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Merge pull request #8869 from hrnr:akaze_part1

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[GSOC] Speeding-up AKAZE, part #1 (#8869)

* ts: expand arguments before stringifications in CV_ENUM and CV_FLAGS

added protective macros to always force macro expansion of arguments. This allows using CV_ENUM and CV_FLAGS with macro arguments.

* feature2d: unify perf test

use the same test for all detectors/descriptors we have.

* added AKAZE tests

* features2d: extend perf tests

* add BRISK, KAZE, MSER
* run all extract tests on AKAZE keypoints, so that the test si more comparable for the speed of extraction

* feature2d: rework opencl perf tests

use the same configuration as cpu tests

* feature2d: fix descriptors allocation for AKAZE and KAZE

fix crash when descriptors are UMat

* feature2d: name enum to fix build with older gcc

* Revert "ts: expand arguments before stringifications in CV_ENUM and CV_FLAGS"

This reverts commit 19538cac1e.

This wasn't a great idea after all. There is a lot of flags implemented as #define, that we don't want to expand.

* feature2d: fix expansion problems with CV_ENUM in perf

* expand arguments before passing them to CV_ENUM. This does not need modifications of CV_ENUM.
* added include guards to `perf_feature2d.hpp`

* feature2d: fix crash in AKAZE when using KAZE descriptors

* out-of-bound access in Get_MSURF_Descriptor_64
* this happened reliably when running on provided keypoints (not computed by the same instance)

* feature2d: added regression tests for AKAZE

* test with both MLDB and KAZE keypoints

* feature2d: do not compute keypoints orientation twice

* always compute keypoints orientation, when computing keypoints
* do not recompute keypoint orientation when computing descriptors

this allows to test detection and extraction separately

* features2d: fix crash in AKAZE

* out-of-bound reads near the image edge
* same as the bug in KAZE descriptors

* feature2d: refactor invariance testing

* split detectors and descriptors tests
* rewrite to google test to simplify debugging
* add tests for AKAZE and one test for ORB

* stitching: add tests with AKAZE feature finder

* added basic stitching cpu and ocl tests
* fix bug in AKAZE wrapper for stitching pipeline causing lots of
! OPENCV warning: getUMat()/getMat() call chain possible problem.
!                 Base object is dead, while nested/derived object is still alive or processed.
!                 Please check lifetime of UMat/Mat objects!
This commit is contained in:
Jiri Horner
2017-06-21 13:33:09 +02:00
committed by Alexander Alekhin
parent 437ca0b62a
commit 5f20e802d2
21 changed files with 849 additions and 1085 deletions
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modules/features2d/perf/opencl/perf_fast.cpp
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#include "../perf_precomp.hpp"
#include "opencv2/ts/ocl_perf.hpp"
#ifdef HAVE_OPENCL
namespace cvtest {
namespace ocl {
enum { TYPE_5_8 =FastFeatureDetector::TYPE_5_8, TYPE_7_12 = FastFeatureDetector::TYPE_7_12, TYPE_9_16 = FastFeatureDetector::TYPE_9_16 };
CV_ENUM(FastType, TYPE_5_8, TYPE_7_12)
typedef std::tr1::tuple<string, FastType> File_Type_t;
typedef TestBaseWithParam<File_Type_t> FASTFixture;
#define FAST_IMAGES \
"cv/detectors_descriptors_evaluation/images_datasets/leuven/img1.png",\
"stitching/a3.png"
OCL_PERF_TEST_P(FASTFixture, FastDetect, testing::Combine(
testing::Values(FAST_IMAGES),
FastType::all()
))
{
string filename = getDataPath(get<0>(GetParam()));
int type = get<1>(GetParam());
Mat mframe = imread(filename, IMREAD_GRAYSCALE);
if (mframe.empty())
FAIL() << "Unable to load source image " << filename;
UMat frame;
mframe.copyTo(frame);
declare.in(frame);
Ptr<FeatureDetector> fd = FastFeatureDetector::create(20, true, type);
ASSERT_FALSE( fd.empty() );
vector<KeyPoint> points;
OCL_TEST_CYCLE() fd->detect(frame, points);
SANITY_CHECK_KEYPOINTS(points);
}
} // ocl
} // cvtest
#endif // HAVE_OPENCL
modules/features2d/perf/opencl/perf_feature2d.cpp
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#include "../perf_precomp.hpp"
#include "opencv2/ts/ocl_perf.hpp"
#include "../perf_feature2d.hpp"
#ifdef HAVE_OPENCL
namespace cvtest {
namespace ocl {
OCL_PERF_TEST_P(feature2d, detect, testing::Combine(Feature2DType::all(), TEST_IMAGES))
{
Ptr<Feature2D> detector = getFeature2D(get<0>(GetParam()));
std::string filename = getDataPath(get<1>(GetParam()));
Mat mimg = imread(filename, IMREAD_GRAYSCALE);
ASSERT_FALSE(mimg.empty());
ASSERT_TRUE(detector);
UMat img, mask;
mimg.copyTo(img);
declare.in(img);
vector<KeyPoint> points;
OCL_TEST_CYCLE() detector->detect(img, points, mask);
EXPECT_GT(points.size(), 20u);
SANITY_CHECK_NOTHING();
}
OCL_PERF_TEST_P(feature2d, extract, testing::Combine(testing::Values(DETECTORS_EXTRACTORS), TEST_IMAGES))
{
Ptr<Feature2D> detector = AKAZE::create();
Ptr<Feature2D> extractor = getFeature2D(get<0>(GetParam()));
std::string filename = getDataPath(get<1>(GetParam()));
Mat mimg = imread(filename, IMREAD_GRAYSCALE);
ASSERT_FALSE(mimg.empty());
ASSERT_TRUE(extractor);
UMat img, mask;
mimg.copyTo(img);
declare.in(img);
vector<KeyPoint> points;
detector->detect(img, points, mask);
EXPECT_GT(points.size(), 20u);
UMat descriptors;
OCL_TEST_CYCLE() extractor->compute(img, points, descriptors);
EXPECT_EQ((size_t)descriptors.rows, points.size());
SANITY_CHECK_NOTHING();
}
OCL_PERF_TEST_P(feature2d, detectAndExtract, testing::Combine(testing::Values(DETECTORS_EXTRACTORS), TEST_IMAGES))
{
Ptr<Feature2D> detector = getFeature2D(get<0>(GetParam()));
std::string filename = getDataPath(get<1>(GetParam()));
Mat mimg = imread(filename, IMREAD_GRAYSCALE);
ASSERT_FALSE(mimg.empty());
ASSERT_TRUE(detector);
UMat img, mask;
mimg.copyTo(img);
declare.in(img);
vector<KeyPoint> points;
UMat descriptors;
OCL_TEST_CYCLE() detector->detectAndCompute(img, mask, points, descriptors, false);
EXPECT_GT(points.size(), 20u);
EXPECT_EQ((size_t)descriptors.rows, points.size());
SANITY_CHECK_NOTHING();
}
} // ocl
} // cvtest
#endif // HAVE_OPENCL
modules/features2d/perf/opencl/perf_orb.cpp
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#include "../perf_precomp.hpp"
#include "opencv2/ts/ocl_perf.hpp"
#ifdef HAVE_OPENCL
namespace cvtest {
namespace ocl {
typedef ::perf::TestBaseWithParam<std::string> ORBFixture;
#define ORB_IMAGES OCL_PERF_ENUM("cv/detectors_descriptors_evaluation/images_datasets/leuven/img1.png", "stitching/a3.png")
OCL_PERF_TEST_P(ORBFixture, ORB_Detect, ORB_IMAGES)
{
string filename = getDataPath(GetParam());
Mat mframe = imread(filename, IMREAD_GRAYSCALE);
if (mframe.empty())
FAIL() << "Unable to load source image " << filename;
UMat frame, mask;
mframe.copyTo(frame);
declare.in(frame);
Ptr<ORB> detector = ORB::create(1500, 1.3f, 1);
vector<KeyPoint> points;
OCL_TEST_CYCLE() detector->detect(frame, points, mask);
EXPECT_GT(points.size(), 20u);
SANITY_CHECK_NOTHING();
}
OCL_PERF_TEST_P(ORBFixture, ORB_Extract, ORB_IMAGES)
{
string filename = getDataPath(GetParam());
Mat mframe = imread(filename, IMREAD_GRAYSCALE);
if (mframe.empty())
FAIL() << "Unable to load source image " << filename;
UMat mask, frame;
mframe.copyTo(frame);
declare.in(frame);
Ptr<ORB> detector = ORB::create(1500, 1.3f, 1);
vector<KeyPoint> points;
detector->detect(frame, points, mask);
EXPECT_GT(points.size(), 20u);
UMat descriptors;
OCL_TEST_CYCLE() detector->compute(frame, points, descriptors);
EXPECT_EQ((size_t)descriptors.rows, points.size());
SANITY_CHECK_NOTHING();
}
OCL_PERF_TEST_P(ORBFixture, ORB_Full, ORB_IMAGES)
{
string filename = getDataPath(GetParam());
Mat mframe = imread(filename, IMREAD_GRAYSCALE);
if (mframe.empty())
FAIL() << "Unable to load source image " << filename;
UMat mask, frame;
mframe.copyTo(frame);
declare.in(frame);
Ptr<ORB> detector = ORB::create(1500, 1.3f, 1);
vector<KeyPoint> points;
UMat descriptors;
OCL_TEST_CYCLE() detector->detectAndCompute(frame, mask, points, descriptors, false);
EXPECT_GT(points.size(), 20u);
EXPECT_EQ((size_t)descriptors.rows, points.size());
SANITY_CHECK_NOTHING();
}
} // ocl
} // cvtest
#endif // HAVE_OPENCL
modules/features2d/perf/perf_agast.cpp
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#include "perf_precomp.hpp"
using namespace std;
using namespace cv;
using namespace perf;
using std::tr1::make_tuple;
using std::tr1::get;
enum { AGAST_5_8 = AgastFeatureDetector::AGAST_5_8, AGAST_7_12d = AgastFeatureDetector::AGAST_7_12d,
AGAST_7_12s = AgastFeatureDetector::AGAST_7_12s, OAST_9_16 = AgastFeatureDetector::OAST_9_16 };
CV_ENUM(AgastType, AGAST_5_8, AGAST_7_12d,
AGAST_7_12s, OAST_9_16)
typedef std::tr1::tuple<string, AgastType> File_Type_t;
typedef perf::TestBaseWithParam<File_Type_t> agast;
#define AGAST_IMAGES \
"cv/detectors_descriptors_evaluation/images_datasets/leuven/img1.png",\
"stitching/a3.png"
PERF_TEST_P(agast, detect, testing::Combine(
testing::Values(AGAST_IMAGES),
AgastType::all()
))
{
string filename = getDataPath(get<0>(GetParam()));
int type = get<1>(GetParam());
Mat frame = imread(filename, IMREAD_GRAYSCALE);
if (frame.empty())
FAIL() << "Unable to load source image " << filename;
declare.in(frame);
Ptr<FeatureDetector> fd = AgastFeatureDetector::create(70, true, type);
ASSERT_FALSE( fd.empty() );
vector<KeyPoint> points;
TEST_CYCLE() fd->detect(frame, points);
SANITY_CHECK_KEYPOINTS(points);
}
modules/features2d/perf/perf_fast.cpp
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#include "perf_precomp.hpp"
using namespace std;
using namespace cv;
using namespace perf;
using std::tr1::make_tuple;
using std::tr1::get;
enum { TYPE_5_8 =FastFeatureDetector::TYPE_5_8, TYPE_7_12 = FastFeatureDetector::TYPE_7_12, TYPE_9_16 = FastFeatureDetector::TYPE_9_16 };
CV_ENUM(FastType, TYPE_5_8, TYPE_7_12, TYPE_9_16)
typedef std::tr1::tuple<string, FastType> File_Type_t;
typedef perf::TestBaseWithParam<File_Type_t> fast;
#define FAST_IMAGES \
"cv/detectors_descriptors_evaluation/images_datasets/leuven/img1.png",\
"stitching/a3.png"
PERF_TEST_P(fast, detect, testing::Combine(
testing::Values(FAST_IMAGES),
FastType::all()
))
{
string filename = getDataPath(get<0>(GetParam()));
int type = get<1>(GetParam());
Mat frame = imread(filename, IMREAD_GRAYSCALE);
if (frame.empty())
FAIL() << "Unable to load source image " << filename;
declare.in(frame);
Ptr<FeatureDetector> fd = FastFeatureDetector::create(20, true, type);
ASSERT_FALSE( fd.empty() );
vector<KeyPoint> points;
TEST_CYCLE() fd->detect(frame, points);
SANITY_CHECK_KEYPOINTS(points);
}
PERF_TEST_P(fast, detect_ovx, testing::Combine(
testing::Values(FAST_IMAGES),
FastType::all()
))
{
string filename = getDataPath(get<0>(GetParam()));
int type = get<1>(GetParam());
Mat frame = imread(filename, IMREAD_GRAYSCALE);
if (frame.empty())
FAIL() << "Unable to load source image " << filename;
declare.in(frame);
Ptr<FeatureDetector> fd = FastFeatureDetector::create(20, false, type);
ASSERT_FALSE(fd.empty());
vector<KeyPoint> points;
TEST_CYCLE() fd->detect(frame, points);
SANITY_CHECK_KEYPOINTS(points);
}
modules/features2d/perf/perf_feature2d.cpp
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#include "perf_feature2d.hpp"
PERF_TEST_P(feature2d, detect, testing::Combine(Feature2DType::all(), TEST_IMAGES))
{
Ptr<Feature2D> detector = getFeature2D(get<0>(GetParam()));
std::string filename = getDataPath(get<1>(GetParam()));
Mat img = imread(filename, IMREAD_GRAYSCALE);
ASSERT_FALSE(img.empty());
ASSERT_TRUE(detector);
declare.in(img);
Mat mask;
vector<KeyPoint> points;
TEST_CYCLE() detector->detect(img, points, mask);
EXPECT_GT(points.size(), 20u);
SANITY_CHECK_NOTHING();
}
PERF_TEST_P(feature2d, extract, testing::Combine(testing::Values(DETECTORS_EXTRACTORS), TEST_IMAGES))
{
Ptr<Feature2D> detector = AKAZE::create();
Ptr<Feature2D> extractor = getFeature2D(get<0>(GetParam()));
std::string filename = getDataPath(get<1>(GetParam()));
Mat img = imread(filename, IMREAD_GRAYSCALE);
ASSERT_FALSE(img.empty());
ASSERT_TRUE(extractor);
declare.in(img);
Mat mask;
vector<KeyPoint> points;
detector->detect(img, points, mask);
EXPECT_GT(points.size(), 20u);
Mat descriptors;
TEST_CYCLE() extractor->compute(img, points, descriptors);
EXPECT_EQ((size_t)descriptors.rows, points.size());
SANITY_CHECK_NOTHING();
}
PERF_TEST_P(feature2d, detectAndExtract, testing::Combine(testing::Values(DETECTORS_EXTRACTORS), TEST_IMAGES))
{
Ptr<Feature2D> detector = getFeature2D(get<0>(GetParam()));
std::string filename = getDataPath(get<1>(GetParam()));
Mat img = imread(filename, IMREAD_GRAYSCALE);
ASSERT_FALSE(img.empty());
ASSERT_TRUE(detector);
declare.in(img);
Mat mask;
vector<KeyPoint> points;
Mat descriptors;
TEST_CYCLE() detector->detectAndCompute(img, mask, points, descriptors, false);
EXPECT_GT(points.size(), 20u);
EXPECT_EQ((size_t)descriptors.rows, points.size());
SANITY_CHECK_NOTHING();
}
modules/features2d/perf/perf_feature2d.hpp
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#ifndef __OPENCV_PERF_FEATURE2D_HPP__
#define __OPENCV_PERF_FEATURE2D_HPP__
#include "perf_precomp.hpp"
/* cofiguration for tests of detectors/descriptors. shared between ocl and cpu tests. */
using namespace std;
using namespace cv;
using namespace perf;
using std::tr1::make_tuple;
using std::tr1::get;
// detectors/descriptors configurations to test
#define DETECTORS_ONLY \
FAST_DEFAULT, FAST_20_TRUE_TYPE5_8, FAST_20_TRUE_TYPE7_12, FAST_20_TRUE_TYPE9_16, \
FAST_20_FALSE_TYPE5_8, FAST_20_FALSE_TYPE7_12, FAST_20_FALSE_TYPE9_16, \
\
AGAST_DEFAULT, AGAST_5_8, AGAST_7_12d, AGAST_7_12s, AGAST_OAST_9_16, \
\
MSER_DEFAULT
#define DETECTORS_EXTRACTORS \
ORB_DEFAULT, ORB_1500_13_1, \
AKAZE_DEFAULT, AKAZE_DESCRIPTOR_KAZE, \
BRISK_DEFAULT, \
KAZE_DEFAULT
#define CV_ENUM_EXPAND(name, ...) CV_ENUM(name, __VA_ARGS__)
enum Feature2DVals { DETECTORS_ONLY, DETECTORS_EXTRACTORS };
CV_ENUM_EXPAND(Feature2DType, DETECTORS_ONLY, DETECTORS_EXTRACTORS)
typedef std::tr1::tuple<Feature2DType, string> Feature2DType_String_t;
typedef perf::TestBaseWithParam<Feature2DType_String_t> feature2d;
#define TEST_IMAGES testing::Values(\
"cv/detectors_descriptors_evaluation/images_datasets/leuven/img1.png",\
"stitching/a3.png")
static inline Ptr<Feature2D> getFeature2D(Feature2DType type)
{
switch(type) {
case ORB_DEFAULT:
return ORB::create();
case ORB_1500_13_1:
return ORB::create(1500, 1.3f, 1);
case FAST_DEFAULT:
return FastFeatureDetector::create();
case FAST_20_TRUE_TYPE5_8:
return FastFeatureDetector::create(20, true, FastFeatureDetector::TYPE_5_8);
case FAST_20_TRUE_TYPE7_12:
return FastFeatureDetector::create(20, true, FastFeatureDetector::TYPE_7_12);
case FAST_20_TRUE_TYPE9_16:
return FastFeatureDetector::create(20, true, FastFeatureDetector::TYPE_9_16);
case FAST_20_FALSE_TYPE5_8:
return FastFeatureDetector::create(20, false, FastFeatureDetector::TYPE_5_8);
case FAST_20_FALSE_TYPE7_12:
return FastFeatureDetector::create(20, false, FastFeatureDetector::TYPE_7_12);
case FAST_20_FALSE_TYPE9_16:
return FastFeatureDetector::create(20, false, FastFeatureDetector::TYPE_9_16);
case AGAST_DEFAULT:
return AgastFeatureDetector::create();
case AGAST_5_8:
return AgastFeatureDetector::create(70, true, AgastFeatureDetector::AGAST_5_8);
case AGAST_7_12d:
return AgastFeatureDetector::create(70, true, AgastFeatureDetector::AGAST_7_12d);
case AGAST_7_12s:
return AgastFeatureDetector::create(70, true, AgastFeatureDetector::AGAST_7_12s);
case AGAST_OAST_9_16:
return AgastFeatureDetector::create(70, true, AgastFeatureDetector::OAST_9_16);
case AKAZE_DEFAULT:
return AKAZE::create();
case AKAZE_DESCRIPTOR_KAZE:
return AKAZE::create(AKAZE::DESCRIPTOR_KAZE);
case BRISK_DEFAULT:
return BRISK::create();
case KAZE_DEFAULT:
return KAZE::create();
case MSER_DEFAULT:
return MSER::create();
default:
return Ptr<Feature2D>();
}
}
#endif // __OPENCV_PERF_FEATURE2D_HPP__
modules/features2d/perf/perf_orb.cpp
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#include "perf_precomp.hpp"
using namespace std;
using namespace cv;
using namespace perf;
using std::tr1::make_tuple;
using std::tr1::get;
typedef perf::TestBaseWithParam<std::string> orb;
#define ORB_IMAGES \
"cv/detectors_descriptors_evaluation/images_datasets/leuven/img1.png",\
"stitching/a3.png"
PERF_TEST_P(orb, detect, testing::Values(ORB_IMAGES))
{
string filename = getDataPath(GetParam());
Mat frame = imread(filename, IMREAD_GRAYSCALE);
if (frame.empty())
FAIL() << "Unable to load source image " << filename;
Mat mask;
declare.in(frame);
Ptr<ORB> detector = ORB::create(1500, 1.3f, 1);
vector<KeyPoint> points;
TEST_CYCLE() detector->detect(frame, points, mask);
EXPECT_GT(points.size(), 20u);
SANITY_CHECK_NOTHING();
}
PERF_TEST_P(orb, extract, testing::Values(ORB_IMAGES))
{
string filename = getDataPath(GetParam());
Mat frame = imread(filename, IMREAD_GRAYSCALE);
if (frame.empty())
FAIL() << "Unable to load source image " << filename;
Mat mask;
declare.in(frame);
Ptr<ORB> detector = ORB::create(1500, 1.3f, 1);
vector<KeyPoint> points;
detector->detect(frame, points, mask);
EXPECT_GT(points.size(), 20u);
Mat descriptors;
TEST_CYCLE() detector->compute(frame, points, descriptors);
EXPECT_EQ((size_t)descriptors.rows, points.size());
SANITY_CHECK_NOTHING();
}
PERF_TEST_P(orb, full, testing::Values(ORB_IMAGES))
{
string filename = getDataPath(GetParam());
Mat frame = imread(filename, IMREAD_GRAYSCALE);
if (frame.empty())
FAIL() << "Unable to load source image " << filename;
Mat mask;
declare.in(frame);
Ptr<ORB> detector = ORB::create(1500, 1.3f, 1);
vector<KeyPoint> points;
Mat descriptors;
TEST_CYCLE() detector->detectAndCompute(frame, mask, points, descriptors, false);
EXPECT_GT(points.size(), 20u);
EXPECT_EQ((size_t)descriptors.rows, points.size());
SANITY_CHECK_NOTHING();
}