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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/perf_fast.cpp
-63
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@@ -1,63 +0,0 @@
#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);
}