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[WIP] Remove Gaussian blur code alternatives that are exotic or didn't work very well #159

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[WIP] Remove Gaussian blur code alternatives that are exotic or didn't work very well #159

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7 changes: 3 additions & 4 deletions src/CMakeLists.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -10,10 +10,9 @@ add_library(popsift
popsift/sift_pyramid.cu popsift/sift_pyramid.h
popsift/sift_octave.cu popsift/sift_octave.h
popsift/s_pyramid_build.cu
popsift/s_pyramid_build_aa.cu popsift/s_pyramid_build_aa.h
popsift/s_pyramid_build_ai.cu popsift/s_pyramid_build_ai.h
popsift/s_pyramid_build_ra.cu popsift/s_pyramid_build_ra.h
popsift/s_pyramid_fixed.cu
popsift/s_pyramid_build_aa.cu
popsift/s_pyramid_build_ai.cu
popsift/s_pyramid_build_ra.cu
popsift/sift_extremum.h
popsift/sift_extremum.cu popsift/s_extrema.cu
popsift/s_orientation.cu
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16 changes: 4 additions & 12 deletions src/application/main.cpp
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Expand Up @@ -71,28 +71,20 @@ static void parseargs(int argc, char** argv, popsift::Config& config, string& in
( "gauss-mode", value<std::string>()->notifier([&](const std::string& s) { config.setGaussMode(s); }),
popsift::Config::getGaussModeUsage() )
// "Choice of span (1-sided) for Gauss filters. Default is VLFeat-like computation depending on sigma. "
// "Options are: vlfeat, relative, relative-all, opencv, fixed9, fixed15"
// "Options are: vlfeat, relative, relative-all, opencv"
("desc-mode", value<std::string>()->notifier([&](const std::string& s) { config.setDescMode(s); }),
"Choice of descriptor extraction modes:\n"
"loop, iloop, grid, igrid, notile\n"
"Default is loop\n"
"Default is loop\n"
"loop is OpenCV-like horizontal scanning, computing only valid points, grid extracts only useful points but rounds them, iloop uses linear texture and rotated gradiant fetching. igrid is grid with linear interpolation. notile is like igrid but avoids redundant gradiant fetching.")
("popsift-mode", bool_switch()->notifier([&](bool b) { if(b) config.setMode(popsift::Config::PopSift); }),
("popsift-mode", bool_switch()->notifier([&](bool b) { if(b) config.setMode(popsift::Config::RefineInOctave); }),
"During the initial upscale, shift pixels by 1. In extrema refinement, steps up to 0.6, do not reject points when reaching max iterations, "
"first contrast threshold is .8 * peak thresh. Shift feature coords octave 0 back to original pos.")
("vlfeat-mode", bool_switch()->notifier([&](bool b) { if(b) config.setMode(popsift::Config::VLFeat); }),
("vlfeat-mode", bool_switch()->notifier([&](bool b) { if(b) config.setMode(popsift::Config::RefineInLevel); }),
"During the initial upscale, shift pixels by 1. That creates a sharper upscaled image. "
"In extrema refinement, steps up to 0.6, levels remain unchanged, "
"do not reject points when reaching max iterations, "
"first contrast threshold is .8 * peak thresh.")
("opencv-mode", bool_switch()->notifier([&](bool b) { if(b) config.setMode(popsift::Config::OpenCV); }),
"During the initial upscale, shift pixels by 0.5. "
"In extrema refinement, steps up to 0.5, "
"reject points when reaching max iterations, "
"first contrast threshold is floor(.5 * peak thresh). "
"Computed filter width are lower than VLFeat/PopSift")
("direct-scaling", bool_switch()->notifier([&](bool b) { if(b) config.setScalingMode(popsift::Config::ScaleDirect); }),
"Direct each octave from upscaled orig instead of blurred level.")
("norm-multi", value<int>()->notifier([&](int i) {config.setNormalizationMultiplier(i); }), "Multiply the descriptor by pow(2,<int>).")
( "norm-mode", value<std::string>()->notifier([&](const std::string& s) { config.setNormMode(s); }),
popsift::Config::getNormModeUsage() )
Expand Down
26 changes: 7 additions & 19 deletions src/application/match.cpp
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Expand Up @@ -70,28 +70,16 @@ static void parseargs(int argc, char** argv, popsift::Config& config, string& lF
modes.add_options()
( "gauss-mode", value<std::string>()->notifier([&](const std::string& s) { config.setGaussMode(s); }),
popsift::Config::getGaussModeUsage() )
("desc-mode", value<std::string>()->notifier([&](const std::string& s) { config.setDescMode(s); }),
( "desc-mode", value<std::string>()->notifier([&](const std::string& s) { config.setDescMode(s); }),
"Choice of descriptor extraction modes:\n"
"loop, iloop, grid, igrid, notile\n"
"Default is loop\n"
"Default is loop\n"
"loop is OpenCV-like horizontal scanning, computing only valid points, grid extracts only useful points but rounds them, iloop uses linear texture and rotated gradiant fetching. igrid is grid with linear interpolation. notile is like igrid but avoids redundant gradiant fetching.")
("popsift-mode", bool_switch()->notifier([&](bool b) { if(b) config.setMode(popsift::Config::PopSift); }),
"During the initial upscale, shift pixels by 1. In extrema refinement, steps up to 0.6, do not reject points when reaching max iterations, "
"first contrast threshold is .8 * peak thresh. Shift feature coords octave 0 back to original pos.")
("vlfeat-mode", bool_switch()->notifier([&](bool b) { if(b) config.setMode(popsift::Config::VLFeat); }),
"During the initial upscale, shift pixels by 1. That creates a sharper upscaled image. "
"In extrema refinement, steps up to 0.6, levels remain unchanged, "
"do not reject points when reaching max iterations, "
"first contrast threshold is .8 * peak thresh.")
("opencv-mode", bool_switch()->notifier([&](bool b) { if(b) config.setMode(popsift::Config::OpenCV); }),
"During the initial upscale, shift pixels by 0.5. "
"In extrema refinement, steps up to 0.5, "
"reject points when reaching max iterations, "
"first contrast threshold is floor(.5 * peak thresh). "
"Computed filter width are lower than VLFeat/PopSift")
("direct-scaling", bool_switch()->notifier([&](bool b) { if(b) config.setScalingMode(popsift::Config::ScaleDirect); }),
"Direct each octave from upscaled orig instead of blurred level.")
("norm-multi", value<int>()->notifier([&](int i) {config.setNormalizationMultiplier(i); }), "Multiply the descriptor by pow(2,<int>).")
( "popsift-mode", bool_switch()->notifier([&](bool b) { if(b) config.setMode(popsift::Config::RefineInOctave); }),
"In extrema refinement, it is possible to move extrema within a level but also between the levels of an octave.")
( "vlfeat-mode", bool_switch()->notifier([&](bool b) { if(b) config.setMode(popsift::Config::RefineInLevel); }),
"In extrema refinement, it is possible to move extrema within a level only.")
( "norm-multi", value<int>()->notifier([&](int i) {config.setNormalizationMultiplier(i); }), "Multiply the descriptor by pow(2,<int>).")
( "norm-mode", value<std::string>()->notifier([&](const std::string& s) { config.setNormMode(s); }),
popsift::Config::getNormModeUsage() )
( "root-sift", bool_switch()->notifier([&](bool b) { if(b) config.setNormMode(popsift::Config::RootSift); }),
Expand Down
99 changes: 6 additions & 93 deletions src/popsift/gauss_filter.cu
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Expand Up @@ -67,42 +67,7 @@ void print_gauss_filter_symbol( int columns )

printf( "\n"
"Gauss tables\n"
" level span sigma : center value -> edge value\n"
" absolute filters octave 0 (compute level 0, all other levels directly from level 0)\n");

for( int lvl=0; lvl<d_gauss.required_filter_stages; lvl++ ) {
int span = d_gauss.abs_o0.span[lvl] + d_gauss.abs_o0.span[lvl] - 1;

printf(" %d %d %2.6f: ", lvl, span, d_gauss.abs_o0.sigma[lvl] );
int m = min( d_gauss.abs_o0.span[lvl], columns );
for( int x=0; x<m; x++ ) {
printf("%0.8f ", d_gauss.abs_o0.filter[lvl*GAUSS_ALIGN+x] );
}
if( m < d_gauss.abs_o0.span[lvl] )
printf("...\n");
else
printf("\n");
}
printf( "\n"
" absolute filters other octaves\n"
" (level 0 via downscaling, all other levels directly from level 0)\n");

for( int lvl=0; lvl<d_gauss.required_filter_stages; lvl++ ) {
int span = d_gauss.abs_oN.span[lvl] + d_gauss.abs_oN.span[lvl] - 1;

printf(" %d %d %2.6f: ", lvl, span, d_gauss.abs_oN.sigma[lvl] );
int m = min( d_gauss.abs_oN.span[lvl], columns );
for( int x=0; x<m; x++ ) {
printf("%0.8f ", d_gauss.abs_oN.filter[lvl*GAUSS_ALIGN+x] );
}
if( m < d_gauss.abs_oN.span[lvl] )
printf("...\n");
else
printf("\n");
}
printf("\n");

printf(" level 0-filters for direct downscaling\n");
" level 0-filters for direct downscaling\n");

for( int lvl=0; lvl<MAX_OCTAVES; lvl++ ) {
int span = d_gauss.dd.span[lvl] + d_gauss.dd.span[lvl] - 1;
Expand Down Expand Up @@ -187,33 +152,6 @@ void init_filter( const Config& conf,

h_gauss.inc.computeBlurTable( &h_gauss );

/* abs_o0 :
* Gauss table to create octave 0 of the absolute filters directly from
* input images.
*/
for( int lvl=0; lvl<h_gauss.required_filter_stages; lvl++ ) {
const float sigmaS = sigma0 * pow( 2.0f, (float)(lvl)/(float)levels );
h_gauss.abs_o0.sigma[lvl] = sqrt( fabs( sigmaS * sigmaS - initial_blur * initial_blur ) );
}

h_gauss.abs_o0.computeBlurTable( &h_gauss );

/* abs_oN :
* Gauss tables to create levels 1 and above directly from level 0 of every
* octave. Could be used on octave 0, but abs_o0 is better.
* Level 0 must be created by other means (downscaling from previous octave,
* direct downscaling from input image, ...) before using abs_oN.
*
*/
h_gauss.abs_oN.sigma[0] = 0;
for( int lvl=1; lvl<h_gauss.required_filter_stages; lvl++ ) {
const float sigmaP = sigma0; // level 0 has already reached sigma0 blur
const float sigmaS = sigma0 * pow( 2.0f, (float)(lvl)/(float)levels );
h_gauss.abs_oN.sigma[lvl] = sqrt( sigmaS * sigmaS - sigmaP * sigmaP );
}

h_gauss.abs_oN.computeBlurTable( &h_gauss );

/* dd :
* The direct-downscaling kernels make use of the assumption that downscaling
* from MAX_LEVEL-3 is identical to applying 2*sigma on the identical image
Expand All @@ -224,17 +162,13 @@ void init_filter( const Config& conf,
* octaves, where it is also good for performance.
* dd is only for creating level 0 of all octave directly from the input image.
*/
for( int oct=0; oct<MAX_OCTAVES; oct++ ) {
// sigma * 2^i
float oct_sigma = scalbnf( sigma0, oct );

// subtract initial blur
float b = sqrt( fabs( oct_sigma * oct_sigma - initial_blur * initial_blur ) );
// subtract initial blur
const float b = sqrt( fabs( sigma0 * sigma0 - initial_blur * initial_blur ) );

// sigma / 2^i
h_gauss.dd.sigma[oct] = scalbnf( b, -oct );
h_gauss.dd.computeBlurTable( &h_gauss );
}
// sigma / 2^i
h_gauss.dd.sigma[0] = b;
h_gauss.dd.computeBlurTable( &h_gauss );

cudaError_t err;
err = cudaMemcpyToSymbol( d_gauss,
Expand All @@ -260,8 +194,6 @@ __host__
void GaussInfo::clearTables( )
{
inc .clearTables();
abs_o0 .clearTables();
abs_oN .clearTables();
dd .clearTables();
}

Expand All @@ -276,20 +208,10 @@ int GaussInfo::getSpan( float sigma ) const
{
switch( _span_mode )
{
case Config::VLFeat_Relative_All :
// return GaussInfo::vlFeatRelativeSpan( sigma );
return GaussInfo::vlFeatSpan( sigma );

case Config::VLFeat_Compute :
return GaussInfo::vlFeatSpan( sigma );
case Config::VLFeat_Relative :
return GaussInfo::vlFeatRelativeSpan( sigma );
case Config::OpenCV_Compute :
return GaussInfo::openCVSpan( sigma );
case Config::Fixed9 :
return 5;
case Config::Fixed15 :
return 8;
default :
stringstream ss;
ss << "ERROR: The mode for computing Gauss filter scan is invalid";
Expand Down Expand Up @@ -317,15 +239,6 @@ int GaussInfo::vlFeatRelativeSpan( float sigma )
return spn;
}

__host__
int GaussInfo::openCVSpan( float sigma )
{
int span = int( roundf( 2.0f * 4.0f * sigma + 1.0f ) ) | 1;
span >>= 1;
span += 1;
return std::min<int>( span, GAUSS_ALIGN - 1 );
}

template<int LEVELS>
__host__
void GaussTable<LEVELS>::clearTables( )
Expand Down
25 changes: 4 additions & 21 deletions src/popsift/gauss_filter.h
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Expand Up @@ -61,25 +61,11 @@ struct GaussInfo
*/
GaussTable<GAUSS_LEVELS> inc;

/* Compute the 1D Gauss tables for all levels of octave 0.
* For octave 0, all of these tables derive from the input
* image.
/* This is the 1D Gauss table for filtering the input image.
* The input image is downscaled and blurred with sigma or by
* blurring the input image with 2*sigma and downscaling afterwards.
*/
GaussTable<GAUSS_LEVELS> abs_o0;

/* Compute the 1D Gauss tables for all levels of octaves 1 and up.
* Level 0 is empty, since it is created by other means.
* All other levels blur from level 0, not considering any
* initial blur.
*/
GaussTable<GAUSS_LEVELS> abs_oN;

/* In theory, level 0 of octave 2 contains the same information
* whether it is constructed by downscaling and blurring the
* input image with sigma or by blurring the input image with 2*sigma
* and downscaling afterwards.
*/
GaussTable<MAX_OCTAVES> dd;
GaussTable<1> dd;

__host__
void clearTables( );
Expand All @@ -99,9 +85,6 @@ struct GaussInfo

__host__
static int vlFeatRelativeSpan( float sigma );

__host__
static int openCVSpan( float sigma );
};

extern __device__ __constant__ GaussInfo d_gauss;
Expand Down
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