Commit 0ffdc782 authored by Davis King's avatar Davis King

Made remove_unobtainable_rectangles() work on scan_fhog_pyramid.

parent 791e9cda
......@@ -7,6 +7,7 @@
#include "scan_image_pyramid.h"
#include "scan_image_boxes.h"
#include "scan_image_custom.h"
#include "scan_fhog_pyramid.h"
#include "../svm/structural_object_detection_trainer.h"
#include "../geometry.h"
......@@ -53,87 +54,117 @@ namespace dlib
return best_rect;
}
}
// ----------------------------------------------------------------------------------------
// ------------------------------------------------------------------------------------
template <
typename image_array_type,
typename Pyramid_type,
typename Feature_extractor_type
>
std::vector<std::vector<rectangle> > remove_unobtainable_rectangles (
const structural_object_detection_trainer<scan_image_pyramid<Pyramid_type, Feature_extractor_type> >& trainer,
const image_array_type& images,
std::vector<std::vector<rectangle> >& object_locations
)
{
using namespace dlib::impl;
// make sure requires clause is not broken
DLIB_ASSERT(images.size() == object_locations.size(),
"\t std::vector<std::vector<rectangle>> remove_unobtainable_rectangles()"
<< "\n\t Invalid inputs were given to this function."
template <
typename image_array_type,
typename image_scanner_type
>
std::vector<std::vector<rectangle> > pyramid_remove_unobtainable_rectangles (
const structural_object_detection_trainer<image_scanner_type>& trainer,
const image_array_type& images,
std::vector<std::vector<rectangle> >& object_locations
)
{
using namespace dlib::impl;
// make sure requires clause is not broken
DLIB_ASSERT(images.size() == object_locations.size(),
"\t std::vector<std::vector<rectangle>> remove_unobtainable_rectangles()"
<< "\n\t Invalid inputs were given to this function."
);
std::vector<std::vector<rectangle> > rejects(images.size());
// If the trainer is setup to automatically fit the overlap tester to the data then
// we should use the loosest possible overlap tester here. Otherwise we should use
// the tester the trainer will use.
test_box_overlap boxes_overlap(0.9999999,1);
if (!trainer.auto_set_overlap_tester())
boxes_overlap = trainer.get_overlap_tester();
std::vector<std::vector<rectangle> > rejects(images.size());
for (unsigned long k = 0; k < images.size(); ++k)
{
std::vector<rectangle> objs = object_locations[k];
// If the trainer is setup to automatically fit the overlap tester to the data then
// we should use the loosest possible overlap tester here. Otherwise we should use
// the tester the trainer will use.
test_box_overlap boxes_overlap(0.9999999,1);
if (!trainer.auto_set_overlap_tester())
boxes_overlap = trainer.get_overlap_tester();
// First remove things that don't have any matches with the candidate object
// locations.
std::vector<rectangle> good_rects;
for (unsigned long j = 0; j < objs.size(); ++j)
for (unsigned long k = 0; k < images.size(); ++k)
{
const rectangle rect = trainer.get_scanner().get_best_matching_rect(objs[j]);
const double score = (objs[j].intersect(rect)).area()/(double)(objs[j] + rect).area();
if (score > trainer.get_match_eps())
good_rects.push_back(objs[j]);
else
rejects[k].push_back(objs[j]);
}
object_locations[k] = good_rects;
std::vector<rectangle> objs = object_locations[k];
// First remove things that don't have any matches with the candidate object
// locations.
std::vector<rectangle> good_rects;
for (unsigned long j = 0; j < objs.size(); ++j)
{
const rectangle rect = trainer.get_scanner().get_best_matching_rect(objs[j]);
const double score = (objs[j].intersect(rect)).area()/(double)(objs[j] + rect).area();
if (score > trainer.get_match_eps())
good_rects.push_back(objs[j]);
else
rejects[k].push_back(objs[j]);
}
object_locations[k] = good_rects;
// Remap these rectangles to the ones that can come out of the scanner. That
// way when we compare them to each other in the following loop we will know if
// any distinct truth rectangles get mapped to overlapping boxes.
objs.resize(good_rects.size());
for (unsigned long i = 0; i < good_rects.size(); ++i)
objs[i] = trainer.get_scanner().get_best_matching_rect(good_rects[i]);
good_rects.clear();
// now check for truth rects that are too close together.
for (unsigned long i = 0; i < objs.size(); ++i)
{
// check if objs[i] hits another box
bool hit_box = false;
for (unsigned long j = i+1; j < objs.size(); ++j)
// Remap these rectangles to the ones that can come out of the scanner. That
// way when we compare them to each other in the following loop we will know if
// any distinct truth rectangles get mapped to overlapping boxes.
objs.resize(good_rects.size());
for (unsigned long i = 0; i < good_rects.size(); ++i)
objs[i] = trainer.get_scanner().get_best_matching_rect(good_rects[i]);
good_rects.clear();
// now check for truth rects that are too close together.
for (unsigned long i = 0; i < objs.size(); ++i)
{
if (boxes_overlap(objs[i], objs[j]))
// check if objs[i] hits another box
bool hit_box = false;
for (unsigned long j = i+1; j < objs.size(); ++j)
{
hit_box = true;
break;
if (boxes_overlap(objs[i], objs[j]))
{
hit_box = true;
break;
}
}
if (hit_box)
rejects[k].push_back(object_locations[k][i]);
else
good_rects.push_back(object_locations[k][i]);
}
if (hit_box)
rejects[k].push_back(object_locations[k][i]);
else
good_rects.push_back(object_locations[k][i]);
object_locations[k] = good_rects;
}
object_locations[k] = good_rects;
return rejects;
}
return rejects;
}
// ----------------------------------------------------------------------------------------
template <
typename image_array_type,
typename Pyramid_type,
typename Feature_extractor_type
>
std::vector<std::vector<rectangle> > remove_unobtainable_rectangles (
const structural_object_detection_trainer<scan_image_pyramid<Pyramid_type, Feature_extractor_type> >& trainer,
const image_array_type& images,
std::vector<std::vector<rectangle> >& object_locations
)
{
return impl::pyramid_remove_unobtainable_rectangles(trainer, images, object_locations);
}
// ----------------------------------------------------------------------------------------
template <
typename image_array_type,
typename Pyramid_type
>
std::vector<std::vector<rectangle> > remove_unobtainable_rectangles (
const structural_object_detection_trainer<scan_fhog_pyramid<Pyramid_type> >& trainer,
const image_array_type& images,
std::vector<std::vector<rectangle> >& object_locations
)
{
return impl::pyramid_remove_unobtainable_rectangles(trainer, images, object_locations);
}
// ----------------------------------------------------------------------------------------
......
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