all image sites - for_all(p) - { - // Create the window around the site - mln_qiter(window2d) q(win, p); - float sum = 0; - int index = 0; - - // Iterate through all window image sites - for_all(q) - { - if (filtered.has(q)) - sum += original(q) * kernel[index++]; - else - sum += 127 * kernel[index++]; - } - - filtered(p) = static_cast<int>(sum); - } -} - -// Blur the image thanks to a convolution matrix -template<typename I> -I blur(const I& original) -{ - I filtered; - float *kernel = gaussian_kernel(); - - initialize(filtered, original); - convolve(original, filtered, kernel); - - return filtered; -} - -// Downscale by 2 the image resolution -template<typename I> -I downscaling2(const I& original) -{ - mln_piter(I) p(original.domain()); - window2d win; - int index = 0; - - // Initialize the rescaled image - box2d size(original.nrows() / 2, original.ncols() / 2); - I reduced(size); - - // Set the 2x2 window matrix - for (int i = 0; i < 2; ++i) - for (int j = 0; j < 2; ++j) - win.insert(i, j); - - // Iterate through all image sites - for_all(p) - { - // Get 1/4 of total pixels - if (index % 2 == 0) - { - int i = (index % original.ncols()) / 2; - int j = (index / original.ncols()) / 2; - int count = 0; - int sum = 0; - mln_qiter(window2d) q(win, p); - - // Iterate through all window image sites - for_all(q) - { - if (original.has(q)) - { - sum += original(q); - ++count; - } - } - - if (reduced.has(point2d(j, i))) - opt::at(reduced, j, i) = sum / count; - } - - ++index; - } - - return reduced; -} - -float *upscalingTL_kernel() -{ - const static float one = 1.0 / 8.0; - const static float two = 2.0 / 8.0; - const static float three = 2.0 / 8.0; - const static float four = 3.0 / 8.0; - - float *kernel = new float[4]; - - kernel[0] = one; - kernel[1] = two; - kernel[2] = three; - kernel[3] = four; - - return kernel; -} - -float *upscalingTR_kernel() -{ - const static float one = 2.0 / 8.0; - const static float two = 1.0 / 8.0; - const static float three = 3.0 / 8.0; - const static float four = 2.0 / 8.0; - - float *kernel = new float[4]; - - kernel[0] = one; - kernel[1] = two; - kernel[2] = three; - kernel[3] = four; - - return kernel; -} - -float *upscalingBL_kernel() -{ - const static float one = 2.0 / 8.0; - const static float two = 3.0 / 8.0; - const static float three = 1.0 / 8.0; - const static float four = 2.0 / 8.0; - - float *kernel = new float[4]; - - kernel[0] = one; - kernel[1] = two; - kernel[2] = three; - kernel[3] = four; - - return kernel; -} - -float *upscalingBR_kernel() -{ - const static float one = 3.0 / 8.0; - const static float two = 2.0 / 8.0; - const static float three = 2.0 / 8.0; - const static float four = 1.0 / 8.0; - - float *kernel = new float[4]; - - kernel[0] = one; - kernel[1] = two; - kernel[2] = three; - kernel[3] = four; - - return kernel; -} - -template<typename I> -unsigned upscalePixel(const I& original, int i, int j, int type) -{ - float *kernel; - window2d win; - mln_psite(I) p(i, j); - float value = 0; - unsigned index = 0; - int iStart = 0; - int jStart = 0; - - if (type == 0) - { - kernel = upscalingTL_kernel(); - iStart = -1; - jStart = -1; - } - else if (type == 1) - { - kernel = upscalingTR_kernel(); - iStart = 0; - jStart = -1; - } - else if (type == 2) - { - kernel = upscalingBL_kernel(); - iStart = -1; - jStart = 0; - } - else - { - kernel = upscalingBR_kernel(); - iStart = 0; - jStart = 0; - } - - for (int ii = iStart; ii < iStart + 2; ++ii) - for (int jj = jStart; jj < jStart + 2; ++jj) - win.insert(ii, jj); - - mln_qiter(window2d) q(win, p); - - for_all(q) - { - if (original.has(q)) - { - value += original(q) * kernel[index]; - } - - ++index; - } - - return (static_cast<int>(value)); -} - -// Upscale by 2 the image resolution -template<typename I> -I upscaling2(const I& original) -{ - box2d size(original.nrows() * 2, original.ncols() * 2); - I upscaled(size); - - mln_piter(I) p(upscaled.domain()); - int index = 0; - - for_all(p) - { - int i = p.col(); - int j = p.row(); - - if (i % 2 == 0 && j % 2 == 0) // Top left - opt::at(upscaled, i, j) = upscalePixel(original, i / 2, j / 2, 0); - else if (i % 2 == 0) // Bottom left - opt::at(upscaled, i, j) = upscalePixel(original, i / 2, j / 2, 2); - else if (j % 2 == 0) // Top right - opt::at(upscaled, i, j) = upscalePixel(original, i / 2, j / 2, 1); - else // Bottom right - opt::at(upscaled, i, j) = upscalePixel(original, i / 2, j / 2, 3); - - ++index; - } - - - return upscaled; -} - -// Build the n-th octave on b blur levels -template<typename I> -void buildOctave(const I& original, - unsigned n, - unsigned b, - std::vector< std::vector<I> >& scaleSpace) -{ - std::vector<I> octave; - std::stringstream name; - I blured; - initialize(blured, original); - - name << "output/SS-o" << n << "-0.pgm"; - io::pgm::save(original, name.str()); - - octave.push_back(original); - blured = duplicate(original); - - for(unsigned i = 1; i <= b; i *= 2) - { - blured = blur(blured); - octave.push_back(blured); - - name.str(""); - name << "output/SS-o" << n << "-" << i << ".pgm"; - io::pgm::save(blured, name.str()); - } - - scaleSpace.push_back(octave); -} - -// Build n octaves on b blur levels -template<typename I> -void buildScaleSpace(std::vector< std::vector<I> >& scaleSpace, - const I& original, - unsigned n, - unsigned b) -{ - if (n > 2) - { - // Upscaled octave - I upscaled = upscaling2(original); - buildOctave(upscaled, 0, b, scaleSpace); - - // 1st octave - buildOctave(original, 1, b, scaleSpace); - - // 2nd octave - I downscaled = downscaling2(original); - buildOctave(downscaled, 2, b, scaleSpace); - - for (unsigned i = 3; i <= n; ++i) - { - // i-th octave - downscaled = downscaling2(downscaled); - buildOctave(downscaled, i, b, scaleSpace); - } - } - else - { - std::cerr << "ERROR: buildScaleSpace: Wrong level number (" << n << ")" - << std::endl; - } -} - -// Build the DoG pyramid of the scale space -template<typename I> -void buildDifferenceOfGaussianSpace(std::vector< std::vector<I> >& scaleSpace, - std::vector< std::vector<I> >& dogSpace) -{ - for (unsigned i = 0; i < scaleSpace.size(); ++i) - { - std::vector<I> octave = scaleSpace.at(i); - std::vector<I> dogOctave; - - for (unsigned j = 0; j < octave.size() - 1; ++j) - { - std::stringstream name; - I level1 = octave.at(j); - I level2 = octave.at(j + 1); - I dog; - - initialize(dog, level1); - - mln_piter(I) p(level1.domain()); - - for_all(p) - { - int diff = ((int) level1(p)) - ((int) level2(p)); - dog(p) = (diff >= 0) ? diff : 0; - } - - dogOctave.push_back(dog); - name << "output/DoG_o" << i << "-" << j << ".pgm"; - io::pgm::save(dog, name.str()); - } - - dogSpace.push_back(dogOctave); - } -} - -// Find the extremum value in the c8 neighborhood -template<typename T, typename I, typename N> -void find_extremum(T& min, T& max, const I& current, N n) -{ - for_all(n) - { - if (current(n) > max) - max = current(n); - - if (current(n) < min) - min = current(n); - } -} - -// Find the minimum value in the upper and lower layers around p -template<typename T, typename I, typename P> -void find_min(T& min, const I& upper, const I& lower, const P& pUpper, const P& pLower) -{ - mln_niter(neighb2d) nUpper(c8(), pUpper); - mln_niter(neighb2d) nLower(c8(), pLower); - - // Upper processing - for_all(nUpper) - if (upper(nUpper) < min) - min = upper(nUpper); - - // Lower processing - for_all(nLower) - if (lower(nLower) < min) - min = lower(nLower); -} - -// Find the maximum value in the upper and lower layers around p -template<typename T, typename I, typename P> -void find_max(T& max, const I& upper, const I& lower, const P& pUpper, const P& pLower) -{ - mln_niter(neighb2d) nUpper(c8(), pUpper); - mln_niter(neighb2d) nLower(c8(), pLower); - - // Upper processing - for_all(nUpper) - if (upper(nUpper) > max) - max = upper(nUpper); - - // Lower processing - for_all(nLower) - if (lower(nLower) > max) - max = lower(nLower); -} - -// Build the extrema image -template<typename I, typename C> -void buildExtrema(C extrema, - I original, - std::vector< std::vector<I> >& dogSpace) -{ - extrema = data::convert(value::rgb8(), original); - - const unsigned blur_level = dogSpace.at(0).size(); - - //unsigned i = 0; - for (unsigned i = 0; i < blur_level; ++i) - { - for (unsigned j = 1; j < dogSpace.size() - 1; ++j) - { - I current = dogSpace.at(j).at(i); - I upper = dogSpace.at(j+1).at(i); - I lower = dogSpace.at(j-1).at(i); - - mln_piter(I) p(current.domain()); - - for_all(p) - { - value::int_u8 min = 255; - value::int_u8 max = 0; - value::int_u8 center = 0; - - mln_niter(neighb2d) n(c8(), p); - center = current(p); - - mln_psite(I) pUpper(p.row() / 2, p.col() / 2); - mln_psite(I) pLower(p.row() * 2, p.col() * 2); - - find_extremum(min, max, current, n); - - if (center <= min) - { - find_min(min, upper, lower, pUpper, pLower); - - if (center < min) - { - mln_psite(I) pOriginal(p.row() * pow(2, (j-1)), - p.col() * pow(2, (j-1))); - extrema(pOriginal) = literal::red; - } - } - else if (center >= max) - { - find_max(max, upper, lower, pUpper, pLower); - - if (center > max) - { - mln_psite(I) pOriginal(p.row() * pow(2, (j-1)), - p.col() * pow(2, (j-1))); - extrema(pOriginal) = literal::red; - } - } - } - } - } - - io::ppm::save(extrema, "output/extrema.ppm"); -} - -// Main entry point -int main(int argc, char** argv) -{ - typedef image2d<value::int_u8> I; - typedef image2d<value::rgb8> C; - - const unsigned blur_level = 5; - const unsigned octave_level = 4; - std::vector< std::vector<I> > scaleSpace; - std::vector< std::vector<I> > dogSpace; - I original; - C extrema; - - io::pgm::load(original, "images/lena.pgm"); - - buildScaleSpace(scaleSpace, original, octave_level, blur_level); - buildDifferenceOfGaussianSpace(scaleSpace, dogSpace); - buildExtrema(extrema, original, dogSpace); - - return 0; -} -- 1.7.2.5